UI Design of eHMI of Autonomous Vehicles

Lim, Dokshin; Kim, Byungwoo

doi:10.1080/10447318.2022.2061123

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…Using familiar road sign symbols on the eHMI of AVs may create confusion [ 20 ]. For example, the same deer crossing symbol in Figure 9 may have different meanings.…”

Section: Discussionmentioning

confidence: 99%

“…The main type of road user addressed in the study is drivers of manually operated vehicles. According to Dey et al [ 16 ], eHMIs address pedestrians in 91% of cases, while cyclists are targeted by only 23%, and manually operated vehicles by 14%, which seems much less than is needed given the high level of influence of other drivers who share public roads with AVs [ 20 ]. Moreover, 60% targeted pedestrians only, while 31% targeted pedestrians and at least one other type of road user.…”

Section: Assumptionsmentioning

confidence: 99%

“…Existing eHMIs have mostly used abstract information through lights and displays (69%), followed by symbols (29%), text (23%), and anthropomorphic features (14%) [ 16 ]. Lim and Kim [ 20 , 21 ] proposed a reference eHMI combining a one-dimensional light status bar and a two-dimensional area that presents textual or graphical information. They incorporated eight of the 12 design patterns above (excluding 1.…”

Section: Introductionmentioning

confidence: 99%

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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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“…Using familiar road sign symbols on the eHMI of AVs may create confusion [ 20 ]. For example, the same deer crossing symbol in Figure 9 may have different meanings.…”

Section: Discussionmentioning

confidence: 99%

Section: Assumptionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Lim

Kwon

2023

Sensors

Self Cite

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“…External human-machine interaction (eHMI) arises as a solution for the vehicle to transmit information to potentially dangerous agents in the vicinity, representing a newly developing direction of autonomous driving [13]. eHMI encompasses the interaction design between autonomous vehicles (AVs), pedestrians, and other road users, primarily involving the communication of the vehicle's status, intentions, and interaction modalities with pedestrians [6].…”

Section: Ehmi and Projection Interaction Of Autonomous Vehiclesmentioning

confidence: 99%

“…The emergence of automated driving system (ADS) technology signifies a transformative epoch in intelligent autonomous mobility, especially in personal devices such as electric wheelchairs [2,4,5]. The adoption of autonomous driving technology enhances the convenience and independence of wheelchair users; however, these advancements introduce novel paradigms and conundrums in human-machine interface dynamics [6]. Contrary to conventional manual joystick mechanisms, autonomous wheelchair users often exhibit apprehension towards machine-dictated trajectories, which can appear as an opaque decision-making algorithm [7,8].…”

Section: Introductionmentioning

confidence: 99%

Shared eHMI: Bridging Human–Machine Understanding in Autonomous Wheelchair Navigation

Zhang,

Song,

Huang

et al. 2024

Applied Sciences

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As automated driving system (ADS) technology is adopted in wheelchairs, clarity on the vehicle’s imminent path becomes essential for both users and pedestrians. For users, understanding the imminent path helps mitigate anxiety and facilitates real-time adjustments. For pedestrians, this insight aids in predicting their next move when near the wheelchair. This study introduces an on-ground projection-based shared eHMI approach for autonomous wheelchairs. By visualizing imminent motion intentions on the ground by integrating real and virtual elements, the approach quickly clarifies wheelchair behaviors for all parties, promoting proactive measures to reduce collision risks and ensure smooth wheelchair driving. To explore the practical application of the shared eHMI, a user interface was designed and incorporated into an autonomous wheelchair simulation platform. An observation-based pilot study was conducted with both experienced wheelchair users and pedestrians using structured questionnaires to assess the usability, user experience, and social acceptance of this interaction. The results indicate that the proposed shared eHMI offers clearer motion intentions display and appeal, emphasizing its potential contribution to the field. Future work should focus on improving visibility, practicality, safety, and trust in autonomous wheelchair interactions.

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