Highway vehicle detection based on ridge-LASSO regression

Xuewei Kou; Qingguo Du; Longting Huang; Honghai Wang; Zhengying Li

doi:10.1117/12.3038530

23 August 2024 Highway vehicle detection based on ridge-LASSO regression

Xuewei Kou, Qingguo Du, Longting Huang, Honghai Wang, Zhengying Li

Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 132502S (2024) https://doi.org/10.1117/12.3038530
Event: 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Distributed acoustic sensing systems can obtain information about road vibration caused by vehicle driving vibration on highways. By characterizing the vehicle driving vibration data, a highway vehicle driving vibration detection scheme based on ridge-LASSO regression is proposed. Firstly, using the random forest's out-of-bag error criterion for vibration signal multi-feature selection, to prove the validity of the feature quantity used to characterize the highway vibration signal, and then the multi-feature quantity values of multiple measurement areas are composed into a data matrix, and then finally the ridge-LASSO regression algorithm is used to detect the vehicles travelling on the highway to obtain the vehicle's trajectory. The experiment proves that the method can effectively detect vehicles on the highway

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xuewei Kou, Qingguo Du, Longting Huang, Honghai Wang, and Zhengying Li "Highway vehicle detection based on ridge-LASSO regression", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 132502S (23 August 2024); https://doi.org/10.1117/12.3038530

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