On the identification of LPV traffic flow model

Author

Luspay, T. ; Kulcsar, B. ; van Wingerden, J.W. ; Verhaegen, M.

Author_Institution

Syst. & Control Lab., Comput. & Autom. Res. Inst., Budapest, Hungary

fYear

2009

fDate

23-26 Aug. 2009

Firstpage

1752

Lastpage

1757

Abstract

Second order nonlinear macroscopic motorway flow model is in the focus of the paper. First, the pure nonlinear traffic flow model is transformed to an approximate Linear but Parameter Varying (LPV) state space form. Second, this paper shows the efficiency of an LPV subspace based identification algorithm in closed-loop, the Predictor Based Subspace IDentification technique for LPV systems. Comparison of the results with the traditional traffic oriented identification (nonlinear parametric solution) is given. Models are validated using real loop detector measurements.

Keywords

identification; linear parameter varying systems; road traffic; LPV subspace based identification algorithm; LPV traffic flow model identification; linear parameter varying state space form; predictor based subspace identification technique; real loop detector measurements; second order nonlinear macroscopic motorway flow model; Approximation methods; Computational modeling; Detectors; Equations; Mathematical model; Traffic control; Vectors; LPV Identification; Linear Parameter Varying (LPV) systems; freeway traffic modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 2009 European

Conference_Location

Budapest

Print_ISBN

978-3-9524173-9-3

Type

conf

Filename

7074656