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Expanding the applicability of random regret minimization for route choice analysis

机译：扩大随机后悔最小化在路线选择分析中的适用性

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摘要

The discrete choice paradigm of random regret minimization (RRM) has been recently proposed in several choice contexts. In the route choice context, the paradigm has been used to model the choice among three routes and to formulate regret-based stochastic user equilibrium. However, in the same context the RRM literature has not confronted three major challenges: (ⅰ) accounting for similarities across alternative routes, (ⅱ) analyzing choice set composition effects on choice probabilities, and (ⅲ) comparing RRM-based models with advanced RUM-based models. This paper looks into RRM-based route choice models from these three perspectives by (ⅰ) proposing utility-based and regret-based correction terms to account for similarities across alternatives, (ⅱ) analyzing the variation of choice set probabilities with the choice set composition, and (ⅲ) comparing RRM-based route choice models with C-Logit, Path Size Logit and Paired Combinatorial Logit. The results illustrate the definition of the correction terms within the regret function, the effect of the choice set specificity of RRM-based route choice models, and the positive performance of these models when compared to advanced RUM-based models.
机译：最近在几种选择环境中提出了随机后悔最小化（RRM）的离散选择范式。在路径选择的上下文中，已使用该范例对三种路径之间的选择进行建模，并建立了基于后悔的随机用户均衡。但是，在相同的背景下，RRM文献并未面临​​三个主要挑战：（ⅰ）解释替代路线之间的相似性；（ⅱ）分析选择集构成对选择概率的影响；（ⅲ）将基于RRM的模型与高级RUM进行比较基于模型。本文从以下三个方面研究了基于RRM的路线选择模型：（ⅰ）提出基于效用和基于遗憾的校正术语，以解决各备选方案之间的相似性；（ⅱ）分析选择集构成随选择集概率的变化，以及（ⅲ）将基于RRM的路由选择模型与C-Logit，路径大小Logit和成对组合Logit进行比较。结果说明了后悔函数中校正项的定义，基于RRM的路线选择模型的选择集特异性的影响以及与基于高级RUM的模型相比这些模型的积极表现。

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