Improved MobileNet V3-Based Identification Method for Road Adhesion Coefficient [PDF]
SensorsTo enable the timely adjustment of the control strategy of automobile active safety systems, enhance their capacity to adapt to complex working conditions, and improve driving safety, this paper introduces a new method for predicting road surface state ...
Binglin Li +5 more
doaj +7 more sources
Predicting road adhesion coefficient with a fusion strategy of SHAP dynamic parameters [PDF]
Scientific ReportsAccurately estimating the road adhesion coefficient is essential for ensuring vehicle driving safety. This study proposes a method that integrates a seven-degree-of-freedom vehicle model and the magic formula tire model with the eXtreme Gradient Boosting
Yi Gong +3 more
doaj +7 more sources
Road Adhesion Coefficient Estimation Based on Vehicle-Road Coordination and Deep Learning [PDF]
Journal of Advanced Transportation, 2023 Accurate estimation of the road adhesion coefficient can help drivers and vehicles perceive changes in road state effectively, reducing the occurrence of traffic crashes accordingly.
Chunjie Li +4 more
doaj +4 more sources
A road adhesion coefficient-tire cornering stiffness normalization method combining a fractional-order multi-variable gray model with a LSTM network and vehicle direct yaw-moment robust control [PDF]
Frontiers in Neurorobotics, 2023 A normalization method of road adhesion coefficient and tire cornering stiffness is proposed to provide the significant information for vehicle direct yaw-moment control (DYC) system design.
Yufeng Lian +5 more
doaj +5 more sources
Segmented Estimation of Road Adhesion Coefficient Based on Multimodal Vehicle Dynamics Fusion in a Large Steering Angle Range [PDF]
SensorsReal-time estimation of the road surface friction coefficient is crucial for vehicle dynamics control. Under large steering angles, the accuracy of existing road surface friction coefficient estimation methods is unsatisfactory due to the nonlinear ...
Haobin Jiang +3 more
doaj +4 more sources
Road adhesion coefficient estimation by multi-sensors with LM-MMSOFNN algorithm [PDF]
Advances in Mechanical Engineering, 2023 Accurate and efficient road adhesion coefficient estimation is the premise for the proper functioning of vehicle active safety control system. With the increased application of distributed drive vehicles and on-board sensors, a multi-module self ...
Guiyang Wang +3 more
doaj +4 more sources
Estimation of Road Adhesion Coefficient Based on Camber Brush Model [PDF]
World Electric Vehicle JournalElectric vehicles, with their distinct power systems, weight distribution, and power control strategies compared to traditional vehicles, influence the pressure distribution in the tire contact area, thereby affecting the estimation of road adhesion ...
Shupei Zhang +4 more
doaj +4 more sources
Road Adhesion Coefficient Estimation Based on Second‐Order Linear Extended State Observer [PDF]
Mathematical Problems in Engineering, 2023 In order to estimate different road adhesion coefficients, a new method based on the second‐order linear extended state observer is proposed to improve the active safety and driving stability of vehicles. The vehicle single‐wheel driving dynamics model and single‐wheel braking dynamics model are built with analyzing the driving and braking processes of
Jian Wang +4 more
semanticscholar +3 more sources
Vehicle State and Road Adhesion Coefficient Joint Estimation Based on High-Order Cubature Kalman Algorithm [PDF]
Applied Sciences, 2023 With regard to the rear-drive in-wheel motor vehicle, this paper studies the joint estimation method for the vehicle state and road adhesion coefficient.
Lingxiao Quan +2 more
doaj +3 more sources
A comparative study of the unscented Kalman filter and particle filter estimation methods for the measurement of the road adhesion coefficient [PDF]
Mechanical Sciences, 2022 The measurement of the road adhesion coefficient is of great significance for the vehicle active safety control system and is one of the key technologies for future autonomous driving.
G. Qi, X. Fan, H. Li
doaj +3 more sources