4.6 Article Proceedings Paper

Drowsiness and distraction while driving: A study based on smartphone app data

期刊

JOURNAL OF SAFETY RESEARCH
卷 72, 期 -, 页码 279-285

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jsr.2019.12.024

关键词

Drowsiness; Distraction; Alerts; Smartphone app; Risk

资金

  1. FCT through national funds under the MIT Portugal Programme [MIT-EXPL/STS/0125/2017]
  2. Fundação para a Ciência e a Tecnologia [MIT-EXPL/STS/0125/2017] Funding Source: FCT

向作者/读者索取更多资源

Introduction: Due to the negative impact on road safety from driver drowsiness and distraction, several studies have been conducted, usually under driving simulator and naturalistic conditions. Nevertheless, emerging technologies offer the opportunity to explore novel data. The present study explores retrospective data, which was gathered by an app designed to monitor the driver, which is available to any driver owning a smartphone. Method: Drowsiness and distraction alerts emitted during the journey were aggregated by continuous driving (called sub-journey). The data include 273 drivers who made 634 sub-journeys. Two binary logit models were used separately to analyze the probability of a drowsiness and distraction event occurring. Variables describing the continuous driving time (subjourney time), the journey time (a set of sub-journeys), the number of breaks, the breaking duration time and the first sub-journey (categorical variable) were included. Additionally, categorical variables representing the gender and age of the drivers were also incorporated. Results: Despite the limitations of the retrospective data, interesting findings were obtained. The results indicate that the main risk factor of inattention is driving continuously (i.e., without stopping), but it is irrelevant whether the stop is long or short as well as the total time spent on the journey. The probability of distraction events occurring during the journey is higher than drowsiness events. Yet, the impact of increasing the driving time of the journey and stopping during the journey on the probability of drowsiness is higher than the probability of distraction. Additionally, this study reveals that the elderly are more prone to drowsiness. The data also include a group of drivers, who did not provide information on gender and age, who were found to be associated to drowsiness and distraction risk. Conclusions: The study shows that data gathered by an app have the potential to contribute to investigating drowsiness and distraction. Practical applications: Drivers are highly recommended to frequently stop during the journey, even for a short period of time to prevent drowsiness and distraction. (C) 2020 National Safety Council and Elsevier Ltd. All rights reserved.

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