Elem Güzel

Elem is a senior data scientist at Virtual Vehicle Research, specializing in driving safety and urban mobility. With expertise in Python, machine learning and data engineering, she contributes to projects like AI-driven seat comfort evaluation and AI models for vulnerable road user behavior prediction. She holds a PhD in computer science from the Free University of Bozen-Bolzano, where she researched ontology-based access to temporal data. Elem has a strong background in data integration, knowledge graphs and AI, having worked on projects with many industry leaders. She has published widely on data science and semantic technologies.

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Presentation

Integrating VR and CARLA for realistic vulnerable road user simulations

Driving simulators often struggle to accurately simulate vulnerable road users (VRUs) in safety-critical scenarios. We present a framework integrating immersive virtual reality and human motion capture with the CARLA driving simulator. This setup allows simulations where real human agents act as VRUs interacting with an AI-equipped ego car featuring advanced ADAS functions. It enables testing and validation of new ADAS features with real pedestrian behaviors, providing valuable data on VRU reactions in dynamic traffic environments. This approach enhances the realism of VRU simulations and supports the development and evaluation of safer, more effective ADAS technologies for real-world applications.