TY - THES A1 - Reddy, Aramalla Saipriya T1 - Enhancing user experience in Carla through optimization of AI/ML-based real-world map import N2 - This master thesis investigates enhancing user experience (UX) in driving simulators by optimizing AI/ML-based processes for importing real-world map data. The research addresses the challenges of accurately replicating real-world environments in simulations, focusing on the CARLA, an open-source simulator, as a case study. A mixed-methods approach is employed, combining a preliminary survey of 111 participants with in-depth interviews of 10 driving simulator experts. The findings reveal a strong preference for real-world map data over synthetic data, highlighting its impact on perceived realism, accuracy, and overall User Experience. The optimization process utilized YOLOv8 models for object detection, specifically for identifying buildings and trees, and MATLAB, a licenced tool for processing spatial relationships and creating virtual environments. These AI-driven enhancements ensure fidelity and realism in the imported maps. The research also identifies technical challenges in data integration and emphasises the need for user-friendly tools and interfaces. The study concludes with recommendations for enhancing UX in driving simulators, including prioritising real-world data and incorporating real-time feedback mechanisms. The implications of this research extend to the broader field of autonomous vehicle (AV) development, offering insights into creating realistic and practical simulation driving environments for testing and validating autonomous driving algorithms. Y1 - 2024 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-49850 CY - Ingolstadt ER -