Webinar Series

Ontario’s Pedestrian Crash Causation Study: A Focus on the Impact of Large-Scale Trends on Road Safety

July 7, 2020   |   Categories: Webinar Series

Last Updated on July 7, 2020


Sarah Plonka is a Senior Safety Research Advisor in the Safety, Policy and Education Branch of the Ministry of Transportation (MTO), a graduate of the University of Toronto and a former teacher. Sarah is the winner of the 2017 CARSP Conference Dr. Charles H. Miller Award for best research and evaluation paper for her study on the safety effectiveness of large truck speed limiters. Other contributions to road safety research include: A published systematic review of fitness to drive post stroke; a study on the safety effectiveness of entry-level commercial driver training; and key contributor to MTO’s Ontario Road Safety Annual Report. Sarah brings her research expertise to the issue of pedestrian safety in the newly completed Pedestrian Crash Causation Study, focused on large-scale trends that may be contributing to an increase in pedestrian fatalities in Ontario.

Title of Abstract

Ontario’s Pedestrian Crash Causation Study: A Focus on the Impact of Large-Scale Trends on Road Safety


Ontario has experienced several decades of decreasing motor-vehicle fatalities, however, pedestrian fatalities are becoming a growing proportion of all road-user fatalities. Currently, pedestrian-involved collisions are one of the key contributors to road safety fatalities in Ontario; in 2016, 24 percent of all fatalities (136/579) on Ontario’s roads were pedestrians. A review of literature identified large-scale trends that have changed in recent years that may have had an impact on pedestrian safety; these hypotheses were confirmed/rejected using Ontario collision data.


To first determine the directional trend in pedestrian fatality rate (per 10,000 population) in Ontario. To subsequently assess the impact of changes in select observed large-scale/macroscopic trends on pedestrian fatalities. The following five key areas were assessed for their impact on pedestrian fatality rates in Ontario: 1) The ageing demographic; 2) the potential for an increase in alcohol-consuming pedestrians associated with a decrease in alcohol-consuming drivers; 3) the increasing use of electronic devices by pedestrians and drivers, leading to distraction; 4) the impact of increasing consumer preference for light trucks, in particular sport utility vehicles and pick-up trucks, and 5) the effects of other macro-economic changes.


Trendline modeling of annual counts of Ontario’s pedestrian fatalities per 10,000 persons (2000-2016) was examined for best fit to determine whether the pedestrian fatality rate has been increasing, decreasing or has remained the same. Literature was reviewed to identify large-scale trends that could hypothetically impact pedestrian fatality rates. Inferential analysis of Ontario collision data (1997-2016) confirmed/rejected hypotheses generated through the literature review. Key areas were assessed individually first, and then where possible, in a multi-variate analysis.


Modeling identified that Ontario’s pedestrian fatality rate began increasing in 2010. 1) A predictive relationship between the proportion of people over 75 and proportion of fatally injured pedestrians over 75 exists, and modeling indicated that by 2041 half or more of pedestrian fatalities could be pedestrians 75+; 2) A logistic regression indicated that for a fatally injured pedestrian, the odds of being positive for alcohol have been decreasing over time. 3) A logistic regression indicated that the odds are higher that a driver who kills a pedestrian is inattentive than that a pedestrian is inattentive; Hypothesis 4 and 5 are still be tested.


The intention of this study was to identify factors that are contributing to an increase in pedestrian fatalities in Ontario with the goal of pinpointing areas where applied countermeasures can be most effective.


At this point we have identified the need to seek countermeasures that protect Ontario’s aging population and a focus on the inattentive driver who strikes a pedestrian as most harmful. Limitations: Collision data based on police reports which have variation in detail.