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Quantifying traveler information provision in dynamic heterogeneous traffic networks

机译:量化动态异构交通网络中的旅行者信息提供

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Information is effectively the same as a change in uncertainty perceived by an observer. This paper adopts the strict definition of information from Shannon's Information Theory and provides procedures for quantifying effective provision of traveler information, considering it to be equivalent to the change of perceived uncertainty. The proposed method combines a cognitive grouping theory and an information learning scheme at an individual's level to evaluate the dynamic information provision in the unit of a bit. Such numerical quantification can be meaningful in evaluating alternatives with more fine-grained information provision strategies and understanding their equity impact. Quantifying information in a manner consistent with Information Theory also provides a shared language' that facilitates more constructive discussion among stakeholders from different backgrounds. The case study is conducted on a heterogeneous dynamic traffic network near Downtown Los Angeles for evaluating different alternatives of a proposed dynamic message board in terms of its location and dynamic content.
机译:信息实际上与观察者感知到的不确定性变化相同。本文采用了香农信息理论中对信息的严格定义,并提供了量化旅行者信息有效提供的程序,因为它等同于感知的不确定性的变化。所提出的方法在个人水平上结合了认知分组理论和信息学习方案,以位为单位评估动态信息提供。这种数字量化对于评估具有更细粒度信息提供策略的替代方案并了解其公平性影响可能是有意义的。以与信息论相一致的方式量化信息还提供了一种共享语言,可促进来自不同背景的利益相关者之间进行更具建设性的讨论。该案例研究是在洛杉矶市中心附近的异构动态交通网络上进行的,旨在根据其位置和动态内容评估拟议动态留言板的不同替代方案。

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