Artificial intelligence and machine learning will be used to improve road markings across the UK, the Department for Transport (DfT) has announced.
As part of a wider 350 million fund to improve the quality of local roads, the department will use 2 million in partnership with an AI startup and a road safety group to advise councils on where best to utilise investment.
DfT will work with the Local Condition Roads Innovation Group (LCRIG), which in turn will use the North Yorkshire-based AI startup Gaist to review almost 150 million high definition images of the UK's roads. With machine learning software, these images will be analysed to provide local councils with an assessment of where road markings could be improved or even added.
"We are using over 146 million HD road images from our national databank and cutting-edge AI technology to assess over 96,000 miles of classified roads as part of this project," said Paula Claytonsmith, managing director at Gaist.
"This is the largest exercise in assessing road marking readiness ever undertaken in England. Gaist is proud to have the AI capability that puts an SMB UK business at the forefront of technological advances."
Worn out and poor road markings can make it difficult for road users to distinguish whether it's safe to overtake, or where they can park, or even determining how wide a lane is. This is a big safety risk, according to the DfT, which said these issues can be rectified by having a stronger road map of where markings need improvement.
Together with this announcement, the DfT will welcome bids for the 348 million investment to improve local roads. The money will be split into two areas, first, 200 million will be available over the next two years for work to strengthening and repair road damage, such as potholes. The remaining 150 million will go to projects designed to tackle traffic "pinch points". These are elements of road design which narrows carriageways to slow and calm traffic near areas with lots of pedestrians.
Last year, road traffic injuries were the leading cause of death among children aged 4 and 14 and young adults aged between 15 and 29, according to the World Health Organisation. There are a number of companies looking to solve this issue with AI-based technology, such as Predina, a firm selected in the Google for Startups incubator, which maps out real-time hotspots to predict areas most at risk of collisions.
