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Uncovering the Spatiotemporal Patterns of Regional and Local Driver Sources in a Freeway Network

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  • Pu Wang

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Bin Wang

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Rihong Ke

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Hu Yang

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Shengnan Li

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Jianjun Dai

    (Hunan Communications Research Institute Co., Ltd., Changsha 410015, China)

Abstract

We propose a method to identify the congestion driver sources contributing to the major traffic congestion of a regional (Hunan province) freeway network. The results indicate that the congestion driver sources are mostly observed during heavy traffic periods and mainly distributed in the regions surrounding Changsha (the capital of Hunan province) and the regions adjacent to other provinces and freeway interconnecting hubs. Moreover, we develop a method to analyze the major driver sources of a local freeway section. Using the method, the trips affected by traffic accidents or road maintenance works can be identified well. Our findings and the proposed methods could facilitate the deployment of effective traffic control countermeasures and the development of sustainable regional transportation.

Suggested Citation

  • Pu Wang & Bin Wang & Rihong Ke & Hu Yang & Shengnan Li & Jianjun Dai, 2024. "Uncovering the Spatiotemporal Patterns of Regional and Local Driver Sources in a Freeway Network," Sustainability, MDPI, vol. 16(8), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3344-:d:1376827
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    References listed on IDEAS

    as
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    3. Shengnan Li & Hu Yang & Minglun Li & Jianjun Dai & Pu Wang, 2023. "A Highway On-Ramp Control Approach Integrating Percolation Bottleneck Analysis and Vehicle Source Identification," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    4. Angus Eugene Retallack & Bertram Ostendorf, 2020. "Relationship Between Traffic Volume and Accident Frequency at Intersections," IJERPH, MDPI, vol. 17(4), pages 1-22, February.
    Full references (including those not matched with items on IDEAS)

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