AuNa: Modularly Integrated Simulation Framework for Cooperative Autonomous Navigation

Harun Teper, Anggera Bayuwindra, Raphael Riebl, Ricardo Severino, Jian-Jia Chen, Kuan-Hsun Chen

Research output: Working paperPreprintAcademic

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Abstract

In the near future, the development of autonomous driving will get more complex as the vehicles will not only rely on their own sensors but also communicate with other vehicles and the infrastructure to cooperate and improve the driving experience. Towards this, several research areas, such as robotics, communication, and control, are required to collaborate in order to implement future-ready methods. However, each area focuses on the development of its own components first, while the effects the components may have on the whole system are only considered at a later stage. In this work, we integrate the simulation tools of robotics, communication and control namely ROS2, OMNeT++, and MATLAB to evaluate cooperative driving scenarios. The framework can be utilized to develop the individual components using the designated tools, while the final evaluation can be conducted in a complete scenario, enabling the simulation of advanced multi-robot applications for cooperative driving. Furthermore, it can be used to integrate additional tools, as the integration is done in a modular way. We showcase the framework by demonstrating a platooning scenario under cooperative adaptive cruise control (CACC) and the ETSI ITS-G5 communication architecture. Additionally, we compare the differences of the controller performance between the theoretical analysis and practical case study.
Original languageEnglish
PublisherarXiv.org
Publication statusPublished - 12 Jul 2022

Keywords

  • cs.RO
  • cs.SY
  • eess.SY

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