| Summary: | This paper investigates a patrol problem based on air-ground cooperation between multiple UAVs and police vehicles. Facing the uncertainty of patrol environment and patrol resources, the model guarantees the deterrence and emergency response capability of the patrol mission by optimizing the allocation strategy of patrol points and patrol routes. Relying on genetic algorithms, we encode patrol points and UAV launch/recovery points together to enhance the local search ability and convergence of the algorithm. Based on the real case of the D police station in Beijing, we explore the interactions among patrol elements and the impact on patrol tasks in different patrol environments. The results show that the Patrol missions formulated by Air-Ground Cooperative Patrol Optimization Model can be used to develop patrol tasks with better environmental adaptability. By analyzing the relationship between multiple groups of patrol elements, controlling the number of UAVs in future missions can improve the security of the area. And raise the ratio of hovering time in medium-risk areas to low-risk areas can improve the efficiency of patrols.
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