关键词: 城市交通, 双层规划, 停车场分配, 嵌套优化算法, 个性化诱导

Abstract:

The conception of personalized parking guidance and service process are defined in order to make up for the drawback of public parking guidance. A parking lot distribution model based on the personalized parking guidance is proposed. The upper- level of the model is to achieve the balance use of parking resources in peak time and avoid local parking congestion, while the lower-level problem is to obtain minimize walking distances, achieve the maximum benefits of the drivers. A nested optimization algorithm of the bi-level programming model is designed based on the deformation particle swarm optimization (PSO), the main body of the optimization algorithm is used to solve the upper-level problem, a nested algorithm is used to solve the lower- level programming. In the simulation experiment, the maximum parking spillover index in peak time is reduced from 0.257 to 0.195 and congestion time is reduced from 5.67 hours to 3.67 hours. The results indicate that the parking lots distribution model, which based on the personalized parking guidance, has obvious effects in balance using parking resources, shorting the parking congestion and reducing peak parking index.

Key words: urban traffic, bi- level programming, parking lots distribution, nested optimization algorithm, personalized guidance