Abstract: As self‐driving cars are introduced into road networks, the overall safety and efficiency of the resulting traffic system must be established and guaranteed. Numerous critical software‐related recalls of existing automotive systems indicate that current design practices are not yet up to this challenge. This project seeks to address this problem, by developing methods to analyze and coordinate networks of fully and partially self‐driving vehicles that interact with conventional human‐driven vehicles on roads.

Abstract: The objective of the project is to demonstrate the synergistic use of a cyber-physical infrastructure consisting of smart-phone devices; cloud computing, wireless communication, and intelligent transportation systems to manage vehicles in the complex urban network – through the use of traffic controls, route advisories and road pricing – to jointly optimize drivers’ mobility and the sustainability goals of reducing energy usage and improving air quality.

Abstract: The goal of this project is to develop fundamental theory, computationally efficient algorithms, and real-world experiments for the analysis and design of safety-critical cyber-physical transportation systems with human operators. To this end, we propose a modeling, theoretical, and experimental collaborative effort combining human factors, control theory, and computer science.   As crashes at traffic intersections account for about 40% of overall vehicle crashes, we will focus on intersection crashes in this project.

Abstract: The objective of this project is to develop a formal methods approach to traffic management. Formal methods is an area of computer science that develops efficient techniques for proving the correct operation of systems, such as computer programs and digital circuits, and for designing systems that are correct by construction.

Abstract: Cyber-­Physical Systems comprise richly heterogeneous collections of devices (mobile devices, home electronics, taxis, robotic drones, etc.) that together gather sensor data, analyze it, and coordinate large-­‐scale actions in response to it.

Abstract: The objective of this project is to develop a theoretical framework for stochastic learning, decision-making, and control in high-dimensional cyber-physical systems. In our general framework, decision makers dynamically refine their estimates of the time-varying physical system based on acquired information, which may be obtained by distributed sensors.

Abstract: 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.

Abstract: Wireless sensor-actuator networks (WSAN) are systems consisting of numerous sensing and actuation devices that interact with the environment and coordinate their activities over a wireless communication network. WSANs represent an important class of cyber-physical system (CPS) found in our national civil infrastructure. This project addresses the issue of resilience in WSANs.

Abstract: As part of our CPS project, we have focused on the problem of model repair for cyber-physical systems. This work involves identifying constraints caused due to physical components during revision. We consider four types of constraints cyber-cyber, cyber-physical, physical-cyber and  physical-physical. Based on the complexity limitations caused by these constraints we are developing efficient heuristics to mitigate the cost of model repair. We have also focused on extending revision to code level.

Securing critical networked cyber-physical systems (NCPSs) such as the power grid or transportation systems has emerged as a major national and global priority. The networked nature of such systems renders them vulnerable to a range of attacks both in cyber and physical domains as corroborated by recent threats such as the Energetic Bear virus.