AUTOSAR AP and ROS 2 Collaboration Framework

TL;DR

The paper tackles the interoperability gap between AUTOSAR AP and ROS 2 in autonomous vehicle development, driven by licensing and tooling disparities. It introduces a DDS-SOME/IP bridge converter implemented as a ROS 2 node, leveraging CommonAPI and vsomeip, along with a FIDL Automatic Generator to auto-create configuration files. Empirical evaluation shows the bridge achieves low conversion latency (sub-100 microseconds in tests) and enables ROS 2 tooling like Rviz and ROSbag to operate with AUTOSAR AP, facilitating visualization, debugging, and smoother transition from research to commercial development. Collectively, this work supports a SOAFEE-inspired mixed AUTOSAR AP and ROS 2 ecosystem, reducing integration friction and accelerating adoption of software-defined vehicle paradigms. Future work will extend message-type support and push toward deployment on actual hardware beyond QEMU-based AUTOSAR AP simulations.

Abstract

The field of autonomous vehicle research is advancing rapidly, necessitating platforms that meet real-time performance, safety, and security requirements for practical deployment. AUTOSAR Adaptive Platform (AUTOSAR AP) is widely adopted in development to meet these criteria; however, licensing constraints and tool implementation challenges limit its use in research. Conversely, Robot Operating System 2 (ROS 2) is predominantly used in research within the autonomous driving domain, leading to a disparity between research and development platforms that hinders swift commercialization. This paper proposes a collaboration framework that enables AUTOSAR AP and ROS 2 to communicate with each other using a Data Distribution Service for Real-Time Systems (DDS). In contrast, AUTOSAR AP uses Scalable service-Oriented Middleware over IP (SOME/IP) for communication. The proposed framework bridges these protocol differences, ensuring seamless interaction between the two platforms. We validate the functionality and performance of our bridge converter through empirical analysis, demonstrating its efficiency in conversion time and ease of integration with ROS 2 tools. Furthermore, the availability of the proposed collaboration framework is improved by automatically generating a configuration file for the proposed bridge converter.

Figures (12)

• Figure 1: The rough architecture proposed in this study.
• Figure 2: Communication between AUTOSAR AP applications.
• Figure 3: Communication between ROS 2 nodes.
• Figure 4: Comparison of DDS and SOME/IP send/receive sequences.
• Figure 5: Publish/Subscribe model.