Evaluating transit network resilience through graph theory and demand-elastic measures: Case study of the Toronto transit system

King, David; Aboudina, Aya; Shalaby, Amer

doi:10.1080/19439962.2018.1556229

Cited by 16 publications

(10 citation statements)

References 16 publications

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“…Transit system resilience has been studied by many researchers to better understand and quantify the effects of a major disruption on users, operators, and the economy. While a wide range of methods exist in the literature to analyze transport resilience, there is no specific method or a single metric to measure and analyze the resilience of a network ( 14 ). Methods from graph theory have been commonly used to analyze the connectivity in the transit and transportation network, while other studies on resilience and vulnerability have been concerned with the interaction between demand and supply, and passenger response to major disruptions ( 3 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Major disruptions lasting for an extended duration (three or more weeks) were shown to have a significant impact on transit ridership ( 1 ). However, other researchers have focused on the resilience of the rail network under operational disruptions with shorter durations ( 4 , 14 , 17 , 18 ) which commonly result from mechanical failures, human emergencies, and other incidents that disrupt the daily operations. This paper is focused on the latter type, using the subway network in Toronto as a case study.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A recent study of the subway system in Toronto examines the effect of outdoor tracks and weather conditions on the recurrence of rail service disruptions while quantifying the delays at the stop level using data collected in 2013 ( 18 ). Another study utilizes graph theory to measure the resilience of the same network ( 14 ). Lastly, Diab et al ( 17 ) used statistical analysis of subway disruption that triggered the deployment and allocation of shuttle buses.…”

Section: Literature Reviewmentioning

confidence: 99%

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Assessing the Bus Bridging Effectiveness on the Operational Resilience of the Subway Service in Toronto

Itani

Shalaby

2021

Transportation Research Record

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Unplanned rail disruptions result in substantial delays to passengers and severe effects on the economy of a large city like Toronto. While bus bridging has been a widely adopted method to replace the subway service in such events, its effect on the operational resilience of the subway service is less often studied. This study assesses the resilience of the subway network of Toronto employing an optimal bus bridging strategy. First, subway incidents are categorized based on their characteristics using K-mean clustering analysis. The incidents are then grouped based on the performance of optimal bus bridging plans. Classification and regression tree analysis is used for this task, employing two metrics: the total user delay and total number of shuttle buses under the optimal bridging scenario. Queueing and optimization models developed previously by the University of Toronto are used to determine and simulate the optimal bus bridging plans of a sample of incidents. The severity of unplanned disruptions is finally demonstrated using a severity scale and the effect of incident duration uncertainty is analyzed. The results show that along the congested city alignments, where the capacity of the roads and stations is limited, the bus bridging service is often insufficient to replace the train service. However, it could be a good alternative in uncongested subway segments where the available street capacity is relatively high, allowing large bus volumes to serve the corridor. This model is easily applicable to different rail systems and it could assess other systems to produce better bridging plans.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Assessing the Bus Bridging Effectiveness on the Operational Resilience of the Subway Service in Toronto

Itani

Shalaby

2021

Transportation Research Record

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“…Recent work has approached the impact of disruption on public transit system performance using accessibility frameworks ( 17 ), graph theory measures ( 18 ), and big data ( 13 , 14 ). These methodologies support investigations into travelers’ behavioral responses ( 17 ) such as mode shift, and into planning robust networks ( 18 ) using, for example, schedule padding ( 19 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Providing real-time information at the stop and vehicle level, GTFS Realtime data provide nuanced and dynamic insights into system performance that are useful for spatiotemporal study. The GTFS format has been instrumental in the analysis of a variety of public transit network measures ( 29 ) including the study of delay ( 19 ), shortest path analysis ( 30 ), accessibility ( 31 , 32 ), and resilience ( 18 ). Vehicle- and stop-level data can be combined with other data sources to better understand how traveler behavior contributes to system performance ( 33 , 34 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Impacts of School Reopening on Variations in Local Bus Performance in Sydney

Yan

Yao

Chen

et al. 2021

Transportation Research Record

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During the COVID-19 pandemic, stay-at-home orders in conjunction with working from home, school closures, and event cancellations resulted in a decrease in travel demand. Under normal circumstances, these activities are components of trip chains and utilize a multimodal transport network. The overall performance of the network can be traced through delays in the bus system as buses capture both changes in ridership and fluctuations in mixed traffic conditions. This paper explores the hypothesis that resumption of a single component in trip chains (i.e., school reopening) is sufficient for a measurable change in transport system performance. This study used school reopening in Sydney, Australia as a case study to explore whether school-related trips affected bus system performance directly with higher student patronage or indirectly with heavier road congestion from parental car trips. Both stop dwell times and differences in delays between successive stops were used as bus service indicators. Dwell times reflect the travel demand for buses and delay differences capture local changes in service reliability. We found that increase in ridership had limited impacts on bus punctuality. However, the level of local bus performance worsened after schools reopened, and the effect was more pronounced in commercial areas in the afternoon when schools ended, suggesting secondary trip purposes such as leisure and shopping in addition to school pick-ups. This study revealed the interaction between different trip purposes during the postshutdown period and threw light on changes in travel behavior patterns as travel restrictions were relaxed in pandemic circumstances.

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Computational methodologies for critical infrastructure resilience modeling: A review

Ji,

He,

Chen

et al. 2024

Advanced Engineering Informatics

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Evaluating transit network resilience through graph theory and demand-elastic measures: Case study of the Toronto transit system

Cited by 16 publications

References 16 publications

Assessing the Bus Bridging Effectiveness on the Operational Resilience of the Subway Service in Toronto

Assessing the Bus Bridging Effectiveness on the Operational Resilience of the Subway Service in Toronto

Impacts of School Reopening on Variations in Local Bus Performance in Sydney

Computational methodologies for critical infrastructure resilience modeling: A review

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