Modeling violation of Hawaii's crosswalk law

Accid Anal Prev. 2008 May;40(3):894-904. doi: 10.1016/j.aap.2007.10.004. Epub 2007 Nov 6.

Abstract

In 2005, Hawaii strengthened its pedestrian crosswalk laws. Previously, motorists had the option yielding or slowing down at a crosswalk and had to stop "only when necessary." The new law requires drivers to stop and yield to pedestrians at crosswalks. The purpose of this study is to examine patterns of violation and compliance with the law among both pedestrians and drivers. Observational studies at crosswalks were done in the Spring of 2006. In addition to reporting on overall rates of compliance, the characteristics of both pedestrians and drivers who either violate or comply with the law are described. While pedestrian compliance is higher than that of drivers, there are interesting differences to report in terms of age, gender, type of intersection, land use, and other factors. In addition to the results of a descriptive analysis, logistic regression models predicting the likelihood of violation of the crosswalk laws by either pedestrians or drivers, as a function of their characteristics, the type of intersection, and other factors are presented. The study finds that drivers tend to commit proportionately more violations than pedestrians, and violations are committed by a broader range of drivers than pedestrians. These results suggest that education and enforcement should be directed towards drivers. Future directions for research and enhancing the safety of pedestrians are described in a concluding section.

MeSH terms

  • Accidents, Traffic / legislation & jurisprudence*
  • Accidents, Traffic / statistics & numerical data
  • Adolescent
  • Adult
  • Age Factors
  • Automobile Driving / legislation & jurisprudence*
  • Automobile Driving / statistics & numerical data
  • Automobiles / legislation & jurisprudence*
  • Automobiles / statistics & numerical data
  • Child
  • Female
  • Hawaii
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Models, Statistical
  • Risk-Taking*
  • Sex Factors
  • Walking / physiology*