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Traffic state estimation per lane in highways with connected vehicles

Bekiaris-Liberis Nikolaos, Roncoli Claudio, Papageorgiou Markos

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URIhttp://purl.tuc.gr/dl/dias/91FE82AD-2372-4C41-A9B6-ECF9E45B2296-
Identifierhttps://www.sciencedirect.com/science/article/pii/S2352146517309547-
Identifierhttps://doi.org/10.1016/j.trpro.2017.12.057-
Languageen-
Extent8 pagesen
TitleTraffic state estimation per lane in highways with connected vehiclesen
CreatorBekiaris-Liberis Nikolaosen
CreatorΜπεκιαρης-Λυμπερης Νικολαοςel
CreatorRoncoli Claudioen
CreatorRoncoli Claudioel
CreatorPapageorgiou Markosen
CreatorΠαπαγεωργιου Μαρκοςel
PublisherElsevieren
DescriptionThe research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. en
Content SummaryA model-based traffic state estimation approach is developed for per-lane density estimation as well as on-ramp and off-ramp flows estimation for highways in presence of connected vehicles, namely, vehicles that are capable of reporting information to an infrastructure-based system. Three are the basic ingredients of the developed estimation scheme: (1) a data-driven version of the conservation-of-vehicles equation (in its time- and space-discretized form); (2) the utilization of position and speed information from connected vehicles’ reports, as well as total flow measurements obtained from a minimum number (sufficient for the observability of the model) of fixed detectors, such as, for example, at the main entry and exit of a given highway stretch; and (3) the employment of a standard Kalman filter. The performance of the estimation scheme is evaluated for various penetration rates of connected vehicles utilizing real microscopic traffic data collected within the Next Generation SIMulation (NGSIM) program. It is shown that the estimation performance is satisfactory, in terms of a suitable metric, even for low penetration rates of connected vehicles. The sensitivity of the estimation performance to variations of the model parameters (two in total) is also quantified, and it is shown that, overall, the estimation scheme is little sensitive to the model parameters.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/en
Date of Item2018-04-16-
Date of Publication2017-
SubjectTraffic state estimationen
SubjectConnected vehiclesen
Bibliographic CitationN. Bekiaris-Liberis, C. Roncoli and M. Papageorgiou, "Traffic state estimation per lane in highways with connected vehicles," in 20th EURO Working Group on Transportation Meeting, 2017, pp. 921-928. doi: 10.1016/j.trpro.2017.12.057en

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