Citation

Jiang C, Tay R, Lu L. Traffic Injury Prev. 2021; ePub(ePub): ePub.

Copyright

(Copyright © 2021, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2020.1852224

PMID

unavailable

Abstract

OBJECTIVE: Hit-and-run behavior in crashes is a severe offense worldwide because the identification and emergency rescue of any injured road user is delayed. A motorist's run from the crash scene is especially serious for a cyclist who would be more prone to be physically injured in a bicycle-vehicle (BV) crash. The objective of this paper is to explore potential risk factors that contribute to the hit-and-run (HR) behavior of a driver after a two-unit BV collision.

METHODS: The data used in this study are extracted from traffic crash records in the city of Durham, North Carolina in 2007-2014. This study uses the skewed logistic (Scobit) model to account for the skewness of the dependent variable (i.e., HR) in the dataset.

RESULTS: The Likelihood ratio test, AIC and BIC results show that the Scobit model is preferred to the standard binary logistic model for modeling a driver's decision to run from a two-unit BV crash scene. Estimation results indicate that, the driver's tendency to run from a crash scene without reporting it in Durham increases if the bicyclist is a teenager or an adult, a drunk-driving or a speeding driver is involved, when the crash happens at night (19:00-6:59), on a local street, or when the automobile overtakes the bicycle. HR behavior will decrease if the cyclist is drunk, an SUV is involved, or the bicyclist fails to yield.

CONCLUSIONS: The findings of this study are important and useful when developing countermeasures to prevent BV-HR crashes and to improve cycling safety.

Language: en

Keywords

road safety; bicycle-vehicle crash; Hit-and-run; logistic model; skewed logistic (Scobit) model