Bridging the gap between visual exploration and agent-based pedestrian simulation in a virtual environment

We present a system to evaluate and improve visual guidance systems and signage for pedestrians inside large buildings. Given a 3D model of an actual building we perform agent-based simulations mimicking the decision making process and navigation patterns of pedestrians trying to find their way to predefined locations. Our main contribution is to enable agents to base their decisions on realistic threedimensional visibility and occlusion cues computed from the actual building geometry with added semantic annotations (e.g. meaning of signs, or purpose of inventory), as well as an interactive visualization of simulated movement trajectories and accompanying visibility data tied to the underlying 3D model. This enables users of the system to quickly pinpoint and solve problems within the simulation by watching, exploring and understanding emergent behavior inside the building. This insight gained from introspection can in turn inform planning and thus improve the effectiveness of guidance systems.

[1]  Tomas Akenine-Möller,et al.  Real-time rendering, 3rd Edition , 2008 .

[2]  Dietmar Bauer,et al.  Comparing pedestrian movement simulation models for a crossing area based on real world data , 2011 .

[3]  J. Charles Hourcade,et al.  Algorithms for antialiased cast shadows , 1985, Comput. Graph..

[4]  Mirosław Lachowicz,et al.  Microscopic, mesoscopic and macroscopic descriptions of complex systems , 2011 .

[5]  Céline Loscos,et al.  Visualizing Crowds in Real‐Time , 2002, Comput. Graph. Forum.

[6]  Soraia Raupp Musse,et al.  Modeling individual behaviors in crowd simulation , 2003, Proceedings 11th IEEE International Workshop on Program Comprehension.

[7]  Eric W. Marchant,et al.  Testing and application of the computer model ‘SIMULEX’ , 1995 .

[8]  Elmar Eisemann,et al.  Real-Time Shadows , 2011 .

[9]  Edwin R. Galea,et al.  Signage Legibility Distances as a Function of Observation Angle , 2007 .

[10]  Daniel Thalmann,et al.  Crowd simulation , 2007 .

[11]  H. Neuschmied,et al.  Realistic Interactive Pedestrian Simulation and Visualization for Virtual 3D Environments , 2009, 2009 15th International Conference on Virtual Systems and Multimedia.

[12]  Demetri Terzopoulos,et al.  Autonomous pedestrians , 2007, Graph. Model..

[13]  Stephan Mantler,et al.  Interactive person path analysis in reconstructed public buildings , 2009, SCCG.

[14]  Lance Williams,et al.  Casting curved shadows on curved surfaces , 1978, SIGGRAPH.

[15]  Serge P. Hoogendoorn,et al.  Pedestrian route-choice and activity scheduling theory and models , 2004 .

[16]  Helmut Schrom-Feiertag,et al.  Creating a richer data source for 3D pedestrian flow simulations in public transport , 2010, MB '10.

[17]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[18]  D. Helbing,et al.  Analysis of Empirical Trajectory Data of Pedestrians , 2010 .

[19]  Michael Wimmer,et al.  Guided visibility sampling , 2006, ACM Trans. Graph..

[20]  Frédo Durand,et al.  A Survey of Visibility for Walkthrough Applications , 2003, IEEE Trans. Vis. Comput. Graph..

[21]  Norman I. Badler,et al.  Controlling individual agents in high-density crowd simulation , 2007, SCA '07.