Passenger avatar and color-coded feedback in a driving simulator: Implications for teledriving

This study investigates the impact of various feedback mechanisms on teledriving-related performance, focusing on the integration of human and non-human feedback to address the challenges of operating a vehicle with reduced multisensory and passenger-comfort feedback in remote driving. Using a driving simulator, 45 participants experienced four feedback conditions: no feedback, color-coded signals, avatars of unfamiliar passengers, and avatars of significant others. Feedback tied to vehicle acceleration intensity was assessed across metrics, including acceleration behavior, decision-making in overtaking situations, crash frequency, subjective workload, and personal preferences. The results revealed that color-coded feedback was most effective in reducing intense braking and steering events. However, both familiar and unfamiliar avatar feedback enhanced overall safety, reducing crash risk and workload. Thus, considering the well-being of another human (represented by the Avatar) can promote safety. While participants subjectively preferred feedback from significant others, performance differences between familiar and unfamiliar avatars were minimal, suggesting the general effectiveness of emotional cues. The findings highlight the complementary strengths of color-coded and emotional feedback mechanisms, emphasizing their potential to improve teledriving systems.