LAUSR

This study explored the relationships between subjective evaluations and objective metrics of vehicle dynamic performance. First, a real vehicle test was performed to measure the acceleration performance under different conditions, and participants’ subjective evaluations of the acceleration performance were investigated. Second, correlation analysis was conducted to explore relationships between each subjective evaluation and its corresponding objective metric as well as between the overall subjective evaluation and three individual subjective evaluations. Finally, an overall subjective evaluation model related to the three objective metrics was established based on the Probabilistic Neural Network (PNN). The analysis results demonstrated that the correlation coefficients of the three groups of data were greater than 0.5 and that each subjective evaluation was significantly correlated with its corresponding objective metric. The individual subjective evaluation of the climbing acceleration performance had the largest effect on the overall subjective evaluation, with a correlation coefficient of 0.47. The established overall subjective evaluation model was relatively reliable, with a prediction accuracy of 90%. This study furthered the existing knowledge of the methods for evaluating vehicle dynamic performance. The proposed overall subjective evaluation model improves the reliability of vehicle dynamic evaluations and offers a theoretical basis for vehicle manufacturers to improve automobile performance.