Improve cyclist safety in toronto. The project entered the Safe Roads competition and analyzed geospatial traffic collision data from the Toronto Police Service. This is to support the Toronto Vision Zero initiative in reducing the number of injuries and accidents of vulnerable road-users. 💥💥
“People are cycling in areas with poor infrastructure because it is convenient. This needs to be addressed in the upcoming cycling network.” Ching Man said.
“We were able to plot geospatial data across different layers, finding more collisions happened along the cycle track. This coincided with bike share station areas, suggesting a need to build more stations along the Bike Lane for users to start and end their journeys more safely” Ching Kiu elaborated.
The files uploaded mainly relate to the mapping of the bike share ridership data, allowing the team to analyze where bike users start and end their journey with Latitude and Longitude. First, the data of bike share ridership is merged into one large csv file, then analyzed based on count, year and location.This allows us to identify areas where bike users are getting on and off frequently, and correlate this with the traffic collisions open dataset.
📈 📈 📈 The number of cyclists have sharply increased from 2019 to 2023, from 2 million to 6 million rides per year on the Bike Share platform alone.
- Traffic Collision Open Data from the Toronto Police Service - https://data.torontopolice.on.ca/datasets/bc4c72a793014a55a674984ef175a6f3
- Killed, Seriously Injured dataset (KSI) from the Toronto Police Service - https://data.torontopolice.on.ca/pages/total-ksi
- Cycling Network from the City of Toronto - https://open.toronto.ca/dataset/cycling-network/
- Bike Share Ridership data from the City of Toronto - https://open.toronto.ca/dataset/bike-share-toronto-ridership-data/