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Abnormal Road Surface Recognition Based on Smartphone Acceleration Sensor

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成果类型:
期刊论文
作者:
Du, Ronghua;Qiu, Gang;Gao, Kai*;Hu, Lin;Liu, Li
通讯作者:
Gao, Kai
作者机构:
[Qiu, Gang; Liu, Li; Hu, Lin; Du, Ronghua; Gao, Kai] Changsha Univ Sci & Technol, Coll Automot & Mech Engn, Changsha 410114, Peoples R China.
[Gao, Kai] Changsha Univ Sci & Technol, Hunan Key Lab Smart Roadway & Cooperat Vehicle In, Changsha 410114, Peoples R China.
通讯机构:
[Gao, Kai] C
Changsha Univ Sci & Technol, Coll Automot & Mech Engn, Changsha 410114, Peoples R China.
Changsha Univ Sci & Technol, Hunan Key Lab Smart Roadway & Cooperat Vehicle In, Changsha 410114, Peoples R China.
语种:
英文
关键词:
Gaussian background model;abnormal road surface;acceleration sensor;road surface recognition
期刊:
Sensors
ISSN:
1424-8220
年:
2020
卷:
20
期:
2
页码:
451
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China [61973047, 51678077, 51875049]; Science Fund for Distinguished Young Scholars of the Hunan ProvinceNational Natural Science Foundation of ChinaNational Science Fund for Distinguished Young Scholars [2019JJ20017]; Open Fund of Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems (Changsha University of Science Technology) [kfj190701]
机构署名:
本校为第一且通讯机构
院系归属:
汽车与机械工程学院
摘要:
In order to identify the abnormal road surface condition efficiently and at low cost, a road surface condition recognition method is proposed based on the vibration acceleration generated by a smartphone when the vehicle passes through the abnormal road surface. The improved Gaussian background model is used to extract the features of the abnormal pavement, and the k-nearest neighbor (kNN) algorithm is used to distinguish the abnormal pavement types, including pothole and bump. Comparing with the existing works, the influence of vehicles with different suspension characteristics on the detecti...

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