Research Terms
Dr. Mohamed Abdel-Aty, PE is a Trustee Chair at the University of Central Florida (UCF). He is a Pegasus Professor and the Chair of the Civil, Environmental, and Construction Engineering Department at UCF. He is leading the Future City initiative at UCF. As part of the initiative, he introduced in 2019 the first MS degree in Smart Cities in Engineering in the US. He is also the director of the Smart and Safe Transportation Lab1, the Winner of the USDOT Solving for Safety Visualization Challenge2, Real-time crash risk visualization using integrated tools for traffic safety evaluation and management, November 2019. His main expertise and interests are in the areas of traffic safety, simulation, big data and data analytics, ITS, and CAV. He is the pioneer and well recognized nationally and internationally in work and research in real-time safety, Proactive traffic management, integrating road safety and transportation planning, Highway Safety Manual, and Connected Vehicles. In 2015, he was awarded the Pegasus Professorship, the highest honor at UCF. Dr. Abdel-Aty has managed 72 research projects of $20 million. Dr. Abdel-Aty has published more than 650 papers, 348 in journals (as of Jan. 2021, Google Scholar citations are more than 20,000 H-Index 74; Science direct papers downloaded > 370,000 times). He supervised to completion of more than 90 Ph.D. and MS students (currently 16 more Ph.D. students). Dr. Abdel-Aty is the Editor-in-Chief of Accident Analysis and Prevention, the premier journal in safety. He is the Associate Editor of Transportation Research Interdisciplinary Perspectives (TRIP), Elsevier. He is a member of the Academy of Science, Engineering, and Medicine of Florida (ASEMFL). He is a member of the Editorial Boards of the ITS Journal, Analytic Methods in Accident Research, Transportation Research Part C, and the International Journal of Sustainable Transportation, Fellow of both ASCE and ITE, and member of multiple TRB Committees, including Safety Performance Analysis and User Information Systems. He is the Chair of the ASCE Transportation Safety Committee. In 2003, he was selected as UCF’s Distinguished Researcher, and in 2007 as UCF’s Outstanding Graduate Teacher. He has received multiple research awards from the College of Engineering & Computer Science in 2003, 2008, 2010, and 2012, including the Dean’s Advisory Board award. He and his students received multiple awards for their papers and research from ASCE, TRB, WCTR, ITS Florida, and FL section ITE. His students received twice the best University dissertation, and once the best MS thesis, and the Milton Pikarsky Memorial Award for the best Master’s thesis in the field of science and technology in transportation studies, Council of University Transportation Centers (CUTC), Dec. 2019. Dr. Aty has received the 2020 Roy W. Crum Distinguished Service Award from the Transportation Research Board of the National Academies, the Francis C. Turner Award from ASCE for his “outstanding leadership in the field of road safety nationally and internationally”. He has also received the 2019 Transportation Safety Council Edmund R. Ricker Award, Institute of Transportation Engineering (ITE), and the Lifetime Achievement Safety Award from ARTBA in 2019. He has also received multiple international awards including the prestigious Prince Michael International Road Safety Award, London 2019. He has delivered more than 22 Keynote speeches at conferences in the US and around the world. He has worked closely with USDOT and multiple state DOTs as well as internationally He is a registered professional engineer in Florida.
The University of Central Florida invention is a real-time safety visualization system that was selected by the U.S. Department of Transportation as an innovative solution for road safety. The system brings together extensive work in real-time safety risk prediction (traffic and weather sensors; smartphone-based data; advanced analytics, artificial intelligence, and Pro-Active Traffic Management (PATM) techniques) to produce a program that enables decision-makers and operators to identify in advance the real-time potential road safety problems and the potential for severe crashes.
The University of Central Florida invention introduces Ped-CrossSafe: an intelligent, real-time system designed to improve pedestrian safety at intersections by predicting crossing intentions using advanced AI and computer vision. Traditional systems rely on push-buttons and static signal timing, often leading to unsafe crossings and traffic inefficiencies. Imagine a crosswalk that knows when you're about to cross—and makes traffic stop for you before you even take the first step. This system eliminates those limitations by detecting and tracking pedestrians - including vulnerable users like children, cyclists, and wheelchair users- and proactively activating pedestrian signals. It also extends crossing time when needed, ensuring safer and more inclusive mobility. The result is a smarter, safer, and more responsive intersection experience.
Technical Details: Ped-CrossSafe uses video feeds from four cameras placed at key points around an intersection to detect and track pedestrians in real time. The system applies deep learning models for pedestrian detection and pose estimation, and advanced object tracking algorithms for tracking movement across defined zones—waiting, start-crossing, and crossing. It calculates features like walking speed, body orientation, and head pose, which are then analyzed using an ensemble machine learning model to predict crossing intentions and direction.
To ensure real-time performance, the system activates pose estimation only when pedestrians are in the waiting area, reducing computational load. It also includes a phase extension checker that monitors pedestrian progress and extends signal time if needed, based on walking speed and crosswalk distance. Optimizations such as reduced video resolution and efficient Python libraries enable processing speeds up to 33 FPS, making the system both fast and scalable for deployment in real-world traffic environments.
