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
Source PublicationIEEE Transactions on Computational Social Systems
2017
VolumePPIssue:99Pages:1-14
AbstractDriver 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.
KeywordDriver Behavior Driver Distraction Feedforward Neural Network (Ffnn) Kinect Random Forest (Rf).
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20268
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Recommended Citation
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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