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Profiling drivers to assess safe and eco-driving behavior - A systematic review of naturalistic driving studies

机译:分析司机评估安全和生态驾驶行为 - 对自然主义驾驶研究的系统审查

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Road accidents and vehicular emissions are two significant issues related to road transportation, affecting both human life and the environment. Prior research suggests that driver behavior is a crucial factor in the majority of road crashes and is a significant factor influencing fuel consumption and vehicle emission. Significant improvement in driving behavior can be achieved by providing feedback to drivers about their driving behavior. An increasing interest among researchers to identify risky and non-economical driving maneuvers has led to the development of driver behavior profiling, i.e., rating/categorizing drivers into different categories based on how they drive. To get an insight into different parameters and methodology adopted by researchers for categorizing drivers into different categories, this paper presents a systematic review of studies on driver behavior profiling. In the present paper, PRISMA approach was adopted to shortlist the most relevant studies for systematic review out of 1231 initial studies, which were extracted using the relevant keywords. The findings from our study suggest that the selection of parameters for profiling the driver will depend on the application of the profiling scheme, type of device used for extracting data, and importance of parameter in rating criteria. Further, the findings suggest that significant improvement in driving behavior can be achieved by providing feedback to the drivers about their driving behavior and by implementing usage-based insurance schemes. It is also suggested that future studies shall focus on using smartphone devices for the collection of driver data as smartphones are nowadays easily accessible to everyone.
机译:道路事故和车辆排放是与道路运输有关的两个重要问题,影响人类生活和环境。现有研究表明,驾驶员行为是大多数道路崩溃的重要因素,并且是影响燃料消耗和车辆排放的重要因素。通过向驱动行为提供对驱动器的反馈来实现驾驶行为的显着改善。越来越多的研究人员识别风险和非经济驾驶机动的兴趣导致了驾驶员行为分析的发展,即根据它们的驱动器如何进入不同类别的评级/分类驱动程序。本文提出了研究人员采用的研究人员采用的不同参数和方法,提出了对司机行为分析研究的系统审查。在本文中,采用PRISMA方法来遗行最相关的系统审查研究,其中1231项初始研究,用相关关键词提取。我们研究的发现表明,用于分析驱动程序的参数的选择将取决于分析方案的应用,用于提取数据的设备类型,以及参数在评级标准中的重要性。此外,该研究表明,通过向驱动程序提供对驱动行为的反馈并通过实现基于使用的保险方案,可以实现驾驶行为的显着改善。还有人建议,未来的研究将重点关注使用智能手机设备,以收集驱动程序数据,因为智能手机现在容易被每个人都可以访问。

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