Map-independent positioning of land vehicles with causative modified motion equations

Abstract

In this paper some results of the project ‘Positioning Component’ are presented, which was subject of a cooperation between the University of Stuttgart and DaimlerChrysler AG. The aim of the project was to develop a map-independent module for the autonomous positioning of vehicles within the framework of Location Based Services (LBS). The integration of the absolute position information (GPS) and the relative information (differential odometer and gyro) is realized with a central Kalman-filter. The system equations of this filter originally base on a kinematic model (constant velocity in one sampling interval). To reduce the filter’s inertia in the case of fast cornering it is necessary to modify these equations in a causative sense: the measured yawing (derived from the gyro) is used as a ‘geometrical’ correcting variable. The presented examples of filter results show different representative driving scenarios in inner urban areas with bad GPS quality and on highways. The mean errors of the estimated positions vary from approx. s _P = 1,9 m (on highways) to 3,0 m (in urban areas with dense buildings and tunnels). The accuracy and availability requirements of the car manufacturer are achieved.