Invited talk by Prof. John S. Baras, University of Maryland College Park, USA on 18/1/2024 @10:30-12:00

Title: Autonomous Vehicles Planning, Control and Safety in Mixed-Traffic Environments

Place: TUC Campus, Room Λ - Κτίριο Επιστημών/ΗΜΜΥ, 145Π-58

Abstract: We present some of our recent research results on Autonomous Vehicles (AV). In the first part, we consider connected autonomous vehicles (CAVs) that promise increased safety, efficiency, and better accessibility. Communication among CAVs (V2V) and with infrastructure (V2I) provide CAVs the ability to share progressively gathered information, policies, and rules, and pursue controls related to both local and global objectives (in space and time). We describe our recently developed methods and associated algorithmic implementations, through which CAVs can contribute to solving some key problems: highway merge junction bottlenecks, highway traffic shock waves, signalized or unsignalized intersection management. We demonstrate that our algorithms achieve vastly superior solutions by harnessing the communication capabilities of CAVs. In the second part, we consider methods that enhance road safety by preventing accidents caused by human errors. AVs will gradually be introduced on public roads and highways in the presence of human-driven vehicles, leading to mixed-traffic scenarios. These situations pose further difficulties pertaining to the variability in human driving patterns. We investigate the joint decision-making and motion planning problem in structured environments with a multi-timescale navigation architecture. Specific problems addressed are: bidirectional highway overtaking, highway maneuvering in traffic, and crash mitigation on highways. We describe our algorithmic modules, that pursue systematic complexity (data and computation) reduction, at different timescales to gain immediate performance improvements in inference and action/response delay minimization. Most importantly, our algorithms ensure that the safety of the overall system is a fundamental constraint built into the system. We close with future directions.

Bio: John S. Baras is a Distinguished University Professor, holding the Lockheed Martin Chair in Systems Engineering, in the Institute for Systems Research (ISR) and the ECE Department at the University of Maryland College Park (UMD). He received his Ph.D. degree in Applied Mathematics from Harvard University, in 1973, and he has been with UMD since then. From 1985 to 1991, he was the Founding Director of the ISR. Since 1992, he has been the Director of the Maryland Center for Hybrid Networks (HYNET), which he co-founded. He is a Fellow of IEEE (Life), SIAM, AAAS, NAI, IFAC, AMS, AIAA, Member of the National Academy of Inventors (NAI) and a Foreign Member of the Royal Swedish Academy of Engineering Sciences (IVA). Major honors and awards include the 1980 George Axelby Award from the IEEE Control Systems Society, the 2006 Leonard Abraham Prize from the IEEE Communications Society, the 2017 IEEE Simon Ramo Medal, the 2017 AACC Richard E. Bellman Control Heritage Award, and the 2018 AIAA Aerospace Communications Award. In 2016 he was inducted in the University of Maryland A. J. Clark School of Engineering Innovation Hall of Fame. In June 2018 he was awarded a Doctorate Honoris Causa by his alma mater the National Technical University of Athens, Greece. His research interests include systems, control, optimization, autonomy, machine learning, artificial intelligence, communication networks, applied mathematics, signal processing and understanding, robotics, computing architectures, formal methods, network security and trust, systems biology, healthcare management, model-based systems engineering. He has been awarded twenty patents and honored with many awards as innovator and leader of economic development.