Haptic feedback on the steering wheel to maximize front axle grip

1. Haptic feedback on the steering wheel to maximize front axle grip Joop van GerwenBioMechanical Design & Precision and Microsystems Engineering, Automotive

2. Contents • Introduction • Methods • Concept • Experiments • Data analysis • Results • Discussion

3. Introduction

4. Introduction ESC systems • Reduces loss of control • Effect: • Reduces fatal single vehicle crashes by [1] • 30-50% among cars and • 50-70% among SUVs • Best since seat belt! • Developed from ABS • But: large impact on velocity • Active Front Steering (AFS) [1] S.A. Ferguson, The Effectiveness of Electronic Stability Control in Reducing Real-World Crashes: A Literature Review, 2007 [2] http://www.guy-sports.com/fun_pictures/95-driving_bd.jpg [3] http://static.howstuffworks.com/gif/28002-rollover-accidents-2.jpg

5. Introduction Haptic feedback • Related research on lateral vehicle dynamics guidance • Lanekeeping • Principle: shared control • Controller is capable of controlling the system • Actuator power not strong enough for full control [1] J. Switkes, E. Rosetter, I. Coe, Handwheel force feedback for lanekeeping assistance: combined dynamics and stability

6. Introduction Idea & title explanation • Goal : • Use haptic feedback to let the driver take the corrective AFS action • Guide to maximum front axle grip

7. Methods

8. Methods Concept – Controller structure • Purpose: • Guide the driver to the proper steering action

9. Methods Concept – Upper controller structure

10. Methods Concept – Lower controller structure • Pacejka combined slip tire model

11. Methods Concept – How does it feel?

12. Methods Concept – How does it feel?

13. Methods Experiments – Vehicle

14. Methods Experiments – Tracks [1] http://maps.google.nl

15. Methods Experiments – Procedures • 9 drivers • 2 tracks • Wet skid-pad • 7 runs of 35 second • Task: follow inner line as fast as possible • Adverse track • 3 runs of 70 second (approximately 2 laps) • Task: take the corners as quick as you can • NASA Task Load Index • 2 experiment days

16. Methods Experiments – Pictures & video

17. Methods Analysis – Filtering & preparation • Filtered: Drivertorque and accelerations (3Hz anti-causal low pass) • Removed: unwanted data • Wet skid-pad • RMS data • Adverse track • Translation of data • One full, running lap isolated

18. Methods Analysis – Metrics • Performance metrics • Example: velocity • Driving behavior metrics • Example: steering wheel angle • Feedback controller metrics • Example: feedback torque

19. Results

20. Results Significance • Two data sets • T-test to calculate chance that data sets originate from the same source • Chance < 5% is significant • Influence of external factors • P-value = 5.1874e-007

21. Results Wet skid-pad

22. Results Adverse track – Velocity

23. Results Adverse track – One corner • Significantly lower • Significantly higher Steering angle error Yaw rate Driver torque Steering angle

24. Results Adverse track – Road position

25. Results NASA Task load index • Variables: • Mental demand • Physical demand • Temporal demand • Performance • Effort • Frustration • No significant changes • Small test group

26. Discussion

27. Discussion Conclusions – Improvements • Room for improvements: • State estimation & sensing • Tire model vs. force sensing bearing • Haptic feedback philosophy • Desired yaw rate determination very simple • Corrective yaw torque controller • Possible negative stiffness of steering system • Do not prevent drivers from steering back to neutral

28. Discussion Conclusions – Significant changes • Haptic feedback caused: • Driving behavior change • Vehicle eager to steer • Higher driver torque • Increased yaw rate • Drivers were drawn to a trajectory • Potential, but unsafe in current form