Prosocial AI Apologies on the Road: Emotional Compensation for Other Drivers' Misbehavior

Read full text
Authors: Jun Zhang, Weiqi Mei, Yuchen Wang, Chang Guo, Weibo Ling, Bo Liu, Qianwen Fu, Jie Zhang, Fang You, Yan Luximon
Cited by: 1
References: 65

Abstract

Aggressive driving often triggers anger and retaliatory behaviors, posing threats to traffic safety. This paper proposes an AI-driven apology mechanism based on an Augmented Reality Head-Up Display (AR-HUD), which delivers immediate apologies on behalf of offending drivers during traffic conflicts and repairs damaged social relations through prosocial lies. We conducted a 2 (scenario risk: high vs. low) × 5 (apology depth) mixed-design experiment (N = 40) to evaluate its effectiveness. Results show that AI apologies enhanced positive emotions and forgiveness intentions while reducing anger, with participants also perceiving psychological benefits. These effects were consistent across both high- and low-risk scenarios. Our findings offer a practical design pathway for human-AI emotional regulation in traffic contexts.

Fields of Study & Subjects

Human-Automation Interaction and Safety Forgiveness and Related Behaviors Social Robot Interaction and HRI

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–18
Publication date
13 April 2026