CPS: Breakthrough: A Dynamic Optimization Framework for Connected Automated Vehicles in Urban Environments

Abstract

Connected Automated Vehicles (CAVs), often referred to as "self-driving cars", will have a profound impact not only on transportation systems, but also in terms of associated economic, environmental, and social effects. As with any such major transformative undertaking, quantifying the magnitude of its expected impact is essential. The first part of this project aims at precisely this quantification (also referred to as the "price of anarchy") by assessing the difference between the performance of a transportation system as it now stands and the performance achievable in a CAV-based environment. A well-designed CAV-based transportation network has the benefit of expanding limited roadway capacity without affecting the existing infrastructure, but rather by seeking novel ways which focus on the vehicles and not the roads. A major part of the proposed project will focus on meeting this goal at the weakest links of a transportation system: the bottleneck points defined by intersections and merging points. The project will use inverse optimization techniques applied to large traffic datasets (from the Eastern Massachusetts road network) to infer unobservable factors, such as user behavior, and use them to construct a predictive model of traffic equilibria. Based on these new traffic demand models, forward optimization problems will be solved which will lead to socially optimal traffic flow equilibria achievable through a CAV-based system. A dynamic optimization framework will also be developed for urban intersections where the motion of CAVs will be controlled based on real-time data communicated over a wireless network to operate both safely and efficiently in a highly dynamic and uncertain environment. Towards this goal, the broader technical challenge of solving dynamic optimization problems on line will be addressed through novel ways that exploit event-driven methodologies with wide applicability in Cyber-Physical Systems. The overall framework will be demonstrated by implementing the key concepts and explicit control and optimization mechanisms in a miniature city test bed with an urban landscape and small mobile robots emulating CAVs with the ability to communicate and share data

Christos Cassandras

Christos G. Cassandras is Head of the Division of Systems Engineering and Professor of Electrical and Computer Engineering at Boston University. He is also co-founder of Boston University’s Center for Information and Systems Engineering (CISE). He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In 1982-84 he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In 1984-1996 he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, stochastic optimization, and computer simulation, with applications to computer and sensor networks, manufacturing systems, and transportation systems. He has published over 300 refereed papers in these areas, and five books. He has guest-edited several technical journal issues and serves on several journal Editorial Boards. He has recently collaborated with The MathWorks, Inc. in the development of the discrete event and hybrid system simulator SimEvents.

Dr. Cassandras was Editor-in-Chief of the IEEE Transactions on Automatic Control from 1998 through 2009 and has also served as Editor for Technical Notes and Correspondence and Associate Editor. He is the 2012 President of the IEEE Control Systems Society (CSS) and has served as Vice President for Publications and on the Board of Governors of the CSS. He has chaired the CSS Technical Committee on Control Theory, and served as Chair of several conferences. He has been a plenary speaker at many international conferences, including the American Control Conference in 2001 and the IEEE Conference on Decision and Control in 2002, and an IEEE Distinguished Lecturer.

He is the recipient of several awards, including the 2011 IEEE Control Systems Technology Award, the Distinguished Member Award of the IEEE Control Systems Society (2006), the 1999 Harold Chestnut Prize (IFAC Best Control Engineering Textbook) for Discrete Event Systems: Modeling and Performance Analysis, a 2011 prize for the IBM/IEEE Smarter Planet Challenge competition, a 1991 Lilly Fellowship and a 2012 Kern Fellowship. He is a member of Phi Beta Kappa and Tau Beta Pi. He is also a Fellow of the IEEE and a Fellow of the IFAC.

Performance Period: 04/01/2017 - 03/31/2020

Institution: Trustees of Boston University

Sponsor: National Science Foundation

Award Number: 1645681