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Driving simulator study of the relationship between motion strategy preference and self-reported driving behavior

SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL 2021年第9期97卷 619-633页

作者： Rengifo, Carolina Chardonnet, Jean-Remy Mohellebi, Hakim Paillot, Damien Kemeny, Andras Renault 1 Ave Golf F-78280 Guyancourt France UBFC LISPEN Arts & Metiers EA7515 HESAM Inst Image Besancon France

Faithful motion restitution in driving simulators normally focuses on track monitoring and maximizing the platform workspace by leaving aside the principal component-the driver. Therefore, in this work we investigated the role of the motion perception model on motion cueing algorithms from a user's viewpoint. We focused on the driving behavior influence regarding motion perception in a driving simulator. Participants drove a driving simulator with two different configurations: (a) using the platform dynamic model and (b) using a supplementary motion perception model. Both strategies were compared and the participants' data were classified according to the strategy they preferred. To this end, we developed a driving behavior questionnaire aiming at evaluating the self-reported driving behavior influence on participants' motion cueing preferences. The results showed significant differences between the participants who chose different strategies and the scored driving behavior in the hostile and violations factors. In order to support these findings, we compared participants' behaviors and actual motion driving simulator indicators such as speed, jerk, and lateral position. The analysis revealed that motion preferences arise from different reasons linked to the realism or smoothness in motion. Also, strong positive correlations were found between hostile and violation behaviors of the group who preferred the strategy with the supplementary motion perception model, and objective measures such as jerk and speed on different road segments. This indicates that motion perception in driving simulators may depend not only on the type of motion cueing strategy, but may also be influenced by users' self-reported driving behaviors.

关键词： motion perception driving behavior motion cueing algorithm driving simulation

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Handiski simulator performance under PSO-based washout and control parameters optimization

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NONLINEAR DYNAMICS 2022年第1期110卷 649-667页

作者： Houda, Taha Beji, Lotfi Amouri, Ali Mallem, Malik ESIEE IT 8 Rue Pierre de Coubertin F-95300 Pontoise France Univ Paris Saclay Evry IBISC EA4526 Lab 34 Rue Pelvoux F-91080 Evry Courcouronnes France

The transfer of advanced technology to the person with a disability who wishes to practice a sporting activity is gaining momentum in the science/engineering world. This paper seeks to approve more comfort and sensations for people with paraplegia on a motion simulation platform during a ski operation. The motion cueing algorithm (MCA) has proven itself for sensation reproduction, which we propose to improve by integrating the physical limits of our 8-DoF mechatronics platform. An extended classical MCA is proposed to respond to the significant lack of restored sensation in the intermediate frequency range. A Particle Swarm Optimization (PSO) is constructed to perform optimal washout filter parameters and control law parameters. Consequently, the reproduced skier trajectory stability is obtained. The results show that the proposed algorithm will overcome the physical limitation problem in the Handiski simulator, improve the realism of movement sensation, and reduce the false cues to enhance dynamic fidelity.

关键词： Handiski motion simulator motion cueing algorithm Disabled people PSO Sliding mode control Washout filter

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

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2022年第0期108卷 104564-104564页

作者： Qazani, Mohammad Reza Chalak Asadi, Houshyar Mohamed, Shady Lim, Chee Peng Nahavandi, Saeid Deakin Univ Inst Intelligent Syst Res & Innovat Geelong Vic 3125 Australia

To experience the motion sensation of a real vehicle through a motion simulator, a motion cueing algorithm (MCA) is required to transform the vehicle motions to the driving motion platform (DMP) while respecting the physical limitations of DMP. In this aspect, the optimal washout filter (WF) extracts the optimal motion signals including linear accelerations and angular velocities for the DMP with consideration of the human vestibular model and DMP motion states using the linear quadratic regulator (LQR) technique. The LQR technique is employed to obtain the optimal and pre-defined higher order transfer functions by solving the Riccati equation. However, the Riccati equation is solved using fixed weights, leading to an inconvenient usage of the DMP workspace. In this research, a new optimal WF model is designed and developed using a neural network (NN) and a fuzzy logic controller (FLC). The NN is introduced to solve the Riccati equation online while the FLC model is designed to extract the weighting matrices of the LQR technique. The proposed technique considers the physical DMP limitations online and reproduces accurate motion signals with a high degree of fidelity. The results demonstrate the efficiency of the developed optimal WF model as compared with those of existing optimal WF models.

关键词： motion cueing algorithm Optimal washout filter Time-varying weights Fuzzy logic controller Riccati equation Neural network

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Numerical comparison of offline motion-cueing algorithms for the ride simulator robocoaster and auto-tuning parameters 2nd

Numerical comparison of offline motion-cueing algorithms for...

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2nd Annual International Conference on Material, Machines and Methods for Sustainable Development, MMMS 2020

作者： Pham, Duc-An Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9783030696092

motion cueing algorithms (MCAs) are the cheating technique to drive physical simulators along offline-generated trajectories such as to produce proper motion cues to the passenger by a combination of tilt gravity and translational acceleration components (so-called linear specific forces or "g-forces"). In this paper, the numerical perception quality of the aforementioned families of MCAs is compared for a virtual test ride along a simple S-shaped planar curve featuring solely lateral accelerations, using two previously published objective measures. To this end, the MCAs were implemented using originally published MCA parameter values and optimally tuned values concerning the test trajectory. The comparison shows large discrepancies between the different MCAs, both in terms of simulated motion perception and fulfillment of robot workspace constraints. The best-fit tuning of MCA parameters for a given trajectory may significantly improve the objective measures. In this study, a new auto-tuning method based on a generic optimal method called mean variance mapping optimization to minimize the performance indicator was introduced to find the off-line optimal algorithm’s tuned parameters. Three testbeds using the auto-tuning process show different tuned parameter sets, however, the off-line optimal MCA has a similar response with all set of tuned parameters. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Auto-tuning parameters motion cueing algorithm Objective critera

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Prepositioning of a Land Vehicle Simulation-Based motion Platform Using Fuzzy Logic and Neural Network

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年第10期69卷 10446-10456页

作者： Qazani, Mohammad Reza Chalak Asadi, Houshyar Mohamed, Shady Nahavandi, Saeid Deakin Univ Inst Intelligent Syst Res & Innovat Geelong Vic 3125 Australia

The motion cueing algorithms (MCAs) is the method that reproduces the motion sensation of the real vehicle for the users of simulation-based motion platforms (SBMPs). Classical MCA is the most common type of MCA due to its simplicity, easy tunning procedure, and higher speed. The fixed neutral position of the SBMP restricts the available workspace and makes the motions of the platform conservative. Then, the high frequency motion inputs cannot be reproduced precisely using SBMP and it increases the motion sensation error between the SBMP and real vehicle driver. The main objective of this study is to enlarge the reachable workspace of the SBMP adaptively using the new prepositioning technique based on fuzzy logic and artificial neural network (ANN). Prepositioning of the SBMPs to an off-centre point can increase the available linear space of the SBMPs based on different driving scenarios to decrease the motion sensation error. The fuzzy logic-based units are working based on the current position of the SBMP and the predicted motion signals. Therefore, the ANN is employed to forecast the motion signal of the SBMP on the finite history of input. The prepositioning of the SBMP using fuzzy logic and ANN is established for the first time in this research with consideration of the road information and vehicle motion information. The proposed method is performed and validated using MATLAB/Simulink and the outcomes show that using the new prepositioning method will lead to better driving sensation with less wrong motion sensation errors compared with the non and previous prepositioning methods.

关键词： Acceleration Vehicles Artificial neural networks Fuzzy logic Roads History Mathematical model motion cueing algorithm prepositioning fuzzy logic artificial neural network simulation-based motion platform

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Adaptive Washout Filter Based on Fuzzy Logic for a motion Simulation Platform With Consideration of Joints' Limitations

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年第11期69卷 12547-12558页

作者： Chalak Qazani, Mohammad Reza Asadi, Houshyar Bellmann, Tobias Mohamed, Shady Lim, Chee Peng Nahavandi, Saeid Deakin Univ Inst Intelligent Syst Res & Innovat Geelong Vic 3125 Australia German Aerosp Ctr Inst Syst Dynam & Control Space Syst Dynam Deutsch Zentrum Luft & Raumfahrt DLR D-82234 Oberpfaffenhofen Germany

motion simulation platforms (MSPs) are widely used to generate driving/flying motion sensations for the users. The MSPs have a restricted workspace area due to the dynamical and physical restrictions of the motion Platforms active joints as well as the physical limitations of its passive joints. The motion cueing algorithm (MCA) is the reproduction of the motion signal including linear accelerations and angular velocities. It aims to simultaneously respect the MSP's workspace limitations and make the same motion feeling for the user as a real vehicle. The Classical washout filter (WF) is a well-known type of MCA. The classical WF is easy to set-up, offers a low computational burden and high functionality but has some major drawbacks such as fixed WF parameters tuned according to worst-case scenarios and no consideration of the human vestibular system. As a result, adaptive WFs were developed to consider the human vestibular system and enhance the efficiency of the method using time-varying filters. The existing adaptive WFs only cogitate the boundaries of the end-effector in the Cartesian coordinate space as a substitute for the active and passive joints limitations, which is MSP's main limiting factor. This conservative assumption reduces the available workspace area of the MSP and increases the motion sensation error for the MSPs user. In this study, a fuzzy logic-based WF is developed, to consider the dynamical and physical boundaries of the active joints as well as the physical boundaries of the passive joints. A genetic algorithm is used to select the membership functions' values of the active and passive joints' boundaries. The model is designed using MATLAB /Simulink and the outcomes demonstrate the efficiency of the proposed method versus existing adaptive WFs.

关键词： Acceleration Fuzzy logic Low pass filters Legged locomotion Vehicles Cutoff frequency Adaptation models motion cueing algorithm fuzzy logic dynamical and physical limitations hexapod platform human sensation error washout filter (WF) genetic algorithm

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MODEL PREDICTIVE motion cueing algorithm FOR A TRUCK SIMULATOR

MODEL PREDICTIVE MOTION CUEING ALGORITHM FOR A TRUCK SIMULAT...

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European Simulation and Modelling Conference (ESM 2013)

作者： Thoendel, E. Czech Tech Univ Dept Elect Drives & Tract Prague 16627 Czech Republic

ISBN: (纸本)9789077381793

The paper looks at the possibilities of applying a model predictive control (MPC) algorithm to control and optimize the motion cueing algorithm (MCA) employed in state-of-the-art simulators for the purposes of reproducing motion effects (in particular acceleration). Typically, MCAs feature a large number of parameters which need to be configured with respect to both the kinematic and dynamic limitations of the motion platform used and the human motion perception thresholds. When an MPC algorithm is employed, these constraints can be fully respected and the ultimate results can, at least in a sense, be considered optimal. The paper shows the possibilities of interlinking MPC with MCA to dynamically adjust the applicable constraints. In addition, all theoretical results will be verified by means of simulations. Since the research described in this paper has been conducted as part of an advanced truck simulator project pursued by the author the parameters chosen for all simulations respect the properties of the motion platform employed in this project.

关键词： motion cueing algorithm washout algorithm Model Predictive Control simulator truck simulator motion platform

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A Case Study on Vestibular Sensations in Driving Simulators

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SENSORS 2022年第15期22卷 5837-5837页

作者： Riera, Jose, V Casas, Sergio Alonso, Francisco Fernandez, Marcos Univ Valencia Higher Tech Sch Engn Comp Sci Dept Valencia 46010 Spain Univ Valencia Inst Robot Informat Technol & Commun Res IRTIC Valencia 46010 Spain Univ Valencia Fac Psychol Valencia 46010 Spain Univ Valencia Res Inst Traff & Rd Safety INTRAS Valencia 46010 Spain

motion platforms have been used in simulators of all types for several decades. Since it is impossible to reproduce the accelerations of a vehicle without limitations through a physically limited system (platform), it is common to use washout filters and motion cueing algorithms (MCA) to select which accelerations are reproduced and which are not. Despite the time that has passed since their development, most of these algorithms still use the classical washout algorithm. In the use of these MCAs, there is always information that is lost and, if that information is important for the purpose of the simulator (the training simulators), the result obtained by the users of that simulator will not be satisfactory. This paper shows a case study where a BMW 325Xi AUT fitted with a sensor, recorded the accelerations produced in all degrees of freedom (DOF) during several runs, and data have been introduced in mathematical simulation software (washout + kinematics + actuator simulation) of a 6DOF motion platform. The input to the system has been qualitatively compared with the output, observing that most of the simulation adequately reflects the input to the system. Still, there are three events where the accelerations are lost. These events are considered by experts to be of vital importance for the outcome of a learning process in the simulator to be adequate.

关键词： driving simulator motion platform motion cueing algorithm washout filter car characterization vestibular perception

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Increasing motion Fidelity in Driving Simulators Using a Fuzzy-Based Washout Filter

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2019年第2期4卷 298-308页

作者： Asadi, Houshyar Lim, Chee Peng Mohamed, Shady Nahavandi, Darius Nahavandi, Saeid Deakin Univ Inst Intelligent Syst Res & Innovat Geelong Vic 3216 Australia

The motion cueing algorithm is the procedure used to regenerate vehicle motion cues by transforming translational and rotational motions of a simulated vehicle into the simulator motion such that high fidelity motions can be generated through a washout filter. Classical washout filters are widely being used in different motion simulators because of their low computational load, simplicity, and functionality. However, they have a number of disadvantages that make them unreliable in some cases. One of themain disadvantages is its parameter selecting procedure, which is based on trial-and-error and the worst case driving scenario. In addition, the washout filter parameters are kept constant during different driving scenarios, causing inflexibility of the filter design. This causes conservative platform workspace usage and as a result false motion cues. Furthermore, the mathematical model of human motion sensation plays no role in designing of the classical washout filter. Ignorance of the online information about physical limitations of the platform and the simulator driver motion sensation factors are other main drawbacks of classical washout filters. The aim of this research is to provide a fuzzy logic-based washout filter that considers the motion sensation error between the real vehicle and simulator drivers as well as the distance of the simulator platform from its physical boundaries to correct false motion cues and decrease human sensation errors. The proposed fuzzy-based washout filter also seeks to increase motion fidelity and enable the simulator to use the platform workspace more efficiently. The simulation results show the efficiency of the proposed fuzzy-based washout filter in reducing the human sensation error and enhancing efficiency of the simulator platform workspace usage.

关键词： motion cueing algorithm fuzzy logic human sensation error washout filter

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Improvement of the driving simulator control and comparison between driver-road-vehicule interaction in real and simulated environment: Amélioration de la commande du simulateur de conduite et comparaison entre l'interaction conducteur-véhicule-route dans un environnement réel et simulé

Improvement of the driving simulator control and comparison ...

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作者： Ghasemi, Navid Université Paris-Est

学位级别：博士

Les activités de recherche ont été menées en collaboration avec l'Université de Bologne, l'Université Paris-Est et l'Université Gustave Eiffel sous la forme d'un doct... 详细信息

Les activités de recherche ont été menées en collaboration avec l'Université de Bologne, l'Université Paris-Est et l'Université Gustave Eiffel sous la forme d'un doctorat cotutelle. Les activités sont divisées en deux macro-domaines ; les études de simulation de conduite réalisées à l'Université Gustave Eifel (IFSTTAR) et les expériences sur route organisées par l'Université de Bologne. La première partie de la recherche se concentre sur l'amélioration de la fidélité physique du simulateur de conduite à deux degrés de liberté avec une attention particulière aux signaux de mouvement et au modèle de dynamique du véhicule. Ce dernier a été développé dans MATLAB-Simulink et a la capacité de calculer en temps réel les états du véhicule et de contrôler la plateforme de mouvement. Au cours de cette phase de la recherche, des algorithmes de repères de mouvement ont été développés pour contrôler les mouvements du simulateur et l'effet des signaux de mouvement sur le comportement des conducteurs a été analysé par expérimentation. Les résultats de ces études sont discutés dans les cas d’études I et II. Dans la deuxième partie de la recherche, les performances du conducteur et le comportement visuel ont été étudiés sur la route sous différents scénarios. Le comportement visuel du conducteur a été enregistré à l'aide d'un dispositif de suivi oculaire monté sur la tête, tandis que la trajectoire du véhicule a été enregistrée avec un véhicule instrumenté équipé du système de positionnement mondial. Au cours de cette phase, plusieurs études de cas ont été développées pour surveiller le comportement des conducteurs en milieu naturaliste. La cas d'étude III vise à intégrer l'audit de sécurité routière traditionnel à un système innovant de surveillance du comportement des conducteurs. L’expérimentation sur route avec des conducteurs a été réalisée sur une artère urbaine afin d'évaluer l'approche proposée à travers des techniques innovantes de suivi des conducteurs. Ces mêmes instrumen

关键词： Simulation de véhicule en temps réel algorithme de restitution de mouvement Mesures de sécurité de substitution Oculomètre Perception Temps de réaction Real-Time vehicle simulation motion cueing algorithm Surrogate safety measures Eye-Tracking Perception Reaction Time

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