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Travel Choice Analysis under Metro Emergency Context: Utility? Regret? Or Both?

Xingchuan Wang (), Enjian Yao () and Shasha Liu ()
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Xingchuan Wang: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Enjian Yao: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Shasha Liu: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Sustainability, 2018, vol. 10, issue 11, 1-15

Abstract: With the continuous expansion of the network scale and increasing of passengers, metro emergencies such as operational equipment failure are happening more frequently. Due to the narrow space and crowds of people, metro emergencies always have more of an impact than road traffic emergencies. In order to adopt appropriate measures to ensure passenger safety and avoid risks, we need to get a better understanding of passengers’ travel choice behaviors under emergencies. Most of the existing research studies related to travel choice behaviors took the random utility maximization (RUM) principle for granted, but failed to realize the potential of different decision-making processes and changes to the decision-making environment. In this research, we aim to analyze metro passengers’ travel choice behaviors under metro network emergency contexts. Based on the data collected from a survey about travel choices under metro emergencies in the Guangzhou Metro, we compared the performances of models that follow the RUM and random regret minimization (RRM) principles, and established a hybrid RUM-RRM model as well as a nested logit model following RRM (NL-RRM) to estimate the effects of various factors on passengers’ travel choice behaviors. Comparisons illustrate that the hybrid model and NL-RRM model can improve model fit, and the combination of RUM and RRM outperforms either of them respectively.

Keywords: travel choice behavior; metro passenger; multiple traffic mode; random regret minimization; network topology; hybrid model; nested logit model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
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