A new intelligent multi-sensor data fusion framework in AFS

Junfeng Liu, Jun Zeng, Ka Wai Eric Cheng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

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.
Original languageEnglish
Title of host publicationProceedings of the 29th Chinese Control Conference, CCC'10
Pages4847-4850
Number of pages4
Publication statusPublished - 22 Dec 2010
Event29th Chinese Control Conference, CCC'10 - Beijing, China
Duration: 29 Jul 201031 Jul 2010

Conference

Conference29th Chinese Control Conference, CCC'10
Country/TerritoryChina
CityBeijing
Period29/07/1031/07/10

Keywords

  • Adaptive Front-light System neural network
  • Data fusion
  • Kalman filter
  • Multi-sensor

ASJC Scopus subject areas

  • Control and Systems Engineering

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