AI-Powered Bin Lorries Could Revolutionise Pothole Detection, MP Tells Parliament

Artificial intelligence mounted on refuse collection vehicles could transform the way councils identify and repair potholes, after a proposal in Parliament called for the technology to be rolled out across England's local road network.

Using bin lorries as mobile road inspectors could provide local authorities with a constant stream of real-time highway condition data, enabling defects to be identified long before they become costly repairs or safety hazards.

The proposal was put forward by Dr Ellie Chowns, MP for North Herefordshire, who urged ministers to investigate fitting refuse collection vehicles with AI-enabled camera systems capable of automatically detecting, recording and mapping potholes and other carriageway defects.

Speaking during a Parliamentary debate, Dr Chowns argued that refuse collection vehicles already visit virtually every residential street on a regular basis, making them an ideal platform for continuous road condition monitoring without the need for dedicated inspection vehicles.

She highlighted similar technology already being deployed overseas, including successful trials in Australia, where artificial intelligence is being used to automate highway inspections and improve the speed at which defects are identified.

Dr Chowns called on the Department for Transport to work alongside the Ministry of Housing, Communities and Local Government to assess whether comparable technology could be adopted more widely across England.

Turning Everyday Vehicles into Mobile Survey Platforms

The proposal reflects a wider shift towards data-driven highway asset management, where AI, machine learning and digital mapping are increasingly being used to supplement traditional visual inspections.

Rather than relying solely on scheduled highway surveys or reports from members of the public, AI-equipped refuse vehicles could automatically capture thousands of images every week, identifying defects as they develop and transmitting precise locations directly into local authority asset management systems.

This continuous flow of condition data would allow engineers to intervene earlier, helping prevent minor defects from developing into larger potholes while enabling maintenance budgets to be targeted more effectively.

With councils facing growing pressure to maintain ageing highway networks against constrained funding, the technology could offer a more efficient and cost-effective approach to network inspection.

Government Backs Highway Innovation

Responding to the proposal, the Transport Minister said the Government is already investing in emerging technologies through its £30 million Live Labs 2 programme, which is supporting local authorities in trialling innovative approaches to highway maintenance and pothole management.

The minister added that ensuring councils have access to high-quality data and modern digital tools—including AI-enabled monitoring technologies—forms part of the Government's wider ambition to improve the efficiency and effectiveness of local road maintenance.

The Future of Highway Asset Management

Artificial intelligence is already beginning to reshape infrastructure management across the UK, with highway authorities increasingly exploring automated condition surveys, digital twins, predictive maintenance and computer vision systems to improve decision-making.

If adopted at scale, AI-enabled refuse collection fleets could significantly increase the frequency of road inspections while reducing operational costs, providing local authorities with near-continuous intelligence on the condition of their networks.

As councils continue to search for smarter ways to maintain roads with limited resources, turning everyday municipal vehicles into mobile data collection platforms may prove to be one of the most practical applications of AI in highway asset management to date.