A unified pedestrian routing model for graph-based wayfinding built on cognitive principles

The wayfinding behavior of pedestrians in street and building networks can be predicted by computer simulations based on routing models. To model realistic routing behavior, it is necessary to integrate spatial- and social-cognitive aspects into the wayfinding models. However, a model that incorporates diverse influencing factors on pedestrian route planning has yet not been developed for microscopic simulations. We present a unified routing model that describes pedestrian route choices in street and building environments by integrating spatial- and social-cognitive aspects. We achieve an integration of both domains by combining different graph-based routing methods, each formalizing a cognitive theory. In addition, we present a calibration method for the spatial-cognitive aspects. For validation purposes, we use the model to simulate how the visitors of a music festival navigate to the event and how people navigate in a city district. Our methodology is highly flexible and can be extended to include other aspects of wayfinding behavior.