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New Method of road surface identification in Anti-Lock Braking System

Journal of Beijing Institute of Technology 2005年第1期14卷 67-70页

作者：齐志权刘昭度张景波马岳峰 School of Mechanical and Vehicular Engineering Beijing Institute of Technology Beijing100081 China School

Based on the vehicle-road dynamic model, the road characteristic parameter, which depends on different types of road surfaces, is introduced and a new method of road surface identification for automotive anti-lock braking system (ABS) is proposed. According to the characteristics of vehicle-road dynamic model, a simple math resolution method of the model's factors is established. Only using the information of wheel speed, the vehicle reference velocity and the wheel slip ratio are estimated real-timely. And based on the wheel dynamic model, the road characteristic parameter is determined to identify the road surface for the determination of thresholds of ABS regulative parameters. With this new method, the road surface identification can be accurately obtained and calculation time is short that it can meet the ABS real time control need, and it also improves the performance of ABS.

关键词： vehicle-road dynamic model road surface identification anti-lock braking system

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Robust identification of road surface Condition Based on Ego‑Vehicle Trajectory Reckoning

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Automotive Innovation 2022年第4期5卷 376-387页

作者： Cheng Tian Bo Leng Xinchen Hou Yuyao Huang Wenrui Zhao Da Jin Lu Xiong Junqiao Zhao School of Automotive Studies Tongji UniversityShanghaiChina College of Electronic and Information Engineering Tongji UniversityShanghaiChina

The type of road surface condition(RSC)will directly affect the driving performance of *** the type of RSC is essential for both transportation agencies and individual ***,most existing methods are solely based on a dynamics-based method or an image-based method,which is susceptible to road excitation limitations and interference from the external ***,this paper proposes a decision-level fusion identification framework of the RSC based on ego-vehicle trajectory reckoning to accurately obtain the type of RSC that the front wheels of the vehicle will ***,a road feature extraction model based on multi-task learning is conducted,which can simultaneously segment the drivable area and road cast ***,the optimized candidate regions of interest are classified with confidence levels by *** environmental interference,candidate regions of interest regarded as virtual sensors are fused by improved Dempster-Shafer evidence theory to obtain the fusion ***,the ego-vehicle trajectory reckoning module based on the kinematic bicycle model is added to the proposed fusion method to extract the RSC experienced by the front *** performance of the entire framework is verified on a specific dataset with shadow and split curve *** results reveal that the proposed method can identify the RSC with accurate predictions in real time.

关键词： road surface identification Ego-Vehicle trajectory reckoning Multi-task learning Dempster-Shafer evidence theory Autonomous vehicle

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road identification method based on angular acceleration of vehicle driving wheel

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Journal of Beijing Institute of Technology 2012年第4期21卷 466-471页

作者：李福庆刘昭度 School of Mechanical Engineering Beijing Institute of Technology

The fundamental principle of road identification by using angular acceleration of driving wheels was demonstrated in this paper. Based on the analysis of energy conversion and parameters variation during the vehicle drive slip process, the change of adhesion coefficient relative to the an- gular acceleration were theoretically studied experimentally validated. The variation shows that the change of adhesion coefficient relative to the angular acceleration and the change of slip ratio in the drive slip process have same trend-both of them exist an only optimal angular acceleration corre- sponding to the peak value of adhesion coefficient. The peak adhesion coefficient of the prototype vehicle is about 0. 14 on the ice-covered road surfaces, with the corresponding optimal angular accel- eration of about 23.5 rad/s2 and optimal slip ratio of about 9. 4%.

关键词： road surface identification adhesion coefficient angular acceleration slip ratio

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