Citation

Kneidl A, Hartmann D, Borrmann A. Transp. Res. C Emerg. Technol. 2013; 37: 223-237.

Copyright

(Copyright © 2013, Elsevier Publishing)

DOI

10.1016/j.trc.2013.03.005

PMID

unavailable

Abstract

One of the most important aspects for a realistic prediction of pedestrian flows is the modelling of human navigation in normal situations such as early design phases of buildings or transportation systems and hubs as well as in evacuation studies to enhance safety in existing infrastructures. To overcome the limitations of current navigation models, this paper proposes a new hybrid multi-scale model, which closely links information between the small-scale and large-scale navigation layer to improve the navigational behaviour. In the presented hybrid navigation model, graph-based methods using visibility graphs are used to model large-scale wayfinding decisions. The pedestrians' movements between two nodes of the navigation graph are modelled by means of a dynamic navigation field. The navigation field is updated dynamically during the runtime of the simulation, explicitly considering other pedestrians for determining the fastest path. The proposed hybrid approach provides a realistic modelling of human navigational behaviour and thus a realistic prediction of flows since it reflects the human cognitive processes triggered by wayfinding tasks. This includes taking into account other pedestrians for routing decisions who are visible from the current position of the considered pedestrian. The paper discusses the concept and the technical details of the proposed hybrid multi-scale approach in detail and presents an extensive case study demonstrating its advantages.