scholarly journals Adaptive Coordinated Path Tracking Control Strategy for Autonomous Vehicles with Direct Yaw Moment Control

2022 ◽  
Vol 35 (1) ◽  
Author(s):  
Ying Tian ◽  
Qiangqiang Yao ◽  
Peng Hang ◽  
Shengyuan Wang
Keyword(s):  
Control Strategy ◽  
Autonomous Vehicles ◽  
Tracking Control ◽  
High Speed ◽  
Front Wheel ◽  
Path Tracking ◽  
Vehicle Stability ◽  
Tracking Accuracy ◽  
Large Curvature ◽  
Yaw Moment

AbstractIt is a striking fact that the path tracking accuracy of autonomous vehicles based on active front wheel steering is poor under high-speed and large-curvature conditions. In this study, an adaptive path tracking control strategy that coordinates active front wheel steering and direct yaw moment is proposed based on model predictive control algorithm. The recursive least square method with a forgetting factor is used to identify the rear tire cornering stiffness and update the path tracking system prediction model. To adaptively adjust the priorities of path tracking accuracy and vehicle stability, an adaptive strategy based on fuzzy rules is applied to change the weight coefficients in the cost function. An adaptive control strategy for coordinating active front steering and direct yaw moment is proposed to improve the path tracking accuracy under high-speed and large-curvature conditions. To ensure vehicle stability, the sideslip angle, yaw rate and zero moment methods are used to construct optimization constraints based on the model predictive control frame. It is verified through simulation experiments that the proposed adaptive coordinated control strategy can improve the path tracking accuracy and ensure vehicle stability under high-speed and large-curvature conditions.

scholarly journals A Two-Layer Controller for Lateral Path Tracking Control of Autonomous Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3689
Author(s):  
Zhiwei He ◽  
Linzhen Nie ◽  
Zhishuai Yin ◽  
Song Huang
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Linear Time ◽  
Lower Layer ◽  
Path Tracking ◽  
Current Control ◽  
Slip Angle ◽  
Vehicle Stability ◽  
Tracking Accuracy ◽  
Steering Angle

This paper presents a two-layer controller for accurate and robust lateral path tracking control of highly automated vehicles. The upper-layer controller, which produces the front wheel steering angle, is implemented with a Linear Time-Varying MPC (LTV-MPC) whose prediction and control horizon are both optimized offline with particle swarm optimization (PSO) under varying working conditions. A constraint on the slip angle is imposed to prevent lateral forces from saturation to guarantee vehicle stability. The lower layer is a radial basis function neural network proportion-integral-derivative (RBFNN-PID) controller that generates electric current control signals executable by the steering motor to rapidly track the target steering angle. The nonlinear characteristics of the steering system are modeled and are identified on-line with the RBFNN so that the PID controller’s control parameters can be adjusted adaptively. The results of CarSim-Matlab/Simulink joint simulations show that the proposed hierarchical controller achieves a good level of path tracking accuracy while maintaining vehicle stability throughout the path tracking process, and is robust to dynamic changes in vehicle velocities and road adhesion coefficients.

Path tracking coordinated control strategy for autonomous four in-wheel-motor independent-drive vehicles with consideration of lateral stability

2020 ◽  
pp. 095440702094688
Author(s):  
Changle Xiang ◽  
Haonan Peng ◽  
Weida Wang ◽  
Liang Li ◽  
Quan An ◽  
...  
Keyword(s):  
Control Strategy ◽  
Tracking Control ◽  
Control Method ◽  
Coordinated Control ◽  
Path Tracking ◽  
Lateral Stability ◽  
Dynamic Adjustment ◽  
Tracking Accuracy ◽  
Multi Objective ◽  
Yaw Moment

How to enhance and ensure the vehicle yaw/lateral stability and safety performance is a crucial and worthy research problem for the autonomous four in-wheel-motor independent-drive vehicle. In this paper, a hierarchical path tracking control strategy coordinated with the direct yaw moment control for autonomous four in-wheel-motor independent-drive vehicle is proposed with consideration of the lateral stability. In the upper controller, a novel model predictive control method based on the vehicle 7-degree-of-freedom dynamic model is presented to obtain the front wheel steering angle and two virtual generalized forces, the traction and yaw moment. A dynamic adjustment method of target weight based on variance adjustment factor is proposed to realize multi-objective cooperative control of maneuverability, path tracking accuracy, and yaw stability. Moreover, the tire stability margin and its standard deviation are put forward in the objective function of the lower optimal generalized force distributor, making full use of the road adhesion of each wheel. Carsim–Simulink joint simulation results illustrate that the proposed coordinated control strategy could prosper the multi-objective coordinated control. In addition, the path tracking coordinated control strategy could further improve the lateral stability and safety of the vehicle compared with the mere path tracking control strategy, when autonomous four in-wheel-motor independent-drive vehicle is placed under extremely dangerous road conditions.

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.

scholarly journals Efficient Path Tracking Control for Autonomous Driving of Tracked Emergency Rescue Robot under 6G Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qing Gu ◽  
Guoxing Bai ◽  
Yu Meng ◽  
Guodong Wang ◽  
Jiazang Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Tracking Control ◽  
Autonomous Driving ◽  
Future Trend ◽  
Path Tracking ◽  
Tracking Accuracy ◽  
Large Curvature ◽  
Emergency Rescue ◽  
Time Performance ◽  
Path Curvature

This paper proposes a path tracking control algorithm of tracked mobile robots based on Preview Linear Model Predictive Control (MPC), which is used to achieve autonomous driving in the unstructured environment under an emergency rescue scenario. It is the future trend to realize the communication and control of rescue equipment with 6G and edge cloud cooperation. In this framework, linear MPC (LMPC) is suitable for the path tracking control of rescue robots due to its advantages of less computing resources and good real-time performance. However, in such a scene, the driving environment is complex and the path curvature changes greatly. Since LMPC can only introduce linearized feedforward information, the tracking accuracy of the path with large curvature changes is low. To overcome this issue, combined with the idea of preview control, preview-linear MPC is designed in this paper. The controller is verified by MATLAB/Simulink simulation and prototype experiment. The results show that the proposed method can improve the tracking accuracy while ensuring real-time performance and has better tracking performance for the path with large curvature variation.

A novel path tracking approach considering safety of the intended functionality for autonomous vehicles

2021 ◽  
pp. 095440702110205
Author(s):  
Huiran Wang ◽  
Qidong Wang ◽  
Wuwei Chen ◽  
Linfeng Zhao ◽  
Dongkui Tan
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Coordinated Control ◽  
Steering System ◽  
Front Wheel ◽  
Path Tracking ◽  
Hierarchical Architecture ◽  
Automatic Steering ◽  
The Stability ◽  
Control Layer

To reduce the adverse effect of the functional insufficiency of the steering system on the accuracy of path tracking, a path tracking approach considering safety of the intended functionality is proposed by coordinating automatic steering and differential braking in this paper. The proposed method adopts a hierarchical architecture consisting of a coordinated control layer and an execution control layer. In coordinated control layer, an extension controller considering functional insufficiency of the steering system, tire force characteristics and vehicle driving stability is proposed to determine the weight coefficients of automatic steering and the differential braking, and a model predictive controller is designed to calculate the desired front wheel angle and additional yaw moment. In execution control layer, a H∞ steering angle controller considering external disturbances and parameter uncertainty is designed to track desired front wheel angle, and a braking force distribution module is used to determine the wheel cylinder pressure of the controlled wheels. Both simulation and experiment results show that the proposed method can overcome the functional insufficiency of the steering system and improve the accuracy of path tracking while maintaining the stability of the autonomous vehicle.

Experimental Validations on Vision-Based Path Tracking With Preview Four Wheel Steering Control

2019 ◽  
Author(s):  
Yansong Peng ◽  
Fengchen Wang ◽  
Saikrishna Gurumoorthy ◽  
Yan Chen ◽  
Mutian Xin
Keyword(s):  
Tracking Control ◽  
Low Cost ◽  
Experimental Tests ◽  
Front Wheel ◽  
Path Tracking ◽  
Steering Control ◽  
Tracking Errors ◽  
The Road ◽  
Experimental Validations ◽  
Lateral Offset

Abstract In this paper, a vision-based path-tracking control strategy using four-wheel steering (4WS) is experimentally investigated via an automated ground vehicle (AGV). A low-cost monocular camera is used to continuously perceive the upcoming lane boundaries via capturing the preview road image frames. Based on the applied image processing algorithms, the vehicle lateral offset error with respect to the road center line and the heading angle error with respect to the road curvature are calculated in real time for the control purpose. The 4WS path-tracking controller is designed to minimize the two path-tracking errors of the AGV. The AGV with the 4WS system is utilized to perform the experimental tests on road to validate the path-tracking control design. For comparison, the road test is also conducted for the path-tracking control with only the front wheel steering. The experimental results show that the proposed 4WS is able to achieve better path-tracking performance.

scholarly journals MME-EKF-Based Path-Tracking Control of Autonomous Vehicles Considering Input Saturation

2019 ◽  
Vol 68 (6) ◽  
pp. 5246-5259 ◽  
Author(s):  
Chuan Hu ◽  
Zhenfeng Wang ◽  
Hamid Taghavifar ◽  
Jing Na ◽  
Yechen Qin ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Input Saturation ◽  
Path Tracking

Vehicle Dynamics Control Based on Linear Quadratic Regulator

2009 ◽  
Vol 16-19 ◽  
pp. 876-880
Author(s):  
Si Qi Zhang ◽  
Tian Xia Zhang ◽  
Shu Wen Zhou
Keyword(s):  
Control Strategy ◽  
Vehicle Dynamics ◽  
Linear Quadratic Regulator ◽  
Active Safety ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Yaw Rate ◽  
Vehicle Dynamics Control ◽  
Yaw Moment

The paper presents a vehicle dynamics control strategy devoted to prevent vehicles from spinning and drifting out. With vehicle dynamics control system, counter braking are applied at individual wheels as needed to generate an additional yaw moment until steering control and vehicle stability were regained. The Linear Quadratic Regulator (LQR) theory was designed to produce demanded yaw moment according to the error between the measured yaw rate and desired yaw rate. The results indicate the proposed system can significantly improve vehicle stability for active safety.

scholarly journals A HEURISTIC CASCADING FUZZY LOGIC APPROACH TO REACTIVE NAVIGATION FOR UAV

2014 ◽  
Vol 15 (2) ◽  
Author(s):  
Yew-Chung Chak ◽  
Renuganth Varatharajoo
Keyword(s):  
Fuzzy Logic ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Tracking Control ◽  
Path Tracking ◽  
Reactive Navigation ◽  
Logic Control ◽  
Fuzzy Logic Approach ◽  
Avoidance Control ◽  
Logic Approach

ABSTRACT: The capability of navigating Unmanned Aerial Vehicles (UAVs) safely in unknown terrain offers huge potential for wider applications in non-segregated airspace. Flying in non-segregated airspace present a risk of collision with static obstacles (e.g., towers, power lines) and moving obstacles (e.g., aircraft, balloons). In this work, we propose a heuristic cascading fuzzy logic control strategy to solve for the Conflict Detection and Resolution (CD&R) problem, in which the control strategy is comprised of two cascading modules. The first one is Obstacle Avoidance control and the latter is Path Tracking control. Simulation results show that the proposed architecture effectively resolves the conflicts and achieve rapid movement towards the target waypoint.ABSTRAK: Keupayaan mengemudi Kenderaan Udara Tanpa Pemandu (UAV) dengan selamat di kawasan yang tidak diketahui menawarkan potensi yang besar untuk aplikasi yang lebih luas dalam ruang udara yang tidak terasing. Terbang di ruang udara yang tidak terasing menimbulkan risiko perlanggaran dengan halangan statik (contohnya, menara, talian kuasa) dan halangan bergerak (contohnya, pesawat udara, belon). Dalam kajian ini, kami mencadangkan satu strategi heuristik kawalan logik kabur yang melata untuk menyelesaikan masalah Pengesanan Konflik dan Penyelesaian (CD&R), di mana strategi kawalan yang terdiri daripada dua modul melata. Hasil simulasi menunjukkan bahawa seni bina yang dicadangkan berjaya menyelesaikan konflik dan mencapai penerbangan pesat ke arah titik laluan sasaran.KEYWORDS: fuzzy logic; motion planning; obstacle avoidance; path tracking; reactive navigation; UAV

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