A Unified Pedestrian Routing Model Combining Multiple Graph-Based Navigation Methods

Abstract

The navigation behavior of pedestrians in street networks can be forecast by computer simulations based on routing models. These models characterize pedestrians' route choices regarding a variety of factors. However, the spatial cog-nition aspects are often omitted in routing models; thus, the diversity of predictable routes is limited. Here, we present a unified routing model that describes route choices of pedestrians by integrating the spatial cognitive aspects of allocentric-based and egocentric-based navigation. We achieved this by combining graph-based routing methods, each formalizing a single spatial cognitive aspect. In addition, we present a generic calibration method for our model. For validation, we show that our model is able to correctly predict the routing behavior of pedestrians in a case study.