Architecture platforms for future vehicles: a comparison of ROS2 and Adaptive AUTOSAR

Henle, Jacqueline; Stoffel, Martin; Schindewolf, Marc; Nägele, Ann-Therese; Sax, Eric

doi:10.1109/itsc55140.2022.9921894

Cited by 9 publications

(2 citation statements)

References 24 publications

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“…Recent studies have been conducted on the interoperability between Adaptive AU-TOSAR and ROS2, and on the application of ROS2 in vehicles. Jacqueline Henle compared ROS2 and Adaptive AUTOSAR to evaluate their suitability for future vehicle architectures [22]. Adaptive AUTOSAR, which applies Service-Oriented Architecture and Ethernet, provides wider bandwidth, and this makes it suitable for the architecture of future vehicles such as autonomous cars.…”

Section: Related Workmentioning

confidence: 99%

Autonomous Driving System Architecture with Integrated ROS2 and Adaptive AUTOSAR

Hong,

Moon

2024

Electronics

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In the automotive industry, research is now underway to apply Adaptive Automotive Open System Architecture (AUTOSAR) to the development of next-generation mobility, such as autonomous driving and connected cars. However, research on autonomous driving is being predominantly conducted on the robotics platform ROS2 (Robot Operating System 2). This demonstrates a considerable distance between autonomous driving research and its application in actual vehicles. To bridge this gap, interoperability that leverages the strengths of the Adaptive AUTOSAR and ROS2 platforms and compensates for their weaknesses is required. Therefore, this study proposes an architecture for interoperability between the two platforms, named Autonomous Driving System with Integrated ROS2 and Adaptive AUTOSAR (ASIRA). The proposed architecture enables communication between each of the two platforms through the ROS2 SOME/IP Bridge and allows for the necessary data exchange. It validates them in autonomous driving scenarios and goes beyond vehicle development, testing, and prototyping to exploit the advantages of each platform. Additionally, the simulation of autonomous vehicles within the ASIRA architecture is demonstrated by interoperating the ROS2 representative open-source autonomous driving project, Autoware, with the Adaptive AUTOSAR simulator. This study contributes to the assimilation of ROS2 into the automotive industry and its application in real vehicles by linking ROS2 and Adaptive AUTOSAR.

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Section: Related Workmentioning

confidence: 99%

Autonomous Driving System Architecture with Integrated ROS2 and Adaptive AUTOSAR

Hong,

Moon

2024

Electronics

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“…Specifically, the AUTOSAR (Automotive Open System Architecture) standard software architecture [66] is proposed in the automotive sector to eliminate dependence on hardware and increase software scalability. A comparative study of ROS2 and AUTOSAR as architectural platforms for future autonomous vehicles (AVs) was recently addressed in [67], pointing out that some AUTOSAR APIs and service functionalities can be completely fulfilled by ROS2, even though the standard implementation of ROS2 does not provide all the automotive functionalities and additional packages need to be added.…”

Section: Ros2: Other Applicationsmentioning

confidence: 99%

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

Bonci,

Gaudeni,

Giannini

et al. 2023

Applied Sciences

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Future challenges in manufacturing will require automation systems with robots that are increasingly autonomous, flexible, and hopefully equipped with learning capabilities. The flexibility of production processes can be increased by using a combination of a flexible human worker and intelligent automation systems. The adoption of middleware software such as ROS2, the second generation of the Robot Operating System, can enable robots, automation systems, and humans to work together on tasks that require greater autonomy and flexibility. This paper has a twofold objective. Firstly, it provides an extensive review of existing literature on the features and tools currently provided by ROS2 and its main fields of application, in order to highlight the enabling aspects for the implementation of modular architectures to increase autonomy in industrial operations. Secondly, it shows how this is currently potentially feasible in ROS2 by proposing a possible high-level and modular architecture to increase autonomy in industrial operations. A proof of concept is also provided, where the ROS2-based framework is used to enable a cobot equipped with an external depth camera to perform a flexible pick-and-place task.

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Revolutionizing Autonomous Vehicle Intelligence with Cutting-Edge Spatial Crowdsourcing Framework

Jain,

Saini,

Dodia

et al. 2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Architecture platforms for future vehicles: a comparison of ROS2 and Adaptive AUTOSAR

Cited by 9 publications

References 24 publications

Autonomous Driving System Architecture with Integrated ROS2 and Adaptive AUTOSAR

Autonomous Driving System Architecture with Integrated ROS2 and Adaptive AUTOSAR

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

Revolutionizing Autonomous Vehicle Intelligence with Cutting-Edge Spatial Crowdsourcing Framework

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