Two-Stage Lane Keeping Control Algorithm for Lane Sensing Inaccuracy Handling

2013 ◽  
Author(s):  
Jin-Woo Lee ◽  
Bakhtiar B. Litkouhi ◽  
Hsun-Hsuan Huang
Keyword(s):  
Steering System ◽  
Poor Quality ◽  
Smooth Transition ◽  
Steering Control ◽  
Two Stage ◽  
Detection Range ◽  
Active Safety Systems ◽  
Automatic Steering ◽  
The Subject ◽  
Lane Keeping

The Lane Keeping Assist (LKA) system is a safety feature that applies an automatic steering torque to the vehicle steering system to keep the subject vehicle in its lane. Like many other active safety systems, the LKA systems may often experience a performance issue in real road situations. The common LKA performance issues are mainly due to poor quality of the front camera’s curvature data and sudden drops of camera’s detection range. To overcome these issues, this paper proposes a two-stage lane keeping control. In this approach, the LKA has two independent algorithms running with a coordination. In the coordination layer, the secondary lane keeping (LK) control has the authority to override the primary LK control if the primary LK fails to maintain the subject vehicle in the current lane due to the above issues. The key aspect of this system is the accurate timing of the secondary LK’s override over the primary LK. The coordination logic between the primary and the secondary LK control, and smooth transition between the controls are also important performance measures. The determination algorithm of the LK initiation and termination plays a key role in achieving the objectives of LKA fail handling. This paper describes these algorithms as well as the path planning and the steering control algorithms. Several vehicle tests were carried out on curved roads. The results show successful and smooth transition from the primary to the secondary LK layer.

A Model of Driver Steering Control Behavior for Use in Assessing Vehicle Handling Qualities

1993 ◽  
Vol 115 (3) ◽  
pp. 456-464 ◽  
Author(s):  
A. Modjtahedzadeh ◽  
R. A. Hess
Keyword(s):  
Steering System ◽  
Manual Control ◽  
Theoretic Model ◽  
Steering Control ◽  
Vehicle Model ◽  
Vehicle Handling ◽  
Analytical Technique ◽  
Handling Qualities ◽  
Control Behavior ◽  
Lane Keeping

A control theoretic model of driver steering control behavior is presented. The resulting model is shown capable of producing driver/vehicle steering responses which compare favorably with those obtained from driver simulation. The model is simple enough to be used by engineers who may not be manual control specialists. The model contains both preview and compensatory steering dynamics. An analytical technique for vehicle handling qualities assessment is briefly discussed. Driver/vehicle responses from two driving tasks evaluated in a driver simulator are used to evaluate the overall validity of the driver/vehicle model. Finally, the model is exercised in predictive fashion in the computer simulation of a lane keeping task on a curving roadway where the simulated vehicle possessed one of three different steering systems: a conventional two-wheel steering system and a pair of four-wheel steering systems.

Energy Losses due to Limit-Cycle Behavior of a Large Tanker Under Automatic Steering Control

1983 ◽  
Vol 105 (2) ◽  
pp. 222-229 ◽  
Author(s):  
R. E. Reid ◽  
M. Youhanaie
Keyword(s):  
Limit Cycle ◽  
Computer Time ◽  
Steering System ◽  
Simulation Studies ◽  
Time Domain Simulation ◽  
Steering Control ◽  
Wide Range ◽  
Calm Water ◽  
Automatic Steering ◽  
Limit Cycle Behavior

The problem of limit-cycle behavior of a 250,000-dwt tanker in full-load and ballast conditions under automatic steering control in calm water is addressed. The approach presented involves digital computer time domain simulation studies of the yaw-sway-surge-rudder coupled motions of the ship emanating from nonlinearities in the steering system. It is shown that the amplitude of limit cycle in yaw remains, in general, within acceptable limits for open-seas navigation for a fairly wide range of autopilot bandwidths. Propulsion losses resulting from limit-cycle behavior in calm water are shown also to be, in general, small relative to the losses experienced in some conditions in waves. It is shown, however, that whereas increasing bandwidth reduces limit-cycle behavior in calm water, it can be expected to increase propulsion losses in heavy weather. The problem this poses in. design of steering gear controls and autopilot for this type of ship is discussed.

Threat Assessment and Control Decision for Automated Lane Change Maneuver

2010 ◽  
Author(s):  
Jin-Woo Lee ◽  
Xingping Chen
Keyword(s):  
Obstacle Avoidance ◽  
Threat Assessment ◽  
Test Cases ◽  
Lane Change ◽  
Steering Control ◽  
Control Decision ◽  
The Subject ◽  
Lane Keeping ◽  
And Control ◽  
Future Path

Automated vehicle steering control has been actively researched in the automotive industries and academia over a decade. While several automotive companies and suppliers have recently demonstrated autonomous parking, lane keeping control, and lane centering control systems, automated lane change and obstacle avoidance maneuvering have not been as well demonstrated with the same level of maturity. This paper describes an algorithm that assesses environment and situation around the subject vehicle and makes a proper decision when an automated lane change or obstacle avoidance maneuvering is needed. The algorithm continuously monitors the surrounding traffic and lane markings using various types of sensors, and makes judgments along the vehicle future motion. Collision threat is evaluated by comparing the future path of the vehicle and the surrounding traffics in temporal-spatial plane. Typical driving behavior patterns are modeled to ensure safety under various scenarios. This algorithm has been implemented on a test vehicle and validated on straight and curved roads for various speeds of up to 110km/h. Several test cases have been completed and the results are provided.

Modelling, Simulation and Validation of 9 DOF Vehicles Model for Automatic Steering System

2012 ◽  
Vol 165 ◽  
pp. 192-196 ◽  
Author(s):  
Mohd Zakaria Mohammad Nasir ◽  
Khisbullah Hudha ◽  
Mohd Zubir Amir ◽  
Faizul Akmar Abdul Kadir
Keyword(s):  
Autonomous Vehicle ◽  
Steering System ◽  
Simulation Software ◽  
Lateral Acceleration ◽  
Vehicle Model ◽  
Acceptable Error ◽  
Active Safety Systems ◽  
Automatic Steering ◽  
Safety Systems ◽  
Yaw Angle

Autonomous vehicle have recently arouse great interest and attention in the academic worldwide because of their great potential. As the new features for driver assistance and active safety systems are growing rapidly in vehicles, the simulation within a virtual environment has become a necessity. A vehicle model is required to represent the vehicle behaviour as close as real vehicle in simulation software. This paper presents 9 DOF vehicle models which consist of handling and Calspan tire model develop in Matlab Simulink environment to study the vehicle behaviour for double lane change (DLC) and step steer input test. Those criteria will be compared with validated vehicle software namely CarsimEd to evaluated the performance of the vehicle model involving lateral acceleration, yaw angle and yaw rate from both output. Results show the 9 DOF vehicle closely follows the CarsimEd trends with acceptable error at both conditions.

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.

Differential steering-based electric vehicle lateral dynamics control with rollover consideration

2019 ◽  
Vol 234 (3) ◽  
pp. 338-348
Author(s):  
Hui Jing ◽  
Rongrong Wang ◽  
Cong Li ◽  
Jinxiang Wang
Keyword(s):  
Electric Vehicles ◽  
Measurement Problem ◽  
Low Cost ◽  
Steering System ◽  
Front Wheel ◽  
Steering Control ◽  
Lateral Velocity ◽  
Lateral Dynamics ◽  
Vehicle Rollover ◽  
Differential Steering

This article investigates the differential steering-based schema to control the lateral and rollover motions of the in-wheel motor-driven electric vehicles. Generated from the different torque of the front two wheels, the differential steering control schema will be activated to function the driver’s request when the regular steering system is in failure, thus avoiding dangerous consequences for in-wheel motor electric vehicles. On the contrary, when the vehicle is approaching rollover, the torque difference between the front two wheels will be decreased rapidly, resulting in failure of differential steering. Then, the vehicle rollover characteristic is also considered in the control system to enhance the efficiency of the differential steering. In addition, to handle the low cost measurement problem of the reference of front wheel steering angle and the lateral velocity, an [Formula: see text] observer-based control schema is presented to regulate the vehicle stability and handling performance, simultaneously. Finally, the simulation is performed based on the CarSim–Simulink platform, and the results validate the effectiveness of the proposed control schema.

Automated steering controller design for vehicle lane keeping combining linear active disturbance rejection control and quantitative feedback theory

2018 ◽  
Vol 232 (7) ◽  
pp. 937-948 ◽  
Author(s):  
Zhengrong Chu ◽  
Christine Wu ◽  
Nariman Sepehri
Keyword(s):  
Disturbance Rejection ◽  
Control Method ◽  
Controller Design ◽  
Active Disturbance Rejection Control ◽  
Quantitative Feedback Theory ◽  
Steering Control ◽  
Parameter Uncertainties ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Lane Keeping

In this article, a new automated steering control method is presented for vehicle lane keeping. This method is a combination between the linear active disturbance rejection control and the quantitative feedback theory. The structure of the steering controller is first determined based on the linear active disturbance rejection control, then the controller is tuned in the framework of the quantitative feedback theory to meet the prescribed design specifications on sensitivity and closed-loop stability. The parameter uncertainties of the vehicle system are considered at the tuning stage. The proposed steering controller is simulated and tested on a scale vehicle. Both the simulation and experimental results demonstrate that the scale vehicle controlled by the proposed controller is able to perform the lane keeping. In the experiments, the lateral offset between the scale vehicle and the road centerline is regulated within the acceptable ranges of ±0.03 m during straight lane keeping and ±0.15 m during curved lane keeping. The proposed controller is easy to be implemented and is simple without requiring complex calculations and measurements of vehicle states. Simulations also show that the control method can be implemented on a full-scale vehicle.

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