DMAVA: Distributed Multi-Autonomous Vehicle Architecture Using Autoware
On the map: End-to-end autonomous driving → Cooperative and V2X driving
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Cooperative and V2X driving, one of 9 directions in End-to-end autonomous driving. Builds on 5 of its 38 references that are in the map. First posted on arXiv 22 Jan 2026.
Builds on
5 of 38 references.
References · 5
- 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
- 2022A Survey on Automated Driving System Testing: Landscapes and Trendscited by 36
- 2024CARLA-Autoware-Bridge: Facilitating Autonomous Driving Research with a Unified Framework for Simulation and Module Developmentcited by 5
- 2025A Vehicle-in-the-Loop Simulator with AI-Powered Digital Twins for Testing Automated Driving Controllerscited by 1
- 2025A Workflow for Map Creation in Autonomous Vehicle Simulationscited by 1
Built on by
Citing papers per year: 2026: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
- 2023Multi-Agent Deep Reinforcement Learning for Cooperative and Competitive Autonomous Vehicles using AutoDRIVE Ecosystem
- 2024Towards Validation of Autonomous Vehicles Across Scales using an Integrated Digital Twin Framework
- 2022AutoDRIVE: A Comprehensive, Flexible and Integrated Digital Twin Ecosystem for Enhancing Autonomous Driving Research and Education
- 2024Towards Safe and Robust Autonomous Vehicle Platooning: A Self-Organizing Cooperative Control Framework
- 2026Multi-Agent Embodied Autonomous Driving (MAEAD): From V2X Information Exchange to Shared World Models
- 2026CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models
- 2025CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving
- 2024End-to-End Autonomous Driving through V2X Cooperation