Pedestrians are not robots: although observations show that they consider congestion when planning, there are evidences that their decisions are not optimal, even in normal situations. We present a model improving consolidated results mitigating the optimization effects of congestion aware path planning by making commonsense estimations of the effects of perceivable congestion, also embedding an imitation mechanism stimulating changes in planned decisions whenever another nearby pedestrian did the same.

Crociani, L., Vizzari, G., Bandini, S. (2018). Neither dumb nor optimal: Plausible wayfinding in pedestrian agent-based models. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS (pp.1918-1920). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

Neither dumb nor optimal: Plausible wayfinding in pedestrian agent-based models

Crociani, L
;
Vizzari, G;Bandini, S
2018

Abstract

Pedestrians are not robots: although observations show that they consider congestion when planning, there are evidences that their decisions are not optimal, even in normal situations. We present a model improving consolidated results mitigating the optimization effects of congestion aware path planning by making commonsense estimations of the effects of perceivable congestion, also embedding an imitation mechanism stimulating changes in planned decisions whenever another nearby pedestrian did the same.
abstract + poster
Agent-based simulation; Pedestrian simulation; Wayfinding
English
17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
2018
Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
9781510868083
2018
3
1918
1920
http://dl.acm.org/event.cfm?id=RE146&tab=pubs
none
Crociani, L., Vizzari, G., Bandini, S. (2018). Neither dumb nor optimal: Plausible wayfinding in pedestrian agent-based models. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS (pp.1918-1920). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/218863
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