Project Details

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Development of an Immersive VR Platform to Study Social Influence in Pedestrian–Automated Vehicle Interactions

Company: PSU Department of Industrial Engineering

Major(s):
Primary: IE
Secondary: CMPSC
Optional: CMPEN

Non-Disclosure Agreement: NO

Intellectual Property: NO

Problem Statement: As automated vehicles become increasingly present in public road environments, pedestrian interactions with these vehicles remain uncertain and potentially unsafe. Pedestrians traditionally rely on vehicle movement, eye contact, driver gestures, and the behavior of nearby pedestrians to determine whether it is safe to cross. Automated vehicles remove many familiar driver-based communication cues, creating ambiguity about whether the vehicle has detected the pedestrian and intends to yield. In group settings, pedestrians may also rely on social information by following others, even when those actions are unsafe or conflict with vehicle behavior. Although eHMIs have been proposed to communicate automated-vehicle intent, limited research has examined how eHMI information interacts with social influence during pedestrian crossing decisions. How the Project Addresses the Gap: This project will conduct a focused literature review and develop a fully functioning immersive VR environment to examine pedestrian decision-making around automated vehicles. The VR scenarios will systematically vary eHMI availability, group size, and the behavior of surrounding pedestrians. Conditions will include crossing alone, observing one or multiple pedestrians cross, watching others remain at the curb, and encountering conflicting or unsafe group behavior. By controlling vehicle speed, yielding behavior, pedestrian actions, and communication cues, the VR platform will provide a realistic and repeatable environment for studying how pedestrians prioritize vehicle movement, eHMI signals, and social information. Expected Outcomes: The project is expected to produce a comprehensive literature review, a fully functional set of VR pedestrian-crossing scenarios, and detailed documentation of the experimental conditions and outcome measures. The developed platform will be ready for pilot testing and future human-subject studies. It is expected to support the measurement of crossing initiation time, waiting duration, accepted gaps, unsafe crossings, and attention to vehicles, eHMIs, and other pedestrians. The project will also establish a foundation for understanding when social influence supports or undermines safe crossing decisions and how eHMIs can be designed to improve communication between automated vehicles and pedestrians. Deliverables: 1. A structured literature review identifying current findings and research gaps. 2. A fully functioning set of VR pedestrian-crossing scenarios. 3. Scenario documentation describing vehicle behavior, eHMI conditions, group behavior, and outcome measures. 4. A pilot-ready VR platform for future human-subject experiments.