Simulating and validating coordination among multiple autonomous vehicles remains challenging, as many existing simulation architectures are limited to single-vehicle operation or rely on centralized control. This paper presents the Distributed Multi-Autonomous Vehicle Architecture (DMAVA), a simulation architecture that enables concurrent execution of multiple independent vehicle autonomy stacks distributed across multiple physical hosts within a shared simulation environment. Each vehicle operates its own complete autonomous driving stack while maintaining coordinated behavior through a data-centric communication layer. The proposed system integrates ROS 2 Humble, Autoware Universe, AWSIM Labs, and Zenoh to support high data accuracy and controllability during multi-vehicle simulation, enabling consistent perception, planning, and control behavior under distributed execution. Experiments conducted on multiple-host configurations demonstrate stable localization, reliable inter-host communication, and consistent closed-loop control under distributed execution. DMAVA also serves as a foundation for Multi-Vehicle Autonomous Valet Parking, demonstrating its extensibility toward higher-level cooperative autonomy. Demo videos and source code are available at: https://github.com/zubxxr/distributed-multi-autonomous-vehicle-architecture.

翻译：模拟和验证多辆自动驾驶车辆之间的协调仍然具有挑战性，因为许多现有的仿真架构仅限于单车操作或依赖于集中式控制。本文提出了分布式多自动驾驶车辆架构，这是一种仿真架构，能够在共享仿真环境中支持分布在多个物理主机上的多个独立车辆自主堆栈的并发执行。每辆车运行其自身完整的自动驾驶堆栈，同时通过以数据为中心的通信层保持协调行为。所提出的系统集成了ROS 2 Humble、Autoware Universe、AWSIM Labs和Zenoh，以支持多车仿真期间的高数据准确性和可控性，从而在分布式执行下实现一致的感知、规划和控制行为。在多主机配置上进行的实验证明了在分布式执行下稳定的定位、可靠的主机间通信以及一致的闭环控制。DMAVA还可作为多车自主代客泊车的基础，展示了其向更高级别协同自主性的可扩展性。演示视频和源代码可在以下网址获取：https://github.com/zubxxr/distributed-multi-autonomous-vehicle-architecture。