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Research on Subjective Rating Prediction Method for Ride Comfort with Learning
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 30, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Event: 11th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference
Suspension is an important chassis part which is vital to ride comfort . However, it is difficult to achieve our targeted comfortability level in a short time. Therefore, improving efficiency of damper development is our primary challenge. We have launched a project which aims to reduce the workload on developing dampers by introducing analytical approaches to the improvement of ride comfort. To be more specific, we have been putting effort into developing the damping force prediction, the vehicle dynamics prediction and subjective rating prediction. This paper describes subjective rating prediction method which output a subjective rating corresponding to the physical value of the vehicle dynamics with deep learning. As a result of verification using objective data which was not used for learning process, DNN (Deep Neural Network) prediction method could fairly precisely predict subjective rating of the expert driver.
CitationAkai, A., Ichimaru, N., and Hirao, R., "Research on Subjective Rating Prediction Method for Ride Comfort with Learning," SAE Technical Paper 2020-01-1566, 2020, https://doi.org/10.4271/2020-01-1566.
Data Sets - Support Documents
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