基于参数灵敏度分析的交通仿真模型校正研究.

In order to carry out the correction work of traffic simulation model more efficiently, this paper proposed a model correction framework based on parameter sensitivity analysis . The method simplified the model by exploring the key parameters that affected the model accuracy through sensitivity analysis, and corrected the model with the usage of the calibrated key parameters. To justify this, the paper analyzed the car following model and lane changing model under the simulation condition of urban expressway weaving area. Firstly, it obtained the value of model parameters under different traffic flow levels through a large number of simulation experiments. Secondly, this paper formulated the interval division rules and cross combination rules of model parameters to improve LH-OAT algorithm and genetic algorithm (GA) . Then, it used the improved LH-OAT algorithm (ILH-OAT ) and GA algorithm to analyze the sensitivity of the model parameters and used GA to calibrate the key parameters. Finally, this paper checked the error of the simulation results according to the verification index. The results show that the combination of ILH-OAT and GA simplifies the simulation model and reduces the simulation operation cost. Besides, it also adds verisimilitude to the simulation on reflecting real traffic operation. [ABSTRACT FROM AUTHOR]