Hostname: page-component-848d4c4894-xfwgj Total loading time: 0 Render date: 2024-07-04T13:14:32.487Z Has data issue: false hasContentIssue false
  • English
  • Français

Strategic Conflict Detection and Resolution Using Aircraft Intent Information

Published online by Cambridge University Press:  01 December 2009

Marco Porretta ,
Wolfgang Schuster ,
Arnab Majumdar  and
Washington Ochieng
Marco Porretta*
Affiliation:
(Imperial College London)
Wolfgang Schuster
Affiliation:
(Imperial College London)
Arnab Majumdar
Affiliation:
(Imperial College London)
Washington Ochieng
Affiliation:
(Imperial College London)
*
(Email: m.porretta@imperial.ac.uk)
Get access Rights & Permissions [Opens in a new window]

Abstract

A number of automated decision support tools will be required in the future air traffic management system to enable continued provision of safe and efficient services in increasingly congested skies. In particular, Conflict Detection and Resolution (CDR) tools should allow for early detection of possible conflicts and propose safe and efficient resolution manoeuvres to avoid loss of separation. However, current approaches in the open literature not only use different levels of aircraft intent information but also make a number of assumptions on models of aircraft motion. Furthermore, information relevant to aircraft performance is often not considered with the consequence of the resulting resolution strategies being potentially unreliable. This paper presents an enhanced, strategic, pairwise, performance-based and distributed CDR algorithm. It accounts for the weaknesses of current approaches by using the maximum level of aircraft intent information together with a novel trajectory prediction model. Numerical results for representative conflict scenarios show that the proposed CDR method is able to generate conflict-free trajectories for participating aircraft while taking into account the actual aircraft capabilities to perform the recommended resolution manoeuvres.

Keywords

Conflict DetectionConflict ResolutionTrajectory Prediction
Type
Research Article
Information
The Journal of Navigation , Volume 63 , Issue 1 , January 2010 , pp. 61 - 88
Copyright
Copyright © The Royal Institute of Navigation 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Beers, C. S. and Huisman, H.(2002), Transitions between Free Flight Airspace and Managed Airspace, A controllers' perspective, NLR-TP-2002-433, National Aerospace Laboratory, NLR, The Netherlands.Google Scholar
Bilimoria, K., Sridhar, B., and Chatterji, G.(1996), Effects of Conflict Resolution Maneuvers and Traffic Density for Free Flight, Proceedings of the AIAA Guidance, Navigation, and Control Conference, San Diego, CA, USA.CrossRefGoogle Scholar
Brudnicki, D. J.; Lindsay, K. S.; McFarland, A. L.(1997), “Assessment of field trials, algorithmic performance, and benefits of the User Request Evaluation Tool conflict probe,” 16th AIAA/IEEE Digital Avionics System Conference (DASC), 26–30 October 1997, Irvine, CA, USA.Google Scholar
EUROCONTROL (1998), Air Traffic Management Strategy for 2000+, Volumes 1 and 2, EUROCONTROL, Brussels.Google Scholar
EUROCONTROL (2002), Investigating Air Traffic Controller Conflict Resolution Strategies, document number ASA.01.CORA.2.DEL04–B.RS.Google Scholar
EUROCONTROL (2003), Use of Safety Nets in Risk Assessment and Mitigation in ATM, Safety Regulation Commission (SRC) Policy Document 2, Reference SRC POL DOC 2, Brussels, Belgium, April 2003.Google Scholar
EUROCONTROL (2004a), User Manual for the Base of Aircraft Data (BADA), Revision 3.6, EUROCONTROL Experimental Centre (EEC) Note 10/04, July 2004.Google Scholar
EUROCONTROL (2004b), Challenges to Growth 2004 Report (CTG04), Document Identifier EUROCONTROL/ESC/SNP/PERF/Doc10, EUROCONTROL, Brussels, Belgium, December 2004.Google Scholar
EUROCONTROL (2006), Long-Term Forecast: IFR Flight Movements 2006–2025, DAP/DIA/STATFOR Doc216.Google Scholar
EUROCONTROL (2007), The ATM Target Concept. Document No. DLM-0612-001-02-00, Deliverable D3, “SESAR”Google Scholar
EUROCONTROL (2008), Performance Review Commission, Performance Review Report Covering the Calendar Year 2007 (PRR 2007), EUROCONTROL Performance Review Commission, Brussels, Belgium, 2008.Google Scholar
Dowek, G., Munoz, C., and Carreno, V.(2005), Provably Safe Coordinated Strategy for Distributed Conflict Resolution, Proceedings of the AIAA Guidance, Navigation, and Control Conference, San Francisco, CA, USA.CrossRefGoogle Scholar
Dowek, G. and Munoz, C.(2007), Conflict Detection and Resolution for 1,2, …, N Aircraft, In the Proc. of 7th American Institute of Aeronautics and Astronautics Aviation Technology, Integration and Operation Conference, Belfast.CrossRefGoogle Scholar
Glover, W. and Lygeros, J.(2003), A Multi Aircraft Model for Conflict Detection and Resolution Algorithm Validation, Technical Report WP1, Deliverable D1.3, “HYBRIDGE” Project.Google Scholar
Hoekstra, J. M.(2001), Designing for Safety: the Free Flight Air Traffic Management Concept, PhD Thesis, TU Delft.Google Scholar
Hoekstra, J. M.(2002), Free Flight with Airborne Separation Assurance, NLR-TP-2002-170, NLR, The Netherlands.Google Scholar
Hwang, I., Kim, J., and Tomlin, C.(2007), Protocol–Based Conflict Resolution for Air Traffic Control, Air Traffic Control Quarterly, 15, 1, 1–34.CrossRefGoogle Scholar
ICAO (1964), Manual of the ICAO Standard Atmosphere, ICAO document No 7488, 2nd Edition.Google Scholar
Kuchar, J. and Yang, L. C.(2000), A review of Conflict Detection and Resolution Methods, IEEE Transactions on Intelligent Transportation Systems, 1, 4, 179–189.CrossRefGoogle Scholar
Majumdar, A. and Ochieng, W. Y.(2002), The factors affecting air traffic controller workload: a multivariate analysis based upon simulation modelling of controller workload, Transportation Research Record, 1788, 58–69.CrossRefGoogle Scholar
Porretta, M., Dupuy, M. D., Schuster, W., Majumdar, A., Ochieng, W.(2008), “Performance Evaluation of a Novel 4D Trajectory Prediction Model for Civil Aircraft,” The Journal of Navigation, 61, 393–420.CrossRefGoogle Scholar
SESAR Consortium (2007), Air Transport Framework, The Performance Target, SESAR Definition Phase, Del. 2.Google Scholar
Vilaplana Ruiz, M. A.(2005), COURAGE Domain Analysis, Deliverables D2.1 and D3.1, The Boeing Research & Technology Europe, Madrid, Spain (http://www.eurocontrol.int/moc-faa-euro/public/standard_page/TIMS.html).Google Scholar