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Experimental Analysis of A Hybrid Route Choice Model to Capture Dynamic Behavioral Phenomena under Advanced Information Systems

机译:先进信息系统下捕获动态行为现象的混合路径选择模型的实验分析

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摘要

The driver route choice problem under real-time information provision is characterized by subjectively interpreted and/or linguistically expressed data in addition to quantitative inputs. In previous work, the authors propose a hybrid probabilistic-possibilistic model which treats qualitative and quantitative data simultaneously in a single framework. This paper presents experimental insights on the performance of the hybrid model based on extensive simulation analysis under potential real-world scenarios. It performs sensitivity analyses on the associated driver behavior model parameters, and investigates the model's ability to capture dynamic qualitative phenomena under information provision. The results highlight the flexibility of the hybrid model in addressing a broad range of driver behavior characteristics and network conditions. They also suggest that the hybrid model can capture the evolution of the driver behavior characteristics over time and the influence of the randomness in network conditions on route choice behavior.
机译:在实时信息提供下的驾驶员路线选择问题的特征在于,除了定量输入之外,还具有主观解释和/或语言表达的数据。在先前的工作中,作者提出了一种混合的概率-可能性模型,该模型在单个框架中同时处理定性和定量数据。本文基于潜在现实场景下的广泛仿真分析,提供了有关混合模型性能的实验性见解。它对相关的驾驶员行为模型参数进行敏感性分析,并研究该模型在信息提供下捕获动态定性现象的能力。结果突出了混合模型在解决各种驾驶员行为特征和网络状况方面的灵活性。他们还建议,混合模型可以捕获驾驶员行为特征随时间的演变以及网络条件中随机性对路线选择行为的影响。

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