Driving Simulator Study to Explore the Situational Acceptance and the Objective Indication Under Automated Driving

Acceptance poses a significant challenge in deploying Level 4 and higher automated driving systems. To address this, the study introduces and validates the concept of situational acceptance, specifically focusing on how it correlates with crucial user behavior metrics such as decision-making timing and gaze behavior during interactions. Our driving simulator study reveals that the decision-making timing and gaze are closely correlated with variations in acceptance across different scenarios, even among the same group of users interacting with the same automated agent. This demonstrates the pivotal role these metrics play in understanding the dynamics of acceptance. Moreover, the study applies the traditional two-dimensional emotional model, linking decision-making timing with arousal and gaze behavior with valence, to analyze acceptance. This approach establishes a foundation for developing a more comprehensive method of evaluating acceptance in future automated systems.