Dual-Horizon Reciprocal Collision Avoidance for Aircraft and Unmanned Aerial Systems

• Published in: Optics Letters
• Main Authors: Alligier, Richard, Gianazza, David, Durand, Nicolas, Olive, Xavier
• Other Authors: Ecole Nationale de l'Aviation Civile (ENAC), Algorithmes Parallèles et Optimisation (IRIT-APO), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Direction Générale de l'Aviation Civile (DGAC), DTIS, ONERA, Université de Toulouse Toulouse, ONERA-PRES Université de Toulouse
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2022
• Subjects: Collision avoidance; Aircraft conflict resolution; Self-separation; Optimal reciprocal collision avoidance; Air traffic control; Unmanned airborne systems; Collision Avoidance aircraft conflict resolution self-separation Optimal Reciprocal Collision Avoidance Air Traffic Control Unmanned Airborne Systems; [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]; [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]; Orca
• Online Access: https://enac.hal.science/hal-03948501; https://enac.hal.science/hal-03948501/document; https://enac.hal.science/hal-03948501/file/main.pdf; https://doi.org/10.1007/s10846-022-01782-2

International audience The aircraft conflict detection and resolution problem has been addressed with a wide range of centralised methods in the past few decades, e.g. constraint programming, mathematical programming or metaheuristics. In the context of autonomous, decentralized collision avoidance without explicit coordination, geometric methods provide an elegant, cost-effective approach to avoid collisions between mobile agents, provided they all share a same logic and a same view of the traffic. The Optimal Reciprocal Collision Avoidance (ORCA) algorithm is a state-of-the art geometric method for robot collision avoidance, which can be used as a Detect & Avoid logic on-board aircraft or Unmanned Aerial Vehicles. However, ORCA does not handle well some degenerate situations where agents operate at constant or near-constant speeds, which is a widespread feature of commercial aircraft or fixed-winged Unmanned Airborne Systems. In such degenerate situations, pairs of aircraft could end up flying parallel tracks without ever crossing paths to reach their respective destination. The Constant Speed ORCA (CS-ORCA) was proposed in 2018 to better handle these situations. In this paper, we discuss the limitations of both ORCA and CS-ORCA, and introduce the Dual-Horizon ORCA (DH-ORCA) algorithm, where two time horizons are used respectively for short-term collision avoidance and medium-term path-crossing. We show that this new approach mitigates the main issues of ORCA and CS-ORCA and yields better performances with dense traffic scenarios.