Use of speed measurements for highway traffic state estimation: case studies on NGSIM data and highway A20Use of speed measurements for highway traffic state estimation: case studies on NGSIM data and highway A20 Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2017-11-132016enThis paper presents two case studies in which a macroscopic model-based approach for the estimation of traffic conditions, which the authors have recently developed, is employed and tested. The estimation method is developed for a mixed traffic scenario, in which traffic is composed of both ordinary and connected vehicles. Only average speed measurements, which may be obtained from connected vehicle reports, and a minimal number (sufficient to guarantee observability) of spot sensor–based total flow measurements are utilized. In the first case study, NGSIM microscopic data are used to test the capability of estimating traffic conditions on the basis of aggregated information retrieved from moving vehicles and considering various penetration rates of connected vehicles. In the second case study, a longer highway stretch with internal congestion is utilized to test the capability of the proposed estimation scheme to produce appropriate estimates for varying traffic conditions on long stretches. In both cases, the performances are satisfactory and the obtained results demonstrate the effectiveness of the method in both qualitative and quantitative terms.The 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.http://creativecommons.org/licenses/by-nc-nd/4.0/Transportation Research Record: Journal of the Transportation Research Board255990-100Roncoli_et_al_TRR_2559_2016_.pdfChania [Greece]Library of TUC2017-11-13application/pdf3.5 MBfree Roncoli Claudio Roncoli Claudio Bekiaris-Liberis Nikolaos Μπεκιαρης-Λυμπερης Νικολαος Papageorgiou Markos Παπαγεωργιου Μαρκος Transportation Research Board Highway traffic state estimation