DMV-AVP: Distributed Multi-Vehicle Autonomous Valet Parking Using Autoware

Fuente: arXiv
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Autori principali: Islam, Zubair, El-Darieby, Mohamed
Natura: Preprint
Pubblicazione: 2026
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author Islam, Zubair
El-Darieby, Mohamed
author_facet Islam, Zubair
El-Darieby, Mohamed
contents 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
format Preprint
id arxiv_https___arxiv_org_abs_2601_16327
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle DMV-AVP: Distributed Multi-Vehicle Autonomous Valet Parking Using Autoware
Islam, Zubair
El-Darieby, Mohamed
Robotics
Artificial Intelligence
Multiagent Systems
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
title DMV-AVP: Distributed Multi-Vehicle Autonomous Valet Parking Using Autoware
topic Robotics
Artificial Intelligence
Multiagent Systems
url https://arxiv.org/abs/2601.16327