Lateral Displacement Error Research Articles

Electronic brake system-based hierarchical motion control of commercial vehicle for autonomous obstacle avoidance

As a high-level autonomous driving technology, efficient and safe automatic obstacle avoidance on highway is one of the critical and ongoing topics that requires in-depth research for commercial vehicles. Electronic control air pressure brake system, owing to its fast response and active braking ability, is an effective active-chassis technology to function path tracking and stability control in such condition. Yaw motion stability control problem of autonomous driving commercial vehicle based on active braking control with electronic air brake system for automatic obstacle avoidance is investigated. First, a hierarchical yaw motion dynamics control architecture is introduced after vehicle and brake system modeling. The quintic polynomial curve-based trajectory planning method and a Model Predictive Control based trajectory tracking control strategy are formulated. Second, to evade the possible stability losing issue in this circumstance, Cubature Kalman Filter (CKF) is utilized to estimate the vehicle motion states, and a fuzzy PID control-based differential brake stability control strategy is designed for the electronic brake system composed of front-and-rear two sets of dual-channel pressure regulator and ABS solenoid valve. Finally, the proposed hierarchical yaw stability control strategy for a commercial vehicle in typical obstacle avoidance conditions is comparatively verified based on the joint simulation tools. After the yaw stability control, the peak value of the lateral displacement error of trajectory tracking can be reduced by 44.7%. The yaw stability control strategy based on fuzzy PID control can reduce the yaw rate by 46%–57% and the sideslip angle by 60%–73% under different conditions. The results show that the proposed control strategy can effectively improve the yaw stability of the vehicle while avoiding obstacles at high speed.

Model predictive control with real-time variable weight for civil aircraft towing taxi-out control systems

Unlike the traditional method of taxying, where civil aircraft reach the runway by relying on their engines, the new mode of towing taxi-out may become preferred because of its lower energy consumption, lower emissions, and higher efficiency. To improve the tracking accuracy and lateral stability of the towing system, this study used a two-level time-varying weight control method (RMPC) based on model predictive control (MPC) and fuzzy control. The tractor speed and front wheel angle were set as the control variables in the MPC controller, and the real-time lateral displacement error and yaw angle error of the tractor were set as the fuzzy control inputs. The influence of the weight matrix on the accuracy and stability of path tracking was coordinated by online optimization of the MPC objective function weight. The simulations of multiple working conditions were performed using TruckSim software in Simulink, which showed that the proposed control method can limit the lateral displacement error of the tractor and aircraft within 0.4 m, which can be reduced by 70.83% and 77.4% compared with the single MPC, respectively. Additionally, the maximum yaw angle errors of the tractor and aircraft are reduced by 76.11% and 51.31% compared with the single MPC, respectively. Furthermore, the yaw angle error of tractors can be limited to 4° and that of aircraft can be limited to 6.5°, which is an improvement of the lateral stability and driving safety for the civil aircraft towing system. The new controller may provide technical insights and support for the practical development and safe application of the towing taxi-out mode.

Optimizing Nonlinear Lateral Control for an Autonomous Vehicle

The lack of general algorithms for the control of nonlinear systems is a generalized problem, especially when attempting to stabilize systems such as ground vehicles, which have uncertainties and are usually linearized under the assumption of small angles. To solve this problem, in this work, the implementation of a suboptimal discrete control is developed to stabilize an autonomous automobile. We assume the system is affine for the optimization procedure of finite horizon that allows us to find a solution while avoiding solving the Ricatti-type equation, commonly encountered in this kind of algorithm. This procedure is applied to the dynamical model of the lateral displacement and orientation errors of the vehicle that was discretized through the method of Euler. These nonlinear models discretized to compute a bounded control. The control is tested in different simulated scenarios to show the efficiency of the system for solving typical tasks for the path planning of an autonomous vehicle.

LQR Trajectory Tracking Control of Unmanned Wheeled Tractor Based on Improved Quantum Genetic Algorithm

In the process of trajectory tracking using the linear quadratic regulator (LQR) for driverless wheeled tractors, a weighting matrix optimization method based on an improved quantum genetic algorithm (IQGA) is proposed to solve the problem of weight selection. Firstly, the kinematic model of the wheeled tractor is established according to the Ackermann steering model, and the established model is linearized and discretized. Then, the quantum gate rotation angle adaptive strategy is optimized to adjust the rotation angle required for individual evolution to ensure a timely jumping out of the local optimum. Secondly, the populations were perturbed by the chaotic perturbation strategy and Hadamard gate variation according to their dispersion degree in order to increase their diversity and search accuracy, respectively. Thirdly, the state weighting matrix Q and the control weighting matrix R in LQR were optimized using IQGA to obtain control increments for the trajectory tracking control of the driverless wheeled tractor with circular and double-shifted orbits. Finally, the tracking simulation of circular and double-shifted orbits based on the combination of Carsim and Matlab was carried out to compare the performance of LQR optimized by five algorithms, including traditional LQR, genetic algorithm (GA), particle swarm algorithm (PSO), quantum genetic algorithm (QGA), and IQGA. The simulation results show that the proposed IQGA speeds up the algorithm’s convergence, increases the population’s diversity, improves the global search ability, preserves the excellent information of the population, and has substantial advantages over other algorithms in terms of performance. When the tractor tracked the circular trajectory at 5 m/s, the root mean square error (RMSE) of four parameters, including speed, lateral displacement, longitudinal displacement, and heading angle, was reduced by about 30%, 1%, 55%, and 3%, respectively. When the tractor tracked the double-shifted trajectory at 5 m/s, the RMSE of the four parameters, such as speed, lateral displacement error, longitudinal displacement error, and heading angle, was reduced by about 32%, 25%, 37%, and 1%, respectively.

Adaptive modified super-twisting sliding mode control based on PSO with neural network for lateral dynamics of autonomous vehicle

In this article, we have developed a strategy for controlling the lateral dynamics of an autonomous vehicle. The bicycle model of the autonomous vehicle is used. In order to improve the systems performance, we take a new dynamic surface of the sliding mode and a novel expression of the super twisting part of the controller. The parameters of the controller are determined using the particle swarm optimisation (PSO). The objective of this strategy is to follow the reference trajectory of the autonomous vehicle while reducing the lateral displacement error. The steering angle is the control input, the outputs of this system are the lateral displacement and the yaw angle. The radial basis function neural network (RBFNN) is used to approximate the unknown nonlinear dynamic. Simulation results show some improvements over the literature.

A closed-loop directional dynamics control with LQR active trailer steering for articulated heavy vehicle

To improve the directional performance of articulated heavy vehicles (AHV), three previewed points driver model and LQR active trailer steering (ATS) strategy are proposed and examined using closed-loop driver/vehicle dynamics simulation. Firstly, a simplified linear three-degree-of-freedom (3-DOF) yaw plane model for AHV is established and validated. Secondly, based on the multi-point preview-predictor following strategy, the weighted-average error of three previewed points of the tractor is defined as the final lateral previewed displacement error. According to the assumption of constant yaw rate and the trajectory prediction of AHV, and three previewed points driver model has been configured, it’s path-following performance is verified. Thirdly, instead of using the idea of minimization, a linear quadratic regulator (LQR) controller is proposed based on the linear 3-DOF yaw plane model of AHV to make the control variables to keep following the desired responses. Through joint simulations using MATLAB/Simulink and TruckSim, the effectiveness of the built-in driver model, three-previewed point driver model and three-previewed point driver model + LQR ATS control methods on improving vehicle orientation performance were compared and analyzed through closed-loop driver/vehicle dynamics simulations. The significant effectiveness of the proposed method in improving maneuverability and stability is verified through low-speed 360° trajectory tracking tests and high-speed double lane change maneuver simulations. Finally, a hardware-in-the-loop (HIL) platform is used to further verify the effectiveness of the designed strategy.

An Adaptive Constrained Path Following Control Scheme for Autonomous Electric Vehicles

To ensure driving safety, autonomous electric vehicles need to follow the planned path accurately, which depends on the vehicle path following control strategy. It is widely acknowledged that the model-based control strategies have excellent potential on path following, but their effect is seriously affected by the parametric uncertainty. To solve this problem, an adaptive constrained path following control scheme considering the influence of parametric uncertainty is proposed for autonomous electric vehicles. Firstly, an adaptive feedback control law and its update law are proposed to deal with the variation of tire cornering stiffness during vehicle path following process. Secondly, a constraint function for lateral displacement error during path following process is designed to further improve driving safety. And then, the closed-loop stability of the proposed control scheme is proved. Finally, the validation is implemented by simulation and experiment, the results show that the proposed control scheme is effective under different working conditions. The maximum lateral displacement error is reduced to 0.0297m by using the proposed scheme in the experiment. The proposed scheme might provide a theoretical reference for control practice of autonomous vehicles.

A retrospective comparison of two different immobilization systems for radiotherapy of extremity soft tissue sarcomas and its influence on CTV-PTV margin

BackgroundOn account of extremity wide range of movements and difficulty of reproducibility during irradiation of extremity sarcomas, assorted immobilization strategies are employed to eliminate setup errors. The study purpose was to compare the setup errors of the commonly used immobilization tools and to define planning target volume (PTV) margins for each device.MethodsA retrospective review comparing Vac-Loc™ and thermoplastic cast (Tcast) was conducted. On radiotherapy treatment, portal imaging was matched with the pre-treatment simulation imaging for both fixation tools. The isocenter shifts and total vector error (TVE) were compared. Random (σ) and systemic errors (Σ) were computed and PTV margins were defined.ResultsThree hundred seven shifts in each direction measured in 14 patients. Mean displacements for the Vac-Loc™ and Tcast, respectively, were as follow: vertical; -0.01 cm vs. 0.02 cm, longitudinal; 0.03 cm vs. 0.04; lateral; 0.04 cm vs. 0.00 cm and TVE; 0.15 cm vs. 0.17 cm with no significant statistical difference. Random and systemic errors were comparable for both devices. The lateral displacement and rotational random errors were higher Vac-Loc™ compared to Tcast. Overall measured PTV margins were marginally lower for Tcast compared to Vac-Loc™.ConclusionVac-Loc™ and Tcast are valid options for immobilization with no clear superiority of either device. The marginal advantage of Tcast warrants further prospective studies.

Form deviations caused by lateral displacement errors in annular subaperture stitching interferometry

Annular subaperture stitching interferometry (ASSI) is a common approach for the measurement of aspherical surfaces. A common obstacle of ASSI is the occurrence of lateral displacement errors when the sensor or specimen is repositioned between the subaperture measurements. Our contribution focuses on modeling of the statistical displacement errors. A virtual experiment is presented simulating the propagation of the displacement errors through a cumulative and a global stitching algorithm to the retrieved surface form. For the considered experimental setup, the uncertainty in lateral position depends on the positioning uncertainties of the employed motion system and the uncertainty in the absolute distance measurement between the sensor and specimen. The lateral displacement uncertainty is determined experimentally employing a calibratable lateral grating. Thus, it is traceable to the SI unit of the length (meter). The experimental results show that the lateral displacement errors may be modeled by a normal distribution, and the results of the virtual experiment indicate that the statistical lateral displacement errors transfer linear through the stitching procedure and also cause a normal distributed topography error. This enables the assignment of an expanded uncertainty to each individual sample point employing the Zernike polynomial expression of the topography measurement.

The indirect shared steering control under double loop structure of driver and automation

Due to the critical defects of techniques in fully autonomous vehicles, man-machine cooperative driving is still of great significance in today&#x02BC s transportation system. Unlike the previous shared control structure, this paper introduces a double loop structure which is applied to indirect shared steering control between driver and automation. In contrast to the tandem indirect shared control, the parallel indirect shared control put the authority allocation system of steering angle into the framework to allocate the corresponding weighting coefficients reasonably and output the final desired steering angle according to the current deviation of vehicle and the accuracy of steering angles. Besides, the active disturbance rejection controller &#x0028 ADRC &#x0029 is also added in the frame in order to track the desired steering angle fleetly and accurately as well as restrain the internal and external disturbances effectively which including the steering friction torque, wind speed and ground interference etc. Eventually, we validated the advantages of double loop framework through three sets of double lane change and slalom experiments, respectively. Exactly as we expected, the simulation results show that the double loop structure can effectively reduce the lateral displacement error caused by the driver or the controller, significantly improve the tracking precision and keep great performance in trajectory tracking characteristics when driving errors occur in one of driver and controller.

Robust controller design for trajectory tracking of autonomous vehicle

In order to improve the stability and fault tolerance of the control system of the autonomous vehicle in the middle and low speed lane changing, a dual loop weighted trajectory tracking robust control system is designed. Firstly, the lateral displacement transfer function and yaw angle transfer function are derived by combining the mathematical model of trajectory planning and vehicle motion, and the proportion integral differential (PID) control parameters are calculated by mathematical derivation and transfer function reduction. Then, the influence of weighting coefficient on system stability and its determination method are studied by simulation. The results show that the dual-loop weighted control is feasible and effective, and it could provide a good fault tolerance, good control ability, good tracking effect, and small lateral displacement error and yaw angular velocity error for lane changing conditions in the medium and low speed.

Robust controller design for trajectory tracking of autonomous vehicle

In order to improve the stability and fault tolerance of the control system of the autonomous vehicle in the middle and low speed lane changing, a dual loop weighted trajectory tracking robust control system is designed. Firstly, the lateral displacement transfer function and yaw angle transfer function are derived by combining the mathematical model of trajectory planning and vehicle motion, and the proportion integral differential (PID) control parameters are calculated by mathematical derivation and transfer function reduction. Then, the influence of weighting coefficient on system stability and its determination method are studied by simulation. The results show that the dual-loop weighted control is feasible and effective, and it could provide a good fault tolerance, good control ability, good tracking effect, and small lateral displacement error and yaw angular velocity error for lane changing conditions in the medium and low speed.

MPC-BASED steering control for backward-driving vehicle using stereo vision

We propose a steering control algorithm for autonomous backward driving in a narrow corridor. Passable spaces are detected using a stereo camera, and the steering angle is controlled by a model predictive controller (MPC). For passable space detection, an UV-disparity map is calculated from the original disparity map. Information regarding passable spaces collected by the stereo camera is used in steering control. Backward driving requires the driver’s preemptive actions, which can be learned by experience because of the non-intuitive responses (the initial motion of the vehicle is opposite to the driver’s steering angle input). This occurs because a backward-driving vehicle is a non-minimum phase system. One of the most popular steering control algorithms is Stanley method, which is based on the feedback of lateral displacement error and heading angle error. The method is very intuitive and works well for forward driving, but it exhibits significant undershoot for backward driving cases. Furthermore, the method does not explicitly consider any constraints on control inputs and states. We designed a steering controller based on the MPC technique that requires future information but can handle constraints explicitly. Because we have near-future information from the stereo camera under limited passable spaces, MPC can be effectively implemented. We performed several simulations and experiments to show the performance and superiority of the suggested method over a simple feedback-based control algorithm.

A robust stabilization method for a saturated LPV system : application to the lateral dynamics of vehicles.

This paper deals with the active control with steering angle saturation constraint in vehicle to improve the safety and its stability. The reference tracking problem is addressed by minimizing both the lateral displacement and velocity errors. The vehicle dynamics is represented by a saturated input LPV (Linear Parameter Varying) system, affected by disturbances / uncertainties to be rejected. The corresponding state-space model considers both polytopic and norm-bounded uncertainties. It is aimed to compute a static output feedback gain, so as to place the set of all eigenvalues of the uncertain closed-loop state matrix AC in a disc, denoted by VD, while minimizing the effect of the disturbances on the system. This paper proposes an original technique, based on the resolution of CM1, to compute the gain matrix of the control law which can be structured as the parameters of a robust PID controller. In order to highlight the performance of the proposed control algorithm, numerical simulations are performed.

Design and validation of a robust immersion and invariance controller for the lateral dynamics of intelligent vehicles

This paper focuses on the lateral control of intelligent vehicles; the aim is to minimize the lateral displacement of the autonomous vehicle with respect to a given reference path. The control input is the steering angle and the output is the lateral displacement error. We present the design and validation of a robust lateral controller based on the Immersion and Invariance (I&I) principle in order to ensure robust stability and good performances with respect to parametric variations and uncertainties that are encountered in driving applications. To validate our control law, tests were performed on SCANeR Studio, a driving simulation engine, according to several real driving scenarios. Simulations were also performed using experimental data acquired by the DYNA vehicle (a Peugeot 308) belonging to the Heudiasyc laboratory. The validation demonstrates the robustness and good performances of the proposed control approach and clearly shows the improvement due to the I&I controller.

Performance metrics and design considerations for a free-space optical orbital-angular-momentum–multiplexed communication link

The capacity of free-space optical (FSO) communication links could potentially be increased by the simultaneous transmission of multiple orbital angular momentum (OAM) beams. For such an OAM multiplexing approach, one requires the collection of adequate power as well as proportion of the phase front for a system with minimal crosstalk. Here we study the design considerations for an OAM-multiplexed free-space data link, analyzing the power loss, channel crosstalk, and power penalty of the link in the case of limited-size receiver apertures and misalignment between the transmitter and the receiver. We describe the trade-offs for different transmitted beam sizes, receiver aperture sizes, and mode spacing of the transmitted OAM beams under given lateral displacements or receiver angular errors. Through simulations and some experiments, we show that (1) a system with a larger transmitted beam size and a larger receiver aperture is more tolerant to lateral displacement but less tolerant to the receiver angular error, and (2) a system with a larger mode spacing, which uses larger OAM charges, suffers more system power loss but less channel crosstalk; thus, a system with a small mode spacing shows a lower system power penalty when system power loss dominates (e.g., a small lateral displacement or receiver angular error), whereas that with a larger mode spacing shows a lower power penalty when channel crosstalk dominates (e.g., a larger lateral displacement or receiver angular error). This work could be beneficial to the practical implementation of OAM-multiplexed FSO links.

Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver–AFS interactive steering control

This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver–AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy.

Double look-ahead reference point control for autonomous agricultural vehicles

A simple automatic path tracking system is developed to satisfy the typical requirements of an unmanned agricultural tractor application based on two look-ahead reference points (2-LARP) on the desired path. The main objective of the proposed control system is to track a desired path within reasonable tolerances of a typical farming process including considerable slippage. The employed look-ahead reference points provide compensation for the centrifugal forces and reduction of the peak lateral deviation due to curvature transition, using only simple arithmetic operations. Extensive numerical tests were carried out on the computer simulation of the system dynamics driven by the proposed control method. Simulation results indicate enhancements in vehicle manoeuvrability. Tests indicated that the peak lateral displacement error at the curvature transitions is reduced to one fifth of single LARP error. ► Simple path tracking for agricultural vehicles using 2 look-ahead reference points. ► Lateral deviations similar to an exponentially decaying 6th order dynamic system. ► One look-ahead reference compensates for centrifugal forces over large speed range. ► Second look-ahead reference reduces the peak deviation at curvature transitions. ► The proposed controller reduces the peak error at curvature transitions.

Effect of taper tension profile on the telescoping in a winding process of high speed roll to roll printing systems

Winding is an integral operation in almost every roll to roll system. A center-wound roll is one of the suitable and general schemes in a winding mechanism. In general, the quality of wound roll is known to be related to the lateral displacement error and starring defect of a wound roll. Especially, a telescoping within a center-wound roll can cause damages such as misalignment between layers, folding, wrinkle, etc. Taper tension is known to be one of the major factors which affect the shape of a wound roll. It is therefore necessary to analyze the relationship between taper tension profile and telescoping within the center-wound roll to prevent winding failure and to sustain high quality of the printed materials. It is hard to compensate for undesirable winding roll shapes such as telescoping, because a winding is commonly a final process in roll to roll systems and has no feedback control mechanism to correct winding roll shape directly during winding operation. Therefore, an optimal taper tension profile and the accurate control of it in a winding section could be one way to shape the fail-safe of a wound roll. Through the correlation between taper tension profile and telescoping in a winding process, a mathematical model for the telescoping due to tension distribution in cross machine direction was developed, and verified by experimental study. A new logic to determine the proper taper tension profile was designed by combining and analyzing the winding mechanism which includes nip induced tension model, relationship between taper tension profile and telescoping, relationship between taper value and telescoping. Numerical simulations and experimental results show that the proposed method is very useful for determining the desirable taper tension profile during the winding process and preventing defects of winding roll shape such as telescoping.

A method for sub-pixel scale feature-tracking using Radarsat images applied to the Mertz Glacier Tongue, East Antarctica

Tracking features between pairs of satellite synthetic aperture radar (SAR) images using image cross-correlation methods is a powerful tool for defining regions of image movement such as ice flow of Antarctic glaciers. Unlike optical images, processed SAR images have various instrumental effects such as view angle distortions and lateral displacement errors caused by slant range mapping. Co-registration issues are problematic and need to be addressed if there are few/no suitable stationary tie points at or near sea level within the images. Methods are presented that use Radarsat ScanSAR images to reliably measure sub-pixel displacements with errors of ≲ ± 0.25 pixels but this estimate is target dependent. The techniques and issues are illustrated using examples from a long-term study of the Mertz Glacier Tongue in East Antarctica. For image pairs only a few days apart, this extensive structure forms an excellent grid-like test pattern which provides up to 5000 valid correlation matches. Images separated by 100's of days can then be processed in the same way to reveal many subtle and some large changes over time. The technique described is robust and may be widely applicable.