This series highlights practical, effective road safety initiatives from ESRC members. Each month, we showcase a project that others can learn from, adapt and build on.
Our July spotlight features the ‘Improved Road Safety with AI Inspections Initiative’ developed by ‘Faxe Kommune’ in Denmark to improve the condition, monitoring and maintenance of road infrastructure while enhancing safety for all road users and significantly improving the working conditions of road inspectors through the introduction of AI-based road inspections.
Inspiration behind the initiative
Well-maintained road infrastructure is fundamental to road safety. Across the road network, road inspectors are increasingly exposed to safety risks as routine inspections require them to spend time physically in the roadway. Additionally, deteriorating road infrastructure, including potholes, faded road markings, damaged bollards and uneven pavements, poses growing risks for drivers, cyclists and pedestrians. When infrastructure defects are not detected and repaired in time, they can contribute to crashes, loss of control, and trips or falls. Together, these challenges highlighted the need for a safer, more systematic and data-driven approach to monitoring road infrastructure conditions and prioritising maintenance.
Project activities
2022 – Present – Partnership development and solution co-creation:
Developed with Pluto Technologies, the initiative uses AI‑based inspection equipment shaped by continuous operational feedback from the teams. This co‑creation process ensured the system met local infrastructure standards and supported smooth alignment with public‑sector partners.
2022 – Present – Implementation of AI-based road inspections:
AI‑enabled inspections were rolled out across the municipal road network, replacing manual methods. Previously, staff had to divide attention while driving or stop in live traffic to document defects, increasing their exposure to risk. The new digital system cuts time spent in traffic and delivers a detailed inventory of more than 60 types of road defects and conditions, including carriageway damage, cycle‑lane hazards, faded signage, damaged bollards and pedestrian‑related issues.
2022 – Present – Data-driven prioritisation and preventive maintenance:
The AI system provides a structured, up‑to‑date overview of road safety hazards and infrastructure conditions across the network. Defects can be filtered and prioritised by urgency, traffic volume and risk, allowing maintenance teams to focus on the most critical sections. This supports faster repairs, more proactive preventive maintenance and stronger long‑term management of road assets, benefiting all road users.
2026 – Dissemination and knowledge sharing:
The project was presented at a national meeting of municipal directors in Denmark, where it was well received. By sharing practical experiences and lessons learned on AI‑supported infrastructure monitoring, the initiative is helping broaden knowledge across the sector and supporting other local authorities considering similar approaches to road infrastructure management.
Outcomes
- Working conditions for road inspectors have improved, with staff now spending around 50% less time on inspections, and they report a safer work environment due to reduced exposure to live traffic during infrastructure assessments.
- AI-based inspections have replaced incomplete pen-and-paper records with a consistent, digital data set that provides a clear overview of road infrastructure conditions, enabling reliable and user-friendly data collection across teams.
- Over the past 12 months, AI inspections identified 1,569 potholes across the road network, including 24 on bicycle lanes and 166 on roads with the highest speed limits. This allowed urgent infrastructure defects to be addressed quickly and maintenance resources to be allocated where safety risks were highest.
- The availability of comprehensive and historical infrastructure data has strengthened maintenance planning, supported objective decision-making and improved discussions around long-term investment in road infrastructure.
Challenges
- Introducing a new AI-based inspection approach required time and attention to ensure staff became confident using the system and integrating it into daily operations.
- There was an initial risk that the technology could be perceived as complex or disruptive to established working practices.
Why this initiative has been recognised as Good Practice of the Month
This initiative shows how practical innovation can strengthen road infrastructure safety by transforming how defects are identified, prioritised and addressed. By introducing AI‑based inspections, it reduces reliance on manual data collection in live traffic and enables faster, targeted repairs, directly improving the safety and resilience of the road network.
Its strength lies in the combination of hands‑on innovation, smooth integration into daily operations and clear safety outcomes. The initiative provides transparent, high‑quality data that supports better planning, objective decision‑making and more efficient use of limited resources. Its positive reception among staff and successful sharing with other road authorities demonstrate its transferability as a scalable model for improving road infrastructure safety.
For more information
Read more about the project and explore its activities and outcomes here .
Interested in developing a similar national strategy?
Contact the project lead, Jorgen Veisig: jvei@faxekommune.dk
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