Travel time prediction and departure time adjustment behavior dynamics in a congested traffic system
Travel time prediction and departure time adjustment behavior dynamics in a congested traffic system
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DOI：
10.1016/0191-2615(88)90017-3
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发表时间：
1988-06
期刊：
影响因子：
--
通讯作者：
G. Chang;H. Mahmassani
中科院分区：
文献类型：
--
作者：
G. Chang;H. Mahmassani
本文研究了两个启发式规则，用于描述城市通勤者对出行时间的预测，以及在有限信息下，针对日常通勤中不可接受的到达而调整发车时间的情况。它基于这样一个概念，即预测出行时间的大小取决于每个通勤者自己的经验，包括可回忆的出行时间、时间表延误以及寻找令人满意的出发时间的困难。首先，基于一组通勤者通过模拟交通系统在24天内相互作用所提供的信息，执行解释性分析来比较这两个规则。然后提出了一个更详细的模型规范，该规范捕捉了通勤者累积的和最近的交通系统性能经验之间的动态相互关系。模型参数的估计明确考虑了由相同个体的重复决策引起的序列相关性，以及通过交通系统的性能与其他系统用户决策的同时交互作用。
This paper examines two heuristic rules proposed for describing urban commuters' predictions of travel time as well as the adjustments of departure time in response to unacceptable arrivals in their daily commute under limited information. It is based on the notion that the magnitude of the predicted travel time depends on each commuter's own experience, including recallable travel time, schedule delay, and difficulties in searching for a satisfactory departure time. An explanatory analysis is first performed to compare these two rules, based on the information provided by a set of commuters interacting over 24 days through a simulated traffic system. A more elaborate model specification which captures the dynamic interrelation between the commuter's cumulative and recent experience with the traffic system's performance is then proposed. The model parameters are estimated with explicit consideration of the serial correlation arising from repeated decisions by the same individuals and the contemporaneous interaction with other system users' decisions through the traffic system's performance.