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Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders

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  • Watkins, Kari Edison
  • Ferris, Brian
  • Borning, Alan
  • Rutherford, G. Scott
  • Layton, David
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    Abstract

    In order to attract more choice riders, transit service must not only have a high level of service in terms of frequency and travel time but also must be reliable. Although transit agencies continuously work to improve on-time performance, such efforts often come at a substantial cost. One inexpensive way to combat the perception of unreliability from the user perspective is real-time transit information. The OneBusAway transit traveler information system provides real-time next bus countdown information for riders of King County Metro via website, telephone, text-messaging, and smart phone applications. Although previous studies have looked at traveler response to real-time information, few have addressed real-time information via devices other than public display signs. For this study, researchers observed riders arriving at Seattle-area bus stops to measure their wait time while asking a series of questions, including how long they perceived that they had waited. The study found that for riders without real-time information, perceived wait time is greater than measured wait time. However, riders using real-time information do not perceive their wait time to be longer than their measured wait time. This is substantiated by the typical wait times that riders report. Real-time information users say that their average wait time is 7.5Â min versus 9.9Â min for those using traditional arrival information, a difference of about 30%. A model to predict the perceived wait time of bus riders was developed, with significant variables that include the measured wait time, an indicator variable for real-time information, an indicator variable for PM peak period, the bus frequency in buses per hour, and a self-reported typical aggravation level. The addition of real-time information decreases the perceived wait time by 0.7Â min (about 13%). A critical finding of the study is that mobile real-time information reduces not only the perceived wait time, but also the actual wait time experienced by customers. Real-time information users in the study wait almost 2Â min less than those arriving using traditional schedule information. Mobile real-time information has the ability to improve the experience of transit riders by making the information available to them before they reach the stop.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 45 (2011)
    Issue (Month): 8 (October)
    Pages: 839-848

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    Handle: RePEc:eee:transa:v:45:y:2011:i:8:p:839-848

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    Keywords: Public transportation Traveler information Real-time information Wait time;

    References

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    1. Lyons, Glenn & Urry, John, 2005. "Travel time use in the information age," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 257-276.
    2. Poudenx, Pascal, 2008. "The effect of transportation policies on energy consumption and greenhouse gas emission from urban passenger transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(6), pages 901-909, July.
    3. Dziekan, Katrin & Kottenhoff, Karl, 2007. "Dynamic at-stop real-time information displays for public transport: effects on customers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(6), pages 489-501, July.
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    Cited by:
    1. Cats, Oded & Loutos, Gerasimos, 2013. "Real-time bus arrival information system: an empirical evaluation," Working papers in Transport Economics 2013:25, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    2. Kuo, Pei-Fen & Lord, Dominique, 2013. "Accounting for site-selection bias in before–after studies for continuous distributions: Characteristics and application using speed data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 256-269.
    3. Kari Watkins & Alan Borning & G. Rutherford & Brian Ferris & Brian Gill, 2013. "Attitudes of bus operators towards real-time transit information tools," Transportation, Springer, vol. 40(5), pages 961-980, September.

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