A review on identification methods of road friction coefficient

2021 ◽  
Vol 15 ◽  
Author(s):  
Gengxin Qi ◽  
Xiaobin Fan ◽  
Hao Li

Background: The development of the tire/road friction coefficient measurement and estimation system has far-reaching significance for the active electronic control safety system of automobiles and is one of the core technologies for autonomous driving in the future. Objective: Estimating the road friction coefficient accurately and in real-time has become the leading research direction. Researchers have used different tools and proposed different algorithms and patents. These methods are widely used to estimate the road friction coefficient or other related parameters. This paper gives a comprehensive description of the research status in the field of road friction coefficient estimation. Method: According to the current research status of Chinese and foreign scholars in the field of road friction coefficient recognition, the recognition methods are mainly divided into two categories: Cause-based and Effect-based. Results: This literature review will discuss the existing two types of identification methods (Cause-based and Effect-based), and the applicable characteristics of each algorithm are analyzed. Conclusion: The two recognition methods are analyzed synthetically, and the development direction of road friction coefficient recognition technology is discussed.

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Chi Jin ◽  
Anson Maitland ◽  
John McPhee

Abstract In this paper, we address nonlinear moving horizon estimation (NMHE) of vehicle lateral speed, as well as the road friction coefficient, using measured signals from sensors common to modern series-production automobiles. Due to nonlinear vehicle dynamics, a standard nonlinear moving horizon formulation leads to non-convex optimization problems, and numerical optimization algorithms can be trapped in undesirable local minima, leading to incorrect solutions. To address the challenge of non-convex cost functions, we propose an estimator with a two-level hierarchy. At the high level, a grid search combined with numerical optimization aims to find reference estimates that are sufficiently close to the global optimum. The reference estimates are refined at the low level leading to high-precision solutions. Our algorithm ensures that the estimates converge to the true values for the nominal model without the need for accurate initialization. Our design is tested in simulation with both the nominal model as well as a high-fidelity model of Autonomoose, the self-driving car of the University of Waterloo.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Lei Zuo ◽  
Duo Meng ◽  
Jinqi Zhang

This paper investigates the vehicle platoon control problems, in which the road-friction coefficient is taken into consideration. In order to improve the vehicle platoon safety in various road-friction conditions, an optimal spacing policy is proposed for the vehicle platoon. In detail, an intervehicle space optimization framework is developed by using a safety cost function and the gradient decent method. In this way, the optimal intervehicle spacing headway is presented such that the vehicle can be safely driven to the desired platoon under various road-friction conditions. Then, based on the proposed optimal spacing policy, we transform this optimal spacing vehicle platoon control problem into a moving target tracking problem. An adaptive distributed integrated sliding mode (DISM)-based vehicle platoon control scheme is proposed such that the vehicles can effectively follow the presented optimal spacing platoon. Moreover, the stability of the proposed vehicle platoon system is strictly analyzed and numerical simulations are provided to verify the proposed approaches.


Author(s):  
Tetsunori Haraguchi ◽  
Ichiro Kageyama ◽  
Yukiyo Kuriyagawa ◽  
Tetsuya Kaneko ◽  
Motohiro Asai ◽  
...  

This research deals with the possibility for construction of the database on the braking friction coefficient for actual roads from the viewpoint of traffic safety especially for automated driving such as level 4 or higher. In an automated driving such levels, the controller needs to control the vehicle, but the road surface condition, especially the road friction coefficient on wet roads, snowy or icy roads, changes greatly, and in some cases, changes by almost one order. Therefore, it is necessary for the controller to constantly collect environment information such as the road friction coefficients and prepare for emergencies such as obstacle avoidance. However, at present, the measurement of the road friction coefficients is not systemically performed, and a method for accurately measuring has not been established. In order to improve this situation, this study examines a method for continuously measurement for the road friction characteristics such as μ-s characteristics.


Author(s):  
Zhuoping Yu ◽  
Renxie Zhang ◽  
Xiong Lu ◽  
Chi Jin ◽  
Kai Sun

A robust adaptive anti-slip regulation controller which consists of two components, namely a road friction coefficient estimator and a wheel dynamics controller, is designed for distributed-drive electric vehicles. The road friction coefficient estimator is based on the latest non-affine parameter estimation theory to achieve the peak road friction coefficient. Also, working conditions for the road friction coefficient estimator are proposed to avoid the estimation error caused by a small slip ratio. According to the results of the road friction coefficient estimator, the desired reference slip ratio is obtained and the key parameters of the robust adaptive anti-slip regulation controller are modified to make sure that the road conditions can be made full use of. Then, according to the desired reference slip ratio, a state feedback control law with a conditional integrator is designed on the basis of the Lyapunov stability theory for a wheel dynamics controller by analysis of the non-linear characteristics of the tyres and the driver’s intended driving torque and constraints from the ground–tyre adhesion. In addition, it achieves smooth switching between optimal driving and the driver’s intended driving torque rather than normal switching logic. Multi-condition simulations and experiments show that the controller is adaptive to different road conditions, can improve the driving efficiency of the vehicle and can ensure stability of the vehicle. Finally, with comparative experiments, the distributed-drive electric vehicle with a robust adaptive anti-slip regulation controller proves to be more efficient than the traditional vehicle with a traditional anti-slip regulation controller.


Author(s):  
Gurkan Erdogan ◽  
Lee Alexander ◽  
Rajesh Rajamani

This paper focuses on the development and experimental evaluation of a novel adaptive feedforward vibration cancellation based friction estimation system. The friction estimation utilizes a small instrumented redundant wheel on the vehicle. Unlike other systems previously documented in literature, the developed system can provide a continuous measurement of the friction coefficient under all vehicle maneuvers, even when the longitudinal and lateral accelerations are both zero. A key challenge in the development of the estimation system is the need to remove the influence of vibrations and the influence of vehicle maneuvers from the measured signal of a force sensor. An adaptive feedforward algorithm based on the use of accelerometer signals as reference inputs is developed. The parameters of the feedforward model estimated by the adaptive algorithm themselves serve to determine the value of the friction coefficient. Detailed experimental results are presented on a skid pad wherein the road surface changes from dry asphalt to ice.


Author(s):  
L Li ◽  
J Song ◽  
H-Z Li ◽  
D-S Shan ◽  
L Kong ◽  
...  

The contact friction characteristic between a tyre and the road is a key factor that dominates the dynamics performance of a vehicle under critical conditions. Vehicle dynamics control systems, such as anti-lock braking systems, traction control systems, and electronic stability control systems (e.g. Elektronisches Stabilitäts Programm (ESP)), need an accurate road friction coefficient to adjust the control mode. No time delay in the estimation of road friction should be allowed, thereby avoiding the disappearance of the optimal control point. A comprehensive method to predict the road friction is suggested on the basis of the sensor fusion method, which is suitable for variations in the vehicle dynamics characteristics and the control modes. The multi-sensor signal fusion method is used to predict the road friction coefficient for a steering manoeuvre without braking; if active braking is involved, simplified models of the braking pressure and tyre force are adopted to predict the road friction coefficient and, when high-intensity braking is being considered, the neural network based on the optimal distribution method of the decay power is applied to predict the road friction coefficient. The method is validated through a ground test under complicated manoeuvre conditions. It was verified that the comprehensive method predicts the road friction coefficient promptly and accurately.


2021 ◽  
Vol 9 ◽  
Author(s):  
Jing Miao ◽  
Yifan Dai ◽  
Ou Xie ◽  
Hao Chen ◽  
Fuzhou Niu ◽  
...  

Recently, more and more research has been conducted to develop Connected Autonomous Vehicles (CAVs) applications that ensures the safety driving of CAVs under some extreme situations. This brief presents a robust control strategy for CAVs to preserve a precise tracking performance and maintain the stability of lateral dynamics when passing a sharp curve with uncertain road friction coefficient changes. In the proposed robust lateral dynamics control, robust optimization-based lateral dynamics controller is designed to achieve the stability of the lateral dynamics with the consideration of the road friction coefficient uncertainty. Simulation validations are carried out to evaluate the proposed control strategy. The results show that the robust optimization-based lateral dynamics can improve the robustness even with the uncertainty of the road friction coefficient.


2011 ◽  
Vol 243-249 ◽  
pp. 4441-4446
Author(s):  
Qing Feng Lin ◽  
Guang Quan Lu

In order to analyze the characteristic of cyclist throw distances and head injuries in car to electric-bicycle side impact accidents, this paper presents an approach to reconstruct the car to electric-bicycle side impact accident using PC-Crash. The distribution characteristic of cyclist head impact points with the hood and windshield is analyzed and the relationships between the vehicle impact velocities and the cyclist’s head injuries are described. In addition, based on several factors including road friction coefficient, vehicle load and braking deceleration, we analyzed the relationships between the vehicle impact velocities and the cyclist throw distances. The results show that 50km/h can be regarded approximately as the threshold of impact velocity to cause the cyclist’s head injuries, meanwhile, the cyclist throw distance is less influenced by the road friction coefficient and vehicle load, and the cyclist throw distance might be larger under lower impact velocities and smaller deceleration conditions.


Author(s):  
Kanwar B. Singh ◽  
Mustafa Ali Arat ◽  
Saied Taheri

The contact between the tire and the road is the key enabler of vehicle acceleration, deceleration and steering. However, due to changes to the road conditions, the driver's ability to maintain a stable vehicle may be at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road friction coefficient is available. Existing tire-road friction estimation approaches often require certain levels of vehicle longitudinal and/or lateral motion to satisfy the persistence of excitation condition for reliable estimations. Such excitations may undesirably interfere with vehicle motion controls. This paper presents a novel development and implementation of a real-time tire-road contact parameter estimation methodology using acceleration signals from an intelligent tire. The proposed method characterizes the terrain using the measured frequency response of the tire vibrations and provides the capability to estimate the tire road friction coefficient under extremely lower levels of force utilization. Under higher levels of force excitation (high slip conditions), the increased vibration levels due to the stick/slip phenomenon linked to the tread block vibration modes make the proposed tire vibrations based method unsuitable. Therefore for high slip conditions, a brush model-based nonlinear least squares (NLLS) parameter estimation approach is proposed. Hence an integrated approach using the intelligent tire based friction estimator and the model based estimator gives us the capability to reliably estimate friction for a wider range of excitations. Considering the strong interdependence between the operating road surface condition and the instantaneous forces and moments generated; this real time estimate of the tire-road friction coefficient is expected to play a pivotal role in improving the performance of a number of vehicle control systems. In particular, this paper focuses on the possibility of enhancing the performance of the ABS control systems. In order to achieve the aforementioned objectives, the design and implementation of a fuzzy/sliding mode/proportional integral (fuzzy-SMC-PI (FSP)) control methodology is proposed. The results show significant improvements in the stopping distance of a vehicle equipped with an intelligent tire based FSP controller as compared to a vehicle equipped with a standard ABS.


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