交通系统行为状态评价模型

Model of behavioral state estimation for traffic systems

针对出行者交通行为路径选择,以时间变量最佳路径算法模拟个体日常出行行为,提出了总体旅行费用最小化的行为计划模型;引入条件概率来描述模型的不确定性,并以贝叶斯方式进行了扩展,提出个体选择路径的最优化模型及求解的迭代算法。结果表明:路径和行为位置选择中要考虑出行计划,该行为模式能使旅行费用最小化;所提供的行为可能性不仅依赖于主观费用,而且能形成交通状态评价问题,所提供的算法有效地解决了该问题。

Based on agent＇s traffic activity and route choice,a time variant best path algorithm is presented to simulate individual daily round activity,a plan model of traveler minimal cost is proposed,the conditional probability is developed to describe the uncertainty of the model,the model is extended in a Bayesian manner,the optimal model of individual route choice is proposed and an iteration of the algorithm is given.The results indicate that the trips plans should be considered in route and activity location choice,the behavioral pattern can minimize a traveler＇s cost;providing behavioral probabilities not only base on subjective costs,but also allow for the formulation of a traffic state estimation problem,which can efficiently be solved by an available algorithm.7 refs.