An online evaluation method for ride comfort based on multivariate physiological indicators

Demand for objectivity, accuracy and online learning is becoming increasingly important to current evaluations for ride comfort. A data-based appraisal model of riding environmental comfort is proposed in this paper. Physiological indicators data is introduced into the improved support vector regression(SVR), then, physiological indicators are used to learn online by correcting the parameters of the model. Excellent evaluation capacity is demonstrated through numerical examples, and rating accuracy is 95.6%.