Pietro Dell'Acqua

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Traffic flow prediction is a fundamental functionality of intelligent transportation systems. After presenting the state of the art, we focus on nearest neighbor regression methods, which are data-driven algorithms that are effective yet simple to implement. We try to strengthen their efficacy in two ways that are little explored in literature, i.e., by(More)
We present a technique for dangerous curve monitoring relying on the innovative concept of Safe Driving Map (SDM), a geo-referenced database with data about safe vehicle behavior in the monitored area, also considering different weather conditions. A vehicle's data are compared with the SDM reference and the driver is warned in case of danger. A road-side(More)
It is well known that iterative algorithms for image deblurring that involve the normal equations show usually a slow convergence. A variant of the normal equations which replaces the conjugate transpose A of the system matrix A with a new matrix is proposed. This approach, which is linked with regularization preconditioning theory and reblurring processes,(More)
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