Novel Algorithm for Calibrating Speed-Density Model Parameters in Mesoscopic Traffic Simulator

Xiao Long Li; Wen Wu Song; Zhu Jiang

doi:10.4028/www.scientific.net/AMM.599-601.1891

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 599-601Novel Algorithm for Calibrating Speed-Density...

Novel Algorithm for Calibrating Speed-Density Model Parameters in Mesoscopic Traffic Simulator

Abstract:

This article is on the basis of the classical speed-density model which combines with the complex road traffic flow, to raise a way that using the weighted regression to calibrate speed-density model parameters in mesoscopic traffic simulator. After processing detector data, the densities are taken as the variables; locally weighted regression is used to build a nonparameter relationship for the number of the traffic flow, to calibrate the vehicle speed. The test with a huge amount of factual data shows that the methods proposed in this paper outperforms the common optimal algorithm: simplex method in the vehicles speed estimation precision, and can accurately descript the dynamic change regularity of the road traffic flow.

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Periodical:

Applied Mechanics and Materials (Volumes 599-601)

Pages:

1891-1896

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.599-601.1891

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Cite this paper

Online since:

August 2014

Authors:

Xiao Long Li*, Wen Wu Song, Zhu Jiang

Keywords:

Locally Weighted Regression, Mesoscopic Traffic Simulation, Preprocessing, Speed-Density Model

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* - Corresponding Author

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