基于机器学习的汽车智能座舱告警筛选系统

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doi：10.11835/j.issn.1000-582X.2025.08.009

关键词：机器学习技术；智能座舱告警；告警源；CNN中图分类号： 文献标志码：A 文章编号：1000-582X（2025）08-099-12

Machine learning-based intelligent cabin alert filtering system for vehicles

ZHANG Ying'，YUAN Haibing²，HE Qi3 ， JIANG Libiao4a5，CHEN Yifeng6， CHEN Qiaofang4b （1. Syncore Autotech Co.，Ltd.， Guangzhou 511400，P.R. China; 2. GAC Energy Technology Co.，LTD.，

Guangzhou 510800，P.R.China; 3.GAC Toyota Motor Co.，LTD.， Guangzhou 511455，P.R. China; 4a.School of Mechanical Engineering and Robotics; 4b. Institute of Engineering Research， Guangzhou City University of

Technology，Guangzhou 510800，P.R.China; 5.Schoolof Mechanical and Automotive Engineering，South China University of Technology ，Guangzhou 510641，P.R. China; 6. School of Vehicle Engineering， Chongqing University of Technology， Chongqing 400054，P.R. China）

Abstract：This study presents amachine learning-based intelligent cabin alert filtering system for vehicles aiming to address safety risks caused by excessive and redundant alarm sources.To overcome limitations in current systems，such as alarm redundancy and inaccurate classifications，a hybrid selection strategy is proposed that combines manual expert filtering with aconvolutional neural network （CNN）model. The system integrates operational data from various devices，applying manual heuristics to eliminate likely false signals and employing the CNN model for robust feature extraction and precise classification.Experimental results show that the CNN model achievesaclassificationaccuracyof 89.07% on the test dataset.When combined with manual filtering， the overall selection accuracy of alarm signals reaches 99.998% ，significantly surpassing the conventional VAS system （90%） ）.These results validate the proposed method’s efectiveness in filtering alarm information.Future research will focus on expanding training datasets，optimizing model parameters，and improving text preprocessing techniques to further enhance the overall system performance.

Keywords： machine learning; intelligent cabin alarms; alarm filtering; CNN

汽车是现代社会重要的交通工具，其安全性受到广泛关注。（剩余18164字）