External Human–Machine Interfaces Can Be Misleading: An Examination of Trust Development and Misuse in a CAVE-Based Pedestrian Simulation Environment

Anees Ahamed Kaleefathullah · Natasha Merat · Yee Mun Lee · Yke Bauke Eisma · Ruth Madigan · Jorge García +1 more

111 citations0/0 files storedHuman Factors The Journal of the Human Factors and Ergonomics Society

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Human-Automation Interaction and Safety Traffic and Road Safety Social Robot Interaction and HRI

Abstract

OBJECTIVE: To investigate pedestrians' misuse of an automated vehicle (AV) equipped with an external human-machine interface (eHMI). Misuse occurs when a pedestrian enters the road because of uncritically following the eHMI's message. BACKGROUND: Human factors research indicates that automation misuse is a concern. However, there is no consensus regarding misuse of eHMIs. METHODS: Sixty participants each experienced 50 crossing trials in a Cave Automatic Virtual Environment (CAVE) simulator. The three independent variables were as follows: (1) behavior of the approaching AV (within-subject: yielding at 33 or 43 m distance, no yielding), (2) eHMI presence (within-subject: eHMI on upon yielding, off), and (3) eHMI onset timing (between-subjects: eHMI turned on 1 s before or 1 s after the vehicle started to decelerate). Two failure trials were included where the eHMI turned on, yet the AV did not yield. Dependent measures were the moment of entering the road and perceived risk, comprehension, and trust. RESULTS: Trust was higher with eHMI than without, and the -1 Group crossed earlier than the +1 Group. In the failure trials, perceived risk increased to high levels, whereas trust and comprehension decreased. Thirty-five percent of the participants in the -1 and +1 Groups walked onto the road when the eHMI failed for the first time, but there were no significant differences between the two groups. CONCLUSION: eHMIs that provide anticipatory information stimulate early crossing. eHMIs may cause people to over-rely on the eHMI and under-rely on the vehicle-intrinsic cues. APPLICATION: eHMI have adverse consequences, and education of eHMI capability is required.

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References

1997Humans and Automation: Use, Misuse, Disuse, Abuse 1992Trust, control strategies and allocation of function in human-machine systems 1999Does automation bias decision-making?2019External Human-Machine Interfaces on Automated Vehicles: Effects on Pedestrian Crossing Decisions 2016Ghost driver: A field study investigating the interaction between pedestrians and driverless vehicles 2018Communicating Intent of Automated Vehicles to Pedestrians 2018Designing the interaction of automated vehicles with other traffic participants: design considerations based on human needs and expectations 2007On the Independence of Compliance and Reliance: Are Automation False Alarms Worse Than Misses?

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2021How should external human-machine interfaces behave? Examining the effects of colour, position, message, activation distance, vehicle yielding, and visual distraction among 1,434 participants 2022External human–machine interfaces: Gimmick or necessity?2021Towards Scalable eHMIs: Designing for AV-VRU Communication Beyond One Pedestrian 2021Calibrating Pedestrians' Trust in Automated Vehicles

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