ROAD SAFETY: AI POWERED PREDICTION AND PREVENTION

Road Safety: AI Powered Prediction and Prevention.

Our fourth AI Mini-Guide, sponsored by TRL, focuses on how AI can help reduce road risk and improve safety outcomes for all road users. It offers a realistic assessment of the technology, verified case studies with documented outcomes, and a breakdown of its benefits, challenges, and practical applications.

Critically, the guide distinguishes between what AI can reliably deliver today versus what remains aspirational.

What’s Inside the Guide

• What is Actually Working – UK Case Studies – Real-world examples demonstrating how AI is already improving road safety.
• AI for Worker Safety – How AI tools designed to protect road users are also being deployed to protect the people who maintain and operate the network.
  Opportunities and Benefits – Improving road safety, helping local authorities understand risk earlier, direct resources more effectively and deliver better outcomes for all road users.
• Barriers and Challenges – Practical considerations, challenges, and limitations to be aware of when adopting AI.
• Evaluating AI Supplier Claims – Key areas to seek clarity on when evaluating AI proposals.

It also features a detailed case study of TRL’s IMAAP – AI-enhanced collision analysis and reporting software. The cloud-based platform provides storage and analysis of STATS19 collision data, enabling road safety professionals to identify problems, establish measurable goals, plan intervention programmes and evaluate effectiveness.