scholarly journals Handling Enhancement of Autonomous Emergency Steering for Reduced Road Friction Using Steering and Differential Braking

2021 ◽  
Vol 11 (11) ◽  
pp. 4891
Author(s):  
Yu-Min Lin ◽  
Bo-Chiuan Chen
Keyword(s):  
Friction Coefficient ◽  
Lateral Displacement ◽  
Work Load ◽  
Path Tracking ◽  
Road Surface ◽  
Steering Angle ◽  
Actuator Dynamics ◽  
Single Input Single Output ◽  
Road Friction ◽  
Road Friction Coefficient

Steering has more potential than braking to prevent rear-end collisions at higher relative velocities. A path tracking controller based on multi-input multi-output (MIMO) model predictive control (MPC) is proposed to enhance the handling performance of autonomous emergency steering in this paper. A six-state MIMO bicycle model including actuator dynamics of steering and differential braking is used for model prediction. Two control inputs are front wheel steering angle and direct yaw moment. Two model outputs are lateral displacement and heading angle. According to the work load ratios at four wheels, control allocation is used to determine the optimal braking force distribution to prevent tire force saturation. The performance of a single-input single-output (SISO) MPC that uses only steering angle control to track the lateral displacement of the desired path is employed to benchmark the performance of the proposed algorithm. Simulation results show that both SISO MPC and MIMO MPC can track the path on nominal road surface with high road friction coefficient of 0.9. For a road surface with medium road friction coefficient of 0.7, the SISO MPC is unable to track the path and loses directional stability. However, the MIMO MPC can still track the path and demonstrate robust path tracking and handling enhancement against model uncertainty due to reduced road friction.

scholarly journals Multi-sensor Fusion Road Friction Coefficient Estimation During Steering with Lyapunov Method

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3816 ◽  
Author(s):  
Letian Gao ◽  
Lu Xiong ◽  
Xuefeng Lin ◽  
Xin Xia ◽  
Wei Liu ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Autonomous Vehicles ◽  
Lateral Displacement ◽  
Kinematic Model ◽  
Nonlinear Observer ◽  
Lateral Acceleration ◽  
Double Line ◽  
The Road ◽  
Road Friction ◽  
Road Friction Coefficient

The road friction coefficient is a key parameter for autonomous vehicles and vehicle dynamic control. With the development of autonomous vehicles, increasingly, more environmental perception sensors are being installed on vehicles, which means that more information can be used to estimate the road friction coefficient. In this paper, a nonlinear observer aided by vehicle lateral displacement information for estimating the road friction coefficient is proposed. First, the tire brush model is modified to describe the tire characteristics more precisely in high friction conditions using tire test data. Then, on the basis of vehicle dynamics and a kinematic model, a nonlinear observer is designed, and the self-aligning torque of the wheel, lateral acceleration, and vehicle lateral displacement are used to estimate the road friction coefficient during steering. Finally, slalom tests and DLC (Double Line Change) tests in high friction conditions are conducted to verify the proposed estimation algorithm. Test results showed that the proposed method performs well during steering and the estimated road friction coefficient converges to the reference value rapidly.

Simulation Analyzed of Vehicle Operating Safety in Rain Weather Condition Based on ADAMS

2013 ◽  
Vol 361-363 ◽  
pp. 2057-2060
Author(s):  
Hai Lin Si
Keyword(s):  
Friction Coefficient ◽  
Model Simulation ◽  
Lateral Displacement ◽  
Weather Condition ◽  
Coupling Model ◽  
Lane Change ◽  
Vehicle Speed ◽  
Road Condition ◽  
Road Friction ◽  
Road Friction Coefficient

The safety of vehicle operating has tight relation with the road condition; vehicle operating safety accident is easy occurred in badness road condition. This paper studied the vehicle Operating Safety in rain weather condition based on Multi-Rigid Body system Automatic Dynamic Analysis of Mechanical Systems (ADAMS). The models include Vehicle model, Road model, Vehicle and Road coupling model, Simulation module were set up. By changing road friction coefficient, road conditions in sunny day, dry, and rain weather were simulated. Single lane change text and ramp steering text were carried out, and the response output of lateral displacement was obtained. Computation result indicated that in the single lane change when road friction coefficient in rain weather is 0.4, vehicle speed is 60km/h in the single line simulation; the vehicle will be easily out of control. When vehicle speed is 55 km/h, maximum steer value is 70degree in the single lane simulation, vehicle will go haywire. In the ramp steer simulation when vehicle speed is 40 km/h, vehicle will go haywire.

Estimation of the Maximum Tire-Road Friction Coefficient

2003 ◽  
Vol 125 (4) ◽  
pp. 607-617 ◽  
Author(s):  
Steffen Mu¨ller ◽  
Michael Uchanski ◽  
Karl Hedrick
Keyword(s):  
Friction Coefficient ◽  
Estimation Algorithm ◽  
Road Surface ◽  
Measurement Noise ◽  
Misclassification Rate ◽  
The Road ◽  
Subtle Effect ◽  
Road Friction ◽  
Friction Estimation ◽  
Road Friction Coefficient

We develop and test a “slip-based” method to estimate the maximum available tire-road friction during braking. The method is based on the hypothesis that the low-slip, low-μ parts of the slip curve used during normal driving can indicate the maximum tire-road friction coefficient, μmax. We find support for this hypothesis in the literature and through experiments. The friction estimation algorithm uses data from short braking maneuvers with peak accelerations of 3.9 m/s2 to classify the road surface as either dry μmax≈1 or lubricated μmax≈0.6. Significant measurement noise makes it difficult to detect the subtle effect being measured, leading to a misclassification rate of 20%.

scholarly journals Study on Pre-Warning Method of the Lateral Security of Heavy Vehicle in Deteriorative Weather

2014 ◽  
Vol 8 (1) ◽  
pp. 292-296
Author(s):  
Zhi-Guo Zhao ◽  
Min Chen ◽  
Nan Chen ◽  
Yong-Bing Zhao ◽  
Xin Chen
Keyword(s):  
Friction Coefficient ◽  
Critical Speed ◽  
Warning System ◽  
Heavy Vehicle ◽  
Heavy Vehicles ◽  
Core Technology ◽  
Road Friction ◽  
Turning Radius ◽  
Safety Features ◽  
Road Friction Coefficient

The lateral security of heavy vehicle in deteriorative weather is one of the main causes of accidents of vehicles on roads. Road safety has become a subject of great concern to institutions of higher education and scientific research institutions. There are important theoretical and practical significances to explore applicable and effective lateral safety warning methods of heavy vehicles. One of the purposes of this paper is to provide a good theoretical basis for the core technology of heavy vehicle safety features for our country's independent research and development. Aiming at the issue of lateral security of heavy vehicle for road conditions in deteriorative weather, this paper constructs the framework of the lateral security pre-warning system of heavy vehicles based on cooperative vehicle infrastructure. Moreover, it establishes vehicle lateral security statics model through analysis of the force of the car in the slope with section bending and states the parameters of vehicles for no rollover. The side slip is indexed to calculate critical speed of vehicles in a bend. This paper also analyzes the influence of road friction coefficient, the road gradient and the turning radius on the lateral security of the vehicle with critical speed on the asphalt pavement with surface conditions ranging from wet, dry, snowing or icy. The calculation results show that the bad weather road conditions, road friction coefficient and turning radius have obvious influence on the lateral security critical speed. Experimental results indicate that the critical speed error warning is within 4% and it meets the design requirements.

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