A simulation study of vehicle localization based on the integration of GPS and vehicle model adaptation
Kichun Jo, Keonyup Chu, Myoungho Sunwoo · 한국자동차공학회 추계학술대회 및 전시회 · 2009
Global Positioning System (GPS) has been widely used for a localization system. However, the localization system based on a stand-alone GPS receiver is frequently inaccurate because of GPS outage and insufficient satellite signal. Therefore, the localization system using the stand-alone GPS has to be aided by sensor fusion technology. In this study, the vehicle localization algorithm is proposed to estimate accurate vehicle position using a vehicle model based sensor fusion algorithm. The sensor fusion algorithm is developed using a Kalman filter based on the vehicle model and GPS. In order to accurately estimate vehicle position with the Kalman filter, the vehicle model should be adapted to various driving environments. Therefore, the cornering stiffness of tires in the vehicle model is identified and adapted in real-time. The developed estimation algorithm was verified by simulation using a commercial vehicle model. The simulation results show that the estimation accuracy of the developed algorithm is accurate enough to be implemented in a vehicle for various driving conditions.