Fatigue analysis and design of a motorcycle online driver measurement tool using real-time sensors

I. A. Soenandi, Lamto Widodo, Budi Harsono, Isnia Oktavera, Vera Lusiana
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Abstract

Work fatigue is an important aspect and is very influential in determining the level of accidents, especially motorbike accidents. According to WHO, almost 30% of all deaths due to road accidents involve two- and three-wheel­ed motorized vehicles, such as motorbikes, mopeds, scooters and electric bicycles (e-bikes), and the number continues to increase. Motor­cycles dominate road deaths in many low- and middle-income countries, where nine out of ten traffic accident deaths occur among motorcyclists, as in Indonesia. However, until now, in Indonesia, there has been no monitor­ing system capable of identifying fatigue in motorbike drivers in the transportation sector. This research aims to determine fatigue patterns based on driver working hours and create a sensor system to monitor fatigue measurements in real-time to reduce the number of accidents. The research began with processing questionnaire data with Pearson correlation, which showed a close relationship between driver fatigue and driving time and a close relationship between fatigue and increased heart rate and sweating levels. From calibration tests with an error of 3% and direct measurements of working conditions, it was found that two-wheeled vehicle driver fatigue occurs after 2-3 hours of work. With a measurement system using the Box Whiskers analysis method, respondents' working conditions can also be de­ter­mined, which are divided into 4 zones, namely zone 1 (initial condition or good condition), zone 2 a declining condition, zone 3 a tired condition and zone 4 is a resting condition. Hopefully, this research will identify fati­gue zones correctly and reduce the number of accidents because it can iden­tify tired drivers so they do not have to force themselves to continue working and driving their motorbikes. As a conclusion from this research, a measure­ment system using two sensors, such as ECG and GSR can identify work fatigue zones well and is expected to reduce the number of accidents due to work fatigue.
利用实时传感器对摩托车在线驾驶员测量工具进行疲劳分析和设计
工作疲劳是一个重要方面,对决定事故,尤其是摩托车事故的程度有很大影响。根据世卫组织的数据,在所有因交通事故死亡的人中,近 30%涉及两轮和三轮机动车辆,如摩托车、轻便摩托车、滑板车和电动自行车(电动自行车),而且这一数字还在继续增加。在许多中低收入国家,摩托车在道路死亡事故中占主导地位,如在印度尼西亚,每十个交通事故死亡者中就有九个是摩托车驾驶员。然而,直到现在,印尼的交通部门还没有能够识别摩托车驾驶员疲劳的监测系统。本研究旨在根据驾驶员的工作时间确定疲劳模式,并创建一个传感器系统来实时监测疲劳测量结果,以减少事故数量。研究首先用皮尔逊相关法处理问卷数据,结果显示驾驶员疲劳与驾驶时间关系密切,疲劳与心率和出汗水平增加关系密切。通过误差为 3% 的校准测试和对工作条件的直接测量,发现两轮车驾驶员在工作 2-3 小时后就会产生疲劳。通过使用盒须分析方法的测量系统,还可以确定受访者的工作状态,并将其分为 4 个区域,即 1 区(初始状态或良好状态)、2 区为下降状态、3 区为疲劳状态和 4 区为休息状态。希望这项研究能正确识别疲劳区,减少事故数量,因为它能识别出疲劳的驾驶员,使他们不必强迫自己继续工作和驾驶摩托车。本研究的结论是,使用两个传感器(如心电图和 GSR)的测量系统可以很好地识别工作疲劳区,并有望减少因工作疲劳而导致的事故数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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