{"title":"AUTOSAR AP and ROS 2 Collaboration Framework for Development in Cloud Environment","authors":"Ryudai Iwakami;Bo Peng;Hiroyuki Hanyu;Tasuku Ishigooka;Takuya Azumi","doi":"10.1109/OJIES.2025.3607248","DOIUrl":null,"url":null,"abstract":"The development of autonomous vehicles is progressing rapidly. For practical implementation, platforms ensuring real-time performance, safety, and security are crucial. AUTOSAR adaptive platform (AUTOSAR AP) meets these needs and is widely used in development. However, it is rarely utilized in research due to licensing and tool availability issues. Instead, robot operating system 2 (ROS 2) is the main platform for autonomous vehicle research. This gap between research and development platforms hinders the swift application of research outcomes, delaying the practical implementation of autonomous vehicles. In addition, software-defined vehicle requires flexible software development in cloud environment. To address these challenges, this article proposes AUTOSAR AP and ROS 2 collaboration framework for development in cloud environment. ROS 2 uses data distribution service for communication, while AUTOSAR AP employs scalable service-oriented middleware over IP. The proposed framework bridges these protocols through conversion, enabling seamless communication. The functionality and performance of the proposed bridge converter are verified through measurements. The proposed bridge converter supports communication between AUTOSAR AP and ROS 2 in cloud environment and allows easy use of ROS 2 tools. Automating file generation further enhances the usability of the proposed collaboration framework.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1533-1545"},"PeriodicalIF":4.3000,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11153079","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of the Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11153079/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
The development of autonomous vehicles is progressing rapidly. For practical implementation, platforms ensuring real-time performance, safety, and security are crucial. AUTOSAR adaptive platform (AUTOSAR AP) meets these needs and is widely used in development. However, it is rarely utilized in research due to licensing and tool availability issues. Instead, robot operating system 2 (ROS 2) is the main platform for autonomous vehicle research. This gap between research and development platforms hinders the swift application of research outcomes, delaying the practical implementation of autonomous vehicles. In addition, software-defined vehicle requires flexible software development in cloud environment. To address these challenges, this article proposes AUTOSAR AP and ROS 2 collaboration framework for development in cloud environment. ROS 2 uses data distribution service for communication, while AUTOSAR AP employs scalable service-oriented middleware over IP. The proposed framework bridges these protocols through conversion, enabling seamless communication. The functionality and performance of the proposed bridge converter are verified through measurements. The proposed bridge converter supports communication between AUTOSAR AP and ROS 2 in cloud environment and allows easy use of ROS 2 tools. Automating file generation further enhances the usability of the proposed collaboration framework.
期刊介绍:
The IEEE Open Journal of the Industrial Electronics Society is dedicated to advancing information-intensive, knowledge-based automation, and digitalization, aiming to enhance various industrial and infrastructural ecosystems including energy, mobility, health, and home/building infrastructure. Encompassing a range of techniques leveraging data and information acquisition, analysis, manipulation, and distribution, the journal strives to achieve greater flexibility, efficiency, effectiveness, reliability, and security within digitalized and networked environments.
Our scope provides a platform for discourse and dissemination of the latest developments in numerous research and innovation areas. These include electrical components and systems, smart grids, industrial cyber-physical systems, motion control, robotics and mechatronics, sensors and actuators, factory and building communication and automation, industrial digitalization, flexible and reconfigurable manufacturing, assistant systems, industrial applications of artificial intelligence and data science, as well as the implementation of machine learning, artificial neural networks, and fuzzy logic. Additionally, we explore human factors in digitalized and networked ecosystems. Join us in exploring and shaping the future of industrial electronics and digitalization.