Title :
Particle filter for combined wheel-slip and vehicle-motion estimation
Author_Institution :
Mitsubishi Electr. Res. Labs., Cambridge, MA, USA
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 :
Global Positioning System; automobiles; braking; inertial systems; motion control; particle filtering (numerical methods); wheels; Rao-Blackwellized particle filter; Volkswagen Golf; active safety systems; aggressive cornering; braking; combined wheel-slip; global positioning system; inertial measurement unit; kinematic relationships; longitudinal velocity; roll angle; state-of-the-art sensors; vehicle-estimation problem; vehicle-motion estimation; wheel encoders; wheel slip; Acceleration; Estimation; Global Positioning System; Sensors; Vehicles; Velocity measurement; Wheels;
Conference_Titel :
American Control Conference (ACC), 2015
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4799-8685-9
DOI :
10.1109/ACC.2015.7172186