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The Role of Workload for Work Organisation in a Remote Tower Control Center

This study examines the impact of workload on work organisation in a remote tower control center. It explores the potential of automation technologies such as virtual reality and immersive visualization. The study presents the background, hypotheses, methodology, results, and discussion of the findings.

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The Role of Workload for Work Organisation in a Remote Tower Control Center

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  1. The Role of Workload for Work Organisation in a Remote Tower Control CenterInstitute for Flight Guidance, German Aerospace Center (DLR)C. Möhlenbrink, A. Papenfuss, J. Jakobi

  2. The Role of Workload for Work Organisation in a Remote Tower Control Center Overview • Background • Introduction • Hypotheses • Method • Results • Discussion • Conclusion

  3. BackgroundConcept Study Vito (Virtual tower) • What`s the potential of automation for tower control? • Technologies for „Virtuel Reality“ • Novel Videotechnologies • Immersive Visualisation • Head-mounted displays • Telepresence • „Wearable computing“

  4. BackgroundRApTOr (2005-2007) RTO-Experimental System • Installed at Braunschweig airport • Prove of technical feasibility • Experimental system running since 2005 • 4 Camera / Zoomcamera • Resolution requirement: 30cm/500 m • Panoramacamera System (4 cameras + PTZ) • Gbit/s – fiber optics LAN RTO-Console • “Augmented Vision” Videopanorama

  5. BackgroundRAiCe: Remote Tower Operation Center (start 2008) Research question of interest: • How can air traffic control be organized in a control center • What is the role of workload for the evaluation of new ATC-concepts • Is it possible, one controller operating two small-sized airports? Approach: • High fidelity simulations as work probe for a remote tower center Erfurt Braunschweig

  6. Def. Workload: [Goper & Donchin 86] Limitation on the capacity of an information processing system. taskload versus workload timeline models strategy shifs Influencing factors in aerodrome control: [Vogt et al. 2006] Aerodrome complexity VFR traffic Calculated take-off times Staffing Technological support IntroductionWorkload Concept

  7. IntroductionDesigning a Remote Tower Center weather data integrated (far-view) (1) Working condition: Single Operator Far-view Braunschweig BWE BWE BWE BWE RADAR BWE RADAR ERF Far-view Erfurt ERF ERF ERF ERF flight strips: black: Depart. EDDE yellow: Arrival EDDE black: Depart. EDVE yellow: Arrival BWE Zoomcamera EDDE Zoomcamera EDVE

  8. IntroductionDesigning a Remote Tower Center (2) Working Condition: Controller (PL) operating BWE Controller (PL) operating ERF Weather data integrated (far-view) Far-view Braunschweig ERF ERF ERF RADAR ERF RADAR BWE ERF Far-view Erfurt BWE BWE BWE BWE Flight strips BWE: black: Departure BWE yellow: Arrival BWE Flight stirps ERF: black: Departure ERF yellow: Arrival EDDV + Zoomcamera ERF + Zoomcamera BWE

  9. IntroductionDesigning a Remote Tower Center (3) Working Condition: Team Variant PL (ERF + BWE) and CO (ERF + BWE) Weather data integrated (far-view) Far-view Braunschweig ERF ERF ERF RADAR ERF RADAR BWE ERF Far-view Erfurt BWE BWE BWE BWE Flight strips BWE: black: Departure BWE yellow: Arrival BWE Flight stirps ERF: black: Departure ERF yellow: Arrival EDDV + Zoomcamera ERF + Zoomcamera BWE

  10. IntroductionDesigning a Remote Tower Center

  11. IntroductionTechnological Support Augmented Vision Aspects Control and surveillance! Aim: Reducing Head-down times • Callsign: - Integration into the far-view - based on transponder data • Alternative: - Movement detection - based on a Live-video: VP-CGD D-EAF

  12. Identification of safety-critical situations Modified Cooper-Harper Scale Expert rater: • Hierachical structure of questions: • No major influence • Capacity • „workload“ • impossible

  13. Hypothesestraffic hypotheses • H1a: For ISA workload ratings (2 min interval) it is expected that the workload ratings are higher for the heavy traffic than for low traffic. • H1b: Under low traffic, the single operator has significantly higher workload ratings compared to all other working conditions. The same assumption is made for heavy traffic. • H1c: From a theoretical point of view it is predicted that the workload of the single controller operating two airports under low traffic load is not significantly higher, than the workload of controllers operating one airport with low traffic.

  14. Hypothesesaugmented vision hypotheses and expert ratings H2 Augmented vision hypotheses • For the between-subject-factor it is predicted that working with the callsign displayed on the video, workload is significantly lower compared to working without the callsign in the video. It is assumed that this effect is independent of the working positions or traffic load. Expert Ratings • Identifying crucial constraints for the Remote Tower Center Concepts • safety critical situation, when one controller is operating two airports

  15. Data recording: process data: * throughput Subjective data: * ISA workload ratings * Shape questionnaires * post-run interviews * final questionnaire Objective data: * eye-data recordings * radio com Interact Heatmap MethodHigh-fidelity simulation: Remote Tower Center

  16. Sample: 12 controllers Deutsche Flugsicherung (DFS) Age: mean=34.6 [25,60] years valide controller license Movements n < 15.000 IFR movements 2 < 35.000 IFR movements 6 > 100.000 IFR movements 4 MethodSample

  17. Mixed traffic IFR & VFR total 16 aircraft raising traffic load over time: - 1st half, low traffic load - 2nd half, heavy traffic load Events: Two parallel landings Two paralle starts MethodTraffic Scenarios

  18. MethodIdentification of critical situations Modified Cooper-Harper Scale S1: Landing on airport A + taxing traffic on airport B S2: Similar call signs for aircraft of airport A and B S3: Simultaneous pilot requests at airport A and B S4: Simultaneous starts at airport A and B S5: Simultaneous landing at airport A and B S6: Conflict on airport A, start/landing on airport B

  19. MethodInstantaneous Self-Assessment Scale „Online“ Workload 5

  20. MethodExperimental Design

  21. Main effect traffic load: heavy traffic  higher workload low traffic:  lower workload Main effect position: TL, CO, SC  higher workload BC, EC  lower workload Interaction effect traffic*position BC, EC  WL: low ~ heavy traffic TL, CO, SC  low traffic  low WL  heave traffic  high WL ResultsTraffic (low, high) ISA-Workload-Ratings

  22. Main effect augmentation: callsign  lower workload no callsign  higher workload Main effect augmentation*position: TL, CO, SC  callsign effect BC, EC  no callsign effect Additional analysis: Augmentation (between-subject factor) Correlation (team variable, augm.) r=.87* ResultsAugmented Vision (yes, no) ISA-Workload-Ratings

  23. ResultsRatings for critical situations

  24. One controller operating two airports * workload raises * task prioritization * two mental traffic pictures? Each controller operating one airport * workload low * task prioritization * mental traffic pictures? * social aspects? Low traffic periods Each controller operating one airport * workload raises * timing conflicts * two mental traffic pictures? * redundancy DiscussionRole of Workload for Work Organisation Single operator One operator for each airport Team (PL,CO)

  25. Previous studies for remote tower  no callsign effect (within-subject design) Operating two airports  callsign effect (training + between subject design) more demanding  callsign effect? problem: high correlation with team variable head-down time issue Seperation of information DiscussionRole of Augmented Vision Effect VP-CGD D-EAF

  26. Expert judgment (here: online monitoring of one controller operating two airports) Smooth operations: parallel starts (ok) parallel landings (ok) …but 33 situations influencing safety, due to…? 28 situations safety critical, due to…? Shortcomings: No comparable data for other working conditions Role of redundancy in ATC today DiscussionIdentification of Critical Situations for the RTC

  27. Workload concept insufficient for the evaluation of work design variants Workload as an independent variable influencing controller strategies Work methods offered by different staffing concepts Role of safety critical situations Future work Deeper analysis of expert judgements robust traffic concepts for RTC? Conclusion

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