Multi-objective evolutionary approach for UAV cruise route planning to collect traffic information

Abstract

Unmanned aerial vehicle (UAV) was introduced as a novel traffic device to collect road traffic information and its cruise route planning problem was considered. Firstly, a multi-objective optimization model was proposed aiming at minimizing the total cruise distance and the number of UAVs used, which used UAV maximum cruise distance, the number of UAVs available and time window of each monitored target as constraints. Then, a novel multi-objective evolutionary algorithm was proposed. Next, a case study with three time window scenarios was implemented. The results show that both the total cruise distance and the number of UAVs used continue to increase with the time window constraint becoming narrower. Compared with the initial optimal solutions, the optimal total cruise distance and the number of UAVs used fall by an average of 30.93% and 31.74%, respectively. Finally, some concerns using UAV to collect road traffic information were discussed.