Impact Estimation of Unplanned Urban Rail Disruptions on Public Transport Passengers: A Multi-Agent Based Simulation Approach

Chengli Cong, Xuan Li, Shiwei Yang, Quan Zhang, Lili Lu and Yang Shi
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Chengli Cong: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Xuan Li: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Shiwei Yang: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Quan Zhang: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Lili Lu: School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
Yang Shi: Ningbo Urban Planning & Design Institute, Ningbo 315042, China

IJERPH, 2022, vol. 19, issue 15, 1-25

Abstract: Once unplanned urban rail disruptions occur, it is essential to evaluate the impacts on public transport passengers since impact estimation results enable transit agencies to verify whether alternative transit services have adequate capacity to evacuate the affected rail passengers and to adopt effective emergency measures in response to the disruptions. This paper focuses on estimating the impacts of unplanned rail line segment disruptions on rail passengers as well as original bus passengers, as the latter are overlooked in existing studies. A method of identifying affected rail passengers based on passenger tap-in time is proposed, which is helpful for evaluating the scale and origin-destination distribution of the affected passengers. Passengers’ response behaviors are analyzed and modeled in a multi-agent simulation system. The system realizes the simulation of the multimodal evacuation process, in which a rule-based logit model is employed to describe passengers’ travel selection behavior and the Monte Carlo method is utilized to address the issue of uncertainty in passengers’ travel selection. In particular, the original bus passengers are integrated into the simulation and interact with rail passengers. Finally, some indicators assessing the impacts on rail passengers and bus passengers are presented, and a case study based on the Ningbo urban rail transit network is conducted.

Keywords: urban rail transit; unplanned disruption; impact estimation; multi-agent simulation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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