Transport for London is turning to data science in an effort to tackle the capital’s gridlocked road network, as part of plans to predict what impact roadworks, congestion and other unplanned events will have on the streets of London.
In the summer, TfL awarded a contract worth up to £6.5m to develop a "world leading" traffic control centre software, dubbed the Surface Intelligent Transport System (SITS).
Sopra Steria, a leading information technology company, won the contract to develop the control centre system providing a "single, unified view of everything happening on the network, including up-to-the minute details of all known incidents and the actions being taken".
Now, the organisation is seeking input from companies about how to add a predictive analytics capability to the SITS scheme through a questionnaire, which is open for responses until October 28 2019.
Tfl wants the enhanced system to accurately forecast the state of the road network after an incident and generate suggested response strategies, while modelling these strategies on the road network to create an effectiveness-based ranking.
It is thought to be the first time artificial intelligence will be used to manage London’s road network. Data would also play a key role in the SITS upgrade, which would draw on a wide range of historic and real-time datasets to predict reactions to incidents on the roads.
To put this in perspective, there are more than 9,000 miles of roads in London, and more than 7,000 of those miles are on ‘minor urban’ roads. Location-based data and analytics company INRIX ranked London as the 5th most congested city in the world.
TfL director of network management Glynn Barton said: “We’re working to completely transform how we manage London’s road network to cope with the challenges we all face as a city, from road danger to congestion and toxic air.
“Using data and intelligent systems to help us shape our response to incidents will be a fundamental part of this new approach."