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Using smartphone logging to gain insight about phone use in traffic

机译:使用智能手机日志记录以获得有关交通中手机使用的洞察力

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The prevalence of mobile phone usage in traffic has been studied by road-side counting, naturalistic driving data, surveillance cameras, smartphone logging, and subjective estimates via surveys. Here, we describe a custom-made smartphone logging application along with suggestions on how future such applications should be designed. The developed application logs' start and end times of all phone interactions (mobile phone applications, incoming/outgoing phone calls and text messages, audio output, and screen activations). In addition, all movements are automatically classified into transport, cycling, walking, running, or stationary. The capabilities of the approach are demonstrated in a pilot study with 143 participants. Examples of results that can be gained from smartphone logging include prevalence in different transportation modes (here found to be 12% while driving, 4% while cycling, and 7% while walking), which apps are being used (here found to be 19% navigation, 12% talking, 12% social media, and 10% games) and on which road types (rural, urban, highway etc.). Smartphone logging was found to be an insightful complement to the other methods for assessing phone use in traffic, especially since it allows the analyses of which apps are used and where they are used, split into transportation mode and road type, all at a relatively low cost.
机译:通过调查,通过路边计数,自然主义驾驶数据,监控和主观估计来研究流量移动电话使用的普遍性。在这里,我们描述了一种定制的智能手机日志记录应用程序以及对应设计未来的建议。开发的应用程序记录所有手机交互的开始和结束时间(移动电话应用程序,传入/拨出电话和短信,音频输出和屏幕激活)。此外,所有运动都自动分为运输,骑自行车,行走,跑步或静止。该方法的能力在具有143名参与者的试点研究中证明。可以从智能手机测井中获得的结果的例子包括不同运输模式的普遍存在性(在此​​发现在驾驶时为12%,循环时为4%,步行时的7%),使用哪种应用程序(这里发现为19%导航,12%谈话,12%的社交媒体和10%的游戏)以及哪些道路类型(农村,城市,公路等)。发现智能手机日志记录是对其他方法进行评估交通中使用的其他方法的富有识别补充,特别是因为它允许分析使用哪个应用程序以及它们的使用,分为运输模式和道路类型,所有这些都是相对较低的成本。

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