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Assessing the performance of coordinated predictive control strategies on urban-motorway networks
Rinaldi, Marco; Viti, Francesco
2018In IFAC-PapersOnLine, 51 (9), p. 285-290
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Keywords :
Modeling; simulation of transportation systems; model predictive control
Abstract :
[en] Coordination and integration of different traffic control policies have been of considerable interest in research in the last decades and, recently, have been object of large scale implementation trials. In the setting of peri-urban motorway systems, coordination of various kinds of controllers must however be accompanied by accurate prediction of both propagation of flows and queues in the network, as well as the users’ response in terms of route choice. In this paper, we showcase through a real-life case study how coordination and prediction are both essential when performing hybrid urban-motorway control. Simulation results of a Model Predictive Control application are compared to simpler local control approaches, and the impact of coordinated intersection control and, additionally, Ramp Metering is evaluated.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Rinaldi, Marco ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Viti, Francesco  ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
External co-authors :
no
Language :
English
Title :
Assessing the performance of coordinated predictive control strategies on urban-motorway networks
Publication date :
July 2018
Event name :
15th IFAC Symposium on Control in Transportation Systems (CTS 2018)
Event place :
Savona, Italy
Event date :
from 6-6-2018 to 8-6-2018
Audience :
International
Journal title :
IFAC-PapersOnLine
ISSN :
2405-8963
Publisher :
IFAC Secretariat, Austria
Special issue title :
IFAC-PapersOnLine
Volume :
51
Issue :
9
Pages :
285-290
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences
Funders :
University of Luxembourg - UL
Available on ORBilu :
since 26 November 2018

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