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A Gaussian Kernel-Based Approach for Modeling Vehicle Headway Distributions

Author

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  • Guohui Zhang

    (Department of Civil Engineering, University of New Mexico, Albuquerque, New Mexico 87131)

  • Yinhai Wang

    (The University of Washington and Harbin Institute of Technology Joint Laboratory on Advanced Transportation Technologies, Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195)

Abstract

Headway distribution models are essential for studying traffic flow theory, roadway accidents, and microscopic traffic simulations. Previous work has focused on parametric models. Vehicle headways were considered to follow some known parametric distributions based on certain assumptions. However, these assumptions are not universally acceptable and, consequently, the reliability of those headway distribution models varies significantly when applied to different flow conditions. In this study, a nonparametric distribution model with Gaussian kernel functions is introduced and assessed for vehicle headways on urban multilane freeways. Without any assumptions, Gaussian kernel models can extract intrinsic patterns from observed headway data to describe the distributing attributes of headways. Experiments were conducted to evaluate the accuracy of Gaussian kernel models for modeling vehicle headways. Results from the experiments indicated that the proposed models outperformed traditional parametric methods in a wide range of flow rates. Furthermore, transferability tests of the nonparametric model were performed, and the results showed that the proposed models can be generalized for applications at other locations with similar traffic flow patterns.

Suggested Citation

  • Guohui Zhang & Yinhai Wang, 2014. "A Gaussian Kernel-Based Approach for Modeling Vehicle Headway Distributions," Transportation Science, INFORMS, vol. 48(2), pages 206-216, May.
    • Handle: RePEc:inm:ortrsc:v:48:y:2014:i:2:p:206-216
    DOI: 10.1287/trsc.1120.0451
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    References listed on IDEAS

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    1. Paul Wasielewski, 1979. "Car-Following Headways on Freeways Interpreted by the Semi-Poisson Headway Distribution Model," Transportation Science, INFORMS, vol. 13(1), pages 36-55, February.
    2. David Branston, 1976. "Models of Single Lane Time Headway Distributions," Transportation Science, INFORMS, vol. 10(2), pages 125-148, May.
    3. D. J. Buckley, 1968. "A Semi-Poisson Model of Traffic Flow," Transportation Science, INFORMS, vol. 2(2), pages 107-133, May.
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    Cited by:

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    3. Young Song, Annie & Lee, Seunghyeon & Wong, S.C., 2023. "A machine learning approach to analyzing spatiotemporal impacts of mobility restriction policies on infection rates," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).

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