一种用户均衡分配不确定性的计算方法

为解决目前交通分配中存在的不确定性问题，基于Wardrop用户平衡原理，利用起讫点（OD，Origin Destination）估计方法和Beckman交通分配模型，建立了一种交通分配不确定性计算方法.该方法分别以不同置信水平下的OD估计结果的上下限为输入量，然后利用Frank-Wolf算法求解交通分配模型，得到不同置信水平下的路段流量区间，以此量化交通分配问题中的不确定性.以南京市区域路网为研究对象进行案例分析，并采用宽度流量比R和无效覆盖率（Kickoff Percentage，KP）对模型结果进行评价，结果表明该方法可以得到路段流量的置信区间，量化交通分配的不确定性.

Method of quantifying uncertainty inuser equilibrium traffic assignment

To solve the uncertainty problems in traffic assignment,this paper established a method of quantifying the uncertainty in traffic assignment model based on Wardrop user equilibrium principle and Beckman traffic assignment model.The model uses the upper and lower limits of OD estimation results under different confidence levels as inputs,and subsequently uses the Frank-Wolf algorithm to solve the model to obtain link traffic flow intervals under different confidence levels to quantify uncertainty in traffic assignment.A case study utilizing a regional road network in Nanjing is performed,and the results were evaluated using the width flow ratio R and the kickoff percentage (KP) as the performance measures.The evaluation results show that the proposed method can effectively compute the confidence intervals of the road link flow,thereby quantifying the uncertainty in traffic assignment.