Unmanned aerial vehicle route planning for traffic information collection

In this paper, the unmanned aerial vehicle (UAV) route planning problem is introduced to deploy the UAV for road traffic information collection. The scenario of using limited UAVs to detect road sections is considered, and a multi-objective optimization model is developed, which uses the number of the UAVs and UAV maximum cruise distance as constraints and aims to minimize the total cruise distance and maximize the number of detected road sections. A novel non - dominated sorting genetic algorithm for this problem is then proposed. The case study shows that the nearly optimal solution for planning UAV routes can be acquired effectively. Compared the obtained solution with the optimal feasible solution, the total cruise distance is reduced by 13.07% and the number of detected targets is increased by 41.67%. Finally, some issues on deploying UAVs for traffic information collection are discussed.