Effects of Link Capacity Reductions on the Reliability of an Urban Rail Transit Network

Link capacity reductions, which occur often, degrade the service quality and performance of urban rail transit (URT) networks. To measure the reliability of a URT network when link capacity reductions occur in a given time period, the passengers’ generalized travel cost (GTC) is computed and passengers are divided into three categories. The GTC considers here the crowding in trains, seat availability, and perceived travel time. Passengers whose relative increase in GTC on a URT is below or above a preset threshold belong to category I or II, respectively, while passengers who cannot travel on the URT due to insufficient capacities on their paths belong to category III. Passenger trips in categories I are acceptable since their GTC increases only slightly with link capacity reductions. The fraction of acceptable trip (FAT) and total GTC increase ratio (TGCR) in a given time period are defined here as the network’s reliability and unreliability metrics, respectively. The ratio of affected passenger trip (RAPT) is proposed to identify each line’s most critical links. The reliability and unreliability metrics of Wuhan’s URT network during evening peak hours are computed when the capacities of the most critical link or multiple most critical links are reduced. The results show that the proposed RAPT indicator is effective in identifying the most critical links that greatly affect the reliability and performance of a URT network. For capacity reductions on a line’s most critical link, the proposed method can determine the capacity reduction ratio corresponding to network’s high FAT and low TGCR as well as the priorities of lines needing emergency measures to maintain high network reliability and performance. For capacity reductions on critical links of multiple lines, the proposed method can identify the number of reduction links and the capacity reduction ratio that the network can withstand while maintaining its reliability and performance above a specified level.

[1]  Anthony Chen,et al.  Performance of transportation network under perturbations: Reliability, vulnerability, and resilience , 2020 .

[2]  Yao Xiao,et al.  Robustness analysis of urban transit network based on complex networks theory , 2013, Kybernetes.

[3]  Gilbert Laporte,et al.  Evaluating passenger robustness in a rail transit network , 2012 .

[4]  H. J. van Zuylen,et al.  A framework for robustness analysis of road networks for short term variations in supply , 2012 .

[5]  Ahmed M El-Geneidy,et al.  Bus Transit Service Reliability and Improvement Strategies: Integrating the Perspectives of Passengers and Transit Agencies in North America , 2015 .

[6]  M. O’Mahony,et al.  Examining the factors that impact public transport commuting satisfaction , 2009 .

[7]  Xiangdong Xu,et al.  Examining the scaling effect and overlapping problem in logit-based stochastic user equilibrium models , 2012 .

[8]  E. Jenelius.  Public transport experienced service reliability: Integrating travel time and travel conditions , 2018, Transportation Research Part A: Policy and Practice.

[9]  Gabriela Beirão,et al.  Understanding attitudes towards public transport and private car: A qualitative study , 2007 .

[10]  Oded Cats,et al.  Passenger Travel Time Reliability for Multimodal Public Transport Journeys , 2019 .

[11]  Yongxue Liu,et al.  Robustness assessment of urban rail transit based on complex network theory: a case study of the Beijing Subway , 2015 .

[12]  Chao Yang,et al.  Alternate Capacity Reliability Measures for Transportation Networks , 2013 .

[13]  Hyun Kim,et al.  Network Reliability and Resilience of Rapid Transit Systems , 2015 .

[14]  Todd Litman,et al.  Impacts of Rail Transit on the Performance of a Transportation System , 2005 .

[15]  Hyun Kim,et al.  Examining Accessibility and Reliability in the Evolution of Subway Systems , 2015 .

[16]  Alan Nicholson,et al.  DEGRADABLE TRANSPORTATION SYSTEMS: SENSITIVITY AND RELIABILITY ANALYSIS , 1997 .

[17]  Todd Litman.  Part 2: Rail Transit and Commuter Rail: Impacts of Rail Transit on the Performance of a Transportation System , 2005 .

[18]  Daniel Sun,et al.  Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China , 2015 .

[19]  Erik Jenelius,et al.  Vulnerability and resilience of transport systems : A discussion of recent research , 2015 .

[20]  Fang Xu,et al.  Characteristics and Reliability Analysis of the Complex Network In Guangzhou Rail Transit , 2013, Intell. Autom. Soft Comput..

[21]  Jing Liu,et al.  Network Vulnerability Analysis of Rail Transit Plans in Beijng-Tianjin-Hebei Region Considering Connectivity Reliability , 2017 .

[22]  Michael G.H. Bell,et al.  A game theory approach to measuring the performance reliability of transport networks , 2000 .

[23]  Henry X. Liu,et al.  Method of Successive Weighted Averages (MSWA) and Self-Regulated Averaging Schemes for Solving Stochastic User Equilibrium Problem , 2009 .

[24]  Nils A. Bruzelius.  Microeconomic theory and generalised cost , 1981 .

[25]  Erik Jenelius,et al.  Beyond a complete failure: the impact of partial capacity degradation on public transport network vulnerability , 2018 .

[26]  Elise Miller-Hooks,et al.  Assessing the role of network topology in transportation network resilience , 2015 .

[27]  L Lesley,et al.  Generalised Costs and the Value of Time as a Method of Patronage Forecasting , 2009 .

[28]  T. Litman.  Valuing Transit Service Quality Improvements , 2008 .

[29]  Paul Schonfeld,et al.  Measures of Travel Reliability on an Urban Rail Transit Network , 2020, Journal of Transportation Engineering, Part A: Systems.

[30]  M. Wardman,et al.  Twenty Years of Rail Crowding Valuation Studies: Evidence and Lessons from British Experience , 2011 .

[31]  Frank J. Cesario,et al.  Value of time in recreation benefit studies. , 1976 .

[32]  Yong Yin,et al.  Connectivity Reliability on an Urban Rail Transit Network from the Perspective of Passenger Travel , 2019 .

[33]  W. Y. Szeto,et al.  Probabilistic assessment of transport network vulnerability with equilibrium flows , 2020 .

[34]  Yena Song,et al.  An integrated measure of accessibility and reliability of mass transit systems , 2018 .

[35]  Qing-Chang Lu,et al.  Modeling network resilience of rail transit under operational incidents , 2018, Transportation Research Part A: Policy and Practice.

[36]  Hironori Kato,et al.  Comparative analysis of transit assignment: evidence from urban railway system in the Tokyo Metropolitan Area , 2010 .

[37]  Niels van Oort,et al.  Incorporating service reliability in public transport design and performance requirements: International survey results and recommendations , 2014 .

[38]  Darren M. Scott,et al.  Network Robustness Index : a new method for identifying critical links and evaluating the performance of transportation networks , 2006 .