汽车工程学报2024，Vol.14Issue(1)：49-59,11.DOI:10.3969/j.issn.2095‒1469.2024.01.05
基于ReliefF-RBF的路面不平度识别算法研究
Research on Road Roughness Recognition Algorithm Based on ReliefF-RBF
摘要
Abstract
Road surface unevenness significantly affects both the driving safety of road vehicles and their dynamic responses.However,the existing data-driven methods for road surface classification struggle to efficiently handle time-varying parameters and vehicle speeds.Meanwhile,the existing model-based road surface recognition algorithms require known and accurate vehicle models,facing the challenge of acquiring vehicle physical parameters in real-world applications.This paper proposes a novel pavement classification algorithm that begins by back-calculating the equivalent pavement profile,followed by data pre-processing.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 real-vehicle tests with different vehicle parameters and speeds.关键词
路面不平度/车辆动力学/数据驱动/加速度传感器/路面识别Key words
road roughness/vehicle dynamics/data driven/accelerometer/pavement recognition分类
交通工程引用本文复制引用
陈凯,史少阳,程姗姗,秦也辰..基于ReliefF-RBF的路面不平度识别算法研究[J].汽车工程学报,2024,14(1):49-59,11.基金项目
国家自然科学基金面上项目(52272386) （52272386）
中国汽车工程学会青年人才托举计划 （）
