Novel Conflict Resolution Model for Multi-Uav Based on Cpn and 4d Trajectories

This paper presents a conflict resolution (CR) model in colored Petri net (CPN) formalism for 4D (three-dimensional + time) planned trajectories of cooperating unmanned aerial vehicles (UAVs). The CR model is integrated with the conflict detection algorithm using spatial data structure to detect time-based separation infringements among UAVs and to generate an intuitionistic representation of 4D conflict information. The main contribution of this paper is the proposed CR model, which is based on the logic of cause-and-effect analysis. This model not only chooses a preferred trajectory according to the priority for solving the current conflict but also considers the follow-up influence (domino effect) to update segments and conflicts. The novel causal model exploits the state space to achieve the solution using CPN. The model is validated with the experimental results of a scenario involving multiple UAVs (composed of clusters) cruising in a bounded region and exhibits the main advantages of scalability, efficiency, and short execution time.