• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.65-71
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• 2011

In modem society, car are the most important transportation. Thereby, car accidents has been increasing steadily. The driver is the biggest factor of car accident. Therefor, various studies about driver (reaction time, mentality, physiological signal, age, pattern of drive) are underway. In this paper, we design a embedded system for measuring the reaction time by driving skill. The proposed system is composed of measuring brake module, OBD-2 scanner and bluetooth transmission module. Also, we implement GUI program to analyze experiment result and database to store results. Though our proposed system, we can analyze driving skill.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.70-76
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• 2022

This paper investigates the effects of age, gender, and situational factors on take-over performance in automated driving. The existing automated driving systems still consider a driver as a fallback-ready user who is receptive to take-over requests. Thus, we need to understand the impact of situations and human factors on take-over performance. 34 drivers drove on a simulated track, consisting of one baseline and four event scenarios. The data, including the brake reaction time and the standard deviation of lane position, and physiological data, including the heart rate and skin conductance, were collected. The analysis was performed using repeated-measures ANOVA. The results showed that there were significant age, gender, and situational differences in the takeover performance and mental workload. Findings from this study indicated that older drivers may face risks due to their degraded driving performance, and female drivers may have a negative experience on automated driving.