Calibrating Wayfinding Decisions in Pedestrian Simulation Models: The Entropy Map
Human-Computer Interaction
2019-09-10 v1 Artificial Intelligence
Abstract
This paper presents entropy maps, an approach to describing and visualising uncertainty among alternative potential movement intentions in pedestrian simulation models. In particular, entropy maps show the instantaneous level of randomness in decisions of a pedestrian agent situated in a specific point of the simulated environment with an heatmap approach. Experimental results highlighting the relevance of this tool supporting modelers are provided and discussed.
Keywords
Cite
@article{arxiv.1909.03054,
title = {Calibrating Wayfinding Decisions in Pedestrian Simulation Models: The Entropy Map},
author = {Luca Crociani and Giuseppe Vizzari and Stefania Bandini},
journal= {arXiv preprint arXiv:1909.03054},
year = {2019}
}
Comments
pre-print of paper presented at the The 16th International Conference on Modeling Decisions for Artificial Intelligence, Milan, Italy September 4 - 6, 2019. arXiv admin note: substantial text overlap with arXiv:1610.07901