scholarly journals PaTAVTT: A Hardware-in-the-Loop Scaled Platform for Testing Autonomous Vehicle Trajectory Tracking

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Zhigang Xu ◽  
Mingliang Wang ◽  
Fengzhi Zhang ◽  
Sheng Jin ◽  
Jin Zhang ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Autonomous Vehicles ◽  
Tracking Control ◽  
High Speed ◽  
Control Function ◽  
Autonomous Vehicle ◽  
Test Method ◽  
Hardware In The Loop ◽  
Positioning Device ◽  
Harsh Conditions

With the advent of autonomous vehicles, in particular its adaptability to harsh conditions, the research and development of autonomous vehicles attract significant attention by not only academia but also practitioners. Due to the high risk, high cost, and difficulty to test autonomous vehicles under harsh conditions, the hardware-in-the-loop (HIL) scaled platform has been proposed as it is a safe, inexpensive, and effective test method. This platform system consists of scaled autonomous vehicle, scaled roadway, monitoring center, transmission device, positioning device, and computers. This paper uses a case of the development process of tracking control for high-speed U-turn to build the tracking control function. Further, a simplified vehicle dynamics model and a trajectory tracking algorithm have been considered to build the simulation test. The experiment results demonstrate the effectiveness of the HIL scaled platform.

scholarly journals Robust trajectory tracking control for autonomous vehicle subject to velocity-varying and uncertain lateral disturbance

2021 ◽  
Vol 57 (1) ◽  
pp. 7-23
Author(s):  
Yuqiong Wang ◽  
Song Gao ◽  
Yuhai Wang ◽  
Pengwei Wang ◽  
Yingchao Zhou ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Autonomous Vehicles ◽  
Tracking Control ◽  
Autonomous Vehicle ◽  
Longitudinal Velocity ◽  
Lane Change ◽  
Trajectory Tracking Control ◽  
Velocity Planning ◽  
Double Lane Change ◽  
Lateral Disturbance

Autonomous vehicles are the most advanced intelligent vehicles and will play an important role in reducing traffic accidents, saving energy and reducing emission. Motion control for trajectory tracking is one of the core issues in the field of autonomous vehicle research. According to the characteristics of strong nonlinearity, uncertainty and chang-ing longitudinal velocity for autonomous vehicles at high speed steering condition, the robust trajectory tracking control is studied. Firstly, the vehicle system models are established and the novel target longitudinal velocity planning is carried out. This velocity planning method can not only ensure that the autonomous vehicle operates in a strong nonlinear coupling state in bend, but also easy to be constructed. Then, taking the lateral location deviation minimiz-ing to zero as the lateral control objective, a robust active disturbance rejection control path tracking controller is designed along with an extended state observer which can deal with the varying velocity and uncertain lateral dis-turbance effectively. Additionally, the feedforward-feedback control method is adopted to control the total tire torque, which is distributed according to the steering characteristics of the vehicle for additional yaw moment to enhance vehicle handing stability. Finally, the robustness of the proposed controller is evaluated under velocity-varying condi-tion and sudden lateral disturbance. The single-lane change maneuver and double-lane change maneuver under vary longitudinal velocity and different road adhesions are both simulated. The simulation results based on Matlab/Simulink show that the proposed controller can accurately observe the external disturbances and have good performance in trajectory tracking and handing stability. The maximum lateral error reduces by 0.18 meters compared with a vehicle that controlled by a feedback-feedforward path tracking controller in the single-lane change maneuver. The lateral deviation is still very small even in the double lane change case of abrupt curvature. It should be noted that our proposed control algorithm is simple and robust, thus provide great potential for engineering application.

scholarly journals Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Runqiao Liu ◽  
Minxiang Wei ◽  
Nan Sang ◽  
Jianwei Wei
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Spline Interpolation ◽  
Lateral Displacement ◽  
Autonomous Vehicle ◽  
State Parameter ◽  
Front Wheel ◽  
Path Tracking ◽  
Adhesion Coefficient ◽  
Polar Coordinate

Curved path tracking control is one of the most important functions of autonomous vehicles. First, small turning radius circular bends considering bend quadrant and travel direction restrictions are planned by polar coordinate equations. Second, an estimator of a vehicle state parameter and road adhesion coefficient based on an extended Kalman filter is designed. To improve the convenience and accuracy of the estimator, the combined slip theory, trigonometric function group fitting, and cubic spline interpolation are used to estimate the longitudinal and lateral forces of the tire model (215/55 R17). Third, to minimize the lateral displacement and yaw angle tracking errors of a four-wheel steering (4WS) vehicle, the front-wheel steering angle of the 4WS vehicle is corrected by a model predictive control (MPC) feed-back controller. Finally, CarSim® simulation results show that the 4WS autonomous vehicle based on the MPC feed-back controller can not only significantly improve the curved path tracking performance but also effectively reduce the probability of drifting or rushing out of the runway at high speeds and on low-adhesion roads.

Emergency obstacle avoidance trajectory tracking control based on active disturbance rejection for autonomous vehicles

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092110
Author(s):  
Runqiao Liu ◽  
Minxiang Wei ◽  
Nan Sang
Keyword(s):  
Obstacle Avoidance ◽  
Disturbance Rejection ◽  
Autonomous Vehicles ◽  
High Speed ◽  
Autonomous Vehicle ◽  
Angular Frequency ◽  
Vehicle Speed ◽  
Feed Forward ◽  
Yaw Rate ◽  
Active Disturbance Rejection

To solve the problem of understeer and oversteer for autonomous vehicle under high-speed emergency obstacle avoidance conditions, considering the effect of steering angular frequency and vehicle speed on yaw rate for four-wheel steering vehicles in the frequency domain, a feed-forward controller for four-wheel steering autonomous vehicles that tracks the desired yaw rate is proposed. Furthermore, the steering sensitivity coefficient of the vehicle is compensated linearly with the change in the steering angular frequency and vehicle speed. In addition, to minimize the tracking errors caused by vehicle nonlinearity and external disturbances, an active disturbance rejection control feedback controller that tracks the desired lateral displacement and desired yaw angle is designed. Finally, CarSim® obstacle avoidance simulation results show that an autonomous vehicle with the four-wheel steering path tracking controller consisting of feed-forward control and feedback control could not only improve the tire lateral forces but also reduce tail flicking (oversteer) and pushing ahead (understeer) under high-speed emergency obstacle avoidance conditions.

scholarly journals Trajectory Tracking Control Algorithm for Autonomous Vehicle Considering Cornering Characteristics

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 59470-59484 ◽  
Author(s):  
Jingwei Cao ◽  
Chuanxue Song ◽  
Silun Peng ◽  
Shixin Song ◽  
Xu Zhang ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Control Algorithm ◽  
Autonomous Vehicle ◽  
Trajectory Tracking Control

Implementing Trajectory Tracking Control Algorithm for Autonomous Vehicles

2021 ◽  
Author(s):  
Xuting Duan ◽  
Qi Wang ◽  
Daxin Tian ◽  
Jianshan Zhou ◽  
Jian Wang ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Autonomous Vehicles ◽  
Tracking Control ◽  
Control Algorithm ◽  
Trajectory Tracking Control
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