scholarly journals MPC-Based Motion-Cueing Algorithm for a 6-DOF Driving Simulator with Actuator Constraints

Vehicles ◽  
2020 ◽  
Vol 2 (4) ◽  
pp. 625-647
Author(s):  
Yash Raj Khusro ◽  
Yanggu Zheng ◽  
Marco Grottoli ◽  
Barys Shyrokau
Keyword(s):  
Driving Simulator ◽  
Motion Platform ◽  
Driver Training ◽  
Human Machine Interaction ◽  
Reference Tracking ◽  
Motion Cues ◽  
Adaptive Weights ◽  
Washout Filter ◽  
Motion Cueing ◽  
And Performance

Driving simulators are widely used for understanding human–machine interaction, driver behavior and in driver training. The effectiveness of simulators in this process depends largely on their ability to generate realistic motion cues. Though the conventional filter-based motion-cueing strategies have provided reasonable results, these methods suffer from poor workspace management. To address this issue, linear MPC-based strategies have been applied in the past. However, since the kinematics of the motion platform itself is nonlinear and the required motion varies with the driving conditions, this approach tends to produce sub-optimal results. This paper presents a nonlinear MPC-based algorithm which incorporates the nonlinear kinematics of the Stewart platform within the MPC algorithm in order to increase the cueing fidelity and use maximum workspace. Furthermore, adaptive weights-based tuning is used to smooth the movement of the platform towards its physical limits. Full-track simulations were carried out and performance indicators were defined to objectively compare the response of the proposed algorithm with classical washout filter and linear MPC-based algorithms. The results indicate a better reference tracking with lower root mean square error and higher shape correlation for the proposed algorithm. Lastly, the effect of the adaptive weights-based tuning was also observed in the form of smoother actuator movements and better workspace use.

scholarly journals MPC-Based Motion Cueing Algorithm for a 6 DOF Driving Simulator with Actuator Constraints

2020 ◽  
Author(s):  
Yash Raj Khusro ◽  
Yanggu Zheng ◽  
Marco Grottoli ◽  
Barys Shyrokau
Keyword(s):  
Driving Simulator ◽  
Motion Platform ◽  
Driver Training ◽  
Human Machine Interaction ◽  
Reference Tracking ◽  
Motion Cues ◽  
Adaptive Weights ◽  
Washout Filter ◽  
Motion Cueing ◽  
And Performance

Driving simulators are widely used for understanding human-machine interaction, driver behavior and in driver training. The effectiveness of simulators in these process depends largely on their ability to generate realistic motion cues. Though the conventional filter-based motion cueing strategies have provided reasonable results, these methods suffer from poor workspace management. To address this issue, linear MPC-based strategies have been applied in the past. However, since the kinematics of the motion platform itself is non-linear and the required motion varies with the driving conditions, this approach tends to produce sub-optimal results. This paper presents a nonlinear MPC-based algorithm which incorporates the nonlinear kinematics of the Stewart platform within the MPC algorithm in order to increase the cueing fidelity and utilize maximum workspace. Further, adaptive weights-based tuning is used to smoothen the movement of the platform towards its physical limits. Full-track simulations were carried out and performance indicators were defined to objectively compare the response of the proposed algorithm with classical washout filter and linear MPC-based algorithms. The results indicate a better reference tracking with lower root mean square error and higher shape correlation for the proposed algorithm. Lastly, the effect of the adaptive weights-based tuning was also observed in the form of smoother actuator movements and better workspace utilization.

Actuator Constrained Motion Cueing Algorithm for a Redundantly Actuated Stewart Platform

2016 ◽  
Vol 138 (6) ◽  
Author(s):  
Justin Pradipta ◽  
Oliver Sawodny
Keyword(s):  
Optimization Problem ◽  
Flight Simulation ◽  
Constrained Motion ◽  
Motion Platform ◽  
Case Scenario ◽  
Worst Case ◽  
Motion Cues ◽  
Motion Cueing ◽  
Redundantly Actuated ◽  
Relationship Of

An improved method to provide a motion trajectory for full flight simulator to simulate the acceleration during a flight simulation is presented. The motion cueing trajectory is based on a constrained optimization problem, with the generated optimal acceleration cues subjected to the actuators travel constraints of the motion platform. The motion platform researched in this contribution is a redundantly actuated parallel manipulator, therefore the available workspace is more limited and the actuator constraints become more complex. The differential kinematic analysis is utilized in the optimization problem to define the relationship of the acceleration in the platform coordinate and in the actuator coordinates. An acceleration profile is defined in function of the actuator travel to create a strict acceleration constraint in the actuator coordinate, thus a strict travel constraint. The algorithm is tested in a simulation and implemented in a full size redundantly actuated motion platform. Measurement results show that the proposed new motion cueing algorithm (MCA) is able to keep the actuators within their travel limit and at the same time provide the correct motion cues for the simulator pilots. The need to tune the MCA for the worst case scenario which is necessary to avoid damage to the platform, while at the same time can be disadvantageous for the normal case use, is relieved by the utilization of the online optimization process.

scholarly journals A Design of Nonlinear Scaling and Nonlinear Optimal Motion Cueing Algorithm for Pilot's Station

2021 ◽  
Vol 26 (6) ◽  
pp. 513-520
Author(s):  
Daoyang ZHU ◽  
Jun YAN ◽  
Shaoli DUAN
Keyword(s):  
Motion Simulation ◽  
Motion Platform ◽  
Motion Simulator ◽  
Pitch Direction ◽  
Washout Filter ◽  
Motion Cueing ◽  
Physical Limitations ◽  
Rotational Motions ◽  
Simulator Motion ◽  
High Degree

Motion cueing algorithms (MCA) are often applied in the motion simulators. In this paper, a nonlinear optimal MCA, taking into account translational and rotational motions of a simulator within its physical limitation, is designed for the motion platform aiming to minimize human’s perception error in order to provide a high degree of fidelity. Indeed, the movement sensation center of most MCA is placed at the center of the upper platform, which may cause a certain error. Pilot’s station should be paid full attention to in the MCA. Apart from this, the scaling and limiting module plays an important role in optimizing the motion platform workspace and reducing false cues during motion reproduction. It should be used along within the washout filter to decrease the amplitude of the translational and rotational motion signals uniformly across all frequencies through the MCA. A nonlinear scaling method is designed to accurately duplicate motions with high realistic behavior and use the platform more efficiently without violating its physical limitations. The simulation experiment is verified in the longitudinal/pitch direction for motion simulator. The result implies that the proposed method can not only overcome the problem of the workspace limitations in the simulator motion reproduction and improve the realism of movement sensation, but also reduce the false cues to improve dynamic fidelity during the motion simulation process.

Motion Cueing Algorithms: A Review

2017 ◽  
Vol 1 (1) ◽  
pp. 90-106 ◽  
Author(s):  
Sergio Casas ◽  
Ricardo Olanda ◽  
Nilanjan Dey
Keyword(s):  
Predictive Control ◽  
Control Strategies ◽  
General Scheme ◽  
Level Control ◽  
Motion Platform ◽  
Motion Cues ◽  
Vehicle Simulation ◽  
Robotic Motion ◽  
Motion Cueing ◽  
High Level

Robotic motion platforms are commonly used in motion-based vehicle simulation. However, the reproduction of realistic accelerations within a reduced workspace is a major challenge. Thus, high-level control strategies commonly referred to as motion cueing algorithms (MCA) are required to convert the simulated vehicle physical state into actual motion for the motion platform. This paper reviews the most important strategies for the generation of motion cues in simulators, listing the advantages and drawbacks of the different solutions. The motion cueing problem, a general scheme and the four most common approaches – classical washout, adaptive washout, optimal control and model predictive control – are presented. The existing surveys of the state-of-the-art on motion cueing are usually limited to list the MCA or to a particular vehicle application. In this work, a comprehensive vehicle-agnostic review is presented. Moreover, evaluation and tuning of MCA are also considered, classifying the different methods, and providing examples of each class.

scholarly journals Comparative Analysis of Kinect-Based and Oculus-Based Gaze Region Estimation Methods in a Driving Simulator

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 26
Author(s):  
David González-Ortega ◽  
Francisco Javier Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez
Keyword(s):  
Virtual Reality ◽  
Comparative Analysis ◽  
Driving Simulator ◽  
Estimation Method ◽  
Estimation Methods ◽  
Gaze Estimation ◽  
Driving Simulators ◽  
Oculus Rift ◽  
Gaze Patterns ◽  
And Performance

Driver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.

Effect of Changing a Traffic Control Device Color on Driver Behavior and Perception across Different Age Groups

2021 ◽  
pp. 036119812110111
Author(s):  
Hatem Abou-Senna ◽  
Mohamed El-Agroudy ◽  
Mustapha Mouloua ◽  
Essam Radwan
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Driving Simulator ◽  
Age Groups ◽  
The United States ◽  
Time Of Day ◽  
General Purpose ◽  
Traffic Density ◽  
Driving Conditions ◽  
And Performance

The use of express lanes (ELs) in freeway traffic management has seen increasing popularity throughout the United States, particularly in Florida. These lanes aim at making the most efficient transportation system management and operations tool to provide a more reliable trip. An important component of ELs is the channelizing devices used to delineate the separation between the ELs and the general-purpose lane. With the upcoming changes to the FHWA Manual on Uniform Traffic Control Devices, this study provided an opportunity to recommend changes affecting safety and efficiency on a nationwide level. It was important to understand the impacts on driver perception and performance in response to the color of the EL delineators. It was also valuable to understand the differences between demographics in responding to delineator colors under different driving conditions. The driving simulator was used to test the responses of several demographic groups to changes in marker color and driving conditions. Furthermore, participants were tested for several factors relevant to driving performance including visual and subjective responses to the changes in colors and driving conditions. Impacts on driver perception were observed via eye-tracking technology with changes to time of day, visibility, traffic density, roadway surface type, and, crucially, color of the delineating devices. The analyses concluded that white was the optimal and most significant color for notice of delineators across the majority of subjective and performance measures, followed by yellow, with black being the least desirable.

A Driving Simulator Study of the Performance Effects of Low Blood Alcohol Concentration

1996 ◽  
Vol 40 (18) ◽  
pp. 943-946 ◽  
Author(s):  
R. Wade Allen ◽  
Zareh Parseghian ◽  
Anthony C. Stein
Keyword(s):  
Divided Attention ◽  
Driving Simulator ◽  
Blood Alcohol Concentration ◽  
Large Body ◽  
Alcohol Concentration ◽  
Blood Alcohol ◽  
Performance Effects ◽  
Driving Task ◽  
Simulator Study ◽  
And Performance

There is a large body of research that documents the impairing effect of alcohol on driving behavior and performance. Some of the most significant alcohol influence seems to occur in divided attention situations when the driver must simultaneously attend to several aspects of the driving task. This paper describes a driving simulator study of the effect of a low alcohol dose, .055 BAC (blood alcohol concentration %/wt), on divided attention performance. The simulation was mechanized on a PC and presented visual and auditory feedback in a truck cab surround. Subjects were required to control speed and steering on a rural two lane road while attending to a peripheral secondary task. The subject population was composed of 33 heavy equipment operators who were tested during both placebo and drinking sessions. Multivariate Analysis of Variance showed a significant and practical alcohol effect on a range of variables in the divided attention driving task.

An optimal washout filter for motion platform using neural network and fuzzy logic

2022 ◽  
Vol 108 ◽  
pp. 104564
Author(s):  
Mohammad Reza Chalak Qazani ◽  
Houshyar Asadi ◽  
Shady Mohamed ◽  
Chee Peng Lim ◽  
Saeid Nahavandi
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Motion Platform ◽  
Washout Filter

scholarly journals Influence of a new discrete-time LQR-based motion cueing on driving simulator

2013 ◽  
Vol 35 (4) ◽  
pp. 454-467 ◽  
Author(s):  
B. Aykent ◽  
F. Merienne ◽  
D. Paillot ◽  
A. Kemeny
Keyword(s):  
Discrete Time ◽  
Driving Simulator ◽  
Motion Cueing

Evaluation of Pc-Based Younger Driver Training Program: Use of a Driving Simulator

1998 ◽  
Vol 42 (20) ◽  
pp. 1403-1407 ◽  
Author(s):  
Donald L. Fisher ◽  
Robert Glaser ◽  
Nancy E. Laurie ◽  
Alexander Pollatsek ◽  
John F. Brock
Keyword(s):  
Traffic Safety ◽  
Driving Simulator ◽  
Preliminary Evaluation ◽  
Driver Education ◽  
Driver Training ◽  
Younger Adults ◽  
Trained Subjects ◽  
University Of Massachusetts ◽  
Pedestrian Crossing ◽  
The University

Younger adults are overinvolved in accidents. Model high school driver education programs were developed in the 1970s in an attempt to reduce this overinvolvement. An evaluation of these programs suggested that they were largely ineffective. Recently, the AAA Foundation for Traffic Safety has developed the first PC-based driver education program (Zero Errors Driving or Driver ZED) using real footage of risky scenarios. The hope is that younger drivers seeing these scenarios will learn to recognize risky situations in the real world before they develop. In an attempt to evaluate the Driver ZED program, the performance of 20 younger drivers is being tested on the University of Massachusetts' driving simulator. Ten of these drivers have been trained with ZED (the trained group) and ten have not seen the program (the untrained group). All 20 drivers must navigate a total of 24 scenarios that have been programmed on the driving simulator. Measures of driving performance were developed which can be used to discriminate between risky and nonrisky drivers. A preliminary evaluation of the performance of the trained and untrained subjects indicates that the trained subjects are performing more cautiously than the untrained subjects in some, but not all, scenarios (e.g., the trained subjects brake sooner when approaching a pedestrian crossing).

Sign in / Sign up

Export Citation Format

Share Document