This paper presents the DMV-AVP System, a distributed simulation of Multi-Vehicle Autonomous Valet Parking (AVP). The system was implemented as an application of the Distributed Multi-Vehicle Architecture (DMAVA) for synchronized multi-host execution. Most existing simulation approaches rely on centralized or non-distributed designs that constrain scalability and limit fully autonomous control. This work introduces two modules built on top of the DMAVA: 1) a Multi-Vehicle AVP Node that performs state-based coordination, queuing, and reservation management across multiple vehicles, and 2) a Unity-Integrated YOLOv5 Parking Spot Detection Module that provides real-time, vision-based perception within AWSIM Labs. Both modules integrate seamlessly with the DMAVA and extend it specifically for multi-vehicle AVP operation, supported by a Zenoh-based communication layer that ensures low-latency topic synchronization and coordinated behavior across hosts. Experiments conducted on two- and three-host configurations demonstrate deterministic coordination, conflict-free parking behavior, and scalable performance across distributed Autoware instances. The results confirm that the proposed Distributed Multi-Vehicle AVP System supports cooperative AVP simulation and establishes a foundation for future real-world and hardware-in-the-loop validation. Demo videos and source code are available at https://github.com/zubxxr/multi-vehicle-avp

翻译：本文提出了DMV-AVP系统，一种用于多车自主代客泊车（AVP）的分布式仿真系统。该系统作为分布式多车架构（DMAVA）的一个应用实现，支持同步多主机执行。现有的大多数仿真方法依赖于集中式或非分布式设计，这限制了可扩展性并制约了完全自主控制。本工作基于DMAVA引入了两个模块：1）多车AVP节点，负责执行基于状态的多车协调、排队和车位预留管理；2）集成Unity的YOLOv5泊车位检测模块，在AWSIM Labs中提供基于视觉的实时感知。两个模块均与DMAVA无缝集成，并专门针对多车AVP操作进行了扩展，其底层由基于Zenoh的通信层支持，确保跨主机的低延迟主题同步与协调行为。在双主机和三主机配置上进行的实验证明了系统具有确定性协调、无冲突泊车行为，以及在分布式Autoware实例间可扩展的性能。结果证实，所提出的分布式多车AVP系统支持协作式AVP仿真，并为未来的实车测试和硬件在环验证奠定了基础。演示视频和源代码可在 https://github.com/zubxxr/multi-vehicle-avp 获取。