Predictive Model of Driver's Perception of Vehicle Stability under Aerodynamic Excitation

Paper i proceeding, 2023

In vehicle development, a subjective evaluation of the vehicle's behavior at high speeds is usually conducted by experienced drivers with the objective of assessing driving stability. To avoid late design changes, it is desirable to predict and resolve perceived instabilities early in the development phase. In this study, a mathematical model is developed from measurements during on-road tests to predict the driver's ability to identify vehicle instabilities under excitations such as aerodynamic excitations. A vehicle is fitted with add-ons to create aerodynamic excitations and is driven by multiple drivers on a high-speed track. Drivers' evaluation, responses, cabin motion, and crosswind conditions are recorded. The influence of yaw and roll rates, lateral acceleration, and steering angle at various frequency ranges when predicting the drivers' evaluation of induced excitation is demonstrated. The drivers' evaluation of vehicle behavior is influenced by driver-vehicle interactions. Excess rotational rates, defined as the part of rotational rates that are not the result of steering action, reduce the importance of steering as a predictor and improve the accuracy of the predictive model. The present model is compared with an earlier developed model derived from data from a driving simulator under preconditioned aerodynamic excitations.