Title:
PAVEMENT UNEVENNESS CLASSIFICATION AND IDENTIFICATION METHOD AND APPARATUS, VEHICLE, AND STORAGE MEDIUM
Document Type and Number:
WIPO Patent Application WO/2024/051661
Kind Code:
A1
Abstract:
The present application discloses a pavement unevenness classification and identification method and apparatus, a vehicle, and a storage medium. The pavement unevenness classification and identification method comprises: acquiring at least one set of training data sequences, and according to the at least one set of training data sequences, performing at least one round of training on a preset neural network model to obtain a pavement unevenness prediction model (S110); when a vehicle is shielded by a front vehicle on a driving prediction track of the vehicle, collecting real-time pose data of the front vehicle (S120); inputting the real-time pose data into the pavement unevenness prediction model, and determining an unevenness classification and identification result matching a pavement on which the front vehicle runs (S130).
Inventors:
HONG RI (CN)
ZHANG JIAN (CN)
LIU QIUZHENG (CN)
WANG CHAO (CN)
WANG YU (CN)
XIE FEI (CN)
HAN YANING (CN)
YAN SHANXIN (CN)
LI YANG (CN)
LI YAXIN (CN)
ZHANG JIAN (CN)
LIU QIUZHENG (CN)
WANG CHAO (CN)
WANG YU (CN)
XIE FEI (CN)
HAN YANING (CN)
YAN SHANXIN (CN)
LI YANG (CN)
LI YAXIN (CN)
Application Number:
PCT/CN2023/116866
Publication Date:
March 14, 2024
Filing Date:
September 05, 2023
Export Citation:
Assignee:
CHINA FAW CO LTD (CN)
International Classes:
G01B21/30; B60W60/00
Foreign References:
| CN115451901A | 2022-12-09 | |||
| CN112896188A | 2021-06-04 | |||
| CN107977641A | 2018-05-01 | |||
| CN109050535A | 2018-12-21 | |||
| CN111290386A | 2020-06-16 | |||
| US20190344783A1 | 2019-11-14 |
Other References:
SHENGFENG GU: "Research on Neural Network Method for Recognizing Road Surface Roughness Based on Vehicle Response", ENGINEERING SCIENCE AND TECHNOLOGY II, CHINA MASTER'S THESES FULL-TEXT DATABASE, 1 June 2018 (2018-06-01), XP093147480, [retrieved on 20240403]
Attorney, Agent or Firm:
BEIJING YZH IP FIRM (CN)
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