- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- 【Updated on June 30, 2025】Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
Development of Driving Fatigue Strain Index for Reducing Accident Risk Among Drivers
Search this article
Description
Driving has become more important as this medium being practically, faster and cheaper in connecting human from one to other places. However, in some occurrences driving activity can cause disaster or death to human in daily life as they get fatigued while driving. Driving fatigue is one of the top contributor to the road crashes. Therefore this study is to develop a driving fatigue strain index (DFSI), collaborate with Decision Support System (DSS), to quantify the risk levels caused by driving activity, and to propose an appropriate solution in minimizing the number of road accidents caused by the driving fatigue. The decision support system provide fast and systematic analysis, and solutions to minimize the risk and the number of accidents associated with driving fatigue. The development of DFSI is based on risk factors associated with driving activity such as muscle activity, heart rate, hand grip force, seat pressure distribution, whole-body vibration, and driving duration. All risk factors are assigned with multipliers, and the DFSI is the output or result of those multipliers. The development of DFSI is essential to analyze the risk factors that would contribute significantly to discomfort and fatigue associated with driving. Besides, in the future this index will have a capability to recommend alternative solutions to minimize fatigue while driving.
Journal
-
- International Journal of Electrical & Electronic Systems Research
-
International Journal of Electrical & Electronic Systems Research 12 2018-06
Universiti Teknologi MARA
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1050867133851510912
-
- NII Article ID
- 120006714435
-
- ISSN
- 19855389
-
- Text Lang
- en
-
- Article Type
- journal article
-
- Data Source
-
- IRDB
- CiNii Articles