Resilience enhancement-oriented traffic police service district division and patrol route planning

With the increase in car ownership and traffic accidents, optimally designing traffic police service districts and patrol routes (TPSD-PR) has practical significance in improving the capability of an urban road system to cope with traffic events. However, existing studies rarely optimize the TPSD-PR cooperatively with the goal of enhancing urban road system resilience. To address the above-mentioned gaps, a bi-level programming model is developed to optimally design the TPSD-PR in a given region. A solution algorithm combining an improved genetic algorithm and a simulated annealing algorithm is developed to solve the developed model. Case studies performed on a real-world urban road system imply that the formulated model can optimally design its TPSD-PR with the goal of minimizing patrol time and team workload variance. Compared to the current scheme, the total weighted patrol time and the workload variance are decreased by 2.01% and 17.92%, respectively. With the increase in the number of patrol teams, the model's solution efficiency decreases, while the objective value improves. Historical accident severity directly affects the model's objective function, implying that the impact of the accident severity on the scheme design cannot be ignored. Finally, the influence of distinct parameters on the model's effectiveness is discussed. Subsequently, based on the analysis results, several practical suggestions are proposed to improve the resilience of an urban road system under traffic events.