mlsanityData to 7 Oct 2026

DMAVA: Distributed Multi-Autonomous Vehicle Architecture Using Autoware

arXiv 2601.16336 ↗First posted 22 Jan 2026cs.RO cs.AI cs.MAcited by 1

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

  1. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  2. 2022A Survey on Automated Driving System Testing: Landscapes and Trendscited by 36
  3. 2024CARLA-Autoware-Bridge: Facilitating Autonomous Driving Research with a Unified Framework for Simulation and Module Developmentcited by 5
  4. 2025A Vehicle-in-the-Loop Simulator with AI-Powered Digital Twins for Testing Automated Driving Controllerscited by 1
  5. 2025A Workflow for Map Creation in Autonomous Vehicle Simulationscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2023Multi-Agent Deep Reinforcement Learning for Cooperative and Competitive Autonomous Vehicles using AutoDRIVE Ecosystem
  2. 2024Towards Validation of Autonomous Vehicles Across Scales using an Integrated Digital Twin Framework
  3. 2022AutoDRIVE: A Comprehensive, Flexible and Integrated Digital Twin Ecosystem for Enhancing Autonomous Driving Research and Education
  4. 2024Towards Safe and Robust Autonomous Vehicle Platooning: A Self-Organizing Cooperative Control Framework
  5. 2026Multi-Agent Embodied Autonomous Driving (MAEAD): From V2X Information Exchange to Shared World Models
  6. 2026CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models
  7. 2025CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving
  8. 2024End-to-End Autonomous Driving through V2X Cooperation