A Formal Approach to Enforce Safety in Cyber-Physical
Professor Domitilla Del Vecchio
Massachusetts Institute of Technology
Department of Mechanical Engineering
and the Laboratory fo Information and Decision Systems (LIDS)
Friday, January 25, 2013
3:30 – 4:30 pm
1500 EECS (Open to the Public)
ABSTRACT: The current progress of embedded computation and communication technologies are pushing several systems toward increased levels of autonomy. Transportation systems, in particular, are experiencing a substantial increase of automation for safety, comfort, and fuel efficiency. Given the life critical role of these systems, it is important to guarantee that the new designed functions keep the vehicles away from collisions. This is a challenging task given the large number of vehicles, the presence of human drivers, and communication failures. In this talk, I will focus on vehicle collision avoidance at traffic intersections and illustrate the theoretical basis of our approach, computational tools, and experiments both on an in-scale test-bed and on full scale vehicles. The models are hybrid automata with hidden information, due to unknown human decisions, imperfect sensory information, or missed communication. The problem of collision avoidance is formulated as a differential game in which one player (the controller) does not have full information about the system, while the other player (the environment) does. Algorithms that solve general differential games are usually computationally prohibitive. In this talk, I will show how, in the specific application scenario, this problem can be efficiently solved leveraging the fact that the vehicle dynamics are input/output monotone with respect to suitable partial orders. I will illustrate the application of these techniques to collision avoidance problems at traffic intersections. Specifically, both instances in which all vehicles communicate and in which not all vehicles communicate will be shown, along with experimental demonstrations on an in-scale test-bed. Finally, a full scale implementation will be shown in which two instrumented Lexus vehicles override their drivers to prevent a crash.
BIO: Domitilla Del Vecchio received the Ph.D. degree in Control and Dynamical Systems from the California Institute of Technology, Pasadena, and the Laurea degree in Electrical Engineering from the University of Rome at Tor Vergata in 2005 and 1999, respectively. From 2006 to 2010, she was an Assistant Professor in the Department of Electrical Engineering and Computer Science and in the Center for Computational Medicine and Bioinformatics at the University of Michigan, Ann Arbor. In 2010, she joined the Department of Mechanical Engineering and the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT), where she is currently the W. M. Keck Career Development Associate Professor in Biomedical Engineering. She is a recipient of the Donald P. Eckman Award from the American Automatic Control Council (2010), the NSF Career Award (2007), the Crosby Award, University of Michigan (2007), the American Control Conference Best Student Paper Award (2004), and the Bank of Italy Fellowship (2000). Her research interests include analysis and control of nonlinear and hybrid dynamical systems and the analysis and design of biomolecular networks.