JOURNAL ARTICLE
Machines meet humans on the social road: Risk implications.
Published In: Risk Analysis: An International Journal, 2024, v. 44, n. 7. P. 1539 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Liu, Peng 3 of 3
Abstract
Human drivers and machine drivers (i.e., automated vehicles or AVs) will share roads and interact with each other, creating mixed traffic. In this perspective, we develop two mental models about them and their social interactions, aiming to understand the risk implications of AVs and mixed traffic. Based on Mental Model I (i.e., machine drivers are superior drivers without human weaknesses), many simulation‐based safety assessments, which often overlook or oversimplify human‐AV social interactions, have predicted significant safety benefits when machine drivers interact with or replace human drivers. In contrast, Mental Model II considers human and machine drivers as heterogeneous and incompatible, suggesting that their interactions may lead to unexpected and occasionally negative outcomes, particularly in imminent mixed traffic. This perspective gains support from recent comparative empirical studies that employ various methods such as survey experiments, driving simulators, test‐tracks, on‐road observations, and AV accident analysis. These studies provide initial evidence of emerging traffic risks arising from human‐AV social interactions, including human drivers' aggression and road rage toward AVs, human drivers exploiting AVs, AVs exerting negative peer influences on human drivers, and their incompatibility increasing human drivers' challenges in joining mixed traffic and thus risky behaviors. We propose specific suggestions to mitigate problematic human‐AV social interactions and the associated emerging risks. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Risk Analysis: An International Journal. 2024/07, Vol. 44, Issue 7, p1539
- Document Type:Article
- Subject Area:Psychology
- Publication Date:2024
- ISSN:0272-4332
- DOI:10.1111/risa.14255
- Accession Number:178355969
- Copyright Statement:Copyright of Risk Analysis: An International Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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