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Analysis of Crash Severity for Hazard Material Transportation Using Highway Safety Information System Data

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  • Xiuguang Song
  • Jianqing Wu
  • Hongbo Zhang
  • Rendong Pi

Abstract

Crash severity, as a major concern in the routing and scheduling of hazardous material shipments, has caused great loss of lives and property damage every year. Although abundant studies have been conducted to identify the relationship between different factors on crash severity, the analysis of the severity of hazard material transportation (HMT) crashes is very limited. Factors including road, vehicle, driver, and environment are not well considered in previous studies. This article analyzed the influence of various factors on HMT crash severity using Highway Safety Information System data. The random forest combined with the ordered logistic model is used for factor analysis. The results showed that annual average daily traffic, fatigues/asleep, number of lanes, speeding, adverse weather, and light are the six most important factors affecting HMT crash severity. Different from the non-HMT crashes, driver factor (e.g., driver age, gender, and drug/alcohol influence) was found to be not significantly related to crash severity. Speeding should be strictly forbidden for HMT drivers, considering the potential increased crash severity. Increasing the level of lighting can help reduce the number of severe crashes. The corresponding recommendations were provided based on the regression results.

Suggested Citation

  • Xiuguang Song & Jianqing Wu & Hongbo Zhang & Rendong Pi, 2020. "Analysis of Crash Severity for Hazard Material Transportation Using Highway Safety Information System Data," SAGE Open, , vol. 10(3), pages 21582440209, July.
    • Handle: RePEc:sae:sagope:v:10:y:2020:i:3:p:2158244020939924
    DOI: 10.1177/2158244020939924
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    References listed on IDEAS

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    2. George F. List & Pitu B. Mirchandani & Mark A. Turnquist & Konstantinos G. Zografos, 1991. "Modeling and Analysis for Hazardous Materials Transportation: Risk Analysis, Routing/Scheduling and Facility Location," Transportation Science, INFORMS, vol. 25(2), pages 100-114, May.
    3. Changxi Ma & Wei Hao & Fuquan Pan & Wang Xiang, 2018. "Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-22, June.
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    Cited by:

    1. Xiuguang Song & Rendong Pi & Yu Zhang & Jianqing Wu & Yuhuan Dong & Han Zhang & Xinyuan Zhu, 2021. "Determinants and Prediction of Injury Severities in Multi-Vehicle-Involved Crashes," IJERPH, MDPI, vol. 18(10), pages 1-16, May.
    2. Ming Sun & Ronggui Zhou & Chengwu Jiao & Xiaoduan Sun, 2022. "Severity Analysis of Hazardous Material Road Transportation Crashes with a Bayesian Network Using Highway Safety Information System Data," IJERPH, MDPI, vol. 19(7), pages 1-22, March.
    3. Ming Sun & Ronggui Zhou, 2023. "Investigation on Hazardous Material Truck Involved Fatal Crashes Using Cluster Correspondence Analysis," Sustainability, MDPI, vol. 15(12), pages 1-21, June.

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