MOSS: A Large-scale Open Microscopic Traffic Simulation System
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Abstract (arXiv)
In the research of Intelligent Transportation Systems (ITS), traffic simulation is a key procedure for the evaluation of new methods and optimization of strategies. However, existing traffic simulation systems face two challenges. First, how to balance simulation scale with realism is a dilemma. Second, it is hard to simulate realistic results, which requires realistic travel demand data and simulator. These problems limit computer-aided optimization of traffic management strategies for large-scale road networks and reduce the usability of traffic simulations in areas where real-world travel demand data are lacking. To address these problems, we design and implement MObility Simulation System (MOSS). MOSS adopts GPU acceleration to significantly improve the efficiency and scale of microscopic traffic simulation, which enables realistic and fast simulations for large-scale road networks. It provides realistic travel Origin-Destination (OD) matrices generation through a pre-trained generative neural network model based on publicly available data on a global scale, such as satellite imagery, to help researchers build meaningful travel demand data. It also provides a complete open toolchain to help users with road network construction, demand generation, simulation, and result analysis. The whole toolchain including the simulator can be accessed at https://moss.fiblab.net and the codes are open-source for community collaboration.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 May 2024.
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Citing papers per year: 2024: 3; 2025: 2; 2026: 1.
6 papers.
- 2024Up-sampling-only and Adaptive Mesh-based GNN for Simulating Physical Systemscited by 4
- 2025UrbanWorld2.0: A Multimodal Agentic Framework for Reality-Aligned 3D World Generation at City-Scalecited by 3
- 2025TrafficSimAgent: A Hierarchical Agent Framework for Autonomous Traffic Simulation with MCP Controlcited by 3
- 2024Gradient-based Trajectory Optimization with Parallelized Differentiable Traffic Simulationcited by 2
- 2024CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Controlcited by 1
- 2026Empirical Grounding Improves the Realism of LLM Agents Simulating Human Behavior During Disruptionscited by 0
- 2026Empirical Grounding Improves the Realism of LLM Agents Simulating Human Behavior During Disruptions19 Jul 2026
- 2025TrafficSimAgent: A Hierarchical Agent Framework for Autonomous Traffic Simulation with MCP Control24 Dec 2025
- 2025UrbanWorld2.0: A Multimodal Agentic Framework for Reality-Aligned 3D World Generation at City-Scale22 Nov 2025
- 2024Gradient-based Trajectory Optimization with Parallelized Differentiable Traffic Simulation21 Dec 2024
- 2024Up-sampling-only and Adaptive Mesh-based GNN for Simulating Physical Systems7 Sep 2024
- 2024CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control4 Jun 2024