Prediction of Drivers’ Subjective Evaluation of Vehicle Reaction Under Aerodynamic Excitations
Journal article, 2024

Objective: The objectives are to determine which quantities are important to measure to determine how drivers perceive vehicle stability, and to develop a regression model to predict which induced external disturbances drivers are able to feel. Background: Driver experience of a vehicle’s dynamic performance is important to auto manufacturers. Test engineers and test drivers perform several on-road assessments to evaluate the vehicle’s dynamic performance before sign-off for production. The presence of external disturbances such as aerodynamic forces and moments play a significant role in the overall vehicle assessment. As a result, it is important to understand the relation between the subjective experience of the drivers and these external disturbances acting on the vehicle. Method: A sequence of external yaw and roll moment disturbances of varying amplitudes and frequencies is added to a straight-line high-speed stability simulation test in a driving simulator. The tests are performed with both common and professional test drivers, and their evaluations to these external disturbances are recorded. The sampled data from these tests are used to generate the needed regression model. Results: A model is derived for predicting which disturbances drivers can feel. It quantifies difference in sensitivity between driver types and between yaw and roll disturbances. Conclusion: The model shows a relationship between steering input and driver sensitivity to external disturbances in a straight-line drive. Drivers are more sensitive to yaw disturbance than roll disturbance and increased steering input lowers sensitivity. Application: Identify the threshold above which unexpected disturbances such as aerodynamic excitations can potentially create unstable vehicle behaviour.

subjective evaluation

driver-vehicle interaction

vehicle stability

unsteady aerodynamics

driving simulator

Author

Arun Kumar

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems

Volvo

Erik Sällström

Volvo

Simone Sebben

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems

Bengt J H Jacobson

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems

Kaveh Amiri

Volvo

Human Factors

0018-7208 (ISSN) 1547-8181 (eISSN)

Vol. 66 5 1600-1615

Subject Categories

Infrastructure Engineering

Applied Psychology

Vehicle Engineering

DOI

10.1177/00187208231157935

PubMed

36802954

More information

Latest update

3/30/2024