Citation

Zhou B, Roshandeh AM, Zhang S, Ma Z. Procedia Eng. 2016; 137: 554-562.

Copyright

(Copyright © 2016, Elsevier Publishing)

DOI

10.1016/j.proeng.2016.01.292

PMID

unavailable

Abstract

Hit-and-run crashes are accidents where drivers of striking vehicles fail to stop after crashes. Without helping victims or reporting accidents to associated authorities could increase the likelihood of serious injuries and even fatalities. In order to reduce hit-and-run crashes, it is important to understand factors contributing to decisions of fleeing crash scenes. In current study, various factors which could affect occurrences of hit-and-run crashes were thoroughly investigated against six different improper driving behaviors. Logistic regression models were established to facilitate the analysis. Police-reported crash data within Cook County, Illinois, USA between 2004 and 2012 were used in this study. The results showed that variables contributing to hit-and-run crashes varied for different improper driving behaviors. Among six established models, "following too closely" and "distraction by phone" models had most statistically significant variables. This study also concluded that following variables would increase the likelihood of hit-and-run crashes in at least one model: multiple vehicle crash, weekend, population of 2,500 - 5,000, population of 5,000 - 10,000, national highway system, traffic signal, yield sign, shoulder, darkness, and less than three lanes. The results of current study could offer important insights for reducing hit-and-run crashes in both planning and operational levels.

Language: en