A New Prepositioning Technique of a Motion Simulator Platform Using Nonlinear Model Predictive Control and Recurrent Neural Network

Qazani, Mohammad Reza Chalak; Asadi, Houshyar; Zhang, Li; Tabarsinezhad, Farzin; Mohamed, Shady; Lim, Chee Peng; Nahavandi, Saeid

doi:10.1109/tits.2022.3195964

Cited by 11 publications

(2 citation statements)

References 41 publications

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“…Motion simulation platforms (MSPs) are widely used for simulating translational accelerations and angular velocities of vehicles [1]- [4]. Among many kinds of the MSPs, six degrees of freedom (6-DOF) platforms are widely investigated by researchers [5]- [7]. However, there are some disadvantages of the 6-DOF stewart platforms, such as difficult forward kinematics, too expensive cost, large space occupation and so on [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

A novel structure of vehicle motion cueing algorithm for a pneumatic motion simulation platform

Liu,

Li,

Zhao

2024

Preprint

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In this paper, a novel structure of motion cueing algorithm (MCA) is proposed to simulate translational accelerations and angular velocities of vehicles on a pneumatic motion simulation platform (PMSP). The designed MCA includes nonlinear scaling algorithm, linear quadraticregulator (LQR), low pass filter and data fusion algorithm.Taking into account absolute sensory thresholds of human vestibular organ, the nonlinear scaling algorithm is designed to scale the translational accelerations and angular velocities of vehicles for ensuring the outputs of the MCA are inangular displacement ranges of the PMSP. According to the model of otolith organ and semicirular canal, the LQR ispresented to constrain the perception errors between the vehicles and PMSP. The data fusion algorithm is proposed to obtain desired angular displacement of the PMSP from the outputs of the nonlinear scaling algorithm for reducing perception errors. Considering the ranges of deflection angleand angular velocity on the PMSP, perception errors and absolute sensory thresholds, gains of the MCA are optimized by genetic algorithm. Note that the designed MCA can notonly be applied to the PMSP, but also be extended to the classical 6-degree-of-freedom platform for improving simulation performance. Finally, the effectiveness of the proposed algorithm is verified by real experiment using an active disturbance rejection controller.

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Section: Introductionmentioning

confidence: 99%

A novel structure of vehicle motion cueing algorithm for a pneumatic motion simulation platform

Liu,

Li,

Zhao

2024

Preprint

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“…Nonetheless, the motion fidelity aspect is a remaining limitation that the driving simulator research field faces [ 10 , 11 ], despite the continuous efforts invested in the enhancement of the motion platform using advanced Artificial Intelligence techniques, including Machine Learning (ML) algorithms [ 12 , 13 , 14 ]. To tackle this challenge, evaluating the realism and accuracy of existing motion platforms is first necessary.…”

Section: Introductionmentioning

confidence: 99%

Fidelity Assessment of Motion Platform Cueing: Comparison of Driving Behavior under Various Motion Levels

Hamdani

Bouchner

Kunclova

et al. 2023

Sensors

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The present paper focuses on vehicle simulator fidelity, particularly the effect of motion cues intensity on driver performance. The 6-DOF motion platform was used in the experiment; however, we mainly focused on one characteristic of driving behavior. The braking performance of 24 participants in a car simulator was recorded and analyzed. The experiment scenario was composed of acceleration to 120 km/h followed by smooth deceleration to a stop line with prior warning signs at distances of 240, 160, and 80 m to the finish line. To assess the effect of the motion cues, each driver performed the run three times with different motion platform settings–no motion, moderate motion, and maximal possible response and range. The results from the driving simulator were compared with data acquired in an equivalent driving scenario performed in real conditions on a polygon track and taken as reference data. The driving simulator and real car accelerations were recorded using the Xsens MTi-G sensor. The outcomes confirmed the hypothesis that driving with a higher level of motion cues in the driving simulator brought more natural braking behavior of the experimental drivers, better correlated with the real car driving test data, although exceptions were found.

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A Development of Time-Varying Weight Model Predictive Control for Autonomous Vehicles

Qazani,

Asadi,

Shajari

et al. 2023

2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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A New Prepositioning Technique of a Motion Simulator Platform Using Nonlinear Model Predictive Control and Recurrent Neural Network

Cited by 11 publications

References 41 publications

A novel structure of vehicle motion cueing algorithm for a pneumatic motion simulation platform

A novel structure of vehicle motion cueing algorithm for a pneumatic motion simulation platform

Fidelity Assessment of Motion Platform Cueing: Comparison of Driving Behavior under Various Motion Levels

A Development of Time-Varying Weight Model Predictive Control for Autonomous Vehicles

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