Intelligent Transportation Systems

Mobile phone based drifters offer distinct advantages over those using custom electronic circuit boards. They leverage the inexpensive and modern hardware provided by the mobile phone market to supply water resource scientists with a new solution to sensing water resources. Mobile phone based drifters strategically address in situ sensing applications in order to focus on the large scale use of mobile phones dealing with communications, software, hardware, and system reliability. We have demonstrated that a simple design of a drifter built around an Android phone robustly survives many...

This paper investigates the problem of detection and isolation of attacks on a water distribution network comprised of cascaded canal pools. The proposed approach employs a bank of delay-differential observer systems. The observers are based on an analytically approximate model of canal hydrodynamics. Each observer is insensitive to one fault/attack mode and sensitive to other modes. The design of the observers is achieved by using a delay-dependent linear matrix inequality method. The performance of our model-based diagnostic scheme is tested on a class of adversarial scenarios based on a...

This article describes the design methodology for a network of robotic Lagrangian floating sensors designed to perform real-time monitoring of water flow, environmental parameters, and bathymetry of shallow water environments (bays, estuarine, and riverine environments). Unlike previous Lagrangian sensors which passively monitor water velocity, the sensors described in this article can actively control their trajectory on the surface of the water and are capable of inter-sensor communication. The addition of these functionalities enables Lagrangian sensing in obstacle-encumbered...

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...