Passenger-Oriented Resilience Assessment of an Urban Rail Transit Network under Partial Disturbances
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 11
Abstract
In daily operation, urban rail transit (URT) systems often experience disturbances that result in a partial reduction in transport capacity [partial disturbances (PDs)] rather than disturbances leading to a complete reduction in transport capacity. However, research that assesses the resilience of URT networks under PDs remains limited. This paper addresses this gap by proposing a passenger-oriented resilience assessment model for URT networks under PDs, considering the travel behaviors of passengers and different relations (i.e., linear, concave, and convex) between the velocity coefficient and failure severity. A simulation-based assessment approach was developed to solve the resilience assessment model. A numerical experiment was conducted on the Chengdu subway network in China. The results demonstrate that the performance indicator employed herein reflects the impact of passenger travel time distribution on network performance. Deliberate PDs cause more significant performance losses than random PDs. Moreover, the network is the least resilient under PDs considering the convex relation between the velocity coefficient and failure severity. The resilience-based critical link of each line is not fixed and varies with the failure severity and disturbance occurrence time. Increasing the failure severity of PDs results in more severe performance losses than increasing the number of PDs. Additionally, the passenger-oriented resilience of a URT network can be enhanced by improving the passengers’ tolerable delay time and disturbance duration.
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Data Availability Statement
Some data, models, and codes generated or used during the study are available from the corresponding author upon request. These data were obtained for five working days of the Chengdu URT and bus system in April 2019.
Acknowledgments
This research was funded by the National Natural Science Foundation of China (U1834209), the National Key R&D Program of China (2017YFB1200700), Hubei Superior and Distinctive Discipline Group of “New Energy Vehicle and Smart Transportation,” and Beijing Municipal Natural Science Foundation (9212014). The first author is deeply grateful for the financial support from the China Scholarship Council (202207000067).
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 11 • November 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Apr 2, 2023
Accepted: Jul 11, 2023
Published online: Sep 15, 2023
Published in print: Nov 1, 2023
Discussion open until: Feb 15, 2024
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