A Sensor and Data Fusion Algorithm for Road Grade Estimation

Abstract

Emerging driver assistance systems, such as look-ahead cruise controllers for heavy duty vehicles, require high precision digital maps. This contribution presents a road grade estimation algorithm for fusion of GPS and vehicle real-time sensor data, with measurements from previous runs over the same road segment. The resulting road grade estimate is thus enhanced using measurements from additional traversals of known roads. Distributed data fusion is utilized to ensure that the storage requirement of known roads does not increase when additional measurements are processed. The implemented algorithm, which is based on extended Kalman filtering and smoothing, is described in detail. Experiments on a Scania test vehicle show the advantages and some of the challenges with the proposed approach.

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

“…The iterative road grade estimation scheme described in this paper was first introduced in Sahlholm, Jansson, Kozica, and Johansson (2007). Initial data from the highway experiments were presented in .…”

Estimation of road roughness from data of on-vehicle mounted sensors

“…Widely used Youla-Kučera parameterization technique also known as Q-parameterization [6]; Kalman filter [18]; Extended Kalman filter [4] and etc. Mathematical algorithms require very fast processing, because it requires additional calculations and precision still unmatched by direct measurement (laser, stereo camera, etc.…”

Kalman Filtering with Uncertain Process and Measurement Noise Covariances with Application to State Estimation in Sensor Networks

“…Example 11: A Kalman filter for estimating the road grade based on uncertain GPS readings is developed and tested in [4]. The structure of the system is similar to the setup of this paper and the uncertainty of the sensor readings, correponding to the number of available satellites, is modelled by varying the measurement noise covariance.…”

“…Look-ahead driver assistance systems and control systems for improved fuel efficiency of auxiliary units are instances of currently developed technologies in heavy duty vehicles based on on-board sensors, online digitized maps, and various traffic information systems [3], [4]. As the number of these type of systems grow, the resource constraints of the CAN and the implementation complexity need to be considered in the design on the distributed estimation and control algorithms.…”