Michael Ganser is an engineer with Kapsch TrafficCom, an Austrian company that provides intelligent transportation systems. “Building new roads or adding new lanes is not sustainable,” he says. Ganser believes the solution to gridlock lies in a combination of smart traffic lights, connected vehicles and congestion charges — all informed by AI.
In cities including Madrid and Mumbai, Kapsch TrafficCom has implemented a system where roadside sensors, traffic cameras and vehicles collect data on things like road works, accidents and congestion.
The information is fed into a central system and a prediction model creates a comprehensive view of traffic conditions in real-time. The system is then able to adjust the timing of traffic light signals, so that they improve the flow of vehicles.
In addition, motorists are sent information via an app telling them which routes to take to avoid congestion, as well as the optimum speed they should drive.
Kapsch has also worked with cities such as Singapore to implement a variable congestion charge that makes it cheaper to travel outside peak times, which encourages drivers to avoid rush hour.
Ganser says combining smart lights, connected vehicles, and congestion charges “leads to a traffic system that, under good conditions, allows almost jam-free roads.” He estimates that combination could reduce congestion by around 75%, saving large cities billions of dollars every year.
The Argentine capital of Buenos Aires is one of the most populous cities in Latin America. It has over 3 million residents, and an additional 3 million commuters from adjacent towns travel there every day. To manage its roads the city implemented a number of intelligent traffic devices, but it needed a way to coordinate the different technologies.
Buenos Aires officials worked with Kapsch TrafficCom to integrate the city’s existing traffic management systems.
Having the disparate traffic data going into a single network means information can be exchanged more effectively and provide commuters with real-time advice, according to Alan Balfour, director of the city’s Special Projects Unit for Mobility Infrastructure.
“The ability we have today to manage transit through this tool allows us to control traffic flow and support tomorrow’s sustainable mobility with quality planning,” says Balfour.
Time and money
Damon Wischik researches traffic flow optimization using AI at Cambridge University. He’s developing software to control traffic signals in UK cities. He equates “queues of cars at traffic lights as blocks in Tetris,” which can be re-routed using AI. “If you treat cities like a computer game, it can learn to clear congestion,” Wischick says.
But he thinks technology alone isn’t the solution. Wischik believes drivers need to be prepared to change their habits and to travel outside peak traffic times.
“It all comes down to — can you change people’s behavior, and can you make people willing to accept some slight change in behavior if it’s imposed on them?” he says.
When it comes to tomorrow’s mobility, Ganser believes digital technologies are the solution. “They are inexpensive and easy to scale,” he says. “So if society wants a quick win that brings down carbon emissions and gets rid of congestion, this is the way to go.”