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Apostolos Kotsialos
Researcher at Durham University
Publications - 63
Citations - 3831
Apostolos Kotsialos is an academic researcher from Durham University. The author has contributed to research in topics: Traffic flow & Optimal control. The author has an hindex of 22, co-authored 62 publications receiving 3444 citations. Previous affiliations of Apostolos Kotsialos include University of Crete & Technical University of Crete.
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Review of road traffic control strategies
TL;DR: In this paper, a comprehensive overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks, and route guidance, and selected application results are briefly outlined to illustrate the impact of various control actions and strategies.
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Freeway ramp metering: an overview
TL;DR: Why ramp metering can lead to a dramatic amelioration of traffic conditions on freeways and an overview of ramps metering algorithms, ranging from early fixed-time approaches to traffic-responsive regulators and to modern sophisticated nonlinear optimal control schemes are provided.
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Coordinated and integrated control of motorway networks via non-linear optimal control
TL;DR: In this article, the problem of designing integrated traffic control strategies for motorway networks with the use of ramp metering, route guidance, and motorway-to-motorway control measures is considered.
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Traffic flow modeling of large-scale motorway networks using the macroscopic modeling tool METANET
TL;DR: The macroscopic simulator METANET, involving a second-order traffic flow model as well as network-relevant extensions, is utilized and a rigorous quantitative validation procedure is applied to individual network links, and subsequently a heuristic qualitative validate procedure is employed at a network level.
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Coordinated ramp metering for freeway networks – A model-predictive hierarchical control approach
TL;DR: In this article, a nonlinear model-predictive hierarchical control approach for coordinated ramp metering of freeway networks is presented, which consists of three layers: the estimation/prediction layer, the optimization layer and the direct control layer.