Transport for London (TfL) is expanding its use of traffic sensors using AI to detect road users and decide which mode of transport they are using. Using sensors from Vivacity Labs, the trials that began in 2018 have proven to be up to 98 percent more accurate than manual methods and are able to gather data 24 hours a day for a much more detailed picture of how the roads are being used. All video captured by the sensors is processed and discarded within seconds, meaning that no personal data is ever stored. The data gathered will help assess demand for new cycle routes and support TfL in planning how it operates the road network for all users.
Glynn Barton, TfL’s director of network management said, “We work around the clock to keep people in London moving and we’re always looking for innovative new ways of making our roads safer and more efficient. New data from trials such as this will be really valuable as we invest and make day-to-day decisions to enable more people to walk and cycle.”
The sensors are part of a modernization program of TfL’s current road network systems and have the potential to link up to London’s traffic signals and control center systems to provide data in real-time, which could enable TfL to better balance demand and improve how it manages congestion. The sensors are also able to detect people walking and other types of traffic, including cars, trucks, motorcyclists, and buses.
London’s Mayor Sadiq Khan’s Transport Strategy target is for 80% of trips in London to be made by walking, cycling, and public transport by 2041.
London’s Walking and Cycling Commissioner, Will Norman said, “By getting more people cycling and walking, we can help to tackle congestion and pollution in London and improve our health. Our Healthy Streets approach is based on evidence and data and we welcome new technology that supports this.”