The recent application of the rational inattention (RI) theory in transportation has shed light on a promising alternative way of understanding how information influences the travel choices of passengers. However, existing RI literature has not yet addressed the discrete choice problem with multiple variates. Thus, this study develops a multivariate rational inattention (MRI) discrete choice model. This assumes that acquiring information is costly and the unit information cost varies among variates, so decision-makers rationally choose the amount of information to acquire for each variate. We demonstrate that the MRI discrete choice model results in a probabilistic formulation similar to the logit model, but with the superiority of integrating unit information costs and the prior knowledge of decision-makers. Furthermore, we apply the MRI discrete choice model to the metro route choice problem and calibrate the model based on the revealed preference (RP) data collected from the Chengdu metro. It is found that the proposed model has satisfactory accuracy with better interpretability than the logit model and univariate rational inattention discrete choice model.

中文翻译：

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具有理性疏忽的多变量离散选择：模型开发、应用和校准


最近在交通中应用理性注意力不集中 （RI） 揭示了一种很有前途的替代方法，可以理解信息如何影响乘客的出行选择。但是，现有的 RI 文献尚未解决具有多个变量的离散选择问题。因此，本研究开发了一个多变量理性注意力不集中 （MRI） 离散选择模型。这假设获取信息的成本很高，并且单位信息成本因变量而异，因此决策者会理性地为每个变量选择要获取的信息量。我们证明 MRI 离散选择模型产生了类似于 logit 模型的概率公式，但具有整合单位信息成本和决策者先验知识的优势。此外，我们将 MRI 离散选择模型应用于地铁路线选择问题，并根据从成都地铁收集的显示偏好 （RP） 数据校准模型。研究发现，所提模型比 logit 模型和单变量理性不注意离散选择模型具有令人满意的准确性和更好的可解释性。