Wayfinding and cognitive maps for pedestrian models

TL;DR

This paper introduces a new wayfinding model for pedestrian dynamics that incorporates individual spatial knowledge with inaccuracies and uncertainties, leading to more realistic simulations of pedestrian movement.

Contribution

It proposes a novel pedestrian wayfinding model that accounts for partial and uncertain spatial knowledge, improving realism over traditional models.

Findings

Model successfully simulates pedestrian behavior with incomplete knowledge

Incorporates knowledge-driven search strategies

Tested on a fictive scenario demonstrating effectiveness

Abstract

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.