Research On Vehicle-drone Cooperative Path Planning For Heterogeneous Tasks

With the continuous expansion of city scale,road construction and vehicle scale continue to develop,so that the demand for traffic management and public security prevention and control continues to increase.Drone,as an aerial sensing platform,has been developed and matured in recent years,and has been widely used in traffic management fields such as road patrol,traffic jam detection and accident investigation.The use of drones for road patrol,reconnaissance and law enforcement has become an important part of traffic management.Research on various scientific problems in the process of traffic patrol has become an important force to promote the development of urban road traffic patrol and public security prevention and control.Due to the limited factors such as drone's endurance,safe control distance and the particularity of road patrol,cooperative patrol between vehicle and drone becomes a more effective solution.However,the research on vehicle-drone cooperative patrol is still in the development stage,and there are still many key technical and theoretical methods to be studied.Aiming at the demand of cooperative route planning between patrol vehicle and drone in traffic patrol,this paper proposes and studies the problem of cooperative route planning between patrol vehicle and drone in urban road system.Heterogeneous task modeling and collaborative allocation of the road network are mainly solved.In this paper,a mixed integer linear programming model is designed innovatively,which can effectively solve the problem of collaborative modeling.At the same time,a two-stage heuristic solution framework is proposed,a heterogeneous task vehicle patrol optimal path solution method and a task assignment optimization heuristic method are designed to solve the problem of actual size.Through the analysis of numerical and simulation experiments,the solution method proposed in this paper can quickly obtain a better path planning scheme for different task requirements under different road network sizes.Compared with traditional vehicle patrol,the proposed method can save at least 9% to 16% of the time.This paper also analyzes several related parameters in the patrol process and verifies the effectiveness of the algorithm.