An UAV Allocation Method for Traffic Surveillance in Sparse Road Network

Unmanned Aerial Vehicle(UAV) technology was introduced into the traffic surveillance in sparse road network and an UAV allocation method for traffic surveillance with/without UAV continuous flight distance constraint was proposed.First,the method of choosing the surveillance road segments and nodes was proposed.Then,UAV traffic surveillance problem without continuous flight distance constraint was formulated as a traveling salesman problem,and the simulated annealing algorithm was introduced to solve this problem.As for UAV traffic surveillance problem with continuous flight distance constraint,K-means clustering algorithm was used to divide the UAV surveillance area into multiple sub-zones to convert this problem into UAV traffic surveillance scenario without continuous flight distance constraint.Finally,taking Korla-Kuqa expressway of Xinjiang and its road network as example,the proposed UAV-based traffic surveillance allocation method for sparse road network was demonstrated and validated by using several field experiments.The experimental results show that UAV is an effective and useful tool for traffic surveillance in sparse road network of China western regions.