On the identification of LPV traffic flow model

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.