Passenger Travel Behavior Analysis under Unplanned Metro Service Disruption: Using Stated Preference Data in Guangzhou, China

Li, Binbin; Yao, Enjian; Yamamoto, Toshiyuki; Huan, Ning; Liu, Shasha

doi:10.1061/jtepbs.0000308

Cited by 9 publications

(3 citation statements)

References 20 publications

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“…According to Zhu et al [ 9 ], income played a vital role in determining travel reactions to disruptions. Nguyen–Phuoc et al [ 10 ] conducted semi-structured interviews with 30 commuters from Melbourne, Australia, and found the most important factors influencing the mode shift when public transport ceases in the short term, e.g., car access, travel time, travel cost, trip importance, which were also observed by Adelé et al [ 11 ] and Li et al [ 12 ].…”

Section: Introductionmentioning

confidence: 73%

“…The travel adjustment choice of the affected passengers at the micro level is finally reflected in the redistribution of passenger flow on the transportation network at the macro level. Thus, some studies were dedicated to understanding the mechanism of passengers’ behaviors and constructing passenger reassignment models under unplanned rail disruptions [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. Generally, these works were conducted by means of a passenger flow survey.…”

Section: Introductionmentioning

confidence: 99%

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

Cong

Yang

et al. 2022

IJERPH

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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.

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Section: Introductionmentioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

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

Cong

Yang

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…These strategies share the common idea of redesigning the transit services by customizing other flexible fleets to rebuild direct or transferable routes. Passengers who rely on the public transit prefer to change their routes to those with higher time efficiency and fewer transfers ( 7 ). In addition, if the in-vehicle congestion exceeds a certain rate, it would lead to loss of passenger satisfaction ( 8 ), and have an influence on mode choice ( 9 ).…”

mentioning

confidence: 99%

Algorithm and Application of Multi-modal Evacuation Strategy for Intercity Railway Disruption in a Metropolitan Area

Liu

Barker

2022

Transportation Research Record: Journal of the Transportation R

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When an emergency situation befalls the intercity high-speed railway system, response contingency always focuses on mitigating the interruption to the original operation. This study addresses an evacuation problem for stranded passengers by coordination of multi-modal transit, with the immediate recovery of transport corridors and the redesign of transit routes. A multi-modal transit-based evacuation strategy is proposed through a bi-level optimization model. The model simultaneously formulates the selection of lines, vehicle scheduling, and passenger assignment that trades off passenger delay versus operating cost. The upper level uses an integer program to determine the transit lines and fleet size, and the lower level assigns passengers onto multi-modal routes considering their perceptions of transfer and vehicle congestion. A hybrid heuristic algorithm is proposed to solve the complexity from back-up conditions and nonlinear on-route utility. The case study is based on a disruption to the Beijing-Hebei metropolitan transit system, which is composed of five transit modes, to analyze the conflicting objectives under different mode combinations and network topologies. The adaptation for demand distribution with regard to trip distance is studied to recommend the vehicle composition in a realistic situation. The application and analysis procedure aim to enhance the decision-support system. Results show that mode combinations could provide time and cost saving solutions and extend the Pareto frontier. Effectiveness of mode combination is not equivalent to different demand distributions. Multi-modal collaboration would effectively accelerate the evacuation and save costs. These findings may be of interest to decision makers developing efficient response strategies to improve post-disruption resilience.

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Urban rail transit disruption management: Research progress and future directions

Wang,

Jin,

Sun

et al. 2024

Front. Eng. Manag.

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Urban rail transit (URT) disruptions present considerable challenges due to several factors: i) a high probability of occurrence, arising from facility failures, disasters, and vandalism; ii) substantial negative effects, notably the delay of numerous passengers; iii) an escalating frequency, attributable to the gradual aging of facilities; and iv) severe penalties, including substantial fines for abnormal operation. This article systematically reviews URT disruption management literature from the past decade, categorizing it into pre-disruption and post-disruption measures. The pre-disruption research focuses on reducing the effects of disruptions through network analysis, passenger behavior analysis, resource allocation for protection and backup, and enhancing system resilience. Conversely, post-disruption research concentrates on restoring normal operations through train rescheduling and bus bridging services. The review reveals that while post-disruption strategies are thoroughly explored, pre-disruption research is predominantly analytical, with a scarcity of practical pre-emptive solutions. Moreover, future research should focus more on increasing the interchangeability of transport modes, reinforcing redundancy relationships between URT lines, and innovating post-disruption strategies.

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Passenger Travel Behavior Analysis under Unplanned Metro Service Disruption: Using Stated Preference Data in Guangzhou, China

Cited by 9 publications

References 20 publications

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

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

Algorithm and Application of Multi-modal Evacuation Strategy for Intercity Railway Disruption in a Metropolitan Area

Urban rail transit disruption management: Research progress and future directions

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