An Online Portal for Making Sense of Toronto Traffic Data

With so many potential sources of data with which to analyze traffic behaviors and real-time conditions, University of Toronto engineers have created an online portal that could one day help drive a system populated with autonomous cars.

1 minute read

October 25, 2015, 5:00 AM PDT

By James Brasuell @CasualBrasuell

Tyler Irving explains the Connected Vehicles and Smart Transportation (CVST) portal, a new tool that "aims to bring harmony to how we monitor and manage traffic by integrating existing traffic monitoring data, using new technologies to address the gaps and generating insights that can inform decision making."

The portal, overseen by University of Toronto Engineering Professor Alberto Leon-Garcia with support from the University of Toronto Transportation Research Institute, includes a high-definition video feed produced by drones among data collected from "smart phones (Google Maps, Twitter), TTC buses, BIXI bicycles, border crossings and much more." Irving explains more about how the portal makes sense of all that data:

"Although it pulls all these data sources together, CVST is more than simply an aggregator of new and existing information. It also incorporates an analytics layer, which uses machine learning and other techniques to translate data into useful information. Crucially, these outputs are made available via an open application program interface (API). This allows anyone from curious citizens to city planners to app developers to leverage the system in order to meet their own needs."

Saturday, October 24, 2015 in U of T Engineering News

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