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Investigating factors that influence bicyclist injury severity in bicycle-motor vehicle crashes at unsignalized intersections in North Carolina

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  • Shatoya Covert Estime

    (Elizabeth City State University)

Abstract

In 2014, North Carolina implemented a strategic highway safety plan to reduce fatalities and serious injuries. The plan defined nine areas of focus to address safety issues; two main areas were investigated, unsignalized intersections and bicyclist safety. The purpose of this study was to evaluate (1) potential factors associated with bicyclist injury severity in bicycle-motor vehicle crashes at unsignalized intersections and (2) the impact of these factors on bicyclist safety. Out of 8,418 bicycle-motor vehicle crash records from the UNC Highway Safety Research Center, 1,273 cases were evaluated. Injury severity is measured on an ordinal scale as minor, major, or severe. Stata's ordinal logistic regression was used to initially analyze potential factors associated with bicyclist injury severity, followed by generalized ordered logit (gologit) via the community-contributed ado-program gologit2 (Williams 2006). Generalized ordered logit relaxes the constraint that a variable has the same estimated coefficient throughout the range of injury severity. Statistical significance was linked to injury severity in the following variables: bicyclists 55 and older, the driver's speed, roadway features, day of week, light conditions, and season.

Suggested Citation

  • Shatoya Covert Estime, 2020. "Investigating factors that influence bicyclist injury severity in bicycle-motor vehicle crashes at unsignalized intersections in North Carolina," 2020 Stata Conference 13, Stata Users Group.
    • Handle: RePEc:boc:scon20:13
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    File URL: http://fmwww.bc.edu/repec/scon2020/us20_Covert.pdf
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