Short Bio
Nikolaos Bekiaris-Liberis received the PhD degree in aerospace engineering from the University of California, San Diego in 2013. From 2013 to 2014, he was a Post-Doctoral Researcher with University of California, Berkeley. From 2019 to 2022, he was an Assistant Professor; from 2017 to 2019, he was a Marie Sklodowska-Curie Fellow; and from 2014 to 2017, he was a Research Associate with the Technical University of Crete, Greece, where he is currently an Associate Professor with the Department of Electrical and Computer Engineering. His research interests include nonlinear delay, switched, and distributed parameter systems, and their applications to transport systems.
Nikolaos Bekiaris-Liberis serves as Associate Editor for Automatica and IEEE Transactions on Automatic Control, and as Senior Editor for IEEE Transactions on Intelligent Transportation Systems. He received the Chancellor's Dissertation Medal in Engineering from the University of California, San Diego in 2014 and the George N. Saridis Outstanding Research Paper Award in 2019 (from IEEE Intelligent Transportation Systems Society). He was a recipient of a 2016 Marie Sklodowska-Curie Individual Fellowship Grant, and he received a 2022 European Research Council (ERC) Consolidator Grant.
Abstract
Delays and transport phenomena are ubiquitous in mobility systems, from actuation and communication delays in connected and automated vehicles to wave propagation in traffic and crowd flows. These phenomena share a common dynamical-system description through transport/hyperbolic partial differential equations (PDEs). In this talk, capitalizing on this connection, I will present control designs for transport systems at both microscopic and macroscopic scales. At the microscopic level, I will present predictor-feedback cooperative adaptive cruise control designs for vehicular platoons that compensate actuation and communication delays, while provably guaranteeing string stability and safety; experimental validation results will also be shown. At the macroscopic level, I will present traffic state estimation schemes that utilize data from connected vehicles, as well as PDE-based traffic flow control designs in which automated vehicles act as actuators by manipulating their time gaps. I will then move from vehicle to people transport, presenting macroscopic models of coupled crowd flow and epidemics spreading processes, their calibration from microscopic data, and control strategies for crowd flows in public spaces such as stations and corridors.