Each commuter in the United States lost on average $818 in 2015 due to congestion. More than 66% of congestion happens on city streets. The situation is steadily getting worse as the number of cars on roads increases and is expected to double by 2050. Solving the mobility problem by building new roads is not feasible. Instead, we need to use emerging technologies such as intelligent transportation systems; connected vehicles and autonomous vehicles; and new services, e.g. car sharing, ride on demand, last mile delivery services, to improve transportation efficiency on city streets. To that end, we are developing Traffic Operating System (TOS) that utilizes the existing computation, communication and automotive technologies and facilitates the deployment of new ones. TOS will increase the throughput of the urban transportation network; reduce intersection accidents by preventing red-light running and rear end collisions; and make traffic behavior more predictable, reliable and efficient. Regions that invest in a TOS could see a return on their investment in reduced transportation network and infrastructure costs, and in enhanced business and economic growth. This project will advance research in several areas of Technology for and Engineering of Cyber-Physical System (CPS). We will develop new design, analysis, and verification tools for TOS, which will embody the scientific principles of CPS, rely on extensive use of heterogeneous sensors, large-scale data collection and processing, and will actively control the dynamics of a transportation network. We will field-test traffic estimation and prediction models using sensor measurement and signal timing data from the cities of Pasadena, Sierra Madre and Arcadia in Southern California. Field test of the combined vehicle-level and traffic-flow-level control, using actual connected vehicles and vehicle-to-infrastructure (V2I) communication with a signalized intersection, will be conducted in the transition to practice (TTP) component of our project. The synergistic combination of research activities will yield novel scientific, technological and practical engineering implementation results in the design, state estimation, forecasting and control of CPS that involve transportation flows on networks. The investigators in this project plan to develop, simulate and test, through targeted vehicle and roadway infrastructure field test experiments, a traffic operating system that organizes existing computation, communication and automotive technologies to: (1) minimize congestion by increasing traffic throughput; (2) enhance safety by reducing driver errors through the use of cooperative adaptive cruise control (CACC) strategies that significantly increase arterial traffic throughput while preserving safety; and (3) contain the cost of parking by minimizing the number of idle vehicles and the number of vehicles searching for parking. These goals are achieved through integration of traffic measurements with the traffic management on vehicle, road link and network levels, making effective use of a dynamic traffic model and simulation. The project will demonstrate how three levels of traffic control are interconnected and we will develop new simulation and control design techniques that receive each other's output as feedback signals.