Investigating Users' Preferences in Adaptive Driving Styles for Level 2 Driving Automation

Abstract

Users prefer different styles (more defensive or aggressive) for their autonomous vehicle (AV) to drive. This preference depends on multiple factors including user's trust in AV and the scenario. Understanding users' preferred driving style and takeover behavior can assist in creating comfortable driving experiences. In this driving simulator study, participants were asked to interact with L2 driving automation with different driving style adaptations. We analyze the effects of different AV driving style adaptations on users' survey responses. We propose linear and generalized linear mixed effect models for predicting the user's preference and takeover actions. Results suggest that trust plays an important role in determining users' preferences and takeover actions. Also, the scenario, pressing brakes, and AV's aggressiveness level are among the main factors correlated with users' preferences. The results provide a step toward developing human-aware driving automation that can implicitly adapt its driving style based on the user's preference.