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CREATING SAFER URBAN ENVIRONMENTS FOR CYCLISTS IN TORONTO - MRP - SMIRNOVA
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<p>Despite Toronto’s dedication to reach Vision Zero goals since 2016, serious injuries and deaths on the roads of the city, including those while cycling, still happen in 2023. The need to prevent serious injuries and deaths of cyclists in Toronto and many other cities in North America is evident. However, research on cyclist safety in the North American context is limited. Therefore, we conducted a study to see which urban environments in Toronto are associated with high injury risks for cyclists and which improvements in the built environment can increase the safety of these vulnerable road users. This study uses the Killed and Seriously Injured dataset provided by Toronto police and the city-wide crowd-sourced cyclist volume dataset provided by Strava Metro to identify hot spots of cyclist injuries and determine the risk to individual cyclists in each of the identified hotspots. Based on these findings, eight types of urban environments in Toronto were identified by K-means clustering analysis and the risks associated with each class were analysed. Based on scientific literature and our analysis, recommendations for improvement for the different types of built environments in Toronto were proposed in the discussion section of this paper. </p>
Title: CREATING SAFER URBAN ENVIRONMENTS FOR CYCLISTS IN TORONTO - MRP - SMIRNOVA
Description:
<p> </p>
<p>Despite Toronto’s dedication to reach Vision Zero goals since 2016, serious injuries and deaths on the roads of the city, including those while cycling, still happen in 2023.
The need to prevent serious injuries and deaths of cyclists in Toronto and many other cities in North America is evident.
However, research on cyclist safety in the North American context is limited.
Therefore, we conducted a study to see which urban environments in Toronto are associated with high injury risks for cyclists and which improvements in the built environment can increase the safety of these vulnerable road users.
This study uses the Killed and Seriously Injured dataset provided by Toronto police and the city-wide crowd-sourced cyclist volume dataset provided by Strava Metro to identify hot spots of cyclist injuries and determine the risk to individual cyclists in each of the identified hotspots.
Based on these findings, eight types of urban environments in Toronto were identified by K-means clustering analysis and the risks associated with each class were analysed.
Based on scientific literature and our analysis, recommendations for improvement for the different types of built environments in Toronto were proposed in the discussion section of this paper.
</p>.
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