A simulation-based optimization for deploying multiple kinds road rescue vehicles in urban road networks

Abstract

In the rescue process of urban road traffic accidents, the decision-making support system is of great importance since it will affect the rescue response time, and the response time is used as an evaluation index of the system performance. A shorter response time can ensure that casualties are rescued timely and can help restore the road as soon as possible. This paper provides a decision tool for traffic accident rescue vehicles’ integrated deployment problem in urban areas. In order to better simulate the stochastic rescue requests, the time and space distribution of traffic, and the dynamic rescue process, a simulation optimization model is established. This model determines the optimal deployment plan for three kinds of road rescue vehicles, i.e., ambulances, wreckers, and sweepers, in several time intervals in one day. To find a better solution, we incorporate a particle swarm optimization (PSO) method into the simulation and optimization procedures. The proposed method is validated by a case study in Shanghai. Additionally, sensitivity analysis is included to study the effects of various parameters and to confirm effectiveness and efficiency of the proposed method. The numerical experiments indicate that simply increasing the number of road rescue resources does not always improve the efficiency of road rescue.