Advancements in traffic simulations with multiMATSim’s distributed framework

Sara Moukir (1, 2) , Miwako Tsuji (3) , Nahid Emad (1, 2) , Mitsuhisa Sato (3) , Stephane Baudelocq (4)

1 MDLS - Maison de la Simulation
2 LI-PaRAD - Laboratoire d'Informatique Parallélisme Réseaux Algorithmes Distribués
3 RIKEN CCS - RIKEN Center for Computational Science [Kobe]
4 Groupe Eiffage

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.

Mots clés: Road Traffic Simulation; Big Data Analysis; High Performance Computing; Complex and Heterogeneous Dynamic System; Unite and Conquer; MATSim; Parallel Computing

Domaines: Informatique [cs]; Mathématiques [math]

Sara Moukir, Miwako Tsuji, Nahid Emad, Mitsuhisa Sato, Stephane Baudelocq. Advancements in traffic simulations with multiMATSim’s distributed framework. ICAART 2024 - the 16th International Conference on Agents and Artificial Intelligence, Feb 2024, rome, Italy. pp.374-385, ⟨10.5220/0012452600003636⟩. ⟨hal-04496277⟩