title: Cyclist activity and injury risk analysis at signalized intersections: a Bayesian modelling approach.
abstract: This study proposes a two-equation Bayesian modelling approach to simultaneously study cyclist injury occurrence and bicycle activity at signalized intersections as joint outcomes. This approach deals with the potential presence of endogeneity and unobserved heterogeneities and is used to identify factors associated with both cyclist injuries and volumes. Its application to identify high-risk corridors is also illustrated. Montreal, Quebec, Canada is the application environment, using an extensive inventory of a large sample of signalized intersections containing disaggregate motor-vehicle traffic volumes and bicycle flows, geometric design, traffic control and built environment characteristics in the vicinity of the intersections. Cyclist injury data for the period of 2003-2008 is used in this study. Also, manual bicycle counts were standardized using temporal and weather adjustment factors to obtain average annual daily volumes. Results confirm and quantify the effects of both bicycle and motor-vehicle flows on cyclist injury occurrence. Accordingly, more cyclists at an intersection translate into more cyclist injuries but lower injury rates due to the non-linear association between bicycle volume and injury occurrence. Furthermore, the results emphasize the importance of turning motor-vehicle movements. The presence of bus stops and total crosswalk length increase cyclist injury occurrence whereas the presence of a raised median has the opposite effect. Bicycle activity through intersections was found to increase as employment, number of metro stations, land use mix, area of commercial land use type, length of bicycle facilities and the presence of schools within 50-800 m of the intersection increase. Intersections with three approaches are expected to have fewer cyclists than those with four. Using Bayesian analysis, expected injury frequency and injury rates were estimated for each intersection and used to rank corridors. Corridors with high bicycle volumes, located mainly in the central neighbourhoods of Montreal, have lower risk of injury. These results may reflect the "safety in numbers" hypothesis or cyclist preference towards safer intersections and corridors. Despite these corridors having a lower individual risk, they are nevertheless associated with a greater number of injuries.
authors.affiliation: Department of Civil Engineering and Applied Mechanics, McGill University, Macdonald Engineering Building, 817 Sherbrooke Street West, Montréal, QC H3A 2K6, Canada. Electronic address: jillian.strauss@mail.mcgill.ca.
authors.forename: Jillian
authors.initials: J
authors.lastname: Strauss
authors.forename: Luis F
authors.initials: LF
authors.lastname: Miranda-Moreno
authors.forename: Patrick
authors.initials: P
authors.lastname: Morency
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001499:Bayes Theorem; D001642:Bicycling / Q000293:injuries*; D004779:Environment Design / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D018986:Motor Vehicles / Q000706:statistics & numerical data; D011792:Quebec; D012044:Regression Analysis; D018570:Risk Assessment
keywords: Bayesian framework; Bicycle injuries; Geometric design and built environment; Signalized intersections