Citation

Ugan J, Abdel-Aty M, Cai Q, Mahmoud N, Al-Omari M. Transp. Res. Rec. 2021; ePub(ePub): ePub.

Copyright

(Copyright © 2021, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981211036681

PMID

unavailable

Abstract

In recent years, cycling has become an increasingly popular transportation mode around the world. In comparison with other popular modes of transportation, cycling is economical and energy efficient. While many studies have been conducted for the analysis of bicycle safety, most were limited in bicycle exposure data and on-street data. This study tries to improve the current safety performance functions for bicycle crashes at urban corridors by utilizing crowdsource data from STRAVA and on-street speed management strategies data. Speed management strategies are any roadway alterations that cause a change in motorists' driving behavior. In Florida, these speed management strategies are defined by the Florida Department of Transportation design manual. Considering the disproportionate representation of cyclists from the STRAVA data, adjustments were made to represent more accurately the cyclists based on the video detection data by developing a Tobit model. The adjusted STRAVA data was used for bicyclist exposure to analyze bicycle crashes on urban arterials. A Bayesian joint model was developed to identify the relations between the bicycle crash frequency and factors relating to speed management strategies. Other factors, such as vehicle traffic data, roadway information, socio-demographic characteristics, and land use data, were also considered in the model. The results suggest that the adjusted STRAVA data could be used as the exposure for bicycle crash analysis. The results also highlight the significant effects of speed management strategies, such as parking lots and surface pavement. It is expected that these findings could help engineers develop effective strategies to enhance safety for bicyclists.

Language: en