Tire road friction coefficient estimation: review and research perspectives

Y Wang, J Hu, F Wang, H Dong, Y Yan, Y Ren… - Chinese Journal of …, 2022 - Springer
Many surveys on vehicle traffic safety have shown that the tire road friction coefficient
(TRFC) is correlated with the probability of an accident. The probability of road accidents …

A review of dynamic state estimation for the neighborhood system of connected vehicles

Y Wang, H Wei, L Yang, B Hu, C Lv - SAE International Journal of Vehicle …, 2023 - sae.org
Precise vehicle state and the surrounding traffic information are essential for decision-
making and dynamic control of intelligent connected vehicles. Tremendous research efforts …

Data-driven friction force prediction model for hydraulic actuators using deep neural networks

S Han, G Orzechowski, JG Kim, A Mikkola - Mechanism and Machine …, 2024 - Elsevier
Hydraulic actuators convert fluid pressure into mechanical motion. They are widely used in
many industrial and aerospace applications due to their reliability, high speed, high force …

Classification of road surfaces based on CNN architecture and tire acoustical signals

J Yoo, CH Lee, HM Jea, SK Lee, Y Yoon, J Lee… - Applied Sciences, 2022 - mdpi.com
This paper presents a novel work for classification of road surfaces using deep learning
method-based convolutional neural network (CNN) architecture. With the development of …

Nonlinear tire model approximation using machine learning for efficient model predictive control

LC Sousa, HVH Ayala - IEEE Access, 2022 - ieeexplore.ieee.org
Model Predictive Controller (MPC) is widely used as a technique for path tracking control
since it allows for dealing with system constraints and future forecasts. However, the …

Pavement friction evaluation based on vehicle dynamics and vision data using a multi-feature fusion network

Z Du, A Skar, M Pettinari, X Zhu - Transportation research …, 2023 - journals.sagepub.com
The tire–road friction coefficient is a critical evaluation index of the service performance of
roads: it governs the stopping distance, traction control, and stability of vehicles. Moreover …

Dynamic joint estimation of vehicle sideslip angle and road adhesion coefficient based on DRBF-EKF algorithm

L Shaohua, W Guiyang, Y Zekun… - Chinese Journal of …, 2022 - lxxb.cstam.org.cn
The vehicle center of mass slip angle and the road adhesion coefficient are the key
parameters required to realize the intelligence of the vehicle chassis. The vehicle's center of …

基于DRBF-EKF 算法的车辆质心侧偏角与路面附着系数动态联合估计

李韶华, 王桂洋, 杨泽坤, 王雪玮 - 力学学报, 2022 - lxxb.cstam.org.cn
车辆质心侧偏角和路面附着系数是实现车辆底盘智能化所需要的关键参数. 车辆质心侧偏角对于
提高车辆安全性和操控性至关重要, 轮胎-路面附着系数决定轮胎力的峰值 …

Mass estimation method for intelligent vehicles based on fusion of machine learning and vehicle dynamic model

Z Yu, X Hou, B Leng, Y Huang - Autonomous Intelligent Systems, 2022 - Springer
Vehicle mass is an important parameter for motion control of intelligent vehicles, but is hard
to directly measure using normal sensors. Therefore, accurate estimation of vehicle mass …

[HTML][HTML] Vehicle state and parameter estimation based on double cubature Kalman filter algorithm

Y Liu, D Cui - Journal of Vibroengineering, 2022 - extrica.com
Obtaining vehicle status in real-time and accurately during the driving process is of great
significance for active safety control of the vehicle. In response to this problem, combining a …