Research on recognition of dangerous driving behavior based on support vector machine

Liumei Zhang; Baoyu Tan; Tianshi Liu; Jiao Li

doi:10.1117/12.2589350

27 January 2021 Research on recognition of dangerous driving behavior based on support vector machine

Liumei Zhang, Baoyu Tan, Tianshi Liu, Jiao Li

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 117201L (2021) https://doi.org/10.1117/12.2589350
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

Research on dangerous driving behavior recognition is beneficial to regulate the driving behavior of drivers. As the existing algorithms are sensitive to noise, and abnormal data often affects the process of identifying dangerous driving behaviors. This paper proposes a novel driving behavior research method. Such method establishes a driving behavior recognition model based on Support Vector Machine (SVM) and oversampling. The experimental results show that the proposed model demonstrates a higher recognition rate.

Citation Download Citation

Liumei Zhang, Baoyu Tan, Tianshi Liu, and Jiao Li "Research on recognition of dangerous driving behavior based on support vector machine", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 117201L (27 January 2021); https://doi.org/10.1117/12.2589350

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