GRIDLOCK UNLOCKED
How big data can help city planners ease traffic congestion
It’s a safe bet that if you get Torontonians together, someone is going to complain about the traffic. It comes as no surprise to commuters that Toronto was recently listed as one of the most congested cities in North America: the average driver spends almost 99 hours a year stuck in traffic. Toronto City Councillor Denzil Minnan-Wong warned in a 2014 report that if traffic congestion went unaddressed, the cost to the local economy could rise to more than $15 billion annually in lost productivity by 2031.
One of the potential solutions to the growing gridlock problem — and to many other challenges in large, metropolitan areas — is “big data.” Staggering amounts of data are created every second, thanks to the information generated by the billions of smartphones and connected devices interfacing with mobile networks around the globe. Big data can illuminate patterns and trends, and several big cities, including Toronto, are looking for ways to harness these masses of information to improve everything from traffic and transportation networks to emergency services and utilities.
Jesse Coleman is the Big Data Innovation team lead for the City of Toronto. His group is building up the city’s analytical capability so they can leverage new and emerging forms of transportation data. Toronto Mayor John Tory created the team last year to deal with the congestion issue. “Vehicles can be thought of as moving sensors,” Coleman explains. “Most are carrying GPS-enabled smartphones or have GPS navigation technology, and most large fleets — buses, taxis, delivery vehicles, etc. — are all being tracked.” His team’s goal is to wrangle all that information to understand how traffic is moving through the city and find ways to make it easier for people to get where they need to go.
Transportation engineers and planners have always relied heavily on data to determine how people move around. Much of that data was gathered through market research and surveys. Pictures were collected; vehicles, bicycles and people were counted by hand. But collecting data that way can be expensive, and it only captures a small percentage of travellers. “This gets that type of data collection to a whole new level,” says Coleman.
The insights uncovered by Coleman and his team are already helping the city to manage its streets more effectively by enabling moreinformed decisions about parking regulations, traffic signals, and more. “We can now see specific places where congestion is negatively impacting streetcars or buses,” he says. “By looking at the data, we can prioritize and strategically address the biggest inconveniences to Torontonians.”
Toronto isn’t alone in harnessing the power of big data to ease traffic congestion. Anonymized information gathered from cellular towers is helping to plan smarter transportation networks around the world. In Wales, telecommunications company Vodafone partnered with the Welsh government to analyze mass-movement patterns throughout the country and identify the demands placed on the transit infrastructure. Over a period of three weeks, Vodafone analyzed more than six million journeys across highways in South Wales, providing invaluable insights that are now being used to inform the planning of new roads and public transportation systems.
As governments increasingly turn to datadriven decision making, new privacy standards are emerging to ensure that the benefits of big data can be realized while safeguarding citizens’ personal information. Data — such as movement patterns throughout a wireless network — can be stripped of any personal information before it’s analyzed. This process is referred to as “de-identification.” The de-identified information is then aggregated into massive bulk data sets using complex algorithmic models, which ensures that no data can be linked back to its source.
“We don’t use any information that could identify any individual. We take that seriously,” says Coleman. “Breaches would completely compromise everything we do, so we always incorporate privacy as the first priority.”
According to Michael Cihra, vice president of Internet of Things at TELUS, while big data has big potential to benefit nearly every aspect of our lives, its greatest impact could be simply shortening our daily commute. “Just imagine how much more productive and less stressed we’d be if we spent less time stuck in traffic each day, not to mention the environmental benefits,” he says. “Transportation is a huge quality-of-life issue that Canadians would love to see prioritized by their governments.”
In a smart city, movement patterns can be used to optimize traffic-light sequences based on real-time traffic flow, sensors can make it simple to find and pay for parking using an app, and predicative analytics can be used to prevent bus, streetcar and subway breakdowns before they occur.
“As we harness the power of big data, we are going to see smarter cities with more effective infrastructure and more efficient public transportation,” says Cihra. “It’s going to have a tremendous impact on our lives.”