We present an innovative approach to traffic incident modelling through the integration of large language models (LLMs) with established machine learning techniques. This method enhances the classification accuracy of traffic incident severity, leveraging the nuanced understanding of unstructured text provided by language models.

This topic focuses on how ai can assist in the betterment of key community assets, leading to positive safety outcomes. We will present real life instances from around the globe of how this technology is enabling efficiency and optimum safety outcomes for citizens including monitoring of roads to provide support for automated detection of road conditions to help direct maintenance services more effectively, detecting vehicles parking or driving in bus and bike lanes illegally.

Connected transport merges digital tech for safer, efficient, and sustainable systems. It includes Connected Vehicles, ITS, and data analytics for informed planning. Integration offers unified management. Cybersecurity is vital amid increasing connectivity. Overall, it revolutionizes transportation, promising safer, more accessible mobility with ongoing technological advancements.