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Exploration on origin–destination-based travel time variability: Insights from Seoul metropolitan area

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  • Kim, Sung Hoo
  • Chung, Jin-Hyuk

Abstract

Travel time variability can be defined as the variation in travel time over a certain time period. This study focuses on O/D-based analysis, which has been rarely studied due to the limited data in the context of travel time variability. The objectives of the study are twofold: to shed light on the O/D-based travel time variability and to get insights on travel time variability in the context of Seoul Metropolitan Area. This study utilizes the web information to obtain real-time estimated travel time data, and employs a Gaussian mixture model (GMM) to model the travel time distributions. The GMM parameters are found to be useful to fit travel time distribution, which exhibits skewness and multimodality, to identify underlying travel time states and to explain variability. The results indicate that O/D-based travel time variability can be characterized and that higher variability occurs during peak hours. In general, the selected O/D pairs are found to have four travel time states but exhibit different patterns. The existence of alternative paths seem to reduce travel time variability at the O/D level. The results suggest directions for future research and implementation of policies.

Suggested Citation

  • Kim, Sung Hoo & Chung, Jin-Hyuk, 2018. "Exploration on origin–destination-based travel time variability: Insights from Seoul metropolitan area," Journal of Transport Geography, Elsevier, vol. 70(C), pages 104-113.
    • Handle: RePEc:eee:jotrge:v:70:y:2018:i:c:p:104-113
    DOI: 10.1016/j.jtrangeo.2018.05.021
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    References listed on IDEAS

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    1. Carrion, Carlos & Levinson, David, 2012. "Value of travel time reliability: A review of current evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 720-741.
    2. Li, Zheng & Hensher, David A. & Rose, John M., 2010. "Willingness to pay for travel time reliability in passenger transport: A review and some new empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 384-403, May.
    3. Kim, Jiwon & Mahmassani, Hani S., 2015. "Compound Gamma representation for modeling travel time variability in a traffic network," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 40-63.
    4. Salonen, Maria & Toivonen, Tuuli, 2013. "Modelling travel time in urban networks: comparable measures for private car and public transport," Journal of Transport Geography, Elsevier, vol. 31(C), pages 143-153.
    5. van Lint, J.W.C. & van Zuylen, Henk J. & Tu, H., 2008. "Travel time unreliability on freeways: Why measures based on variance tell only half the story," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 258-277, January.
    6. Robert B. Noland & John W. Polak, 2002. "Travel time variability: A review of theoretical and empirical issues," Transport Reviews, Taylor & Francis Journals, vol. 22(1), pages 39-54, January.
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    Cited by:

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