Applying embedded hybrid ANFIS/quantum-tuned BPNN prediction to collision warning system for motor vehicle safety

Bao Rong Chang, Chung Ping Young, Hsiu Fen Tsai, Jian Jr Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This study is to explore how to realize highperformance collision warning system (CWS), providing the precaution against traffic crash in transit. An embedded hybrid adaptive network-based fuzzy inference system (ANFIS) plus quantum-tuned back-propagation neural network (QT-BPNN) built in the platform with Davinci+XScale-NAV270 was employed to realize collision warning system and we also installed motor vehicle event data recorder (MVEDR). Finally, experiments and verification of the proposed approach were successfully done to achieve better accuracy and more effectiveness on warning level and event data record to motor vehicle.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
Pages3-8
Number of pages6
DOIs
Publication statusPublished - 2008
Event8th International Conference on Intelligent Systems Design and Applications, ISDA 2008 - Kaohsiung, Taiwan
Duration: 2008 Nov 262008 Nov 28

Publication series

NameProceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
Volume1

Other

Other8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
CountryTaiwan
CityKaohsiung
Period08-11-2608-11-28

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

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