Please use this identifier to cite or link to this item:
Title: Stima delle condizioni di deflusso del traffico stradale
Authors: Mannini, Livia
metadata.dc.contributor.advisor: Gori, Stefano
Keywords: GPS
data fusion
Issue Date: 16-Apr-2012
Publisher: Università degli studi Roma Tre
Abstract: The aim of this study is the estimation of traffic flow conditions either in urban or in freeway contests; in order to reach the objective of the research, the micro and macro simulations have been adopted as model tools, verified through specific experiments, carried out detecting measurements with operational tools, as vehicles equipped with differential GPS devices, and fixed traffic detectors, as radar technologies. These tools either, technological or methodological, are different but completing and give the opportunities to be integrated each other. The macroscopic and microscopic models have been studied and analyzed; on the basis of the results obtained during the calibration and validation of some of the existing car-following models four new microscopic models have been formulated; one of them considers the interaction between the follower vehicle and 2 leader vehicles. Then, the attention has been focalized on the fusion of data detected by two different sensor types in order to improve the traffic flow estimation. Starting from the application of the procedure reported in Wang, Papageorgiou (2005) based on the correction through the Extended Kalman Filter of the second order traffic model, also a different type of measurement has been taken into account, such as probe vehicles, which has been added to the conventional fixed ones, in order to improve the estimation process. Different data fusion techniques have been analyzed, such as the fusion of measurements and the fusion of estimations. Moreover, an application with freeway real data has been carried out in order to validate the procedure.
Access Rights: info:eu-repo/semantics/openAccess
Appears in Collections:X_Dipartimento di Scienze dell'ingegneria civile
T - Tesi di dottorato

Files in This Item:
File Description SizeFormat
Tesi di dottorato_Livia Mannini_XXIV ciclo.pdf34.77 MBAdobe PDFView/Open
SFX Query Show full item record Recommend this item

Page view(s)

Last Week
Last month
checked on Sep 26, 2020


checked on Sep 26, 2020

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.