Here is a selection of some projects I did over the years
Here is a selection of some projects I did over the years
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In my professional journey, I've had the privilege of leading and collaborating on projects with diverse teams.
Smart LensOur project introduces Smart Lens, an augmented reality lens designed to enhance daily activities. Smart Lens seamlessly integrates with smartphones to project essential information into the user's field of vision, simplifying tasks such as navigation and fitness. Through our development efforts, we've created a practical solution that facilitates smoother interactions with technology in everyday life.
WürGloveData gloves in retail are too costly. To address this, my team and I developed a prototype for a more affordable version. Our glove provides precise hand position and movement data to computers, allowing immersive gaming experiences without the need for a mouse or keyboard. We showcased our innovation at the University of Würzburg.
AutoMateAutoMate is dedicated to crafting the "TeamMate Car," a vehicle blending the strengths of highly automated driving with human capabilities. This innovative car collaborates with drivers during critical moments, bridging gaps where automation falls short. Our department assesses this partnership, refining human-vehicle interaction through cutting-edge situation comprehension concepts.
FATThe rise of driver assistance systems has paved the way for significant advancements in automated driving, reshaping future mobility and transportation. However, even with SAE L2 and L3 systems, human involvement remains crucial for ensuring safety. Maintaining adequate situation awareness is pivotal, yet challenging, especially in safety-critical scenarios. To address this, our project aimed to develop and validate an algorithm for dynamically assessing situation awareness in the context of SAE L2 and L3 automation. This involved modeling cognitive processes and observable correlates to infer and evaluate the driver's real-time situation awareness status, essential for designing adaptive driver-vehicle interactions. Our approach utilized dynamic Bayesian networks (DBNs) to capture the complexities of situation awareness, allowing for real-time assessment and validation in experimental studies conducted at the University of Ulm's Human Factors department's driving simulator.
Compilation of appropriate safety indicators for the evaluation of MMI of level 3 systemsThe project aimed to develop a checklist for evaluating the safety of MMI (Man-Machine Interface) in level 3 autonomous systems. We identified relevant publication channels and systematically developed a comprehensive keyword collection. We collected and analyzed relevant publications meeting the criteria of scientific papers. A meta-analysis was conducted on the gathered publications to identify pertinent safety indicators. The results of the meta-analysis were used to supplement previously published results on safety indicators, including those from predecessor projects for Level 2 systems. The findings from the literature research and meta-analysis were condensed into a checklist, which underwent evaluation in expert interviews and for which a concept for digitization was developed.
SEMULINIn the SEMULIN project, we aimed to develop a natural and seamless communication system for automated driving vehicles. By incorporating multimodal input and output concepts, including facial expressions and gestures, along with environmental cues, our goal was to create a self-supporting interaction model. This model, inspired by human-human communication, utilizes advanced sensor technology and semantic interpretation algorithms to enable effective communication in various driving scenarios, from fully automated to driver-controlled.
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