Machines versus humans: People's biased responses to traffic accidents involving self-driving vehicles

Accident; Analysis and Prevention
Peng LiuZhigang Xu

Abstract

Although self-driving vehicles (SDVs) bring with them the promise of improved traffic safety, they cannot eliminate all crashes. Little is known about whether people respond crashes involving SDVs and human drivers differently and why. Across five vignette-based experiments in two studies (total N = 1267), for the first time, we witnessed that participants had a tendency to perceive traffic crashes involving SDVs to be more severe than those involving conventionally human-driven vehicles (HDVs) regardless of their severity (injury or fatality) or cause (SDVs/HDVs or others). Furthermore, we found that this biased response could be a result of people's reliance on the affect heuristic. More specifically, higher prior negative affect tagged with an SDV (vs. an HDV) intensifies people's negative affect evoked by crashes involving the SDV (vs. those involving the HDV), which subsequently results in higher perceived severity and lower acceptability of the crash. Our results imply that people's over-reaction to crashes involving SDVs may be a psychological barrier to their adoption and that we may need to forestall a less stringent introduction policy that allows SDVs on public roads as it may lead to more crashes that could possibly...Continue Reading

Citations

Jan 15, 2021·Risk Analysis : an Official Publication of the Society for Risk Analysis·Peng Liu, Yong Du
Sep 4, 2021·Accident; Analysis and Prevention·Owain T RitchieAlex Mouzakitis
Feb 15, 2020·Accident; Analysis and Prevention·Peng LiuJu Da Young

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