The Federal Highway Administration (FHWA) issued a Presolicitation Notice for its 2018 Exploratory Advanced Research Program’s Broad Agency Announcement (BAA). It is expected that the BAA will be released soon.

The exponential growth of information and communication technologies have caused a profound shift in the way humans engineer systems leading to the emergence of closed-loop systems involving strong integration and coordination of physical and cyber components, often referred to as cyber-physical systems (CPSs). Because of these disruptive changes, physical systems can now be attacked through cyberspace and cyberspace can be attacked through physical means.

The goal of this project is to create a scalable and robust cyber-physical system (CPS) framework for the observation and control of the functional interdependencies between bridge structures (stationary physical systems) and trucks (mobile physical agents). A CPS framework (Figure 1) is being developed to monitor and control trucks within a single highway corridor to manage the imposed loads and the consumption of structural life by trucks on highway infrastructure including bridges.

Cyber-Physical Systems (CPS) are being increasingly deployed in critical infrastructures such as electric-power, water, transportation, and other networks. These deployments are facilitating real-time monitoring and closed-loop control by exploiting the advances in wireless sensor-actuator networks, the internet of “everything,” data-driven analytics, and machine-to-machine interfaces. CPS operations depend on the synergy of computational and physical components.

Traffic control management strategies have been largely focused on improving vehicular traffic flows on highways and freeways but arterials have not been used properly and pedestrians are mostly ignored. New urban arterial designs encourage modal shifts which gives further impetus to devise novel traffic control strategies to more quickly respond to changing conditions and salient events, while balancing safety and efficiency for all users.

As self-driving cars are being introduced into road networks, the overall safety and efficiency of the resulting traffic system must be established and it must be guaranteed. This project develops methods to analyze and coordinate networks of fully and partially self-driving vehicles that interact with conventional human-driven vehicles on road grids. The outcomes of the research add to the understanding of more general systems with reconfigurable hierarchical structures and they help create designs with minimal computation and communication delay.

In this project we consider the development of a Cyber Physical Freight Transportation System for load balancing in multimodal transportation networks. We use on line simulation models to capture the nonlinear and complex dynamical characteristics of the transportation networks. The simulation models generate the states of the network that are used to solve an optimization problem which finds the optimum routes.

This project is developing tools for traffic management and control using formal methods. By applying techniques such as model-checking and correct-byconstruction synthesis, we ensure that traffic flow satisfies high-level objectives expressed using temporal logics that guarantee desirable behavior such as avoiding congestion, maintaining high throughput, ensuring fairness of ramp metering strategies, and reacting to incidents or unexpected conditions.