🤖 AI Summary
This work proposes the first autonomous valet parking (AVP) system based on a distributed multi-vehicle architecture, termed DMAVA, addressing the limitations of existing centralized simulation frameworks that struggle to support scalable, fully autonomous coordination among multiple vehicles. The system integrates Autoware, Unity, and a YOLOv5-based visual perception module, and leverages the Zenoh communication middleware to enable low-latency message passing. Through a combination of state coordination, queuing strategies, and a parking-slot reservation mechanism, DMAVA achieves conflict-free and deterministic cooperative parking in multi-host environments. Experimental validation on two to three hosts demonstrates strong scalability and collaborative performance, establishing a foundation for future real-vehicle deployment and hardware-in-the-loop testing.
📝 Abstract
This paper presents DMV-AVP, a distributed simulation of Multi-Vehicle Autonomous Valet Parking (AVP). The system was implemented as an application of the Distributed Multi-Autonomous 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 DMAVA: 1) the Multi-Vehicle AVP Coordination Framework, composed of AVP Managers and a per-vehicle AVP Node, is responsible for global parking state tracking, vehicle queuing, parking spot reservation, lifecycle coordination, and conflict resolution across multiple vehicles, and 2) the Unity-Integrated YOLOv5 Parking Spot Detection Module, that provides real-time, vision-based perception within AWSIM Labs. Both modules integrate seamlessly with DMAVA and extend it specifically for multi-vehicle AVP operation, supported by a Zenoh communication layer that ensures high data accuracy and controllability across hosts. Experiments conducted on two- and three-host configurations demonstrate consistent coordination, conflict-free parking behavior, and scalable performance across distributed Autoware instances. The results confirm that the proposed DMV-AVP 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