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Determining an efficient and precise choice set for public transport based on tracking data

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  • Marra, Alessio Daniele
  • Corman, Francesco

Abstract

To understand the route choices of public transport users, it is important to know the information available to them, and the context present at that moment. In fact, each choice situation in a transport network has different characteristics and possibilities, also depending on the current status of the transport network. In this regard, travel diaries based on tracking technologies can capture precise observations for a long term. In this work, we exploit a large-scale tracking dataset, collected through a mode detection algorithm, to understand route choices of public transport users. We propose a choice set generation algorithm, able to cover more than 94% of the collected trips without any computational constraint. We compare the users’ paths in the public transport network with different choice sets, under multiple performance indicators, including coverage, size, and fit. This latter is computed by the estimation of a Path Size Logit model.

Suggested Citation

  • Marra, Alessio Daniele & Corman, Francesco, 2020. "Determining an efficient and precise choice set for public transport based on tracking data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 168-186.
    • Handle: RePEc:eee:transa:v:142:y:2020:i:c:p:168-186
    DOI: 10.1016/j.tra.2020.10.013
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    Cited by:

    1. Zhu, Yiyang & Jin, Jian Gang & Wang, Hai, 2024. "Path-choice-constrained bus bridging design under urban rail transit disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    2. Marra, Alessio D. & Sun, Linghang & Corman, Francesco, 2022. "The impact of COVID-19 pandemic on public transport usage and route choice: Evidences from a long-term tracking study in urban area," Transport Policy, Elsevier, vol. 116(C), pages 258-268.

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