Distracted driving detection by sensing the hand gripping of the phone

Ruxin Wang, Long Huang, Chen Wang
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引用次数: 2

Abstract

Phone usage while driving is unanimously considered a really dangerous habit due to a strong correlation with road accidents. This paper proposes a phone-use monitoring system that detects the driver's handheld phone use and eliminates the distraction at once. Specifically, the proposed system emits periodic ultrasonic pulses to sense if the phone is being held in hand or placed on support surfaces (e.g., seat and cup holder) by capturing the unique signal interference resulted from the contact object's damping, reflection and refraction. We derive the short-time Fourier transform from the microphone data to describe such impacts and develop a CNN-based binary classifier to discriminate the phone use between the handheld and the handsfree status. Additionally, we design a classification error correction filter to correct the classification errors during the monitoring. The experiments with six people, one phone and one car model show that our system achieves 99% accuracy in recognizing handheld phone-use activities.
通过感应手握手机来检测分心驾驶
开车时使用手机被普遍认为是一种非常危险的习惯,因为它与交通事故有很强的相关性。本文提出了一种手机使用监控系统,该系统可以检测驾驶员的手机使用情况,并立即消除分心。具体来说,该系统通过捕捉接触物体的阻尼、反射和折射产生的独特信号干扰,发射周期性超声波脉冲来感知手机是握在手里还是放在支撑表面(例如座椅和杯架)上。我们从麦克风数据中导出短时傅里叶变换来描述这种影响,并开发了一个基于cnn的二元分类器来区分手持和免提状态下的电话使用情况。此外,我们还设计了一个分类错误校正滤波器来校正监测过程中的分类错误。六个人、一部手机和一辆汽车模型的实验表明,该系统对手持电话使用行为的识别准确率达到99%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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