{"title":"驾驶安全检测器:一种基于可穿戴的细粒度驾驶员手部位置检测技术","authors":"Huangxun Chen, Zhice Yang, Chenyu Huang, Qian Zhang","doi":"10.1109/GLOCOM.2018.8647653","DOIUrl":null,"url":null,"abstract":"This paper presents DriveSafe Inspector, a fine-grained driver hand position monitoring system, which continuously detects a driver's hand position on the steering wheel. The steering wheel is divided into twelve 30° sectors like a clock. Our system can be applied on off-the-shelf hardware and works without extra modification to vehicles. In our system, sensor readings from both a wearable and its paired smartphone are fused to infer hand posture and turning angle between static holding states. With both static holding and dynamic turning information, our system achieves fine-grained hand position prediction in the presence of diverse road conditions and inter-individual differences. The on-road evaluation shows that our system can achieve an average 91.59% hand position detection accuracy with only static information, and can be further improved to 94.63% accuracy combined with dynamic turning information.","PeriodicalId":201848,"journal":{"name":"2018 IEEE Global Communications Conference (GLOBECOM)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Drive Safe Inspector: A Wearable-Based Fine-Grained Technique for Driver Hand Position Detection\",\"authors\":\"Huangxun Chen, Zhice Yang, Chenyu Huang, Qian Zhang\",\"doi\":\"10.1109/GLOCOM.2018.8647653\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents DriveSafe Inspector, a fine-grained driver hand position monitoring system, which continuously detects a driver's hand position on the steering wheel. The steering wheel is divided into twelve 30° sectors like a clock. Our system can be applied on off-the-shelf hardware and works without extra modification to vehicles. In our system, sensor readings from both a wearable and its paired smartphone are fused to infer hand posture and turning angle between static holding states. With both static holding and dynamic turning information, our system achieves fine-grained hand position prediction in the presence of diverse road conditions and inter-individual differences. The on-road evaluation shows that our system can achieve an average 91.59% hand position detection accuracy with only static information, and can be further improved to 94.63% accuracy combined with dynamic turning information.\",\"PeriodicalId\":201848,\"journal\":{\"name\":\"2018 IEEE Global Communications Conference (GLOBECOM)\",\"volume\":\"221 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Global Communications Conference (GLOBECOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLOCOM.2018.8647653\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Global Communications Conference (GLOBECOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.2018.8647653","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Drive Safe Inspector: A Wearable-Based Fine-Grained Technique for Driver Hand Position Detection
This paper presents DriveSafe Inspector, a fine-grained driver hand position monitoring system, which continuously detects a driver's hand position on the steering wheel. The steering wheel is divided into twelve 30° sectors like a clock. Our system can be applied on off-the-shelf hardware and works without extra modification to vehicles. In our system, sensor readings from both a wearable and its paired smartphone are fused to infer hand posture and turning angle between static holding states. With both static holding and dynamic turning information, our system achieves fine-grained hand position prediction in the presence of diverse road conditions and inter-individual differences. The on-road evaluation shows that our system can achieve an average 91.59% hand position detection accuracy with only static information, and can be further improved to 94.63% accuracy combined with dynamic turning information.