Advancements in Traffic Simulations with multiMATSim’s Distributed Framework

Sara Moukir, Sara Moukir, Miwako Tsuji, Nahid Emad, Mitsuhisa Sato, Stephane Baudelocq

2024

Abstract

In an era characterized by massive volumes of data, the demand for advanced road traffic simulators has reached an even greater scale. In response to this call, we propose an approach applied to MATSim, specifically called multiMATSim. Beyond its tailor-made implementation in MATSim, this innovative approach is designed with generic intent, aiming for adaptability to a variety of multi-agent traffic simulators. Its strength lies in its blend of versatility and adaptability. Fortified by a multi-level parallelism and fault-tolerant framework, multiMATSim demonstrates promising scalability across diverse computing architectures. The results of our experiments on two parallel architectures based on x86 and ARM processors systematically underline the superiority of multiMATSim over MATSim. This especially in load scaling scenarios. We highlight the generality of the multiMATSim concept and its applicability to other road traffic simulators. We will also see how the proposed approach can contribute to the optimization of multi-agent road traffic simulators and, impact the simulation time thanks to its intrinsic parallelism.

Paper Citation

in Harvard Style

Moukir S., Tsuji M., Emad N., Sato M. and Baudelocq S. (2024). Advancements in Traffic Simulations with multiMATSim’s Distributed Framework. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 374-385. DOI: 10.5220/0012452600003636

in Bibtex Style

@conference{icaart24,
author={Sara Moukir and Miwako Tsuji and Nahid Emad and Mitsuhisa Sato and Stephane Baudelocq},
title={Advancements in Traffic Simulations with multiMATSim’s Distributed Framework},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2024},
pages={374-385},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012452600003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Advancements in Traffic Simulations with multiMATSim’s Distributed Framework
SN - 978-989-758-680-4
AU - Moukir S.
AU - Tsuji M.
AU - Emad N.
AU - Sato M.
AU - Baudelocq S.
PY - 2024
SP - 374
EP - 385
DO - 10.5220/0012452600003636
PB - SciTePress