Title: Efficient Traffic Management: A Formal Methods Approach 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. This project extends this formalism to traffic networks where correctness specifications include eliminating congestion, ensuring that the freeway throughput remains over a minimum threshold, that queues are always eventually emptied, etc. The task is then to design signal timing and ramp metering strategies to meet such specifications. To accomplish this task, the project takes advantage of the inherent structure of existing, validated mathematical models of traffic flow and develops computationally efficient design techniques. The results are tested with real traffic data from the Interstate 210 travel corridor in Southern California. The educational component of the project includes course development on modeling and control of traffic networks, featuring in particular the formal methods approach of this project, and organizing workshops to train traffic engineers and operation practitioners on the use of software tools and methodologies of the project. To meet rich control objectives expressed using temporal logic, the project exploits the piecewise affine nature of existing, validated traffic models, and derives efficient finite state abstractions that form the basis of correct-by-construction control synthesis. To ensure scalability, the project further takes advantage of inherent monotonicity properties and decomposibility into sparsely connected subsystems. The first research task is to develop a design framework for signal timing and ramp metering strategies for signalized intersections and freeway traffic control. The second task is the coordinated control of freeway onramps and nearby signalized intersections to address situations such as a freeway demand surge after a sporting event, or an accident on the freeway when signal settings must be adjusted to favor a detour route. The third task is to pursue designs that exploit the statistics of demand for probabilistic correctness guarantees, as well as designs that incorporate optimality requirements, such as minimizing travel time. Validation of the results is pursued with high-fidelity simulation models calibrated using traffic data from the Interstate 210 travel corridor.

Large battery systems with 100s/1000s cells are being used to power various physical platforms. For example, automobiles are transitioning from conventional powertrains to (plug-in) hybrid and electric vehicles (EVs). To achieve the desired efficiency of EVs, significant improvements are needed in the architecture and algorithms of battery management. This project will develop a new comprehensive battery management architecture, called Smart Battery Management System (SBMS). The research is expected to bridge the wide gap existing between cyber-physical system (CPS) research and electrification industry communities, provide environment-friendly solutions, increase the awareness of CPS, and develop skilled human resources. This project will incorporate and enhance a battery management system (BMS) by including battery state-of-charge (SoC) and state-of-health (SoH) algorithms as well as power management strategies on both pack and cell levels. Specifically, it consists of five main research tasks: (i) design a dynamically reconfigurable energy storage system to tolerate harsh internal and external stresses; (ii) develop cell-level thermal management algorithms; (iii) develop efficient, dependable charge and discharge scheduling algorithms in hybrid energy storage systems; (iv) develop a comprehensive, diagnostic/prognostic (P/D) algorithm with system parameters adjusted for making optimal decisions; and (v) build a testbed and evaluate the proposed architecture and algorithms on the testbed. This research will advance the state-of-the-art in the management of large-scale energy storage systems, extending their life and operation-time significantly, which is key to a wide range of battery-powered physical platforms. That is, SBMS will enable batteries to withstand excessive stresses and power physical platforms for a much longer time, all at low costs. SBMS will also serve as a basic framework for various aspects of CPS research, integrating (cyber) dynamic control and P/D mechanisms, and (physical) energy storage system dynamics.

This project will design next-generation defense mechanisms to protect critical infrastructures, such as power grids, large industrial plants, and water distribution systems. These critical infrastructures are complex primarily due to the integration of cyber and physical components, the presence of high-order behaviors and functions, and an intricate and large interconnection pattern. Malicious attackers can exploit the complexity of the infrastructure, and compromise a system's functionality through cyber attacks (that is hacking into the computation and communication systems) and/or physical attacks (tampering with the actuators, sensors and the control system). This work will develop mathematical models of critical infrastructures and attacks, develop intelligent control-theoretic security mechanisms, and validate the findings on an industry-accredited simulation platform. This project will directly impact national security and economic competitiveness, and the results will be available and useful to utility companies. To accompany the scientific advances, the investigators will also engage in educational efforts to bring this research to the classroom at UCR, and will disseminate their results via scientific publications. The work will also create several opportunities for undergraduate and graduate students to engage in research at UCR, one of the nation's most ethnically diverse research-intensive institutions. This study encompasses theoretical, computational, and experimental research at UCR aimed at characterizing vulnerabilities of complex cyber-physical systems, with a focus on electric power networks, and control-theoretic defense mechanisms to ensure protection and graceful performance degradation against accidental faults and malicious attacks. This project proposes a transformative approach to cyber-physical security, which builds on a unified control-theoretic framework to model cyber-physical systems, attacks, and defense strategies. This project will undertake three main research initiatives ranging from fundamental scientific and engineering research to analysis using industry-accepted simulation tools: (1) modeling and analysis of cyber-physical attacks, and their impact on system stability and performance; (2) design of monitors to reveal and distinguish between accidental and malignant contingencies; and (3) synthesis of adaptive defense strategies for stochastic and highly dynamic cyber-physical systems. Results will first be characterized from a pure control-theoretic perspective with focus on stochastic, switching, and dynamic cyber-physical systems, so as to highlight fundamental research challenges, and then specialized for the case of smart grid, so as to clarify the implementation of monitors, attacks, and defense strategies. The findings and strategies will be validated for the case of power networks by using the RTDS simulation system, which is an industry-accredited tool for real-time tests of dynamic behavior, faults, attacks, monitoring systems, and defensive strategies.

An appointed National Research Council committee will conduct the second phase of a study to consider future research goals and directions for foundational science in cybersecurity and how investments in foundational work support civilian and national security mission needs in the long term. It will consider relevant topics in social and behavioral sciences as well as more "traditional" cybersecurity topics. The committee will review current federal cybersecurity research strategies, plans, and programs as well as requirements for both civilian and national security applications. It will consider major challenge problems, explore proposed new directions, identify gaps in the current portfolio, consider the complementary roles of research in unclassified and classified settings, and consider how foundational work in an unclassified setting can be translated to meet national security objectives. In Phase 1, already completed with separate funding, the study committee conducted initial data gathering and analysis. In Phase 2, to be funded under this activity, the committee will undertake additional data-gathering, analysis and deliberations and produce a report providing a high-level roadmap for foundational cybersecurity research. Foundational cybersecurity research that yields yield new technologies and approaches is an important element of the nation's response to the cybersecurity challenge. The results of this study are expected to inform future activities by federal agencies that conduct cybersecurity research and federal coordinating bodies for IT and cybersecurity. It is also expected to inform cybersecurity researchers as well as industry -- which is both a developer and consumer of cybersecurity technologies and services -- about needs, opportunities, and future directions.

U.S. economic growth, energy security, and environmental stewardship depend on a sustainable energy policy that promotes conservation,efficiency, and electrification across all major sectors. Buildings are the largest sector and therefore an attractive target of these efforts: current Federal sustainability goals mandate that 50% of U.S.commercial buildings become net-zero energy by 2050. A range of options exists to achieve this goal, but financial concerns require a data-driven, empirically-validated approach. However, critical gaps exist in the energy and water measurement technology, and indoorclimate control science, needed to benchmark competing options, prioritize efficiency investments, and ensure occupant comfort. To address these challenges, this project proposes a new kind of "peel-and-stick" sensor that can be affixed to everyday objects to infer their contributions to whole-building resource consumption. To use the sensors, occupants or building managers simply tag end loads like a ceiling light, shower head, or range top. The sensors monitor the ambient conditions around a load and, using statistical methods,correlate those conditions with readings from existing electricity, gas, or water meters, providing individual estimates without intrusive metering. The sensors are built from integrated circuit technology laminated into smart labels, so they are small, inexpensive, and easy-to-deploy. The sensors are powered by the same ambient signals they sense, eliminating the need for periodic battery replacement or wall power. Collectively, these properties address cost and coverage challenges, and enable scalable deployment and widespread adoption. The intellectual merit of this proposal stems from the insight that the transfer and use of energy (and other resources) usually emits energy, often in a different domain, and that this emitted energy is often enough to intermittently power simple, energy-harvesting sensors whose duty cycle is proportional to the energy being transferred or used. Hence, the mere activation rate of the sensors signalsthe underlying energy use. The power-proportional relationship between usage activity and side channel harvesting, when coupled with state-of-the art, millimeter-scale, nano-power chips and whole-house or panel-level meters, enables small and inexpensive sensor tags that are pervasively distributed with unbounded lifetimes. But, networking and tasking them, and making sense of their data, requires a fundamental rethinking of low-power communications, control, and data fusion to abstract the intermittent, unreliable, and noisy sensor infrastructure into actionable information. This project's broader impact stems from an integrated program of education, research, and outreach that (i) creates a smart objects focused curriculum whose classroom projects are motivated by research needs, (ii) provides research experiences for undergraduates and underrepresented minorities, (iii) mentors students on all aspects of successful research from articulating hypotheses to peer-reviewing papers,(iv) disseminates teaching materials on embedded systems and research pedagogy, (v) produces students who bridge disciplines,operating at the intersection of measurement science, information technology, and sustainability policy, and (vi) translates scientific discovery and technical knowledge into beneficial commercial products through industry outreach and internships, and (vii) engages with the National Labs to ensure that the research addresses pressing problems.

Designing software that can properly and safely interact with the physical world is an important cyber-physical systems design challenge. The proposed work includes the development of a novel approach to designing planning and control algorithms for high-performance cyber physical systems. The new approach was inspired by statistical mechanics and stochastic geometry. It will (i) identify behavior such as phase transitions in cyber-physical systems and (ii) capitalize this behavior in order to design practical algorithms with provable correctness and performance guarantees. The algorithms developed through this research effort hold the potential for immediate industrial impact, particularly in the development of real-time robotic systems. These algorithms may strengthen the rapidly developing U.S. robotics industry. The proposed research activity will also vitalize the PI?s educational plans. Undergraduate and graduate courses that make substantial contributions to the embedded systems education at MIT will be developed. The classes will focus on provably-correct controller synthesis for cyber-physical systems, which is currently not thought at MIT. Undergraduate students will be involved in research activities.

The goal of this project is to establish a theoretical and empirical foundation for secured and efficient energy resource management in the smart grid - a typical energy-based cyber-physical system and the future critical energy infrastructure for the nation. However, as a large distributed and complex system, the smart grid inherently operates under the presence of various uncertainties, which can be raised from natural disasters, malicious attacks, distributed renewable energy resources, plug-in electrical vehicles, habits of energy usage, and weather. These uncertainties make the development of a secured and efficient energy resource management system challenging. To address this challenging problem, a novel modeling framework and techniques to deal with these uncertainties will be developed. Threats and their impact on both system operations and end users will be studied and effective defensive schemes will be developed. The outcomes of this project will have broader impacts on the higher education system and national economy and will provide a scientific foundation for designing a secured and efficient energy-based critical infrastructure. The contributions of this project include: a theoretical framework, techniques, and toolkits for smart grid research and education. Specifically, a modeling framework for secured and efficient energy resource management will be developed to quantify uncertainties from both the cyber and physical power grids. Techniques based on statistical modeling, data mining, forecasting, and others will be developed to manage energy resources efficiently. Based on the developed framework, the space of attacks against system operations and end users from key function modules, attack venue, abilities of adversaries, and system knowledge will be studied systematically. Based on the deep understanding of attacks, novel schemes to prevent, detect, and attribute attacks will be developed. An integrated cyber and physical power grid simulation tool and testbed will be developed to evaluate the proposed modeling framework and techniques using realistic scenarios. This project will integrate research, education, and outreach. The outcomes of the project will be integrated into curriculum development and provide research and educational opportunities for both graduate and undergraduate students, including underrepresented minorities and CyberCorps: Scholarship for Service students.

This NSF-FDA Scholar-In-Residence award supports translational research in modeling to inform future medical device design and approval processes. It is supported by the NSF Cyber-Physical Systems program in the Division of Computer and Network Systems in the Directorate for Computer and Information Science and Engineering. Sudden cardiac death is the leading cause of fatalities in the industrialized world. One in five people in the United States is affected by some sort of heart disease and one third of all deaths are due to cardiac diseases with an economic impact of about $200 billion a year. Most of these deaths result from arrhythmias, particularly fibrillation, which is rapid, disorganized electrical activity. The classification of arrhythmias as either reentrant or focal is of clinical significance, yet is difficult to assess. The FDA is responsible for regulating the systems and algorithms that aim to make this important differentiation. Such differentiation is a complex task involving the analysis of complex spatio-temporal patterns of electrical activity. The objectives of this project are to identify the key features of fibrillation that models should represent, to compare how well (or poorly) existing models correspond to measured values of these features, and to develop models that better represent fibrillation. The project develops and extends cell and tissue models and explores the analysis of clinical, experimental and simulation data from the perspective of regulatory science at the FDA, including verification, validation, and uncertainty quantification (VVUQ). The project seeks to 1) validate and create new models that reproduce not only single-cell dynamics, but also experimental and clinically relevant physiological dynamics in tissue and 2) initiate a new developmental framework that the FDA can use not only to test cardiac electrophysiology devices but also to characterize and verify massive submissions of therapeutic compounds obtained by computer-aided drug design methods. The research is conducted in collaboration with the Center for Devices and Radiological Health at FDA, and is aimed at developing tools that can characterize and evaluate real-world performance of devices. This will help the FDA to better regulate and verify the safety and effectiveness of devices that are developed to treat and terminate cardiac arrhythmias. All results from this project will be made freely available to the research community and to the general public.

This INSPIRE award is partially funded by the Interdisciplinary Research Program in the Division of Civil, Mechanical and Manufacturing Innovation in the Directorate for Engineering, the Computer systems Research Program in the Division of Computer and Network Systems in the Directorate for Computer and Information Science and Engineering, and the Robust Intelligence Program in the Division of Information and Intelligent Systems in the Directorate for Computer and Information Science and Engineering. Integrated circuits are produced in billion-dollar chip fabs, which require many months of processing to go from a design to a chip. The goal of this proposal is to accomplish that in an afternoon, with a table-top process. Rather than etching or depositing electronic materials, as is done today, it is based on assembling digital materials. These use a discrete set of components, reversibly joined in a discrete set of relative positions and orientations. Those attributes allow positions to be determined by the parts, errors in their placement to be detected and corrected, dissimilar materials to be joined, and them to be disassembled rather than disposed. A conducting and insulating part type will be used to replace multilayer printed circuit boards, connectors and cabling for three-dimensional interconnect, inductors and capacitors, striplines and antennas. A resistive part type will be added for producing passive components, semiconducting part types will be added for active components, and magnetic and flexural part types for electromechanical components. This project will develop prototypes of the parts, the processes to produce them, the assemblers to place them, and the software tools to design with them. The research will progress in stages of size and complexity, reproducing the history of integrated electronics. First will be the equivalent of small-scale integration, using tens of parts with a 100 micron feature size. A test case at this level of integration will be assembling a radiofrequency matching network. Then will come medium-scale integration, using hundreds of parts with a 10 micron feature size. A goal here will be assembling a ring oscillator and binary counter. Finally, large-scale integration will use thousands of parts with a 1 micron feature size, with a goal of assembling a microprocessor. Computer-controlled manufacturing has progressed from subtractive to additive processes; this research roadmap will introduce the discrete assembly and disassembly of functional digital materials, to code the construction of complete systems in an integrated process.

The objective of this project is to improve the performance of autonomous systems in dynamic environments, such as disaster recovery, by integrating perception, planning paradigms, learning, and databases. For the next generation of autonomous systems to be truly effective in terms of tangible performance improvements (e.g., long-term operations, complex and rapidly changing environments), a new level of intelligence must be attained. This project improves the state of robotic systems by enhancing their ability to coordinate activities (such as searching a disaster zone), recognize objects or people, account for uncertainty, and "most important" learn, so the system's performance is continuously improving. To do this, the project takes an interdisciplinary approach to developing techniques in core areas and at the interface of perception, planning, learning, and databases to achieve robustness. This project seeks to significantly improve the performance of cyber-physical systems for time-critical applications such as disaster monitoring, search and rescue, autonomous navigation, and security and surveillance. It enables the development of techniques and tools to augment all decision making processes and applications which are characterized by continuously changing operating conditions, missions and environments. The project contributes to education and a diverse engineering workforce by training students at the University of California, Riverside, one of the most diverse research institutions in US and an accredited Hispanic Serving Institution. Instruction and research opportunities cross traditional disciplinary boundaries, and the project serves as the basis for undergraduate capstone design projects and a new graduate course. The software and testbeds from this project will be shared with the cyber-physical system research community, industry, and end users. The project plans to present focused workshops/tutorials at major IEEE and ACM conferences. The results will be broadly disseminated through the project website. For further information see the project website at: http://vislab.ucr.edu/RESEARCH/DSLC/DSLC.php