ABSTRACT 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.

中文翻译：

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动态异构交通网络中旅客信息提供的量化

摘要 信息实际上与观察者感知的不确定性变化相同。本文采用香农信息论中对信息的严格定义，并提供了量化有效提供旅行者信息的程序，认为它等同于感知不确定性的变化。所提出的方法结合了认知分组理论和个体层面的信息学习方案，以比特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影响可能很有意义。以与信息理论一致的方式量化信息还提供了一种“共享语言”，有助于来自不同背景的利益相关者之间进行更具建设性的讨论。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，以评估提议的动态留言板的位置和动态内容的不同替代方案。