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.