Interaction between pedestrians and automated vehicles: A Wizard of Oz experiment

Palmeiro, Ana Rodríguez; Kint, Sander van der; Vissers, Luuk; Farah, Haneen; Winter, Joost de; Hagenzieker, Marjan

doi:10.1016/j.trf.2018.07.020

Cited by 146 publications

(86 citation statements)

References 24 publications

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“…The results showed no significant effect of the type and presence of the eHMI. Similar results were obtained by Palmeiro et al [22]. They found that the presence of a sign "self-driving" did not significantly affect participants' critical gap times, that is, the last moment participants felt safe to cross.…”

Section: Of 18supporting

confidence: 86%

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

2019

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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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Section: Of 18supporting

confidence: 86%

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

2019

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“…The study noticed that pedestrians are adaptable road users as they are already used to operating without communication e.g., in dark conditions [13]. This argument is based on the observation that a vehicle's speed and distance to a pedestrian crossing are more important factors than the visual signal of HAVs would be when a pedestrian makes the decision to cross the street [3]. In addition, Tengvall [14] found that other road users (e.g., pedestrians), when interacting with an HAV, seem to be able to anticipate the HAV's operation by detecting its speed and trajectory, and changes in these factors.…”

Section: Interaction Between Highly Automated Vehicles and Pedestriansmentioning

confidence: 99%

“…How HAVs indicate that they have registered the pedestrian and that the pedestrian is safe to cross the street is an essential situation to be solved as e.g., Ackermann et al [4] and Rodríguez Palmeiro et al [3] have discussed. Before HAVs communicate to pedestrians by e.g., changes in vehicle speed or visual signals, the system needs to identify the nearby pedestrians, who are going to cross the street.…”

Section: Interaction Between Highly Automated Vehicles and Pedestriansmentioning

confidence: 99%

“…However, in the encounters between HAVs and other road users (e.g., pedestrians and cyclists), interaction between vehicle automation and humans is an important factor from the perspective of safety [2]. The elimination of driver error is also an important factor for improved safety in these encounters, but changes in interaction and behavior cause potentially new safety problems [3].…”

Section: Introductionmentioning

confidence: 99%

“…For pedestrians, eye contact with the driver is a clear message to decide to cross the street [3]. Text-based or visual messages, as e.g., Ackermann et al [4] have described, can be options to replace eye contact when implementing HAVs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prioritizing Safety or Traffic Flow? Qualitative Study on Highly Automated Vehicles’ Potential to Prevent Pedestrian Crashes with Two Different Ambitions

Utriainen

Pöllänen

2020

Sustainability

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Interaction between drivers and pedestrians enables pedestrians to cross the street without conflicts. When highly automated vehicles (HAVs) become prevalent, interaction will change. Although HAVs manage to identify pedestrians, they may not be able to assess pedestrians' intentions. This study discusses two different ambitions: Prioritizing pedestrian safety and prioritizing efficient traffic flow; and how these two affect the possibilities to avoid fatal crashes between pedestrians and passenger cars. HAVs' hypothetical possibilities to avoid different crash scenarios are evaluated based on 40 in-depth investigated fatal pedestrian crashes, which occurred with manually-driven cars in Finland in 2014-2016. When HAVs prioritize pedestrian safety, they decrease speed near pedestrians as a precaution which affects traffic flow due to frequent decelerations. When HAVs prioritize efficient traffic flow, they only decelerate, when pedestrians are in a collision course. The study shows that neither of these approaches can be applied in all traffic environments, and all of the studied crashes would not likely be avoidable with HAVs even when prioritizing pedestrian safety. The high expectations of HAVs' safety benefits may not be realized, and in addition to safety and traffic flow, there are many other objectives in traffic which need to be considered.

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Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles

Crosato,

Tian,

Shum

et al. 2023

Advanced Intelligent Systems

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Interaction‐aware autonomous driving (IAAD) is a rapidly growing field of research that focuses on the development of autonomous vehicles (AVs) that are capable of interacting safely and efficiently with human road users. This is a challenging task, as it requires the AV to be able to understand and predict the behaviour of human road users. In this literature review, the current state of IAAD research is surveyed. Commencing with an examination of terminology, attention is drawn to challenges and existing models employed for modeling the behaviour of drivers and pedestrians. Next, a comprehensive review is conducted on various techniques proposed for interaction modeling, encompassing cognitive methods, machine‐learning approaches, and game‐theoretic methods. The conclusion is reached through a discussion of potential advantages and risks associated with IAAD, along with the illumination of pivotal research inquiries necessitating future exploration.

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Interaction between pedestrians and automated vehicles: A Wizard of Oz experiment

Abstract: Interaction between pedestrians and automated vehicles A Wizard of Oz experiment

Cited by 146 publications

References 24 publications

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

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

Prioritizing Safety or Traffic Flow? Qualitative Study on Highly Automated Vehicles’ Potential to Prevent Pedestrian Crashes with Two Different Ambitions

Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles

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