Nottingham City Council have partnered with transport technology company VitaCity to install sensors aiming to transform the city into a smarter, more efficient place to live.
Across Nottingham, 219 sensors are being installed with a mix of Automatic Number Plate Recognition, traffic monitoring and Smart Signal Control system capabilities.
Nottingham City Council’s Portfolio Holder for Highways, Transport and Parks, Councillor Audra Wynter, said: “Our city needs the best, latest technology to help us in our fight to become carbon neutral by 2028.
“Our city needs the best.”
Councillor Audra Wynter
“To help us to monitor traffic flow and analyse the behaviours of road users in the area, we’re looking forward to working with VivaCity to help make accurate decisions on future schemes and to reduce pollution in the heart of our city.”
These sensors use their Artificial Intelligence (AI) to gather detailed yet anonymous data on transport modes, traffic flow and travel times, supporting strategic decisions to help enhance the transport network and improve urban infrastructure.
This is also in a plan to understand how transport mode volumes affect pollution levels which will be installed in February and be finalised in November 2023.
Nottingham resident Eleanor Jarvis, 21, said: “I feel confident in myself and my ability to navigate the city by car, however I regularly find the biggest risk being other drivers around me.
“The city is always busy, especially when it comes to the main city centre areas and at rush hours, however aside from the occasional full-speed racer type drivers zipping past, I find driving in Nottingham quite easy.”
Overall the sensors will help make the traffic lights more reactive to current traffic levels and help reduce waiting times and if it’s successful the smart junctions could be installed in other areas of the city.
With Artificial Intelligence technology being developed further new functions will be introduced to the system such as identifying specific vehicles like taxis and mobility scooters.
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