Identification of Parameters in a Freeway Traffic Model
- 1 March 1976
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics
- Vol. SMC-6 (3) , 176-185
- https://doi.org/10.1109/tsmc.1976.5409233
Abstract
The methodology of discrete time, extended Kalman filtering is applied to the problem of identifying parameters of a macroscopic freeway traffic model. Macroscopic models provide a representation of traffic flow in terms of its gross properties, i.e., volume, density, and speed. The local identifiability of a parameterization of macroscopic model at nominal values of the unknown parameters is checked before any identification is attempted. It is shown that the parameterization is locally identifiable. Two parameters of the model (reaction time and sensitivity to changing density) were identified through the use of this methodology. The data base for studies to date was generated from a microscopic simulation of freeway traffic, which involves following all individual vehicle movements. Techniques for extending the methodology to employ real freeway traffic data, especially as can be obtained from automated surveillance systems, are discussed.Keywords
This publication has 4 references indexed in Scilit:
- Parameter identifiability of dynamical systemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1974
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