SIMULATING KNOWLEDGE AND INFORMATION IN PEDESTRIAN EGRESS

Kyle Feuz, Vicki Allan

Abstract

Accurate pedestrian simulation is a difficult yet important task. One of the main challenges with pedestrian simulation is providing the simulated pedestrians with appropriate amounts of route knowledge to be used in the route selection algorithm. In this paper, we propose a novel use of reinforcement learning as a means to represent different amounts of route knowledge. Using this techniques we show the impact learning about route distances and average route congestion levels has upon the egress time of pedestrians. We also look at the effect that dynamic congestion information has upon the efficiency of pedestrian egress.

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Paper Citation


in Harvard Style

Feuz K. and Allan V. (2012). SIMULATING KNOWLEDGE AND INFORMATION IN PEDESTRIAN EGRESS . In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8425-96-6, pages 246-253. DOI: 10.5220/0003755202460253


in Bibtex Style

@conference{icaart12,
author={Kyle Feuz and Vicki Allan},
title={SIMULATING KNOWLEDGE AND INFORMATION IN PEDESTRIAN EGRESS},
booktitle={Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2012},
pages={246-253},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003755202460253},
isbn={978-989-8425-96-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - SIMULATING KNOWLEDGE AND INFORMATION IN PEDESTRIAN EGRESS
SN - 978-989-8425-96-6
AU - Feuz K.
AU - Allan V.
PY - 2012
SP - 246
EP - 253
DO - 10.5220/0003755202460253