External human–machine interfaces: Gimmick or necessity?

Winter, Joost de; Dodou, Dimitra

doi:10.1016/j.trip.2022.100643

Cited by 28 publications

(7 citation statements)

References 136 publications

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“…In a recent review, Ref. [8] aimed to advance the discussion of whether eHMIs are necessary, which presented arguments covering both the positive and negative effects of eHMI inclusion. While eHMIs are generally desired by VRUs and have been shown to support safe crossing decisions, Ref.…”

Section: Related Workmentioning

confidence: 99%

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External Human–Machine Interfaces for Automated Vehicles in Shared Spaces: A Review of the Human–Computer Interaction Literature

Brill

Payre

Debnath

et al. 2023

Sensors

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Given the rise of automated vehicles from an engineering and technical perspective, there has been increased research interest concerning the Human and Computer Interactions (HCI) between vulnerable road users (VRUs, such as cyclists and pedestrians) and automated vehicles. As with all HCI challenges, clear communication and a common understanding—in this application of shared road usage—is critical in order to reduce conflicts and crashes between the VRUs and automated vehicles. In an effort to solve this communication challenge, various external human–machine interface (eHMI) solutions have been developed and tested across the world. This paper presents a timely critical review of the literature on the communication between automated vehicles and VRUs in shared spaces. Recent developments will be explored and studies analyzing their effectiveness will be presented, including the innovative use of Virtual Reality (VR) for user assessments. This paper provides insight into several gaps in the eHMI literature and directions for future research, including the need to further research eHMI effects on cyclists, investigate the negative effects of eHMIs, and address the technical challenges of eHMI implementation. Furthermore, it has been underlined that there is a lack of research into the use of eHMIs in shared spaces, where the communication and interaction needs differ from conventional roads.

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Section: Related Workmentioning

confidence: 99%

“…While eHMIs are generally desired by VRUs and have been shown to support safe crossing decisions, Ref. [8] noted that with repeated exposure VRUs may begin to over-rely on the device which could result in dangerous situations. Across academia and industry, several eHMI concepts have been proposed.…”

Section: Related Workmentioning

confidence: 99%

External Human–Machine Interfaces for Automated Vehicles in Shared Spaces: A Review of the Human–Computer Interaction Literature

Brill

Payre

Debnath

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Existing human-AV interaction studies have explored a range of scenarios (AV interacting with pedestrians (Terwilliger et al, 2019;Schmidt et al, 2019;Ackermann et al, 2019;Dey et al, 2019), cyclists (Ackermann et al, 2021), or human drivers around (Imbsweiler et al, 2018;Miller et al, 2022;), types of communication (explicit vs implicit (Dey and Terken, 2017;de Winter and Dodou, 2022;Lee et al, 2020;), and specific means of communication (e.g. longitudinal (Terwilliger et al, 2019;Miller et al, 2022;Schmidt et al, 2019;Ackermann et al, 2019), lateral (Sripada et al, 2021;Miller et al, 2022), and pitch (Bindschädel et al, 2022) maneuvers of AV).…”

Section: Introductionmentioning

confidence: 99%

Subtle motion cues by automated vehicles can nudge human drivers’ decisions: Empirical evidence and computational cognitive model

Zgonnikov¹,

Beckers²,

George³

et al. 2023

Preprint

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Automated vehicles (AVs) can bring about numerous benefits for society but they are unprepared to enter our roads yet, in large part because of the difficulties in interacting with humans around them. Addressing this issue requires not only developing novel interaction planning approaches for AVs, but also understanding human behavior in interactions with them. Existing investigations of such behavior have predominantly focused on situations in which AV a priori needs to take action because the human has the right of way, e.g., pedestrian crossing interactions. However, future AVs would likely need to proactively manage interactions even if they have the right of way over humans. Yet it remains unclear how AVs could behave in such interactions and how humans would react to them. In this paper, we investigate human responses to subtle nudge maneuvers of an oncoming AV when making an unprotected left turn. We found that participants (N=19) of a driving simulator experiment were sensitive to the deceleration nudge but not acceleration nudge (for the studied magnitude and duration of the nudge). Most importantly, we compare the obtained data to predictions of a computational cognitive model based on the concept of evidence accumulation. We demonstrate that the model captures the key qualitative patterns observed in participants' decisions and response times. Finally, we illustrate how the cognitive model, even if fitted to a limited set of experimental conditions, can flexibly generate predictions of human responses to arbitrary longitudinal AV maneuvers. These predictions are quantitative and testable, making the model a potentially useful tool for both informing future studies of human behavior and incorporating insights from such studies into computational frameworks potentially suitable for AV interaction planning.

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“…The majority of them, however, report that communicating the intent of the AV using an external interface can contribute to a positive interaction experience [ 9 , 22 , 23 , 24 , 25 , 26 , 27 ]. Other studies have concluded that the car’s motion may suffice [ 28 , 29 ] or leave the judgment open [ 30 ]. The majority of experts in the field of AVs suggest that eHMIs will enhance future AV–ORU interaction, but note that implicit communication will remain dominant, advising against text-based and instructive eHMIs [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

How to Design the eHMI of AVs for Urgent Warning to Other Drivers with Limited Visibility?

Lim

Kwon

2023

Sensors

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The importance of an external interaction interface (eHMI) has grown in recent years. Most eHMI concepts focus on communicating autonomous vehicle (AV)’s yielding intention to pedestrians at a crossing. However, according to previous studies, pedestrians at a crossing rely mainly on the vehicle’s movement information (implicit communication) rather than information from eHMIs (explicit communication). This paper has the purpose of proposing a specific use case in which the eHMI of future AVs could play an indispensable role in the safety of other road users (ORUs). Often VRUs cannot see the traffic flow due to a series of parked or stopped vehicles, which is a frequent cause of fatal traffic collision accidents. Drivers may also not be able to see approaching pedestrians or other cars from the side for the same reason. In this paper, the impact of an eHMI is tested from the perspective of drivers with limited visibility when a jaywalker steps into the road. A combination of colors, shapes, and information levels is presented on an eHMI. We show that our proposed eHMI design, in the deadlock scenario of a jaywalker and a driver who both lack visibility, significantly reduced the reaction time compared to when there was no eHMI. In the experiment, the willingness to stop, varying from 0 to 5, was measured from the driver’s perspective. The results showed that most users felt uncertainty and did not move quickly when seeing the light band color alone. Textual information on the eHMI was significantly more effective in providing an urgent warning of this specific scenario than vertical and horizontal light bands with color without text. In addition, red color, blinking rapidly above 3 Hz, and egocentric messages were also necessary to reduce the PRT(perception response time). By using text-added eHMI (Vertical + Text eHMI), the mean time to achieve a score above 4 for willingness to stop was 2.113 s faster than when there was no eHMI. It was 2.571 s faster than the time until the slider of the participants reached the maximum level for willingness to stop. This is a meaningful amount of difference when considering a PRT of 2.5 s, which is the Korean road design standard. As eHMIs tend to be applied for smarter mobility, it is expected that they will be more effective in preventing accidents if the eHMI is standardized in autonomous driving level 2 to 3 vehicles driven by humans before fully autonomous driving becomes a reality.

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External human–machine interfaces: Gimmick or necessity?

Cited by 28 publications

References 136 publications

External Human–Machine Interfaces for Automated Vehicles in Shared Spaces: A Review of the Human–Computer Interaction Literature

External Human–Machine Interfaces for Automated Vehicles in Shared Spaces: A Review of the Human–Computer Interaction Literature

Subtle motion cues by automated vehicles can nudge human drivers’ decisions: Empirical evidence and computational cognitive model

How to Design the eHMI of AVs for Urgent Warning to Other Drivers with Limited Visibility?

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