Abstract
The study is intended to investigate the prevalence and severity of 13 types of driver distractions. Two types of survey, an anonymous online questionnaire and a field distribution and recycling questionnaire, have been performed to collect the data. Four hundred and four respondents contributed to the survey. Independent sample T-test and one-way ANOVA method are used to analyze the influences of driver personality traits (i.e., gender, professional, age, and driving experience) on the prevalence of driver distractions. In addition, clustering analysis method is used to the classification of driver distractions. Results indicated that the most frequent distraction was “Listening to music,” and the most dangerous distraction was “Writing text messages.” Three personality traits (professional, age, and driving experience) were found to have a significant impact on the prevalence of driver distractions. According to the influence factors, driver distractions could be divided into three categories: low, middle, and high. The multiple resource theory was used to explain the rationality of categories in the view of cognition. The results could contribute to the drivers’ subjective perceptions of each driver distraction and offer the basis for the further research on driver distraction and road safety.
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Zhang, H., Qian, DL., Shao, CF., Qian, ZW., Mi, XY. (2018). Analyzing the Influences of Driver Distractions Based on Driver’s Subjective Cognition. In: Wang, W., Bengler, K., Jiang, X. (eds) Green Intelligent Transportation Systems. GITSS 2016. Lecture Notes in Electrical Engineering, vol 419. Springer, Singapore. https://doi.org/10.1007/978-981-10-3551-7_21
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DOI: https://doi.org/10.1007/978-981-10-3551-7_21
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