Modeling Injury Severity Score as a More Precise Measure of Motorcyclist Injuries: A Correlated Random Parameter Corner Solution Framework

To analyze key risk factors in motorcycle crashes, this study quantifies how different “policy-sensitive” factors correlate with injury severity, while controlling for rider and crash specific factors, and other observed/unobserved factors. Data on 321 motorcycle injury crashes from a comprehensive US DOT FHWA’s Motorcycle Crash Causation Study (MCCS) are analyzed. A unique approach is taken by analyzing an anatomical injury severity scoring system, termed as Injury Severity Score (ISS), that provided an overall score by accounting for the possibility of multiple injuries to different body parts of a rider. ISS varies from 1 to 75, averaging at 10.12 for this sample (above 9 is considered serious injury), with a spike at 1 (very minor injury). As two alternative measures of injury severity, a strong correlation is found between AIS and ISS classification (Kendall’s tau of 0.911), but significant contrasts are observed in that, when compared to ISS, AIS tends to underestimate the injury severity sustained by a rider. For modeling, fixed and random parameter Tobit modeling frameworks were used in a corner-solution setting to account for the left-tail spike in the distribution of ISS and to account for unobserved heterogeneity. To additionally account for the interactive effects of key risk factors, the developed random parameters Tobit framework allows for possible correlations among the random parameters. A correlated random parameter Tobit model was found to significantly out-perform uncorrelated random parameter Tobit and fixed parameter Tobit models. Several findings related to rider experience, helmet coverage, and alcohol/multiple drugs intake are quantified.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ANF30 Standing Committee on Motorcycles and Mopeds.
  • Corporate Authors:

    Transportation Research Board

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  • Authors:
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 7p

Subject/Index Terms

Filing Info

  • Accession Number: 01697926
  • Record Type: Publication
  • Report/Paper Numbers: 19-05185
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:41AM