Artificial intelligence (AI) will give an insight into the condition of Britain’s local road markings in a £2m project announced by the Department for Transport (DfT).
In a study conducted by Gaist, a small business based in North Yorkshire, machine learning AI technology will be used to review over 146 million high definition (HD) images of roads.
The national assessment will analyse nearly 100,000 miles of road, providing a clearer-than-ever picture of where investment is needed. The department will then be able to advise local councils on where they could invest in areas that may need it most, improving road user safety.
Poor road markings pose an issue for all road users, from cyclists to motorists, the DfT explained. If road markings aren’t clear it can make it hard for road users to understand how wide a lane is, or whether they can overtake or park on the side of the road.
“Road markings play a vital role in keeping everyone who is using the road safe, so making sure they’re up to standard is imperative,” said Transport Secretary Chris Grayling.
“This funding will allow for advanced AI learning technology to assess the condition of the markings to improve the safety of our roads for all users.”
Clear road markings will also be essential for the rollout of connected and autonomous vehicles (CAVs) in the UK.
As part of the new project, the DfT is also planning to assess sections of the National Cycle Network, building on an audit undertaken by cycling and walking charity Sustrans, to better understand the condition of the network.
And it will conduct a survey of councils about pavement and footway conditions to help outline where funding could be targeted.
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Tags: AI, Artificial Intelligence, autonomous vehicles, connected vehicles, CAVs
