Citation

Schneider RJ, Schmitz A, Lindsey G, Qin X. Transp. Res. Rec. 2021; 2675(8): 468-480.

Copyright

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

DOI

10.1177/0361198121998692

PMID

unavailable

Abstract

Multi-use trails are popular for transportation and recreation, but pedestrians and bicyclists are exposed to motor vehicle traffic at trail crossings (locations where trails cross roadways), creating the risk of crashes, injuries, and fatalities. Many trail crossing design guidelines suggest best practices to make trail crossings safe, but few studies have quantified the statistical relationship between trail user crashes and a broad set of trail crossing characteristics. Our study developed one of the first trail crossing crash models using trail user crashes reported at 197 crossings in the city of Minneapolis, MN, and in the Milwaukee, WI, region between 2011 and 2018. We took advantage of widespread trail counting programs and historic aerial and street-level imagery to create and test more than 30 theoretically important potential explanatory variables. We addressed the challenge that many crossings had small numbers of crashes (or zero crashes) during the study period by using a Poisson-lognormal model. Our model showed significant associations between trail crossing crashes and trail traffic volume, roadway motor vehicle volume, three-way intersections where the trail crosses perpendicular to the mainline roadway, and total crossing length. Although not statistically significant, signalized intersections and limited sight lines between drivers and trail users near crossings may also be associated with more crashes. Future research can build on this study and expand systemic efforts to improve trail crossing safety.

Language: en