Artificial Intelligence in Proactive Road Infrastructure Safety Management
Summary and Conclusions
This report examines and determines the most relevant cases for artificial intelligence (AI) use in a transport planning context for crash prevention on an entire road network. It explores the possibility of using computer vision to acquire relevant information and the capability of computer models to map high-risk locations. It offers recommendations to stakeholders on the development and appropriate use of life-saving AI solutions.
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- Develop a competitive market for the sharing and monetising of traffic and mobility data.
- Do not wait for real-time data before developing risk maps.
- Mandate the sharing of aggregate vehicle data.
- Learn from other fields and best practice for data sharing and privacy protection.
- Support research and innovation towards trusted and explainable AI.
- Align new tools with precise policy objectives.
- Develop new skills and digital infrastructure.
- Clarify regulatory frameworks for data protection and digital security.
- Design user-friendly risk-mapping tools.