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Examining Injury Severity of Pedestrians in Vehicle–Pedestrian Crashes at Mid-Blocks Using Path Analysis

Author

Listed:
  • Haorong Peng

    (The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao’an Road, Jiading, Shanghai 201804, China)

  • Xiaoxiang Ma

    (The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao’an Road, Jiading, Shanghai 201804, China)

  • Feng Chen

    (The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao’an Road, Jiading, Shanghai 201804, China)

Abstract

Walking is a sustainable mode of transport which has well established health and environmental benefits. Unfortunately, hundreds of thousands of pedestrians lose their lives each year over the world due to involvement in road traffic crashes, and mid-blocks witness a significant portion of pedestrian fatalities. This study examined the direct and indirect effects of various contributing factors on the pedestrian injury severity in vehicle–pedestrian crashes at mid-blocks. Data of vehicle–pedestrian crashes during 2002–2009 were extracted from the NASS-GES, with pre-crash behaviors and injury severity included. The SEM path analysis method was applied to uncover the inter-relationships between the pedestrian injury severity and various explanatory variables. Both the direct and indirect effects of these explanatory variables on the pedestrian injury severity were calculated based on the marginal effects in the multinomial and ordered logit models. The results indicate some variables including number of road lanes and the age of pedestrian have indirect impacts on the injury severity through influencing the pre-crash behaviors. Although most indirect effects are relatively small compared with the direct effects, the results in this study still provide some valuable information to improve the overall understanding of pedestrian injury severity at mid-blocks.

Suggested Citation

  • Haorong Peng & Xiaoxiang Ma & Feng Chen, 2020. "Examining Injury Severity of Pedestrians in Vehicle–Pedestrian Crashes at Mid-Blocks Using Path Analysis," IJERPH, MDPI, vol. 17(17), pages 1-16, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:17:p:6170-:d:403873
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    References listed on IDEAS

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    1. Feng Chen & Mingtao Song & Xiaoxiang Ma, 2019. "Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model," IJERPH, MDPI, vol. 16(14), pages 1-12, July.
    2. Ralf Risser & Matus Sucha, 2020. "Start Walking! How to Boost Sustainable Mode Choice—Psychological Measures to Support a Shift from Individual Car Use to More Sustainable Traffic Modes," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
    3. Qiang Zeng & Wei Hao & Jaeyoung Lee & Feng Chen, 2020. "Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis," IJERPH, MDPI, vol. 17(8), pages 1-15, April.
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    Cited by:

    1. Sheng Dong & Afaq Khattak & Irfan Ullah & Jibiao Zhou & Arshad Hussain, 2022. "Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations," IJERPH, MDPI, vol. 19(5), pages 1-23, March.
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    3. Arsalan Esmaili & Kayvan Aghabayk & Nirajan Shiwakoti, 2022. "Latent Class Cluster Analysis and Mixed Logit Model to Investigate Pedestrian Crash Injury Severity," Sustainability, MDPI, vol. 15(1), pages 1-29, December.

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