A fatigue driving detection method based on Frequency Modulated Continuous Wave radar

Zhening Dong, Meiyan Zhang, Jinwei Sun, Tianao Cao, Runqiao Liu, Qisong Wang, Danliu
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引用次数: 7

Abstract

Fatigue driving often causes serious traffic accidents and heavy casualties. In order to detect fatigue driving, the application based on driver’s physiological characteristics have been presented and investigated. However, the existing methods are usually contacting and the detection environment is singular. The accuracy under face occlusion is always low and some fatigue recognition indicators are missing. Therefore, this paper proposes a method of fatigue driving detection based on Frequency Modulated Continuous Wave (FMCW) radar. An millimeter wave(mmWave) AWR1642 radar sensor was chosen, and the platform of fatigue driving detection was designed and built. Respiration and heartbeat signals were acquired, separated and preprocessed. In addition, logistics regression was utilized in the fatigue driving judgment algorithm. Multiple indicators of heart rate frequency, respiration frequency, heart rate amplitude and respiration amplitude were fused. The results showed that the accuracy of determining driving fatigue was up to S5%. Our proposed method realizes the accurate non-contacting detection of respiration and heartbeat signals of human beings. It provides all-weather and multi-index measurement, which is suitable to most driving environments.
基于调频连续波雷达的疲劳驾驶检测方法
疲劳驾驶经常造成严重的交通事故和重大人员伤亡。为了检测疲劳驾驶,提出并研究了基于驾驶员生理特征的疲劳驾驶检测方法。然而,现有的检测方法往往是接触式的,检测环境单一。人脸遮挡下的疲劳识别准确率一直较低,缺少一些疲劳识别指标。为此,本文提出了一种基于调频连续波(FMCW)雷达的疲劳驾驶检测方法。选择毫米波(mmWave) AWR1642雷达传感器,设计并搭建了疲劳驾驶检测平台。呼吸和心跳信号采集、分离和预处理。此外,在疲劳驾驶判断算法中引入了logistic回归。融合心率频率、呼吸频率、心率幅度、呼吸幅度等多项指标。结果表明,该方法对驾驶疲劳的判定精度可达5%。该方法实现了对人体呼吸和心跳信号的精确非接触检测。它提供全天候和多指标测量,适用于大多数驾驶环境。
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