Collision Avoidance Strategies in AR, VR, and Physical Reality

A study comparing locomotor outcomes and user experience during a walking collision avoidance task. The experiment was conducted in Augmented Reality, Virtual Reality, and Physical Reality environments using Varjo XR-3 and VIVE XR Elite headsets. Data includes participant characteristics, motion sickness, presence questionnaires, ease-of-use ratings, and locomotor task performance.

Use Cases

• Analyze locomotor task data to compare collision avoidance strategies between AR, VR, and Physical Reality environments.
• Correlate Holistic Presence Questionnaire (HPQ) scores with locomotor outcomes to assess the impact of immersion on task performance.
• Compare Fast Motion Sickness (FMS) scale data across the Varjo and VIVE headsets to evaluate device-specific user comfort.
• Use Single Ease Question (SEQ) data to gauge perceived task difficulty relative to the interferer distance of 3m or 3.5m.
• Model participant characteristics against locomotor outcomes to identify demographic factors influencing collision avoidance behavior.

Strengths

• Data collected from three distinct experimental environments: Augmented Reality, Virtual Reality, and Physical Reality.
• Includes outcomes from two specific headset models, the Varjo XR-3 and VIVE XR Elite.
• Task performed with a static interferer positioned at two defined distances: 3m and 3.5m from the participant's start.

Limitations

• Sample size and number of participants are unknown, limiting statistical power assessment.
• Specific locomotor outcome measures and column definitions are not provided, complicating direct analysis.
• Geographic origin of participants is unspecified, which may limit generalizability of findings.

Provenance

Source

Borealis Harvested Dataverse

Collection Method

Data from a controlled collision avoidance task performed while walking overground.

Time Range

null

Freshness

null

Geography

null