Road grade estimation for look-ahead vehicle control using multiple measurement runs

Look-ahead cruise controllers and other advanced driver assistance systems for heavy duty vehicles require high precision digital topographic road maps. This paper presents a road grade estimation algorithm for creation of such maps based on Kalman filter fusion of vehicle sensor data and GPS positioning information. The algorithm uses data from multiple passes over the same road to improve previously stored road grade estimates. Measurement data from three test vehicles and six experiments have been used to evaluate the quality of the obtained road grade estimate compared to a known reference. The obtained final grade estimate compares favorably to one acquired from a specialized road grade measurement vehicle with a DGPS receiver and inertial measurement unit, with an average root mean square error of 0.17% grade.