Robotics Auton. Syst. | 2021

Directional optimal reciprocal collision avoidance

 
 
 

Abstract


Abstract A great amount of effort has been devoted to the study on self-separation assurance approach for civil aviation in the airspace with increasing density. In this article, the Optimal Reciprocal Collision Avoidance (ORCA) algorithm is modified to make it work for autonomous and decentralized collision avoidance for civil aircraft. Without considering the direction selectivity of collision-free maneuver, aircraft may select the relative parallel trajectories by deploying the ORCA algorithm in both decentralized and centralized way. As a result, the collision tends to be postponed to the next time horizon because civil aircraft need to return to original trajectories. Simultaneously, the unified rules can hardly be integrated into the approach due to the lack of direction selectivity for collision-free navigation. The process of separation assurance will be disorderly when multiple aircraft are involved. To solve the problem mentioned above, a new algorithm called Directional Optimal Reciprocal Collision Avoidance (DORCA) is proposed. The DORCA algorithm employs a vector rotation mode to construct the forbidden Velocity Obstacle (VO) set in order to improve the computation efficiency. In addition, the direction selectivity of maneuver is achieved through constructing the direction-constrained VO set according to the direction of relative motion in velocity space. Direction selectivity of the algorithm enables the process of collision avoidance to comply with the unified rules. A number of encounter scenarios are conducted to confirm the validity and feasibility of the proposed DORCA algorithm. In all scenarios tested, the direction selectivity of collision-free maneuver can be successfully integrated into the DORCA algorithm, and the algorithm is more efficient than the ORCA algorithm for collision avoidance in decentralized way.

Volume 136
Pages 103705
DOI 10.1016/j.robot.2020.103705
Language English
Journal Robotics Auton. Syst.

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