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

Area of Science:

• Human-computer interaction
• Robotics and automation
• Transportation engineering

Background:

• Remote driving (teledriving) faces challenges due to reduced sensory feedback and passenger comfort.
• Integrating human and non-human feedback is crucial for safe and effective teledriving.
• Existing systems often lack sufficient feedback to compensate for remote operation limitations.

Purpose of the Study:

• To investigate the impact of different feedback mechanisms on teledriving performance.
• To compare the effectiveness of non-human (color-coded signals) and human-like (avatars) feedback.
• To assess how emotional cues influence driver behavior and safety in remote driving scenarios.

Main Methods:

• A driving simulator study with 45 participants was conducted.
• Four feedback conditions were tested: no feedback, color-coded signals, unfamiliar passenger avatars, and significant other avatars.
• Performance was evaluated based on acceleration behavior, overtaking decisions, crash frequency, workload, and user preferences.

Main Results:

• Color-coded feedback effectively reduced intense braking and steering.
• Both familiar and unfamiliar avatar feedback significantly enhanced safety by reducing crash risk and workload.
• Participants preferred feedback from significant others, but performance differences between avatar types were minor.

Conclusions:

• Color-coded and emotional feedback mechanisms offer complementary benefits for teledriving.
• Considering the well-being of others, even represented by avatars, can improve remote driving safety.
• Emotional cues and clear visual signals are promising for enhancing teledriving systems.