scholarly journals Hierarchical Control for Trajectory Generation and Tracking Via Active Front Steering

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Joseph S. Hellewell ◽  
Atanas A. Popov ◽  
Gary E. Burnett
Keyword(s):  
Autonomous Vehicle ◽  
Tracking Error ◽  
Hierarchical Control ◽  
Path Optimization ◽  
Lateral Acceleration ◽  
Reference Trajectory ◽  
Arc Length ◽  
Steering Control ◽  
The Road ◽  
Reference Path

Abstract A new hierarchical model predictive controller (HMPC) for autonomous vehicle steering control is presented. The controller generates a path of shortest distance by determining lateral coordinates on a longitudinal grid, while respecting road bounds. This path is then parameterized by arc length before being optimized to restrict the normal acceleration values along the trajectory's arc length. The optimized trajectory is then tracked using a nonlinear MPC scheme using a bicycle plant model to calculate an optimal steering angle for the tires. The proposed controller is evaluated in simulation during a double-lane-change maneuver, where it generates and tracks a reference trajectory while observing the road boundaries and acceleration limits. Its performance is compared to a controller without path optimization, along with another that uses a smooth, predetermined, reference path instead of creating its own initial reference. It is shown that the proposed controller improves the tracking compared to a controller without path optimization, with a four-times reduction in average lateral tracking error. The average lateral acceleration is also reduced by 6%. The controller also maintains the tracking performance of a controller that uses a smooth reference path, while showing a much greater flexibility due to its ability to create its own initial reference path rather than having to follow a predetermined trajectory.

scholarly journals Real-Life Implementation of a GPS-Based Path-Following System for an Autonomous Vehicle

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3940 ◽  
Author(s):  
Alexander de Winter ◽  
Simone Baldi
Keyword(s):  
Real Time ◽  
Autonomous Vehicle ◽  
Tracking Error ◽  
Experimental Studies ◽  
Real Life ◽  
Path Following ◽  
Lateral Acceleration ◽  
The Real ◽  
Gps System ◽  
Toyota Prius

This work is meant to report on activities at TU Delft on the design and implementation of a path-following system for an autonomous Toyota Prius. The design encompasses: finding the vehicle parameters for the actual vehicle to be used for control design; lateral and longitudinal controllers for steering and acceleration, respectively. The implementation covers the real-time aspects via LabVIEW from National Instruments and the real-life tests. The deployment of the system was enabled by a Spatial Dual Global Positioning System (GPS) system providing more accuracy than the regular GPS. The results discussed in this work represent the first autonomous tests on the Toyota Prius at TU Delft, and we expect the proposed system to be a benchmark against which to test more advanced solutions. The tests show that the system is able to perform in real-time while satisfying comfort and trajectory tracking requirements: in particular, the tracking error was within 16 cm, which is compatible with the 13 cm precision of the Spatial Dual GPS, whereas the longitudinal and lateral acceleration are within comfort levels as defined by available experimental studies.

Implementation of Trailer Steering Control on a Multi-Unit Vehicle at High Speeds

2013 ◽  
Vol 136 (2) ◽  
Author(s):  
Richard Roebuck ◽  
Andrew Odhams ◽  
Kristoffer Tagesson ◽  
Caizhen Cheng ◽  
David Cebon
Keyword(s):  
Control System ◽  
High Speed ◽  
Tracking Error ◽  
Path Following ◽  
Stability Control ◽  
Substantial Improvement ◽  
Lateral Acceleration ◽  
Steering Control ◽  
Stability Margins ◽  
Stability Control System

A high-speed path-following controller for long combination vehicles (LCVs) was designed and implemented on a test vehicle consisting of a rigid truck towing a dolly and a semitrailer. The vehicle was driven through a 3.5 m wide lane change maneuver at 80 km/h. The axles of the dolly and trailer were steered actively by electrically-controlled hydraulic actuators. Substantial performance benefits were recorded compared with the unsteered vehicle. For the best controller weightings, performance improvements relative to unsteered case were: lateral tracking error 75% reduction, rearward amplification (RA) of lateral acceleration 18% reduction, and RA of yaw rate 37% reduction. This represents a substantial improvement in stability margins. The system was found to work well in conjunction with the braking-based stability control system of the towing vehicle with no negative interaction effects being observed. In all cases, the stability control system and the steering system improved the yaw stability of the combination.

Steering Controller Design For Automated Guideway Transit Vehicles

1978 ◽  
Vol 100 (1) ◽  
pp. 1-8 ◽  
Author(s):  
S. E. Shladover ◽  
D. N. Wormley ◽  
H. H. Richardson ◽  
R. Fish
Keyword(s):  
Controller Design ◽  
Broad Class ◽  
Tracking Error ◽  
Lateral Acceleration ◽  
Mean Square ◽  
Steering Control ◽  
Control Techniques ◽  
Position Errors ◽  
Automatic Steering ◽  
Single Sensor

The fundamental lateral performance capabilities of rubber-tired automated guideway transit (AGT) vehicles operating under automatic steering control on exclusive guideways are discussed. Control is achieved by steering the front wheels in response to signals derived from the position errors between the vehicle and a guideway-based reference containing random irregularities. Optimal control techniques are used to synthesize controllers which minimize a performance index consisting of mean square lateral acceleration and tracking error, defining a frontier which limits the performance of vehicles steered by a broad class of controllers. Simple single-sensor proportional steering controllers are found to achieve near-optimum performance for a typical AGT vehicle. The degradations in performance arising from dynamic lags in the steering actuator and operation at off-design speeds are shown.

Steering Control of an Autonomous Vehicle Based on RBF Neural Networks Compensation and Dynamic Systems

2012 ◽  
Vol 460 ◽  
pp. 98-102 ◽  
Author(s):  
Sheng Min Cui ◽  
Kun Zhang ◽  
Jian Feng Wang ◽  
Ji Meng Wang
Keyword(s):  
Neural Networks ◽  
Autonomous Vehicles ◽  
Vision System ◽  
Autonomous Vehicle ◽  
Physical Parameters ◽  
Rbf Neural Networks ◽  
Steering Control ◽  
The Road ◽  
Lateral Offset ◽  
The Stability

A tracking controller based on RBF (Radial Basis Function) neural networks compensating in vision based autonomous vehicles is designed in this paper. One input of the RBF compensating model are the lateral offset which measured by the vision system as the distance between the road centerline and the center of the vehicle a certain distance before. Another input is the steering angle which was collected when the vehicle was driving by a human testing driver. The controller is finally made by linearly fitting the parameter of the RBF neural networks. The stability is proven by composite Lyapunov functions. The robustness of the controlled system is theoretically investigated with respect to speed variations and uncertain vehicle physical parameters. Several simulations are made on a sedan vehicle to prove the effectiveness of this controller when perform path tracking on roads with an uncertain curvature.

Proportional Navigation and Model Predictive Control of an Unmanned Autonomous Vehicle for Obstacle Avoidance

2018 ◽  
Author(s):  
Ryan P. Shaw ◽  
David M. Bevly
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Vehicle ◽  
Integrated System ◽  
Reference Trajectory ◽  
Ground Vehicles ◽  
Proportional Navigation ◽  
Predictive Controller ◽  
Proportional Navigation Law ◽  
Vehicle Dynamic Model ◽  
And Control

This paper presents a new approach for the guidance and control of a UGV (Unmanned Ground Vehicle). An obstacle avoidance algorithm was developed using an integrated system involving proportional navigation (PN) and a nonlinear model predictive controller (NMPC). An obstacle avoidance variant of the classical proportional navigation law generates command lateral accelerations to avoid obstacles, while the NMPC is used to track the reference trajectory given by the PN. The NMPC utilizes a lateral vehicle dynamic model. Obstacle avoidance has become a popular area of research for both unmanned aerial vehicles and unmanned ground vehicles. In this application an obstacle avoidance algorithm can take over the control of a vehicle until the obstacle is no longer a threat. The performance of the obstacle avoidance algorithm is evaluated through simulation. Simulation results show a promising approach to conditionally implemented obstacle avoidance.

scholarly journals Model Contrast of Autonomous Vehicle Impacts on Traffic

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Derek Hungness ◽  
Raj Bridgelall
Keyword(s):  
Autonomous Vehicles ◽  
Travel Demand ◽  
Autonomous Vehicle ◽  
Sociodemographic Factors ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Traffic Conditions ◽  
Demand Models ◽  
Wide Range ◽  
Potential Benefits

The adoption of connected and autonomous vehicles (CAVs) is in its infancy. Therefore, very little is known about their potential impacts on traffic. Meanwhile, researchers and market analysts predict a wide range of possibilities about their potential benefits and the timing of their deployments. Planners traditionally use various types of travel demand models to forecast future traffic conditions. However, such models do not yet integrate any expected impacts from CAV deployments. Consequently, many long-range transportation plans do not yet account for their eventual deployment. To address some of these uncertainties, this work modified an existing model for Madison, Wisconsin. To compare outcomes, the authors used identical parameter changes and simulation scenarios for a model of Gainesville, Florida. Both models show that with increasing levels of CAV deployment, both the vehicle miles traveled and the average congestion speed will increase. However, there are some important exceptions due to differences in the road network layout, geospatial features, sociodemographic factors, land-use, and access to transit.

scholarly journals A model reference adaptive variable impedance control method for robot

2021 ◽  
Vol 336 ◽  
pp. 03005
Author(s):  
Xinchao Sun ◽  
Lianyu Zhao ◽  
Zhenzhong Liu
Keyword(s):  
Real Time ◽  
Tracking Control ◽  
Control Method ◽  
Impedance Control ◽  
Tracking Error ◽  
Reference Trajectory ◽  
Control Parameters ◽  
Model Reference ◽  
Force Tracking ◽  
Model Reference Adaptive

As a simple and effective force tracking control method, impedance control is widely used in robot contact operations. The internal control parameters of traditional impedance control are constant and cannot be corrected in real time, which will lead to instability of control system or large force tracking error. Therefore, it is difficult to be applied to the occasions requiring higher force accuracy, such as robotic medical surgery, robotic space operation and so on. To solve this problem, this paper proposes a model reference adaptive variable impedance control method, which can realize force tracking control by adjusting internal impedance control parameters in real time and generating a reference trajectory at the same time. The simulation experiment proves that compared with the traditional impedance control method, this method has faster force tracking speed and smaller force tracking error. It is a better force tracking control method.

scholarly journals Adhesion state estimation based on improved tire brush model

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401774770
Author(s):  
Bei Shaoyi ◽  
Li Bo ◽  
Zhu Yanyan
Keyword(s):  
Lateral Force ◽  
Longitudinal Force ◽  
Lateral Acceleration ◽  
Stable Range ◽  
The Road ◽  
Nonlinear Compensation ◽  
The Stability ◽  
Standard Calculation ◽  
Double Nonlinear ◽  
Brush Model

On the basis of calculating the longitudinal force using the original brush model, we simplify the tire structure and consider the lateral force generated by the lateral elasticity of the tread. At the same time, the boundary conditions between the adhesion area and the slip zone in the contact area of the tire are fully discussed. By establishing an improved tire brush model, the error caused by neglecting the sideslip characteristics is avoided, and the adaptability of the tire model is improved. A double nonlinear compensation method based on the lateral acceleration deviation and the yaw rate deviation is employed to estimate the road adhesion coefficient, which is closer to the actual attachment situation than the standard calculation. Based on this model, the vehicle stability coefficient k is defined and calculated to describe the stability of the vehicle during the driving process. The modeling results show that the value of k is always in the stable range of [0, 1]. Therefore, the vehicle that utilizes the improved tire brush model is always within the controllable range in the driving process, which verifies the effectiveness of the model.

Practical Tracking Control of a Class of Uncertain Surface Vessels Under Weak Assumptions on Uncertainties and Reference Trajectories

2021 ◽  
Author(s):  
Jian Li ◽  
Wenqing Xu ◽  
Zhaojing Wu ◽  
Yungang Liu
Keyword(s):  
Tracking Control ◽  
Broad Class ◽  
Tracking Error ◽  
Reference Trajectory ◽  
Unknown Parameters ◽  
Related Literature ◽  
Surface Vessels ◽  
Control Scheme ◽  
Reference Trajectories ◽  
Theoretical Results

Abstract This paper is devoted to the tracking control of a class of uncertain surface vessels. The main contributions focus on the considerable relaxation of the severe restrictions on system uncertainties and reference trajectory in the related literature. Specifically, all the system parameters are unknown and the disturbance is not necessarily to be differentiable in the paper, but either unknown parameters or disturbance is considered but the other one is excluded in the related literature, or both of them are considered but the disturbance must be continuously differentiable. Moreover, the reference trajectories in the related literature must be at least twice continuously differentiable and themselves as well as their time derivatives must be known for feedback, which are generalized to a more broad class ones that are unknown and only one time continuously differentiable in the paper. To solve the control problem, a novel practical tracking control scheme is presented by using backstepping scheme and adaptive technique, and in turn to derive an adaptive state-feedback controller which guarantees that all the states of the resulting closed-loop system are bounded while the tracking error arrives at and then stay within an arbitrary neighborhood of the origin. Finally, simulation is provided to validate the effectiveness of the proposed theoretical results.

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