Journal article

Topology-regularized universal vector autoregression for traffic forecasting in large urban areas

Florin Schimbinschi, Luis Moreira-Matias, Xuan Nguyen Vinh, James Bailey

EXPERT SYSTEMS WITH APPLICATIONS | PERGAMON-ELSEVIER SCIENCE LTD | Published : 2017

Abstract

Autonomous vehicles are soon to become ubiquitous in large urban areas, encompassing cities, suburbs and vast highway networks. In turn, this will bring new challenges to the existing traffic management expert systems. Concurrently, urban development is causing growth, thus changing the network structures. As such, a new generation of adaptive algorithms are needed, ones that learn in real-time, capture the multivariate nonlinear spatio-temporal dependencies and are easily adaptable to new data (e.g. weather or crowdsourced data) and changes in network structure, without having to retrain and/or redeploy the entire system. We propose learning Topology-Regularized Universal Vector Autoregress..

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