The city of Toronto is using its traffic data in a new way. The city was already using public transit data to help riders move around the city, and now all residents will get a leg up with the creation of a big data team for transportation services. That team will be using transportation data analytics to improve transportation of all modes throughout the city.
The initiative comes on the heels of a recent traffic report that cited Toronto as one of the most congested cities in Canada. According to the report from TomTom, in Toronto, Vancouver and Montreal, the average commuter loses 84 hours a year being delayed in traffic while the average time lost to traffic across the country is almost 79 hours.
Some of the required analysis is already underway in the Transportation Services department. The big data team plans to take things a step further by partnering with McMaster University to analyze historical travel data, and working with individual units within Transportation Services like the Cycling Unit to evaluate travel patterns.
The group will also vet products and services that might be useful in assisting the city’s initiative. Toronto recently posted a Request for Information (RFI) for vendors that have proven products for monitoring and measuring travel and traffic in the urban environments. Interested vendors will take part in an event on April 14 and 15 to showcase their technology for city officials.
Toronto is currently seeking a team lead for this unit who understands both transportation and big data.
“The availability of travel data has improved dramatically over the past few years and is at a point where the city can – and should – be using it to better understand travel patterns, evaluate the city’s investments and monitor performance. With this information, we can get Toronto moving smarter,” said Mayor John Tory. “This will be a game changer and will establish Toronto as a leader in running a truly smart city.”