Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-22T11:11:07.306Z Has data issue: false hasContentIssue false

Conflict detection and resolution algorithms for UAVs collision avoidance

Published online by Cambridge University Press:  27 January 2016

G. Migliaccio*
Affiliation:
University of Pisa, Pisa, Italy
G. Mengali*
Affiliation:
University of Pisa, Pisa, Italy
R. Galatolo*
Affiliation:
University of Pisa, Pisa, Italy

Abstract

Collision-avoidance is a safety-critical requirement to operate UAVs in non-segregated airspaces. In case of communication problems between a UAV and the corresponding pilot-in-command, a technology is required onboard the UAV to implement a capability to detect and avoid collision-hazards even autonomously. After an introduction to the problem of developing a so-called sense-and-avoid system and its avoid-function, this work presents a solution in terms of algorithms to implement the above capability. To detect and resolve potential mid-air conflicts, a geometric deterministic approach has been utilised: an intruder is modeled trough a moving-ellipsoid and a four-dimensional approach in the time-space domain provides the solution. The approach makes use of kinematics information to detect potential conflicts and to provide actions for conflict resolution, such as speed-changes in intensity and/or direction. The proposed solution also enables the UAV to meet the applicable vertical and horizontal minima of separation and to comply with real-time constraints.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2014 

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

1. De Garmo, M. and Nelson, G.M. Prospective unmanned aerial vehicle operations in the future national airspace system, AIAA paper 2004-6243, 4th Aviation Technology, Integration and Operation (ATIO) Forum, 20-22 September 2004.Google Scholar
2. Lacher, A., Zeitlin, D.A., Maroney, D., Marklin, K., Ludwig, D. and Boyd, J. Airspace integration alternatives for Unmanned Aircraft, Paper presented at AUVSI’s Unmanned Systems Asia-Pacific 2010 Conference, Pan Pacifc Singapore, 29 January – 1 February 2010.Google Scholar
3. Sense And Avoid (SAA) for Unmanned Aircraft System (UAS), Final Report of the FAA Sponsored ‘Sense-And-Avoid’ Workshop, October 2009.Google Scholar
4. EUROCONTROL, EUROCONTROL Specifications for the use of Military Unmanned Aerial Vehicle as Operational Traffic Outside Segregated Airspaces, SPEC-0102, July 2007.Google Scholar
5. Sense and Avoid requirements for unmanned aerial vehicle systems operating in non-segregated airspace, NATO Unclassified, 2008.Google Scholar
6. ICAO, Global Air Traffc Management Operational Concept, Doc 9854, 1st ed, International Civil Aviation Organization, 2005.Google Scholar
7. ICAO, Annex 2 to the Convention on International Civil Aviation – Rules of the Air, 10th Edition, International Civil Aviation Organization, 1990.Google Scholar
8. Federal Aviation Administration, Title 14 of the Code of Federal Regulations, Part 91, Sec. 91.113 Right of Way Rules: Except water operations, 1 January 2011.Google Scholar
9. Kuchar, J.K. and Yang, L.C. A review of conflict detection and resolution modeling methods, IEEE Transaction on Intelligent Transportation Systems, December 2000, I, (4), pp 179189.Google Scholar
10. Mujumdar, A. and Padhi, R. Evolving philosophies on autonomous obstacle/collision avoidance of unmanned aerial vehicles, J Aerospace Computing, Information, and Communication, 8, (2), pp 1741, 2011.Google Scholar
11. Carbone, C., Ciniglio, U., Corraro, F. and Luongo, S. A Novel 3D Geometric Algorithm for Aircraft Autonomous Collision Avoidance, proceedings of the 45th IEEE Conference on Decision and Control, pp 15801585, San Diego, CA, USA, December 2006.Google Scholar
12. Han, S.C., Bang, H. and Yoo, C.S. Proportional Navigation-based Collision Avoidance for UAVs, Int J Control, Automation and Systems, August 2009, 7, (4), pp 553565.Google Scholar
13. Lai, C.K. and Whidborne, J.F. Real-Time Trajectory Generation for Collision Avoidance with Obstacle Uncertainty, AIAA paper 2011-6598, Guidance, Navigation and Control Conference, Portland, Oregon, USA, August 2011.Google Scholar
14. Standard Specification for Design and Performance of an Airborne Sense-And-Avoid System, ASTM Standard F2411-07, 2007.Google Scholar
15. Fasano, G., Accardo, D., Moccia, M., Carbone, C., Ciniglio, U., Corraro, F. and Luongo, S. Multi-sensor-based fully autonomous non-co-operative collision avoidance system for unmanned aerial vehicles, J Aerospace Computing, Information and Communication, October 2008, 5, (10), pp 338360.Google Scholar
16. Zeitlin, D.A. Tradeoffs for achieving a Sense and Avoid capability for unmanned aircraft system, AIAA paper 2010-3340, AIAA Infotech@Aerotech 2010, 20-22 April 2010.Google Scholar
17. Rousseau, M., Ratton, L. and Fournet, T. Multiple sensor tracking in a sense and avoid context, ICAS paper 2010-6.5.2, 27th International Congress of the Aeronautical Sciences, Nice, France, 19-24 September 2010.Google Scholar
18. Chakravarthy, A. and Ghose, D. Obstacle Avoidance in a Dynamic Environment: A Collision Cone Approach, IEEE Transaction on Systems, Man, and Cybernetics, Part A: Systems and Humans, September 1998, 28, (5).Google Scholar
19. Paul, T., Krogstad, T.R. and Gravdahl, J.T. UAV Formation Flight using 3D Potential Field, 16th Mediterranean Conference on Control and Automation, Ajaccio, France, 25-27 June 2008.Google Scholar
20. ICAO, Annex 11 to the Convention on International Civil Aviation – Air Traffic Services, 13th ed, International Civil Aviation Organization, July 2001.Google Scholar
21. Federal Aviation Administration, Introduction to TCAS II version 7 November 2000.Google Scholar
22. ICAO, Airborne Collision Avoidance System (ACAS) manual, Doc 9863, 1st ed, International Civil Aviation Organization, 2006.Google Scholar