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Does real-time transit information reduce waiting time? An empirical analysis

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  • Liu, Luyu
  • Miller, Harvey J.

Abstract

A claimed benefit of real-time information (RTI) apps in public transit systems is the reduction of waiting time by allowing passengers to appropriately time their arrivals at transit stops. Although previous research investigated the overall impact of RTI on waiting time, few studies examine the mechanisms underlying these claims, and variations in its effectiveness over time and space. In this paper, we theorize and validate the sources of RTI-based users’ waiting time penalties: reclaimed delay (bus drivers compensating for being behind schedule) and discontinuity delay (an artifact of the update frequency of RTI). We compare two RTI-based strategies – the greedy strategy used by popular trip planning apps and a prudent strategy with an insurance buffer – with non-RTI benchmarks of arbitrary arrival and following the schedule. Using real-time bus location data from a medium-sized US city, we calculate the empirical waiting times and risk of missing a bus for each trip planning strategy. We find that the best RTI strategy, a prudent tactic with an optimized insurance time buffer, performs roughly the same as the simple, follow-the-schedule tactic that does not use RTI. However, relative performance varies over time and space. Moreover, the greedy tactic in common transit apps is the worst strategy, even worse than showing up at a bus stop arbitrarily. These results suggest limitations on claims that RTI reduces public transit waiting times.

Suggested Citation

  • Liu, Luyu & Miller, Harvey J., 2020. "Does real-time transit information reduce waiting time? An empirical analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 167-179.
  • Handle: RePEc:eee:transa:v:141:y:2020:i:c:p:167-179
    DOI: 10.1016/j.tra.2020.09.014
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    References listed on IDEAS

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    1. Konstantinos Papangelis & John D. Nelson & Somayajulu Sripada & Mark Beecroft, 2016. "The effects of mobile real-time information on rural passengers," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(1), pages 97-114, February.
    2. Brakewood, Candace & Barbeau, Sean & Watkins, Kari, 2014. "An experiment evaluating the impacts of real-time transit information on bus riders in Tampa, Florida," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 409-422.
    3. Oded Cats & Zafeira Gkioulou, 2017. "Modeling the impacts of public transport reliability and travel information on passengers’ waiting-time uncertainty," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 247-270, September.
    4. Watkins, Kari Edison & Ferris, Brian & Borning, Alan & Rutherford, G. Scott & Layton, David, 2011. "Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 839-848, October.
    5. Candace Brakewood & Kari Watkins, 2019. "A literature review of the passenger benefits of real-time transit information," Transport Reviews, Taylor & Francis Journals, vol. 39(3), pages 327-356, May.
    6. Cats, Oded & Loutos, Gerasimos, 2016. "Evaluating the added-value of online bus arrival prediction schemes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 35-55.
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    Cited by:

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    2. Javanmard, Reyhane & Lee, Jinhyung & Kim, Junghwan & Liu, Luyu & Diab, Ehab, 2023. "The impacts of the modifiable areal unit problem (MAUP) on social equity analysis of public transit reliability," Journal of Transport Geography, Elsevier, vol. 106(C).
    3. Singh, Suraj Shirodkar & Javanmard, Reyhane & Lee, Jinhyung & Kim, Junghwan & Diab, Ehab, 2021. "The new BRT system has led to an overall increase in transit-based accessibility to essential services during the COVID-19 pandemic: Empirical evidence from Winnipeg, Canada," OSF Preprints anjd7, Center for Open Science.
    4. Ansari Esfeh, Mohammad & Saidi, Saeid & Wirasinghe, S.C. & Kattan, Lina, 2022. "Waiting time and headway modeling considering unreliability in transit service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 219-233.

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