Although ride comfort has been researched for many years, there is still no definite objective evaluation method that can very well match the subjective assessment feeling. The main presented approaches are mostly based on ISO 2631, but the consistency and correlation between subjective evaluation and objective evaluation are inadequate in some existing studies. This article focuses on motion control performance, which is a primary ride comfort aspect. Different types of components of the vehicle have been combined in a tuning car to achieve various ride performances, such as springs, dampers, jounce bumpers, and tires, and then corresponding subjective evaluation results and acceleration measurement data have been collected when driving the tuning car on a sine wave road. With correlation and clustering analysis, the most representative features of measurement data for subjective assessment were extracted. Based on the small-sample statistics theory, a new objective evaluation method for ride motion control has been established using the features of the Least Absolute Shrinkage and Selection Operator (LASSO) model, which is a shrinkage and selection method commonly used in statistical analysis for linear regression. The cross-validation and comparison results indicate that the new objective evaluation method has a good estimation for ride motion control performance.
