OpenCAMS: An Open-Source Connected and Automated Mobility Co-Simulation Platform for Advanced Transportation Research

2025-07-12

AI Summary

To address the challenges of large-scale traffic modeling, high-fidelity perception-based control, and co-simulation of C-V2X communications, this paper proposes and implements the first open-source, synchronized, and scalable multi-domain co-simulation platform. The platform achieves seamless integration of SUMO (microscopic traffic simulation), CARLA (3D perception and vehicle dynamics), and OMNeT++ (event-driven network communication) via a time-synchronized, bidirectional coupling architecture, resolving cross-domain consistency and modular integration bottlenecks. Its key innovation lies in a custom interface design enabling millisecond-level temporal alignment and closed-loop data exchange across simulators, thereby supporting joint validation of safety, efficiency, and cybersecurity in autonomous driving and cooperative ITS scenarios. Fully open-source, the platform ensures high reproducibility and flexible extensibility, providing a unified, high-fidelity experimental foundation for intelligent transportation systems research.

Technology Category

• Application Domains: Transportation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: Multi-modal Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Web Mining and Content Analysis: Web data generation and simulation
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

We introduce OpenCAMS (Open-Source Connected and Automated Mobility Co-Simulation Platform), an open-source, synchronized, and extensible co-simulation framework that tightly couples three best-in-class simulation tools: (i) SUMO, (ii) CARLA, and (iii) OMNeT++. OpenCAMS is designed to support advanced research in transportation safety, mobility, and cybersecurity by combining the strengths of each simulation domain. Specifically, SUMO provides large-scale, microscopic traffic modeling; CARLA offers high-fidelity 3D perception, vehicle dynamics, and control simulation; and OMNeT++ enables modular, event-driven network communication, such as cellular vehicle-to-everything (C-V2X). OpenCAMS employs a time-synchronized, bidirectional coupling architecture that ensures coherent simulation progression across traffic, perception, and communication domains while preserving modularity and reproducibility. For example, CARLA can simulate and render a subset of vehicles that require detailed sensor emulation and control logic; SUMO orchestrates network-wide traffic flow, vehicle routing, and traffic signal management; and OMNeT++ dynamically maps communication nodes to both mobile entities (e.g., vehicles) and static entities (e.g., roadside units) to enable C-V2X communication. While these three simulators form the foundational core of OpenCAMS, the platform is designed to be expandable and future-proof, allowing additional simulators to be integrated on top of this core without requiring fundamental changes to the system architecture. The OpenCAMS platform is fully open-source and publicly available through its GitHub repository https://github.com/minhaj6/carla-sumo-omnetpp-cosim, providing the research community with an accessible, flexible, and collaborative environment for advancing next-generation intelligent transportation systems.

Problem

• Integrates SUMO, CARLA, OMNeT++ for transportation research
• Enables synchronized simulation of traffic, perception, communication
• Provides open-source platform for intelligent transportation systems

Innovation

• Open-source co-simulation framework combining SUMO, CARLA, OMNeT++
• Time-synchronized bidirectional coupling for coherent simulation
• Expandable architecture for future simulator integration