Transportation Systems Resilience: Capacity-Aware Control and Value of Information



Resilience of a transportation system is its ability to operate under adverse events like incidents and storms. Availability of real-time traffic data provides new opportunities for predicting  travelers’ routing behavior and implementing network control operations during adverse events. In this talk, we will discuss two problems: controlling highway corridors in response to disruptions and modeling strategic route choices of travelers with heterogeneous access to incident information. Firstly, we present an approach to designing control strategies for highway corridors facing stochastic capacity disruptions such random incidents and vehicle platoons/moving bottlenecks. We exploit the properties of traffic flow dynamics under recurrent incidents to derive verifiable conditions for stability of traffic queues, and also obtain guarantees on the system throughput. Secondly, we introduce a routing game in which travelers receive asymmetric and incomplete information about uncertain network state, and make route choices based on their private beliefs about the state and other travelers’ behavior. We study the effects of information heterogeneity on travelers’ equilibrium route choices and costs. Our analysis is useful for evaluating the value of receiving state information for travelers, which can be positive, zero, or negative in equilibrium. These results demonstrate the advantages of considering network state uncertainty in both strategic and operational aspects of system resilience. 



Saurabh Amin is Robert N. Noyce Career Development Associate Professor in the Department of Civil and Environmental Engineering at MIT. He is also affiliated with the Institute of Data, Systems and Society and the Operations Research Center at MIT. His research focuses on the design of network inspection and control algorithms for infrastructure systems resilience. He studies the effects of security attacks and natural events on the survivability of cyber-physical systems, and designs incentive mechanisms to reduce network risks. Dr. Amin received his Ph.D. from the University of California, Berkeley in 2011. His research is supported by NSF CPS FORCES Frontiers project, NSF CAREER award, Google Faculty Research award, DoD-Science of Security Program, and Siebel Energy Institute Grant.