DEVELOPMENT OF DRIVING FATIGUE STRAIN INDEX
Development of DFSI using Fuzzy Logic to Analyze Risk Levels of Driving Activity
Ani, Mohammad Firdaus Tokushima University
Fukumi, Minoru Tokushima University Tokushima University Educator and Researcher Directory KAKEN Search Researchers
RahayuKamat, Seri Tokushima University
Minhat, Mohamad Universiti Teknikal Malaysia Melaka
Husain, Kalthom International Islamic University College Selangor
The objective of this study is to develop a Driving Fatigue Strain Index using fuzzy logic to analyze the risk levels of driving activity among road users. Driving fatigue is always related to the driving activity and has been identified as one of the vital contributors to the road accidents and fatalities in Malaysia. Therefore, the present paper introduces the use of fuzzy logic for the development of strain index to provide the systematic analysis and propose an appropriate solution in minimizing the number of road accidents and fatalities. The development of strain index is based on the six risk factors associated with driving fatigue; muscle activity, heart rate, hand grip pressure force, seat pressure distribution, whole-body vibration, and driving duration. The data is collected for all the risk factors and consequently, the three conditions or risk levels are defined as “safe”, “slightly unsafe”, and “unsafe”. A membership function is defined for each fuzzy conditions. IF-THEN rules were used to define the input and output variables which correspond to physical measures. This index is a reliable advisory tool for providing analysis and solutions to driving fatigue problem, which constitutes the first effort toward the minimization of road accidents and fatalities.
IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING
Institute of Electrical Engineers of Japan|John Wiley & Sons
This is the peer reviewed version of the following article: Ani, M. F., Fukumi, M. , RahayuKamat, S. , Minhat, M. and Husain, K. (2019), Development of driving fatigue strain index using fuzzy logic to analyze risk levels of driving activity. IEEJ Trans Elec Electron Eng, 14: 1764-1771, which has been published in final form at https://doi.org/10.1002/tee.23002. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
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