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Automotive Engineering ›› 2022, Vol. 44 ›› Issue (6): 909-918.doi: 10.19562/j.chinasae.qcgc.2022.06.013

Special Issue: 底盘&动力学&整车性能专题2022年

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Cross-Country Road Classification Method Based on Vehicle Dynamic Response Characteristics

Jian Zhao1,Yaxin Li1,Jing Tong1,Bing Zhu1(),Weixiang Wu2,Bohua Sun1,Jiayi Han1   

  1. 1.Jilin University,State Key Laboratory of Automotive Simulation and Control,Changchun  130022
    2.Shanghai E-Propulsion Auto Technology Co. ,Ltd. ,Shanghai  201804
  • Received:2022-01-14 Revised:2022-02-21 Online:2022-06-25 Published:2022-06-28
  • Contact: Bing Zhu E-mail:zhubing@jlu.edu.cn

Abstract:

Terrain classification based on vehicle dynamic response is one of the key technologies of off-road intelligent vehicles. In this paper, a method of off-road terrain classification, combining the terrain roughness features and mechanical characteristics, is proposed, with the sand, dirt, cement and snow roads classified. In this method, the equivalent terrain profile and the vertical acceleration of vehicle body are selected as the characteristics of terrain roughness, with the driving resistance and wheel speed fluctuation as the mechanical characteristics, the cross-country road classifier is designed based on LSTM model, and the training and testing are conducted on the cross-country driving dataset of vehicle. The results show that the correct rate of terrain classification reaches 95.5%. Finally, the post-processing of classification is fulfilled by using HMM model to solve the issue of the abrupt change of continuous data, enabling the correct rate of the algorithm in terrain classification with off-road continuous data rises from 88.44% to 90.13%.

Key words: off-road terrain, terrain classification, classification post-processing, vehicle response, machine learning