Optimization-Based Collision Avoidance for Cooperating Airplanes

Application of autonomous intelligent systems into airspace domain is very important nowadays. The paper presents decentralized collision avoidance algorithm utilizing a solution of the defined optimization problem where efficiency criteria, collision penalties and airplanes’ missions are integrated in an objective function. Two different implementation approaches used for stochastic Probability Collectives optimizer are presented and evaluated – a complex distributed multi-agent deployment among participating airplanes and the Process Integrated Mechanism inspired architecture. Both approaches have been validated and evaluated on the multi-agent framework AGENTFLY providing precise simulation for airspace operations.