有限理性下考虑出发时间选择的网络交通流演化

假设出行者出发时间与路径选择随历史出行信息的更新而不断调整,研究网络交通流逐日动态演化规律.考虑出行者有限理性,基于累积前景理论,建立了出行者出发时间选择、时间间隔权重更新、路径选择及路径行程时间分布更新模型.通过数值实验表明:出行者对历史理解行程时间依赖程度对每个出发时段的稳定的流量分布无显著影响,但是对路径流量演化有显著影响;当出行者对历史理解行程时间的依赖程度大于等于0.90时,考虑出发时间选择的路网流量演化最终能达到稳定状态;从系统的整体效率来看,当出行者对历史理解行程时间的依赖程度在0.90,0.95]时,有限理性下的交通分配结果优于完全理性.

Network Traffic Flow Evolution Considering Departure Time Choice Based on Bounded Rationality

It is assumed that travelers adjust departure time and route choices according to updating historical information. With considering traveler’s bounded rationality, the day- to-day dynamic models of network traffic flow are developed based on the cumulative prospect theory. The proposed models reveal how travelers make departure time and route choices, update the time interval weight, and the route travel time distribution function. Numerical experiments on a grid network show that the reliance on historical perceived travel time have no significant effect on the stable flow distribution of each departure time interval, but have significant effect on network traffic flow evolution. When the reliance on historical perceived travel time is greater than or equal to 0.90, the network traffic flow considering departure time choice will eventually reach a steady state. From the perspective of the overall efficiency of the network system, when the reliance on historical perceived travel time is within 0.90, 0.95], the boundedly rational traffic assignment will be better than the perfectly rational one.