DocumentCode
2073277
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
fYear
2010
fDate
29-31 July 2010
Firstpage
4847
Lastpage
4850
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2010 29th Chinese
Conference_Location
Beijing
Print_ISBN
978-1-4244-6263-6
Type
conf
Filename
5572130
Link To Document