@inproceedings{7d88b33f2a9347589a97400fd2bd119b,
title = "Particle Filter for Combined Wheel-Slip and Vehicle-Motion Estimation",
abstract = "The vehicle-estimation problem is approached by fusing measurements from wheel encoders, an inertial measurement unit, and (optionally) a global positioning system in a Rao-Blackwellized particle filter. In total 14 states are estimated, including key variables in active safety systems, such as longitudinal velocity, roll angle, and wheel slip for all four wheels. The method only relies on kinematic relationships. We present experimental data for one test scenario, using a Volkswagen Golf equipped with state-of-the-art sensors for determining ground truth. We report highly promising results, even for periods of combined aggressive cornering and braking.",
keywords = "particlef filtering, nonlinear estimation, wheel slip, vehicle control",
author = "Karl Berntorp",
year = "2015",
doi = "10.1109/ACC.2015.7172186",
language = "English",
isbn = "978-1-4799-1773-0",
series = "IEEE Xplore Digital Library",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",
pages = "5414--5419",
booktitle = "2015 American Control Conference (ACC)",
address = "United States",
note = "American Control Conference, 2015, ACC 2015 ; Conference date: 01-07-2015 Through 03-07-2015",
}