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Highway traffic state estimation with mixed connected and conventional vehicles

Bekiaris-Liberis Nikolaos, Roncoli Claudio, Papageorgiou Markos

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URIhttp://purl.tuc.gr/dl/dias/2B91921D-1DBB-494E-8BBC-8D8F2608086A-
Identifierhttps://doi.org/10.1016/j.ifacol.2016.07.052-
Languageen-
Extent6 pagesen
TitleHighway traffic state estimation with mixed connected and conventional vehiclesen
CreatorBekiaris-Liberis Nikolaosen
CreatorΜπεκιαρης-Λυμπερης Νικολαοςel
CreatorRoncoli Claudioen
CreatorRoncoli Claudioel
CreatorPapageorgiou Markosen
CreatorΠαπαγεωργιου Μαρκοςel
PublisherInternational Federation of Automatic Controlen
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 macroscopic model-based approach for estimation of the traffic state, specifically of the (total) density and flow of vehicles, is developed for the case of “mixed” traffic, i.e., traffic comprising both ordinary and connected vehicles. The development relies on the following realistic assumptions: (i) The density and flow of connected vehicles are known at the (local or central) traffic monitoring and control unit on the basis of their regularly reported positions; and (ii) the average speed of conventional vehicles is roughly equal to the average speed of connected vehicles. Thus, complete traffic state estimation (for arbitrarily selected segments in the network) may be achieved by merely estimating the percentage of connected vehicles with respect to the total number of vehicles. A model is derived, which describes the dynamics of the percentage of connected vehicles, utilizing only wellknown conservation law equations that describe the dynamics of the density of connected vehicles and of the total density of all vehicles. Based on this model, which is a linear parameter-varying system, an estimation algorithm for the percentage of connected vehicles is developed employing a Kalman filter. The estimation methodology is validated through simulations, using a second-order macroscopic traffic flow model as ground truth for the traffic state, as well as using real microscopic traffic data collected within the Next Generation SIMulation (NGSIM) program.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/en
Date of Item2017-11-13-
Date of Publication2016-
SubjectHighway trafficen
SubjectVehiclesen
Bibliographic CitationN. Bekiaris-Liberis, C. Roncoli and M. Papageorgiou, "Highway traffic state estimation with mixed connected and conventional vehicles," in 14th IFAC Symposium on Control in Transportation Systems, 2016, pp. 309-314. doi: 10.1016/j.ifacol.2016.07.052 en

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