C2M2 would like to thank Mizanur “Mizan” Rahman, University of Alabama, for participating in our inaugural C2M2 Cyber-Physical Systems (CPS) Frontiers Series. This speaking series was created to showcase former and current C2M2 doctoral students and early-career faculty researchers who have worked on C2M2 funded projects. Rahman’s talk took place on Friday, May 28th, 2021.
A Physics-based Longitudinal Control Model for Automated Vehicles in a Mixed Traffic Environment
The penetration level of automated vehicles (AV) will be low in the near future. In a mixed traffic environment, AVs will travel by different types of road users, such as human-driven vehicles. The AV controller needs to engage its acceleration and deceleration in such a way so that AV movement must be compatible with immediate upstream vehicles, which could be a human-driven vehicle, and passengers in the AV should feel comfortable as it moves through a mixed traffic environment. This presentation will focus on a physics-based autonomous vehicle longitudinal driver model (PAVL-DM) to move an AV forward with a minimum following gap while considering safety and passenger comfort. The concept, theoretical considerations, and mathematical formulations of the PAVL-DM longitudinal control model will be discussed along with PAVL-DM model equilibria and robustness for safety assurance and string stability. The numerical analysis related to riding comfort and a dynamic minimum following gap while considering safety will also be presented. It is revealed that PAVL-DM (i) can maintain safety between a subject AV and an immediate front vehicle using a newly defined safe gap function depending on the speed and reaction time of an AV; (ii) shows local stability and string stability; and (iii) provides riding comfort for a range of autonomous driving aggressiveness depending on passengers’ corresponding preferences on driving aggressiveness. In addition, a case study using a real-world dataset will be presented, which proves that an AV with the PAVL-DM model maintains a minimum following gap between a subject AV and an immediate front vehicle without compromising safety and passenger comfort.
Mizanur “Mizan” Rahman is an Assistant Professor in the Department of Civil, Construction and Environmental Engineering at the University of Alabama (UA), Tuscaloosa, Alabama. He is also the director of the Connected and Automated Mobility laboratory (CAM Lab) at UA. His research focuses on traffic flow theory, driver behavior modeling for connected/automated vehicles (CAVs), cybersecurity, artificial intelligence-based predictive analytics, and transportation cyber-physical systems for CAVs/smart cities. He received the best paper award from America’s Intelligent Transportation Society (ITS) at the 2014 ITS World Congress. He also received the 2015 IEEE ITS Society George N. Saridis Best Transactions Paper Award for Outstanding Survey. Rahman received his M.Sc. and Ph.D. degrees in Civil Engineering (Transportation systems), from Clemson University, in 2013 and 2018, respectively. After his graduation in August 2018, he joined the Center for Connected Multimodal Mobility (C2M2), a U.S. Department of Transportation Tier 1 University Transportation Center as a postdoctoral research fellow. After that, Rahman served as Assistant Director of C2M2 and a research associate for the NSF Engineering Research Center for Computer and Network RESIliency and Security for Transportation (CAN-RESIST) planning grant.