为了同时考虑路网的随机变化特征和出行者的感知误差,在有限理性框架下基于累积前景理论建立了一个弹性需求随机用户均衡模型,给出了等价的变分不等式,设计了求解算法并通过算例进行了验证,结合参数敏感性对均衡状态出行者的认知和心理特征进行了分析。结果表明,OD出行需求和网络均衡态具有显著的参照点依赖效应,出行者对路况满意度越高OD出行需求越大,对路况熟悉程度越高OD出行需求越小。模型及算法可以加深对出行行为的理解,改进传统模型理论假设及适用性的局限,更加精确描述交通流的实际分布形态。
In order to simultaneously take traffic network's randomness and travelers' perception error into account,formulated a stochastic user equilibrium model with elastic demand based on bounded rationality framework and cumulative prospect theory.Then presented an equivalent variational inequality,followed by an algorithm and a numerical example to test it.Depicted travelers' cognition and psychological features by means of parameter sensitivity analysis.The results indicate that travel demands and network equilibrium significantly depend on reference point,and travel demands will become lager when travelers are more satisfied with network traffic condition,while it will become fewer when travelers are more familiar with it.The model and algorithm can help to deepen the understanding of travel behavior,improve the theoretic assumptions and adaptability of traditional traffic assignment model,and demonstrate actual traffic flow pattern more accurately.