Pedestrian Crossing Decisions in Virtual Environments: Behavioral Validity in CAVEs and Head-Mounted Displays.

OBJECTIVE: To contribute to the validation of virtual reality (VR) as a tool for analyzing pedestrian behavior, we compared two types of high-fidelity pedestrian simulators to a test track. BACKGROUND: While VR has become a popular tool in pedestrian research, it is uncertain to what extent simulator studies evoke the same behavior as nonvirtual environments. METHOD: An identical experimental procedure was replicated in a CAVE automatic virtual environment (CAVE), a head-mounted display (HMD), and on a test track. In each group, 30 participants were instructed to step forward whenever they felt the gap between two approaching vehicles was adequate for crossing. RESULTS: Our analyses revealed distinct effects for the three environments. Overall acceptance was highest on the test track. In both simulators, crossings were initiated later, but a relationship between gap size and crossing initiation was apparent only in the CAVE. In contrast to the test track, vehicle speed significantly affected acceptance rates and safety margins in both simulators. CONCLUSION: For a common decision task, the results obtained in virtual environments deviate from those in a nonvirtual test bed. The consistency of differences indicates that restrictions apply when predicting real-world behavior based on VR studies. In particular, the higher susceptibility to speed effects warrants further investigation, since it implies that differences in perceptual processing alter experimental outcomes. APPLICATION: Our observations should inform the conclusions drawn from future research in pedestrian simulators, for example by accounting for a higher sensitivity to speed variations and a greater uncertainty associated with crossing decisions.

Analysis of Street-Crossing Behavior: Comparing a CAVE Simulator and a Head-Mounted Display among Younger and Older Adults.

Interactive pedestrian simulators have become a valuable research tool for investigating street-crossing behavior and developing solutions for improving pedestrian safety. There are two main kinds of pedestrian simulators: one uses a technology based on rear-projection screens (Cave Automatic Virtual Environment, or CAVE), the other a head-mounted display (HMD). These devices are used indiscriminately, regardless of the research objective, and it is not yet known whether they are equally effective for studying street crossing. The present study was aimed at comparing the street crossing behavior and subjective evaluations of younger and older adult pedestrians when they are using a CAVE-like or HMD-based (HTC Vive Pro) pedestrian simulator. Thirty younger adults and 25 older adults performed 36 street-crossing trials (combining different speeds, two-way traffic conditions, and gap sizes) on each of the two types of simulators. The results indicated that participants in the HMD condition crossed the street significantly more often (58.6 %) than in the CAVE condition (42.44%) and had shorter safety margins. The most striking difference pertained to crossing initiation, which occurred considerably earlier (1.78 s) in the HMD condition than in the CAVE condition. Synchronization of crossing initiation with oncoming traffic was not as good in the CAVE condition because visual information in front of the pedestrian was missing due to the absence of ground projection. In both simulators, older adults caused more collisions than did younger ones, had shorter safety margins, and a slower crossing speed. Hence, the HMD reproduced classical age-related differences in most street-crossing behaviors already found on the CAVE. Usually observed speed effects were also found for both simulators. Neither cybersickness nor any adverse effects on stereoacuity or postural balance were found for either simulator. The HMD produced a higher level of presence and preference than the CAVE did. These findings provide evidence that HMDs have a clear potential for studying pedestrian behaviour.

Measuring egocentric distance perception in virtual reality: Influence of methodologies, locomotion and translation gains.

Virtual reality has become a popular means to study human behavior in a wide range of settings, including the role of pedestrians in traffic research. To understand distance perception in virtual environments is thereby crucial to the interpretation of results, as reactions to complex and dynamic traffic scenarios depend on perceptual processes allowing for the correct anticipation of future events. A number of approaches have been suggested to quantify perceived distances. While previous studies imply that the selected method influences the estimates' accuracy, it is unclear how the respective estimates depend on depth information provided by different perceptual modalities. In the present study, six methodological approaches were compared in a virtual city scenery. The respective influence of visual and non-visual cues was investigated by manipulating the ratio between visually perceived and physically walked distances. In a repeated measures design with 30 participants, significant differences between methods were observed, with the smallest error occurring for visually guided walking and verbal estimates. A linear relation emerged between the visual-to-physical ratio and the extent of underestimation, indicating that non-visual cues during walking affected distance estimates. This relationship was mainly evident for methods building on actual or imagined walking movements and verbal estimates.