| Many past studies have focused on the static sitting comfort of the driver’s posture rather than the sitting comfort under non-driving postures.With the development of automated transportation,passengers will have more non-driving tasks to perform in the vehicle,requiring the adoption of non-driving postures to better execute these tasks.With the development of smart cabins,the future will provide passengers with smarter and more comfortable postures,requiring a fundamental understanding of what makes a posture comfortable and how to achieve a comfortable sitting experience.Therefore,understanding the mechanism of this sensory experience is of great significance for designing cabins suitable for automated transportation and improving passenger comfort.Based on the OpenSim simulation platform and relevant biomechanical theory,this article aims to establish a comfort model using a combination of subjective and objective approaches as the prediction method.Specifically,the research focuses on driving and non-driving postures as the objects of study,and simulation and experimentation as the research methods.The goal is to investigate the mechanism of passenger comfort and health in the context of automated driving,and to identify the factors that improve passenger experience.This knowledge is of great significance in designing cabins suitable for automated transportation and enhancing passenger comfort.(1)A secondary development of the musculoskeletal model was conducted in OpenSim.This involved the establishment of marker and metabolic probe models,and the interactive connection of the musculoskeletal model with the cabin environment model.The musculoskeletal model was scalable according to actual human body size,and the cabin environment model could be adjusted based on layout parameters.Ultimately,a simulation model was constructed to compute the biomechanical load on the relevant muscles of passengers in different postures.(2)"Study on Driving Posture.Firstly,a simulation experiment was designed by changing the parameters of the steering wheel(L11),and a posture model was established using the CPM model.Secondly,the weight of inverse kinematics calculation was optimized using FAHP,and four types of biological loads were calculated.The biological load of different anatomical regions of muscles was analyzed layer by layer to verify the viewpoint that "the intermediate position is more comfortable".Finally,based on this hypothesis,a three-factor five-level simulation orthogonal experiment was designed starting from the intermediate posture,including the seat back angle(A40),seat cushion angle(A27),and seat height(H30).The high-dimensional biological load indicators were compressed into comprehensive scores through principal component analysis,and the optimal parameter combination and the main parameters affecting the score were analyzed.(3)"Study on Non-Driving Posture.Firstly,an actual man-machine experimental platform was built,and three occupants with a height of 95 th percentile were selected for posture experiments.The sitting posture drove the OpenSim human body model to further calculate muscle activation,and the muscle activation was solved by collecting muscle electromyography signals,and the consistency between the two results was analyzed.Then,the occupants subjectively evaluated the comfort of body parts in sitting posture,and the normality,correlation,and difference of the evaluation results were analyzed.The evaluation results of participant No.3 were selected for trend analysis.In addition,the NBP posture was preliminarily explored based on posture experiments and subjective evaluations.Finally,a subjective comfort prediction model was established based on the data of participant No.3.Furthermore,using random forest and BP neural network,the subjective-objective comfort prediction model was established by respectively using subjective and objective data as labels and features.The evaluation indicators showed that the model had a good expression effect on the dataset. |
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