The City of Toronto has an advanced data and analytics practice that supports transportation safety and mobility programs such as the Vision Zero Road Safety Plan and the Congestion Management Plan. This practice includes the full spectrum of data management: data collection, data operations, advanced data analytics, data science, and digital product delivery.
Much of the code developed for data management and project evaluation is open-source and available in repositories prefixed by “bdit” on the City of Toronto’s GitHub Page.
This page highlights several key transportation datasets available through the City of Toronto’s Open Data Portal, and provides information on related transportation data projects, programs, and initiatives.
The City of Toronto hosts several public transportation-related datasets on the Open Data Portal.
These datasets are used to analyze existing conditions in the right-of-way, prioritize and plan initiatives that address issues and further the City’s safety and mobility goals, and monitor and evaluate the effectiveness of on-street changes.
These datasets help to identify safety issues that affect all road users:
These datasets measure how people move through Toronto’s transportation network:
The City of Toronto collects trip and vehicle operating data from Private Transportation Companies (PTCs) to regulate and evaluate the impacts of the vehicle-for-hire industry on Toronto’s transportation network:
Find more information about traffic signals and control devices here. Select data about the location of signals are available on the Portal:
These datasets contain information about various on-street programs and safety initiatives:
Active Transportation Infrastructure:
Automated Enforcement & Speed Management:
Right-of-Way Usage:
The City has completed three separate analyses of the impacts of the vehicle-for-hire (VFH) industry on the City of Toronto’s Transportation Network.
The most recent 2024 study updates the trends up to September 2024, while completing additional work to better understand the VFH sector.
The executive summary of this analysis can be found as an attachment to the 2024.EX19.4 staff report.
The full report and appendices can be found here:
The 2021 analysis covers the period from October 2018 to July 2021, examining the period following the previous report and the impacts of the COVID-19 pandemic on the vehicle-for-hire industry.
The report was prepared to support the 2021.GL27.19 staff report:
The 2019 analysis covers the period from September 2016 (when Private Transportation Company services were first licensed) to September 2018.
The executive summary of this analysis can be found as attachment to the 2019.GL6.31 staff report. The full report and supplementary documents can be found here:
The City conducted a Micromobility Cordon and Classification Count in the fall of 2022. A cordon count is a study that measures the number of users that cross a prescribed boundary in certain locations within the City. The count recorded the number of people cycling and other micromobility users crossing two boundaries – an inner cordon bounded by Spadina Avenue, Bloor Street, Jarvis Street, and Queens Quay Boulevard, and an outer cordon bounded by Dufferin Street, the CP Rail Corridor (roughly adjacent to Dupont Street), the Don River, and Lake Ontario. It classified people cycling and other micromobility users crossing the cordon boundaries according to the type of bicycle or other micromobility device being used (e.g. e-bicycle, electric kick scooter, Toronto Bike Share), the apparent trip purpose (e.g. food delivery), and the type of infrastructure used (sidewalk, bike lane, or mixed-traffic).
The cordon count supports:
Report and supporting datasets:
In 2020, the City created a measure for monitoring congestion in Toronto referred to as the Travel Time Index (TTI), based on data obtained from a third-party vendor. This metric provides a basis for comparison of congestion levels in the City before and after the pandemic, and also provides a basis for comparison to measure the benefits of the congestion measures implemented to date.
Throughout 2020, the City introduced a variety of COVID-19 response programs in consultation with the Medical Officer of Health to accommodate the need for residents to be outside of their homes while physical distancing. These programs, including ActiveTO, transformed Toronto’s streets to support the city during the first summer of the pandemic. The ActiveTO program included three initiatives: major road closures, quiet streets, and cycling network expansion.
ActiveTO dedicated road space to facilitate active transportation for essential trips and physical activity and is highlighted in the Toronto Office of Recovery and Rebuild's COVID-19: Impacts and Opportunities Report.
The overall ActiveTO monitoring and evaluation strategy included the collection of volume data and bike share data and public intercept surveys that were conducted in partnership with Park People and Clean Air Partnership – The Centre for Active Transportation (TCAT). The results of this evaluation can be found here:
The City deployed sensor technology to monitor the performance of the corridor and surrounding impacts. Reports and dashboards on the performance and impacts of the corridor can be found here.
Relevant datasets include:
In 2018, the City partnered with Code for Canada to build and maintain data management software to store traffic collision and volume data. MOVE is an internal web application and data management platform that centralizes these datasets and enables the City to take a more proactive approach to decision-making and mobility in Toronto. The open-source code is available on GitHub. An overview of the approach and lessons learned from the project is available on the Code for Canada Blog.