Citation

Şahin H, Hemesath S, Boll S. Front. Robot. AI 2022; 9: e885319.

Copyright

(Copyright © 2022, Frontiers Media)

DOI

10.3389/frobt.2022.885319

PMID

35875705

PMCID

PMC9304697

Abstract

Recent evidence suggests that the assumed conflict-avoidant programming of autonomous vehicles will incentivize pedestrians to bully them. However, this frequent argument disregards the embedded nature of social interaction. Rule violations are socially sanctioned by different forms of social control, which could moderate the rational incentive to abuse risk-avoidant vehicles. Drawing on a gamified virtual reality (VR) experiment (n = 36) of urban traffic scenarios, we tested how vehicle type, different forms of social control, and monetary benefit of rule violations affect pedestrians' decision to jaywalk. In a second step, we also tested whether differences in those effects exist when controlling for the risk of crashes in conventional vehicles. We find that individuals do indeed jaywalk more frequently when faced with an automated vehicle (AV), and this effect largely depends on the associated risk and not their automated nature. We further show that social control, especially in the form of formal traffic rules and norm enforcement, can reduce jaywalking behavior for any vehicle. Our study sheds light on the interaction dynamics between humans and AVs and how this is influenced by different forms of social control. It also contributes to the small gamification literature in this human-computer interaction.

Language: en

Keywords

bullying; pedestrian; virtual reality; social control; automated vehicles; deviant behavior; self-driving cars; vulnerable road users