Data-driven approach for solving the route choice problem with traveling backward behavior in congested metro systems

Chao Yu, Haiying Li, Xinyue Xu and Jun Liu

Transportation Research Part E: Logistics and Transportation Review, 2020, vol. 142, issue C

Abstract: This study proposes a data-driven approach to understand traveling backward (TB) behavior while making a route choice in congested metros. First, TB behavior during route choice in overcrowded metros is defined and analyzed. Second, a hybrid model comprising three hierarchical Bayesian models is developed to describe the TB behavior. Third, a novel sampling method based on Hamiltonian dynamics is introduced to estimate the model parameters. Finally, a case study of Beijing metro is discussed to illustrate the effectiveness and robustness of the proposed model. The contributions of application of the proposed model to accurate demand assignment and passenger flow control for metro managers are demonstrated.

Keywords: Metro system; Data driven; Bayesian; Traveling backward (TB); Route choice (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.tre.2020.102037

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