TY - JOUR
T1 - Road classification based on SVM and vehicle body vibration
AU - Fu, Xiaoyi
AU - Zhao, Yuzhuang
N1 - Publisher Copyright:
© The Authors, published by EDP Sciences, 2021.
PY - 2021/6/11
Y1 - 2021/6/11
N2 - 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.
AB - 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.
KW - Road surface recognition
KW - Support vector machine
KW - Vehicle information
UR - http://www.scopus.com/inward/record.url?scp=85108362457&partnerID=8YFLogxK
U2 - 10.1051/e3sconf/202126801074
DO - 10.1051/e3sconf/202126801074
M3 - Conference article
AN - SCOPUS:85108362457
SN - 2267-1242
VL - 268
JO - E3S Web of Conferences
JF - E3S Web of Conferences
M1 - 01074
T2 - 2020 6th International Symposium on Vehicle Emission Supervision and Environment Protection, VESEP2020
Y2 - 25 November 2020 through 27 November 2020
ER -
