Artificial intelligence to be used to detect road defects in NSW

road defects

Artificial intelligence will be used to detect road defect issues and safety risks in New South Wales.

The Asset AI project, a Transport for NSW-led project in partnership with the Institute of Public Works Engineering Australasia (IPWEA), will use dash-mounted cameras on council vehicles and sensors to detect, log and eventually predict critical road defect issues.

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Shoalhaven City and Warren Shire councils have recently joined the project, now feeding data into the platform and receiving updates through the system.

TfNSW executive director Matthew Wilson says the project is ambitious, with 3000 kilometres of state roads around Sydney, 85,000 metres of line marking and more than 800 bridges and 18 tunnels.

“It’s great to see our Transport teams as early adopters using this new technology and its potential to enhance our current quality inspection capabilities, and help shift contracted road maintenance programs towards preventative, and ideally predictive maintenance,” he says.

The project seeks out damaged signs, faded line markings, potholes and rutting, and ranks them based on severity and safety risk, to council asset maintenance teams.

Shoalhaven mayor Amanda Findley says gathering data on our road network infrastructure is beneficial for planning and allocating budgets in the long-term.

“The installation of AI cameras on road worker crew vehicles will be a welcome addition to the fleet and effectively act as another set of eyes inspecting our roads,” she says.

“We are hopeful that the application of this new technology will create efficiencies in the process to remediate our roads and potentially reduce costs by cutting back on the manual inspection and assessment process.”

Councils can see the location of each issue detected by Asset AI, pull up images and severity ratings for defects, and receive an overall rating of the condition of the road network.

The IPWEA NSW and ACT risk-based defect priority scoring system will be used on the platform to help maintenance crews address the most critical defects first, reducing the overall risk to road users and the community.

Griffith city council director Phil King says the Asset AI platform will allow Griffith staff to get a broader picture across the entire local government area, particularly over rural roads.

“The council’s continuous monitoring of the data collected provides feedback to the AI model and this will improve the ability to identify what is happening to the road assets over time,” he says.

Another 48 local councils across NSW have also expressed interest in joining the project.

Asset AI received a $2.9 million funding co-contribution through the NSW Government’s Smart Places Acceleration Program, a special reservation under the Digital Restart Fund.

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