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A hybrid model for en-route driver behavior under real-time information

机译:实时信息下沿途驾驶员行为的混合模型

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The driver en-route route choice problem under real-time information is characterized by subjectively interpreted and/or linguistically expressed data on nonquantitative variables, as well as limited data on some quantitative variables. This paper proposes a hybrid fuzzy logit model to enable the treatment of nonquantitative and quantitative data simultaneously in a single framework to address the problem. Synergistically, its computational efficiency enables real-time deployment in a traffic control framework. The study highlights the appropriateness of using fuzzy variables to address recently identified en-route driver behavioral characteristics under information provision.
机译:实时信息下的驾驶员在途路线选择问题的特征在于非量化变量的主观解释和/或语言表达数据,以及一些定量变量的有限数据。本文提出了一种混合模糊logit模型,以在单个框架中同时处理非定量和定量数据,以解决该问题。协同地,其计算效率可在流量控制框架中进行实时部署。这项研究强调了在信息提供下使用模糊变量解决最近发现的途中驾驶员行为特征的适当性。

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