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A Random Parameters Multinomial Logit Model Analysis of Median Barrier Crash Injury Severity on Wyoming Interstates

Author

Listed:
  • Milhan Moomen

    (Louisiana Transportation Research Center, 4101 Gourrier Avenue, Baton Rouge, LA 70808, USA)

  • Amirarsalan Mehrara Molan

    (Department of Civil Engineering, University of Mississippi, 206 Carrier Hall, University, MS 38677, USA)

  • Khaled Ksaibati

    (Department of Civil Engineering, University of Mississippi, 206 Carrier Hall, University, MS 38677, USA
    Department of Civil & Architectural Engineering, 1000 E. University Avenue, Laramie, WY 82071, USA)

Abstract

This paper investigated factors influencing injury severity of crashes involving median traffic barriers, including the impact of barrier characteristics and their geometric features in Wyoming. Combining field data of inventoried median barriers with crash data on Wyoming interstates highways, a random parameters multinomial logit (mixed logit) model of injury severity was estimated. This methodological approach allowed for the possibility of estimated model parameters to vary randomly across crash observations to account for heterogeneity with respect to driver characteristics, roadway attributes, and vehicle characteristics. The estimation results indicated concrete barriers installed on front side-slopes and box beam barriers were associated with severe injury crashes. It was also found that median barrier crashes involving sports utility vehicles, pickups, and improperly restraint vehicle occupants are complex and vary significantly across observations. Other statistically significant variables found to increase the likelihood of severe injury crashes were rural interstate roads, concrete barriers installed on a front side-slope, box beam barriers with lateral offset less than 2 feet, and rollover crashes. These parameters were fixed across observations. The findings of this research point to the need to further investigate the impacts of sport utility vehicles, pickups, and rollover crashes on median barrier crash injury severity.

Suggested Citation

  • Milhan Moomen & Amirarsalan Mehrara Molan & Khaled Ksaibati, 2023. "A Random Parameters Multinomial Logit Model Analysis of Median Barrier Crash Injury Severity on Wyoming Interstates," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:10856-:d:1191334
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    References listed on IDEAS

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    1. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    2. Kenneth E. Train & Terry Atherton, 1995. "Rebates, Loans, and Customers' Choice of Appliance Efficiency Level: Combining Stated- and Revealed-Preference Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 55-70.
    3. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    4. Eisenberg, D. & Warner, K.E., 2005. "Effects of snowfalls on motor vehicle collisions, injuries, and fatalities," American Journal of Public Health, American Public Health Association, vol. 95(1), pages 120-124.
    5. 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.
    6. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    7. Archilla, Ricardo & Morrall, John, 1996. "Traffic characteristics on two-lane highway downgrades," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(2), pages 119-133, March.
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