Wayfinding and cognitive maps for pedestrian models
This addresses the problem of unrealistic pedestrian behavior in simulations for urban planning or safety applications, but it appears incremental as it builds on existing models with added cognitive elements.
The paper tackled the unrealistic assumption of global knowledge in pedestrian routing models by introducing a wayfinding model that incorporates individual spatial knowledge with inaccuracies and uncertainties, and tested it on a fictive scenario.
Usually, routing models in pedestrian dynamics assume that agents have fulfilled and global knowledge about the building's structure. However, they neglect the fact that pedestrians possess no or only parts of information about their position relative to final exits and possible routes leading to them. To get a more realistic description we introduce the systematics of gathering and using spatial knowledge. A new wayfinding model for pedestrian dynamics is proposed. The model defines for every pedestrian an individual knowledge representation implying inaccuracies and uncertainties. In addition, knowledge-driven search strategies are introduced. The presented concept is tested on a fictive example scenario.