考虑出行者路径选择过程中的有限理性和参考点依赖,以基于累积前景理论的路径选择决策规则为基础,建立随机网络用户均衡及其等价的变分不等式模型,力图展示现实中的交通流分布形态.提出了求解模型的算法,并通过简单的算例对模型和算法的合理性进行验证.考虑到日常出行路径选择是一个重复的学习与更新过程,通过模型描述出行者路径选择过程中的学习、选择和更新行为,进一步建立基于累积前景理论的动态交通系统,最后通过算例说明动态交通系统演化到用户均衡的过程.

investigated travelers' reference-dependent route choices and network equilibrium with bounded rationality. A decision-making rule for travelers' route choices was presented on the basis of cumulative prospect theory (CPT). The paper established the equivalence of the CPT-based user equilibrium model and a variational inequality formulation. The model is expected to describe the traffic flow pattern in realistic transportation network. An algorithm was proposed to solve the model. We constructed a numerical example to illustrate the algorithm as well as the model. This research further established a CPT-based dynamic system which incorporated travelers' learning and renewal procedure and dynamic route choices. The proposed system is expected to capture the day-to-day dynamic traffic flows. Another numerical example was constructed to show how the dynamic system evolved to the user equilibrium state.