André Dietrich

André Dietrich serves as a Researcher at the Department of Ergonomics, Technical University of Munich, since March 2015. His work centers on pedestrian-vehicle interactions within automated driving contexts, utilizing advanced simulation methodologies and field studies to enhance urban traffic safety.

Education:

• Diploma in Aerospace Engineering from Technical University of Munich specializing in aircraft propulsion and aerospace engineering
• Completed diploma thesis "Feasibility Analysis of a Pedestrian Simulator" in December 2014

Research Interests: Dietrich investigates pedestrian crossing behavior in automated urban environments through human factors and ergonomics frameworks. His work pioneers external human-machine interfaces (eHMIs) for vehicle-pedestrian communication, examining kinematic effects, cultural influences, and age-related perception differences. Key methodologies include augmented reality simulations, LiDAR-based field observations, and motion-platform pedestrian simulators to capture behavioral nuances in traffic scenarios. His research directly addresses safety challenges posed by increasing vehicle automation levels in complex urban settings.

Publication Trends: Analysis of Dietrich's 12 publications (2016-2022) reveals consistent focus on pedestrian-AV interaction mechanisms. His work demonstrates evolving methodologies from controlled simulator studies toward real-world field validations, with growing emphasis on inclusive eHMI design for diverse user groups. Cross-cultural comparisons and technical innovations in projection-based interfaces represent significant thematic threads across his publication history.

Advising and Grants: No student supervision or grant funding details are documented in the provided materials.

Labs and Infrastructure: Dietrich operates within TUM's Ergonomics Chair facilities including the Dynamical Mock-Up, Modular Ergonomic Mockup, Static Driving Simulator, and robotics labs. These resources support his research on cabin design, automated driving systems, and human-robot interaction within traffic contexts.