Mechanical Sciences
Mechanical Sciences
Mechanical Sciences
Articles | Volume 13, issue 2
Articles | Volume 13, issue 2
https://doi.org/10.5194/ms-13-735-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ms-13-735-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 2
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

Viewed

Total article views: 1,146 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
884 225 37 1,146 23 32
  • HTML: 884
  • PDF: 225
  • XML: 37
  • Total: 1,146
  • BibTeX: 23
  • EndNote: 32
Views and downloads (calculated since 25 Aug 2022)
Cumulative views and downloads (calculated since 25 Aug 2022)

Viewed (geographical distribution)

Total article views: 1,078 (including HTML, PDF, and XML) Thereof 1,078 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
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.
Read more