Safe Interaction of pedestrians and cyclists with automated transport (SIPCAT)

Safe Interaction of pedestrians and cyclists with automated transport (SIPCAT) is a project using Virtual Reality to study the interaction among pedestrians, cyclists and automated vehicles. This project uses a 3D VR Digital Twin to safely and efficiently study the interaction of pedestrians and cyclists with automated shuttles and delivery robots.

Optimize and evaluate wayfinding design in hospitals by incorporating theories

Extensive research has demonstrated that finding one's way within big buildings structures is often perceived as a complex process for a variety of reasons. In particular, hospitals present a noteworthy context where wayfinding poses a significant challenge for patients, as evidenced by patient complaints reported by hospital management.

Using Virtual Reality to understand wheelchair pedestrians’ road-crossing behavior

Pedestrians with reduced mobility (PRM) are particularly vulnerable when it comes to road safety. Research on PRM’s interactions with other road users is still lacking. Understanding PRM’s road crossing behavior is crucial for designing accessible, inclusive, and safe mobility systems.

Impact of various IT-based crowd management measures on pedestrian behaviour

This project aims to quantify the impact of various IT-based crowd management measures on pedestrian behaviour, such that those measure can be implemented by operators of crowded pedestrian infrastructures.

Exploring cyclist-automated vehicle interactions through Virtual Reality

With increasing automation on our roads, understanding cyclist interactions with automated vehicles is essential. Using a cycling simulator, our study delves into the effects of automated vehicles’ capabilities and implicit communication, assessing the impact on cyclists and safety in future automated traffic environments.