Predicting the Subjective Evaluation of Drivers in a Driving Simulator During Loss of Adherence

This paper investigates the possibility of using objective indicators to predict the subjective evaluation of a driver in a simulator. Situations of loss of adherence (LOA) were controlled and modulated in intensity and duration on a static and on a dynamic simulator (with and without a motion base). Multiple regression analyses were performed using the subjective evaluation of participants as the dependent variable, and the objective physical variables of the interaction driver/vehicle as the independent variables. The results assigned the most contributive variables to the accuracy of the model’s prediction for each subjective item, lateral acceleration and yaw rate for “control feeling” for instance. They also underlined the consistency of our approach and the influence of motion rendering on the perception of LOA intensity. A similar method could be used to evaluate the perception of various configurations of electronic stability control (ESC) systems.