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The joint analysis of injury severity of drivers in two-vehicle crashes accommodating seat belt use endogeneity

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  • Abay, Kibrom A.
  • Paleti, Rajesh
  • Bhat, Chandra R.

Abstract

The current study contributes to the existing injury severity modeling literature by developing a multivariate probit model of injury severity and seat belt use decisions of both drivers involved in two-vehicle crashes. The modeling approach enables the joint modeling of the injury severity of multiple individuals involved in a crash, while also recognizing the endogeneity of seat belt use in predicting injury severity levels as well as accommodating unobserved heterogeneity in the effects of variables. The proposed model is applied to analyze the injury severity of drivers involved in two-vehicle road crashes in Denmark.

Suggested Citation

  • Abay, Kibrom A. & Paleti, Rajesh & Bhat, Chandra R., 2013. "The joint analysis of injury severity of drivers in two-vehicle crashes accommodating seat belt use endogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 74-89.
    • Handle: RePEc:eee:transb:v:50:y:2013:i:c:p:74-89
    DOI: 10.1016/j.trb.2013.01.007
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    4. 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.
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    6. Afghari, Amir Pooyan & Faghih Imani, Ahmadreza & Papadimitriou, Eleonora & van Gelder, Pieter & Hezaveh, Amin Mohamadi, 2021. "Disentangling the effects of unobserved factors on seatbelt use choices in multi-occupant vehicles," Journal of choice modelling, Elsevier, vol. 41(C).
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    10. Rahman, Moshiur & Yasmin, Shamsunnahar & Eluru, Naveen, 2019. "Controlling for endogeneity between bus headway and bus ridership: A case study of the Orlando region," Transport Policy, Elsevier, vol. 81(C), pages 208-219.
    11. Tong Zhu & Zishuo Zhu & Jie Zhang & Chenxuan Yang, 2021. "Electric Bicyclist Injury Severity during Peak Traffic Periods: A Random-Parameters Approach with Heterogeneity in Means and Variances," IJERPH, MDPI, vol. 18(21), pages 1-19, October.
    12. Miguel Santolino & Luis Céspedes & Mercedes Ayuso, 2022. "The Impact of Aging Drivers and Vehicles on the Injury Severity of Crash Victims," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    13. B. Claus & L. Warlop, 2022. "The Car Cushion Hypothesis: Bigger Cars Lead to More Risk Taking—Evidence from Behavioural Data," Journal of Consumer Policy, Springer, vol. 45(2), pages 331-342, June.
    14. Abay, Kibrom A., 2015. "Evaluating simulation-based approaches and multivariate quadrature on sparse grids in estimating multivariate binary probit models," Economics Letters, Elsevier, vol. 126(C), pages 51-56.
    15. Miguel Santolino & Mercedes Ayuso, 2020. "Number and severity of BI victims, assuming dependence between vehicles involved in the crash," IREA Working Papers 202018, University of Barcelona, Research Institute of Applied Economics, revised Dec 2020.
    16. Xiaojun Shao & Xiaoxiang Ma & Feng Chen & Mingtao Song & Xiaodong Pan & Kesi You, 2020. "A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions," IJERPH, MDPI, vol. 17(2), pages 1-18, January.
    17. Abay, Kibrom A., 2013. "Examining pedestrian-injury severity using alternative disaggregate models," Research in Transportation Economics, Elsevier, vol. 43(1), pages 123-136.

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