Study On The Evaluation Of Motion Cueing Algorithm In Vehicle Driving Simulator

Driving simulators are becoming more and more popular due to the needs of vehicle design and development,performance evaluation,driver training,etc.As the core technology of driving simulator,the motion cueing algorithm is to convert the vehicle motion signal into the position and pose signal of the driving simulation platform.As an indispensable part of the driving simulator,the evaluation of the motion cueing algorithms plays a pivotal role in the automatic tuning,evaluation and comparison of the motion cueing algorithms.However,there is still no universally recognized effective mechanism as the standard solution for the evaluation of the motion cueing algorithms at present.In order to solve this problem,the objective evaluation method of the motion cueing algorithms is researched and improved in this paper.Driving simulation platform and motion perception system analysis.In this paper,the basic structure,kinematic inversion and working space of the Stewart platform selected for this project are analyzed,and then the human motion perception system is analyzed and modeled,which lays a foundation for the research of the motion cueing algorithm and the improvement of the objective evaluation method of the motion cueing algorithm.The establishment of the objective evaluation index system of the motion cueing algorithms.By analyzing the advantages and disadvantages of the existing motion cueing algorithms’ evaluation methods and the development process of the motion cueing algorithms,a motion cueing algorithms’ evaluation system focusing on perceived fidelity and working space utilization of the motion platform is proposed.In addition,by introducing a more advanced visual-vestibular interaction perception system and head tilt angle perception system,the model of human motion perception system in the evaluation of perceptual realism is improved.After that,the normalized average absolute error,normalized Pearson correlation coefficient,working space utilization and comprehensive performance evaluation indicators of washing out algorithm are proposed,and an evaluation index system is established based on the combined weighting method of CRITIC method and gray correlation analysis method,and the weight of each index is determined.Parameter optimization of classical motion cueing algorithm based on adaptive genetic algorithm.Based on the adaptive genetic algorithm,a multi-objective optimization model is established with the specific force and angular velocity perception error as the goal,and the parameters of the classical motion cueing algorithm are multi-objective optimized.In addition,the motion cueing algorithms optimized by different algorithms is evaluated and compared by using the motion cueing algorithms’ evaluation system presented in this paper,and the simulation results show that compared with the traditional single-objective optimization motion cueing algorithm method,the motion cueing algorithm based on adaptive genetic algorithm optimization brings better motion cue quality and less false perception.The objective evaluation method of the motion cueing algorithms was experimentally verified.The mathematical model of the motion cueing algorithms designed in the previous paper is discretized,and the corresponding communication module,position inversion module and motor drive module are developed,and the control system software is written.The effectiveness of the objective evaluation method presented in this paper is verified experimentally by using the driving simulator prototype.