诱导信息下的路径选择行为模型

本文为诱导信息下的驾驶员路径选择行为提出了一种基于决策场理论和贝叶斯理论的推理、预测、判断和路径选择决策的交互仿真模型. 首先，由贝叶斯推理理论建立诱导信息和以往出行经验共同作用下的路况动态更新模型；进而将其与基于决策场理论的动态路径选择模型相结合，构成诱导信息下的路径选择行为交互模型. 通过诱导信息下的路径选择行为动态模拟，获取诱导信息对路径选择行为的量化影响效能值. 仿真分析显示，诱导信息可信度、出行经验、路径固有偏好、决策速度/质量和路线选择标准是影响驾驶员对诱导信息做出响应的关键因素. 分析结果表明，决策场理论与贝叶斯理论相结合能较好地解释驾驶员路径选择行为的动态特性.

Route Choice Behavior Model with Guidance Information

Using modeling and simulation methods, the driver’s route choice behavior under guidance information is explored based on the combination of the decision field theory (DFT) and Bayesian theory. First, based on the Bayesian theory, a road condition dynamic updating model is presented in light of the guidance information and the driver’s previous travel experiences. Then, the route choice behavior model under guidance information is formed by the fusion of the process-oriented vehicle dynamic route choice model and the road condition dynamic updating model. The developed model describes a driver’s propensity to comply with received guidance information in terms of the interaction between perceived unreliability of the information, his previous travel experiences, preference for different road alternatives, decision-making speed/quality, and route selection criteria. The simulation results show that the combination of the DFT and Bayesian theory can effectively explain the driver’s travel dynamics behavior.