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Exploiting ACC vehicles for improved traffic flow on motorways

Vandorou Foteini

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URIhttp://purl.tuc.gr/dl/dias/0311CC2D-790D-4247-AEE2-240DFBAF4E4A-
Identifierhttps://doi.org/10.26233/heallink.tuc.79098-
Languageen-
Extent66 pagesen
TitleExploiting ACC vehicles for improved traffic flow on motorwaysen
TitleΑξιοποίηση των ACC οχημάτων για την βελτίωση των κυκλοφοριακών συνθηκών σε αυτοκινητοδρόμουςel
CreatorVandorou Foteinien
CreatorΒανδωρου Φωτεινηel
Contributor [Thesis Supervisor]Papageorgiou Markosen
Contributor [Thesis Supervisor]Παπαγεωργιου Μαρκοςel
Contributor [Committee Member]Papamichail Ioannisen
Contributor [Committee Member]Παπαμιχαηλ Ιωαννηςel
Contributor [Committee Member]Nikolos Ioannisen
Contributor [Committee Member]Νικολος Ιωαννηςel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitTechnical University of Crete::School of Production Engineering and Managementen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Μηχανικών Παραγωγής και Διοίκησηςel
DescriptionDiploma thesis submitted in fulfillment of the requirements for the diploma of Production Engineering and Management at Technical University of Crete.en
Content SummaryTraffic congestion is a severe problem which has emerged due to the continuously increasing number of vehicles on motorways in many countries. In most cases, the construction of new transport infrastructure is not an option. In order to improve the traffic conditions on motorways, research has been performed on intelligent transportation systems. An aspect of these systems are Adaptive Cruise Control (ACC) Systems, which are, at present, mainly designed to increase the driving safety and comfort. This thesis presents an ACC-based traffic control strategy, which aims to adapt in real time the driving behavior of ACC-equipped vehicles to the prevailing traffic conditions so as to increase traffic flow efficiency if and where needed. The ACC system acts automatically and adjusts the vehicle’s acceleration or deceleration so as to maintain either the desired maximum speed or the desired time-gap to the leading vehicle. The proposed control concept receives real-time traffic measurements from motorway sections and suggests to the drivers, or imposes directly, appropriate values for the time gap and modified acceleration dynamics, within acceptable safety limits. It should be stressed that the strategy intervenes only when needed, i.e. only when the motorway traffic flow efficiency needs to be improved so as to avoid or mitigate congestion. While demonstrating the potential benefits that may arise by applying the proposed control concept, different ACC penetration rates are used. Microscopic simulation is applied to a real motorway stretch (Motorway A20 in The Netherlands) where recurrent traffic congestion is created under the current manual-driving conditions due to an on-ramp bottleneck. The simulation results demonstrate that for various, even low, penetration rates of ACC-vehicles, the proposed control concept improves the traffic conditions in general. Specifically, the average vehicle delay and the total fuel consumption have lower values compared to the case of only manually-driven or regular ACC-vehicles. This improvement is achieved by retarding the onset and reducing the space-time extent of the congestion in comparison to the no control case.en
Type of ItemΔιπλωματική Εργασίαel
Type of ItemDiploma Worken
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-10-11-
Date of Publication2018-
SubjectACCen
SubjectAdaptive Cruise Controlen
SubjectMotorway traffic controlen
SubjectMicroscopic simulationen
Bibliographic CitationFoteini Vandorou, "Exploiting ACC vehicles for improved traffic flow on motorways", Diploma Work, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2018en
Bibliographic CitationΦωτεινή Βανδώρου, "Αξιοποίηση των ACC οχημάτων για την βελτίωση των κυκλοφοριακών συνθηκών σε αυτοκινητοδρόμους", Διπλωματική Εργασία, Σχολή Μηχανικών Παραγωγής και Διοίκησης, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2018el

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