A driving style recognition method based on SAX and bitmap

Yiying Wei; Zhicheng Li; Jianguo Zhu; Yunxiao Shen; Hui Zhang

doi:10.1117/12.2684246

1 August 2023 A driving style recognition method based on SAX and bitmap

Yiying Wei, Zhicheng Li, Jianguo Zhu, Yunxiao Shen, Hui Zhang

Author Affiliations +

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127543C (2023) https://doi.org/10.1117/12.2684246
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

In this paper, we propose a new method for driving style recognition on the basis of SAX and bitmap technology. This method converts the sensor signal into a discrete symbol sequence and uses a bitmap for feature extraction. The weight matrix is generated based on the vector space model (VSM) to characterize the driving style fingerprint. Different from the traditional driving feature representation method, we propose a new concept of using bitmap to represent driving fingerprints. Given the sensor data captured by the vehicle during natural driving, we regard driving style recognition as a time series classification task and divides it into three classifications: normal driving, aggressive driving and drowsy driving. We evaluate our proposed model on the open natural driving behavior classification dataset UAH-DriveSet. Compared with traditional classification methods, our proposed model achieves the most advanced results on UAH-DriveSet, achieving 83% and 95% F1-measure scores in motorway and secondary road, which is more than 20% higher than the closest comparison method.

Citation Download Citation

Yiying Wei, Zhicheng Li, Jianguo Zhu, Yunxiao Shen, and Hui Zhang "A driving style recognition method based on SAX and bitmap", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127543C (1 August 2023); https://doi.org/10.1117/12.2684246

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