Factors Affecting Pedestrians' Trust in Automated Vehicles: Literature Review and Theoretical Model

Siyuan Zhou, Xu Sun, Bingjian Liu, Gary Burnett

Research output: Journal PublicationReview articlepeer-review

2 Citations (Scopus)

Abstract

Automated vehicles (AVs) are one critical application area of artificial intelligence (AI). However, a lack of appropriate trust can be a major barrier to successfully introducing AVs into the market. The objective of this study is to summarize and synthesize the existing literature to gain a greater understanding of factors that will potentially influence the development of pedestrians' trust in AVs over time. Since AVs will become part of a larger infrastructure system that influences more than just AV users, they should also be accepted by pedestrians and other road users. There is a need for pedestrians to form appropriate levels of trust toward AVs to achieve safe interaction with such vehicles in circumstances characterized by uncertainty and vulnerability. Consequently, factors relevant to the building of this appropriate trust must be understood. By integrating the reviewed empirical studies and related theories, a theoretical model has been proposed and developed, comprising three layers of variability in pedestrian-AV trust (dispositional trust, situational trust, and learned trust). Given that this is an emerging field of research, much still remains unknown, and this review identifies several gaps in current knowledge for each layer of trust, as well as providing suggestions for consideration in future studies. Additionally, the proposed model of pedestrian-AV trust can be useful to transportation researchers, practitioners, designers, and AV manufacturers for designing AVs and related transportation systems for the purposes of successfully integrating AVs into society, and calibrating pedestrians' trust to the appropriate level.

Original languageEnglish
Pages (from-to)490-500
Number of pages11
JournalIEEE Transactions on Human-Machine Systems
Volume52
Issue number3
DOIs
Publication statusPublished - 1 Jun 2022

Keywords

  • Artificial intelligence (AI)
  • automated vehicles (AVs)
  • human-automation interaction
  • pedestrians
  • trust

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Factors Affecting Pedestrians' Trust in Automated Vehicles: Literature Review and Theoretical Model'. Together they form a unique fingerprint.

Cite this