AVR3 congratulates Mohammed Elhenawy and collaborators Shadi Jaradat, Huthaifa I. Ashqar, Alexander Paz, and Richi Nayak on their paper being selected as Runner-Up for the 2025 Best Paper Award by the Open Journal of the IEEE Computer Society.

The award-winning paper, “Leveraging Deep Learning and Multimodal Large Language Models for Near-Miss Detection Using Crowdsourced Videos,” demonstrates how artificial intelligence can transform everyday dashcam footage into valuable road safety insights. By identifying and analysing near-miss events, the research has the potential to support more proactive approaches to road safety and help prevent future crashes.

This achievement highlights the strength of interdisciplinary collaboration, bringing together researchers from multiple faculties and areas of expertise to tackle complex transport and safety challenges through innovative, data-driven approaches.

AVR3 is proud to celebrate this outstanding international recognition and the team’s contribution to advancing safer roads and smarter transport systems. Their work demonstrates the growing role of AI and machine learning in creating practical solutions to real-world mobility challenges.