The Delegation-Level Choice of an Automated Vehicle: An Analysis by Structural Equation Modeling

Bel, Marlène; Cœugnet, Stéphanie

doi:10.1080/10447318.2023.2170368

Cited by 3 publications

(1 citation statement)

References 102 publications

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“…The complete automation of driving is more than just the replacement of drivers by sophisticated technological systems; it is also a global transformation of road use that affects pedestrians. AVs need to gain the trust of all road users in order to be accepted (Habibovic et al, 2018;Bel and Coeugnet, 2023). Concerning pedestrians specifically, the classic beacons allowing crossing must be recomposed, designed, and imagined to ensure a high level of trust in the AVs.…”

Section: Introduction Pedestrians' Trust In Automated Vehiclesmentioning

confidence: 99%

How to improve pedestrians' trust in automated vehicles: new road infrastructure, external human–machine interface with anthropomorphism, or conventional road signaling?

2023

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IntroductionAutomated vehicles need to gain the trust of all road users in order to be accepted. To make technology trustworthy, automated vehicles must transmit crucial information to pedestrians through a human-machine interface, allowing pedestrians to accurately predict and act on their next behavior. However, the unsolved core issue in the field of vehicle automation is to know how to successfully communicate with pedestrians in a way that is efficient, comfortable, and easy to understand. This study investigated the impact of three human-machine interfaces specifically designed for pedestrians' trust during the street crossing in front of an automated vehicle. The interfaces used different communication channels to interact with pedestrians, i.e., through a new road infrastructure, an external human-machine interface with anthropomorphism, or with conventional road signaling.MethodsMentally projected in standard and non-standard use cases of human-machine interfaces, 731 participants reported their feelings and behavior through an online survey.ResultsResults showed that human-machine interfaces were efficient to improve trust and willingness to cross the street in front of automated vehicles. Among external human-machine interfaces, anthropomorphic features showed significant advantages in comparison with conventional road signals to induce pedestrians' trust and safer crossing behaviors. More than the external human-machine interfaces, findings highlighted the efficiency of the trust-based road infrastructure on the global street crossing experience of pedestrians with automated vehicles.DiscussionAll of these findings support trust-centered design to anticipate and build safe and satisfying human-machine interactions.

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Section: Introduction Pedestrians' Trust In Automated Vehiclesmentioning

confidence: 99%

How to improve pedestrians' trust in automated vehicles: new road infrastructure, external human–machine interface with anthropomorphism, or conventional road signaling?

2023

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Attitudes toward artificial intelligence: combining three theoretical perspectives on technology acceptance

Koenig

2024

AI & Soc

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Evidence on AI acceptance comes from a diverse field comprising public opinion research and largely experimental studies from various disciplines. Differing theoretical approaches in this research, however, imply heterogeneous ways of studying AI acceptance. The present paper provides a framework for systematizing different uses. It identifies three families of theoretical perspectives informing research on AI acceptance—user acceptance, delegation acceptance, and societal adoption acceptance. These models differ in scope, each has elements specific to them, and the connotation of technology acceptance thus changes when shifting perspective. The discussion points to a need for combining the three perspectives as they have all become relevant for AI. A combined approach serves to systematically relate findings from different studies. And as AI systems affect people in different constellations and no single perspective can accommodate them all, building blocks from several perspectives are needed to comprehensively study how AI is perceived in society.

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Risk-Taking Driving Behavior in Interacting With an Autonomous Vehicle at Two-Way Stop-Controlled Intersections

Jiang,

Lee,

Baig

2024

International Journal of Human–Computer Interaction

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The Delegation-Level Choice of an Automated Vehicle: An Analysis by Structural Equation Modeling

Cited by 3 publications

References 102 publications

How to improve pedestrians' trust in automated vehicles: new road infrastructure, external human–machine interface with anthropomorphism, or conventional road signaling?

How to improve pedestrians' trust in automated vehicles: new road infrastructure, external human–machine interface with anthropomorphism, or conventional road signaling?

Attitudes toward artificial intelligence: combining three theoretical perspectives on technology acceptance

Risk-Taking Driving Behavior in Interacting With an Autonomous Vehicle at Two-Way Stop-Controlled Intersections

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