Abnormal Driving Detection With Normalized Driving Behavior Data: A Deep Learning Approach

Abnormal driving may cause serious danger to both the driver and the public. Existing detectors of abnormal driving behavior are mainly based on shallow models, which require large quantities of labeled data. The acquisition and labelling of abnormal driving data are, however, difficult, labor-inten...

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Veröffentlicht in:	IEEE transactions on vehicular technology Jg. 69; H. 7; S. 6943 - 6951
Hauptverfasser:	Hu, Jie, Zhang, Xiaoqin, Maybank, Stephen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Abnormal driving detection Acceleration Adaptation models Algorithms Biological system modeling Data models Deep learning Feature extraction Machine learning Noise reduction stacked autoencoder Vehicles
ISSN:	0018-9545, 1939-9359
Online-Zugang:	Volltext
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