Movement and Waiting of Crowds - State of the Art Models and Data

Explore a comprehensive keynote lecture by Prof. Dr. Armin Seyfried from Forschungszentrum Jülich that examines the evolution and current state of crowd movement modeling. Begin with a historical perspective on how data collection capabilities have shaped modeling approaches over time. Discover various contemporary modeling techniques for pedestrian movement in crowds, including cellular automata, force models, speed models, and machine learning-based trajectory prediction systems. Learn how individual movement options and collective phenomena are classified across different density ranges, with critical analysis of the strengths and weaknesses of each modeling approach. The final portion delves into empirical findings on waiting behavior, particularly in platforms and queueing systems for event venues, along with emerging modeling approaches for these scenarios.