Abstract Developing and evaluating connected and autonomous vehicles mobility is inherently complex. To capture vehicle dynamics, perception and decision-making, and also realistic communication behavior, it requires dedicated simulation environments for traffic respectively, flow modeling, vehicle dynamics, and communication networks. Integrated tool that supports all these capabilities simultaneously remain scarce. When further considering the requirement that algorithms developed in simulation should be directly transferable to real-world deployments, existing solutions prove insufficient. This paper presents a novel modular co-simulation framework designed to support comprehensive experimentation across the broad spectrum of Intelligent Transportation Systems, which integrates three widely used tools: RTMaps for real-time data processing and algorithm prototyping, CARLA for high-fidelity vehicle and environment simulation, and NS-3 for detailed network and V2X communication modeling. The main contribution of this work is a modular and extensible toolchain that enables synchronized, closed-loop simulation of perception, control, and communication layers within a single experimental workflow. The proposed framework facilitates reproducible evaluation of Connected and Autonomous Vehicles use cases under realistic traffic and network conditions. An urban intersection with obstructed visibility representative scenario is presented to demonstrate the capabilities of this framework and to highlight its relevance for the design and assessment of cooperative driving applications. Furthermore, the framework supports seamless transition from simulation to real-world testing, as the same vehicle-dynamics control algorithms can be executed on physical vehicles without modification.
Hilt et al. (Fri,) studied this question.
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