A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle  Pedestrian Interaction

Faas, Stefanie M.; Kao, Andrea C.; Baumann, Martin

doi:10.1145/3313831.3376484

Cited by 56 publications

(31 citation statements)

References 44 publications

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“…The learning curve seems to have a similar pattern for all combinations of conditions crossing conditions (e.g., distance-color combinations). These findings are aligned with previous research findings regarding the learning effect over time ( Faas et al, 2020 ) and strengthen them. Thus we can confirm h3 that there is a learning effect regardless of the crossing context and e-HMI display content.…”

Section: Discussionsupporting

confidence: 91%

“…Also, it was found that learnability directly influences safety when considering drivers ( Noel et al, 2005 ). When investigating the learnability of a pedestrian’s interaction with a FAV, in a WoZ field experiment, researchers found a learning curve over time but in a rather limited form as the authors based the learning on rating questionnaires over time ( Faas et al, 2020 ). Researchers investigated learnability with a single item: the participant agreement with the statement, “It is easy to learn that the light signal on the vehicle indicates yielding” (strongly disagree – strongly agree) while comparing steady, flashing, and sweeping light signals.…”

Section: Introductionmentioning

confidence: 99%

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Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time

Parmet

Oron-Gilad

2020

Front. Psychol.

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This study explored pedestrians’ understanding of Fully Autonomous Vehicles (FAVs) intention to stop and what influences pedestrians’ decision to cross the road over time, i.e., learnability. Twenty participants saw fixed simulated urban road crossing scenes with a single FAV on the road as if they were pedestrians intending to cross. Scenes differed from one another in the FAV’s, distance from the crossing place, its physical size, and external Human-Machine Interfaces (e-HMI) message by background color (red/green), message type (status/advice), and presentation modality (text/symbol). Eye-tracking data and decision measurements were collected. Results revealed that pedestrians tend to look at the e-HMI before making their decision. However, they did not necessarily decide according to the e-HMIs’ color or message type. Moreover, when they complied with the e-HMI proposition, they tended to hesitate before making the decision. Overall, a learning effect over time was observed in all conditions regardless of e- HMI features and crossing context. Findings suggest that pedestrians’ decision making depends on a combination of the e-HMI implementation and the car distance. Moreover, since the learning curve exists in all conditions and has the same proportion, it is critical to design an interaction that would encourage higher probability of compatible decisions from the first phase. However, to extend all these findings, it is necessary to further examine dynamic situations.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time

Parmet

Oron-Gilad

2020

Front. Psychol.

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“…For example, Faas et al. showed in a longitudinal video study that using an eHMI communicating the vehicle status yields effects increasing with time, such as earlier crossing onset as well as higher perceived safety, trust, learnability and reliance on eHMI [28]. Lee et al.…”

Section: Discussionmentioning

confidence: 99%

A field study investigating road safety effects of a front brake light

Monzel

Keidel

Schubert³

et al. 2021

IET Intelligent Trans Sys

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Recent research shows that braking of vehicles equipped with a front brake light is identified significantly earlier than braking of vehicles without front brake lights. Moreover, the absence of front brake lights leads to more conservative road crossing decisions. These results suggest that front brake lights are able to facilitate the pedestrians' anticipation of dangerous traffic situations, thereby increasing road safety. The present research investigated the effects of front brake lights in the real traffic of the Berlin Tegel Airport airside. A total of 102 vehicles were equipped with front brake lights and circulated in airport traffic for a period of three and a half months. Before and after this test period, 197 staff members were asked about their experiences with and their attitude towards front brake lights. The results show that front brake lights rarely led to misunderstandings, whereas they were significantly more often perceived to facilitate communication avoiding dangerous situations. The attitude towards front brake lights was already positive at the first interview and improved significantly during the measurement period. Overall, a great majority of participants stated that front brake lights improve communication between road users and thus increase road safety.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…We conducted three measuring points to study the stability of eHMI effects. The results of the study are published in Faas et al [39]. The study showed that pedestrians benefit from an eHMI communicating SDVs' status, and that additionally communicating SDVs' intent adds further value.…”

Section: Proposed Concept To Capture Street Crossing Onset Time (Cot)mentioning

confidence: 94%

“…The present paper focuses on the description and validation of the applied research method. For the present paper, we specifically re-evaluated the data of the first measuring time of the longitudinal study of Faas et al [39], since we argue that our method is able to compare the efficacy of eHMI variants with one measuring time only. Furthermore, the present paper includes additional procedures that were not reported in Faas et al [39] to validate the applied research method.…”

Section: Proposed Concept To Capture Street Crossing Onset Time (Cot)mentioning

confidence: 99%

Efficient Paradigm to Measure Street-Crossing Onset Time of Pedestrians in Video-Based Interactions with Vehicles

et al. 2020

Self Cite

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With self-driving vehicles (SDVs), pedestrians can no longer rely on a human driver. Previous research suggests that pedestrians may benefit from an external Human–Machine Interface (eHMI) displaying information to surrounding traffic participants. This paper introduces a natural methodology to compare eHMI concepts from a pedestrian’s viewpoint. To measure eHMI effects on traffic flow, previous video-based studies instructed participants to indicate their crossing decision with interfering data collection devices, such as pressing a button or slider. We developed a quantifiable concept that allows participants to naturally step off a sidewalk to cross the street. Hidden force-sensitive resistor sensors recorded their crossing onset time (COT) in response to real-life videos of approaching vehicles in an immersive crosswalk simulation environment. We validated our method with an initial study of N = 34 pedestrians by showing (1) that it is able to detect significant eHMI effects on COT as well as subjective measures of perceived safety and user experience. The approach is further validated by (2) replicating the findings of a test track study and (3) participants’ reports that it felt natural to take a step forward to indicate their street crossing decision. We discuss the benefits and limitations of our method with regard to related approaches.

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A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle Pedestrian Interaction

Cited by 56 publications

References 44 publications

Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time

Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time

A field study investigating road safety effects of a front brake light

Efficient Paradigm to Measure Street-Crossing Onset Time of Pedestrians in Video-Based Interactions with Vehicles

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A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle  Pedestrian Interaction

Cited by 56 publications

References 44 publications

Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time

Pedestrians’ Understanding of a Fully Autonomous Vehicle’s Intent to Stop: A Learning Effect Over Time

A field study investigating road safety effects of a front brake light

Efficient Paradigm to Measure Street-Crossing Onset Time of Pedestrians in Video-Based Interactions with Vehicles

Contact Info

Product

Resources

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A Longitudinal Video Study on Communicating Status and Intent for Self-Driving Vehicle Pedestrian Interaction