DMAVA: Distributed Multi-Autonomous Vehicle Architecture Using Autoware
This addresses the problem of multi-vehicle simulation for autonomous driving researchers, though it is incremental as it builds on existing tools like ROS 2 and Autoware.
The paper tackles the challenge of simulating and validating coordination among multiple autonomous vehicles by introducing DMAVA, a distributed simulation architecture that enables concurrent execution of independent vehicle autonomy stacks across multiple hosts, demonstrating stable localization and reliable communication in experiments.
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.