2013 aptitudes requeridas para cta en 2018 faa

8/16/2019 2013 Aptitudes Requeridas Para Cta en 2018 FAA

http://slidepdf.com/reader/full/2013-aptitudes-requeridas-para-cta-en-2018-faa 1/67

See discussions, stats, and author profiles for this publication at: http://www.researchgate.net/publication/235967310

Selection of the Next Generation of Air TrafficControl Specialists: Aptitude Requirements forthe Air Traffic Control Tower Cab in 2018

BOOK · MARCH 2013

DOWNLOADS

62VIEWS

118

1 AUTHOR:

Dana Broach

Federal Aviation Administration

43 PUBLICATIONS 92 CITATIONS

SEE PROFILE

Available from: Dana BroachRetrieved on: 08 September 2015

http://www.researchgate.net/profile/Dana_Broach?enrichId=rgreq-f79bbb00-47b7-4db0-8af0-1f6ad909b165&enrichSource=Y292ZXJQYWdlOzIzNTk2NzMxMDtBUzo5OTcyMTc2MjgzNjQ5MUAxNDAwNzg2OTMwMDE3&el=1_x_4

http://www.researchgate.net/?enrichId=rgreq-f79bbb00-47b7-4db0-8af0-1f6ad909b165&enrichSource=Y292ZXJQYWdlOzIzNTk2NzMxMDtBUzo5OTcyMTc2MjgzNjQ5MUAxNDAwNzg2OTMwMDE3&el=1_x_1


http://www.researchgate.net/institution/Federal_Aviation_Administration?enrichId=rgreq-f79bbb00-47b7-4db0-8af0-1f6ad909b165&enrichSource=Y292ZXJQYWdlOzIzNTk2NzMxMDtBUzo5OTcyMTc2MjgzNjQ5MUAxNDAwNzg2OTMwMDE3&el=1_x_6



http://www.researchgate.net/?enrichId=rgreq-f79bbb00-47b7-4db0-8af0-1f6ad909b165&enrichSource=Y292ZXJQYWdlOzIzNTk2NzMxMDtBUzo5OTcyMTc2MjgzNjQ5MUAxNDAwNzg2OTMwMDE3&el=1_x_1

http://www.researchgate.net/publication/235967310_Selection_of_the_Next_Generation_of_Air_Traffic_Control_Specialists_Aptitude_Requirements_for_the_Air_Traffic_Control_Tower_Cab_in_2018?enrichId=rgreq-f79bbb00-47b7-4db0-8af0-1f6ad909b165&enrichSource=Y292ZXJQYWdlOzIzNTk2NzMxMDtBUzo5OTcyMTc2MjgzNjQ5MUAxNDAwNzg2OTMwMDE3&el=1_x_3

http://www.researchgate.net/publication/235967310_Selection_of_the_Next_Generation_of_Air_Traffic_Control_Specialists_Aptitude_Requirements_for_the_Air_Traffic_Control_Tower_Cab_in_2018?enrichId=rgreq-f79bbb00-47b7-4db0-8af0-1f6ad909b165&enrichSource=Y292ZXJQYWdlOzIzNTk2NzMxMDtBUzo5OTcyMTc2MjgzNjQ5MUAxNDAwNzg2OTMwMDE3&el=1_x_2



Selection of the Next Generationof Air Traffic Control Specialists:Aptitude Requirements for the AirTraffic Control Tower Cab in 2018

Dana Broach

Civil Aerospace Medical InstituteFederal Aviation AdministrationOklahoma City, OK 73125

March 2013

Final Report

DOT/FAA/AM-13/5Of ce of Aerospace MedicineWashington, DC 20591

Federal AviationAdministration



NOTICE

This document is disseminated under the sponsorshipof the U.S. Department of Transportation in the interest

of information exchange. The United States Governmentassumes no liability for the contents thereof.

___________

This publication and all Office of Aerospace Medicine

technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications website:

www.faa.gov/go/oamtechreports



i

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No.

DOT/FAA/AM-13/54. Title and Subtitle 5. Report Date

Selection of the Next Generation of Air Traffic Control Specialists: AptitudeRequirements for the Air Traffic Control Tower Cab in 2018

March 20136. Performing Organization Code

7. Author(s) 8. Performing Organization Report No.

Broach, D

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

FAA Civil Aerospace Medical InstituteP.O. Box 25082 11. Contract or Grant No.

Oklahoma City, OK 73125

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered

Office of Aerospace MedicineFederal Aviation Administration800 Independence Ave., S.W.

Washington, DC 20591 14. Sponsoring Agency Code

15. Supplemental Notes

Developed under FAA Human Factors research task 1209AC082110.HRR523.AV9300.10 Strategic Job Analysis:Selecting the Air Traffic Controller of the Future 16. Abstract

The Federal Aviation Administration (FAA) faces two significant organizational challenges in the 21st century:(1) transformation of the current NAS into the Next Generation Air Transportation System (“NextGen”); and(2) recruitment, selection, and training the next generation of air traffic control specialists (ATCSs or air trafficcontrollers). What aptitudes should be assessed in the selection of future air traffic controllers? This report, thefirst of three, focuses on the aptitudes required in the air traffic control tower cab. First, the aptitude profile

currently required at the time of hire into the ATCS occupation is described based on Nickels, Bobko, Blair,Sands, & Tartak (1995). Second, mid-term (2018) changes in the tower cab are described. Change driversinclude increased traffic and the introduction of five decision support tools (DSTs): 1) Airport Configuration; 2)Departure Routing; 3) Runway Assignment; 4) Scheduling and Sequencing; and 5) Taxi Routing (withConformance Monitoring). Third, the impact of these DSTs on tower cab operational activities, sub-activities,and tasks was assessed. Overall, the activities, sub-activities, and tasks of the controllers in the Ground Controland Local Control positions in the cab will not change with the introduction of these DSTs and associateddisplays. However, the way the work is performed will change at the keystroke or interface level. Fourth, theimpact of the DSTs on aptitudes required of controllers is evaluated. The importance of the following aptitudes

will increase in the mid-term:Scanning , across both auditory and visual sources,Perceptual Speed and Accuracy ,Translating Information, Chunking , Interpreting Information, Sustained Attention, Recall from Interruption,Situational Awareness , Long-Term Memory , Problem Identification, Prioritization, Time-Sharing , InformationProcessing Flexibility , and Task Closure/Thoroughness . Two new aptitude requirements were identified:Dispositional Trust in Automation; and Computer-Human Interface (CHI) Navigation. Gaps in current aptitudetesting are identified, and recommendations presented for test development and validation to close the gap.17. Key Words 18. Distribution Statement

Air Traffic Control Specialist, Next Generation AviationTransportation System, Job/Task Analysis

Document is available to the publicthrough the Internet:

www.faa.gov/go/oamtechreports19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price

Unclassified Unclassified 57Form DOT F 1700.7 (8-72) Reproduction of completed page authorized



iii

ACKNOWLEDGMENTS

Research reported in this paper was conducted under the Air raffic Program Directive / Level of Effort Agreement between the Human Factors Research and Engineering Group (AJP-61), FAA Headquartersand the Civil Aerospace Medical Institute Aerospace Human Factors Division (AAM-500).

Special thanks are extended to Perry Starkey (Xyant Inc.), Brian Laramore (Air raffic Controllerraining and Development Group (AJL-11), and Lois Legako (FAA Academy Air raffic ower Section

(AMA-510), who reviewed and corrected my description of tower operations. Tanks are extended thetechnical reviewers, including Dino Piccione, Carol Manning, and Kate Bleckley for their substantive andhelpful comments and suggestions. Tanks are also extended to Melanie Cannon and Mike Wayda fortheir detailed proof-reading.

Te opinions expressed are those of the author alone, and do not necessarily reect those of the Federal Aviation Administration, the Department of ransportation, or government of the United States of America.



v

CONTENTS

Selection of the Next Generation of Air Traffic Control Specialists: Aptitude Requirements for the Air Traffic Control Tower Cab in 2018

Report Organization -----------------------------------------------------------------------------------------------1 Problem and Setting -----------------------------------------------------------------------------------------------1C C --------------------------------------------------------------------------------------------------3 Overview ------------------------------------------------------------------------------------------------------------3C O C ---------------------------------------------------------------------6 Ground Control ----------------------------------------------------------------------------------------------------6 Local Control -------------------------------------------------------------------------------------------------------6 Flight Data ----------------------------------------------------------------------------------------------------------7 Clearance Delivery -------------------------------------------------------------------------------------------------7 ower Cab eam ---------------------------------------------------------------------------------------------------7 Current Equipment in the ower Cab --------------------------------------------------------------------------8 Current Workow in the ower Cab ----------------------------------------------------------------------------8 Single Aircraft Departure -----------------------------------------------------------------------------------------9 Single Aircraft Arrival -------------------------------------------------------------------------------------------- 11 Multiple Aircraft Operations ----------------------------------------------------------------------------------- 12 Current Job/ ask Analyses -------------------------------------------------------------------------------------- 12 C A Inc. Operations Concept Analysis for the ower Cab ------------------------------------------------ 12 Observational Studies of the ower Cab ---------------------------------------------------------------------- 14 AIR® 2007 Update for the ower Cab ------------------------------------------------------------------------ 14 1995 Selection-oriented J A ----------------------------------------------------------------------------------- 14 Baseline Aptitude Prole ---------------------------------------------------------------------------------------- 15

C -------------------------------------------------------------------------------------------- 19 ower Cab Organization in 2018 ------------------------------------------------------------------------------ 19 ower Cab Equipment in 2018 -------------------------------------------------------------------------------- 19 DataComm ------------------------------------------------------------------------------------------------------- 19 ower Cab DS s ------------------------------------------------------------------------------------------------- 21 A C Cab Workow in 2018 --------------------------------------------------------------------------------- 31 Nominal Departure ---------------------------------------------------------------------------------------------- 31 Nominal Arrival -------------------------------------------------------------------------------------------------- 34 Multiple Operations --------------------------------------------------------------------------------------------- 34 Mixed Equipage -------------------------------------------------------------------------------------------------- 34 Change in Operational Priority -------------------------------------------------------------------------------- 34 Mid- erm A C s ------------------------------------------------------------------------------------------------ 35

A M - N G I A R A C C -------------- Mid- erm DS Impact on ower Cab Controller Roles & Responsibilities ---------------------------- 36 Mid- erm OWER DS Impact on Aptitude -------------------------------------------------------------- 36 Aptitude esting Gap Analysis --------------------------------------------------------------------------------- 38C R ---------------------------------------------------------------------------- 41F ------------------------------------------------------------------------------------------------------------ 42R ------------------------------------------------------------------------------------------------------------ 42

A A. Worker requirements identied by Nickels et al. (1995), sorted in descendingorder of mean (average) importance to successful controller performance -------------------A1



vii

GLOSSARY

ACARS ---------- Aircraft Communications Addressing and Reporting System AMS ------------- FAA Acquisition Management System AR CC --------- Air Route raffic Control Center A CS ------------ Air raffic Control Specialist

A C ------------ Air raffic Control ower A -SA ---------- Air raffic Selection & raining est (A CS aptitude test battery)CHI -------------- Computer-Human Interface (also Computer-Human Interaction)CR -------------- Cathode Ray ubeDataComm ----- Data CommunicationsDS -------------- Decision Support oolEA ---------------- Enterprise ArchitectureFAA -------------- Federal Aviation AdministrationFD/CD ---------- Flight Data/Clearance Delivery GC --------------- Ground Control

IDRP ------------ Integrated Departure Route Planning LC ---------------- Local ControlLCD ------------- Liquid Crystal Display PA CO ---------- Professional Air raffic Controller OrganizationPDC ------------- Pre-Departure ClearanceRC ---------------- Ramp ControlSID --------------- Standard Instrument Departure

FDM ----------- ower Flight Data ManagerDLS ------------ erminal Data Link SystemFM ------------- raffic Flow Management

M --------------- raffic ManagerRACON ------- erminal Radar Approach ControlS ---------------- ower Supervisor

VHF ------------- Very-High Frequency VDL ------------- VHF Data Link UHF ------------- Ultra-High Frequency



ix

EXECUTIVE SUMMARY

ProblemTe Federal Aviation Administration (FAA) faces two

signicant organizational challenges in the 21st century:(1) transformation of the current National Airspace System

(NAS) into the Next Generation Air ransportationSystem (“NextGen”); and (2) recruitment, selection, andtraining the next generation of air traffic control specialists(A CSs or air traffic controllers). What aptitudes shouldbe assessed in the selection of future air traffic controllers?

Aptitudes in personnel selection refer to the innateand learned abilities and other personal characteristicsrequired of a person at the time of hire and for whichthe employer (the FAA) provides no specic training ordevelopment. Air traffic control (A C) knowledge andskills are learned after hire through formal and on-the-

job training. Short-term memory, perceptual speed, andemotional stability are examples of aptitudes. Aircraft

weight classes, wake vortex separation procedures, andamending ight routes are examples of A C-specicknowledge and skills.

Tis report focuses on the aptitudes required to work in the A C tower cab (A C or “tower cab”)environment. Te analysis assumes that selection willcontinue to be based on aptitude, not demonstrated

A C-specic knowledge and skill.Te analysis is straightforward: Compare current

aptitude to future aptitude requirements. First, the cur-rent work of tower cab controllers is described. Second,the current aptitude prole is reviewed. Tird, the future

work of tower cab controllers circa 2018 is described,based on a review of available information. Fourth,future aptitude requirements are deduced based on thedescription of work in the mid-term tower cab. Fifth, thecurrent aptitude prole is compared to the future aptitudeprole. Te report closes with specication of the abilitiesto be assessed in the future and recommendations for testdevelopment and validation.

Current Work

Te current work of controllers is organized aroundfour operational positions in the tower cab: Flight Data,Clearance Delivery, Ground Control, and Local Control.

At present, the cab controllers have little automationsupport in the form of decision support tools (DS s). Teprimary mode of communication with aircraft is VHFradio. Departure clearances are delivered electronically atlarge airports equipped with the ower Data Link System( DLS). Controllers rely upon the out-the-window viewof operations, ight strips (or their functional equivalent,depending on local facility practices and policies), andthe surface and airspace radar displays to determine the

position and identication of aircraft and to formulatecontrol instructions and other communications. Controlis very tactical on a short time horizon and is based onthe “First Come, First Served” paradigm.

Current AptitudesTe aptitudes currently required can be organized,

for discussion purposes, around an input-process-outputmodel.

Input to the controller is through Active Listening and visual Scanning , with Perceptual Speed and Accuracy as the limiting factor.

From a process view, what is seen and heard isentered into Short- erm Memory and used to constructa model of the current and future state of operations.Te abilities called upon include Situtational Awareness ,Visualization, Dynamic Visual-Spatial ability, andSummarizing Information. Any current and anticipatedproblems are solved through Problem Identication,Prioritization, Rule Application, and (logical) Reasoning .Te dynamic comprehension of the current and futurestate of operations and problem solving requireSustained Attention and Concentration from the controllers. Workingtraffic draws upon their ability to Tink Ahead , Plan,and Project (Projection) from the current to the near-term future. Controllers must divide their attention andperform multiple tasks ( ime-Sharing ). Performance of

the job requires constant Self-Awareness , Self-Monitoring/ Evaluation, and Information Processing Flexibility .Controllers must haveSelf-Condence , be willing to akeCharge of a situation with olerance for High-IntensityWork Situations , and do so byWorking Cooperatively whilemaintaining their emotional Stability/Adjustment .

Controller outputs are control actions deliveredprimarily as voice instructions to pilots. Some keyboardingand writing is required.

Future Work In the mid-term (circa 2018), DS s will be intro-

duced in the cabs at the 30 largest and busiest airportssuch as Dallas/Fort Worth (DFW) and Atlanta (A L).Five DS capabilities are envisioned for the tower cab atthese complex facilities: Airport Conguration, DepartureRouting , Runway Assignment , Scheduling and Sequencing ,and axi Routing (with Conformance Monitoring ). TeDS s will generate recommendations for control actions.Some instructions will be delivered electronically to theaircraft view Data Communications (DataComm) Seg-ment 1, building on ower Data Link System ( DLS);however, time- and safety-critical messages will still bedelivered by voice in the mid-term (Wargo & D’Arcy,



x

2011). Te goals for the tower cab DS s include reduced waiting and taxi times, greater utilization of resources,increased throughput (especially in bad weather) anddecreased environmental impact, through more “stra-tegic “management of the traffic on the surface and inthe immediate airspace. Te computational algorithmsunderlying the ve DS s are the subject of intensive

research, engineering, and development. Assuming thatstable and robust solutions will be delivered, the Runway

Assignment, Scheduling and Sequencing, and axi Rout-ing (with Conformance Monitoring) DS s are likely tochange the “how” rather than the “what” controllers do

working traffic in the tower cab. Te concepts of opera-tion and use for each DS require controllers to accept,reject, or modify the recommended control action, suchas a sequence for departures and runway assignments viaunspecied (as yet) computer-human interfaces (CHIs).Tis has two primary implications. First, controllers willbe required to interact with the DS s and associateddisplays. Second, controllers will evaluate the proposed(computed) solution and remain responsible for the safetyand efficiency of surface operations.

Future AptitudesOverall, the introduction of surface-oriented DS s

under the NextGen umbrella and increased traffic will resultin a shift in emphasis on the aptitudes required for success-ful performance in the tower cab of 2018. Some aptitudesthat are important now will become more important inthe future, and a few will become less important in the

future. Tis evolutionary shift in emphasis resulting fromNextGen is summarized as follows in the context of an“input-process-output” framework for human aptitudes.

First, in terms of aptitudes relating to acquiringinformation (“input”), Scanning (of visual sources),Perceptual Speed and Accuracy, ranslating Information,Chunking, and Interpreting Information will increase inimportance to successful performance in the tower cab.Tis is especially true for towers at the 30 largest airportsthat are most likely to receive surface-oriented DS s inthe mid-term. Second, from a “process” perspective, theimportance of attention and memory aptitudes such asSustained Attention, Recall from Interruption, Situational

Awareness, and Long- erm Memory to successful jobperformance will increase in the mid-term. Te increasein the importance of Sustained Attention and Recall fromInterruption is driven by the projected increases in A Coperations. Te increase in the importance of Situational

Awareness and Long- erm Memory is coupled to thesurface-oriented DS s needed to handle the increase intraffic. Tird, Problem Identication and Prioritization

will become more complicated and more important in themid-term, depending on the transparency and operational

acceptability of the mid-term DS recommendations andthe reliability of the systems. Te importance of the apti-tudes ime-Sharing, Information Processing Flexibility,and ask Closure/Toroughness will increase with bothtraffic and the implementation of surface-oriented DS s.Fourth, just two new aptitude requirements were identi-ed with NextGen in the mid-term: Dispositional rust

in Automation and CHI Navigation. Finally, in terms of“output,” the importance of the aptitude Manual Dexterity(in using a keyboard, mouse, touch screen, and/or numerickeypad) will depend on the actual CHI implementationsbut is likely to increase.

Aptitude Testing Gap AnalysisTe current A CS occupational aptitude test battery

assesses many, but not all, of the aptitudes likely to beimportant to successful job performance in the mid-termtower cab of 2018. Tree input-related aptitudes that

will become more important (than they currently are) to job performance in the 2018 tower cab are not currentlyassessed in the pre-employment testing: ranslating In- formation, Chunking , and Interpreting Information. Treeprocess-related aptitudes that will be important to towercab controller performance in 2018 are not explicitlyassessed in the current test battery:Sustained Attention,Long-term Memory , and ime-sharing .Dispositional rust in Automation is a new aptitude requirement associated withNextGen DS s. Te two output-related aptitudes likelyto be important in 2018, CHI Navigation and ManualDexterity , are not assessed in the current test battery.

Some of the aptitudes that will be important in themid-term are assessed through multi-factorial tests, butexplicit scores for those aptitudes are not computed. Forexample, while it is clear that applicants must prioritizetheir actions in both the Letter Factory est and Air rafficScenarios est, there are no scores explicitly representingPrioritization. Similarly, while applicants are required toperform multiple tasks such as tracking objects, consideringthe next actions to be taken simultaneously in those twodynamic, multi-factorial tests, the candidate’s time-sharingcapacity can only be inferred from the overall scores on thetests. No explicit score for ime-sharing as a psychologicalconstruct is derived from either test.

More subtle gaps between current A CS aptitudetesting and mid-term requirements exist. For example, thecurrent test of Scanning is based on a 2-D radar displayrather than an out-the-window search of a true 3-D visualscene for relevant information. It is not clear if scanningthe two sources invokes the same fundamental ability.

Another gap is the relative importance (weights) assignedto tests representing the aptitudes likely to be more orless important to successful job performance in the towercab of 2018. Finally, aptitudes Sustained Attention and



xi

Concentration are assessed by a questionnaire (e.g., self-reports of typical behavior). While assessment of traitssuch asSelf-awareness and Stability/Adjustment are widelyavailable for personnel selection, reliance on self-reportsfor attention-related aptitudes is problematic. Self-reportscan be vulnerable to applicant impression managementtactics and socially desirable response sets, particularly in

high-stakes selection settings. Assessment of attention-based performance would be preferable.

Recommendationso close these gaps in A CS aptitude testing, the

following actions are recommended.First, adapt or develop and then validate tests for

Dispositional rust in Automation, CHI Navigation, and Manual Dexterity . Tese aptitudes are not currently assessedin pre-employment aptitude testing but will be importantto job performance under NextGen.

Second, adapt or develop and then validate tests forthe following aptitudes: ranslating Information, Chunk-ing , Interpreting Information, Sustained Attention, Long-term Memory , and ime-sharing. Tese aptitudes wereidentied as important in the baseline job analysis. Teyare likely to become more important to job performancein the mid-term tower cab than at present, particularly

with the implementation of surface-oriented DS s underthe NextGen umbrella. Tese aptitudes are not currentlyassessed in pre-employment aptitude testing.

Tird, derive scores from the multi-factorial tests,if possible, to represent the aptitudesPrioritization and

ime-sharing . Tese aptitudes are likely to become evenmore important in the mid-term tower than they are now

because of both NextGen and increased traffic. Alterna-tively, adapt or develop tests of these aptitudes. Validatethe derived, adapted, or newly developed tests for theseaptitudes against mid-term job performance measures fortower cab controllers.

Fourth, conduct multi-trait, multi-method analysesofScanning of different sources of visual information such

as a true 3-D out-the-window view versus 2-D represen-tation of that view and 2-D radar display. Determine ifdifferent tests are required.

Fifth, review the relative weights for aptitudes as-sessed in the current occupational aptitude test batteryin relation to their increased importance to the mid-termcab environment with surface DS s. In other words,reect the shift in emphasis or degree on the variousaptitudes relevant to job performance in the mid-termtowers of large airports in the weights assigned to scoresrepresenting relevant aptitudes. Tis recommendationincludes determination of cut-scores to reect minimumrequirements, if justied.

Sixth, investigate alternative performance-based as-sessments ofSustained Attention and Concentration thatdo not rely upon transparent, self-report questionnairesof applicant “typical” behavior.

Finally, each of the recommended studies shouldbe conducted in accordance with accepted guidelines,standards, principles, and practices for the developmentand validation of personnel selection tests. Specic at-tention and resources must be given to the developmentof meaningful, reliable, and valid measures of controller

job performance in the tower cab of 2018 against whichto validate future-oriented tests.



1

SELECTION OF THE NEXT GENERATION OF A IR T RAFFIC CONTROL SPECIALISTS : A PTITUDE R EQUIREMENTS FOR THE A IR T RAFFIC CONTROL T OWER C AB IN 2018

Te Federal Aviation Administration faces two sig-nicant organizational challenges. Te rst is to transformthe current National Airspace System (NAS) into theNext Generation Air ransportation System (“NextGen”).NextGen intends to shift the fundamental air trafficcontrol paradigm from ground-based tactical control tosatellite-based strategic management (FAA, 2010g). Tetransformation can be organized into three time periods:near-term (now through about 2015), mid-term (throughabout 2018), and far-term (through about 2025 andbeyond). Te second challenge is to recruit, select, andtrain the next generation of air traffic control specialists.

Te two challenges are intertwined: Te evolution ofNextGen will impact the knowledge, skills, abilities, andother personal characteristics required of controllers inthe future, yet the characteristics of the workforce willinuence the design of NextGen. Tis report is the rstin a series that evaluates the impact of NextGen on theselection of the next generation of air traffic controllers.

Report OrganizationTis report is organized into ve parts. First, the over-

all problem and setting are described. Second, the current work of controllers is described. Tis “as is” descriptionincludes the aptitude prole currently required to enterthe controller workforce. Tird, what the work of control-lers might look like at a specic future time is described.Tis “to be” description includes the aptitude prolethat might be required to enter the workforce. Fourth,the current and future aptitude proles are compared inrelation to current selection procedures to identify gaps.Finally, conclusions and recommendations are presented.

Problem and SettingTe air traffic control specialist (A CS, “air traffic

controller,” or simply “controller”) workforce is the singlelargest (>15,000 controllers and 1st-level supervisors as ofFY2010; FAA, 2010d) and most publicly visible workforcein the FAA. It is also experiencing a unique generationalchange. Te FAA hired a large cohort of controllers fol-lowing the 1981 PA CO strike (see Broach, 1998). Mostof the members of this “Post-Strike Generation” wereunder age 30 when hired. Now, that workforce is aging.In 1996, the average age of the Post-Strike Generation ofcontrollers at eld facilities was 37, and most (88%) werehired between August, 1981 and March, 1992 (Schroeder,Broach & Farmer, 1998). Now, in 2010, the average age

of the Post-Strike Generation is 48, and they represent just 44% of the non-supervisory controller workforceassigned to eld facilities. Most members of the Post-Strike Generation face mandatory retirement at age 56 byabout 2018. Te FAA projects hiring about 10,000 newcontroller trainees by 2018 to replace those losses; about80% will successfully complete the arduous two to threeyear training program (FAA, 2010a; see able 4.1, p. 27and Figure 5.1, p. 37).

Hiring 10,000 new controllers is a signicantorganizational effort. Based on recent FAA experiencein recruiting and selecting over 7,000 Next Generation

controllers since 2002, the FAA can expect many applicantsfor each opening. Te selection problem is complicatedby the need to consider not just current aptitude require-ments, but also aptitudes that are likely to be required byNextGen in the mid-term.

Tere is considerable speculation on what aptitudes will be required of Next Generation controllers. For ex-ample, the Congress directed the FAA to investigate “theattributes and aptitudes needed to function well in a highlyautomated air traffic control system and the developmentof appropriate testing methods for identifying individuals

with those attributes and aptitudes” in the Aviation SafetyResearch Act of 1988 (Public Law 100-591 (November3, 1988), codied at itle 49 United States Code section44506(a) (3)). In 1995, Cole suggested that the A Csystem of the future “…will require individuals with adifferent mix of abilities than what is needed today” (p.47). A National Research Council panel came to a similarconclusion, suggesting that different abilities, or a different

weighting of abilities, might be required under differentfuture automation paradigms (Wickens, Mavor, & Mc-Gee, 1997). More recently, the FAA National AviationResearch Plan set out a requirement to “Develop selection

procedures to transform the (controller) workforce intoa new generation of service providers that can managetraffic ows in a highly automated system” by 2015 (p.35). Te assumption reected in these and similar docu-ments is that the aptitude prole required to work “ina highly automated system” will be at least qualitativelydifferent than what is required to work in today’s air trafficcontrol system.

However, the available empirical data suggest thatthe aptitudes required to enter the occupation are morestable than assumed (Manning & Broach, 1992; Eißfeldt,2009; Goeters, Maschke, & Eißfeldt, 2009). However,



2

it might be the case that some of the abilities on whichcontrollers were selected in the past might not be justi-able in the future and that new ability constructs mightbecome important. A systematic evaluation of the impactof NextGen on the aptitudes required to enter the control-ler occupation is needed.

In considering what to assess in selection, it is im-

portant to dene what is meant by “knowledge, skills,abilities, and other personal characteristics” (KSAOs).For purposes of this strategic job analysis, “knowledge”and “skill” are dened explicitly as the A C-specic in-formation, procedures, and methods that the FAA teachesnew controllers through formal instruction at the FAA

Academy and on-the-job training at an A C eld facility.In contrast, “abilities” and “other personal characteristics”are used to specically refer to innate and learned abilitiesand other personal characteristics required at the timeof hire and for which the employer (the FAA) providesno explicit training or development. “Aptitude” is usedthroughout this report as a shorthand label for these innateand learned abilities and other personal characteristics.

Aptitude in this usage encompasses cognitive attributesof a person such as working memory and logical reason-ing, perceptual abilities such as color vision and hearing,and personality traits such as conscientiousness andemotional stability. Aptitude, as used in this report, alsoincludes learned capabilities such as comprehension ofspoken and written English, arithmetic, basic algebra (forexample, computing time from speed and distance), andrecognizing angles. Tese abilities are acquired through

education and experience before a person is consideredfor employment by the FAA. Te focus of the strategic

job analysis is on the aptitudes required to enter the A CSoccupation, on the assumption that the selection policyof the FAA for controllers will continue to be based onaptitude, not on demonstrated A C-specic knowledgeand skill. A C-specic knowledge and skills are explicitlyexcluded from this analysis.

Te FAA must decide when to make changes tothe A CS selection procedures. A selection procedureis required to be grounded in the realities of the actual

job, not in what might or might not be the work at somedistant point in the future with some reasonable degreeof certainty. On one hand (or time horizon), the vision ofNextGen in 2025 is conceptual rather than concrete; to

what degree that vision will be achieved is yet to be seen.Terefore, targeting aptitude requirements in the far-termis likely to be unrealistic – and indefensible within thecurrent technical and legal framework for the developmentand validation of employee selection procedures. On theother hand, the FAA has invested substantial effort indening what is termed the “mid-term” NextGen at about

2018. Sufficient information about specic technologiesand procedures is available through formal concepts ofoperation and use, design descriptions, requirementsdocuments, human-in-the-loop (HI L) simulations, andprototypes in demonstration and operational testing todeduce future aptitude requirements with some degree ofcondence. Terefore, this analysis focuses on the mid-

term NextGen at 2018.Finally, to make the analysis tractable, each report

in this series will analyze an operational working environ-ment. Te iconic A C facility at an airport is the glasscab on top of the A C tower. Controllers in the towercab direct pilots to land and takeoff from the airport.Tey direct traffic on the runways, taxiways, and in theairspace around the airport out to about three to ve miles.

ower cab controllers rely upon direct visual observationof aircraft operating on the airport surface and in the im-mediate airspace around the airport. Surface and airspaceradar displays are available to the controllers at many (butnot all) towers.

Once a departing aircraft is the air, it is handed offto a controller in the servicing erminal Radar ApproachControl ( RACON) facility. RACONs are less wellknown to the public but are critical to the safety and ef-ciency of ight. RACON controllers direct ights intoand out of the airspace around an airport (or airports),generally out to about 50 miles and up to 10,000 feet inaltitude. RACON controllers rely upon radar to “see” thetraffic. Some RACONs are co-located with the tower. Forexample, the tower serving the Will Rogers International

Airport (OKC) in Oklahoma City has both a cab on topof the tower and a RACON at the base of the tower.Other RACONs are stand-alone facilities, particularlythose that serve metropolitan areas with multiple airports,such as the New York City area, Chicago, the Dallas-Fort

Worth metroplex, Atlanta, and southern California (Los Angeles and San Diego). RACON controllers handoff departing ights to controllers at a third facility typeknown as an air route traffic control center (AR CC, “enroute center,” or simply “center”). Center controllers pro-vide air traffic services to aircraft ying between airports,usually at higher altitudes. Like RACON controllers,they rely upon radar to “see” air traffic. Multiple centersmight handle a ight, depending on its route. An arrivalis handled in reverse: center hands-off to the RACON;

RACON hands off to the tower cab.Given the diversity of the operating environments,

focusing on one type of facility at a time makes the analyticproblem more tractable. Tus, the work of controllersin the tower cab circa 2018 is analyzed in this report.Subsequent reports will analyze the work of controllersin the RACON and AR CC environments.



3

CURRENT TOWER CAB

Overview When air traffic control is mentioned, the rst

thought is often of the control tower cab at an airport. Airports have long been recognized as a constraint onthe capacity of the NAS (FAA, 2007; Feron et al., 1997;

Gosling, 1993; Shaver, 2002). Airports constrain NAScapacity in several ways. First, there are limits to the num-ber of aircraft that can physically be handled at any givenmoment on the airport surface. Tese limits include thenumber of gates for emplaning and deplaning passengers(and cargo), ramps (also called alleys), taxiways, and run-

ways (Figure 1). For example, only so many airplanes canphysically occupy a taxiway of a given length at a givenpoint in time. Only one airplane at a time can occupy agate, and there are only so many gates in a terminal.

Second, A C procedures impose operational limitson airports. For example, controllers may require aircraft to

wait at an intersection while other traffic proceeds throughthe intersection. A departing aircraft might have to lineup and wait on the departure runway until an arrival hasgone a specied distance down the runway or turned off.Smaller aircraft have to wait to take off behind “heavy”aircraft such as a Boeing 747, due to wake turbulence.

Arrivals on closely-spaced parallel runways might have tobe staggered by a specic distance.

Tird, weather constrains airport capacity. Weather isa leading cause of delays. For example, aircraft that mightbe departing from other airports (say, from New York’s

LaGuardia (LGA) to Dallas-Fort Worth International(DFW)) one afternoon might be delayed on the ground

due to a summer thunderstorm and high winds at DFW.Similarly, the planned departures out of DFW to LGA andother airports might also be delayed until the thunderstormpasses. After the thunderstorm, DFW might experiencecongestion until the backlog of ights is cleared.

Fourth, random (stochastic) events constrain capac-ity. While these events can be expected, their actual oc-

currence is unpredictable. Example stochastic events thatconstrain airport capacity are aircraft mechanical problemsand holding for late-connecting passengers.

Finally, controller workload might also constraincapacity. For example, Balakrishna, Ganesan, and Sherry(2009) asserted that controllers “are often overwhelmedby the increase in the number of arrivals and departuresduring peak hours of operation” at major hub airports. Tesame assertion had been made 40 years earlier: Controllersbecame fatigued under peak loads and had difficulty in“retaining the picture” required to safely and efficientlydirect arrivals to and departures from the airport (Luffsey& Wendell, 1969).

Tese ve physical, operational, and psychologicallimits combine to constrain the ow of aircraft throughan airport, particularly the major hubs for which thereare overlapping “banks” or waves of departures and arriv-als throughout the day (Glass, 1997; Idris et al., 1998).

One well-known and frequently experienced formof delay is in taxiing out to the departure runway. Indeed,the iconic image of aviation delay is a queue of outboundaircraft, lined up almost nose to tail, inching their wayalong a taxiway to the end of the departure runway. Te

aircraft engines spool up and down as the aircraft moveforward in short spurts, burning fuel and releasing carbon

Figure 1: Example airport layout (from Atlanta Harts eld (ATL)) illustrating ramps,taxiways, & runways



4

dioxide and other pollutants. Te average taxi-out delay inminutes-per-ight is approximately twice that of airbornedelay; the cost of taxi-out delay is about one-third greaterthan the cost of airborne delay (Atkins, Brinton & Walton,2002). Reducing taxi-out and other delays on the airportsurface, thereby increasing the efficiency of the airport,might have signicant benets to the operators and the

public in the forms of greater operational predictability,scheduling, and reduced emissions. o that end the Na-tional Aeronautics and Space Administration (NASA) andthe FAA have conducted signicant research on methodsfor increasing airport efficiency and reducing delays.

One approach to reducing delays in airport surfaceoperations provides tools for tower cab controllers tocontrol departing and arriving aircraft on the airportsurface and immediate airspace around the airport. Tecab controllers perform a series of sequential control tasksfor each departing and arriving aircraft. Depending onairport conguration, they instruct the pilot of depart-ing aircraft when to push back from the gate, what taxiroute to take to the departure runway, and when to takeoff (Anagnostakis, Clarke, Bohme, & Volckers, 2001).

An arrival is handled in reverse; pilots are instructed on which runway to land, what exit to take from the runway,and what taxi route to take to the gate. Most of theseinstructions are issued by voice by controllers to pilotsvia Very High Frequency (VHF) radio (Gosling, 1993).Te procedures used in managing departures and arriv-als are largely “manual,” that is, performed with little,if any, computer support. At large, hub airports such as

DFW, A L, Chicago’s O’Hare (ORD), and Los AngelesInternational (LAX), these communication and controltasks impose a high workload on controllers and mustbe performed under signicant time pressure. Tere isno time for errors.

Moreover, modern airports such as ORD have mul-tiple terminals, a complex web of taxiways, and multipleparallel, diverging, and sometimes intersecting runways(Figure 2). Finding an “optimal” taxi route and runwayassignment, in real time, that minimizes taxi-out timeand meets other criteria for a given ight can be complexand difficult. Anagnostakis and Clarke (2002) argue that“given the complexity of the departure process and thesite specic nature of departure operations, it is difficultfor controllers to fully explore all the possible solutions

within the relatively short time period in which decisionsmust be made” (p. 1). Controllers might rely upon estab-lished procedures and pre-planned taxi routes based onthe conguration of the airport at a given time. However,those plans might not result in an optimal solution fromthe operator’s view for a specic ight. A proposed solu-tion is to provide automation aids or decision supporttools (DS s) to cab controllers to “help optimize and

control the departure ow” to benet both controllersand aircraft operators (Anagnostakis & Clarke, 2002, p.1). Te expectation is that DS s will enable tower cabcontrollers to handle more aircraft with greater efficiency,less delay, increased safety, and less environmental impact.

Tis is not a new idea. For example, a system forcomputer-ordered arrivals spacing was tested in the mid-

and late-1960s in a laboratory simulation and with livetraffic at New York’s John F. Kennedy International (JFK)airport, reportedly with some success (Cirino, 1986). Hurstdescribed the Surface raffic Control System (S RACS)as an automated ground control system. S RACS wasintended to “… relieve the human Ground Controller inthe ower from much of the burdensome routine tasksassociated with ground control” (1971, p. 15). Te con-troller’s role would be one of “instructing the computerand monitoring the complete system operation” (p. 15).Te early 1980s brought the erminal Air raffic Control

Automation ( A CA) as a component of the FAA’s Ad-vanced Automation System (AAS) program that was tomodernize the NAS (Gosling, 1993). Yet nearly 30 yearslater, the tower controller’s role and the tools available havenot signicantly changed. Control of the airport surfaceis still the least automated part of the A C system, rely-ing largely on controller “out-the-window” surveillance,voice radio, and controller judgment (Gosling), despitesignicant investments in research and engineering.

ower A C operations might change under NextGenin two ways. First, surface operations in NextGen willchange from “a highly visual, tactical environment to a

more strategic set of operations that are independent ofvisibility, better achieve operator and ANSP [air navigationservice provider] efficiency objectives, and better integratesurface, airspace, and traffic ow decisionmaking” (JointProgram Development Office (JPDO), 2007, p. 2-5). TeNextGen controller (re-titled as the “Air Navigation ServiceProvider,” or ANSP1) will rely “more on automation toperform routine tasks, yielding ANSP productivity gainsas controllers handle more traffic” at major airports andtake “a more strategic view” (p. 2-27) of airport surfaceoperations. Digital data communications between ightoperators and the ANSP will be the norm, with voice radioused on exception and as a backup (p. 2-31). Second, airtraffic control services at lower-volume airports might beprovided remotely through a “Staffed NextGen ower”(FAA, 2008a). Controllers will provide services from a“ground-level,” possibly off-airport facility to one or moreairports. Te controllers “will be assisted by an integratedtower information display that presents weather, surveil-lance data and other essential information and [a] suiteof decision support tools (DS s)” (p. 1). An “alternativemethod” will be used in lieu of the out-the-window viewfrom today’s tower cab for “…various A M functions



5

such as issuing clearances, alerting [aircraft] of runwayobstructions, and providing separation assurance” (p. 2).Increased reliance on automation, digital communications,a shift from a tactical to a “strategic” control paradigm,and possibly providing services remotely might impactthe aptitudes required of controllers for successful per-formance of their duties.

Controllers working in the FAA tower cab areresponsible for the safe and efficient movement of air-craft and ground vehicles operating on the taxiways andrunways of the airport itself, and aircraft in the air nearthe airport, generally within 2 to 5 nautical miles (nm;3.7 to 9.2 kilometers (km)) of the airport, depending on

the particular airport. Te primary function of the towercab is to separate aircraft landing or taking off from anairport and moving on the airport surface (Nolan, 1994).Separation in A C refers to the physical and/or temporaldistance, at a given time or location, between aircraft andother aircraft, vehicles, terrain, airspace, and other objectsthat might obstruct a ight. Te primary tool to controlthe movement of aircraft and vehicles on the airport sur-face is the clearance. A clearance is a set of instructionsissued to a specic aircraft, vehicle, or person. Commontower cab clearances are for a route of ight from originto destination and for landing on or taking-off from arunway. Controllers also issue instructions for aircraft,

Figure 2: Chicago O'Hare (ORD) airport diagram



6

vehicles, and personnel to move from point A to point Bon the airport surface. Tey also issue safety advisories andother information such as airport conditions and weather.Generally, clearances, instructions, and advisories fromthe tower cab controllers are issued by voice radio andare tactical in nature.

ower cab clearances and instructions are tactical

in three ways. First, a clearance is issued to a specic air-craft, vehicle, or person. Second, their geographic scope isgenerally limited to the airport surface and its associatedairspace (the exception is the departure route-of-ightclearance, discussed below). Tird, tower cab clearancesand instructions are for actions to be taken within a limitedtime horizon, often just a few minutes. For example, aninstruction to cross an active runway is generally a “doit now” rather than a “do in the next 10 minutes at youroption” instruction.

Controllers in the cab continuously monitor andevaluate aircraft, vehicles, and personnel operating onand around the airport for separation and conformance toclearances and instructions. Other cab functions includeassessing weather impact on A C operations, disseminatinginformation, advisories, and recommendations, operatingairport taxiway and runway lighting systems, record-keeping, and coordinating with adjacent A C facilities,airport authorities, and airlines as required.

CURRENT ORGANIZATIONOF THE TOWER CAB

Te tower cab is organized functionally around“working positions” that are staffed by on-duty controllers(FAA, 2010e). A working position in the cab is generallyresponsible for the surveillance, control, and communi-cations with aircraft in specic areas of the airport andimmediately adjacent airspace. Te controller in eachposition provides specic services. Tere are generally four

working positions in an air traffic control tower cab: LocalControl, Ground Control, Flight Data, and ClearanceDelivery. A ower Supervisor is also on duty in the cab.Te four working positions may be combined or split atthe supervisor’s direction. For example, the Flight Dataand Clearance Delivery positions are often combined. A

raffic Management Coordinator position might also bestaffed at large, complex hub airports.

Ground ControlTe controller working the Ground Control position

(sometimes referred to simply as “Ground”) is responsiblefor the safe and efficient movement of aircraft and groundvehicles in the airport “movement areas.” Movement areasgenerally include all taxiways, inactive runways, holdingareas, and some transitional aprons or intersections where

aircraft arrive, having vacated the runway or departuregate. Ground may also be responsible for the ramp areas,depending on airport conguration and complexity. Teremay be more than one Ground position for large, complexand busy airports. Te exact specication of movementareas over which FAA exerts positive control varies withspecics of an airport and its operations.

Any aircraft, vehicle, or person moving, walking, or working in a movement area is required to have clearancefrom Ground. A clearance is a set of instructions issuedto an aircraft, vehicle, or person for a specic operationsuch as taking off or inspecting a runway. Clearances arenormally transmitted by Ground via VHF or Ultra-HighFrequency (UHF) radio. Most importantly, Ground con-trols aircraft movements on the taxiways to and from theactive runway(s). Ground inuences the sequence of air-craft heading towards the departure runway. For example,if two aircraft call “Ready to taxi” at essentially the sametime, Ground has discretion in determining which aircraft

will be handled rst. Ground might direct ight 123 tostop short of an intersection with a taxiway, and instructight 789 (already on the taxiway) to proceed through theintersection and on to the departure runway. Flight 123

would then turn onto the taxiway and follow ight 789 onout to the departure runway. Factors taken into accountby Ground in determining the sequence of aircraft on thetaxiways to the departure runway(s) include (but are notlimited to) destination, route, departure xes, runwayloading, winds, aircraft size and weight, and associated

wake turbulence constraints. Ground must also ensure

that aircraft, vehicles, and pedestrians are appropriatelyseparated while moving on the airport surface.

Local ControlTe controller working the Local Control position

(or, more simply, “Local”) is responsible for the activearrival and departure runway(s). Local clears aircraft fortakeoff or landing, ensuring that prescribed runway sepa-ration exists at all times. Communication and control ofdeparting aircraft is transferred to the RACON departurecontroller, provided the aircraft is properly separated fromother traffic and is established in a normal climb. Arrivalscontact tower on the Local frequency; Local clears the ar-rival to land on a specic runway (again, if and only if theaircraft is properly separated from other traffic or obstaclesto a safe landing). Depending on the specic airport,Local will direct arriving aircraft to exit the runway at aspecic point, usually a taxiway. Once the aircraft clearsthe runway, control and communication is transferred toGround. A key responsibility for Local is to ensure thatthere are no obstructions or impediments to arriving anddeparting traffic. Sensibly, the runway must be clear ofall other traffic for an aircraft to land or take-off. If the



7

controller working Local detects any unsafe condition, suchas a vehicle intruding on the active runway or an aircraftthat failed to exit the runway as directed, the next landingaircraft in the sequence may be told to “go-around” and bere-sequenced into the landing pattern. Known as runwayincursions, unauthorized intrusions of aircraft, vehicles,or personnel onto an active runway are among the most

serious and dangerous aviation errors.Close coordination and continuous communication

within the tower, especially between Local and Ground, isabsolutely imperative. Generally, Ground must explicitlycoordinate with Local to cross any active runway with anyaircraft or vehicle. For example, when DFW is operatingin what is known as the “South Flow” conguration, jetarrivals land from the north on the outboard runwayslabeled 17C, 17L on the east and 18R on the west sideof the airport.2 Departures take off to the south from theinboard labeled 17R on the east side and 18L on the westside (Figure 3). As a result, the arriving aircraft must crossthe active departure runways to reach the terminals in themiddle of the airport. Te requirement to coordinate andcommunicate is reciprocal: Local must ensure that Groundis aware of any operations that will impact the taxiwaysor other movement areas in Ground’s control.

Flight Data Flight Data is responsible for ensuring that control-

lers and pilots have the most current aireld information:pertinent weather changes, outages, airport ground delays/ground stops, runway closures, etc. Flight Data may inform

the pilots about airport information using Automaticerminal Information Service (A IS). A IS is a recording

of pertinent information broadcast in a continuous loopon a published frequency for that airport.

Clearance Delivery Controllers working the Clearance Delivery posi-

tion issue departure clearances to aircraft, typically beforethey commence taxiing. Clearances contain details of theroute that the aircraft is expected to y such as departurexes (rst x after take off), waypoints along the route,and destination. Te primary responsibility of ClearanceDelivery is to ensure that aircraft have the proper routeand departure “slot” time (that is, a specic time windowin which to depart). Tis information is also coordinated

with Ground and the appropriate en route center to ensurethat the aircraft reaches the runway in time to meet the slottime provided by the national Air raffic Control SystemCommand Center. Clearance Delivery and Flight Dataare often combined into a single position.

Tower Cab TeamCollectively, the four “standard” working positions

and tower supervisor are known as the tower cab team or“cab crew.” A tower may staff other working positions asneeded. Te FAA order governing A C facility organizationand operations (FAA, 2010e) lists as many as 17 differentpositions that might be lled in a tower cab. Positions canalso be combined. However, it is important to note thatcontrollers working in the cab must function as a team.

Figure 3: DFW in South Flow configuration (wind from the south)



8

Paragraph 10-1-2 of the order readsTere are no absolute divisions of responsibilities regard-

ing position operations. Te tasks to be completed remainthe same whether one, two, or three people are workingpositions within a tower cab/facility/sector. Te team, as a

whole, has responsibility for the safe and efficient operationof the tower cab/facility/sector.

Current Equipment in the Tower CabTe primary method of controlling traffic in the im-

mediate airport environment today is visual surveillance(e.g., “out-the-window” [O W] view) of movement areasby controllers from the tower. Basic facility equipmentincludes radios, telephones, weather instruments, (voice)recorders, airport lighting controls, Runway Visual Range(RVR) system, and the Flight Data Input/Output (FDIO)system. Multiple displays are available to the controllersin tower cabs, each associated with a particular system.Tese displays include the Certied ower Radar Display(C RD) and the Airport Surface Detection Equipment(ASDE) displays. C RD (Figure 4) provides tower con-trollers with a visual display of the airport surveillanceradar/beacon signals and data received from the terminalradar system, including airborne aircraft position, iden-tication, radar beacon, and weather information. It isa high intensity display that can be seen by the towercontroller even in a bright daylight environment. WhileC RD provides information about airborne traffic, the

ASDE displays information for traffic on the surface of

the airport. Te most modern ASDE system is the ASDEModel X (ASDE-X; Figure 5), which presents a 2-D mapof the airport surface and allows the tower controllers totrack surface movement of aircraft and vehicles. ASDE-Xassociates data tags with aircraft on the airport surface, us-

ing data from the aircraft ight plan. Finally, many towershave an Electronic Flight Strip ransfer System (EFS S), which provides an electronic method for transferring ightinformation from the tower cab to other facilities suchas the RACON.

Current Workow in the Tower CabTe workow in a tower cab is driven by the tempo

of departures and arrivals, the communications requiredto handle the traffic, the mix of aircraft types and equi-page, and airport layout. Te work is also highly cyclicaland repetitive, especially in high-volume hub airportsdominated by air carriers operating commercial passen-ger and cargo ights. Example high-volume hub airportsin the U.S.A. include A L (the nation’s busiest), ORD(second-busiest), LAX (third busiest), and DFW (fourthbusiest). Tese airports typically have multiple runwaysand complex taxiways. Departures and arrivals are com-monly scheduled by air carriers in overlapping “banks”at major airports. For example, a “bank” of 45 arrivalsmight be scheduled in the period 1200 to 1245. A bankof 36 departures might be expected between 1225 and1310. Te arrivals might be a mix of hub-to-hub traffic

Figure 4: CTRD in ORD tower cab



9

and “feeders” from secondary markets to the hub. Tedeparture bank would be a similar mix of hub-to-hubights and ights to secondary markets. Tere might bea relative lull in the overall traffic, with a slower pace ofarrivals and departures between 1330 and 1410, followed

by overlapping banks for arrivals and departures startingat 1410. In the early part of the busy period, workowis driven by the arrivals; towards the end the workow isdriven by departures. A major hub will experience manyof these tides during the day.

o illustrate the workow, single departures and ar-rivals will be used to describe the major tasks required ofeach position.

Single Aircraft DepartureTe departure cycle for a scheduled ight operating

under itle 14 of the Code of Federal Regulations (CFR)Part 121 (14 CFR 121) begins with the ight operator(either the aircraft pilot or a dispatcher in the Airline Op-erations Center [AOC]) ling a ight plan with the FAA.Depending on local procedures, a ight progress strip (FPS)is generated in the tower cab anywhere from 20 minutesto 2 hours before the scheduled departure. Example stripsin both machine-generated and hand-written formatare illustrated in Figure 6. Briey, from left to right, themajor blocks (columns) are aircraft information (items1-4), assigned beacon code, proposed departure time,and requested altitude (items 5-7), departure airport (8),

and route information (9). Te Flight Data controller canalso request a ight progress strip via FDIO. Flight Datareviews the ight plan as printed on the strip and makesamendments if required. Many (most) plans for scheduledcommercial ights are led far in advance. Tese “canned”

ight plans might require amendments due to weather andother constraints on the day and at the time of the ight.Certain amendments to the led route are made by the Airraffic Control System Command Center before the ight

strip is printed at the local tower. Tese amendments reectimposition of constraints (known as raffic ManagementInitiatives [ MIs]) such as holding ights for a specicdestination on the ground at the departure airports andre-routes for entire ows of traffic to avoid severe weather.Other ight constraints are more airport specic, such asa runway closure.

After reviewing the ight plan and making appropri-ate amendments, Flight Data passes the departure strip toClearance Delivery. Clearance Delivery issues the departureclearance via voice VHF radio to aircraft that do not subscribeto electronic delivery via erminal Data Link Services ( DLS;FAA, 2008b). An IFR departure clearance includes specic,mandatory elements ( able 1). Tese are (a) aircraft identi-cation, (b) a clearance limit, (c) the departure procedure,(d) the route of ight, (e) altitude, (f ) departure frequency,and (g) the transponder code. After issuing the departureclearance, Clearance Delivery passes the ight progress stripto the controller working the Ground position.

Figure 5: ASDE-X display (ORD)



10

When the ight is ready to depart, the pilot callsthe tower on the Ground Control frequency (generallypublished on the airport diagrams as shown in Figure 2,upper left-hand corner). At some airports, the pilot con-tacts the tower cab to request pushback (or powerback

where tugs are not available) from the gate. At the largerhub airports, more often the pushback from the gateis controlled by a Ramp Controller (employed by theight operator or airport) rather than an FAA controller.

At these large airports, the aircraft pushes back from thegate, and then taxis to what is known as a “spot.” A spot isthe location at which the FAA assumes responsibility forcontrol of the aircraft’s movement. Te pilot calls Groundon the designated frequency and requests permission totaxi. Ground then issues instructions for the aircraft totaxi to the departure runway. axi instructions do notinclude the word “Cleared.” Rather, verbs such as “ axi,”“Proceed,” “Continue,” “Follow,” “Cross,” and “Hold shortof” are used. At a minimum, a taxi-out instruction willinclude (a) the departure runway for the aircraft, and (b)the taxi route: “Highline three fty-nine, taxi to runway

one eight left via taxiway Golf.” o reduce ambiguity andtime required to issue taxi instructions at complex airports,a standardized or Coded axi Route (C R) might beused. Tese are published procedures for specic airports,and essentially are shorthand for a series of discrete taxiinstructions. So instead of saying, “ axi to runway one-seven right via taxiway Juliet to Juliet 6, taxiway Bravo,then Whiskey,” the instruction would be given as “ axi torunway one-seven right via Scenic.” Alternatively, Groundcan issue progressive taxi instructions, in which instruc-tions are given for each step of the taxi: “Highline threefty-nine, taxi to runway one-eight left via Juliet, holdat Juliet Six and report.” Upon reaching the designatedintersection, the aircraft would call Ground for additionaltaxi instructions: “Highline three fty-nine, Continuetaxi to runway one-eight left via Bravo, then Whiskey.”Te departing aircraft executes the taxi instruction andGround monitors the progress of the ight through theairport movement area by looking out the window and

watching the ASDE display.

Figure 6: Flight Progress Strip (FPS) layout and example machine-generated and hand-written strips(from FAA Academy Initial Terminal Training: Stripmarking (TLP-11) (March, 2007)

Table 1: Example simple departure clearance

IFR Clearance Element Example

Aircraft Identification UNITED FIFTY-FIVEClearance Limit CLEARED TO BURBANK AIRPORTDeparture Procedure MARIC THREE DEPARTURE GORMAN TRANSITIONRoute of Flight VICTOR TWENTY-THREE, TWINE, DIRECTAltitude MAINTAIN FIVE THOUSAND, EXPECT FLIGHT LEVEL TWO

ONE ZERO, ONE ZERO MINUTES AFTER DEPARTUREDeparture Frequency DEPARTURE FREQUENCY ONE ONE NINER POINT ONE

Transponder Code SQUAWK ZERO FOUR FIVE FOUR



11

Under the current “First Come, First Served” controlparadigm (see Paragraph 2-1-4 of FAA JO7110.65 (FAA,2010b)), aircraft are handled in the order in which theycontact Ground. However, Ground has a great deal ofdiscretion in responding to aircraft calls and can managethe sequence of aircraft for the departure runway througha variety of tactics. Te controller working Ground

solves a real-time optimization problem with signicantconstraints, particularly at large, complex airports withvarying mixes of aircraft. Te overall optimization goalsare to minimize taxi-out delay, maximize the departurerate, and to depart the aircraft on an efficient trajectory.

At large hub airports, Ground manages this optimizationproblem though facility-specic Standard OperatingProcedures (SOPs), “game plans,” and experience. Forexample, an SOP might direct aircraft bound for the easternhalf of the country (relative to the airport) to depart offa runway on the east side of the airport and west-boundaircraft to depart from a runway on the west side. Tispractice might entail using specic taxiways preferentiallyfor most departures and anticipate congestion at a specicintersection. Informal “give way” or “right-of-way” rulesmight be applied to govern which aircraft proceeds throughthe intersection and which must stop for crossing aircraft.For example, departing “heavy” aircraft might have right-of-way through an intersection when established on anorth-south taxiway but not in crossing from east to west.Similarly, Ground might “tee up” a series of four smalleraircraft such as two Boeing 737s and two McDonnell-Douglas Super 80s, followed by two “heavies” (such as a

Boeing 747 and 777), followed by three smaller aircraft,and so forth. Tis sequencing allows the Ground to takeadvantage of the longer inter-departure interval betweenthe heavies and the smaller aircraft to send arrivals acrossthe active runway. In normal operations, Ground doesnot improvise new procedures on the y, but rather uses

well-established methods to manage the departure queue,minimize delay, and maximize throughput with a highmargin of safety. In other words, the work is highly pro-ceduralized. At present, those procedures are embodied asverbal instructions delivered over the radio to the aircraftby Ground Control. Te tower cab staffing standards, infact, are driven by the radio communications associated

with aircraft operations (Schmeidler & D’Avanzo, 1994):More aircraft means more radio communications forGround Control.

Upon arriving or nearing the active departure runway, the aircraft then contacts Local Control for actualtake-off instructions. Local controls the active runway;aircraft must have positive permission from Local to be onor to cross an active runway. Local is also responsible foraircraft in ight within a few miles of the airport (usually3 to 5 miles); generally, these aircraft will be departing,

arriving, or circling the airport. Local issues the take-offclearance, which in its simplest form has just three ele-ments: Aircraft ID (call sign), runway, and “cleared fortakeoff.” For example, a simple takeoff clearance would be“Highline three fty-nine, runway one eight left, clearedfor takeoff.” Local must ensure positive identication ofthe aircraft and that the active runway is clear of obstruc-

tions, aircraft, vehicles, personnel, or other obstacles beforeissuing the takeoff clearance. With a queue of departuresat the end of the active runway and taxiways supplyingthe runway, Local must consider the timing and condi-tions of each successive takeoff. For example, Local must

wait a specied time before clearing any aircraft to takeoffbehind a “heavy” aircraft (for example, a Boeing 747)due to wake turbulence. Aircraft might require turnsto specic headings immediately after takeoff for noisereduction, avoidance of prohibited or restricted airspace,other traffic, and other reasons. In each instance, specicphraseology is required to accomplish the intended goal ofa safe, efficient, and orderly series of departures. Once thedeparture is airborne and about 0.5 nautical miles beyondthe runway end, Local instructs the aircraft to contactDeparture (FAA, 2010b, Paragraph 3-9-3, DepartureControl Instructions). Local scans the bar code printedon a machine-generated FPS to electronically transferight data to the departure controller.

Single Aircraft ArrivalLocal Control manages the arrivals, often interleaving

them with departures. At some large hubs, runways might

be allocated solely or primarily to arrivals or departuresby facility SOP or informal practices. For example, in thesouth conguration at DFW, Local might use 17 Right(the 1st runway on the east side of the airport) primarilyfor east-bound takeoffs (departures), and 17 Center and 17Left for turbojet arrivals (see Figure 3). akeoffs and arrivalsare to the south in this conguration. At the basic level,a landing clearance has just three components: AircraftID (call sign); runway; and landing clearance: “Highlinethree ninety-ve, runway one seven center, cleared toland.” Additional instructions may be necessary, suchas an instruction to hold short of another active runwaythat crosses the landing runway. After the aircraft lands,Local will issue runway exiting instructions and possiblyan instruction on when to contact the Ground Control.For example, an aircraft landing to the south on 17Cat DFW might be instructed to turn right and exit therunway at the Mike Six (M6) high-speed turnoff, crosstaxiway Mike (between 17C and 17R), hold short at theEcho Mike (EM) intersection with runway 17R, andto contact Ground on the appropriate radio frequency:“Highline three ninety-ve, runway 17 center, cleared toland. urn right at Mike Six, cross taxiway Mike, hold



12

short of runway 17 right at Echo Mike, contact Groundpoint seven four.” Te arriving aircraft in this scenariolands from north to south on 17C, exits the runway atM6 with a right hand turn, crosses taxiway M betweenthe two runways, stops just east of the departure runway17R at the intersection labeled Echo Mike, switches tothe frequency, and contacts Ground. Te pilot reports the

current position and intended destination (gate, terminal,hangar, or other location on the airport). In this example,the arrival is headed for a specic gate, as directed by theight operator. Ground coordinates with Local to havethe arrival (“Highline three ninety-ve”) cross the activedeparture runway (17R), and then issues the appropri-ate crossing and taxi instruction to get the aircraft to theappropriate “spot.” On nearing or reaching the “spot”nearest the company assigned gate, the aircraft switchesto its company frequency. Te associated electronic recordfor the ight is then closed out and archived.

Multiple Aircraft Operations While the basic ow is relatively straightforward

for a single departure or arrival, the reality is far morecomplex with multiple aircraft in different phases ofthe operation, especially at large hubs with overlappingbanks of arrivals and departures. Controllers, particularly

when working the Ground and Local positions, are re-sponsible for multiple aircraft at any given moment in amix of arrivals and departures on the active runways andtaxiways. For example, the Local Controller might issue alanding clearance to an aircraft several miles out on nal

approach to the arrival runway, then turn her attentionto issue a takeoff clearance to an aircraft in the queuefor departures, and then coordinate with the Ground toclear several aircraft across the active departure runway, all

within a minute or less. Similarly, Ground Control mighthave an arrival waiting for clearance to cross the activedeparture runway, two departure aircraft calling from thetransfer-of-control “spots” at the boundary between theairline’s ramp and the FAA’s movement areas, ready tobegin their taxi, three aircraft established on the taxiwayto the departure runway, and two inbound aircraft taxiingtoward the terminal.

Te Local and Ground controllers maintain anactive scan of their areas of responsibility (FAA, 2010b,Paragraph 3-1-12, Visually Scanning Runways). Te lo-cations of aircraft, vehicles, and other objects relative toexpectations and intentions are constantly evaluated andactions taken as needed by the controller. For example,the controller working Ground might evaluate the relativetaxi speed of two aircraft heading towards the same inter-section, and issue an instruction to one aircraft to “give

way” to the other. Similarly, Local might shift attentionto a departing aircraft to determine its progress and if it

has rotated for take-off as a visual cue to issuing a take-offclearance for the next aircraft in the departure queue. Inboth examples, the sequence of behaviors associated witheach clearance or instruction is completed (or completedthrough a certain point), and the scan of the area underthe controller’s responsibility is resumed. External eventsmight trigger another behavioral sequence such as an

aircraft checking in on the GC frequency with a “readyto taxi” call. On completion of that behavioral sequence,the controller returns to monitoring and evaluating themovement and positions of objects, ready to take actionas needed to ensure the safe, efficient, and orderly owof traffic into, on, and out of the airport.

Current Job/Task AnalysesTe work done by controllers in today’s NAS has

been described in several formal analyses. Te most relevantanalyses are (a) the Computer echnology Associates,Inc. (C A, Inc.) operations concepts analyses from thelate 1980s (see Alexander, Alley, Ammerman, Fairhurst,Hostetler, Jones & Rainey, 1989; Ammerman, Becker,

Jones, obey, & Phillips, 1987), (b) observational studiesby Booz, Allen, Hamilton, Inc. (2006), Durso and col-leagues (Durso, Sethumadhavan, & Crutcheld, 2008;Durso, Fleming, Johnson, & Crutcheld, 2009), andPinska (Pinska & Bourgois, 2005; Pinska, 2006); (c) an“update” of the C A, Inc. description by the AmericanInstitutes for Research (AIR®; Krokos, Baker, Norris, &Smith, 2007); and (d) the University Research Corpora-tion (URC) selection-oriented job/task analysis (Nickels,

Bobko, Blair, Sands, & artak, 1995). Te C A, Inc.analysis has become the de facto “standard” job/taskanalysis for air traffic control in the FAA for describingthe work of controllers in centers, RACONs, and towers.For example, FAA instructional system designers used theC A, Inc. descriptions as the starting point for identify-ing changes in controller tasks with new technologiesand procedures such as the User Request Evaluation ool(URE ) and the Airport Movement Area Safety System(AMASS; R. Welp, personal communication). Similarly,the 1995 Nickels et al. analysis of worker requirements hasbecome the de facto standard catalog of aptitudes requiredat the time of hire into the A CS occupation in the FAA.

CTA Inc. Operations Concept Analysis forthe Tower Cab

Te goal of the C A, Inc. operations concept analy-sis was to describe how future controller work would beperformed in the Advanced Automation System (AAS).C A, Inc. produced a series of volumes describing (a)the “as is” (as of the late 1980s) for controller work in thetower, RACON, and center, (b) the knowledge requiredin the “as is” NAS (as of the early 1990s), and (c) the “to



13

be” for controller work in AAS facilities such as the owerControl Computer Complex (A C / CCC; Ammerman,Becker, Bergen, Claussen, Davies, Inman, et al., 1987).Te C A, Inc. operations concept analysis is similar toa hierarchical task analysis (H A; see Annett, 2004), a widely used method for representing the work performedby humans in a system. However, C A, Inc. developeda graphical depiction of the work performed by control-lers, a full decade before commercially-available job/taskanalysis applications began incorporating that capability.Te graphics depict operational events or conditions thattrigger different sequences of controller actions and also showthe inherently cyclical and repetitive nature of the work.

In the C A, Inc. operations concept analyses, control-ler work is described at ve levels, as shown in able 2. Tehighest level of description is an “Activity” in their approach. An A CS activity is a major job duty or function. Te workof controllers at a working position is described with veto nine activity statements. Each activity is decomposed by Ammerman et al. into ve to nine “Sub-activities.” Sub-activities are decomposed into tasks, and, in turn, tasks aredecomposed into task elements.

Te task is the focus of the C A, Inc. analysis ofcontroller work. A task is a concise, specic statement of what is accomplished by a person in a specic operatingenvironment and position, with a clear beginning andending, with sufficient detail to understand what is ac-complished without enumerating the minor, proceduralsteps required in performing the task (Ammerman, et al.,1987). All descriptions of controller work in the C A, Inc.analysis take the form of a verb-noun (object) phrase, withmodiers appropriate to the context for a particular workstatement. Te procedural steps are “task elements” in theC A approach. Te lowest level of description is the UserInterface Language (UIL), which refers to (a) the operationaldata and control messages entered into the system by thecontroller in the performance of a task element and (b)the graphical displays, alphanumeric displays, written andprinted messages, and alerts, alarms, and other signals forcontroller attention. Display contents and controller mes-sage entries cataloged in the UIL are used as the objects inthe verb-object statement that constitutes a task element.

Te high-level activities originally dened by C A,Inc. for CD/FD, Ground, and Local control are presentedin able 3. Tere are redundancies in the activities across

Table 2: Five levels of description used by Ammerman et al. (1987, 1989)

Level Description

Activity A group of related sub-activitiesSub-activity The operations performed in response to a single eventTask The smallest discrete unit of human behavior that can be fully understood within the

general context of the job environmentTask Element A single identifiable step in the performance of a task UIL (a) Operational data and control messages entered into the system in performance of a

specific task element;(b) graphical and alphanumeric displays, written and printed messages, alerts, alarmsand other signals for controller attention.

Table 3: High-level activities by position from the CTA, Inc. ATCT operations concept analysis

Local Control Ground Control Flight Data/Clearance Delivery

Perform local situationmonitoring

Perform ground situationmonitoring

Perform clearance delivery/flightdata situation monitoring

Resolve conflict situations Control aircraft/vehicle groundmovementManage air traffic sequences Manage air traffic sequencesRoute or plan flights Route or plan flights Route or plan flights

Respond to flow constraintsAssess weather impact Assess weather impact Assess weather impactManage local controller positionresources

Manage ground controller position resources

Manage clearance delivery/flightdata controller position resources

Respond to system/equipmentdegradation





14

the three working positions. For example, controllers inall three positions “Route or Plan Flights.” While there aredifferences by position, especially at the task element andUIL levels of analysis, the actual work is very similar. Inrouting or planning ights, a controller considers informa-tion about the ight, selects a course of action, ensures thatthe planned action is safe, and communicates that action

to the aircraft directly or for relay by another controller.Local might rely upon the C RD, ight progress strips,and out-the-window observations, while Ground looks atthe ASDE(-X) display, strips, and out-the-window view asinformation sources.

Observational Studies of the Tower CabObservational studies focused on controller be-

haviors in the tower cab. For example, Pinska (Pinska& Bourgois, 2005) reported that looking out the tower

windows occupied 30 to 40% of controller time in thetower cab. Other frequently used information sources

were ight progress strips and radar displays. Furtherstudy conrmed these results (Pinska, 2006). Booz, Al-len, Hamilton, Inc. (2006) collected observational data atseven towers to identify information needs and sources.Te analysts reported that the out-the-window view, ightprogress strips, and radar displays (both air and surface)

were the most frequently used information sources. Dursoand colleagues (Durso et al., 2008, 2009) investigated theuse of paper ight progress strips for each working posi-tion in the tower cab. While some strip marking mightbe characterized as primarily “bookkeeping,” the marks

were also useful to the controllers to reduce workload,and to aid communications, memory, organization, andsituation awareness. While these studies highlight aspectsof work behavior, they were not full-scale job analyses tosupport identication of aptitudes.

AIR® 2007 Update for the Tower CabKrokos, Baker, Norris, and Smith (2007), on the

other hand, reviewed the C A, Inc. descriptions down tothe task level of analysis and endeavored to consolidate theactivities, sub-activities, and tasks into a single, integrateddescription of the work of a controller in the tower cabacross the working positions. Te result is a functionalrather than positional analysis. AIR® described the workof controllers in terms of eight activities: (1) Perform situ-ation monitoring, (2) Resolve aircraft conict situations,(3) Control aircraft or vehicle ground movements, (4)Manage air traffic sequences, (5) Route or plan ights,(6), Assess weather impact, (7) Manage controller posi-tion resources, and (8) Respond to system/equipmentdegradation. Tese job activities provide a useful way toorganize the description of tower controller work for thepurpose of this paper.

1995 Selection-oriented JTA Te operations concept analyses, observational stud-

ies, and the 2007 update focused on describing the workof tower cab controllers. While useful, personnel selectionrequires a specication of the knowledge, skills, abilities,and other personal characteristics (KSAOs) as well. TeFAA, at least at present and in the foreseeable future, selects

new controllers on their aptitude rather than demonstrated A C-specic knowledge and skill. Aptitude, in this usage,refers to the set of innate and acquired abilities and othercharacteristics a person possesses at the time of hire, andfor which the employer provides no explicit training ordevelopment. Te most recent analysis of the aptitudesrequired to enter the A CS occupation was the 1995 job/task analysis to support the Selection and Control Hir-ing Assessment (SACHA; Nickels et al. in 1995). Tatformal, selection-oriented job/task analysis identied 67“worker requirements” based on psychological and A Cresearch. Incumbent controllers rated the importance ofeach worker requirement to learning and doing the job.Nickels et al. analyzed the ratings by type of facility: airroute traffic control center (AR CC), terminal (includ-ing cab and RACON), and ight service station. Teimportance ratings were also analyzed by job assignmentand facility level within the terminal option. Te three

job assignments were A C cab only, RACON only,and A C cab and co-located RACON (“up/down”facilities). Overall, there was a high level of agreement inthe ratings of the importance of the worker requirementsacross the three job assignments within the terminal option.

Te list of worker requirements (aptitudes) identiedby the 1995 job analysis are presented in the Appendix,sorted by average importance (IMP) to doing the job(from high to low). Importance was rated on a 0 to 5 (i.e.,not needed to extremely important) scale by a sample of

job incumbents (n=389). Te importance ratings werealso analyzed by working environment (A C cab,

RACON, and AR CC). In comparing A C cab andRACON, the study authors concluded that “…there

were no substantive differences in the relative rankings ofthe worker requirements across the job assignments withinthe erminal option, and that these assignments can beconsidered to be quite similar for purposes of selection”(p. 158; emphasis added). Similarly, in considering therank ordering of worker requirements across workingenvironments (e.g., A C , RACON, and AR CC), theauthors concluded, “From a selection perspective thereappear to be no substantial differences between AR CCcontrollers and A CSs working erminal option by jobassignment” (p. 159, emphasis added). In other words,there is a common prole of aptitudes required for selec-tion into the A CS occupation (but the differences inimportance by working environment might be useful for



15

placement purposes). As the focus of this paper is selectioninto the A CS occupation, the overall prole of aptitudesderived by Nickels et al (1995) is adopted as the baselinefor this analysis. Te analytic question addressed in thisreport is “How and to what degree mid-term NextGentechnologies and procedures change that occupationalprole in the tower cab?”

Baseline Aptitude ProleOf the 67 worker requirements evaluated in the

1995 job/task analysis, 29 had an average rating of four(“Very important to doing the job”) to ve (“Extremelyimportant to doing the job”). 3 Tese aptitudes can beloosely organized, for explanatory purposes only, in termsof an input-process-output model (Figure 74). Te abili-ties related to the “input” side are visual perception andauditory perception; sight and hearing are fundamental tosuccess in air traffic. Te specic visual abilities importantto work in the tower cab are (a)Scanning and (b) PerceptualSpeed and Accuracy . Scanning in the 1995 analysis wasdened as the “ability to quickly and accurately visuallysearch for information (e.g., on a computer screen, radarscope, ight strip bay, runway, on the horizon).” In other

words, tower cab controllers must have the ability to visu-ally search multiple sources of information, including theout-the-window view, radar display, surface display, ightstrips, and other visual elements. Te controllers must beable to “perceive visual information quickly and accurately,”otherwise known as demonstratingPerceptual Speed and Accuracy . Te third “input” is labeled Active Listening .

Tis ability was dened by controllers and psychologistsin the 1995 analysis of worker requirements as the abil-ity “to hear and comprehend spoken information.” Tisanalysis is sensible in that even a cursory considerationof the work of tower cab controllers would conclude thatit is dominated by visual and auditory stimuli. It makessense, then, that controllers would need the ability to seeand hear those stimuli.

However, a ner distinction can be made. Control-lers in the tower cab are ooded with information in thevisual and the auditory channels. Te denition of ActiveListening in the 1995 analysis includes “…the ability torecognize or pick out pertinent auditory information.”In other words, auditory attention (i.e., Active Listening )is part of the prole of aptitude for the A CS occupa-tion. One can argue that the same qualication is madefor visual information: It is important for controllers tohave the ability to selectively attend to (quickly and ac-curately) the relevant visual elements that are “pertinent”to the task at hand.

Te primary output for controllers is speech, or inthe 1995 lexicon, Oral Communications . Tere are alsomotor outputs, as shown in Figure 7, in terms of writ-

ing, typing, and using a computer mouse, but they palein signicance compared to talking on the radio andtelephone. Controllers in the current tower cab rely uponspeaking clearances and instructions over the radio. Ofthe 184 tower controllers participating in the 1995 jobanalysis survey, two-thirds ratedOral Communications as“Extremely Important – Lack of this ability will seriously

jeopardize [your] ability to do the job.” In contrast, just21 of those tower controllers rated the ability to write(Written Communication) as “Extremely Important.” Te1995 analysis qualies the denition ofOral Communica-tions : “Projecting a condent tone of voice is an importantcomponent of this ability.” However, as with the “abilityto quickly and accurately” pick out the visual and auditoryinput elements relevant to the situation at hand, it is notclear if the implied “ability to project a condent toneof voice” is innate, learned and developed in job-relatedtraining, or some mixture of both.

Te abilities required to process the visual and audi-tory input and produce the spoken outputs (clearances,instructions, and advisories) are both more numerousand more complicated to describe. Of the 29 abilitiesrated as very or extremely important, 19 were cognitivein nature and six can be described as personality traits orperhaps cognitive style. As with every description of hu-man cognition, memory was a key aptitude. In particular,Short-term Memory was rated by 83% (152 of 185) ofthe tower controllers as “Extremely Important” or “VeryImportant” to their job performance. Long-term Memory

was rated by about two-thirds of the tower controllers as

very or extremely important. Even casual observation ofthe job would suggest that both “types” of memory arefundamental abilities required of controllers. On one hand,the situation in which they work is uid and dynamic, witha cast of actors that changes within just a few minutes.On the other hand, controllers must memorize a largebody of rules and procedures, a specialized vocabulary andsyntax (to orally produce the highly formatted clearances,instructions, and advisories), and uniquely, a spatial mapof an airport and its airspace. However, the job analysisdid not further rene or explore ner distinctions in thesetwo commonplace cognitive constructs.

From an input-process-output perspective, theimportant perceptual abilities – Active Listening (includ-ing Auditory Attention), (visual)Scanning , and (visual)Perceptual Speed and Accuracy – are shown in Figure 7as feeding into Short-term Memory . Long-term Memory underlies the entire “process” block as containing the de-clarative and procedural knowledge required to performthe tasks of a tower cab controller.

For explanatory purposes only, the next set of cog-nitive abilities can be framed as those relating to atten-tion. Cab controllers must focus or attend to pertinent



16

F i g u r e

7 :

H e u r i s

t i c A T C S a

p t i t u d e

i n p u

t - p r o c e s s - o u

t p u

t m o d e

l



17

information embedded in multiple auditory and visualstreams of information in a very dynamic situation. woaspects of attention were rated, on average, as very orextremely important to doing the job by three-quartersof the incumbent tower controllers participating in the

job analysis survey:Sustained Attention; and Concentra-tion. Sustained Attention was dened in the job analysis

survey as the “ability to stay focused on a task(s) for longperiods of time (over 60 minutes).” Te second construct,Concentration, was dened as the “ability to focus on jobactivities amid distractions.”Sustained Attention explicitlyreferences duration, whileConcentration appears to reectthe intensity of the controller’s focus on the task at hand.

Given perceptual input into Short-term Memory ,declarative and procedural knowledge retrieved fromLong-term Memory , and attention to those events, thenext step, for explanatory purposes only, is to compre-hend the meaning of the dynamic situation. While thisstep seems to be sequential, in fact it is a dynamic andon-going cognitive process. Controllers often describe thisas “getting the ick” or “seeing the problem.” Anecdot-ally, some describe the awareness in terms of directing amovie, a state in which they visualize where the actors(aircraft and vehicles) will be in the next few frames. Amore psychological term is dynamic comprehension, thatis, the understanding of a dynamic, changing situation.Te relevant abilities rated by controllers, on average, asvery or extremely important, wereSituational Awareness ,Visualization, Dynamic Visual-Spatial , Flexibility (inInformation Processing), and Summarizing Information.

Situational Awareness was dened in the job analysis surveyas the “ability to be aware of, and to integrate, all relevantinformation within a four-dimensional (three dimensionalplus time) space (e.g., getting the picture).”Situational Awareness as a psychological construct is not withoutcontroversy ( enney & Pew, 2006) but has been widelyadopted in the aviation community. Not unsurprisingly,given the phrase “getting the picture” in the denition,a large majority (85% of 202) of tower controllers ratedSituational Awareness as very or extremely important to

job performance. Visualization in the 1995 job analysis was dened as the ability “to translate information intoa visual/mental representation of what is currently oc-curring,” with 83% of tower controllers indicating thisability was very or extremely important. Other abilitiesrelated to “getting the picture” that were less stronglyendorsed include Summarizing Information, DynamicVisual-Spatial , and Flexibility (in Information Processing).Summarizing Information, dened as the ability “to sum-marize and consolidate information most relevant to thesituation;” 70% of participating controllers marked itas very or extremely important.Dynamic Visual-Spatial

was dened as the ability “to interpret the movement of

objects in space.” For example, cab controllers observe themovement of aircraft and vehicles in, on, and around theairport. About two-thirds (68%) of cab controllers markedthis ability as very or extremely important. Cab controllersconstruct a representation of the dynamic traffic situationby using these abilities.

At the same time, cab controllers also identify prob-

lems such as an immediate or possible loss of separation. While Figure 7 suggests a sequence of cognitive opera-tions, in fact, problem identication and solving occurssimultaneously with dynamic comprehension. Severalabilities are grouped under the general heading of problemsolving, for expositional purposes only. Te constructProblem Identication (Solving) forms the core of thisset of abilities. Nickels et al. dened this as the “ability toidentify a potential or existing problem and to identify thevariables used in solving the problem.” A large majority(88%) of terminal controllers rated this ability as veryor extremely important to job performance. Reasoning,dened as the “ability to apply available information inorder to make decisions, draw conclusions, or identifyalternative solutions,” is another aspect of problem solv-ing; 87% of terminal controllers rated this as a very orextremely important ability. In most cases, a controllerselects a learned procedure or rule to apply to the situationat hand. Te 1995 job/task analysis termed this Rule Ap-plication, and 82% of terminal controllers rated this as avery or extremely important ability. Deciding which ruleto apply implies conditional, logical “if-then” reasoning.For example, if the departing aircraft is “heavy” (such as a

Boeing 747), then the next departure must wait 3 minutesbefore departing to ensure safe separation from any waketurbulence generated by the departing 747. Sometimes,however, a unique or unusual situation arises for whichexisting procedures or rules don’t apply or simply don’texist. Some degree of Creativity, dened as the “abilityto identify new or novel solutions to potential problems

when existing or established solutions no longer apply,”might be required. More than two-thirds of the controllers(69%) rated this aptitude as very or extremely important.

Te next group of aptitudes, for explanatory pur-poses, relates to the notion of thinking ahead. Air trafficcontrol is very future-oriented: What might happen, at atime horizon measured in minutes from now, is impor-tant; what has happened is largely irrelevant. Controllerssometimes describe this as “being ahead of the problem.”Tree aptitudes are grouped here for explanatory purposesonly: Projection; Tinking Ahead; and Planning. Tinking

Ahead was dened in 1995 as the “ability to anticipate orrecognize problems before they occur and to develop plansto avoid problems. Tis includes thinking about whatmight happen.” Almost all (93%) controllers rated this asa very or extremely important aptitude. Projection has a



18

somewhat different sense as it was dened as the “abilityto translate material into a visual representation of what

will occur in the future.” For example, a cab controllermight see where two aircraft are in relation to each otheron two taxiways and the end of the departure runway, andthen by Projection, develop an internal representation of

where the two aircraft will be in two or three minutes. Most

(86%) controllers indicated this was a very or extremelyimportant aptitude to doing the job. Finally, Planning

was dened as the “ability to determine the appropriatecourse(s) of action to take in any given situation.” Tisaptitude is very closely related to the abilities groupedunder the “Problem-solving” umbrella. However, thefocus of “problem-solving” is the present, while the focusof Planning is the future. As might be expected, nearly all(93%) controllers rated Planning as a very or extremelyimportant aptitude.

Tese aptitudes are used in a dynamic setting, oftenrequiring the controller to appear to be doing two ormore activities at once. Regardless of the technical nice-ties in the denition of “multi-tasking” or “time-sharing”as being either truly simultaneous activities or (merely)rapid attention-shifting between activities, controllers arerequired to perform multiple activities in very short timeperiods. From an observational perspective, controllersoften seem to be doing two things at once in the towercab. For example, the Ground controller might be talkingon the radio, issuing a clearance, while also marking oneor more ight strips, or perhaps re-sequencing an arrayof ight strips. As shown in Figure 7, the ability to multi-

task overlies the input-process-output model for controllerabilities. Te 1995 job/task analysis used the term “ imeSharing,” which was dened as the “ability to performtwo or more job activities at the same time.” Some 87%of terminal controllers participating in the 1995 job/taskanalysis survey marked this aptitude as very or extremelyimportant to doing the job of a controller.

At a higher order of description, three groups ofabilities (aptitudes) –Dynamic Comprehension, Prob-lem-solving, and Tinking Ahead – at the core of thisexpository model are consistent with the construct FluidIntelligence (symbolized as Gf in the individual differencesliterature) as described in the Cattell-Horn-Carroll (CHC)model of human abilities. McGrew (2009) described Gfas “Te use of deliberate and controlled mental opera-tions to solve novel problems that cannot be performedautomatically.” Example mental operations encompassed

within Gf include comprehending implications, problemsolving, transforming information, generating and testinghypotheses, identifying relations, extrapolating, inductiveand deductive reasoning (McGrew). In other words, basedon the 1995 job/task analysis, Gf is central to the humanabilities (aptitudes) required of air traffic controllers.

Te remaining abilities (aptitudes) also can bethought of as providing a framework or context forcontrolling air traffic. Tese abilities have more to do

with person-job and person-environment “t” than thetechnical work itself. Nonetheless, controllers rated theseabilities as very or extremely important to the job. Terst set has to do, for lack of a better descriptive label,

with a controller’s cognitive style. Like pilots, controllersmust continuously monitor, evaluate, and, if necessary,change their behavior in response to their operationalenvironment. Self-awareness was dened as the internalawareness of one’s actions and attitudes – and limitations.

About three-quarters of controllers (77%) marked this asa very or extremely important aptitude. Self-monitoring/Evaluation is a closely related aptitude, dened in the 1995analysis as the ability and, importantly, willingness to checkone’s work, evaluate the effectiveness of decisions, and alterperformance if necessary. Self-monitoring/Evaluation hasthe sense of doing something about or with one’s internalself-awareness. Some 73% of controllers marked this ap-titude as very or extremely important to performing the

job. Making that adjustment implies a degree of exibility.Tis is reected in the construct Flexibility (InformationProcessing), which was dened as the “ability to nd newmeanings for stimuli, to combine stimulus attributes tocome up with new and different solution protocols, andto employ exible ways of relating new information tostored knowledge.” Most (61%) controllers consideredthis to be a very or extremely important aptitude.

Te nal set of abilities, for explanatory purposes, is

related to personality and interpersonal style. One of thestriking things about controllers is their self-condence andself-assurance, as reected in this set of abilities. Overall,they have the distinct avor of surgency. While surgencycan be thought of as a facet of the broader construct ofExtroversion in the Five-Factor Model of personality, itis used more specically here as a label for constructssuch as self-condence. Self-condence was dened inthe 1995 job/task analysis as the belief “that you are theperson for the job and knowing that your processes anddecisions are correct.” A large majority of controllers (72%)marked this as a very or extremely important aptitude.

A related aptitude is aking Charge (Aggressiveness),dened as the “ability to take control of a situation—toreach out and take correct action.” Tis aptitude speaksto the willingness of the controller to “step up” insteadof “hiding from the problem.” Tis self-condence andaggressiveness is tempered or balanced by two otherabilities. Flexibility (Stability/Adjustment), dened asthe “ability to adjust or adapt to changing situations orconditions,” was endorsed by 81% of terminal controllersin the 1995 job/task analysis survey. Te other aptituderelates to the simple fact that controllers rarely work alone



19

and must cooperate with others to accomplish their mis-sion, especially in the tower cab. Working Cooperatively,dened as the “willingness to work with others to achievea common goal,” was endorsed by 79% of participatingcontrollers. Working Cooperatively also encompassedthe notion of providing assistance to another controllerif the situation warranted. Te last aptitude construct

focuses on the reaction of the individual to the perceiveddemands of the job. Te construct olerance for HighIntensity Work Situations was dened as the “ability toperform effectively and think clearly during heavy workow.” Almost all (96%) terminal controllers participatingin the 1995 job/task analysis rated this aptitude as veryor extremely important to job performance.

THE TOWER CAB IN 2018

Te next step in the strategic job analysis is to considerhow the work of the controllers in the tower cab mightchange by 2018. First, information from the FAA’s NASEnterprise Architecture (NAS EA; FAA, 2010f) is evalu-ated to determine the overall organization of the towercab in terms of working positions. Ten the workow inthe mid-term tower cab is described. Tis description isderived from available concepts of operation and use ofnew controller technologies, HI L simulation reports,and other artifacts. Key technologies such as DS s aredescribed in this sub-section. Ten, as in the analysis ofthe current tower cab, the aptitudes likely to be requiredof tower cab controllers in the mid-term are described.

Tower Cab Organization in 2018Te rst question is how the tower cab might be or-

ganized in the mid-term in terms of working positions andgeneral responsibilities. o answer this question, the mostrecent iterations of the NAS EA, service, infrastructure,and human-systems integration roadmaps were reviewed,along with the accompanying OV-5 (Operational ActivityModel, dated January 29, 2010) and OV-6c (OperationalEvent race Description, dated March, 2010) views. Terst page of the human-systems integration roadmap isreproduced in Figure 8. It appears that, as in the currentorganizational paradigm, the tower cab in 2018 will beorganized around the working positions in use today:Ground Control, Local Control, Flight Data, and Clear-ance Delivery.

Ground Control remains the linchpin for the safeand efficient ow of traffic on the airport surface in themid-term. In the NAS EA Operational Activity Model(OV-5), “Te ground controller is responsible for separat-ing aircraft and vehicles operating on taxiways and otherairport surface areas (not including active runways” (Ap-pendix A, p. 58). Ground responds to pilot taxi requests

and issues instructions. Local, in the NAS EA OV-5,“has primary responsibility for operations conductedon the active runway and must control the use of thoserunways.” Local’s responsibility “includes positive coor-dination with Ground Controller, monitor and controlof vehicles using/crossing runways” (Appendix A, p.58). Te controller in Clearance Delivery position will

be responsible for reviewing, updating, and issuing theight clearance. However, the tools used by the control-ler working Clearance Delivery will change, as discussedin more detail below. In particular, Clearance Delivery

will rely on electronic ight strips and digital, text-basedmessaging, although radio and telephone services willstill be available. Flight Data responsibilities are unlikelyto change in the mid-term. In the NAS EA OV-5, FlightData will operate interphones (e.g., dedicated telephonelines between facilities and positions), process and forwardight plan information, compile statistical data, observeand report weather information, “assist [the] tower cab inmeeting situation objects” (Appendix A, p. 59).

Tower Cab Equipment in 2018wo signicant changes in tower cab equipment

can be expected by 2018: Data communications (“Data-Comm”) and new automation in the form of DS s. Atthe same time, the number of display screens (CR andLCD) in the cab will be reduced by 2018.

DataCommTe FAA has long planned to shift from voice to

digital, data communications. For example, Wayman Deal wrote in 1962 that the “application of digital techniques toaeronautical air traffic control communications has beenunder study in the United States for more than fteenyears.” Almost ve decades later, data communications(DataComm) is a transformational technology and a keycomponent of NextGen. As described by the FAA, Data-Comm will “assume an ever increasing role in controllerto ight crew communication” and eventually becomethe predominant mode of communication between theair crews and controllers. FAA (2009a) describes Data-Comm this way:

Data Comm will provide comprehensive data con-nectivity, including ground automation message genera-tion and receipt, message routing and transmission, andaircraft avionics requirements. Data Comm will automaterepetitive tasks, supplement voice communications withless workload-intensive data communications, and enableground systems to use real-time aircraft data to improvetraffic management efficiency. Initially, data communica-tions will be a supplemental means for two-way exchangebetween controllers and ight crews for air traffic controlclearances, instructions, advisories, ight crew requests andreports. As data communications becomes the new method



20

F i g u r e

8 :

A T C T P o s i t i o n s

i n t h e

N A S E A H u m a n

S y s

t e m s

I n t e g r a

t i o n

R o a

d m a p



21

of operation, the majority of air/ground exchanges will behandled by data communications for appropriately equippedusers. Automated Data Communications technologies willsupport and enhance the Next Generation Air ransporta-tion System (NextGen). Once implemented, Data Com-munications and NextGen will enable air traffic control toissue complex clearances to a pilot and the aircraft’s ightmanagement system via electronic data transfer instead of

time consuming voice transmission.Development and implementation of this transfor-

mational technology is important to achieve the benets ofNextGen. An overview of the planned path (“roadmap”)for DataComm in the context of NextGen is illustrated inFigure 9, taken from the FAA NAS EA as of November,2010. Between 2010 and about 2015, the FAA will buildon the existing DLS used to deliver pre-departure clear-ances and the Digital Air erminal Information Service(D-A IS) to the ight deck.

Te NAS EA Communication Roadmap (Figure 9)indicates that implementation of DataComm Segment 1(DataComm1) should begin about 2012. In the A Ccab operating environment, DataComm1 “will implementdata communications capabilities that will provide newmethods for delivery of departure clearances, revisions,and taxi instructions.” Te rst two capabilities – depar-ture clearances and revisions – are extensions of currentower Data Link Services ( DLS) capabilities. Issuing taxi

instructions via digital messaging will be more complex.Te message set for digital taxi instructions has not beendened (Wargo & D’Arcy, 2011). Te Computer-HumanInterface (CHI) for creating and issuing digital taxi instruc-

tions has yet to be dened. One implementation is foundin the ower Operations Digital Data System ( ODDS;ruitt, 2006; ruitt & Muldoon, 2007, 2009, 2010).

However, voice-over-radio will remain the primarymethod for delivery of time- and safety-critical instruc-tions in the mid-term, depending on aircraft equipage( ruitt & Muldoon, 2010; Wargo & D’Arcy). Te FinalInvestment Decision for DataComm Segment 2 (Data-Comm2) is planned in 2015, according to the NAS EA(Decision Point 304 in the NAS EA), with an initialoperating capability about 2019. For the purposes ofthis analysis, DataComm1 refers to capabilities expectedby 2018, and DataComm2 refers to far-term capabilities(2019 and beyond). DataComm2 capabilities are excludedfrom this analysis.

Tower Cab DSTsower cabs have the least automation of the three

operational A C environments, imposing a signicant workload on the cab controllers. Signicant investmentshave been made in research, engineering, and develop-ment to address operational shortfalls. Te work on tower

cab automation has been dominated by three technicalapproaches: 1) operations research; 2) integrated informa-tion displays; and 3) shared situational awareness. Whilethere is conceptual overlap in the three approaches, theygenerally have been undertaken by relatively discrete andindependent groups. Te operations research approach hasbeen dominated by researchers, academics, students, and

organizations affiliated with the Massachusetts Instituteof echnology (MI ). A key concept that emerged outof the operations research work is the notion of the De-parture Planner (Anagnostakis, Idris, Clarke, Hansman,Odoni, & Hall, 2000; Feron et al., 1997). Integratedinformation displays have been the focus of FAA research( ruitt, 2005). Te key concept from the display-centeredresearch is the electronic representation of ight strips forthe tower. Te shared situational awareness line of inquiryis dominated by NASA and associated researchers. Tisline of research produced the Surface Movement System(SMS), which has undergone trials in simulations and atDFW, Memphis International (MEM), and LouisvilleStandiford (SDF) airports (Lockwood, Atkins, & Dorighi,2002; Atkins, Walton, Arkind, Moertl, & Carniol, 2003;National Aeronautics & Space Administration, 1999a,199b; Walton, Atkins, & Quinn, 2002).

In recent years, these three lines of research havecoalesced around a set of ve “capabilities” for the towercab: 1) airport conguration; 2) departure routing; 3)runway assignment; 4) sequencing and scheduling; and5) taxi routing. Each “capability” consists of a bundleof functional requirements. For example, the airport

conguration capability encompasses four functions inthe mid-term: airport planning information; stochasticanalysis (of the impact of a proposed conguration onairport ow rates); coordination with the airport author-ity; and conguration advisories for multiple airports ina single metroplex (for example, DFW and Dallas Love(DAL)) (Morgan, 2010).

Te ower Flight Data Manager ( FDM; System706 in the NAS EA; FAA, 2010f; Nene & Morgan, 2009)is intended to provide the automation platform on whichthese capabilities will be hosted. Conceptually, FDMconsists of an interface to data sources such as radars andthe Enhanced raffic Management System (E MS), aFlight Data Manager (FDM), Surveillance Data Manager(SDM), and a suite of DS s (Nene & Morgan, p. 1-2).

FDM will feature (user) congurable displays. owercontrollers will interact with the displays and DS s throughan as-yet unspecied computer-human interface (CHI).Prototypes of some display and DS concepts have beensubject to limited HI L simulations, but overall, theyare largely in the concept exploration and developmentphase of the FAA’s acquisition cycle, with key investment



22

F i g u r e

9 :

D a

t a C o m m

i n t h e

N A S E A C o m m u n

i c a

t i o n

R o a

d m a p

( a s o

f J a n u a r y ,

2 0 1 2 )



23

decisions yet to be made. Te FDM acquisition programis in two phases. FDM Phase 1 ( FDM1) will

…integrate the Airport Resource Management ool(ARM ), ower Data Link Services ( DLS), SurfaceMovement Advisor (SMA), and Airport Movement AreaSafety System (AMASS) functions. erminal will determinethrough trade studies the means of integrating four addi-tional legacy systems: Flight Data Input Output, ElectronicFlight Strip ransfer System (EFS S), Advanced ElectronicFlight Strips (AEFS)/Electronic Flight Strips (EFS), andDeparture Spacing Program/Departure Flow Manage-ment (DSP/DFM), the latter of which will reside as a newcomponent (known as the Integrated Departure/ArrivalCapability) in either FDM or FMS. (https://nasea.faa.gov/system/main/display/706)

FDM Phase 2 ( FDM2) will deliver “Full DecisionSupport ools (DS ) with DLS and SAIDS Integration”(https://nasea.faa.gov/decision/main/display/198/tab/detail). SAIDS (the Systems Atlanta Information Display

System) is also known as the Integrated Display System(Version 4) and is installed at 390 facilities, including 25of the 30 largest airports (“Core 30”; FAA, 2011).

FDM1 and FDM2 are depicted on the NAS EA Automation Roadmap (Figure 10). Te Final InvestmentDecision for FDM1 (as dened by the FAA’s AcquisitionManagement System (AMS) (FAA, 2010c)) will not bemade until late 2012 (Decision Point 115), with capabili-ties entering the NAS in the period between about 2013and 2016 or 2017. A system schedule (e.g., describingactual delivery, installation, and commissioning at eldfacilities) is not available through the NAS EA. Te Fi-nal Investment Decision for FDM2 will not be madeuntil 2014. Te Final Investment Decision determines

whether to move forward with a particular “investmentopportunity” to “solution implementation” (AMS 2.4.4).Te Automation Roadmap indicates that FDM2 willspan the period of about 2016 through 2019, that is, themid-term focus of this analysis.

For purposes of this analysis, each proposed surfaceDS capability and its concept of use is briey summa-rized. Te working position most likely to use a givencapability is identied. Te use of these capabilities is

then described, based on the available information suchas NAS EA operational event threads (“OV-6c” scenarios)and simulations. Te overall impact of the mid-termcapabilities on cab controller functions, as described byKrokos et al in their 2007 update, is then assessed. Givenan updated description of controller functions, aptituderequirements are then inferred from available informationand compared to the baseline requirements.

Airport Conguration DS . 5 Airports have manydiscrete structural and operational elements, such as thefamiliar passenger terminal buildings, aircraft hangars,expanses of concrete around those buildings and hangars

(known as aprons, ramps, and alleys), taxiways fromterminals to runways, and runways. Just 17 (6%) of 262FAA-towered airports have a single runway, 111 (42%)have two runways, 92 (35%) have three runways, and

just 42 (16%) have four or more runways. A commonconguration is two (nearly) parallel runways based onthe prevailing winds; some have a third runway crossingthe others at an angle. Te tower, in cooperation withthe airport authority, the aircraft operators (such asairlines), servicing RACON, and traffic management,designates which runways and taxiways are to be usedfor various operations. Generally, this designation, orairport conguration, is largely based on past experienceand practice, perhaps codied into a set of more-or-less“standard” congurations in routine use. Events suchas a shift in wind, scheduled runway maintenance (toremove the rubber that builds up in the touchdown zoneof a runway, for example), and unexpected closures of

a runway or taxiway (due to a disabled aircraft, for ex-ample) might dictate a change from one conguration toanother. At airports with a lower tempo of operations andsimpler layouts, such a conguration might be relativelyeasy to implement. However, conguration changes atmajor hubs, with their streams of arrivals, departures,and taxiing aircraft, pose a signicant challenge to thetower. Te timing of a change can be especially important.Current tools available to supervisors include the AirportResource Management ool, elded at 15 facilities (El-Sahragty, Burr, Nene, Newberger, & Olmos, 2004), andthe Surface Movement Advisor (SMA) legacy system at16 airports. However, most FAA towers have no automa-tion or computerized support for assessing the merits ofdifferent congurations.

Te Airport Conguration DS is intended toaddress this operational shortfall. Te tools within thiscapability will provide assistance for setting up, assess-ing, and changing the conguration of an airport. Teprimary users of the Airport Conguration capabilityare the tower manager, tower supervisor on duty, and inlarger facilities, the raffic Management Coordinator;controllers at the Ground, Local, Clearance Delivery,

and Flight Data positions are not intended to be userson a routine basis, except if serving as the Controller-in-Charge.6 Te mid-term concept of use for this capabilityincludes scheduling the reconguration, optimizationof the proposed conguration using stochastic analysis,and communication of the reconguration to users andstakeholders via data exchange (Dziepak, 2010; Morgan,2010). Te capability provides information on departurex loadings, traffic management initiatives, and arrival/departure rates and future demand to the ower Supervisorand/or the raffic Management Coordinator (Sekhavat,2009). Te primary impact on tower cab controllers



24

F i g u r e

1 0 :

T F D M

i n N A S E A A u

t o m a

t i o n

R o a

d m a p

( J a n u a r y ,

2 0 1 2 )



25

comes in executing the reconguration as directed by the

supervisor. For example, Ground might need to issue aseries of new taxi instructions to aircraft in the departurequeue to direct them from the north to the south end ofthe departure runway because of a wind shift (from southto north, as sometimes happens at DFW with winterstorm fronts). While there is clearly additional workloadassociated with a reconguration of the airport, the overallactivities performed by controllers in the cab remain thesame. Controllers will still scan their areas of responsibilityon the airport surface, monitor movement on the surface,assess separation, manage sequences of departures and ar-rivals, issue control instructions, mark ight progress strips,and manage position resources. Terefore, the AirportConguration capability has minimal impact on the du-ties, responsibilities and roles of the tower cab controllers.Teir workload, however, is likely to temporarily increaseduring the actual execution of the conguration change.

Departure Routing DST. Te Departure RoutingDS provides ight-specic assessments of the availabilityof (led) departure routes, given weather conditions andtraffic ow constraints. For example, the frequently useddeparture routes out of the New York metropolitan area(from JFK, LGA, and EWR) for south- and west-bound

aircraft are geographically concentrated (Figure 11). Con-vective (and other) weather systems can require greaterspacing between aircraft on some routes. Weather canalso close routes entirely. Te Departure Routing capabil-ity integrates weather, traffic, and airspace information toassist air traffic managers and ight operators in makingtraffic ow management decisions (Kell, Masalonis, Stelzer,

Wanke, DeLaura, & Robinson, 2010). Te DepartureRouting capability provides raffic Management Coordi-nators and ight operators with the capability to answerquestions such as “Where is the weather or congestion?”and “How will a traffic management initiative or re-route

of specic ights avoid the weather or mitigate conges-

tion?” (Jackson, 2010; see Figure 12).Te Departure Routing DS extends the basic func-tionality of the Route Availability Planning ool (RAP )currently in use by air route traffic control centers in theupper midwest and northeast, New York metropolitan areaairports, the New York RACON (N90), and several ightoperators (Kell, et al.).Departure Routing will provide agraphical depiction of departure routes with an overlay of

weather information. It provides tools to MCs to identifyintersections of routes and specic ights with adverse

weather or congestion and to evaluate route alternatives(Sekhavat, 2009). Te primary users of Departure Routing are raffic Management Coordinators and ight operators.Te primary impact on tower cab controllers will be indelivering route amendments to pilots to implement DS -generated solutions. Route amendments are an example of

workload-intensive voice communications that might besupplanted by DataComm. But overall,Departure Routing does not change the activities, sub-activities, tasks, roles,and responsibilities of the tower cab controllers.

Runway Assignment DST. A key responsibilityfor Ground Control is the assignment of departures torunways. ower procedures generally require designating

which runway(s) will be used for departures, arrivals, andmixed operations. At simpler airports with one, two, andeven three runways with lighter traffic, assignment of depar-tures to a runway is a relatively simple decision. However,at large, complex and busy airports, runway assignmentis complex and can have substantial consequences on theairport departure rate and departure delay. Ground mustconsider factors such as the destination, initial departurex (marking the beginning of the intended route), numberand types of aircraft in the queue for each active departurerunway, route of ight, and operator preferences. Forexample, in the “South Flow” conguration of DFW

Figure 11: Illustration of air traffic routes from New York metro area (Source: MIT Lincoln Laboratory)



26

(Figure 3), east-bound aircraft generally depart from 17Rand 17L (and turn left on departure), while west-boundaircraft depart from 18L (and turn right on departure).

At present, departures are assigned to runways byGround, based on codied procedures, rules-of-thumb,past practice, and A CS experience and judgment. Asa consequence, this manual process is characterized as

resulting in inefficiencies in use of airport resources suchas the runways, especially at times when demand exceedsthe capacity (FAA, 2009b). Provision of a DS to assignaircraft to runways is one way to address this operationalshortfall. Te mid-term Runway Assignment capability willassign departures to runways based on rule sets, such asdeparture xes and destinations for load balancing. Es-sentially, this capability computerizes existing StandardOperating Procedures and practices. By the mid-term,the Runway Assignment capability will also display anyadded delay cost for not using the recommended runway(Dziepak, 2010; Morgan, 2010), but responsibility for the

actual assignment of an aircraft to a runway will reside with the controller as part of his or her responsibility formanaging the departure queue and sequence. Te con-troller can accept, modify, or ignore the recommended

runway assignment appearing on the departure electronicight strip (Figure 13).

Te interface for assigning a runway has not beenspecied as yet. Current concepts are based on electronicight strips arranged in bays on a touch-screen display,

where the bays correspond to operational phases such aspending, departures, and arrivals (see Stelzer, 2010, Ap-

pendix D for an example, and Figure 14). Te controllerselects a strip by touch or mouse click. In the MI REsimulation, the selected strip “opens up” and the eldscan be selected and edited. Runway assignment might bemade via a drop-down list or direct data entry. However,these details have not yet been fully worked out and arestill in concept development and exploration. Te “peakdepartures” and “peak taxi demand” scenarios in the FAAEA OV-6c scenarios refer to runway assignment as partof the development of an “integrated and collaborativeschedule” for airport operations.

Scheduling & Sequencing DST. Te Scheduling &Sequencing DS proposed in the mid-term is intendedto derive a schedule of departures, given traffic owmanagement constraints, runway assignments, aircraftreadiness, and wake turbulence mitigation. Tere is no

Figure 12: Overview of graphical interface for Route Availability Planning Tool (RAPT) (Source: MITLincoln Laboratory http://www.ll.mit.edu/mission/aviation/wxatmintegration/rapt.html)

Figure 13: Example electronic flight strip for a departure assigned to Runway 17R (Source:MITRE CAASD MTR100188, p. 2-7)



27

automation support for the Ground controller at pres-ent to develop a schedule or sequence of aircraft; as aconsequence, controllers work with the ights at handin a very tactical approach, generally on a “First Come,First Served” basis in accordance with the FAA Air rafficControl procedures order (specically, Paragraph 2-1-4;

FAA, 2010b). Tis strategy allows the Ground controllerto provide surface control services in an equitable mannerto the various classes of users. TeScheduling & SequencingDS is intended to provide recommendations to Groundas to which aircraft to take next for taxi instructions. Inthe mid-term, the order of service might be determinedby ight prioritization rules other than “First Come, FirstServed” (Joint Planning & Development Office, 2011).

For example, an aircraft with a Flight ManagementSystem that can receive and execute a digital taxi instruc-tion (D- AXI) might be given priority in the scheduleover a similar aircraft without that capability. Te betterequipped aircraft would be sequenced ahead of the otheraircraft in the departure queue. However, schedulingand sequencing algorithms are the subject of on-goingresearch and modeling. A key problem in the develop-ment of surface scheduling and sequencing algorithms isthe inherent uncertainty of surface operations (Brinton,Krozel, Capozzi, & Atkins, 2002a, b; Brinton & Atkins,2008; Atkins, Brinton & Jung, 2008; Rapport, Yu, Grif-n, & Daviau, 2009).

Tere are several sources of uncertainty in surfaceoperations that will impact the stability and efficiency of

the DS proposed solution. Te rst source is that notall aircraft are required to le a ight plan, so some areunknown to the automation system. Even a small airplanecan technically y from and to a major airport without aight plan, provided the airplane has certain equipment,the pilot can afford the airport fees, and the ight is con-

ducted under visual ight rules (VFR). As shown in Figure15, the vast majority of operations at the 30 large “core”airports are conducted under Parts 121 and 135, mostlikely with led Instrument Flight Rule (IFR) ight plans.For example, 99% of over 614,000 operations at DEN in2009 were conducted under Parts 121 and 135 accordingto historical data from the FAA’s erminal Area Forecast(FAA, 2010h). Tese ights, with led ight plans, wouldbe taken into account by the Scheduling and SequencingDS . Just 1% of operations at DEN were conducted underPart 91 or military regulations, representing over 3,800operations a year, or roughly 100 a day. At least someof the Part 91 and military operations involved ights

without ight plans. Tus, they would be unknown tothe DS and would not be incorporated automaticallyinto the computer-generated scheduling and sequencingsolution. At other core airports, even larger proportions ofoperations were conducted under regulations other thanPart 121 and 135 according to FAA terminal operationsdata. For example, about 18% of the 246,738 loggedoperations at Chicago Midway (MDW) involved ightsoperating under Part 91 or military regulations, averagingabout 100 a day. Some number of these ights would have

Figure 14: Electronic flight strip display used by MITRE in Conformance Monitoring human-in-the-loopsimulation (Stelzer, 2010, p. 2-8)



28

to be made known to the Scheduling and Sequencing DS through an as-yet unspecied mechanism.

Te tower controllers, on the other hand, can observethe ights directly and integrate them into operations. Tesecond source of uncertainty that would impact schedul-ing and sequencing on the airport surface is variance inestimating gate turn time for air carrier ights (as noted inFigure 15, the majority of ights at the 30 core airports).Te lower bound for the error in estimating turn-timeis about ve minutes; the average error is closer to 15minutes (Carr, 2004).

urn-time directly impacts gate availability and arriv-als in the taxi-in phase of operations. Developing schedulesand departure queues (sequences) that are robust to theuncertainty in turn-time is challenging (Carr). Te thirdsource of uncertainty in surface operations is in aircraftmovement, engendered by two factors: the physics ofaircraft movement; and pilot reaction time and controlinputs in response to A C instructions (Williams, Hooey,& Foyle, 2006). A Scheduling and Sequencing DS wouldneed to be robust enough to accommodate at least these

three sources of uncertainty or “noise” to avoid excessivere-planning (Carr).

Yet surface operations scheduling and sequencingalgorithms developed to date assume deterministic (thatis, known and xed) push-back, call-up, taxi times, aircraftmovement, and pilot reaction to instructions. For example,the NASA Spot Release Planner, a scheduling application,is characterized as a “deterministic optimization problem”(Jung, Hoang, Montoya, Gupta, Malik, & obias, 2010).Te assumption of deterministic, known, or xed times fordifferent key events, particularly in departure taxi opera-tions on the airport surface, leads to “…a brittle decisionsupport capability that provides unstable modeling resultsdue to small variations in inputs, and/or decision supportrecommendations that end up being much less efficientthan planned due to these uncertainties” (Brinton &

Atkins, 2008, p. 1). Assuming that a stable and efficient solution can

be developed by the Scheduling and Sequencing DS(for example, through a stochastic algorithm (Brinton& Atkins)), it will be presented to Ground Control as a

Figure 15: Ratio of Part 121 & 135 operations to total itinerant operations (Parts 121, 135, 91 & military)

based on the 2009 Terminal Area Forecast (TAF)



29

recommendation. Ground retains the overall responsibilityfor scheduling and sequencing aircraft onto the taxiways,and can accept, reject, or modify the recommendation(Dziepak, 2010; Morgan, 2010). Te CHI for presenta-tion of and action on the recommended schedule andsequence has not been positively dened for the mid-term.One approach might be through the electronic ightstrips, in which the schedule and sequence are implicitin the ordering of the strips in the departure bay(s). Inthis approach, doing nothing to change the order of strips

would constitute acceptance of the automation’s recom-mendation, while moving a strip (through a “drag & drop”method, for example) would represent a modication.It is not clear how the controller would reject the DSrecommendation. Overall, it is likely that a Schedulingand Sequencing DS will change the details of what thecontroller looks at in the cab on a display, but the functionperformed by the controller will not dramatically changein the mid-term with the introduction of a Schedulingand Sequencing DS .

Taxi Routing DST. In the mid-term, automation will also generate a recommended or advisory taxi routefor a given aircraft, based on factors such as pre-established

routes, congestion, and user preferences. Te Ground con-troller can accept, reject, or modify the recommended taxiroute via an (as yet) unspecied CHI. rials of automatedtaxi routing (“D- AXI”) have been optimistic about theconcept but cautious about the details of implementation,particularly with reference to the CHI and required localadaptations. Te European Airport Movement Managementby A-SGMCS Part 2 (“EMMA2;” Jakobi, Porris, Moller,Montebello, Scholte, Supino, et al., 2009; eutsch, Scholte, Jakobi, Biella, Gilbert, Supino, et al., 2009) project simpli-ed the CHI by integrating taxi routing with the electronicight data display. ODDS ( ruitt & Muldoon, 2010)takes a similar approach, as shown in Figure 16, as does theSurface Decision Support System (SDSS; McGarry & Kerns,2010). However, a cautionary note was sounded with regardto automated taxi route generation (Jakobi et al., 2009):

A highly sophisticated and responsive routing function,that is able to cope with all operational circumstances inorder to provide the A CO [air traffic controller] withthe right taxi route, whenever called upon, is an absolutemust to keep manual interaction to a minimum and to getthe A COs acceptance to transmit taxi routes by AXI-CPDLC (p. 17).

Figure 16: Example future electronic flight strip bay (left) and airport surface display (right) (photocourtesy of Todd Truitt, FAA Technical Center)



30

What constitutes a “highly sophisticated and re-sponse routing function” is the subject of continuingresearch and development. As with the Scheduling andSequencing DS , solution stability, (physical) feasibility,and operational acceptability are important criteria. More-over, air traffic procedures for the use of the taxi routingDS will be required, with modications to the FAA Air

raffic Procedures order (FAA, 2010b) and the Airman’sInformation Manual (AIM). Procedural issues that mustbe addressed in parallel with development of the axiRouting DS include under what conditions Ground

will (mandatory) and might (discretionary) accept therecommended taxi route, amend (modify) it, and reject it.

If Ground rejects the rst proposed route, it isunclear if the system will generate another route or if thecontroller will be prompted to create an independentsolution. In addition, some research suggests that a rout-ing tool will re-plan about every 10 minutes as eventsplay out on the surface and that re-computation of thetaxi routes can take about two minutes (Balakrishnan &

Jung, 2007). Re-planning might also be triggered whenthe controller rejects a proposed taxi route. Te sensitivityto perturbations and time required for computation arebeing addressed in intensive research and modeling byorganizations such as MI RE CAASD, Mosaic A M,and ME RON Aviation.

If, and only if, stable, achievable, and efficient routescan be generated by a “sophisticated and responsive” al-gorithm, what is left to the controller, particularly at theGC position? First while the taxi route might be uplinked

directly to aircraft that are properly equipped, the actualinstruction to move will still be issued by the humancontroller working Ground by voice (Morgan & Burr,2009, p. 56). It is worth noting that not all aircraft callingthe tower will be in the system with a led ight plan andthat some might le just before calling the tower for taxiinstructions. Te Air raffic Procedures order requires theFAA to provide taxi and control instructions to all aircraftin the movement area. Since the axi Routing DS willnot be aware of ights without a led ight plan, it cannotgenerate a route for such ights. It is not clear how thisoperational fact will be solved. Te most likely solutionis manual controller intervention.

Moreover, because of the inherent stochastic (un-certain) nature of surface operations as noted previously,Ground will not be able to simply default to pressingthe “Accept” or “Send” button for a proposed taxi route

without at least some (quick) evaluation. Te controller working Ground will have to assess the safety of a pro-posed taxi route in light of current and future conditions.

Without the axi Routing DS , this evaluation is of thecontroller’s own plan relative to current surface traffic andconditions. With the axi Routing DS , the evaluation

is of the automation’s proposed taxi route, to ensure thatit is conict-free and complies with any airport-specicconstraints. Te controller then issues the taxi instruc-tion by selecting “Accept axi Route” (or its functionalequivalent) and, presumably, DataComm transmits theinstruction to the aircraft Flight Management System.

Alternatively, Ground Control might say the taxi instruc-

tion over the radio if there are time and/or safety issues.Tus, the overall functions of the Ground in issuing taxiinstructions does not change substantively; an additionaldata input as an advisory is presented, but the controllerretains decision-making responsibility – and liability – forthose decisions.

However, taxi Conformance Monitoring, a subsetof the axi Routing DS capability, might have moreimpact on the Ground and Local controller than any ofthe other mid-term tower cab capabilities. As noted byDziepak (2010) and McGarry and Kerns (2010), thereare no alert systems for detecting taxi route deviationsat present; the NAS relies on controller scanning of theairport surface to detect conformance problems. Te

Airport Movement Area Safety System (AMASS) is anadd-on to ASDE-X. AMASS predicts collisions betweentracked objects but does not monitor conformance to taxiinstruction(s) (Northrop Grumman Norden Systems, Inc.,Performance echnologies International, Inc., FAA Airraffic raining (A X-100), & FAA Academy Air rafficraining Division (AMA-500), 2004).

Te mid-term Conformance Monitoring capabilitymight supplement controller perception. HI L simula-

tion suggested that conformance monitoring was helpfulto controllers in detecting pilot deviations: Controllersdetected 100% of pilot deviations with conformance moni-toring, and just 73% without monitoring (Diffenderfer &Morgan, 2010; McGarry & Kerns, 2010; Stelzer, 2010).Te research on the speed with which a controller detectsa deviation with and without conformance monitoringis equivocal. In one HI L simulation, the controllers

were no faster in detecting deviations with than withoutconformance monitoring (Stelzer). In the second HI Lsimulation, the controllers were faster (McGarry & Kerns).Both simulations demonstrated that there are signicantissues in determining how much of a deviation will trig-ger an alert, particularly for “hold short” instructions.Te Conformance Monitoring capability relies upon theexistence of a ight plan with current trajectory and intent(taxi instruction) data. Such data would be unavailablefor aircraft without led ight plans in the system, andthe cab controllers would be required to monitor thoseaircraft in much the same way as today. Moreover, keepingthe system updated with current intent data, particularlyif Ground modies a taxi instruction, could increasecontroller workload, offsetting any reductions gained



31

through use of the Conformance Monitoring capability(McGarry & Kerns). Overall, the mid-term ConformanceMonitoring might be a supplement to human perceptionin 2018. But it is likely that controllers will still have toscan the airport movement area and runways. Terefore,the functions of monitoring the ground situation andcontrolling aircraft movement remain the controllers’

responsibility in the mid-term.

ATCT Cab Workow in 2018Te workow within the A C cab in the mid-term

timeframe is described next. Tis provides the basis forcomparing and contrasting mid-term to current control-ler behavior. First, the activities required of the tower cabcontrollers in handling a single IFR Part 121 nominaldeparture with a led ight plan are described. Te de-scription is based on two sources: (1) the OV-6c scenariosfor peak taxi and peak departures in the NAS EA (FAA,2010f); and (2) concepts of operations and use deliveredby the MI RE Center for Advanced Aviation Systems De-velopment (CAASD) (Nene & Morgan, 2009; Sekhavat,2009; Morgan & Burr, 2009). Tis section closes withbrief discussion of multiple operations, mixed equipage,and changes in the operating paradigm for the mid-term.

Nominal DepartureStandard or “canned” ight plans for IFR Part 121

departures are often led months in advance with the FAA,and are activated by the AOC (also referred to as the FlightOperations Center (FOC)). Te airline activates the ight

plan at some point before the scheduled departure time viaFAA-AOC automation. raffic ow management automa-tion then “works” the ight plan based on user preferences,

weather, traffic, and other constraints that might apply tothe specic ight. While details are not available as yet,at some point before the scheduled or planned departuretime, the ight operator updates the Flight Data Object,the repository for the data for that specic ight, with theestimated departure time and departure gate (Morgan &Burr, 2009). Te surface automation takes (receives) theFlight Data Object and develops a proposed sequence andschedule for the departure and, possibly, runway assign-ment and taxi routing, taking into account the airportconguration, traffic management initiatives, weather,congestion, and other factors. Te ight plan is dynamicand is updated before the scheduled departure to reectnew data, weather conditions, and traffic constraints. TeScheduling and Sequencing DS builds an “integratedcollaborative schedule” (Morgan & Burr, p. 48 & 52) fordeparting aircraft, including this specic ight. In parallel,the Runway Assignment DS tentatively allocates the ightto a departure runway based on procedures, constraints,and congestion. Given the expected departure runway,

airport conguration, and the “integrated collaborativeschedule,” the axi Routing DS identies the set of pre-dened taxi routes applicable to the ight (for convenience,ight ABC432). Te proposed solutions developed by theDS s are updated as the surface traffic situation evolvesover time. At this point, nothing for this particular ight(ABC432) is displayed to the controllers working the

Ground or Local control positions in the tower cab. About an hour before the scheduled departure time,

the airline updates the system with new or changed in-formation, such as a gate change or a slip in the planneddeparture time for ABC432. Te surface automation up-dates the sequence and schedule, runway assignment, andtaxi route in response. At this point, the ight informationis available to the supervisor, tower raffic ManagementCoordinator (if staffed), and to the ight operator. Teight operator’s Ramp Control might use the CollaborativeDeparture Queue Manager (CDQM; Brinton, Lent &Provan, 2010; Diffenderfer, 2010) to determine the timeand sequence for push-back of different ights, includingthe present one, based on the operator’s procedures, pri-orities, preferences and the scheduled “spot time” for theight. Some electronic negotiation with the FAA might berequired through CDQM or other external data interface.

Anywhere from an hour to perhaps 15 to 20 minutesbefore the scheduled departure time, depending on localpractices, the controller working Flight Data or ClearanceDelivery positions (or the combined positions) in the cabrequests the ight plan for ABC432 via the cab controller

workstation. Alternatively, the data for the specic ight

might be “pushed” to the FAA Flight Data and ClearanceDelivery positions and to the operator Ramp Control(Audenaerd, Burr, Diffenderfer, & Morgan, 2010). TeFAA Flight Data and/or Clearance Delivery controllersand operator Ramp Controller review the ight data,presented as an electronic ight strip. Any changes inthe route of ight (the “4D trajectory” in NextGen), dueto information not known to the system or other localreasons, are made by the Flight Data/Clearance Deliverycontroller via an as-yet unspecied workstation CHI.Ten Flight Data/Clearance Delivery issues the departureclearance via DataComm (assuming the aircraft is properlyequipped) (Step 4, Scenario 7 “Peak Departures,” OV-6cdated December 2010). Te departure clearance includesthe route of ight and clearance limit for ABC432, anyrestrictions, and other required or pertinent information.Te interface used by the Flight Data/Clearance Deliverycontroller in the mid-term might be similar to the cur-rent DLS interface under DataComm1. Te aircraftacknowledges the departure clearance transmission; ifacceptable, a “WILCO” (Will Comply) digital messageis sent to the Flight Data/Clearance Delivery position.Te surface automation uses this exchange to update the



32

ight data for ABC432 with a “(departure) clearancedelivered” message; this action transfers the ight planfor ABC432 to the Ground Control’s “pending departurelist” (Audenaerd et al., p. 4-7). Te aircraft is still at thedeparture gate when the DCL is sent by the FAA andacknowledged by the pilot.

Once “buttoned up,” the aircraft calls the company

Ramp Control for push-back from the departure gate inaccordance with the “integrated collaborative schedule,”Ramp Control has access to the departure clearance, therequired spot time, and runway assignment via externaldata exchange. Te Ramp Control instructs ight ABC432to push back from the gate and taxi to the designated“spot.” Ramp Control enters the actual push-back timefor ABC432; that time is propagated through the externaldata exchange to the FAA automation, and the FlightData Object is updated, including expected runway as-signment and proposed taxi route. In the mid-term, thispreliminary taxi route constitutes the initial 2-dimensional(2-D) surface trajectory to be used by the ConformanceMonitoring capability.

As noted above, ABC432 is now in the GroundControl’s “pending departure list.” Te exact manner ofpresentation or display for the “pending departure list” hasnot been specied. However, it is seems likely that it willconsist of an array of electronic ight strips. Te sequenceand schedule of departures might be implicit within theordering of strips. Te electronic ight strip arrays might

also be split by departure runway and perhaps taxiway ortaxi route, as well as status (“pending” versus “active”).Screen shots in reports and briengs all suggest layouts ofstrip bays that reect the physical queues and runways. Teelectronic ight strip display used by MI RE in a human-in-the-loop simulation is illustrated in Figure 17 (Nene& Morgan, 2009). In that study, controllers interacted

with strips through a touch screen and keyboard; voicerecognition is an unlikely technical possibility, given theaccuracy required and time constraints. It might be the casethat failure to re-order the sequence of strips constitutes(passive) acceptance of the automation’s solution. In anycase, the controller working the Ground Control positionreviews the proposed sequence and schedule as presented

Figure 17: Example possible configuration of departures flight data display (Source: Nene & Morgan,2009, p. 5-5 (Figure 5-3, Credited to William Hall, FAA))



33

in the array of strips. However, the criteria by which theproposed sequence and schedule of “pending” departures

will be evaluated by the controller are not described.Flight ABC432 taxis to the designated “spot,” arriving

at the required time, and calls Ground on the designatedfrequency: “ZYX ground, ABC432 at spot #, Ready fortaxi.” Te most current concept of use indicates that in

response, the Ground Control “updates” the “system”to indicate that the aircraft is in active taxi status. Temethod by which Ground updates the system has notbeen explicitly described. Whether it will be somethinglike dragging an electronic ight strip from the “pendingdeparture list” to the appropriate queue or highlightingthe strip and pressing a physical or virtual “Accept” or“In axi” button, the key point is that an affirmativeinteraction with the “system” is required of the GroundControl. Additional controller actions might be requiredif the acknowledgment and taxi instruction are given viaDataComm; what those actions are will depend on howDataComm is implemented. Potentially, multiple discretephysical interactions with a display could be required ofGround for a departure, in addition to any scanning ofvisual displays and of the airport surface.

Te next step in the departure sequence is to issuethe actual taxi instruction to the aircraft via DataComm orvoice (Step 5, Scenario 7 “Peak Departures,” OV-6c datedDecember, 2010). Te proposed taxi route (generated bythe axi Routing DS ) will be displayed to Ground; thecontroller has the option to accept the proposed route,modify it, or reject it and issue a different route entirely.

Te controller might specify an ad hoc route by joiningsegments of pre-dened routes. Te specic means by

which the proposed routing is displayed to Ground hasyet to be specied. One approach might be to display theproposed route graphically, as an overlay on the “bird’s-eye”or plan view of the airport, when the aircraft call from the“spot” is acknowledged. Ground could manipulate linesegments, for example, to modify a proposed taxi route(see McGarry &Kerns, 2010, Figure 2-9, p. 2-9). Alter-natively, a text-based interface might be used, in whichthe controller types in alphanumeric strings representingintersections, taxiways, and hold short points, by editingthe electronic ight strip. Both methods might be avail-able to Ground.

In the Conformance Monitoring HI L simulation(Stelzer, 2010), the taxi route was printed in an area cor-responding to Block 9b of the standard paper ight stripfor a departure. As shown in Figure 12, the taxi route for

American 1032 was K.K7.L.EH, read as “ axiway Kilo tointersection Kilo seven, then taxiway Lima to intersectionEcho Hotel.” Te last intersection is with the assigneddeparture runway, 17 Right (the innermost runway on theeast side of DFW), at the north end of the runway. In the

MI RE simulation, this was a standard taxi route named“Outer.” In the MI RE simulation, doing nothing with astrip appears to have implied acceptance when automationgenerated the route. Ground could modify the route byselecting the strip by touch or by mouse-click. Ten anediting screen opened through which the controller couldtype in a taxi route such as “K.K8.L.EH.” Given passive

acceptance of the proposed route or entry of an alternateroute (by text or graphically), the actual taxi instruction isthen issued to the aircraft. It is unclear what the interfaceand procedural steps will be to issue a taxi instruction viaDataComm. Voice instructions are the norm today and

will be optional in the mid-term (Step 5, Scenario 7 “PeakDepartures,” OV-6c dated December 2010). Regardlessof how the taxi route for ABC432 is generated and issuedto the pilot, the “automation system” is made aware of theintended taxi route to enable conformance monitoringon the airport surface.

After acknowledging the taxi instruction, ABC432begins moving from the spot onto the assigned taxiway.Te Conformance Monitoring capability compares cur-rent aircraft position to the expected route. If an aircraftdeviates from the expected taxi route, current concepts ofoperation and use for conformance monitoring indicatethat a auditory alert is sounded and the ight strip forthe deviating aircraft is illuminated in red (Stelzer, 2010;McGarry & Kerns, 2010). In this example, ight ABC432taxis, as instructed, uneventfully towards the departurerunway. At some point, depending on local procedures,Ground instructs (by voice or DataComm) the pilot to

contact Local Control on the designated frequency, andthe aircraft is handed off to the Local controller “for take-off procedures” (Step 5, Scenario 7 “Peak Departures,”OV-6c dated December 2010). As shown in Figure 12,this might be accomplished electronically by clicking orpressing the “LC” virtual button in the far right end ofthe electronic ight strip.

Local acknowledges the call from ABC432 and issuesa “line up and wait” instruction to the ight in this simplescenario. Te pilot taxis onto the departure runway, linesup on the runway centerline, and waits for the take offclearance. After visually scanning the departure runway tomake sure it is clear, Local clears ABC432 for take-off. Asthe “line up and wait” instruction and take-off clearanceare time and safety-sensitive, it is likely that these instruc-tions will be issued by voice rather than DataComm inthe mid-term. Moreover, absent a convincing demonstra-tion that the surface and airspace situation displays areequivalent to visual operations and a corresponding changein A C procedures, Local will still need to visually scanthe departure runway by looking out the window, issuethe take-off clearance, and instruct the pilot to contact

RACON. o complete this simple illustration, ABC432



34

takes off and then ies a published Standard InstrumentDeparture (SID). As ABC432 leaves the ground, its ADS-B (Out) signal is detected and processed by RACONsurveillance. Te pilot switches to the RACON departurecontrol frequency in accordance with the published SIDor as instructed by Local. Te Local controller indicatesthat the aircraft has departed through an interaction with

the ight data display. For example, Local might highlightthe strip for ABC432 on the display and select a virtual“DEPAR ED” on-screen button. From the perspective ofGround Control and Local Control, ABC432 is historyand their attention turns to other events.

Nominal ArrivalIn parallel to this departure operation, other ights

are coming into the airport airspace and landing. Forconvenience, ight XYZ987 is arriving at the airport on arunway parallel to and outboard of the departure runwayin the preceding nominal departure scenario. Tere is ataxiway between the two runways, and another taxiwayinboard of the departure runway. Te inboard taxiwayconnects with the operator’s ramp and gates. raffic owmanagement automation exchanges data for the in-boundight with the surface automation. Te expected landingrunway is identied and given a gate assignment fromthe operator, the axi Routing DS generates a proposed2-D inbound taxi route (Audenaerd et al, p. 4-5), andthe surface model is updated. Te surface automationreceives nal verication of the landing runway from theservicing RACON automation as XYZ987 joins the nal

approach on a Standard erminal Arrival Route (S AR).Te inbound taxi route is nalized and uplinked to theFlight Management System from the surface automationvia DataComm. Te aircraft is instructed to join the paral-lel taxiway on runway exit; a specic runway high-speedturnout is not specied. A “hold short” of the paralleldeparture runway is included in the taxi instruction.

In accordance with the published arrival proce-dure, ight XYZ987 calls the tower on the Local arrivalfrequency for clearance to land. After acknowledgingthe call, Local visually scans the arrival runway and thenclears XYZ987 to land. In Audenaerd et al.’s description,the surface automation “anticipates” which turnout willbe taken based on aircraft deceleration and updates thetaxi route based on the actual turnout taken and initi-ates Conformance Monitoring. At some airports (DFW,for example), Local clears the ight across the parallel(departure) runway in accordance with established localprocedures and instructs the pilot to contact Ground.

At other airports, Local hands off the arrival as it exitsthe runway and Ground coordinates the crossing of theinboard departure runway. Ground observes the ight asit progresses along the inboard taxiway to the transfer spot

and noties the operator Ramp Control that XYZ987is released to their control. Conformance Monitoring isautomatically terminated as the aircraft transitions fromthe taxiway to the ramp area. Ramp Control noties thesurface automation when XYZ987 is at the gate.

Multiple Operations

Te nominal scenarios described by the conceptsof operation and use for FDM and associated surfaceDS s are based on single aircraft examples. However, thecab rarely handles just one aircraft in any given phase ofthe operation. At almost any time of day at large airportssuch as DFW and A L, the tower cab team is respon-sible for several aircraft, particularly when departure andarrival banks of ights overlap. Both Local and Groundare managing queues of aircraft, with a series of discreteactions required for each aircraft. Some of these actions

will be aided by automation in the mid-term, for example,taxi routing. However, cab controllers are very likely toretain overall responsibility for the safety of the arrivalsand departures. Te tools used will change, and greaterinteraction with displays will be required of the controllers.

Mixed EquipageIt is not clear, at this point, what proportion of the

eet will be equipped for DataComm and ADS-B (Out)by 2018. Te level of equipage might vary between and

within operators. For cab controllers, the major questions will be (a) how to know which aircraft have what capabili-ties, and (b) what procedures to use with which aircraft,

given an indication of their capabilities. For example, ruittand Muldoon (2010) incorporated a triangular symbolinto the aircraft data block to indicate data link capabil-ity in their DataComm Segment 2 HI L simulation ofground operations. However, national air traffic technicalprocedures for aircraft with and without DataComm havenot yet been published. Procedures for use of air trafficcontrol DS s are dependent on the specic design andimplementation of a given capability. Te denition andpublication of procedures for use of a DS can be lengthy.For example, the User Request Evaluation ool (URE )

was initially elded in the mid-1990s under the “FreeFlight Phase 1” program umbrella. However, rules for usingURE were only recently incorporated into the nationalair traffic procedures order (FAA, 2010b). Developmentand vetting of procedures for handling aircraft with dif-ferent levels of equipage will likely take several years andimplementation in the mid-term will be a challenge forthe air traffic control procedures community.

Change in Operational Priority Another mid-term consideration is a change from

the established equitable operational priority of “First



35

Come, First Served” to a different ight prioritizationmodel (Joint Planning & Development Office, 2011).

An early ight prioritization model was labeled “BestEquipped, First Served” (Department of ransportationOffice of the Inspector General, 2009, p. 12; FAA, 2009b,p. 27). Te model is straightforward: At any given timeor in any given operation, the aircraft that has the “best”

equipment prole will be given priority over a lesser-equipped aircraft, barring other operational or safetyconsiderations. Tis operating concept is linked directly tothe procedures for handling aircraft with mixed equipageas discussed above. Since 2009, a range of alternative ightprioritization models have been proposed (Joint Planning& Development Office, 2011); no single model has beenadopted as yet. Tat being said, the impact of a changein operating paradigm will be different across positions

within the tower cab. Te sequence of aircraft to be handledby Local is determined by other positions. For example,the sequence of arrival aircraft will largely be determinedby the servicing RACON; Local will literally be takingthe arrival stream “First Come, First Served” as hand-offsfrom the RACON. Teoretically, the arrival sequence

will have been optimized by the raffic Flow Managementautomation and the surface automation’s Scheduling andSequencing DS . Changing the sequence of aircraft onnal approach with a landing clearance would be an ex-ception. For example, Local might issue a “Go Around”instruction to an arrival on nal because of a pilot deviationonto the active arrival runway (e.g., runway incursion).Similarly, which departure will be taken next by Local will

be largely determined by the sequence of aircraft setupby Ground Control, with the aid of the Sequencing andScheduling DS in the form of the single, “integratedcollaborative schedule.” For example, the Sequencing andScheduling DS could provide the Ground with a listof which departure to take rst, second, and so on fromthe ramp, using equipage as a factor, along with taxiwayloading, runway balancing, and wake mitigation rules. Ifthe raffic Flow Management automation and cab DS s

work as described, then the best equipped (or betterperforming) aircraft will likely have precedence over less

well equipped (or performing) aircraft. Te rub will come with exceptions, aircraft not known to the system, andunexpected (stochastic) events that create “off-nominal”situations. Since these types of events are unknown and/or unexpected, the cab controllers will likely have to adaptto the circumstances, with safety of operations being farmore important than aircraft equipage in determining

what action to take next.

Mid-Term ATCTsFinally, the surface-oriented automation is targeted at

the 30 largest U.S. airports. Some mid-size airports mightalso acquire these tools; a detailed waterfall schedule hasyet to be made available. It is unclear what surface automa-tion tools will be implemented at the other 200+ air trafficcontrol towers staffed by the FAA by 2018. It is also not

clear how the proposed DS s, especially the Schedulingand Sequencing and axi Routing (with ConformanceMonitoring) DS s, could be used at airports with signi-cant General Aviation (GA) operations conducted underVFR without led ight plans. Example airports are VanNuys (VNY) and ulsa Riverside (RVS), both of whichare among the 50-busiest towers in the country (FAA,2010d). Te current concepts of operation, concepts ofuse, Enterprise Architecture artifacts, and research anddevelopment reports are focused on solutions for theproblems of large, busy hub airports.

About 20% of current terminal controllers (andtheir supervisors) work in the 30 largest core airports,based on September 2010 FAA employment data fromthe FAA Personnel and Payroll System provided to CAMI.

About 25% of current terminal controllers (and supervi-sors) worked in stand-alone RACONs (or CombinedCenter-Approach facilities such as Honolulu and San Juan,PR). Te majority, however – more than 5,000 controllersand rst-level supervisors – worked at 200+ mid-size andsmaller airports. It is more likely than not that the toolsand procedures used in these towers in 2018 will be similarto the ones in current use. Some mid-term automation,

primarily those relating to traffic ow management, mightbe used by the ower Supervisor in towers at mid-size andsmaller airports. Some of these towers might be contractedout by 2018. It is also possible that some might be com-bined into Staffed NextGen owers (SN s), if the safety,cost, technological, political, and public risk perceptionconcerns can be addressed in the next few years. A keytechnical issue will be certifying systems such as closedcircuit V for visually monitoring runways and taxiwaysas equivalent to visual operations. Finally, a “business case”for extending surface automation down to mid-size andsmaller airports would have to be made for both the FAAand users. In view of these considerations, it seems morelikely than not that that a signicant number of FAAcontrollers –probably a majority of terminal controllers– will be working in 2018 in a tower cab environmentmore similar to today’s working environment than theDS -centered environment envisioned for the mid-termat the 30 Core airports.



36

ANALYSIS OF MID TERM NEXTGENIMPACT ON APTITUDES REQUIRED

IN THE ATCT CAB

Mid-Term DST Impact on Tower Cab Controller Roles& Responsibilities

Overall, the proposed DS capabilities will provide

an electronic representation of ight data (as electronicight strips, airport maps with tracks and associated ightdata tags, and airspace map with targets and tags) anddisplay recommendations for key tasks such as runwayassignment, sequencing and scheduling, taxi routing, andconformance monitoring. Controllers will interact withthese tools via unspecied (as yet) CHIs hosted on the

FDM platform. However, the controllers will remainresponsible overall for the major job functions they cur-rently perform such as monitoring the airport movementarea, detecting problems, resolving conicts and devia-tions, managing sequences of aircraft, and managing towerresources. Te automation capabilities supplement ratherthan supplant human perception. Terefore, controllersare likely to continue relying upon their own perceptionsand judgments, perhaps looking to the automation to con-rm a course of action in the mid-term. How to performthose actions and use the automation (e.g., knowledgeand skill) is a matter of training, not selection (undercurrent FAA policy).

Mid-Term TOWER DST Impact on AptitudeGiven that the overall functions to be performed by

human controllers are unlikely to change by the mid-term,then the prole of aptitudes required to perform thosefunctions is likely to be very nearly the same. Tis is cer-tainly the case for 200+ airports with FAA towers that arenot slated to receive many (if any) of the NextGen DScapabilities by the mid-term – and the 5,000+ controllers

working in those towers. Te aptitude requirements forselection into these towers, representing about a third ofthe overall controller workforce, are unlikely to changeas a consequence.

However, the larger, more complex towers associated with the 30 largest (and perhaps some of the mid-size air-ports) are slated to have at least some of the proposed DS sinstalled and functional in the mid-term. Specic DScapabilities (depending on their actual implementation)and increased operations might make some aptitudes moreimportant and others less so to successful performance ofthe job at these towers.

Te heuristic input-process-output model (Figure7) is used to organize the description of the aptitudeslikely to be required of controllers at these larger, busytowers in 2018 ( able 4). Te degree to which the im-portance of any given set of innate aptitudes increases or

decreases depends heavily on the assumptions one makes with respect to the reliability of the proposed DS s, theoperational acceptability and stability of their solutions,and the likelihood of “Black Swan” (extremely rare butpotentially catastrophic) off-nominal events. For thisanalysis, the perspective taken is that the DS s will bereliable, produce stable, operationally acceptable solutions,

and that off-nominal events such as equipment failure andloss of connectivity will be truly rare. Learned A C-specicknowledge and skill will be more relevant to coping withsuch off-nominal events than aptitude per se.

In terms of input-related aptitudes, the requirementfor (visual) Scanning will increase as the number andcomplexity of displays increase in the mid-term towerat large airports. Scanning the airport movement areaout-the-window might be supplemented, or less likely,supplanted by scanning multiple large integrated displays.Tis shift from out-the-window to high-resolution dis-plays will increase the need for controllers to apprehendand interpret symbols and other information on thosedisplays. Te worker requirements, Interpreting Informa-tion and ranslating Information from displays, are likelyto become more important to successful job performancein the 2018 cab. At the same time, the sheer volume of“data” presented to the controller via the DS s and theirdisplays will increase. For example, the timeline displaysuggested by Jung and colleagues (Jung et al, 2010) usessequence, alphanumerics, highlighting, and color to rep-resent a departure sequence. Tere simply will be moredata points to be apprehended across fewer displays in

the tower cab at large airports. Controllers will need fastand efficient heuristics to apprehend, organize, and assessdisplayed data. Tis aptitude was labeled Chunking inthe 1995 analysis. With the volume of data and opera-tions, the importance of Perceptual Speed and Accuracyto successful job performance is likely to increase in themid-term as well.

Te “chunked” information gained by the control-ler through scanning of the displays goes into Short-termMemory (S M); S M will continue to be a key aptitudethrough the mid-term. Greater demands will be made onLong-term Memory as controllers in the mid-term willhave to memorize how to interact with the CHI for thecab DS s under different circumstances or scenarios inaddition to airport layout and the many air traffic controlprocedures (rules). Te need for Sustained Attention willincrease in the mid-term due to increased traffic and tocounter complacency. Te importance of Concentrationon the task at hand is likely to remain unchanged in themid-term. However, Recall from Interruption might playa greater role in successful job performance with increasedtraffic loads and multiple display-based informationsources. As noted in the descriptions of multi-aircraft



37

operations in the present and in the future, controllers areoften called upon to start actions with one aircraft, shift toanother, then another, and then return to the rst aircraftto complete the cycle. Teir work might be characterizedas serial interruption; returning to an action “in suspense”is, and will be, important.

Dynamic comprehension, problem solving, and

thinking ahead of the traffic situation are at the heart ofcontroller cognition. On one hand, the abilities requiredto comprehend the traffic situation, solve any problems,and think ahead of the traffic will remain very nearly thesame in towers at non-OEP and other airports. On theother hand, understanding the present and future stateof surface and airborne traffic at the largest and busiestairports will be a signicant challenge to controllers in themid-term. Te demand on Situational Awareness at theseairports will be driven by increased traffic, more complexdisplays, mixed equipage, and implementation of DS s.However, well designed displays and DS s will enablecontrollers to “look ahead” of proposed operations. TeDS s might also summarize information in a more ac-cessible manner in tabular and graphic displays. Te neteffect will be to reduce Visualization, Dynamic Visual-Spatial, and Summarizing Information by the controlleras the bases for control actions in towers at the 30 Coreand other large towers.

Solving problems will be more complicated at theselarge towers in the mid-term if projected traffic increasesmaterialize. Problem Identication will become moreimportant to job performance to detect and evaluate DS

errors and faults and their impact on proposed solutions.Te need to prioritize actions (Prioritization) will increase

with greater and more complex traffic. Rule Application willbe embedded in the DS algorithms; hence the need forthat aptitude will decrease in the mid-term. Te aptitudeto reason conditionally about events (“if-then” Reasoning)

will still be important to successful job performance. Withthe implementation of surface DS s in the mid-term atlarge airports, the abilities such as one’s innate capabil-ity for Tinking Ahead might become less important tosuccessful job performance. For example, the Sequencingand Scheduling, Runway Assignment, and axi Routing(with Conformance Monitoring) DS s will do much ofthe planning. Te importance of Planning and Projectionto successful job performance might decrease. Change inthe importance of Creativity to successful job performanceis linked to the likelihood of situations in which existing(in the mid-term) solutions and procedures do not applyor work, and new, creative solutions are needed. Giventhe stated assumptions of DS reliability, stability, andoperational acceptability, Creativity is likely to be lessimportant in the mid-term.

At the same time, the importance of aptitudesgrouped under the rubric of cognitive style is likely to,on the whole, increase in the mid-term. Self-awarenessand Self-monitoring/Evaluation will continue to be veryor extremely important to successful job performance.Information Processing Flexibility is likely to become evenmore important in the mid-term as controllers switch

between and integrate multiple information sources(some not previously available) and evaluate, revise, anddevise solutions to the problems at hand. ask Closure/Toroughness will also increase in importance in themid-term, most particularly to ensure that an accurateand up-to-date model of the intended aircraft trajectoryis maintained. Depending on CHI design, controllers inthe mid-term will need to make more computer entries tocapture intent and changes in trajectories than at present.Tis shift to DS -centered interaction is likely to introducea new attribute requirement in the mid-term cab: “ rust in

Automation.” What this label means operationally is stillbeing debated (see Parasuraman, Sheridan, & Wickens,2008). It is not clear to what degree “trust in automa-tion” is experiential and situational versus dispositional.In general, research supports an experiential componentto “ rust in Automation:” System characteristics, such asfalse alarm rate, predict user trust. In turn, experientialtrust predicts automation use. However, Merritt and Ilgen(2008) found that individual differences were related totrust. Tey recommended distinguishing between dis-positional and history- or experience-based trust in theautomation. Te dispositional or trait-like component

identied by Merritt and Ilgen (labeled “Dispositionalrust in Automation” in this report) might be seen as an

aptitude for selection purposes.Te last “process” group of aptitudes related to A C

was labeled as Personality: Surgency (Figure 7). It is morelikely than not that the factors such as Self-condence,

aking Charge, Flexibility (Stability/Adjustment), and Working Cooperatively will continue to be very or ex-tremely important to successful job performance in anytower cab. With increased traffic at the 35 OEP airportsand mid-size hubs, olerance for High Intensity WorkSituations might become even more important in themid-term cab.

urning to the “output” aspects of the heuristic modelof Figure 7, it is clear that controllers will interact withsystems via CHIs to a greater degree in the mid-term thanat present. In today’s tower cab environment, there arerelatively few “modern” CHIs; “CHI Navigation” is largelyirrelevant. Te mid-term cab is likely to be dominated bydisplays and their interfaces. Tere are two implicationsfor aptitudes. First, Manual Dexterity, in terms of usinga keyboard, mouse, touch screen and/or keypad, mightbe more important than it is now. Second, and perhaps



38

more importantly, one’s ability to navigate a structuredCHI, through screens, menus, windows, drop-downlists, target selection, hot spots, etc. (“CHI Navigation”)might be more important to successful job performancethan at present.

Finally, some aptitudes might become less important with the introduction of increasingly sophisticated DS s

that are reliable and produce solutions that are operation-ally advantageous. For example, tower controllers mightnot need to perform quick, rule-of-thumb distance-rate-time estimates with the advent of tower DS s. However,as noted previously, the prole of aptitudes required attowers without (or late in receiving) these technologies

will be the same as today.

Aptitude Testing Gap AnalysisTe current A CS occupational aptitude test bat-

tery assesses many, but not all, of the aptitudes likelyto be required in the mid-term tower cab, as shown in

able 4. Several of the tests in current use are intendedto assess multiple aptitudes, particularly the two dynamictests (Letter Factory est and Air raffic Scenarios est).

Aptitudes assessed in these two multi-factorial, dynamictests include Situational Awareness, Planning, Tinking

Ahead, Prioritization, Visualization, and Projection. Ascore representing Situational Awareness is computed fromapplicant performance on the Letter Factory est. A singlescore representing both Planning and Tinking Ahead isalso computed from the Letter Factory est. At present, noscore is computed on the basis of performance on either

dynamic test to assess applicant aptitude for Prioritiza-tion. A method for parsing applicant performance on the

Air raffic Scenarios est was proposed in the mid-1990s(Broach, 1995) but has never been fully implemented orvalidated. Further research and development on Prioritiza-tion, Visualization, and Projection is needed to close thegap between current and future aptitude requirements.

At present, Scanning is assessed explicitly by the Scantest, while Perceptual Speed and Accuracy is assessed by theDials est. Both tests are based on a 2D display. Furtherresearch is needed to determine if depth perception willbe relevant to future operations in the tower, particularly

with respect to the Staffed NextGen ower concept.Reasoning is assessed by the Analogies test; the rela-

tive importance of this ability is not expected to change with NextGen. In contrast, Flexibility (InformationProcessing) is expected to become more important to jobperformance in the tower cab of 2018. Tis aptitude isnot assessed in the current version of A -SA (see able2.10, Ramos, Heil & Manning, 2001). est developmentand validation will be required to address this shortfall.

raits such as Self-awareness, Stability/Adjustment,ask Closure/Toroughness, and olerance for High

Intensity Work Situations are assessed presently in a self-report questionnaire. However, the current assessments arevulnerable to applicant impression management tactics.Research on the reliability and validity of alternative as-sessments is currently underway.

Te current test battery has a component related toConcentration, but it does not have an explicit assessmentof Sustained Attention. In the mid-term, the issue mightnot be sustaining attention under high workload (and littleautomation support). Rather, sustaining attention underlow workload (with more automation support) mightbe more important. Reecting these conditions (highversus low workload, with little versus more automationsupport) in an aptitude test will require further constructdenition and validation.

Four aptitudes that will increase in importance arenot currently assessed in an explicit manner: Active Lis-tening (specically, auditory attention in the presence ofvoice, telephone, alarms and ambient noise), ranslatingInformation, Chunking, and Interpreting Information.ests of Dispositional rust in Automation and Computer-

Human Interface (CHI) Navigation that might be usedin selection will need to be identied or developed andthen validated for use by the FAA.

Tere are three corollary research issues that willrequire further research. First, the relative weights givento existing test scores should be reviewed. Some aptitudescurrently assessed will decrease in importance to perfor-

mance in the tower cab of 2018; the importance of others will remain the same, and some are likely to become moreimportant. Te weighting scheme will require modica-tion to address these changes as well as to incorporate newscores. Te second research issue relates to the questionof “how much” of a given aptitude is required for somethreshold of performance. Te overall aptitude scoreis currently computed as the sum of weighted sub-testscores. Mathematically, low scores on one test are offsetby higher scores on other tests (depending on the weightgiven a particular score). Research is needed to assessthe benets and costs of using minimum cut-scores oneach measure as part of the overall scoring model. Tethird research issue reects the differences in degree, ifnot kind, in aptitudes required in the towers at the 30largest airports and in the towers at mid-size and smallerairports. It might be the case that differential weightingschemes and cut-scores by tower size (towers for the 30largest airports versus other towers) are needed. Empiri-cally demonstrating differential validity by facility level(large versus other tower) will be challenging.



39

Table 4: Changes in aptitude requirements at 2018 (at 35 OEP & other large airports), rationale, andcoverage by AT-SAT, organized into Figure 7 heuristic input-process-output model

Worker Requirement In 2018 Rationale AT-SATINPUT

Active Listening (AuditoryAttention)

Same Voice, telephone, alarms, ambient noise

Scanning Increase DST CHIs + Out-The-Window (OTW) ATST,LFT, SC

Perceptual Speed and Accuracy Increase Multiple visual (DST & DataComm CHIs,OTW) & Audio sources

ATST,LFT, SC,DI

Translating Information Increase DST & display symbologyChunking Increase DST & display symbologyInterpreting Information Increase DST & display symbology

PROCESS

Short-term Memory Same

AttentionConcentration Same LFTSustained Attention Increase Risk of DST-induced complacency,

Increased trafficRecall from Interruption Increase Increased traffic LFT

Dynamic Comprehension

Situational Awareness Increase DST recommendations, DataCommmessaging, CHIs

ATST,LFT

Visualization Decrease DST, Displays “look ahead” (particularlywith graphic displays)

ATST

Dynamic Visual-Spatial Same ATST,LFTSummarizing Information Decrease DST, Displays

Long-term Memory Increase Memorize procedures, DST algorithms (atsome level), and user interface actions

Problem Solving

Problem Identification Increase DST Error, Modes, Faults, Solutionevaluation

EQ

Prioritization Increase Increased traffic ATST,LFT

Rule Application Decrease DST applies rules AYReasoning Same ATST,

AYThinking Ahead

Thinking Ahead Same “Stay ahead of the problem” even withDST support

ATST,LFT

Planning Decrease DST-based planning ATST,LFT



40

Worker Requirement In 2018 Rationale AT-SAT

Projection Decrease DST, Displays “look ahead” (particularlywith graphic displays)

LFT,ATST

Creativity Uncertain Depends on assumptions about DSTreliability and likelihood of “Black Swan”off-nominal events

Time Sharing Increase Multiple DST & DataComm, Increasedtraffic

LFT

Cognitive Style

Self-awareness Same EQSelf-Monitoring/Evaluating Same EQFlexibility (InformationProcessing)

Increase Multiple sources of information, DSTMode changes, Adaptation of DST-generated plans

AY

Task Closure/Thoroughness Increase DST & DataComm follow-through

(update system to ensure current withATCS intent)*Trust in Automation

Personality (Surgency)

Self-Confidence Same EQTaking Charge Same EQTolerance for High-Intensity WorkSituations

Increase Increased traffic EQ

Flexibility (Stability/Adjustment) Same EQWorking Cooperatively Same EQ

OUTPUTOral Communication Decrease DataComm*CHI Navigation (Menus,Windows, etc.)

CHI

*Manual Dexterity (Keyboard,Mouse, Touch screen, Keypad)

CHI

Notes: 1AT-SAT: Blank indicates aptitude not assessed in current test configuration; ATST = Air TrafficScenarios Test; LFT = Letter Factory Test; SC = Scanning; DI = Dials; AY = Analogies; AN = Angles;AM = Applied Math2 New worker requirements indicated by asterisk preceding construct label (*Label)

Table 4 (continued)



42

FOOTNOTES

1 A CS will be used throughout, as it is more familiar and widely used, rather than the idiosyncratic ANSP, exceptin direct quotes.2Runways are labeled by their heading and, where thereare multiple runways on the same compass heading, by therelative position as it appears to the pilot. For example, atDFW, the three north-south runways on the east side areon a compass heading of 170 (to the south) and 350 (tothe north). On approach (landing) from the north, theinboard runway closest to the terminal would be labeled“17L,” the middle runway would be labeled “17C,” andthe farthest east runway would be labeled “17R.” Te east-side diagonal, running on a 130 compass heading (andits reciprocal, 310) is labeled “13L,” while the diagonalon the west side of DFW is labeled “13R.”3Excluding Flight Service, which was contracted out in2005 to Lockheed-Martin, Inc.4No specic model or architecture of cognition is impliedby Figure 7. It is meant simply to be a means for organizingthe description of the 1995 Nickels et al. job/task analysis.5 When referring to a specic DS , the function is capital-ized and in italics in the text:Sequencing and Scheduling DS . Te generic function accomplished by the specicDS is not capitalized or italicized: Algorithms for se-quencing and scheduling a bank of outbound ightsmust be developed.6

A non-supervisory A CS will temporarily assume limited,operational supervisory responsibilities as a Controller-In-Charge (CIC) under certain conditions; for example,if the on-duty supervisor is “off the oor” attending ameeting or other reason.

REFERENCES

Alexander, J. R., Alley, V. L., Ammerman, H. L., Fairhurst, W. S., Hostetler, C. M., Jones, G. W., & Rainey, C.L. (1989). FAA air traffic control operations conceptsVolume VII: A C tower controllers. (Contractdeliverable CDRL B112, Vol. VII delivered under

FAA contract D FA01-85-Y-01034). Washington,DC: Federal Aviation Administration Advanced

Automation Program (AAP-100).

Ammerman, H. L., Becker, E. S., Bergen, L. J., Claussen,C. A., Davies, D. K., Inman, E. E., & Jones, G.

W. (1987). FAA air traffic control operations con-cepts Volume V: A C / CCC tower controllers.(CDRL B112, Vol. V delivered under FAA contractD FA01-85-Y-01034). Washington, DC: Federal

Aviation Administration Advanced AutomationProgram (AAP-100).

Ammerman, H. L., Becker, E. S., Jones, G. W., obey, W.K., & Phillips, M. D. (1987). FAA air traffic controloperations concepts. Volume I: A C backgroundand analysis methodology. (CDRL B112, Vol. Idelivered under FAA contract D FA01-85-01034).

Washington, DC: Federal Aviation Administration Advanced Automation Program (AAP-100).

Anagnostakis, I. & Clarke, J.-P. (2002). Runway opera-tions planning: A two-stage heuristic algorithm.(AIAA2002-5886). Paper presented at the AIAA Aircraft

echnology Integration and Operations (A IO)Conference, Los Angeles, CA.

Anagnostakis, I., Clarke, J.-P., Bohme, D. & Volckers, U.(2001). Runway operations planning and control:Sequencing and scheduling. Journal of Aircraft ,38(6), 988–996.

Anagnostakis, I., Idris, H. R., Clarke, J.-P., Feron, E.,Hansman, R. J., Odoni, A. R., & Hall, W. D. (2000,

June). A conceptual design of a departure planner deci-sion aid.Paper presented at the 3rd US/Europe Air

raffic Management R&D Seminar, Napoli, Italy.

Annett, J. (2004). Hierarchical task analysis. In D. Dia-per & N. A. Stanton (Eds.). he handbook of taskanalysis for human-computer interaction (pp. 67-82). Mahwah, NJ: Lawrence Erlbaum Associates.

Atkins, S., Brinton, C. & Jung, Y. (2008, September).Implication of variability in airport surface opera-tions for 4-D trajectory planning. AIAA Aviation

echnology, Integration and Operations (A IO)Conference, Anchorage, AK.



43

Atkins, S., Brinton, C., & Walton, D. (2002, October).Functionalities, displays and concept of use for theSurface Management System. 21st Digital AvionicsSystems Conference (DASC), Irvine, CA.

Atkins, S., Walton, D., Arkind, K., Moertl, P., & Carniol,. (2003, June). Results from the initial surface man-

agement system field tests.Paper presented at the 5thUS/Europe Air raffic Management R&D Seminar,Budapest, Hungary, June 23-27, 2003.

Audenaerd, L., Burr, C., Diffenderfer, P., & Morgan, C.(2010). Surface trajectory-based operations (S BO)mid-term concept of operations overview andscenarios. Revision 1. (MP090230R1). McLean,VA: MI RE Center for Advanced Aviation SystemDevelopment.

Balakrishana, P., Ganesan, R., & Sherry, L. (2009, May). Application of reinforcement learning algorithms for

predicting taxi-out times.8th USA/Europe Air rafficManagement Research and Development Seminar,Napa, CA.

Balakrishnan, H. & Jung, Y. (2007, August). A framework for coordinated surface operations planning at Dallas-Fort Worth International Airport. (AIAA 2007-6553).

AIAA Guidance, Navigation & Control Conference(GNCC), Hilton Head, SC.

Booz, Allen, Hamilton, Inc. (2006, Jun). ower modulardesign analysis. Washington, DC: Federal Aviation

Administration Human Factors Research & Engi-neering Group (AJP-61).

Brinton, C. & Atkins, S. (2008). A probabilistic modeling foundation for airport surface decision support tools. 2008 Integrated Communications, Navigation andSurveillance (ICNS) Conference.

Brinton, C., Lent, S., & Provan, C. (2010, October).Field test results of Collaborative Departure Queue Management. Paper presented at the 29th AnnualDigital Avionics Systems Conference (DASC29),Salt Lake City, U .

Brinton, C., Krozel, J., Capozzi, B., & Atkins, S. (2002a, July). Airport surface modeling algorithms for the Sur- face Management System. 16th Conference for theInternational Federation of Operational ResearchSocieties (IFORS), Edinburgh, Scotland.

Brinton, C., Krozel, J., Capozzi, B., & Atkins, S. (2002b, August). Automated routing algorithms for Surface Management Systems. (AIAA 2002-4857). AIAAGuidance, Navigation, and Control Conference(GNCC), Monterey, CA.

Broach, D. (1995). Objective assessment of prioritizationin the WinA S . Unpublished manuscript, FAA

Aerospace Human Factors Research Division.

Broach, D. (Ed.) (1998). Recovery of the FAA air trafficcontrol specialist workforce. (Report No. DO /FAA/

AM-98/23). Washington, DC: Federal Aviation Administration Office of Aviation Medicine.

Carr, F.R. (2004, February). Robust decision-support tools for airport surface traffic. Unpublished doctoral dis-sertation, Massachusetts Institute of echnology.Last retrieved November 1, 2012 from http://hdl.handle.net/1721.1/34945

Cirino, F. A. (1986). Air traffic delays and runway capac-ity: What’s the game plan and who’s keeping score? Airport and terminal-area operations of the future (pp.36 – 43). ( ransportation Research Circular 325).

Washington, DC: ransportation Research Board.

Cole, L. (1995). Air traffic control and the National Planfor Civil Aviation Human Factors. Journal of A C , 37 (3), 43 – 49.

Diffenderfer, P. A. (2010). Mid-term surface trajectory-basedoperations concepts of use: Collaborative departurequeue management. (M R100269V3). McLean,VA: he MI RE Center for Advanced AviationSystems Development.

Department of ransportation Office of the InspectorGeneral. (2009). Federal Aviation Administration:

Actions needed to achieve mid-term NextGen goals. (CC-2009-044). Washington, DC: Author.

Durso, F., Fleming, J., Johnson, B., & Crutchfield, J.(2009). Situation dimensions of air traffic controlinformation needs: From information requests to displaydesign. Oklahoma City, OK: FAA Aerospace HumanFactors Research Division (AAM-500).

Durso, F., Sethumadhavan, A., & Crutchfield, J.(2008). Linking task analysis to informationrelevance. Human Factors , 50 (5), 755-762. doi:10.1518/001872008X312369

Dziepak, A. E. (2010, August). Assessment of ower FlightData Manager Phase 1 ( FDM1) operations and capa-bilities. (M R100291). McLean, VA: he MI RECenter for Advanced Aviation System Development.

Eißfeldt, H. (2009, April). Aviator 2030-Determiningability requirements in future A M systems. Paperpresented at the 15th International Symposium on

Aviation Psychology, Dayton, OH, April 27-30,2009.



44

El-Sahragty, A. S., Burr, C. S., Nene, V. D., Newberger, E.G., & Olmos, B. O. (2004, September). Functionalanalysis of surface traffic management systems: Overlapsand gaps. (MP 04W0000143R01). McLean, VA:

he MI RE Center for Advanced Aviation SystemDevelopment.

Federal Aviation Administration (2007).Capacity needs inthe National Airspace System 2007 – 2025. RetrievedNovember 22, 2010 from the FAA website: http://

www.faa.gov/about/initiatives/nextgen/defined/ why/cap%20needs%20in%20the%20NAS.pdf

Federal Aviation Administration (2008a). An operationalconcept for NextGen owers. (Version 5.1). RetrievedNovember 22, 2010 from the FAA website:https://faaco.faa.gov/attachments/NextGen_ ow-ers_ConOps_FINAL_9-30-08.pdf

Federal Aviation Administration (2008b). erminal data

link services in the National Airspace System (Version1.0, dated January 15, 2008). Retrieved February14, 2011 from the FAA website http://www.faa.gov/air_traffic/publications/media/ DLS.pdf

Federal Aviation Administration (2009a).Data communi-cations (DataComm). Retrieved November 22, 2010from the FAA website: http://www.faa.gov/about/office_org/headquarters_offices/ato/service_units/techops/atc_comms_services/datacomm/

Federal Aviation Administration (2009b).FAA’s NextGenimplementation plan 2009. Retrieved February 17,2011 from the FAA website: http://www.faa.gov/about/initiatives/nextgen/media/ngip.pdf.

Federal Aviation Administration (2010a). A plan forthe future: 10-Year strategy for the air traffic controlworkforce 2010-2019.Retrieved December 1, 2010from the Federal Aviation Administration website:http://www.faa.gov/air_traffic/publications/con-troller_staffing/media/CWP_2010.pdf

Federal Aviation Administration (2010b). Air traffic con-trol. (FAA Order 7110.65 ). Retrieved November

22, 2010 from the Federal Aviation Administration website: http://www.faa.gov/air_traffic/publica-tions/atpubs/A C/index.htm

Federal Aviation Administration (2010c). Acquisition Management System. Federal Aviation Administra-tion website: http://fast.faa.gov/

Federal Aviation Administration (2010d).FAA Adminis-trator’s Handbook (March, 2010). Retrieved Decem-ber 1, 2010 from the Federal Aviation Administra-tion website: http://www.faa.gov/about/office_org/headquarters_offices/aba/admin_factbook/

Federal Aviation Administration (2010e).Facility opera-tion and administration. (FAA Order 7210.3W).Retrieved November 22, 2010 from the Federal

Aviation Administration website: http://www.faa.gov/air_traffic/publications/atpubs/FAC/index.htm

Federal Aviation Administration (2010f).National Air-space System Enterprise architecture. Federal Aviation

Administration website: https://nasea.faa.gov/

Federal Aviation Administration (2010g).NextGen imple-mentation plan 2011 (Version 1.0 dated November8, 2010). Washington, DC: Author.

Federal Aviation Administration (2010h). erminal area forecast(APO100_ AF_Final_2010.zip) [Data file].Retrieved February 17, 2011 from the FAA websitehttp://aspm.faa.gov/main/taf.asp.

Federal Aviation Administration (2011). Core 30. Re-trieved November 7, 2012 from the Federal Aviation

Administration website http://aspmhelp.faa.gov/index.php/Core_30

Feron, E., Hansman, R. J., Odoni, A., Cots, R. B., De-claire, B., Feng, X.,...& Pujet, N. (1997). he De- parture Planner – A conceptual discussion. Cambridge,

MA: he Massachusetts Institute of echnologyInternational Center for Air ransportation. (Re-trieved April 1, 2009 from http://dspace.mit.edu/handle/1721.1/34944).

Glass, B. (1997). Automated data exchange and fusion forairport surface traffic management. (AIAA-1997-3679). AIAA Guidance, Navigation, and ControlConference, New Orleans, LA, Aug. 11-13, 1997.

Goeters, K.-M., Maschke, P., & Eißfeldt, H. (2009). Ability requirements in core aviation professions: Job analyses of airline pilots and air traffic control-lers. In K.-M. Goeters (Ed.), Aviation psychology:Practice & research (pp. 99-118). Farnham, UnitedKingdom: Ashgate.

Gosling, G. D. (1993). Development of a frameworkfor assessing the benefits of airport surface trafficautomation. IEEE ransactions on Control Systems

echnology , 1(3), 155 – 167.

http://www.faa.gov/air_traffic/publications/controller_staffing/media/CWP_2010.pdf






45

Hurst, L. R. (1971). S RACS for ground control. Journalof A C , 13(1), 14-15.

Idris, H. R., Delcaire, B., Anagnostakis, I., Hall, W. D.,Clark, J-P., Hansman, R. J., … & Odoni, A. R.(1998). Observations of departure processes at Logan Airport to support the development of departure plan-ning tools. 2nd USA/Europe Air raffic Manage-ment R&D Seminar, Orlando, FL, USA. http://

www.atmseminar.org/past-seminars/2nd-seminar-orlando-fl-usa-december-1998/papers/paper_053

Jackson, C. (2010). Integrated Departure Route Planning(IDRP). (Enclosure F045-B10-056 to Letter F045-L10-033). McLean, VA: he MI RE Center for

Advanced Aviation System Development.

Jakobi, J., Porras, F., Moller, M., Montebello, P., Scholte, J., Supino, M., et al. (2009). European Airport Movement Management by A-SGMCS, Part 2 Rec-

ommendations report. (Report 2-D6.7.2)(ContractREN/04/FP6AE/S12.3749991/503192). Braun-schweig, Germany: EMMA2 Project Partners. Re-trieved November 22, 2010 from the DLR EMMA

website: http://www.dlr.de/emma2/maindoc/2-D672_RECOM_V1.0.pdf

Joint Planning & Development Office (JPDO). (2007).Concept of operations for the Next Generation Aviation

ransportation System (NextGen). (Version 2.0). Re-trieved December 1, 2010 from the JPDO website:http://www.jpdo.gov/library/NextGen_v2.0.pdf

Joint Planning & Development Office (JPDO). (2011).Flight Prioritization Deep Dive: Final Report. Re-trieved February 15, 2011 from the JPDO websitehttp://www.jpdo.gov/library/20110113_FP_Re-port_Final_v3.pdf

Jung, Y. C., Hoang, . Montoya, J., Gupta, G., Malik, W. & obias, L. (2010, September). A concept andimplementation of optimized operations of airportsurface traffic. 10th Aviation echnology, Integration,& Operations (A IO) Conference, Fort Worth, X.

Kell, S., Masalonis, A. J., Stelzer, E. K., Wanke, C. R.,DeLaura, R., & Robinson, M. (2010). IntegratedDeparture Route Planning (IDRP) phase 1 evaluationand benefits assessment plan. (MP100060). McLean,VA: McLean, VA: he MI RE Center for Advanced

Aviation System Development.

Krokos, K.J., Baker, D.P., Norris, D.G., & Smith, M.A.(2007). Development of performance standards forair traffic control specialists. (Final report deliveredunder FAA grant No. 99-G-048). Washington, DC:

American Institutes for Research.

Lockwood, S. M., Atkins, S. C., & Dorighi, N. (2002, Aug). Surface Management Systems simulations inNASA’s Future Flight Central. (AIAA 2002-4680).

AIAA Guidance, Navigation, and Control Confer-ence, Monterey, CA. http://www.aviationsystem-sdivision.arc.nasa.gov/publications/hitl/technical/surface_management_systems.pdf

Luffsey, W.S., & Wendel, .B. (1969, October). An airport surface traffic system. (AIAA-1969-1086). Paperpresented at AIAA 6th Annual Meeting & echnicalDisplay, Anaheim, CA, October 20-24, 1969.

Manning, C. A., & Broach, D. (1992). Identifying selection

criteria for operators of future automated systems. (FAAReport No. DO /FAA/AM-92/26). Washington,DC: Federal Aviation Administration Office of

Aviation Medicine.

McGarry, K. A. & Kerns, K. (2010). Results of a second(controller) human-in-the-loop simulation study ofautomated capabilities supporting surface trajectory-based operations. (M R100483). McLean, VA: heMI RE Center for Advanced Aviation SystemsDevelopment.

McGrew, K. S. (2009). CHC theory and the humancognitive abilities project: Standing on the shouldersof the giants of psychometric intelligence research.Intelligence , 37 , 1-10.

Merritt, S. M. & Ilgen, D. R. (2008). Not all trust iscreated equal: Dispositional and history-based trustin human-automation interactions. Human Factors,50, 194-210.

Morgan, C. (2010, June). A high-level description of airtraffic management decision support tool capabilities foNextGen surface operations.(MP100131). McLean,

VA: he MI RE Center for Advanced AviationSystem Development.

Morgan, C. & Burr, C. (2009). Airport surface trajectory-based operations mid-term concept of operations forsurface decision support tools (Draft coordinationbriefing). (MP090113). McLean, VA: he MI RECorporation Center for Advanced Aviation SystemsDevelopment.



46

National Aeronautics & Space Administration (NASA).(1999). Surface Management System research & devel-opment plan Volume I – echnical plan (SMS-101).Moffett Field, CA: NASA Ames Research CenterComputation Sciences Division. http://cdm.fly.faa.gov/archives/related/SMS_RD.pdf

National Aeronautics & Space Administration (NASA).(1999). Operations concept for the Surface Manage-ment System prototype (SMS-102). Moffett Field,CA: NASA Ames Research Center ComputationSciences Division. http://cdm.fly.faa.gov/archives/related/Ops_con.pdf

Nene, V. D. & Morgan, C. E. (2009). A mid-term concept ofoperations for a ower Flight Data Manager ( FDM). (MP090169). McLean, VA: MI RE Center for


Nickels, B. J., Bobko, P., Blair, M. D., Sands, W. A., &

artak, E. L. (1995). Separation and Control Hiring Assessment (SACHA) final job analysis report. (De-liverable Item 007A under FAA contract D FA01-91-C-00032.) Washington, DC: Federal Aviation

Administration Office of the Assistant Administratorfor Human Resources Management.

Nolan, M. S. (1994). Fundamentals of air traffic control (2nd Ed.). Belmont, CA: Wadsworth Publishing Co.

Northrop Grumman Norden Systems, Inc., Performanceechnologies International, Inc., FAA Air rafficraining (A X-100), & FAA Academy Air rafficraining Division (AMA-500). (2004). ask and

skills analysis report for air traffic control Airport Movement Area Safety System (AMASS) builds 1-6. Oklahoma City, OK: FAA Academy Air raffic

raining Division.

Parasuraman, R., Sheridan, . J., & Wickens, C. D.(2008). Situation awareness, mental workload, andtrust in automation: Viable, empirically supportedcognitive engineering constructs. Journal of CognitiveEngineering and Decision Making , 2 , 140–160. doi:10.1518/155534308X284417.

Pinska, E. (2006). An investigation of the head-up time attower and ground control positions. Bretigy-sur-Orge,France: EUROCON ROL Experimental Centre.

Pinska, E. & Bourgis, M. (2005). Behavioral analysis oftower controller activity. Bretigy-sur-Orge, France:EUROCON ROL Experimental Centre.

Ramos, R.A., Heil, M.C., & Manning, C.A. (2001).Documentation of validity for the A -SA computer-ized test battery, Volume I.(FAA Report No. DO /FAA/AM-01/5). Washington, DC: Federal Aviation

Administration Office of Aerospace Medicine.

Rapport, D. B., Yu, P., Griffin, K., & Daviau, C. (2009).Quantitative analysis of uncertainty in airport surfaceoperations. (AIAA-2009-6987). Paper presented atthe 9th AIAA Aviation echnology, Integration andOperations (A IO) Conference, Hilton Head, SCSeptember 21 – 23, 2009.

Schmeidler, N. F. & D’Avanzo, J. J. (1994).Developmentof staffing standards for air traffic control functions intower cabs, technical report. (Report delivered underFAA contract D FA01-89-Y-01307). Vienna, VA:Operational echnologies Services, Inc.

Schroeder, D.J., Broach, D., & Farmer, W.L. (1998).

Current FAA controller workforce demographics,future requirements, and research questions. In D.Broach (Ed.), Recovery of the FAA air traffic controlspecialist workforce (pp. 43-52) . (Report No. DO /FAA/AM-98/23). Washington, DC: Federal Avia-tion Administration Office of Aviation Medicine.

Sekhavat, S. (2009). Near-term concept of use (ConUse) for surface decision support tools. (M R090233).McLean, VA: he MI RE Center for Advanced

Aviation System Development.

Shaver, R. (2002). he growing congestion in the National Airspace System (NAS): How do we measure it? Arecurrent plans sufficient to constrain its growth? Ifnot, what else can we do? Air raffic Control Quar-terly , 10 (3), 169 – 195.

Stelzer, E. K. (2010). Human-in-the-loop concept evalua-tion of surface conformance monitoring automation. (M R100188). McLean, VA: MI RE Center for


enney, Y. V. & Pew, R. W. (2006). Situation awarenesscatches on: What? So what? Now what? In R. C.

Williges (Ed.).Review of Human Factors and Ergo-nomics , Vol. 2 (pp. 1-34). Santa Monica, CA: HumanFactors & Ergonomics Society.



47

eutsch, J., Scholte, J., Jakobi, J. Biella, M. Gilbert, A.,Supino, M., et al. (2009). European Airport Move-ment Management by A-SMGCS Part 2 Validationcomparative analysis report (Report 2-D6.7.1)(Contract REN/04/FP6AE/S07.45797/513522).Braunschweig, Germany: EMMA2 Project Partners.Retrieved November 22, 2010 from the EEMA2

website: http://www.dlr.de/emma2/maindoc/2-D671_Analysis_Report_V1.0.pdf

ruitt, . R. (2005). Electronic flight data in airport trafficcontrol towers: Literature review. (FAA Report No.DO /FAA/C -05/13). Atlantic City, NJ: FAA

William J. Hughes echnical Center.

ruitt, . R. (2006). Concept development and design de-scription of electronic flight data interfaces for airporttraffic control towers. (FAA Report No. DO /FAA/

C- N-06/17). Atlantic City, NJ: FAA William J.Hughes echnical Center.

ruitt, . R. & Muldoon, R. (2007). New electronic flightdata interface designs for airport traffic control tow-ers: Initial usability test. (FAA Report No. DO /FAA/ C-07/16). Atlantic City, NJ: FAA William

J. Hughes echnical Center.

ruitt, . R. & Muldoon, R. (2009). Comparing the owerOperations Digital Data System to paper flight progressstrips in zero-visibility operations. (FAA Report No.DO /FAA/ C-09/08). Atlantic City, NJ: FAA

William J. Hughes echnical Center.

ruitt, . R. & Muldoon, R. (2010). Data Communica-tions Segment 2 airport traffic control tower human-in-the-loop simulation. (FAA Report No. DO /FAA/ C-10/05). Atlantic City, NJ: FAA William

J. Hughes echnical Center.

Walton, D., Atkins, S., & Quinn, C. (2002, October).Human factors lessons learned from the second Sur- face Management System simulation. (AIAA 2002-5810). AIAA Aviation echnology Integration andOperations (A IO) Conference, Los Angeles, CA,October 1-3, 2002. Retrieved from the NASA AmesResearch Center website: http://www.aviationsys-temsdivision.arc.nasa.gov/publications/surface/

walton_10_02.pdf

Wargo, C. & Darcy, J.-F. (2011, March). Performanceof data link communications in surface managementoperations. Paper presented at the IEEE AerospaceConference, March 5-12, 2011, Big Sky, M .

Wickens, C., D., Mavor, A. S., & McGee, J. P. (Eds.).(1997). Flight to the future: Human factors in air trafficcontrol. Washington, DC: National Academy Press.

Williams, J., Hooey, B., & Foyle, D. (2006, August). 4-Daxi clearances: Pilots’ usage of time- and speed-

based formats. (AIAA-2006-6611). Paper presentedat the AIAA Modeling and Simulation echnologiesConference, Keystone, CO, August 21-24, 2006.



A1

Worker Requirement Description/Definition Mean SDTolerance for High-Intensity Work

Situations

The ability to perform effectively and think clearlyduring heavy work flow.

4.60 0.62

Oral Communication The ability to speak clearly and concisely to individualsso they understand what is being communicated.Projecting a confident tone of voice is an importantcomponent of this ability.

4.56 0.63

Active Listening The ability to hear and comprehend spoken information.This ability requires an individual to recognize or pickout pertinent auditory information.

4.53 0.66

Prioritization The ability to identify the activities that are most criticaland require immediate attention. This involves a constantevaluation of new information followed by re-

prioritization of job activities.

4.53 0.70

Concentration The ability to focus on job activities amid distractions for

short periods of time.

4.50 0.70

Planning The ability to determine the appropriate course(s) ofaction to take in any given situation.

4.45 0.69

Dynamic Visual-Spatial The ability to deal with dynamic visual movement. 4.40 0.71Flexibility (InformationProcessing)

The ability to find new meanings for stimuli, to combinestimulus attributes to come up with new and differentsolution protocols, and to employ flexible ways ofrelating new information to stored knowledge.

4.37 0.80

Thinking Ahead The ability to anticipate or recognize problems beforethey occur and to develop plans to avoid problems. Thisincludes thinking about what might happen.

4.35 0.81

Scanning The ability to quickly and accurately search forinformation on a computer screen, radar scope, orcomputer print-out.

4.33 0.79

Situational Awareness Being cognizant of all information within a fourdimensional space (i.e., Separation Standards plus time).This involves the ability to "understand" the airspace asan integrated whole (e.g., getting the picture).

4.33 0.86

Reasoning The ability to apply available information in order tomake decisions, draw conclusions, or identify alternativesolutions.

4.31 0.74

Short-term Memory The ability to remember pertinent information within a brief period of time (less than one minute). Examples ofinformation include call signs and keywords.

4.30 0.80

Taking Charge The ability to take control of a situation--to reach out andtake correct action.

4.30 0.73

Visualization The ability to translate material into a visualrepresentation of what is currently occurring.

4.26 0.85

Projection The ability to translate material into a visualrepresentation of what will occur in the future.

4.26 0.84

Time Sharing The ability to perform two or more job activities at thesame time.

4.26 0.78

Rule Application The ability to apply learned rules to the real worksituation.

4.25 0.79

APPENDIX A

Worker requirements identied by Nickels et al. (1995), sorted in descending order of mean (average)importance to successful controller performance



A2

Worker Requirement Description/Definition Mean SDCreativity The ability to identify new or novel solutions to potential

problems when existing or established solutions nolonger apply.

4.23 0.80

Problem Identification The ability to identify a potential or existing problem andto identify the variables used in solving the problem.

4.23 0.83

Flexibility

(Stability/Adjustment)

The ability to adjust or adapt to changing situations or

conditions.

4.22 0.77

Perceptual Speed andAccuracy

The ability to perceive visual information quickly andaccurately and to perform simple processing tasks with it(e.g., comparison).

4.13 0.83

Long-term Memory The ability to remember pertinent information much laterin time (longer than 10 minutes). Examples ofinformation include maps and separation procedures.

4.11 0.92

Self-awareness An internal awareness of your actions and attitudes. Thisincludes knowing your limitations.

4.11 0.78

Working Cooperatively The willingness to work with others to achieve a commongoal. This includes a willingness to voluntarily assistanother controller if the situation warrants.

4.10 0.81

Sustained Attention The ability to stay focused on a task(s) for long periods of

time (over 60 minutes).

4.07 0.94

SummarizingInformation

The ability to summarize and consolidate informationmost relevant to the situation.

4.06 0.83

Self-Monitoring/Evaluating

The ability and willingness to check your own work performance, evaluate the effectiveness of yourdecisions, and alter your performance if necessary.

4.04 0.84

Self-Confidence A belief that you are the person for the job and knowingthat your processes and decisions are correct.

4.02 0.78

Internal Locus ofControl

Believes that individuals have influence over the outcomeof an event; takes responsibility for outcomes.

3.96 0.88

Task Closure/Thoroughness

The ability to continue an activity to completion throughthe coordination and inspection of work.

3.96 0.85

Reading The ability to read and understand written information(e.g., ATCS documents, manuals).

3.95 0.89

Recall from Interruption The ability to recall a deferred or interrupted action when priorities permit, and to be able to resume the actionappropriately (Ammerman, 1983).

3.92 0.90

Decisiveness The ability to make effective decisions in a timelymanner.

3.92 0.90

Verbal Reasoning Ability to perceive and understand principles governingthe use of verbal concepts and symbols.

3.89 0.86

Composure The ability to think clearly in stressful situations. 3.88 0.92Translating Information The ability to translate symbols/symbolic abbreviations

into meaningful information.3.88 0.98

Interpersonal Tolerance The ability to accommodate or deal with differences in personalities, criticisms, and interpersonal conflicts in thework environment.

3.83 0.92

Movement Detection The ability to detect physical movement of objects and to judge their direction.

3.80 1.03

Execution The ability to take timely action in order to avoid problems and to solve existing problems.

3.80 1.02

Attention to Detail The ability to recognize and attend to the details of the job that others might overlook.

3.80 0.85

Professionalism The ability to establish respect and confidence in yourabilities among other controllers.

3.79 0.87



A3

Worker Requirement Description/Definition Mean SDVisuospatial Reasoning Ability to perceive and understand principles governing

relationships among several figures.3.78 0.97

Chunking Ability to organize stimuli into meaningful groups orunits.

3.78 1.00

Self-esteem Having a positive opinion/image of oneself. 3.77 0.88Behavioral Consistency The ability to behave consistently at work (e.g., dealing

with coworkers in a consistent manner; consistently usingthe correct phraseology).

3.76 0.85

Interpreting Information The ability to put information into meaningful terms. It isthe ability to recognize the implications of a statement orcondition (e.g., cold front).

3.68 0.86

Translation ofUncertainty

The ability to assign a subjective probability regardingthe likelihood of an event occurring; The ability to use

probabilities to identify optimal courses of action (CTA,1988)

3.67 1.01

Commitment to the Job The desire to be an ATCS and work hard to besuccessful.

3.53 0.92

Motivation The desire to motivate oneself through challenges on the job and to progress to a higher level of skill.

3.47 0.93

Written Communication The ability to write legibly and accurately (e.g., stripmarkings). 3.40 0.96

Intermediate-termMemory

The ability to remember pertinent information over a 1-10 minute period.

3.32 1.13

3-D Mental Rotation The ability to identify a three-dimensional object whenseen at different angular orientations either within the

picture plane or about the axis in depth.

3.24 1.20

2-D Mental Rotation The ability to identify a two-dimensional figure whenseen at different angular orientations.

3.20 1.12

Realistic Orientation Prefers dealing with activities which have tangible andmeasurable consequences; enjoys activities which requireskill; is reinforced by accomplishing realistic tasks.

3.19 1.02

Mechanical Reasoning Ability to perceive and understand the relationship of

physical forces and mechanical elements in a prescribedsituation.

3.15 1.00

Mathematical Reasoning Ability to perceive and understand principles governingthe use of quantitative concepts and symbols.

3.08 1.01

Numeric Ability(Add/Subtract)

The ability to quickly and accurately perform basic mathoperations (primarily addition and subtraction).

2.91 1.02

Angles This is the ability to apply the principles of geometry toangles and computations involving angles. The abilityinvolves both the speed and accuracy of computation.

2.79 1.13

Numeric Ability(Multiply/Divide)

The ability to quickly and accurately perform basic mathoperations (primarily multiplication and division).

2.63 1.04

2013 aptitudes requeridas para cta en 2018 faa

Documents