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Modeling Repeated Multinomial Route Choices Under Advanced Traveler Information System: Generalized Estimating Equations with Polytomous Logit Function

机译:在高级旅行者信息系统下建模重复多项式路线选择:具有多对数Logit函数的广义估计方程

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Correlated multinomial route choice data were modeled under an advanced traveler information system (ATIS). A travel simulator was used as a dynamic data collection tool. The simulator uses realistic network and real historical traffic volumes. It provides five levels of ATIS and accounts for types of delay. A 25-node and 40-link network was used. Sixty-three qualified subjects performed a total of 539 trial days. Forty-four distinct routes were chosen. The multinomial generalized estimating equation (MGEE) methodology was used with a generalized polytomous function and an exchangeable correlation structure. MGEEs account for the serial correlation between repeated choices made by the same subject as well as the correlation due to the overlapping between alternatives. The modeling results show that drivers can identify and follow the shortest path when they are provided with advice-free traffic information on all the network links. In addition, it is shown that the odds of choosing a certain shortest-path route, whether the drivers are advised or not, vary from route to route, depending on the characteristics of the route itself. It was proved that the proposed model could account for a correlation in the multinomial repeated route choices with simple computational effort, even for a large number of alternatives.
机译:相关的多项路线选择数据是在高级旅行者信息系统(ATIS)下建模的。旅行模拟器被用作动态数据收集工具。该模拟器使用真实的网络和真实的历史流量。它提供了五个级别的ATIS,并说明了延迟类型。使用25个节点和40个链接的网络。六十三名合格的受试者总共进行了539天的试验。选择了四十四条不同的路线。使用具有多项式函数和可交换相关结构的多项式广义估计方程(MGEE)方法。 MGEEs解释了同一主题重复选择之间的序列相关性,以及由于选择之间的重叠而引起的相关性。建模结果表明,在所有网络链路上为驾驶员提供无建议的交通信息时,驾驶员可以识别并遵循最短路径。此外,还显示出,选择某条最短路径的可能性(无论是否建议驾驶员)因路径本身的特性而异。事实证明,所提出的模型可以通过简单的计算工作,甚至在大量替代方案中,解决多项式重复路线选择中的相关性。

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