Magnetic markers are used as position reference devices for vehicles in AHS (Automated Highway Systems). There is a trade-off problem between the accuracy of markers and the construction cost. Lateral deviations measured on a vehicle include position errors of the markers. This paper describes the method of reducing the position measurement errors by use of Kalman filter. Disturbance observer is added to Kalman filter in order that the algorithm may have robustness against input errors and model errors. The effect of this method is confirmed by simulation and experiment. In this paper Kalman filter with disturbance observer is proposed to be used for estimation systems of vehicle position in AHS environment. Kalman filter reduces the error of measured noise and disturbance observer improves the robustness against input and model error. The conclusions of this paper is as follows: (1) It is clarified that the Kalman filter algorithm with disturbance observer can efficiently reduce the measurement errors of lateral deviations of a vehicle. For example the measurement errors can be reduced to under 60 % if the interval of markers is 1 m. (2) If yaw rate can be observed, the accuracy of measurement is improved. (3) The relationship between interval of markers and the estimation errors of lateral deviation is clarified.
Estimation system for vehicle position by use of Kalman filter and disturbance observer
Schätzung der Fahrzeugposition zum automatischen Autobahnfahren mit Hilfe von Kalman-Filtern
1998
6 Seiten, 13 Bilder, 2 Tabellen, 6 Quellen
Conference paper
English
Estimation System for Vehicle Position by Use of Kalman Filter and Disturbance Observer
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