预测信息下的驾驶员逐日路径选择行为与系统演化

运用微观仿真方法,研究预测信息作用下驾驶员逐日路径选择行为与路网交通流的演化.首先,分析了目前研究存在的不足,针对预测信息情形,设计了一种可行的行程时间预测方法,根据驾驶员逐日路径选择过程,建立了理解行程时间更新模型和路径选择模型.然后,在2条平行路径的简单路网中,仿真了预测信息条件下驾驶员逐日路径选择过程,分析了模型参数取值不同时路径流量随时间演化的波动性和路网系统的效率.结果表明:路网流量的波动性和系统效率都与驾驶员对预测信息的依赖程度和预测模型参数有关,且二者的变化规律相似.最后,以系统最优为目标,给出了预测模型参数的最佳取值范围.

Drivers' Day-to-Day Route Choice Behavior and System Evolution Under Forecast Information

Based on microscopic simulation,drivers’ day-to-day route choice behavior and evolution of network flow under forecast information are investigated.First,current reports hardly research drivers’ day-to-day route choice under forecast information.A feasible travel time prediction method is designed.A model updating the drivers’ perceived travel time and a route choice model are developed according to the drivers’ day-to-day route choice process.Then,by establishing a simple road network with two parallel routes,the drivers’ day-to-day route choice is simulated under forecast information.The fluctuation of route flow and efficiency of the system are analyzed when the parameters take different values.Results show that the fluctuation of network flow and efficiency of network are both related to drivers’ reliance on the information and forecast model’s parameters.Moreover,their changes are similar.Finally,the parameter’s optimal range is obtained.