External Human-Machine Interfaces on Automated Vehicles: Effects on Pedestrian Crossing Decisions

Objective: In this article, we investigated the effects of external human-machine interfaces (eHMIs) on pedestrians’ crossing intentions. Background: Literature suggests that the safety (i.e., not crossing when unsafe) and efficiency (i.e., crossing when safe) of pedestrians’ interactions with automated vehicles could increase if automated vehicles display their intention via an eHMI. Methods: Twenty-eight participants experienced an urban road environment from a pedestrian’s perspective using a head-mounted display. The behavior of approaching vehicles (yielding, nonyielding), vehicle size (small, medium, large), eHMI type (1. baseline without eHMI, 2. front brake lights, 3. Knightrider animation, 4. smiley, 5. text [WALK]), and eHMI timing (early, intermediate, late) were varied. For yielding vehicles, the eHMI changed from a nonyielding to a yielding state, and for nonyielding vehicles, the eHMI remained in its nonyielding state. Participants continuously indicated whether they felt safe to cross using a handheld button, and “feel-safe” percentages were calculated. Results: For yielding vehicles, the feel-safe percentages were higher for the front brake lights, Knightrider, smiley, and text, as compared with baseline. For nonyielding vehicles, the feel-safe percentages were equivalent regardless of the presence or type of eHMI, but larger vehicles yielded lower feel-safe percentages. The Text eHMI appeared to require no learning, contrary to the three other eHMIs. Conclusion: An eHMI increases the efficiency of pedestrian-AV interactions, and a textual display is regarded as the least ambiguous. Application: This research supports the development of automated vehicles that communicate with other road users.

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How Do eHMIs Affect Pedestrians’ Crossing Behavior? A Study Using a Head-Mounted Display Combined with a Motion Suit

Information ◽

10.3390/info10120386 ◽

2019 ◽

Vol 10 (12) ◽

pp. 386 ◽

Cited By ~ 7

Author(s):

Lars Kooijman ◽

Riender Happee ◽

Joost de Winter

Keyword(s):

Urban Environment ◽

Motion Tracking ◽

Automated Vehicles ◽

Forward Motion ◽

The Road ◽

Head Mounted Display ◽

Human Machine Interfaces ◽

Do So

In future trac, automated vehicles may be equipped with external human-machine interfaces (eHMIs) that can communicate with pedestrians. Previous research suggests that, during first encounters, pedestrians regard text-based eHMIs as clearer than light-based eHMIs. However, in much of the previous research, pedestrians were asked to imagine crossing the road, and unable or not allowed to do so. We investigated the effects of eHMIs on participants’ crossing behavior. Twenty-four participants were immersed in a virtual urban environment using a head-mounted display coupled to a motion-tracking suit. We manipulated the approaching vehicles’ behavior (yielding, nonyielding) and eHMI type (None, Text, Front Brake Lights). Participants could cross the road whenever they felt safe enough to do so. The results showed that forward walking velocities, as recorded at the pelvis, were, on average, higher when an eHMI was present compared to no eHMI if the vehicle yielded. In nonyielding conditions, participants showed a slight forward motion and refrained from crossing. An analysis of participants’ thorax angle indicated rotation towards the approaching vehicles and subsequent rotation towards the crossing path. It is concluded that results obtained via a setup in which participants can cross the road are similar to results from survey studies, with eHMIs yielding a higher crossing intention compared to no eHMI. The motion suit allows investigating pedestrian behaviors related to bodily attention and hesitation.

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Negative Effect of External Human-Machine Interfaces in Automated Vehicles on Pedestrian Crossing Behaviour: A Virtual Reality Experiment

Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021) - Lecture Notes in Networks and Systems ◽

10.1007/978-3-030-74608-7_88 ◽

2021 ◽

pp. 718-725

Author(s):

Jieun Lee ◽

Tatsuru Daimon ◽

Satoshi Kitazaki

Keyword(s):

Virtual Reality ◽

Automated Vehicles ◽

Human Machine Interfaces ◽

Negative Effect ◽

Pedestrian Crossing

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The Pilot Study of the Hazard Perception Test for Evaluation of the Driver’s Skill Using Virtual Reality

Electronics ◽

10.3390/electronics10091114 ◽

2021 ◽

Vol 10 (9) ◽

pp. 1114

Author(s):

Tatsunori Sawada ◽

Hiroki Uda ◽

Akira Suzuki ◽

Kounosuke Tomori ◽

Kanta Ohno ◽

...

Keyword(s):

Limited Range ◽

Chi Square ◽

Hazard Perception ◽

Novice Drivers ◽

Head Mounted Display ◽

Road Users ◽

Driving Skill ◽

Significant Difference ◽

Chi Square Test ◽

Gender Groups

Background: Although various technologies are used to evaluate driving skill, there are some limitations such as the limited range of the monitor and the possible risk of causing cybersickness. The purpose of this study is to investigate differences in the hazard perception and cybersickness experienced between novice and experienced drivers measured in a VR hazard perception test with a head-mounted display (HMD). Methods: The novice (n = 32) and the experienced drivers (n = 36) participated in the hazard perception test through the VR of an HMD. Results: The total number of identified hazards was 1071 in the novice drivers and 1376 in the experienced drivers. Two of the hazards appeared to be only identifiable through the HMD. A chi-square test revealed that experienced drivers were more likely to identify the hazards than the novice drivers (p < 0.05). The novice drivers appeared to identify “hazard prediction of the current behavior of other road users” more than other hazard types, unlike the experienced group. The Simulator Sickness Questionnaire scores indicated no significant difference in the different age or gender groups (p > 0.05). Conclusion: Our results suggest that the VR hazard perception test may be useful for evaluating patients’ driving skills.

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Drivers’ Attention Strategies before Eyes-off-Road in Different Traffic Scenarios: Adaptation and Anticipation

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073716 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3716

Author(s):

Zhuofan Liu ◽

Wei Yuan ◽

Yong Ma

Keyword(s):

Visual Attention ◽

Driving Simulator ◽

Test Drive ◽

Urban Road ◽

Strong Shift ◽

Related Information ◽

Road Users ◽

Urban Rural ◽

Within Subjects ◽

Driving Task

The distribution of drivers’ visual attention prior to diverting focus from the driving task is critical for safety. The object of this study is to investigate drivers’ attention strategy before they occlude their vision for different durations under different driving scenarios. A total of 3 (scenarios) × 3 (durations) within-subjects design was applied. Twenty-three participants completed three durations of occlusion (0, 1, and 2 s) test drive in a motion-based driving simulator under three scenarios (urban, rural, motorway). Drivers’ occlusion behaviour, driving behaviour, and visual behaviour in 6 s before occlusion was analyzed and compared. The results showed that drivers tended to slow down and increased their attention on driving task to keep safety in occlusion 2 s condition. The distribution of attention differed among different driving scenarios and occlusion durations. More attention was directed to Forward position and Speedometer in occlusion conditions, and a strong shift in attention from Forward position to Road users and Speedometer was found in occlusion 2 s condition. Road users was glanced more frequently in urban road with a higher percentage of attention transitions from Forward position to Road users. While gaze switching to Speedometer with a higher intensity was found on motorway. It suggests that drivers could adapt their visual attention to driving demand and anticipate the development of upcoming situations by sampling enough driving-related information before eyes-off-road. Moreover, the adaptation and anticipation are in accordance with driving situation and expected eyes-off-road duration. Better knowledge about attentional strategies before attention away from road contributes to more efficient and safe interaction with additional tasks.

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Impact of External Human–Machine Interface Communication Strategies of Automated Vehicles on Pedestrians’ Crossing Decisions and Behaviors in an Urban Environment

Sustainability ◽

10.3390/su13158396 ◽

2021 ◽

Vol 13 (15) ◽

pp. 8396

Author(s):

Marc Wilbrink ◽

Merle Lau ◽

Johannes Illgner ◽

Anna Schieben ◽

Michael Oehl

Keyword(s):

Urban Traffic ◽

Automated Vehicles ◽

Negative Effects ◽

Communication Tools ◽

Automated Vehicle ◽

Additional Information ◽

Road Users ◽

Vulnerable Road Users ◽

And Behaviors ◽

Vehicle Automation

The development of automated vehicles (AVs) and their integration into traffic are seen by many vehicle manufacturers and stakeholders such as cities or transportation companies as a revolution in mobility. In future urban traffic, it is more likely that AVs will operate not in separated traffic spaces but in so-called mixed traffic environments where different types of traffic participants interact. Therefore, AVs must be able to communicate with other traffic participants, e.g., pedestrians as vulnerable road users (VRUs), to solve ambiguous traffic situations. To achieve well-working communication and thereby safe interaction between AVs and other traffic participants, the latest research discusses external human–machine interfaces (eHMIs) as promising communication tools. Therefore, this study examines the potential positive and negative effects of AVs equipped with static (only displaying the current vehicle automation status (VAS)) and dynamic (communicating an AV’s perception and intention) eHMIs on the interaction with pedestrians by taking subjective and objective measurements into account. In a Virtual Reality (VR) simulator study, 62 participants were instructed to cross a street while interacting with non-automated (without eHMI) and automated vehicles (equipped with static eHMI or dynamic eHMI). The results reveal that a static eHMI had no effect on pedestrians’ crossing decisions and behaviors compared to a non-automated vehicle without any eHMI. However, participants benefit from the additional information of a dynamic eHMI by making earlier decisions to cross the street and higher certainties regarding their decisions when interacting with an AV with a dynamic eHMI compared to an AV with a static eHMI or a non-automated vehicle. Implications for a holistic evaluation of eHMIs as AV communication tools and their safe introduction into traffic are discussed based on the results.

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