A Bayesian approach to jointly estimate tire radii and vehicle trajectory

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2011-10-05

Author

Özkan, Emre
Gustafsson, Fredrik

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High-precision estimation of vehicle tire radii is considered, based on measurements on individual wheel speeds and absolute position from a global navigation satellite system (GNSS). The wheel speed measurements are subject to noise with time-varying covariance that depends mainly on the road surface. The novelty lies in a Bayesian approach to estimate online the time-varying radii and noise parameters using a marginalized particle filter, where no model approximations are needed such as in previously proposed algorithms based on the extended Kalman filter. Field tests show that the absolute radius can be estimated with millimeter accuracy, while the relative wheel radius on one axle is estimated with submillimeter accuracy.

Subject Keywords

Wheels, Global Positioning System, Trajectory , Joints , Vehicles , Noise, Tires

URI

https://hdl.handle.net/11511/37463

DOI

https://doi.org/10.1109/itsc.2011.6082980

Conference Name

14th International IEEE Conference on Intelligent Transportation Systems (ITSC)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

E. Özkan and F. Gustafsson, “A Bayesian approach to jointly estimate tire radii and vehicle trajectory,” presented at the 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), Campus George Washington Univ (GWU), Washington, DC, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37463.