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

Kaleefathullah, Anees Ahamed; Merat, Natasha; Lee, Yee Mun; Eisma, Yke Bauke; Madigan, Ruth; García, Juan de Dios; Winter, Joost de

doi:10.1177/0018720820970751

Cited by 66 publications

(41 citation statements)

References 39 publications

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“…Authors found an effect of eHMI when the approaching AV was in the 'Gentle Brake' and 'Early Brake' conditions, but no effect of eHMI was shown in the 'Aggressive' braking and 'Constant Speed' conditions. Conversely, in a CAVE-based pedestrian simulator study, Kaleefathullah et al (2020) demonstrated that after a series of exposures to a functioning eHMI conveying a yielding message, approximately 35% of pedestrians walked onto the road when the eHMI was presented but the approaching vehicle was not decelerating. This suggests that pedestrians may become over-reliant on information conveyed through eHMI, to the point where they start to ignore the vehicle movement behaviour.…”

Section: Introductionmentioning

confidence: 97%

Learning to interpret novel eHMI: The effect of vehicle kinematics and eHMI familiarity on pedestrians' crossing behaviour

Lee¹,

Madigan²,

Uzondu³

et al. 2020

Preprint

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In current urban traffic, pedestrians attempting to cross the road at un-signalised locations are thought to mostly use implicit communication, such as deceleration cues, to interpret a vehicle’s intention to yield. There is less reliance on explicit driver- or vehicle-based messages, such as hand/head movements, or flashing lights/beeping horns. With the impending deployment of Automated Vehicles (AV), especially those at SAE Level 4 and 5, where the driver is no longer in control of the vehicle, there has been a surge in interest in the value of new forms of communication for AVs, for example, via different types of external Human Machine Interfaces (eHMIs). However, there is still much to be understood about how quickly a novel eHMI affects pedestrian crossing decisions, and whether it provides any additional aid, above and beyond implicit/kinematic information from the vehicle. The aim of this between-participant study, funded by the H2020 interACT project, was to investigate how the combination of kinematic information from a vehicle (e.g. Speed and Deceleration), and eHMI designs, play a role in assisting the crossing decision of pedestrians in a cave-based pedestrian simulator. Using an existing, well-recognised, message for yielding (Flashing Headlights - FH) as a benchmark, this study also investigated how quickly a novel eHMI (Slow Pulsing Light Band – SPLB) was learned. To investigate the effect of eHMI visibility on crossing decisions, the distance at which each eHMI was perceivable was also measured. Results showed that, compared to SPLB, the FH led to earlier crossings during vehicle deceleration, especially at lower approaching speeds, and smaller time gaps. However, although FH was visible earlier than SPLB, this visibility does not appear to be the only reason for earlier crossings, with message familiarity thought to play a role. Participants were found to learn the meaning conveyed by FH relatively quickly, crossing around 1 second earlier in its presence (compared to the no eHMI condition), across the three blocks of trials. On the other hand, it took participants at least one block of 12 trials for the new SPLB signal to affect crossing, which only accelerated crossing initiations by around 200ms, compared to the no eHMI condition. The role of comprehension, long-term exposure, and familiarity of novel messages in this context is therefore important, if AVs are to provide safe, trustworthy communication messages, which will enhance traffic flow and efficiency.

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Section: Introductionmentioning

confidence: 97%

Learning to interpret novel eHMI: The effect of vehicle kinematics and eHMI familiarity on pedestrians' crossing behaviour

Lee¹,

Madigan²,

Uzondu³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Focusing on the design of eHMIs for different vehicle types, a study by Lau et al [12] investigated the application of eHMI communication strategies on an automated bus and revealed eHMIs as contribution to a well-working interaction in terms of pedestrians' perceived safety and perceived information quality [12]. However, current research also pointed out negative effects of eHMIs, e.g., overtrust, which can affect the overall safety in urban traffic [13][14][15] and, therefore, need to be investigated for larger vehicle types, e.g., buses, particularly as negative effects here in a pedestrian interaction might lead to serious accidents or even fatalities.…”

Section: Introductionmentioning

confidence: 86%

Investigating the Interplay between eHMI and dHMI for Automated Buses: How Do Contradictory Signals Influence a Pedestrian's Willingness to Cross?

Lau

Jipp

Oehl

2021

13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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In future urban traffic, communication abilities of automated vehicles (AVs) are needed to enable a safe interaction with pedestrians as so-called vulnerable road users. Dynamic human-machine interfaces (dHMIs) and external human-machine interfaces (eHMIs) are designed to enable AVs to communicate implicitly, e.g., via vehicle dynamics, and explicitly, e.g., by light signals. To this point, it is neither sufficiently studied how the exact interplay of both communication tools should take place nor how this should be considered for an automated bus. This study aims to shed light on pedestrians' interaction with an automated bus by combining vehicle behavior (dHMI) and different eHMIs. The main focus was on the effect of contradictory communication messages on pedestrians' willingness to cross. Results showed that for non-yielding conditions, a dynamic eHMI that displayed an erroneous yielding intent lead to a significantly higher pedestrians' willingness to cross compared to static eHMI or no eHMI.

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“…If the vehicle kinematics contradicted the message of the eHMI, pedestrians primarily based their willingness to cross on the vehicle kinematics rather than the eHMI communication (Dey et al, 2020a). In contrast, a study by Kaleefathullah et al (2020) revealed that when the eHMI was on, but the AV did not indicate a braking process, pedestrians still crossed the street. This result demonstrated possible negative effects, i.e., over-trust, which have been also found by other studies (Kitazaki and Daimon, 2018;Holländer et al, 2019;Lee et al, 2021).…”

Section: Joint Role Of Implicit and Explicit Communicationmentioning

confidence: 98%

Toward a Holistic Communication Approach to an Automated Vehicle's Communication With Pedestrians: Combining Vehicle Kinematics With External Human-Machine Interfaces for Differently Sized Automated Vehicles

2022

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Future automated vehicles (AVs) of different sizes will share the same space with other road users, e. g., pedestrians. For a safe interaction, successful communication needs to be ensured, in particular, with vulnerable road users, such as pedestrians. Two possible communication means exist for AVs: vehicle kinematics for implicit communication and external human-machine interfaces (eHMIs) for explicit communication. However, the exact interplay is not sufficiently studied yet for pedestrians' interactions with AVs. Additionally, very few other studies focused on the interplay of vehicle kinematics and eHMI for pedestrians' interaction with differently sized AVs, although the precise coordination is decisive to support the communication with pedestrians. Therefore, this study focused on how the interplay of vehicle kinematics and eHMI affects pedestrians' willingness to cross, trust and perceived safety for the interaction with two differently sized AVs (smaller AV vs. larger AV). In this experimental online study (N = 149), the participants interacted with the AVs in a shared space. Both AVs were equipped with a 360° LED light-band eHMI attached to the outer vehicle body. Three eHMI statuses (no eHMI, static eHMI, and dynamic eHMI) were displayed. The vehicle kinematics were varied at two levels (non-yielding vs. yielding). Moreover, “non-matching” conditions were included for both AVs in which the dynamic eHMI falsely communicated a yielding intent although the vehicle did not yield. Overall, results showed that pedestrians' willingness to cross was significantly higher for the smaller AV compared to the larger AV. Regarding the interplay of vehicle kinematics and eHMI, results indicated that a dynamic eHMI increased pedestrians' perceived safety when the vehicle yielded. When the vehicle did not yield, pedestrians' perceived safety still increased for the dynamic eHMI compared to the static eHMI and no eHMI. The findings of this study demonstrated possible negative effects of eHMIs when they did not match the vehicle kinematics. Further implications for a holistic communication strategy for differently sized AVs will be discussed.

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

Cited by 66 publications

References 39 publications

Learning to interpret novel eHMI: The effect of vehicle kinematics and eHMI familiarity on pedestrians' crossing behaviour

Learning to interpret novel eHMI: The effect of vehicle kinematics and eHMI familiarity on pedestrians' crossing behaviour

Investigating the Interplay between eHMI and dHMI for Automated Buses: How Do Contradictory Signals Influence a Pedestrian's Willingness to Cross?

Toward a Holistic Communication Approach to an Automated Vehicle's Communication With Pedestrians: Combining Vehicle Kinematics With External Human-Machine Interfaces for Differently Sized Automated Vehicles

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