摘要
Obtaining road surface information to make the vehicle run in the best condition can not only reduce energy consumption and vehicle loss, but also improve driving safety. In this paper, specific car body information was preprocessed as root mean square value, and SVM offline training was used. The recognition rate of off-road and highway can reach 98%. Compared with traditional threshold recognition, SVM has better adaptability and robustness. On the premise of keeping easy to obtain, the discrimination accuracy of the root mean square value is obviously better than the original value and the mean value.
源语言 | 英语 |
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文章编号 | 01074 |
期刊 | E3S Web of Conferences |
卷 | 268 |
DOI | |
出版状态 | 已出版 - 11 6月 2021 |
活动 | 2020 6th International Symposium on Vehicle Emission Supervision and Environment Protection, VESEP2020 - Wuhan, 中国 期限: 25 11月 2020 → 27 11月 2020 |
指纹
探究 'Road classification based on SVM and vehicle body vibration' 的科研主题。它们共同构成独一无二的指纹。引用此
Fu, X., & Zhao, Y. (2021). Road classification based on SVM and vehicle body vibration. E3S Web of Conferences, 268, 文章 01074. https://doi.org/10.1051/e3sconf/202126801074