scholarly journals Research on Intelligent Vehicle Path Tracking Algorithm Based on Model Predictive Control

2020 ◽  
Vol 9 (3) ◽  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Intelligent Vehicle ◽  
Vehicle Path ◽  
Path Tracking Algorithm

Low-Speed Vehicle Path-Tracking Algorithm Based On Model Predictive Control Using QPKWIK Solver

2021 ◽  
Author(s):  
Yihuai Zhang ◽  
Baijun Shi ◽  
Xizhi Hu ◽  
Wandong Ai
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Autonomous Vehicles ◽  
Control Method ◽  
Tracking Error ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Tracking Performance ◽  
Low Speed ◽  
Path Tracking Algorithm

Abstract Automated valet parking is a part of autonomous vehicles. Path tracking is a vital capability of autonomous vehicles. In the scenario of automatic valet parking, the existing control algorithm will produce a high tracking error and a high computational burden. This paper proposes a path-tracking algorithm based on model predictive control to adapt to low-speed driving. By using the model predictive control method and vehicle kinematics model, a path tracking controller is designed. Combining the dual algorithm to further optimize the solver, a new QPKWIK solver is proposed. The simulation results show that the solution time of the QPKWIK solver is 25% less than that of the QP solver, and the tracking error is reduced by up to 41% compared with the QP solver. In the parking lot, the tracking performance is tested under four common scenarios, and the experimental results show that this controller has better tracking performance.

scholarly journals Model Predictive Control With Learned Vehicle Dynamics for Autonomous Vehicle Path Tracking

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 128233-128249
Author(s):  
Mohammad Rokonuzzaman ◽  
Navid Mohajer ◽  
Saeid Nahavandi ◽  
Shady Mohamed
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Vehicle Dynamics ◽  
Autonomous Vehicle ◽  
Path Tracking ◽  
Vehicle Path

scholarly journals Vehicle Path Tracking Maneuver Based on Model Predictive Control Theory

2020 ◽  
Vol 1650 ◽  
pp. 032028
Author(s):  
Qijiang Xu ◽  
Jian Wang ◽  
Wenzheng Zhao ◽  
Jinchuan Ding ◽  
Xinjie Liu
Keyword(s):  
Control Theory ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Path Tracking ◽  
Vehicle Path

scholarly journals Electrical Vehicle Path Tracking Based Model Predictive Control With a Laguerre Function and Exponential Weight

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 17082-17097 ◽  
Author(s):  
Bing Zhang ◽  
Changfu Zong ◽  
Guoying Chen ◽  
Bangcheng Zhang
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Path Tracking ◽  
Exponential Weight ◽  
Laguerre Function ◽  
Electrical Vehicle ◽  
Vehicle Path

scholarly journals A Model Predictive Controller with Longitudinal Speed Compensation for Autonomous Vehicle Path Tracking

2019 ◽  
Vol 9 (22) ◽  
pp. 4739 ◽  
Author(s):  
Yao ◽  
Tian
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Autonomous Vehicle ◽  
Tracking Error ◽  
Path Tracking ◽  
Vehicle Stability ◽  
Tracking Accuracy ◽  
Prediction Horizon ◽  
Tracking Model ◽  
Vehicle Path

Autonomous vehicle path tracking accuracy faces challenges in being accomplished due to the assumption that the longitudinal speed is constant in the prediction horizon in a model predictive control (MPC) control frame. A model predictive control path tracking controller with longitudinal speed compensation in the prediction horizon is proposed in this paper, which reduces the lateral deviation, course deviation, and maintains vehicle stability. The vehicle model, tire model, and path tracking model are described and linearized using the small angle approximation method and an equivalent cornering stiffness method. The mechanism of action of longitudinal speed changed with state vector variation, and the stability of the path tracking closed-loop control system in the prediction horizon is analyzed in this paper. Then the longitudinal speed compensation strategy is proposed to reduce tracking error. The controller designed was tested through simulation on the CarSim-Simulink platform, and it showed improved performance in tracking accuracy and satisfied vehicle stability constrains.

Research on autonomous vehicle path tracking control considering roll stability

2020 ◽  
Vol 235 (1) ◽  
pp. 199-210
Author(s):  
Fen Lin ◽  
Shaobo Wang ◽  
Youqun Zhao ◽  
Yizhang Cai
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Vehicle Dynamics ◽  
Tracking Control ◽  
Autonomous Vehicle ◽  
Path Tracking ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Vehicle Path ◽  
Target Path

For autonomous vehicle path tracking control, the general path tracking controllers usually only consider vehicle dynamics’ constraints, without taking vehicle stability evaluation index into account. In this paper, a linear three-degree-of-freedom vehicle dynamics model is used as a predictive model. A comprehensive control method combining Model Predictive Control and Fuzzy proportional–integral–derivative control is proposed. Model Predictive Control is used to control the vehicle yaw stability and track the target path by considering the front wheel angle, sideslip angle, tire slip angles, and yaw rate during the path tracking. Fuzzy proportional–integral–derivative algorithm is adopted to maintain the vehicle roll stability by controlling the braking force of each tire. Co-simulation with CarSim and MATLAB/Simulink shows the designed controller has good tracking performance. The controller is smooth and effective and ensures handling stability in tracking the target path.

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