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Driver's Good Postures Correction Model while Driving for Smart Vehicle Seat using Multinomial Logistic Regression
| Content Provider | Semantic Scholar |
|---|---|
| Author | Park, Heum Gi Lee, Chang-Bum |
| Copyright Year | 2019 |
| Abstract | This paper presents a driver's good postures correction model while driving for smart vehicle seat using multinomial logistic regression. The good driver’s seating postures are considered the angles for the placement of human body, the space for foot controls in vehicles, and the ranges of adjustments of the driver's seat and steering wheel. According to them, for the good postures, it has adjusted seat height, seat angle, head height, back of knees, distances of foot pedals, tilt of seat, etc. for each driver. There have been some studies on analysis for comfort vehicle driver’s seat, analysis of interface pressure of drivers, correction of good posture, effects of driving environment on the posture, and sitting strategies with seating pressure distribution. However, there are a few studies on correction model for driver’s good postures while driving using machine learning. Therefore, we suggest 1) a driver's good postures while driving in vehicle and 2) a good postures correction model for them using multinomial logistic regression. We developed the system with the Arduino board and C-type piezoelectric effect elements to get driver’s postures while driving. For the experiments using the logistic regression models, first, we collected the piezoelectric values from 55 drivers and 17 types of cars from the system, second, defined the 6 types of good postures with thresholds, and third, analyzed the postures from test data using multinomial logistic regression for the types using them. As the results, it can apply with a smart vehicle seat system and can guide the good postures correction for the bad postures while driving in real-time. Index Term— Correction of Driver’s Posture, Machine Learning, Smart Vehicle Seat, Multinomial Logistic Regression, Driver’s Good Posture |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ijens.org/Vol_19_I_03/192403-8585-IJMME-IJENS.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
