Analysis of UAV path planning effectiveness and evaluation index scores combined with urban logistics scenarios

Abstract

Using logistics drones for distribution is an optional solution to the problems of saturated logistics industry, insufficient transportation capacity, and high work pressure on employees in real cities. In a realistic urban environment, it is of practical significance to establish a logistics drone path planning model to improve the efficiency of logistics drones by fully considering the multiple requirements of both logistics service parties, such as time and location, and aiming at minimizing transportation costs. Aiming at this problem, this paper analyzes and studies the path planning problem of unmanned aerial vehicles based on the factors that need to be considered in actual life logistics distribution. Firstly, the actual scenario requirements of logistics UAV applications are analyzed and a path planning algorithm for this scenario is enumerated. Subsequently, mathematical models are established from both path planning and customer satisfaction to assess the performance of logistics drones. Then, a comparative analysis of four existing classical path planning algorithms is conducted, and simulated annealing algorithm is used to optimize logistics delivery scenarios for path planning. Finally, combining the mathematical model and simulated annealing algorithm constructed in the previous article, logistics UAV simulation experiments are conducted in urban distribution scenarios and an ideal path planning model is obtained. The work of this article provides a certain reference basis for logistics companies in the application of logistics UAVs and the selection of path planning methods.