Investigating factors that affect conflicts between bicyclists and right turning vehicles at signalized intersections
DOI:
https://doi.org/10.55329/pytz4050Keywords:
bicyclists, cross-sectional regression models, intersection safety, right hook conflicts, safety countermeasures, surrogate measures of safetyAbstract
Due to the recognition of active transportation as a beneficial alternative to more traditional modes of transportation, there is increasing interest in designing infrastructure systems to promote the safe use of forms such as bicycling. Collision data, which are typically used in road safety studies, may be incomplete and the use of such data is reactive as it requires collisions to have already taken place. Additionally, collisions involving bicyclists and vehicles are less common than those between vehicles. As a result, alternative approaches for evaluating the safety effect of various infrastructure attributes, such as the use of surrogate safety measures, specifically traffic conflicts, could be considered. Most collisions between bicyclists and vehicles occur at intersections and of these, collisions between right turning vehicles and bicyclists form the majority. The main objective of this study was to use cross-sectional regression models to investigate various intersection characteristics, including geometry, signal phasing, and bicycle infrastructure, with a view to determining which attributes are associated with a significant effect on right turning conflicts and how this may vary with different conflict severity levels. Using data for 65 signalized intersection approaches across Canada, various intersection attributes were found to be associated with the frequency of right turning conflicts such as exposure levels, the lateral offset of the bicycle facility and the grade of the approach to the intersection. The significance levels of the associated effects of certain attributes were observed to change with the severity level of the conflicts.
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Copyright (c) 2024 Robert Mansell, Bhagwant Persaud, Craig Milligan, Amanda Pushka
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Natural Sciences and Engineering Research Council of Canada
Grant numbers RGPIN-2017-04457;ALLRP 566916–21