Location: Room SF3103, 3rd floor, Sandford Fleming Building, 10 King’s College Road, University of Toronto.   MAP

The Big Data Innovation Team, in partnership with Municipal Licensing and Standards, prepared an analysis of the impacts of Vehicles for Hire and Private Transportation Companies on the City of Toronto’s Transportation Network including on congestion, equity, transit, and curb utilization. This talk will discuss the methods used in the analysis and the results, as well as the outcomes following the presentation of these analyses to Toronto City Council.

Raphael Dumas did his undergrad at McGill in Civil Engineering before doing a double degree at MIT, completing a Master of City Planning and a Master of Science in Transportation in 2015. During his three years there he did his thesis research in the MIT Transit Lab for the MBTA, Boston’s Transit Authority. He merged Automated Fare Collection (AFC) data with Automatic Vehicle Location (AVL) and train tracking data to infer origins, destinations, and journeys. With this data he analyzed differences between commute travel times for different demographic areas, the subject of this talk. He is now Research Analyst with the Transportation Services Big Data Innovation Team at City of Toronto, where he has been collecting and centralizing emerging and existing transportation data sets to improve the user experience on the city’s streets and highways.

This seminar is presented by the University of Toronto Institute of Transportation Engineers (ITE) Student Chapter.

More by Raphael Dumas:

• How the City of Toronto Used Shared Streets’ PUDO Data to Examine Curbside Impacts by Raphael Dumas, medium.com, September 10, 2019
• Previous UT-ITE seminar, “New Methods of Analyzing Transportation Equity with Big Data” October 20, 2018.