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A Heckman selection model for the safety analysis of signalized intersections

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Listed:
  • Xuecai Xu
  • S C Wong
  • Feng Zhu
  • Xin Pei
  • Helai Huang
  • Youjun Liu

Abstract

Purpose: The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously. Methods: This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI), respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years. Results: The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels. Conclusions: A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections.

Suggested Citation

  • Xuecai Xu & S C Wong & Feng Zhu & Xin Pei & Helai Huang & Youjun Liu, 2017. "A Heckman selection model for the safety analysis of signalized intersections," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-16, July.
    • Handle: RePEc:plo:pone00:0181544
    DOI: 10.1371/journal.pone.0181544
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    References listed on IDEAS

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    1. Lord, Dominique & Mannering, Fred, 2010. "The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 291-305, June.
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    Cited by:

    1. Chen Xu & Decun Dong & Dongxiu Ou & Changxi Ma, 2019. "Time-of-Day Control Double-Order Optimization of Traffic Safety and Data-Driven Intersections," IJERPH, MDPI, vol. 16(5), pages 1-18, March.
    2. Cheelo, Tulumbe, 2019. "Milk production and marketing channel decisions of smallholder farmers in the Zambian milk value chain," Research Theses 334747, Collaborative Masters Program in Agricultural and Applied Economics.
    3. Tang, Tie-Qiao & Yi, Zhi-Yan & Zhang, Jian & Wang, Tao & Leng, Jun-Qiang, 2018. "A speed guidance strategy for multiple signalized intersections based on car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 399-409.
    4. Nomsa Y. Nkomo & Beatrice D. Simo-Kengne & Mduduzi Biyase, 2021. "The impact of mental health behaviour on tobacco consumption in South Africa," Economic Development and Well-being Research Group Working Paper Series edwrg-02-2021, University of Johannesburg, College of Business and Economics, revised 2021.
    5. Alex Scott & Christopher W. Craighead & Chris Parker, 2020. "Now You See It, Now You Don't: Explicit Contract Benefits In Extralegal Exchanges," Production and Operations Management, Production and Operations Management Society, vol. 29(6), pages 1467-1486, June.

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