Citation

Lee J, Abdel-Aty M, Huang H, Cai Q. Transp. Res. Rec. 2019; 2673(4): 898-906.

Copyright

(Copyright © 2019, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198119837962

PMID

unavailable

Abstract

Multiple approaches have been proposed to take traffic safety into consideration in long-term transportation plans, referred to as transportation safety planning. Some early studies used trip generation data as the explanatory variables for their macro-level crash safety performance functions, or crash prediction models. However, no study to date has attempted to integrate walking exposure and pedestrian safety at the modeling stage. Thus, a novel methodological framework for integrating the analyses of walking exposure and pedestrian crashes is proposed toward better transportation safety planning for pedestrians. In comparison with walking trips and walking miles, walking hours was identified as the best walking exposure variable by a preliminary analysis. Thus, an integrated modeling structure with walking hours as its exposure variable was developed. The modeling results indicate that climate conditions, population, and car usage patterns affect walking hours, and predicted walking hours, climate conditions, percentage of mid-elderly (64-75 years), proportions of minority race/ethnicity, and percent of tertiary industry occupations have significant effects on pedestrian fatalities. In addition, the integrated modeling framework was compared with non-integrated ones, and the results indicate that the integrated framework outperforms its counterparts in relation to deviance information criterion. The proposed approach and the findings from this study are expected to provide useful insights not only to researchers but also to policy makers and practitioners in the fields of transportation planning and traffic safety.

Language: en