Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition
	Yang Xing; Chen Lv; Zhaozhong Zhang; Huaji Wang; Xiaoxiang Na; Dongpu Cao; Efstathios Velenis; Fei-Yue Wang
发表期刊	IEEE Transactions on Computational Social Systems
	2017
卷号	PP 期号:99 页码:1-14
摘要	Driver decisions and behaviors regarding the surrounding traffic are critical to traffic safety. It is important for an intelligent vehicle to understand driver behavior and assist in driving tasks according to their status. In this paper, the consumer range camera Kinect is used to monitor drivers and identify driving tasks in a real vehicle. Specifically, seven common tasks performed by multiple drivers during driving are identified in this paper. The tasks include normal driving, left-, right-, and rear-mirror checking, mobile phone answering, texting using a mobile phone with one or both hands, and the setup of in-vehicle video devices. The first four tasks are considered safe driving tasks, while the other three tasks are regarded as dangerous and distracting tasks. The driver behavior signals collected from the Kinect consist of a color and depth image of the driver inside the vehicle cabin. In addition, 3-D head rotation angles and the upper body (hand and arm at both sides) joint positions are recorded. Then, the importance of these features for behavior recognition is evaluated using random forests and maximal information coefficient methods. Next, a feedforward neural network (FFNN) is used to identify the seven tasks. Finally, the model performance for task recognition is evaluated with different features (body only, head only, and combined). The final detection result for the seven driving tasks among five participants achieved an average of greater than 80% accuracy, and the FFNN tasks detector is proved to be an efficient model that can be implemented for real-time driver distraction and dangerous behavior recognition.
关键词	Driver Behavior Driver Distraction Feedforward Neural Network (Ffnn) Kinect Random Forest (Rf).
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/20268
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
推荐引用方式 GB/T 7714	Yang Xing,Chen Lv,Zhaozhong Zhang,et al. Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition[J]. IEEE Transactions on Computational Social Systems,2017,PP(99):1-14.
APA	Yang Xing.,Chen Lv.,Zhaozhong Zhang.,Huaji Wang.,Xiaoxiang Na.,...&Fei-Yue Wang.(2017).Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition.IEEE Transactions on Computational Social Systems,PP(99),1-14.
MLA	Yang Xing,et al."Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition".IEEE Transactions on Computational Social Systems PP.99(2017):1-14.

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