Title :
A new intelligent multi-sensor data fusion framework in AFS
Author :
Liu Junfeng ; Zeng Jun ; Cheng, K.W.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., Hong Kong, China
Abstract :
Adaptive Front-light System (AFS) is attracting more and more attentions, and plays an important role in road security improvement. This paper firstly introduces the AFS system structure and vehicle dynamics, and then presents a new hybrid multisensory data fusion framework based on neural network and Kalman filter to monitor the status of vehicle and send control signal out. The simulation shows the fusion algorithm can effectively filter the disturbance and provide the optimal signal to actuator.
Keywords :
actuators; adaptive systems; intelligent sensors; road safety; sensor fusion; vehicle dynamics; Kalman filter; actuator; adaptive front-light system; intelligent multisensor data fusion; neural network; road security improvement; vehicle dynamics; vehicle status monitoring; Adaptation model; Adaptive systems; Artificial neural networks; Electronic mail; Kalman filters; Security; Vehicles; Adaptive Front-light System Neural Network; Data Fusion; Kalman Filter; Multi-sensor;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
