Open-Source Autonomous Driving Software Platforms: Comparison of Autoware and Apollo
Hee-Yang Jung, Dong-Hee Paek, and Seung-Hyun Kong

TL;DR
This paper provides a detailed comparison of the core modules and middleware performance of two leading open-source autonomous driving platforms, Autoware and Apollo, to guide selection and development in the field.
Contribution
It offers the first systematic, quantitative comparison of Autoware and Apollo's capabilities, focusing on core modules and middleware performance.
Findings
Identified key differences in core modules
Evaluated middleware performance metrics
Provided practical guidance for platform selection
Abstract
Full-stack autonomous driving system spans diverse technological domains-including perception, planning, and control-that each require in-depth research. Moreover, validating such technologies of the system necessitates extensive supporting infrastructure, from simulators and sensors to high-definition maps. These complexities with barrier to entry pose substantial limitations for individual developers and research groups. Recently, open-source autonomous driving software platforms have emerged to address this challenge by providing autonomous driving technologies and practical supporting infrastructure for implementing and evaluating autonomous driving functionalities. Among the prominent open-source platforms, Autoware and Apollo are frequently adopted in both academia and industry. While previous studies have assessed each platform independently, few have offered a quantitative and…
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Taxonomy
TopicsAutonomous Vehicle Technology and Safety
