Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
article

Exact and Approximate Solving of the Aircraft Collision Resolution Problem via Turn Changes

Published: 01 February 2016 Publication History

Abstract

The aircraft conflict detection and resolution problem in air traffic management consists of deciding the best strategy for an arbitrary aircraft configuration such that all conflicts in the airspace are avoided. A conflict situation occurs if two or more aircraft do not maintain the minimum safety distance during their flight plans. A two-step approach is presented. The first step consists of a nonconvex mixed integer nonlinear optimization MINLO model based on geometric constructions. The objective is to minimize the weighted aircraft angle variations to obtain the new flight configuration. The second step consists of a set of unconstrained quadratic optimization models where aircraft are forced to return to their original flight plan as soon as possible once there is no aircraft in conflict with any other. The main results of extensive computation are reported by comparing the performance of state-of-the-art nonconvex MINLO solvers and an approximation by discretizing the possible angles of motion for solving a sequence of integer linear optimization SILO models in an iterative way. Minotaur, one of the nonconvex MINLO solvers experimented with, gives better solutions but requires more computation time than the SILO approach, which requires only a short time to obtain a good, feasible solution. Its value in the objective function has a reasonable goodness gap compared with the Minotaur solution. Given the need to solve the problem in almost real time, the approximate SILO approach is favored because of its short computation time and solution quality for the testbeds used in the experiment, which include both small-and real-sized instances. However, Minotaur is useful in this particular case for simulation purposes and for calibrating the SILO approach.

References

[1]
Alonso-Ayuso A, Escudero LF, Martín-Campo FJ (2011) Collision avoidance in the air traffic management: A mixed integer linear optimization approach. IEEE Trans. Intelligent Transportation Systems 12(1):47-57.
[2]
Alonso-Ayuso A, Escudero LF, Martín-Campo FJ (2012) A mixed 0-1 nonlinear optimization model and algorithmic approach for the collision avoidance in ATM: Velocity changes through a time horizon. Comput. Oper. Res. 12(39):3136-3146.
[3]
Alonso-Ayuso A, Escudero LF, Martín-Campo FJ (2014) On modeling the air traffic control coordination in the collision avoidance problem by mixed integer linear optimization. Ann. Oper. Res. 222:89-105.
[4]
Alonso-Ayuso A, Escudero LF, Martín-Campo FJ, Mladenovic N (2015) A VNS metaheuristic for solving the aircraft conflict detection and resolution problem by performing turn changes. J. Global Optim. 63(3):583-596.
[5]
Alonso-Ayuso A, Escudero LF, Olaso P, Pizarro C (2013) Conflict avoidance: 0-1 linear models for conflict detection and resolution. TOP 21(3):485-504.
[6]
Bellotti P, Lee J, Liberti L, Margot F, Waechter A (2009) Branching and bounds tightening techniques for non-convex MINLP. Optim. Methods Software 24(4-5):597-634.
[7]
Cafieri S, Durand N (2014) Aircraft deconfliction with speed regulation: New models from mixed-integer optimization. J. Global Optim. 58(4):613-629.
[8]
Christodoulou MA, Costoulakis C (2004) Nonlinear mixed integer programming for aircraft collision avoidance in free flight. IEEE Melecon 2004, Dubrovnik, Croacia, Vol. 1, 327-330.
[9]
Dell'Olmo P, Lulli G (2003) A new hierarchical architecture for air traffic management: Optimization of airway capacity in a free flight scenario. Eur. J. Oper. Res. 144(1):179-193.
[10]
Fourer R, Gay DM, Kernighan BW (2003) A Modeling Language for Mathematical Programming (Duxbury Press, Independence, KY).
[11]
Frazzoli E, Mao Z-H, Oh J-H, Feron E (2001) Resolution of conflicts involving many aircraft via semidefinite programming. AIAA J. Guidance, Control Dynam. 24(1):79-86.
[12]
GUROBI Optimization (2012) GUROBI Optimizer Reference Manual.
[13]
IBM ILOG (2012) CPLEX v12.4. User's Manual for CPLEX.
[14]
Jardin MR (2003) Real-time conflict-free trajectory optimization. Fifth USA/Europe Air Traffic Management RD Seminar, Budapest.
[15]
Kuchar JK, Yang LC (2000) A review of conflict detection and resolution modeling methods. IEEE Trans. Intelligent Transportation Systems 1(4):179-189.
[16]
Lee J, Leyffer S (2012) Mixed integer nonlinear programming. Lee J, Leyffer S, eds. The IMA Volumes in Mathematics and Its Applications, Vol. 154 (Springer, New York).
[17]
Leyffer S, Linderoth J, Luedtke J, Mahajan A, Munson T (2011) Minotaur solver. Accessed October 2013, http://wiki.mcs.anl.gov/minotaur/index.php/MINOTAUR.
[18]
Lindo Systems Inc. (2011) The LINGO User's Manual.
[19]
Martín-Campo FJ (2012) The Collision Avoidance Problem: Methods and Algorithms (Lambert Academic Publishing, Saarbrücken, Germany).
[20]
Pallottino L, Feron E, Bicchi A (2002) Conflict resolution problems for air traffic management systems solved with mixed integer programming. IEEE Trans. Intelligent Transportation Systems 3(1):3-11.
[21]
Peyronne C, Conn AR, Mongeau M, Delahaye D (2015) Solving air-traffic conflict problems via local continuous optimization. Eur. J. Oper. Res. 241(2):502-512.
[22]
Sahinidis NV (1996) A general purpose global optimization software package. J. Global Optim. 8(2):201-205.

Cited By

View all
  • (2024)Aircraft conflict resolution with trajectory recovery using mixed-integer programmingJournal of Global Optimization10.1007/s10898-024-01393-190:4(1031-1067)Online publication date: 1-Dec-2024
  • (2024)Quantum Variational Algorithms for the Aircraft Deconfliction ProblemComputational Science – ICCS 202410.1007/978-3-031-63778-0_22(307-320)Online publication date: 2-Jul-2024
  • (2022)Dual-Horizon Reciprocal Collision Avoidance for Aircraft and Unmanned Aerial SystemsJournal of Intelligent and Robotic Systems10.1007/s10846-022-01782-2107:1Online publication date: 28-Dec-2022
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Transportation Science
Transportation Science  Volume 50, Issue 1
February 2016
362 pages

Publisher

INFORMS

Linthicum, MD, United States

Publication History

Published: 01 February 2016
Accepted: 01 April 2014
Received: 01 October 2012

Author Tags

  1. air traffic management
  2. aircraft conflict detection and resolution problem
  3. heuristic sequential integer linear optimization
  4. nonconvex mixed integer nonlinear optimization

Qualifiers

  • Article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 12 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2024)Aircraft conflict resolution with trajectory recovery using mixed-integer programmingJournal of Global Optimization10.1007/s10898-024-01393-190:4(1031-1067)Online publication date: 1-Dec-2024
  • (2024)Quantum Variational Algorithms for the Aircraft Deconfliction ProblemComputational Science – ICCS 202410.1007/978-3-031-63778-0_22(307-320)Online publication date: 2-Jul-2024
  • (2022)Dual-Horizon Reciprocal Collision Avoidance for Aircraft and Unmanned Aerial SystemsJournal of Intelligent and Robotic Systems10.1007/s10846-022-01782-2107:1Online publication date: 28-Dec-2022
  • (2021)Detecting and solving aircraft conflicts using bilevel programmingJournal of Global Optimization10.1007/s10898-021-00997-181:2(529-557)Online publication date: 1-Oct-2021
  • (2018)Feasibility pump for aircraft deconfliction with speed regulationJournal of Global Optimization10.1007/s10898-017-0560-771:3(501-515)Online publication date: 1-Jul-2018

View Options

View options

Get Access

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media