This EAGER project on Smart and Connected Communities focuses on developing new fundamental models of urban parking in order to address issues of congestion that negatively impact mobility and health. Traffic congestions are increasingly becoming bottlenecks to sustainable urban growth as infrastructures are being stretched to their limits. A significant amount-up to 40%-of all surface level traffic in urban areas stems from drivers looking for parking. This project will develop new parking management tools (algorithms for cities and apps for drivers) that allow municipalities to achieve better congestion control and enable drivers to act more efficiently. These tools are more targeted, robust and accurate than the current control scheme of only using price to influence the average occupancy rate over a city. This project will result in fundamental advances in queuing theory and mechanism design. Specifically, the models study circulating traffic at block level resolution and the role of information plays in driver decisions. The three main thrusts of the project are: 1) Develop a queue-flow network model of traffic informed by real data that captures network topology and spatio-temporal behavior. 2) Impose a game theoretic structure on the queue-flow network that captures the strategic nature of heterogeneous users. 3) Create a living lab experimental platform in collaboration with the city of Seattle and industry partners for validation of our theories. This project engages with the City of Seattle, industrial partners such as Sidewalk Labs, and undergraduate students. Seattle will provide data and the opportunities to test and validate the results developed, industrial partners will provide technical support, and students will develop mobile apps and learn how a modern smart city can be managed. If successful, this project provides a demonstration of how cities, academia, and industry can partner to conduct rigorous research that will have short-term, practical impact.