Transport for London (TfL) and Yunex Traffic Limited have transferred the transport authority’s ‘ageing’ traffic signal system to the cloud-based Real Time Optimiser (RTO) system.
Almost 4,000 junctions, 1,500 pedestrian crossings, and more than 16,000 traffic detectors across Greater London were migrated to a new system without any impact on London’s road network over a two-week period, TfL said.
It added that the ‘world-leading’ upgrade enables improved journey times, traffic flows and responses to incidents, as well as improved data on journey demand and road network patterns, which will help inform its work to optimise the road network.
Carl Eddleston, TfL’s director of network management and resilience, said: ‘This world-leading new traffic management system will be a game-changer for us in London.
‘It will use new data sources to better manage our road network, tackle congestion, reduce delay for people choosing healthier travel options and improve air quality.'
Wilke Reints, managing director of Yunex Traffic in the UK, said: ‘We worked closely with TfL to develop this innovative solution for transport authorities both in the UK and internationally.
‘Building on the UK’s track record of developing modern traffic management and control solutions, RTO provides a robust, reliable system that will meet the needs of the world’s largest cities, helping improve air quality, reduce congestion and make sustainable travel more appealing and accessible to everyone.’
TfL manages around 6,400 automated traffic signal junctions and pedestrian crossings, one of Europe’s largest traffic signal networks.
It said transferring to the RTO will allow it to mitigate against the challenges of the capital’s complex, older road layout, providing resilience and future-proofing its road network management.
The RTO also provides TfL with the platform to support the introduction of FUSION, a new intelligent adaptive control optimiser, which can replace the existing SCOOT system that has been operating across London for more than 30 years.
