Automobile vehicles today are not only used for transportation or solely for driving to the desired destination, but can also be used for leisure. Distraction driving often result in can results in driver distractions causing road accidents. According to research studies for detecting driver distractions, which discovered weaknesses in both the comfort and privacy of drivers. In this research, full and half bridge loadcells are installed on the seat and backrest, total of 9 points to detect weight changes when changing the posture of driver. The sensor signals are analyzed using Support Vector Machine (SVM), which is Machine Learning deployed to identify 13 different poses. Measurement data taken from 20 people were analyzed with Support Vector Machine, which revealed the highest prediction certainty of 99.89 percent.
Predictions of Undesirable behaviors while driving using Support Vector Machine
2023-10-11
7534537 byte
Conference paper
Electronic Resource
English
Low-latitude storm time ionospheric predictions using support vector machines
Online Contents | 2011
|Driving Style Recognition Incorporating Risk Surrogate by Support Vector Machine
Springer Verlag | 2021
|Intersection intelligent driving method based on support vector machine and system thereof
European Patent Office | 2020
|British Library Conference Proceedings | 1999
|