Assessing the Safety of Cyclist–Pedestrian Interactions in Seasonal Pedestrian Streets Using Computer Vision Techniques

Abstract

Pedestrian streets, also known as streets closed to motorized traffic, serve to promote active modes of transportation. This concept offers the potential to enhance safety for the most vulnerable road users while concurrently reducing air pollution. The present study aims to evaluate the safety of interactions between pedestrians and cyclists, focusing on three pedestrian streets within the city of Montreal. Video data was collected during the day in the summer of 2021. Following camera calibration, a total of 80 h of data was analyzed. Each road user detected and tracked was categorized as either a “pedestrian” or “cyclist”. The analysis involves the computation of indicators for individual cyclists (speed and acceleration) and for their interactions with pedestrians (distance and time to collision [TTC]). Two multivariate regression models were estimated to analyze the relationship between TTC or the cyclist speed as the dependent variables and several other factors. The findings from the safety analysis reveal a discernible variation in safety indicator values between distinct sites, even those situated on the same thoroughfare, independent of regulatory measures. The statistical analysis indicates that elevated TTC values correspond to high acceleration and increased distances between pedestrians and cyclists. Moreover, high TTC values are associated negatively with the density of pedestrians within the camera’s field of view. In contrast, concerning speed, high values are linked to low TTC and distances, together with elevated acceleration values.