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Recent advances in mobile devices and internet technology have led Caltrans to investigate a data collection solution that offers improved data reliability and availability at a significantly lower cost. It has been postulated that information from GPS cell phones could provide position and speed data for highways and arterials in near real time over much of the transportation network. Position and speed data provided by mobile phones or other GPS enabled devices being transported in vehicles is normally referred to as probe data. The Mobile Millennium project was established to...

This article presents a dual splitting technique for a class of strongly convex optimization problems whose constraints are block-wise independent. The average-based input in the objective is the only binding element. A dual splitting strategy enables the design of distributed and privacy preserving algorithms. Theoretical convergence bounds and numerical experiments show this method successfully applies to the problem of charging electric devices so as to even out the daily energy demand in California. The solution we provide is a privacy enforced algorithm readily implementable in a...

We develop reinforcement learning (RL) boundary controllers to mitigate stop-and-go traffic congestion on a freeway segment. The traffic dynamics of the freeway segment are governed by a macroscopic Aw–Rascle–Zhang (ARZ) model, consisting of 2 \times 2 quasi-linear partial differential equations (PDEs) for traffic density and velocity. The boundary stabilization of the linearized ARZ PDE model has been solved by PDE backstepping, guaranteeing spatial L² norm regulation of the traffic state to uniform density and velocity and ensuring that traffic oscillations are...

This paper develops methods for model identification of aggregated thermostatically controlled loads (TCLs) in smart grids, via partial differential equation (PDE) techniques. Control of aggregated TCLs provides a promising opportunity to mitigate the mismatch between power generation and demand, thus enhancing grid reliability and enabling renewable energy penetration. To this end, this paper focuses on developing parameter identification algorithms for a PDE-based model of aggregated TCLs. First, a two-state boundary-coupled hyperbolic PDE model for homogenous TCL populations is derived...