Abstract
Car accidents are one of the major causes of death in modern society and driver fatigue is identified as one major risk factor. In this study, a neuro-fuzzy detecting and combating fatigue system, a possible more economical solution for detecting and combating driver fatigue, was developed. First, we surveyed and selected adaptive tendency indices (i.e. relative strength index (RSI), stochastic oscillators (KDL), and moving average convergence divergence (MACD)) based actual driving performance to predict driver fatigue and found that RSI, KDL, and MACD of vehicle speed indicated significantly different momentum before and after the occurrence of fatigue. RSI and MACD were also significant in lateral position, but were insignificant in steering wheel angle. Second, a neuro-fuzzy technology was used to integrate multi-tendency indices for exactly predicting fatigue and control alarm for combating fatigue. The experiment results showed that the neuro-fuzzy system could efficiently alert subjects for keeping concentration on traffic conditions. The alarm reducing some symptoms of fatigue is marginally significant.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of the Chinese Institute of Industrial Engineers
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
