Three emerging technologies provide unique opportunities for denser cities throughout the developed world: vehicle sharing, electric vehicles, and autonomous systems. Bringing these technologies close together can help enable joint mobility-on-demand and urban-logistics services. This project focuses on the co-development of design and algorithms to enable new concepts that will serve this purpose. The Persuasive Electric Vehicle (PEV) is a tricycle navigating in the bike lanes. The PEV can autonomously drive itself to its next customer; it can also deliver packages to its customers who order goods online. On the algorithmic front, the project will investigate (i) provably-safe algorithms for autonomous navigation in bike lanes, and (ii) algorithms for high-performance routing and rebalancing for joint mobility on demand and urban logistics. On the design front, the project will investigate (i) the vehicle-level designs that can best embrace the relevant CPS technologies, and (ii) the system-level designs and urban planning practices that can help enable the PEV concept. The PIs will collaborate with the City of Boston and participate in the Global City Teams Challenge, where they will demonstrate the PEV concept and its potential impact on future smart cities.

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. The outcomes of the research are expected to also contribute to the safety of other cyber-physical systems with scalable configurable hierarchical structures, by developing a mathematical framework and corresponding software tools that analyze the safety and reliability of a class of systems that combine physical, mechanical and biological components with purely computational ones. The project research spans four technical areas: autonomous and human-controlled collaborative driving; scheduling computations over heterogeneous distributed computing systems; security and trust in V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) networks; and Verification & Validation of V2X systems through semi-virtual environments and scenarios. The integrating aspect of this research is the development of a distributed system calculus for Cyber-Physical Systems (CPS) that enables modeling, simulation and analysis of collaborative vehicular systems. The development of a comprehensive framework to model, analyze and test reconfiguration, hierarchical control, security and trust differentiates this research from previous attempts to address the same problem. Educational and outreach activities include integration of project research in undergraduate and graduate courses, and a summer camp at Ohio State University for high-school students through the Women in Engineering program.

Traditionally, the design of urban transit services has been based on limited sampling data collected through surveys and censuses, which are often dated and incomplete. Lacking massive online feeds from multiple transit modes makes it hard to achieve real-time equilibrium in demand and supply relationship through cyber-control, which eventually manifests into multiple urban transportation issues: (i) lengthy last-mile transit due to non-supply, (ii) prolonged waiting due to undersupply, and (iii) excessive idle mileage due to oversupply. This project addresses these issues by focusing on two types of transportation systems in metropolitan areas: (i) public bike rental sharing systems and (ii) fleet-oriented ride sharing systems. The public bike rental sharing systems are used to allow commuters to rent bikes near public transit stations for the last mile of their trips. The fleet-oriented ride sharing systems schedule a fleet of participating vehicles for ride sharing among passengers in which shared ridership reduces individual fare paid by passengers, increases the profit of taxi drivers, and can improve the availability of service. The theory and practice of transportation sharing systems have typically focused on isolated individual transportation modes. The project will collect massive multi-modal online feeds from metropolitan information infrastructure to model dynamic behaviors of transportation systems, and then utilize massive micro-level trip information to apply fine-grained real-time control to handle rapid changes in dynamic metropolitan environments. General principles and design methodologies will be designed to build multi-modal, integrated urban transportation systems. These research discoveries will be applied toward commercial applications. Long-term deployment problem of bike stations will be addressed, especially in the low-income districts, to provide suggestions on the station deployment and assessment for specific deployment plans. The project also solves the short-term bike maintenance issue to balance the usage of shared bikes to prevent quick deterioration of rental bikes, and improve availability of bike rental services in real time. This project will also study fleet-oriented ride sharing systems that decide fares based on real-time supply/demand ratio to handle dynamic metropolitan scenarios. This project will support two Ph.D. students who will receive innovation and technology translation training through close interactions with municipal governments and small-business companies. Such partnerships expedite the adoption of cutting-edge technology, evaluate research solutions in operational environments, and obtain user feedback to trigger further innovations. The project will improve the efficiency of existing transportation systems under sharing economy and ultimately the work would noticeably improve the quality of every-day life in metropolitan areas across the United States.

One of the challenges for the future cyber-physical systems is the exploration of large design spaces. Evolutionary algorithms (EAs), which embody a simplified computational model of the mutation and selection mechanisms of natural evolution, are known to be effective for design optimization. However, the traditional formulations are limited to choosing values for a predetermined set of parameters within a given fixed architecture. This project explores techniques, based on the idea of hidden genes, which enable EAs to select a variable number of components, thereby expanding the explored design space to include selection of a system's architecture. Hidden genetic optimization algorithms have a broad range of potential applications in cyber-physical systems, including automated construction systems, transportation systems, micro-grid systems, and space systems. The project integrates education with research by involving students ranging from high school through graduate school in activities commensurate with their skills, and promotes dissemination of the research results through open source distribution of algorithm implementation code and participation in the worldwide Global Trajectory Optimization Competition. Instead of using a single layer of coding to represent the variables of the system in current EAs, this project investigates adding a second layer of coding to enable hiding some of the variables, as needed, during the search for the optimal system's architecture. This genetic hiding concept is found in nature and provides a natural way of handling system architectures covering a range of different sizes in the design space. In addition, the standard mutation and selection operations in EAs will be replaced by new operations that are intended to extract the full potential of the hidden gene model. Specific applications include space mission design, microgrid optimization, and traffic network signal coordinated planning.

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 Stuxnet worm. Developing security mechanisms for such NCPSs significantly differs from traditional networked systems due to interdependence between cyber and physical subsystems (with attacks originating from either subsystem), possible cooperation between attackers or defenders, and the presence of human decision makers in the loop. The main goal of this research is to develop the necessary science and engineering tools for designing NCPS security solutions that are applicable to a broad range of application domains. This project will develop a multidisciplinary framework that weaves together principles from cybersecurity, control theory, networking and criminology. The framework will include novel security mechanisms for NCPSs founded on solid control-theoretic and related notions, analytical tools that allow incorporation of bounded human rationality in NCPS security, and experiments with real-world attack scenarios. A newly built cross-institutional NCPS simulator will be used to evaluate the proposed mechanisms in realistic environments. This research transcends specific cyber-physical systems domains and provides the necessary tools to building secure and trustworthy NCPSs. The broader impacts include a new infrastructure for NCPS research and education, training of students, new courses, and outreach events focused on under-represented student groups

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 Stuxnet worm. Developing security mechanisms for such NCPSs significantly differs from traditional networked systems due to interdependence between cyber and physical subsystems (with attacks originating from either subsystem), possible cooperation between attackers or defenders, and the presence of human decision makers in the loop. The main goal of this research is to develop the necessary science and engineering tools for designing NCPS security solutions that are applicable to a broad range of application domains. This project will develop a multidisciplinary framework that weaves together principles from cybersecurity, control theory, networking and criminology. The framework will include novel security mechanisms for NCPSs founded on solid control-theoretic and related notions, analytical tools that allow incorporation of bounded human rationality in NCPS security, and experiments with real-world attack scenarios. A newly built cross-institutional NCPS simulator will be used to evaluate the proposed mechanisms in realistic environments. This research transcends specific cyber-physical systems domains and provides the necessary tools to building secure and trustworthy NCPSs. The broader impacts include a new infrastructure for NCPS research and education, training of students, new courses, and outreach events focused on under-represented student groups.

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 Stuxnet worm. Developing security mechanisms for such NCPSs significantly differs from traditional networked systems due to interdependence between cyber and physical subsystems (with attacks originating from either subsystem), possible cooperation between attackers or defenders, and the presence of human decision makers in the loop. The main goal of this research is to develop the necessary science and engineering tools for designing NCPS security solutions that are applicable to a broad range of application domains. This project will develop a multidisciplinary framework that weaves together principles from cybersecurity, control theory, networking and criminology. The framework will include novel security mechanisms for NCPSs founded on solid control-theoretic and related notions, analytical tools that allow incorporation of bounded human rationality in NCPS security, and experiments with real-world attack scenarios. A newly built cross-institutional NCPS simulator will be used to evaluate the proposed mechanisms in realistic environments. This research transcends specific cyber-physical systems domains and provides the necessary tools to building secure and trustworthy NCPSs. The broader impacts include a new infrastructure for NCPS research and education, training of students, new courses, and outreach events focused on under-represented student groups.

Enhanced Structural Health Monitoring of Civil Infrastructure Systems by Observing and Controlling Loads using a Cyber-Physical System Framework The economic prosperity of the nation is dependent on vast networks of civil infrastructure systems. Unfortunately, large fractions of these infrastructure systems are rapidly approaching the end of their intended design lives. The national network of highway bridges is especially vulnerable to age-based deterioration as revealed by recent catastrophic bridge collapses in the United States. Two major bottlenecks currently exist that severely limit the effectiveness of existing bridge health management methods. First, the causal relationship between repeated truck loading and long-term structural deterioration is not well understood. Second, current management methods are reliant on visual inspections which only provide qualitative information regarding bridge health and introduce subjectivity in post-inspection decision making. This project aims to resolve these major bottlenecks by advancing a cyber-physical system (CPS) designed to monitor the health of highway bridges, control the loads imposed on bridges by heavy trucks, and provide visual inspectors with quantitative information for data-driven bridge health assessments. The CPS framework created will have enormous impact on the national economy by enhancing public safety while dramatically improving the cost-effectiveness of infrastructure management methods. The project will also create publically available graduate-level course curricula focused on CPS technology and engages inner-city middle-school students from underrepresented groups to prepare them to pursue careers in the science, technology, engineering, and mathematics (STEM) fields. The overarching goal of the research project is to create a scalable and robust CPS framework for the observation and control of mobile agents that asynchronously and transiently interact with a stationary physical system. While this class of problem is found throughout many engineering disciplines, the project focuses on the health management of highway bridges. The mobile agents relevant to bridge health are the trucks that load and introduce long-term damage in the bridge and inspectors who visually inspect the bridge. The task of devising a robust CPS framework will be challenged by the highly transient nature of the agents involved. Specifically, the compressed time of interaction between the truck and bridge results in tight time constraints on observation, quantification and control of the truck's loading. The project will rely on ad-hoc wireless communications to seamlessly integrate sensors embedded in the mobile agents (trucks and inspectors) with wireless sensors installed on the bridge and with servers dedicated to cloud-based analytics located on the Internet. The project will design the CPS framework to quantify in real-time truck loads based on sensor data streaming into the CPS framework. A distributed computing architecture will be created for the CPS framework to automate the decomposition of computational tasks in order to dramatically improve the speed and efficiency of the framework's data processing capabilities. Finally, the CPS framework will establish ad-hoc feedback control of the mobile agents in order to control mobile agent-stationary system interactions. In particular, feedback control of an instrumented truck allows the CPS framework to control the loads imposed on the bridge for improved health assessments. The CPS framework will be further extended to control visual inspection processes by providing inspectors with recommend inspection actions based on rigorous analysis of collected sensor data. The intellectual significance of the CPS framework is that it observes and controls truck loads on highway bridges for the first time while creating an entirely new data-driven paradigm for more accurate health assessment of infrastructure systems.

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.

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.