Citation

Marshall WE, Garrick NW. Accid. Anal. Prev. 2011; 43(3): 769-781.

Affiliation

University of Colorado Denver, Department of Civil Engineering, 1200 Larimer Street, Campus Box 113, Denver, CO 80217, United States.

Copyright

(Copyright © 2011, Elsevier Publishing)

DOI

10.1016/j.aap.2010.10.024

PMID

21376865

Abstract

Negative binomial regression models were used to assess the effect of street and street network characteristics on total crashes, severe injury crashes, and fatal crashes. Data from over 230,000 crashes taking place over 11 years in 24 California cities was analyzed at the U.S. Census Block Group level of geography. In our analysis we controlled for variables such as vehicle volumes, income levels, and proximity to limited access highways and to the downtown area. Street network characteristics that were considered in the analysis included street network density and street connectivity along with street network pattern. Our findings suggest that for all levels of crash severity, street network characteristics correlate with road safety outcomes. Denser street networks with higher intersection counts per area are associated with fewer crashes across all severity levels. Conversely, increased street connectivity as well as additional travel lanes along the major streets correlated with more crashes. Our results suggest that in assessing safety, it is important to move beyond the traditional approach of just looking at the characteristics of the street itself and examine how the interrelated factors of street network characteristics, patterns, and individual street designs interact to affect crash frequency and severity.

Language: en