{"title":"A fatigue driving detection method based on Frequency Modulated Continuous Wave radar","authors":"Zhening Dong, Meiyan Zhang, Jinwei Sun, Tianao Cao, Runqiao Liu, Qisong Wang, Danliu","doi":"10.1109/ICCECE51280.2021.9342080","DOIUrl":null,"url":null,"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.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"455 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE51280.2021.9342080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.