Yang, GarySarkar, AbhijitRidgeway, ChristieThapa, SurendrabikramJain, SandeshMiller, Andrew M.2024-11-192024-11-192024-11-18https://hdl.handle.net/10919/123634Artificial intelligence (AI) and machine learning technologies have the potential to enhance road safety by monitoring driver behavior and analyzing road scene and safety-critical events (SCEs). This study combined a detailed literature review on the application of AI to driver monitoring systems (DMS) and road scene perception, a market scan of commercially available AI tools for transportation safety, and an experiment to study the capability of large vision language models (LVLMs) to describe road scenes. Finally, the report provides recommendations, focusing on integrating advanced AI methods, data sharing, and collaboration between industry and academia. The report emphasizes the importance of ethical considerations and the potential of AI to significantly enhance road safety through innovative applications and continuous advancements. Future research directions include improving the robustness of AI models, addressing ethical and privacy concerns, and fostering industry-academic collaborations to advance AI applications in road safety.application/pdfenCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalartificial intelligenceAItransportation safetydriver monitoring systemTechnical report