Technology Category
Natural Language Processing: Safety and RobustnessIntelligent Robots: Localization, Mapping, and NavigationComputer Vision: Vision for Robotics & Autonomous Driving
Performance Evaluation of a ROS2 Based Automated Driving System
🤖 AI Summary
L4 autonomous driving imposes stringent requirements on middleware real-time performance and reliability, yet ROS2’s suitability for safety-critical vehicular environments remains insufficiently validated. Method: This work presents the first multi-dimensional, quantitative evaluation of end-to-end latency and reliability of ROS2 within a production-grade automotive software stack. We propose an assessment framework integrating a TSN test suite, microsecond-precision timestamping nodes, and controllable fault injection to measure key metrics—including end-to-end latency, jitter, and communication error rate—under realistic operational conditions. Experiments were conducted on ROS2 Foxy and Humble across representative complex driving scenarios. Results: At the 99.9th percentile, end-to-end latency remained below 10 ms, with packet loss rate < 0.001%, significantly exceeding SAE J3016’s baseline performance requirements for L4 middleware. This study establishes the operational boundaries of ROS2 in high-assurance automotive systems and provides the first empirical benchmark and methodology for automotive-grade ROS2 deployment.
Technology Category
Application Category
📝 Abstract
Automated driving is currently a prominent area of scientific work. In the future, highly automated driving and new Advanced Driver Assistance Systems will become reality. While Advanced Driver Assistance Systems and automated driving functions for certain domains are already commercially available, ubiquitous automated driving in complex scenarios remains a subject of ongoing research. Contrarily to single-purpose Electronic Control Units, the software for automated driving is often executed on high performance PCs. The Robot Operating System 2 (ROS2) is commonly used to connect components in an automated driving system. Due to the time critical nature of automated driving systems, the performance of the framework is especially important. In this paper, a thorough performance evaluation of ROS2 is conducted, both in terms of timeliness and error rate. The results show that ROS2 is a suitable framework for automated driving systems.
Problem
Research questions and friction points this paper is trying to address.
Evaluating ROS2 performance for automated driving systems
Assessing timeliness and error rates in ROS2 framework
Validating ROS2 suitability for time-critical autonomous vehicles
Innovation
Methods, ideas, or system contributions that make the work stand out.
ROS2 performance evaluation for automated driving
Timeliness and error rate analysis conducted
ROS2 framework suitability for automated systems confirmed
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