Abstract

<div class="section abstract"><div class="htmlview paragraph">Bad weather conditions such as torrential rain, heavy snow, and thick fog frequently occur worldwide. Vehicle accidents in such bad weather conditions account for a significant portion of all vehicle accidents, and the level of damage is relatively severe compared to other accidents that occur in clear weather.</div><div class="htmlview paragraph">This paper analyzes the driver's driving stability in bad weather conditions, which has such a significant meaning, in various ways through experiments on the inconvenience experienced by the driver. In this study, three levels of bad weather conditions were implemented in a driving simulator environment to evaluate driver inconvenience for six activities. Through driving experiment, quantitative bio-signals and vehicle signals were analyzed in each weather condition. The SD survey was used to assess the driver's inconvenience level for activities performed while driving and analyze the ranking of inconvenience. In the above experiment, quantitative indicators and qualitative inconvenience scores according to weather conditions showed that bad weather such as fog and rain increased driver inconvenience while driving.</div><div class="htmlview paragraph">And in order to improve this problem, it is suggested that two measures, 'simplification of switch operation' and 'improvement of the driver's visual and auditory awareness', should be applied first. It is to optimize the previously developed technology centered on the driver rather than the new development of the new technology, and there is a high possibility that the actual application of the vehicle and the inconvenience of the driver may be quickly improved.</div><div class="htmlview paragraph">Through this study, we expect that there will be meaningful results to improve driver inconvenience and increase vehicle stability before fully autonomous driving is implemented.</div></div>

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