Siemens Mobility and Transport for London announce launch of ‘the new SCOOT’


Siemens Mobility Limited and Transport for London (TfL) have announced the launch of Sitraffic Fusion – an all-new adaptive traffic control solution that will be able to optimise traffic flows more intelligently, using connected vehicle data to identify pedestrians, cyclists and public transport vehicles, as well as cars.

Fusion is a key part of London’s Real Time Optimiser (RTO) system, which will provide a completely new way of managing roads across the city, revolutionising the system that has been keeping London moving for over 30 years.

Until now, traffic lights across the capital have been managed using information gathered from inductive loops, which are buried in the road and detect vehicles approaching, a system that was part of SCOOT (split cycle offset optimisation technique). While SCOOT will continue to operate for the time being across most of the capital, Fusion will soon be tested, live, in specific areas.

The new Fusion system uses richer data sources from a variety of transport modes, including data from connected vehicles and buses. With flexible, policy-driven adaption techniques, Fusion improves on the SCOOT philosophy of minimising vehicle delay and stops, by optimising signalised junctions and pedestrian crossings based on all road users’ needs.

Developed by Siemens Mobility in collaboration with TfL and supported by the University of Southampton, Fusion enables all modes of transport to be modelled and optimised in a way that responds to the challenges that cities such as London face, such as cleaning up toxic air, making walking and cycling easier and safer and delivering a reliable and sustainable public transport system.

Fusion is set to enter operation over the coming weeks, where it will control a number of ‘living laboratory’ trial sites in London. This will allow Siemens Mobility to test increasingly complex functionality and verify its enhanced performance at existing traffic intersections in a live environment.

“We’re working to overhaul the way we manage London’s road network as we tackle some of the biggest issues London faces, such as poor air quality and congestion, ensuring that the capital has a green, healthy and sustainable future,” says Glynn Barton, TfL’s director of network management. “This ground-breaking new adaptive control system, part of our Surface Intelligent Transport Systems programme, has the potential to make our road network more efficient and responsive to people’s needs and movement. We’re very much looking forward to seeing the results of our first trial sites.”

Wilke Reints, MD, Siemens Mobility ITS, UK

“This trial marks a major milestone in the development of this ground-breaking traffic management solution, and I know its progress will be followed closely by industry colleagues around the world,” says Wilke Reints, MD of Siemens Mobility’s Intelligent Traffic Systems business in the UK. “Whilst London is using our hosted UTC solution for the first time to provide Fusion with connectivity to the street, the system is designed to work with a range of UTC systems. Although this is just the first manifestation of the new system, we are enormously excited by its potential and the degree of control that it will give transport authorities.

“London is a high-profile showcase for this intelligent traffic solution, with Fusion a great example of how our digital solutions are enabling authorities to make their networks and infrastructure intelligent. Ultimately this will deliver an enhanced experience for road users.”

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About Author


Tom has edited Traffic Technology International (TTi) magazine and its Traffic Technology Today website since May 2014. During his time at the title, he has interviewed some of the top transportation chiefs at public agencies around the world as well as CEOs of leading multinationals and ground-breaking start-ups. Tom's earlier career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).