Predictive Haptic Feedback for Obstacle Avoidance Based on Model Predictive Control

Abstract

New sensing and steering technologies enable safety systems that work with the driver to ensure a safe and collision-free vehicle trajectory using a shared control approach. These shared control systems must constantly balance the sometimes competing objectives of following the driver’s command and maintaining a feasible trajectory for the vehicle. This paper presents a novel technique for creating haptic steering feedback based on a prediction of the system’s need to intervene in the future. This feedback mirrors the tension between the two controller objectives of following the driver and maintaining a feasible path. The paper uses simulation and experiment to investigate the impact of varying the prediction horizon on system performance. A novel in-vehicle driver study based on decoupling visual and haptic cues demonstrates that this feedback provides a statistically significant improvement in response time and reduced time to collision (TTC) in an obstacle avoidance task.