基于PSO算法的微观交通仿真模型参数标定

摘要

对微观交通仿真模型的参数自动化标定是确保仿真模型有效性的基础和前提.选用微观交通仿真软件VISSIM为基础平台,建立了仿真参数的一般标定流程,对基于粒子群优化(PSO)算法的仿真模型参数标定方法进行了研究,对影响模拟结果的主要参数进行标定,并实现了程序的自动化校正.同时,结合工程实例将该方法应用于北京市快速路仿真模型的驾驶员行为参数标定中.结果显示,采用该方法标定后的仿真模型参数能够更好的符合实际道路交通状况,且能够有效减少参数标定的仿真试验次数.%Parameter automatic calibration of microscopic traffic simulation model is the basis and prerequisite to ensure the effectiveness of simulation models. The paper selects the VISSIM model as the basic platform, and proposes a procedure for microscopic simulation model calibration. It studied a parameter calibration approach based on PSO algorithm, calibrated the influence on the simulation results of the main parameters, and realized a corresponding automatic calibration procedure as well. Finally , combined with the engineering example, the proposed approach is applied to the driving behavior parameter calibration of the simulation model for the expressway road network of Beijing. The results show that after using this method calibration parameters of simulation model can better meet the actual traffic conditions, and can effectively reduce the number of parameters calibration simulation test.