Citation

Dai D. J. Transp. Geogr. 2012; 24: 206-214.

Copyright

(Copyright © 2012, Elsevier Publishing)

DOI

10.1016/j.jtrangeo.2012.02.005

PMID

unavailable

Abstract

There is a growing concern about pedestrian injuries on road. Using pedestrian crash records (2000-2007) from the Georgia Department of Transportation as a case study, this paper applied a spatiotemporal clustering technique to identify clusters of injured pedestrians and then investigated the influence of personal and environmental factors on pedestrian injuries. The Bernoulli model in SatScan was used to detect the roadway segments, where pedestrian injuries were significantly clustered. Descriptive statistics and temporal (yearly, monthly, day of week, and hourly) trends of the injuries were explored, respectively. The logistic regression model was used to assess the injury risk associated with pedestrian factors (gender, age, intoxication, and maneuvers), driver's factors (gender, age, and intoxication), and environmental factors (light conditions, surface conditions, and weather conditions). The results showed that suburban high-activity corridors, where state highways intersect local streets, significantly elevated injury risks in crashes compared to other areas. The percentage of injuries was pronounced in summers, on the weekends, and from evenings to early mornings. Age, pedestrian maneuvers, and inadequate lighting were significant risk factors for pedestrian injuries. Walking/driving under influence and male pedestrians/motorists showed an increased risk of injuries when only the main effect of the factors was considered. The high-risk roadway segment and the risk factors highlight the need for heightened investigation and education in the specific areas and populations.