Interaction between pedestrians and automated vehicles: Exploring a motion-based approach for virtual reality experiments

Author(s):  
Janina Bindschädel ◽  
Ingo Krems ◽  
Andrea Kiesel
Author(s):  
J. Pablo Nuñez Velasco ◽  
Haneen Farah ◽  
Bart van Arem ◽  
Marjan P. Hagenzieker

Information ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 7
Author(s):  
Juan Pablo Nuñez Velasco ◽  
Anouk de Vries ◽  
Haneen Farah ◽  
Bart van Arem ◽  
Marjan P. Hagenzieker

Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected that automated vehicles (AV) will be safer than human-driven vehicles, but this depends on the nature of interactions between non-automated road users, among them cyclists. Little research on the interactions between cyclists and AVs exists. This study aims to determine the main factors influencing cyclists’ crossing intentions when interacting with an automated vehicle as compared to a conventional vehicle (CV) using a 360° video-based virtual reality (VR) method. The considered factors in this study included vehicle type, gap size between cyclist and vehicle, vehicle speed, and right of way. Each factor had two levels. In addition, cyclist’s self-reported behavior and trust in automated vehicles were also measured. Forty-seven participants experienced 16 different crossing scenarios in a repeated measures study using VR. These scenarios are the result of combinations of the studied factors at different levels. In total, the experiment lasted 60 min. The results show that the gap size and the right of way were the primary factors affecting the crossing intentions of the individuals. The vehicle type and vehicle speed did not have a significant effect on the crossing intentions. Finally, the 360° video-based VR method scored relatively high as a research method and comparable with the results of a previous study investigating pedestrians’ crossing intentions confirming its suitability as a research methodology to study cyclists’ crossing intentions.


Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 291 ◽  
Author(s):  
Tanja Fuest ◽  
Elisabeth Schmidt ◽  
Klaus Bengler

Integrating automated vehicles into mixed traffic entails several challenges. Their driving behavior must be designed such that is understandable for all human road users, and that it ensures an efficient and safe traffic system. Previous studies investigated these issues, especially regarding the communication between automated vehicles and pedestrians. These studies used different methods, e.g., videos, virtual reality, or Wizard of Oz vehicles. However, the extent of transferability between these studies is still unknown. Therefore, we replicated the same study design in four different settings: two video, one virtual reality, and one Wizard of Oz setup. In the first video setup, videos from the virtual reality setup were used, while in the second setup, we filmed the Wizard of Oz vehicle. In all studies, participants stood at the roadside in a shared space. An automated vehicle approached from the left, using different driving profiles characterized by changing speed to communicate its intention to let the pedestrians cross the road. Participants were asked to recognize the intention of the automated vehicle and to press a button as soon as they realized this intention. Results revealed differences in the intention recognition time between the four study setups, as well as in the correct intention rate. The results from vehicle–pedestrian interaction studies published in recent years that used different study settings can therefore only be compared to each other to a limited extent.


Author(s):  
Mark Colley ◽  
Svenja Krauss ◽  
Mirjam Lanzer ◽  
Enrico Rukzio

Passengers of automated vehicles will likely engage in non-driving related activities like reading and, therefore, be disengaged from the driving task. However, especially in critical situations such as unexpected pedestrian crossings, it can be assumed that passengers request information about the vehicle's intention and an explanation. Some concepts were proposed for such communication from the automated vehicle to the passenger. However, results are not comparable due to varying information content and scenarios. We present a comparative study in Virtual Reality (N=20) of four visualization concepts and a baseline with Augmented Reality, a Head-Up Display, or Lightbands. We found that all concepts were rated reasonable and necessary and increased trust, perceived safety, perceived intelligence, and acceptance compared to no visualization. However, when visualizations were compared, there were hardly any significant differences between them.


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