Emerging mobility systems, e.g., connected and automated vehicles and shared mobility, provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better decisions for improving safety and transportation efficiency. However, different levels of vehicle automation in the transportation network can significantly alter transportation efficiency metrics (travel times, energy, environmental impact). Moreover, we anticipate that efficient transportation might alter human travel behavior causing rebound effects, e.g., by improving efficiency, travel cost is decreased, hence willingness-to-travel is increased. The latter would increase overall vehicle miles traveled, which in turn might negate the benefits in terms of energy and travel time. The project will consolidate emerging mobility systems and modes with real-world data and processed information leading to an equitable transportation system with broad economic, environmental, and societal benefits. We expect the outcome of this project to enhance our understanding of the rebound effects, changes in travel demand and capacity, human reception, adoption, and use of emerging mobility systems.
The outcome of this research will deliver an online learning framework that will aim at distributing travel demand in a given transportation network resulting in a socially-optimal mobility system that travelers would be willing to accept. A ?socially-optimal mobility system? is defined as a mobility system that (1) is efficient (in terms of energy consumption and travel time), (2) does not cause rebound effects, and (3) ensures equity in transportation. The framework will establish new approaches in optimally controlling cyber-physical systems by merging learning and control approaches. It includes the development of new methods to enhance accessibility, safety, and equity in transportation and travelers? acceptance. In the context of the proposed framework, a ?social planner? faces the problem of aggregating the preferences of the travelers into a collective, system-wide decision when the private information of the travelers is not publicly known. Mechanism design theory will be used to derive the optimal routes and the selection of a transportation mode for all travelers so as to maximize accessibility, safety, and equity in transportation and travelers? acceptance. Online learning algorithms for contextual bandit problems will be developed to identify traveler preferences and to determine how they would respond to the social planner?s recommendations on routing and selection of a transportation mode.
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.