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Sensitivity analysis of potential capacity and safety of flow corridor to self-separation parameters

Published online by Cambridge University Press:  16 October 2018

B. Ye Open the ORCID record for B. Ye [Opens in a new window] ,
J. Shortle ,
W. Ochieng  and
T. Yong
B. Ye*
Affiliation:
College of Civil AviationNanjing University of Aeronautics and AstronauticsNanjingChina
J. Shortle
Affiliation:
Center for Air Transportation Systems ResearchDepartment of Systems Engineering & Operations ResearchGeorge Mason UniversityFairfax, VAUSA
W. Ochieng
Affiliation:
Imperial College LondonLondonUK
T. Yong
Affiliation:
National Key Laboratory of Air Traffic Flow ManagementNanjing University of Aeronautics and AstronauticsNanjingChina
*
[email protected]
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Abstract

A flow corridor is a new class of trajectory-based airspace that encloses groups of flights which fly along the same path in one direction and accept responsibility for separation from each other. A well-designed corridor could reduce the airspace complexity, decrease the workload of air traffic controllers and increase the airspace capacity. This paper analyses the impact of different self-separation parameters on capacity and conflicts of the flow corridor. Both the quantitative impact and interaction effects of pairs of parameters are evaluated using the combined discrete-continuous model and Monte Carlo simulation method. The simulation results show that although the initial separation is the dominating factor, the interactions between initial separation and separation buffer, minimum separation, extra switch buffer, extra threshold buffer and velocity difference threshold also have some significant impacts on the capacity and conflicts for the flow corridor.

Keywords

Air traffic managementFlow corridorSelf-separationMonte Carlo simulation
Type
Research Article
Information
The Aeronautical Journal , Volume 123 , Issue 1259 , January 2019 , pp. 56 - 78
Copyright
© Royal Aeronautical Society 2018 

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References

1. JPDO, Concept of Operations for the Next Generation Air Transportation System (Version 3.2), 2010.Google Scholar
2. Alipio, J., Castro, P., Kaing, H., Shahid, N., Sherzai, O., Donohue, G.L. and Grundmann, K. Dynamic airspace super sectors (DASS) as high-density highways in the sky for a new US air traffic management system. Proceedings of the 2003 IEEE Systems and Information Engineering Design Symposium, 24–25 April 2003, Charlottesville, USA, pp 57-66.Google Scholar
3. Yousefi, A., Donohue, G.L. and Sherry, L. High-volume tube-shape sectors (HTS): a network of high capacity ribbons connecting congested city pairs. Proceedings of the 23rd Digital Avionics Systems Conference (DASC 2004), 24–28 October 2004, Salt Lake City, USA, pp 594–593, 591.Google Scholar
4. Hering, H. Air traffic freeway system for Europe. EEC-Note-No. 20/05, 2005.Google Scholar
5. Wing, D.J., Smith, J.C. and Ballin, M.G. Analysis of a dynamic multi-track airway concept for air traffic management, NASA/TP-2008-215323, 2008.Google Scholar
6. Yousefi, A. and Zadeh, A.N. Dynamic allocation and benefit assessment of NextGen flow corridors, Transportation Research Part C: Emerging Technologies, 2013, 33, pp 297–310.Google Scholar
7. ICAO, Manual on Global Performance of the Air Navigation System (First Edition), Doc 9883, 2009.Google Scholar
8. Sridhar, B., Grabbe, S., Sheth, K. and Bilimoria, K. Initial study of tube networks for flexible airspace utilization. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, 21–24 August 2006, Keystone, USA, pp 6768.Google Scholar
9. Guichard, L., Guibert, S., Dohy, D. and Grau, J. A human in the loop experiment to assess the dual airspace concept. Proceedings of the 2nd International Conference on Research in Air Transportation (ICRAT 2006), June 24–28 2006, Belgrade, Serbia and Montenegro, pp 1–11.Google Scholar
10. Yousefi, A., Lard, J. and Timmerman, J. Nextgen flow corridors initial design, procedures, and display functionalities. Proceedings of the 2010 IEEE/AIAA 29th Digital Avionics Systems Conference (DASC 2010), 3–7 October 2010, Salt Lake City, USA, pp 4.D.1-1–4.D.1-19.Google Scholar
11. Mundra, A.D. and Simons, E.M. Self-separation corridors. Proceedings of the 2007 IEEE/AIAA 26th Digital Avionics Systems Conference (DASC 2007), 21–25 October 2007, Dallas, USA, pp 3.C.3-1–3.C.3-11.Google Scholar
12. Xue, M. and Zelinski, S. Complexity analysis of traffic in corridors-in-the-sky. Proceedings of the 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference, 13–15 September 2010, Fort Worth, USA, pp 9112.Google Scholar
13. Xue, M. and Kopardekar, P.H. High-capacity tube network design using the Hough transform, J Guidance, Control, and Dynamics, 2009, 32, pp 788–795.Google Scholar
14. Xue, M. Design analysis of corridors-in-the-sky. Proceedings of the AIAA Guidance, Navigation, and Control Conference, 10–13 August 2009, Chicago, USA, pp 5859.Google Scholar
15. Kotecha, P. and Hwang, I. Optimization based tube network design for the next generation air transportation system (NextGen). Proceedings of the AIAA Guidance, Navigation, and Control Conference, 10–13 August 2009, Chicago, USA, pp 5860.Google Scholar
16. Sheth, K.S., Islam, T.S. and Kopardekar, P.H. Analysis of airspace tube structures. Proceedings of the IEEE/AIAA 27th Digital Avionics Systems Conference (DASC 2008), 26–30 October 2008, St. Paul, USA, pp 3.C.2-1–3.C.2-10.Google Scholar
17. Hoffman, R. and Prete, J. Principles of airspace tube design for dynamic airspace configuration. Proceedings of the 26th Congress of ICAS and 8th AIAA ATIO, 14–19 September 2008, Alaska, USA, pp 8939.Google Scholar
18. Gupta, G., Sridhar, B. and Mukherjee, A. Freeways in the sky: Exploring tube airspace design through mixed integer programming. Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, 18–21 August 2008, Honolulu, USA, pp 6824.Google Scholar
19. Ye, B., Hu, M. and Shortle, J. Collision risk-capacity tradeoff analysis of an en-route corridor model, Chinese J Aeronautics, 2014, 27, pp 124–135.Google Scholar
20. Blom, H.A. and Bakker, G. Safety evaluation of advanced self-separation under very high en route traffic demand, J Aerosp Information Systems, 2015, 12, pp 413–427.Google Scholar
21. Welch, J. En Route Sector Capacity Model Final Report, ATC-426, 2015.Google Scholar
22. Zhang, Y., Shortle, J. and Sherry, L. Methodology for collision risk assessment of an airspace flow corridor concept, Reliability Engineering & System Safety, 2015, 142, pp 444–455.Google Scholar
23. Belle, A., Sherry, L., Yousefi, A. and Lard, J. Analysis of performance of Q routes for establishing future design criteria. Proceedings of the 2010 Integrated Communications Navigation and Surveillance Conference (ICNS), 11–13 May 2010, Herndon, USA, pp B2-1–B2-7.Google Scholar
24. ICAO, Aircraft Operations – Volume2 Construction of Visual and Instrument Flight Procedure (Sixth Edition), Doc 8168, 2014.Google Scholar
25. Glover, W. and Lygeros, J. A multi-aircraft model for conflict detection and resolution algorithm evaluation. IST–2001–32460, 2004.Google Scholar
26. Palm, W.J. System dynamics. McGraw-Hill Higher Education, USA; 2005.Google Scholar
27. EEC, User manual for the Base of Aircraft Data (BADA) Revision 3.11, EEC Technical Report 130416, 2013.Google Scholar
28. ICAO, Procedures for Air Navigation Services: Air Traffic Management (Sixteenth Edition), Doc 4444, 2016.Google Scholar