Transport for Greater Manchester has teamed up with Google to use AI to improve traffic flow and reduce stop-and-go emissions.
With responsibility to install, maintain and manage traffic signals on behalf of Greater Manchester’s 10 councils, TfGM oversees a signal network that includes 2,500 sets of traffic signals.
The Green Light project brought together Googles experience in AI, and their wealth of data with TfGM’s knowledge of Urban Traffic Control, the local road network and signal assets.
During the project Google reviewed traffic movements and provided recommendations where there was potential to for signal timing changes to provide an overall reduction in stop-and-go traffic.
In many instances signals are being used to provide priority to buses, pedestrians or encourage route choice (reduce rat running), so recommendations did not always lead to a change in signal timings. Where they were, traffic conditions were monitored and recommended changes at one junction led to an average improvement of 9% during the morning peak period and 18% during the afternoon peak period.
You can read a blog about it from Yossi Matias, Google VP Engineering & Research, here.
David Atkin, TfGM’s analysis and reporting manager (pictured), said: “Greater Manchester’s road network – which includes 2,400 traffic signals and millions of journeys every week – is complex and managing it a challenge when balancing the needs of motorists, cyclists, pedestrians and public transport users.
“With traffic levels now at or beyond pre-pandemic levels, we are working really hard to tackle congestion and are delighted to be amongst the first areas in the World – and the first in the UK – to work with Google on the innovative Green Light initiative.
“Our aim is to make the network run as efficiently and sustainably as possible and the pilot provided valuable insights, with teams from both Green Light and TfGM bringing expertise and ideas to the table to reduce stop-and-go traffic and emissions.”
(Picture – TfGM)