Towards Real-Time Credible and Scalable Agent-Based Simulations of Autonomous Pedestrians Navigation

International audience In this paper, we focus on real-time simulation of autonomous pedestrians navigation. We introduce a Macroscopic-Influenced Microscopic (MIM) approach which aims at reducing the gap between microscopic and macroscopic approaches by providing credible walking paths for a potent...

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Bibliographic Details
Published in:Proceedings of the 20th ACM Symposium on Virtual Reality Software and Technology - VRST '14
Main Authors: Simo Kanmeugne, Patrick, Beynier, Aurélie
Other Authors: Systèmes Multi-Agents (SMA), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)
Format: Conference Object
Language:English
Published: HAL CCSD 2014
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Online Access:https://hal.science/hal-01217231
https://doi.org/10.1145/2671015.2671030
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Summary:International audience In this paper, we focus on real-time simulation of autonomous pedestrians navigation. We introduce a Macroscopic-Influenced Microscopic (MIM) approach which aims at reducing the gap between microscopic and macroscopic approaches by providing credible walking paths for a potentially highly congested crowd of autonomous pedestrians. Our approach originates from a least-effort formulation of the navigation task, which allows us to consistently account for congestion at every level of decision. We use the multi-agent paradigm and describe pedestrians as autonomous and situated agents who plan dynamically for energy efficient paths and interact with each other through the environment. The navigable space is considered as a set of contiguous resources that agents use to build their paths. We emulate the dynamic path computation for each agent with an evolutionary search algorithm, especially designed to be executed in real-time, individually and autonomously. We have compared an implementation of our approach with the ORCA model, on low density and high density scenarios, and obtained promising results in terms of credibility and scalability. We believe that ORCA model and other microscopic models could be easily extended to embrace our approach, thus providing richer simulations of potentially highly congested crowd of autonomous pedestrians.