论文部分内容阅读
城市交通控制的许多决策都是基于微观交通流仿真模型进行的。每次仿真,都需要标定建立模型和描述驾驶员行为的相关参数。为了减轻模型参数标定的工作量,需要引入适当的方法对模型进行标定。为此,本研究应用了视频检测系统来对微观交通流仿真模型的参数进行标定,并使用模拟退火算法使仿真的结果和被仿真对象的实际观测数据吻合。模型参数的标定过程和仿真结果通过一个具体的例子进行阐述。
Many decisions of urban traffic control are based on the micro-traffic flow simulation model. For each simulation, you need to calibrate the model and describe the parameters related to the driver’s behavior. In order to reduce the workload of model parameter calibration, we need to introduce appropriate methods to calibrate the model. In order to do this, the video detection system is applied to calibrate the parameters of the micro traffic flow simulation model, and the simulated annealing algorithm is used to match the simulation results with the actual observed data of the simulated object. The calibration of the model parameters and simulation results are illustrated by a concrete example.