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Research on Road Roughness Recognition Algorithm Based on ReliefF-RBF
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Kai CHEN1, Shaoyang SHI1, Shanshan CHENG2, Yechen QIN1
Chinese Journal of Automotive Engineering | 2024, 14(1) : 49 - 59
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Chinese Journal of Automotive Engineering | 2024, 14(1): 49-59
• System Dynamics Setion •
Research on Road Roughness Recognition Algorithm Based on ReliefF-RBF
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Kai CHEN1, Shaoyang SHI1, Shanshan CHENG2, Yechen QIN1
Affiliations
  • 1 Beijing Institute of Technology Beijing 100081 China
  • 2 Research Institute of Highway Ministry of Transport Beijing 100088 China
doi: 10.3969/j.issn.2095–1469.2024.01.05
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Road surface unevenness significantly affects both the driving safety of road vehicles and their dynamic responses. However, the existing datadriven methods for road surface classification struggle to efficiently handle timevarying parameters and vehicle speeds. Meanwhile, the existing modelbased road surface recognition algorithms require known and accurate vehicle models, facing the challenge of acquiring vehicle physical parameters in realworld applications. This paper proposes a novel pavement classification algorithm that begins by backcalculating the equivalent pavement profile, followed by data preprocessing. Subsequently, it computes time and frequency domain features for the equivalent pavement profile and response information, and key features are extracted using the ReliefF algorithm. A radial basis function neural network is used to construct a classifier for pavement grading and recognition. Finally, the robustness of the proposed algorithm is verified through simulation tests and realvehicle tests with different vehicle parameters and speeds.

road roughness  /  vehicle dynamics  /  data driven  /  accelerometer  /  pavement recognition
Kai CHEN, Shaoyang SHI, Shanshan CHENG, Yechen QIN. Research on Road Roughness Recognition Algorithm Based on ReliefF-RBF[J]. Chinese Journal of Automotive Engineering, 2024 , 14 (1) : 49 -59 . DOI: 10.3969/j.issn.2095–1469.2024.01.05
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Article Info
doi: 10.3969/j.issn.2095–1469.2024.01.05
  • Receive Date：2023-02-27
  • Online Date：2025-07-21
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History
  • Received：2023-02-27
  • Revised：2023-04-03
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    1 Beijing Institute of Technology Beijing 100081 China
    2 Research Institute of Highway Ministry of Transport Beijing 100088 China
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https://castjournals.cast.org.cn/joweb/qcgcxb/EN/10.3969/j.issn.2095–1469.2024.01.05
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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