Abstract
This paper presents a collision avoidance (CA) algorithm for cooperative unmanned aerial vehicles (UAVs) sharing three-dimensional airspace. The method based on geometric optimization model aims to provide feasible optimal trajectory for the selected UAV, with a local optimization scope at operational level. It generates optimal flight trajectory by the objective function (the integration equation of distance, time and track adjustment costs) in response to a set of restrictions (performance, state and distance constraints) reducing the solution space. The CA maneuver has been validated with various simulations, owning such advantages as optimization spending a minimal cost, robustness considering the global traffic situation, scalability possessing explicit coordinates of waypoints and efficiency in implementing different tests of tuning parameters.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Rajagopal S., Ganguli R.: Multidisciplinary design optimization of long endurance unmanned aerial vehicle wing. CMES Comput. Model. Eng. Sci. 81(1), 1–34 (2011)
Federal Aviation Administration: Introduction to TCAS II version 7.1. USA (2011)
Hoekstra, J.; Ruigrok, R.; Gent, R.V.; Visser, J.; Gijsbers, B.; Clari, M.V.; Heesbeen, W.M.; Hilburn, B.G.; Groeneweg, J.; Bussink, F.L.: Overview of NLR Free Flight Project 1997–1999. Tech. Report NLRCR-2000-227, National Aerospace Laboratory (2000)
Bilimoria, K.D.; Sridhar, B.; Chatterji, G.B.; Sheth, K.S.; Grabbe, S.R.: FACET: Future ATM concepts evaluation tool. In: Proceedings of the 3rd USA/Europe Air Traffic Management R&D Seminar, Naples, Italy (2000)
Albaker, B.M.; Rahim, N.A.: Unmanned aircraft collision detection and resolution: concept and survey. In: Proceedings of the 5th IEEE Conf. Ind. Electron. Appl., Taichung, Taiwan, pp. 248–253 (2010)
Kuchar J., Yang L.: A review of threat detection and resolution modeling methods. IEEE Trans. Intell. Transp. Syst. 1(4), 179–189 (2000)
Vivona, R.A.; Karr, D.A.; Roscoe, D.A.: Pattern-based genetic algorithm for airborne conflict resolution. In: Proc. AIAA Guidance, Navigation, and Control Conference and Exhibit, Keystone, Colorado, 21–24 August 2006, pp. 1–8 (2006)
Lecchini A., Glover W., Lygeros J., Maciejowski J.: Monte Carlo optimization for conflict resolution in air traffic control. IEEE Trans. Intell. Transp. Syst. 7(4), 470–482 (2006)
Carbone, C.; Ciniglio, U.; Corraro, F.; Luongo, S.: A novel 3D geometric algorithm for aircraft autonomous collision avoidance. In: Proc. 45th IEEE Conference on Decision and Control, San Diego, CA, 13–15 December 2006, pp. 1580–1585 (2006)
Duan H.B., Ma G.J., Wang D.B., Liu S.Q.: An improved ant colony algorithm for solving continuous space optimization problems. J. Syst. Simul. 19(1), 974–977 (2007)
Prandini M., Hu J., Lygeros J., Sastry S.: A probabilistic approach to aircraft conflict detection. IEEE Trans. Intell. Transp. Syst. 1(4), 199–220 (2000)
Masci, P.; Tedeschi, A.: Modeling and evaluation of a game-theory approach for airborne conflict resolution in Omnet++. In: Proc. Second International Conference on Dependability, Athens, Glyfada, 18–23 June 2009, pp. 162–165 (2009)
Lamont, G.B.; Slear, J.N.; Melendez, K.: UAV swarm mission planning and routing using multi-objective evolutionary algorithms. In: Proc. of Computational Intelligence in Multicriteria Decision Making, Honolulu, HI, 1–5 April 2007, 10–20 (2007)
Frazzoli E., Mao Z.H., Oh J.H., Feron E.: Resolution of onflicts involving many aircraft via semi-definite programming. J. Guid. Control Dyn. 24(1), 79–86 (2001)
Albaker B.M., Rahim N.A.: Unmanned aircraft collision avoidance system using cooperative agent-based negotiation approach. Int. J. Simul. Syst. Sci. Technol. 11(5), 1–7 (2007)
Park, J.W.; Oh, H.D.; Tahk, M.J.: UAV collision avoidance based on geometric approach. In: Proc. of SICE Annual Conference, The University Electro-Communications, Japan, 20–22 August 2008, pp. 2122–2126 (2008)
Brooker P.: Airborne collision avoidance systems and air traffic management safety. J. Navig. 58(1), 1–16 (2005)
Fedja, N.; Andrija, V.; Vojin, T.; Mariken, E.; Henk, B.: Stochastically and dynamically coloured Petri net model of ACAS operations. In: Proc. of 4th International Conference on Research in Air Transportation, Budapest, HUN, 01–04 June 2010, pp. 449–456 (2010)
Bondi, A.B.: Characteristics of scalability and their impact on performance. In: Proceedings of the 2nd International Workshop on Software and Performance, ACM, Ottawa, Canada, pp. 195–203 (2000)
Ruiz, S.: Strategic Trajectory De-confliction to Enable Seamless Aircraft Conflict Management. PhD Thesis, University Autonomous of Barcelona (2013)
Archibald J.K., Hill J.C., Jepsen N.A., Strirling W.C., Frost R.L.: A satisficing approach to aircraft conflict resolution. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 38(4), 510–521 (2008)
George, J.; Ghose, D.: A reactive inverse PN algorithm for collision avoidance among multiple unmanned aerial vehicles. In: Proc. of 2009 American Control Conference, St. Louis, MO, 10–12 June 2009, pp. 3890–3895 (2009)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Tang, J., Fan, L. & Lao, S. Collision Avoidance for Multi-UAV Based on Geometric Optimization Model in 3D Airspace. Arab J Sci Eng 39, 8409–8416 (2014). https://doi.org/10.1007/s13369-014-1368-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13369-014-1368-0