Articles | Volume 13, issue 2
https://doi.org/10.5194/ms-13-735-2022
https://doi.org/10.5194/ms-13-735-2022
Research article
 | 
25 Aug 2022
Research article |  | 25 Aug 2022

A comparative study of the unscented Kalman filter and particle filter estimation methods for the measurement of the road adhesion coefficient

Gengxin Qi, Xiaobin Fan, and Hao Li

Related subject area

Subject: Dynamics and Control | Techniques and Approaches: Mathematical Modeling and Analysis
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Cited articles

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Short summary
The road adhesion coefficient is of profound significance for the vehicle active safety control system and is one of the core technologies of future autonomous driving. Based on the unscented Kalman filter (UKF) and particle filter (PF) algorithms, a road adhesion coefficient estimator is designed and simulations are carried out. To verify the feasibility and robustness of the algorithms on a real road, a hub-based motor vehicle test platform is built to complete real vehicle experiments.