Analysis of the dynamic influence of typical emotions on driving tendency

Abstract

This paper proposes a quantitative representation of driving tendency based on paired sample t-test and entropy, which is used to analyze the influence of anger, happiness, sadness and other driving emotions on dynamic driving tendency. By quantifying driving propensity, the dynamic changes of driving propensity under the influence of different emotions can be visualized. Randomly select the experimental personnel to carry out the simulation driving experiment. During the experiment, collect driving data of various driving states and human factors data of physiological indicators of drivers. A total of 84 effective experimental samples and 336 effective experimental data are obtained. The t-test of paired samples was used to analyze the differences of each index under different emotions. The characteristic parameters were selected to construct data matrix. The entropy value of each index was calculated by entropy and the driving tendency was quantitatively expressed according to the index weight. The driving tendency values of typical emotions and normal emotions were compared and analyzed, and the driving tendency transfer matrix was established to explore the driving tendency transfer law. The results show that the characteristics of driving propensity are different under different emotions. The three typical driving emotions have an impact on the dynamic change of driving propensity, and the most significant difference is the quantitative change of driving propensity under the influence of anger.