Modeling Riders’ Behavioral Responses to Real-Time Information at Light Rail Transit Stations

Yuan Bai · Lina Kattan

21 citations0/0 files storedTransportation Research Record Journal of the Transportation Research Board

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Transportation Planning and Optimization Railway Systems and Energy Efficiency Transportation and Mobility Innovations

Abstract

An advanced passenger information system (APIS) can play a significant role in improving the satisfaction of transit riders in the short term and increasing ridership in the long term. This research focuses on investigating riders’ behavioral responses to en route real-time information on light rail transit (LRT). A survey was designed and conducted to collect LRT riders’ behavioral responses by presenting hypothetical scenarios in Calgary, Alberta, Canada. Two scenarios were examined: an estimated arrival time of 10 min for the next LRT and an LRT service interruption attributable to an incident or weather with no information on expected recovery time. The survey collected 505 responses. Four multinomial logit models were developed and calibrated to explore the factors affecting trip decision making for the described scenarios for commuter and noncommuter trips. The results led to the conclusion that various socioeconomic attributes (e.g., age, gender, and number of autos per household), experience with an APIS (familiarity with APIS and perceived accuracy of APIS), and experience with transit and the LRT system (use of transit as the primary mode of transportation, frequency of LRT use, and familiarity with LRT) had strong influences on travelers’ behavioral responses in the context of real-time LRT information. Analysis of the data also determined that travelers’ actions varied by trip purposes, travel time, and weather conditions.

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References

2005The Geography of urban transportation 2011Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders 2010OneBusAway 1996Variable message signs and radio traffic information: An integrated empirical analysis of drivers' route choice behaviour 2007The combined effect of information and experience on drivers’ route-choice behavior 1996Modeling Revealed and Stated En-Route Travel Response to Advanced Traveler Information Systems 2006Psychological Effects of and Design Preferences for Real-Time Information Displays 2010Evaluation of a bus passenger information system from the users’ point of view in the city of Thessaloniki, Greece

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2018Subway user behaviour when affected by incidents in Toronto (SUBWAIT) survey — A joint revealed preference and stated preference survey with a trip planner tool 2020A stated-preference intercept survey of transit-rider response to service disruptions 2018LRT passengers’ responses to advanced passenger information system (APIS) in case of information inconsistency and train crowding 2016Transit User Behaviour in Response to Service Disruption: State of Knowledge

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