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The AI4CCAM Participatory Space continues its work and the focus moves now to VRU–CAV Virtual Reality Interaction Experiment on User Acceptance.

The User Acceptance Questionnaire for Use Case 3 in the AI4CCAM project is a comprehensive tool designed to evaluate participants’ perceptions, comfort, and trust regarding Connected and Automated Vehicles (CAVs) in Virtual Reality (VR) environments. It focuses on realistic urban scenarios, including standard and adverse conditions such as T-junctions, crossroads, roundabouts, lane closures, and busy commercial streets. These scenarios are crafted to assess key factors influencing user acceptance: risk perception, comfort level, and realism of the VR experience.

The questionnaire is structured into baseline and post-experiment segments for each scenario, enabling researchers to capture participants’ expectations before the VR experience and their reflections afterward. It addresses demographic details, familiarity with technology, and specific attitudes toward CAVs, incorporating scenarios with varying complexity, weather conditions, and visibility. The VR setup aims to replicate real-world interactions with immersive detail, enhancing participants’ ability to evaluate CAV behavior and their own comfort levels in a simulated but realistic environment.

Through this detailed approach, the questionnaire gathers critical data to guide the development of CAV technology that meets the needs of Vulnerable Road Users (VRUs) a category comprising pedestrians, cyclists, e-scooter riders and those with reduced mobility and builds trust in automated systems. The experiment combines questionnaires, VR-based scenarios, and physiological measurements to evaluate three key metrics: risk perception, comfort level, and realism of the experience.

Participants first complete baseline questionnaires to capture socio-demographics, attitudes, and intentions toward CAVs. They are then exposed to immersive VR scenarios simulating CAV–VRU interactions in realistic settings, T-junctions, crossroads, roundabouts, lane closures, and high commercial street areas. Additionally, adverse conditions (e.g., poor lighting, rain, low visibility) are specifically applied only to T-junction and roundabout scenarios. During these simulations, physiological responses are monitored to assess stress and comfort.

Finally, post-experiment questionnaires compare pre- and post-interaction results, allowing the project to measure acceptability (initial willingness to use) and acceptance (approval after actual experience) of CAV technologies among diverse user groups across France and Italy.

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