Citation

Sultana M, Qin X, Chitturi M, Noyce D. Transp. Res. Rec. 2014; 2404: 68-76.

Copyright

(Copyright © 2014, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.3141/2404-08

PMID

unavailable

Abstract

According to NHTSA, more than 400,000 truck-related crashes occurred in 2009; approximately 7,800 of those were fatal. Truck-related crashes undermine the truck's remarkable contribution to the U.S. economy. Truck safety research on arterial streets is considerably disproportionate when compared with the extensive studies of truck safety on freeways. Identifying critical factors that contribute to truck-related crashes and developing remedial and preventive strategies to reduce truck-related crashes and their consequences on arterials are imperative. Truck-related crashes can be mitigated through careful planning of the location, design, and operation of driveways, median openings, and street connections. In this study, access-related data were collected manually in addition to roadway geometric characteristics. The augmented data offered more explanation and prediction power for truck crashes. The standard deviation of commercial driveway throat width, commercial driveway throat width with flare and its standard deviation, and the proportion of divided commercial driveway, signal density, and shoulder width were significant factors for crash frequency prediction. A generalized negative binomial model was used to identify sources of data overdispersion. This study found that some previously significant variables were no longer significant after access parameters were added; this finding demonstrated the impact of access parameters on truck-related crashes on arterials. This noticeable change in the statistical models composed of different variables is a reminder that a spurious relationship can form if a causal relationship is nonexistent.