CAREER: Control Design for Dynamical Network Flows with Applications to Transportation

University Of Southern California, Los Angeles CA

Investigators

Abstract

As our society is becoming more dependent on critical infrastructure networks such as transportation, communication, water, power, and gas, their efficient and resilient operation is becoming ever more important. Hence, one of the engineering grand challenges identified by the National Academy of Engineering is to restore and improve urban infrastructure systems. However, as recent evaluations by the American Society of Civil Engineers show, the state of our infrastructure systems continues to be substandard, and will likely remain so without massive investments. With significant growth in demand projected, a future infrastructure system that maintains the status quo will not function even at today's current, often inadequate, levels. It is increasingly being realized that leveraging sensing, actuation, and information technologies can achieve substantial improvements in the performance of these systems. These cyber technologies have the potential to endow our infrastructure networks with the capability to dynamically respond to changes in demand, supply, and even physical properties under disruptions. The existing approaches to control of infrastructure networks, however, are inadequate to realize the potential of this capability. This is because they are either heuristic with no formal performance guarantees; or they adopt static abstractions, and hence are useful only for long term planning; or the dynamical frameworks are used only for simulation and analysis purposes with little or no consideration for control design. The project will develop an integrated research and education program on rigorous control design for intelligent infrastructure networks, with a special emphasis on transportation. Collaborations with local transportation and planning agencies will facilitate rapid transition from research to practice. The outreach activities include development of an interactive traffic simulator, which would also serve as an experiment test bed to model dynamic driver behavior; and interactive network interdiction games to demonstrate the concepts of cascading failures and network robustness to general public. The education activities include development of new courses on analysis, control and estimation of infrastructure networks. Research opportunities will be expanded for undergraduates to implement control algorithms on professional transportation software to generate case studies, which will be used for our interactions with transportation agencies. Existing programs at the University of Southern California will be utilized to integrate inclusive teaching practices into educational activities in order to address retention of women, underrepresented and minority students. Network flow is a natural modeling paradigm for several infrastructure networks. The current state-of-the-art in theoretical network flow research primarily consists of algorithms for fast computation of maximum network flow capacity, or optimal flow distribution with respect to some performance metrics; and numerical analysis of dynamical network flows with cascade effects under fixed routing policies. The intellectual merits of the proposed research are: (i) a dynamical network flow framework that models coupling between dynamics of flow and jumps in network topology, e.g., due to cascading failures, as well as facilitates control design; (ii) new advancements in analysis for nonlinear dynamical systems using differential analysis and contraction principles, and applying them for analysis and control synthesis under proposed dynamical network flow; (iii) a computational framework for quantifying margins of resilience in terms of the disturbance generation process, network topology, and cascade dynamics; (iv) application of proposed tools to transportation through dynamic signal control, and inclusion of resilience metric in network design. The margin of resilience computations will identify canonical network flow concepts, besides the classical notion of cuts, as key indicators of network performance from efficiency and resilience perspective, under control and dynamical considerations. Beyond its immediate emphasis on dynamical network flows, the project aims to develop elements of robust control theory for networked dynamical systems.