title: A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation.
abstract: This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a "pseudo-roll angle" through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors' estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator.
authors: Mechanical Engineering Department, Universidad Carlos III de Madrid, Avda. de la Universidad 30, Madrid 28911, Spain. lvargas@ing.uc3m.es.
authors: Leandro
authors: L
authors: Vargas-Meléndez
authors: Mechanical Engineering Department, Universidad Carlos III de Madrid, Avda. de la Universidad 30, Madrid 28911, Spain. bboada@ing.uc3m.es.
authors: Beatriz L
authors: BL
authors: Boada
authors: Mechanical Engineering Department, Universidad Carlos III de Madrid, Avda. de la Universidad 30, Madrid 28911, Spain. mjboada@ing.uc3m.es.
authors: María Jesús L
authors: MJ
authors: Boada
authors: Mechanical Engineering-Engineering Mechanics Department, Michigan Tech University, 1400 Townsend Drive, Houghton 49931, Michigan, MI, USA. antonio@mtu.edu.
authors: Antonio
authors: A
authors: Gauchía
authors: Mechanical Engineering Department, Universidad Carlos III de Madrid, Avda. de la Universidad 30, Madrid 28911, Spain. vdiaz@ing.uc3m.es.
authors: Vicente
authors: V
authors: Díaz
keywords: linear Kalman filter; neural network; roll angle estimation; sensor fusion