Citation

Russo B, Kothuri S, Smaglik E, Hurwitz D. Transp. Res. Rec. 2023; 2677(12): 187-200.

Copyright

(Copyright © 2023, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981231167414

PMID

unavailable

Abstract

Transportation modes converge at intersections resulting in conflicts between bicyclists and motor vehicles. A common conflict and crash type involving bicycles at intersections is the right-hook, where a right-turning vehicle collides with a through bicyclist. While various geometric and signal control treatments have been used in attempts to mitigate bicycle-vehicle crashes and conflicts, agencies often face questions about optimal treatment selection. To date, limited research has been conducted to analyze how certain treatments (bike boxes, mixing zones, and bicycle signals) along with traffic characteristics (e.g., vehicle, bicycle, and pedestrian volumes) affect the frequency of bicycle-vehicle conflicts, as well as the severity of such conflicts. To address this research need, this study provides an analysis of bicycle-vehicle conflicts extracted from field-collected videos at 12 intersections; three with bike boxes, three with mixing zones, three with bicycle signals, and three control sites with no specific bicycle treatment. From these videos, bicycle-vehicle conflicts were identified and their severity measured using post-encroachment time (PET), along with conflict-involved road user speeds and hourly road user volumes. From these data, a series of Poisson regression models were estimated to assess hourly predicted conflicts as a function of bicycle and vehicle volumes across different treatment types. Additionally, differences in conflict severity across treatments were analyzed, including use of a novel measure which incorporates both PET and vehicle speed. Ultimately, several differences in conflict frequency and severity were observed between the treatment types, providing new data-driven guidance to assist practitioners in treatment selection.

Language: en