Managing asbestos across the UK’s Strategic Road Network (SRN) remains a significant responsibility for transport authorities. Much of the network infrastructure—bridges, tunnels, drainage systems, and roadside assets—was constructed before the 1999 asbestos ban, meaning Asbestos-Containing Materials (ACMs) still exist within many ageing structures. The Highways Agency introduced structured management frameworks such as the General Asbestos Management Plan (GAMP) to systematically monitor and control these legacy risks. Today, intelligent infrastructure platforms like AI-powered road infrastructure management systems are helping authorities strengthen inspection planning, improve safety oversight, and manage road assets more efficiently.
Effective asbestos management goes far beyond regulatory compliance—it plays a critical role in protecting people and infrastructure.
Structured asbestos planning safeguards:
• Highway maintenance teams
• Contractors and service providers
• The travelling public
• Long-term resilience of UK transport infrastructure
Under the Control of Asbestos Regulations (CAR) 2006, highway authorities must identify, record, and manage ACMs across all non-domestic premises, including bridges, tunnels, depots, culverts, electrical systems, and other SRN infrastructure assets.
Modern safety monitoring tools such as AI-powered road safety audit platforms help authorities improve visibility into infrastructure risks across large transport networks.
Without structured asbestos action planning, agencies risk accidental disturbance, emergency remediation costs, safety incidents, and costly infrastructure delays.
The UK’s asbestos management strategy relies on systematic planning frameworks that ensure consistent monitoring across thousands of infrastructure assets.
Service providers must inspect at least 5% of assigned assets annually as part of a rolling inspection programme designed to achieve full asset coverage by March 2025.
Infrastructure monitoring technologies such as AI-based pavement condition intelligence systems help improve inspection efficiency and maintenance planning.
Annual Asbestos Action Plans typically include infrastructure built before 2000, including:
• Road pavements and roadside furniture
• Electrical cabling and communication ducts
• Bridges, tunnels, and retaining walls
• Depots and operational facilities
Maintaining accurate inventories using AI-driven roadside asset inventory platforms helps agencies track infrastructure components across large transport corridors.
Three planning frameworks ensure coordinated asbestos management across the network:
• Area Asbestos Management Plans (AAMPs) – regional survey prioritisation
• Scheme Asbestos Management Plans (SAMPs) – major infrastructure projects
• Technology National Asbestos Management Plans (TNAMPs) – technology and communication assets
Survey priorities are determined using several risk indicators:
• Asset age
• Planned maintenance works
• Known ACM locations
• Historical inspection records
Survey outputs are stored within infrastructure databases such as SMIS, HAPMS, and TPMS.
The GAMP framework encourages collaboration between:
• Service providers
• Police and emergency services
• Utility companies
• Third-party infrastructure owners
This coordinated approach helps prevent accidental asbestos exposure during maintenance or construction activities.
All service providers must appoint trained Asbestos Action Plan Owners and ensure personnel complete training that complies with CAR Regulation 10.
Modern infrastructure management increasingly relies on data-driven technologies that provide real-time visibility across transport networks.
Platforms such as AI-powered road condition monitoring systems give engineers valuable insights into infrastructure performance.
RoadVision AI systems help monitor:
• Pavement deterioration
• Cracking and surface defects
• Early-stage potholes
• Drainage failures and surrounding infrastructure degradation
These insights allow agencies to align asbestos inspections with broader infrastructure maintenance cycles.
AI-powered survey tools reduce reliance on manual inspections while identifying:
• high-risk work zones
• traffic constraints
• environmental conditions affecting maintenance activities
This improves planning for both infrastructure repair and asbestos inspection operations.
Advanced analytics help engineers prioritise surveys based on:
• roads approaching rehabilitation cycles
• structures built before 2000
• high-traffic corridors
• locations with higher probability of ACM disturbance
Smart inspection technologies such as AI-based rapid road damage detection systems enable faster decision-making for infrastructure managers.
RoadVision AI solutions align with major infrastructure standards including:
• UK Highways operational frameworks
• Control of Asbestos Regulations (CAR 2006)
• international road asset management practices
Predictive analytics allow authorities to model:
• fFuture infrastructure maintenance costs
• Evolving asset risk profiles
• Deterioration trends
• Long-term budget planning
These insights help infrastructure planners adopt a “measure twice, cut once” approach to major maintenance projects.
Despite robust regulatory frameworks, several challenges still affect asbestos management across the Strategic Road Network.
Older infrastructure structures make predicting ACM locations more difficult.
Historical construction documentation may be incomplete or inconsistent.
Many inspections require working in confined spaces such as tunnels, culverts, or live traffic corridors.
Coordination is often required with telecommunications, power, water, and rail infrastructure operators.
Maintaining a workforce trained in asbestos risk management remains an ongoing challenge across large infrastructure networks.
The UK’s structured asbestos management strategy—built around GAMP and Annual Asbestos Action Plans—provides a strong framework for managing legacy infrastructure risks across the Strategic Road Network.
However, as infrastructure ages and road networks expand, traditional manual inspection approaches are no longer sufficient.
Advanced digital platforms combining AI-based infrastructure monitoring, predictive analytics, and automated asset intelligence allow transport authorities to:
• Detect infrastructure risks earlier
• Prioritize asbestos inspections more effectively
• Improve worker safety
• Strengthen regulatory compliance
• Reduce long-term infrastructure maintenance costs
By integrating structured asbestos planning with intelligent monitoring technologies, the UK can continue protecting its workforce, maintaining public safety, and ensuring the resilience of its national road infrastructure for decades to come.
The Autonomous Road Engineer
AI that is transforming road infrastructure, from reactive to predictive.
