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Modelling parking choice behaviour using Possibility Theory

机译:使用可能性理论对停车选择行为进行建模

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This article presents a discrete choice model for evaluating parking users' behaviour. In order to explicitly take into account imprecision and uncertainty underlying a user's choice process, the proposed model has been developed within the framework of Possibility Theory. This approach is an alternative way to represent imperfect knowledge (uncertainty) of users about both parking and transportation system status, as well as the approximate reasoning of the human decision maker (imprecision). The resulting model is a quantitative soft computing tool that could support traffic analysts in planning parking policies and Advanced Traveller Information Systems. In fact, effects of information on user choice can be incorporated into the model itself. Thus, we consider the parking user be a decision maker who assumes a certain choice set (set of perceived parking alternatives); the user has some information about the parking supply system and he/she associates each parking alternative with an approximate perceived cost/utility that is represented by a possibility distribution; and, finally, the user chooses the alternative which minimises/maximises his/her perceived parking cost/utility. The results show how the model is able to represent the effect of various parking policies on users' behaviour and how the single component of parking policy affects the decision process.
机译:本文提出了一种用于评估停车用户行为的离散选择模型。为了明确考虑用户选择过程的不精确性和不确定性,已在可能性理论的框架内开发了所提出的模型。这种方法是表示用户关于停车和运输系统状态的不完善知识(不确定性)以及人类决策者的近似推理(不精确)的一种替代方法。最终的模型是一个定量的软计算工具,可以为交通分析员提供停车政策和高级旅行者信息系统的规划支持。实际上,信息对用户选择的影响可以并入模型本身。因此,我们认为停车用户是一个决策者,他假设某个选择集(感知停车选择集);用户拥有有关停车位供应系统的一些信息,并且他/她将每个停车位选择与可能的分布所表示的近似感知成本/效用相关联;最后,用户选择最小化/最大化他/她感知的停车成本/效用的替代方案。结果表明,该模型如何能够表示各种停车政策对用户行为的影响,以及停车政策的单个组成部分如何影响决策过程。

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