Artificial intelligence project launched by Transport for NSW

Two additional regional New South Wales councils and a Sydney-based team from Transport for NSW have joined what is being called an innovative artificial intelligence project.

The Asset AI project seeks to revolutionise road asset maintenance and operations by using a combination of dash-mounted cameras on council vehicles and sensors to detect, log – and eventually predict – critical road defect issues.

These likely include damaged signs, faded line markings, potholes and rutting.

Repairs will be escalated based on severity and safety risk to council asset maintenance teams.

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

The Transport for NSW asset inspection team that carries out quality assurance monitoring of state roads across Sydney will also trial three vehicles fitted with dash-mounted cameras.

Asset AI is a Transport for NSW-led project, in partnership with the Institute of Public Works Engineering Australasia (IPWEA) NSW and ACT Division and City of Canterbury Bankstown.

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

Canterbury-Bankstown and Griffith councils were the first councils to trial the Australian-first technology with data from Asset AI cameras on vehicles including street sweepers and utes feeding near-real time road condition updates into the platform.

The application allows councils to easily 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.

Councils ready to be onboarded in 2024 include Liverpool Plains Shire and Mid Coast. Another 48 local councils across NSW have also expressed an 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.

“Asset AI is an exciting and ambitious project, and we are now for the first time trailing its use for quality assurance monitoring of our state roads around Sydney,” said Transport for NSW Executive Director of Road Maintenance and Motorway Partnerships, Matthew Wilson.

“There are nearly 3000 kilometres of state roads around Sydney with 85,000 metres of line markings, 5,000 metres of median strips 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.”

Shoalhaven City Council Mayor, Amanda Findley was hopeful that the application of the new technology would create efficiencies in the process to remediate roads and potentially reduce costs by cutting back on the manual inspection and assessment process.

“Right now, gathering data on our assets such as the critical road network infrastructure is vital to planning and allocating budgets in the long term,” she said.

“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.”

The project has garnered support from Warren Shire Council Divisional Manager Engineering Services, Sylvester Otieno.

“Asset AI provides a fantastic platform to monitor the condition of our vast road network,” he said.

“As a small rural and remote council with severe challenges in attracting qualified staff, the platform would lessen the effort required in road inspection, thus enabling our staff to be deployed elsewhere.”

Early results of the trial have shown that Asset AI can successfully detect many different types of defects within Council’s roads including potholes, pavement cracking, faded line marking, damaged signs and even graffiti, according to City of Canterbury Bankstown Systems Coordinator Waste, Troy Leedham.

“It’s helping us identify faults in the road before they become a bigger issue. Getting onto issues proactively and improving our ability to fix them,” he said.

Griffith City Council Director Infrastructure and Operations Phil King said the new platform allowed Griffith staff to get a much broader picture across its entire LGA.

“Particularly over the rural roads, to show where the defects are, and we hope to improve our response time to address these defects,” he said.

“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.”

The IPWEA NSW and ACT risk-based defect priority scoring system reportedly allows for easy comparison of all defects across the road network.

“We are excited to work with additional NSW councils over the next 12 months before the platform is made available to further councils in mid-2025,” said Joshua Devitt, IPWEA NSW and ACT Chief Engineer.

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