Pedestrian safety at signalized intersections: Modelling spatial effects of exposure, geometry and signalization on a large urban network

Publication date: January 2020Source: Accident Analysis & Prevention, Volume 134Author(s): Joshua Stipancic, Luis Miranda-Moreno, Jillian Strauss, Aurélie LabbeAbstractIntersections represent the most dangerous sites in the road network for pedestrians: not only is modal separation often impossible, but elements of geometry, traffic control, and built environment further exacerbate crash risk. Evaluating the safety impact of intersection features requires methods to quantify relationships between different factors and pedestrian injuries. The purpose of this paper is to model the effects of exposure, geometry, and signalization on pedestrian injuries at urban signalized intersections using a Full Bayes spatial Poisson Log-Normal model that accounts for unobserved heterogeneity and spatial correlation. Using the Integrated Nested Laplace Approximation (INLA) technique, this work leverages a rich database of geometric and signalization variables for 1864 intersections in Montreal, Quebec. To collect exposure data, short-term pedestrian and vehicle counts were extrapolated to AADT using developed expansion factors. Results of the model confirmed the positive relationship between pedestrian and vehicle volumes and pedestrian injuries. Curb extensions, raised medians, and exclusive left turn lanes were all found to reduce pedestrian injuries, while the total number of lanes and the number of commercial entrances were found to increase them. Pedestrian priority phases reduced inju...
Source: Accident Analysis and Prevention - Category: Accident Prevention Source Type: research