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  • Writer's pictureSafer Highways

Patent granted for University collaboration on urban traffic management using AI

A patent has been granted for a new traffic management system created in collaboration with University of Huddersfield artificial intelligence experts.


Professor of Artificial Intelligence Mauro Vallati and the AI4UTMC research team, including Dr Rongge Guo, Saumya Bhatnagar, and Dr Francesco Percassi, have been working with Simplifai Systems on the use of artificial intelligence to help reduce congestion and air pollution.


The system they have created together has already been successfully trialled on one busy route in Huddersfield, but the patent approval is key to progressing their innovation further.


Simplifai, based at the University’s 3M Buckley Innovation Centre alongside the campus, was created through a collaboration between the University of Huddersfield’s research centre which encompasses AI, now known as the Centre for Autonomous and Intelligent Systems.


The collaboration has already begun transforming traffic flow on roads through a new form of smart urban traffic management using artificial intelligence.


Professor Vallati explained that the system they have created builds on the traffic authority’s existing data and can allow simulations to take place ahead of a big local event, for example.


He said: “What we are doing is designing AI solutions for dealing with traffic issues, optimising traffic signals in order to reduce congestion and pollution.


“This will improve the quality of life for people living in urban areas, as well as reducing journey times for people travelling to work in the morning and coming back home in the evening.


“For example, an operator can set the objective to move traffic through the corridor as fast as possible within speed limits, to avoid congestion. The system then creates traffic signal strategies, telling each junction how long each signal should be on green in order to maximise movements.”


The AI technology is able to access existing information on congestion, traffic lights, bus movements, incidents and air quality to generate real-time strategies to solve traffic control issues.

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