Tigran T. Tchrakian

Learn More
An algorithm for the implementation of short-term prediction of traffic with real-time updating based on spectral analysis is described. The prediction is based on the characterization of the flow based on modal functions associated with a covariance matrix constructed from historical flow data. The number of these modal functions used for prediction(More)
In this paper, we propose a new framework for macroscopic traffic state estimation based on the Fourier-Galerkin projection method and minimax state estimation approach. We assign a Fourier-Galerkin reduced model to a partial differential equation describing a macroscopic model of traffic flow. Taking into account a priori estimates for the projection(More)
We introduce a new view of parked cars as a massive, flexible resource that is currently wasted. Given the power supply in batteries as well as computing, communication, and sensing facilities in cars in conjunction with the precise localization they can provide, parked cars have the potential to serve as a service delivery platform with a wide range of(More)
In this paper, we develop a data-assimilation algorithm for a macroscopic model of traffic flow. The algorithm is based on the Discontinuous Galerkin Method and Minimax Estimation, and is applied to a macroscopic model based on a scalar conservation law. We present numerical results which demonstrate the shock-capturing capability of the algorithm under(More)
Traffic State Estimation (TSE) refers to the estimation of the state (i.e., density, speed, or other parameters) of vehicular traffic on roads based on partial observation data (e.g., road-side detectors and on-vehicle GPS devices). It can be used as a component in applications such as traffic control systems as a means to identify and alleviate congestion.(More)
In this paper, we propose an algorithm estimating parameters of a source term of a linear advection-diffusion equation with an uncertain advection-velocity field. First, we apply a minimax state estimation technique order to reduce uncertainty introduced by the coefficients. Then we design a source localization algoritm which uses the state estimator as a(More)
The Dirac-Yang monopoles are singular Yang–Mills field configurations in all Euclidean dimensions. The regular counterpart of the Dirac monopole in D = 3 is the t Hooft-Polyakov monopole, the former being simply a gauge transform of the asymptotic fields of the latter. Here, regular counterparts of Dirac-Yang monopoles in all dimensions, are described. In(More)
We obtain a state space representation of a first order macroscopic model from a Godunov discretization of its Lagrangian reformulation. The resulting model comprises four linear regimes, each of which comes into effect for the appropriate traffic conditions using a simple switching mechanism. Unlike previous state space models of traffic flow, ours is(More)