What is OCTAS®?

OCTAS® is a highly modular simulation framework, developed by Fraunhofer IOSB and various partners. Its main purpose is to provide a joint, efficient platform that connects independently-developed modules efficiently. Use cases for simulation differ widely, but they often require the many of the same building blocks, such as the simulation of sensors, physics, kinematics or human behavior.

Instead of developing and linking standalone, complete simulation softwares through co-simulation, OCTAS® allows compact binary plugins to collaborate on a joint, transparent world model.

Technical requirements

supported systems* Windows, Linux, macOS
setup* download & run (no installation required)
system requirements* depend largely on simulation complexity
license* Apache 2.0 unless otherwise noted
plugin development requirements* CMake, C++17 compiler (routinely tested with GCC, MS Visual, Clang)
predefined interfaces* ROS1, ROS2, CAN, DroneCAN, Mavlink, Blender

* This refers to OCTAS® as a framework and most base plugins. Specific plugin requirements may differ.

Interaction concepts

Task GUI XML Python C++
Running simulations and interacting at runtime
Building new simulations from existing plugins
Adding new simulation models
Adding new properties
Adding new interfaces
Rewriting the core

● Possible and widely supported  ○ Limited  — Not currently supported

Developers

Such plugins can be developed by anyone, on almost any system, using any compiler and toolchain. Developing in C++ gives you unlimited freedom to change any aspect of OCTAS® and connect your own software, while Python provides simple interfaces for many applications.

Developers can distribute their plugins commercially, or release their code as open source. With OCTAS®, developers can focus on what matters most: Developing better simulation models for their domain. Running the overall simulation, providing external interfaces, and adding other aspects of the world, is handled by the open OCTAS® core and the ecosystem of other developers.

Users

OCTAS® runs on a wide range of systems, in many cases even without installation. Commercial use of the framework is permitted, and thanks to the open framework, you own it and you keep it.

Building complex simulations is complex—we know. That’s why OCTAS® offers multiple interfaces. Many functions are available through the graphical user interface (GUI). Simply download the program and plugins, and run your first scenarios.

Once you are familiar with the framework, build your own scenarios using the general XML language: A selection of different models allows to tailor your individual simulation setup. Access the whole state of the simulation in a single source of truth at any time. Recombine plugins and modules, change levels of detail at runtime. Develop scenarios in the GUI, then run them from console or on servers.

Why another simulation framework?

Simulation requirements have increased considerably in the past decade. AI and autonomous systems have become increasingly complex agents fulfilling complex tasks in a complex world.

Developing these systems safely, efficiently and understandably requires a platform for modeling this complexity in a virtual space.

OCTAS® allows experts from any background to collaborate on modeling this world, piece by piece, plugin by plugin. It was designed to be the most flexible, versatile and general simulation framework there is—while still being as efficient and user friendly as possible.

If you want to take your simulations into your own hands, recombine modules according to your needs, and make sure to be forward-compatible with other developments, OCTAS® is the framework for you.

Background

OCTAS® has been developed since 2014 at Fraunhofer IOSB (then under the name OCTANE) along with several partners from industry, research and academia. It has been used and shared since then in various projects, with applications in automotive, urban air mobility, automatic train operation, public security, and space.

Open access datasets generated with OCTAS® are available under synset.de.

Research publications

2017 Ziehn, J. R., Beyerer, J., Filsinger, M., Frese, C., Roschani, M., Ruf, M., … & Rosenhahn, B.. A non-invasive cyberrisk in cooperative driving. In 8. Tagung Fahrerassistenz.
2018 Clausen, U., & Klingner IVI, M.. Automatisiertes Fahren: Computer greifen zum Steuer. In Digitalisierung: Schlüsseltechnologien für Wirtschaft und Gesellschaft (pp. 385-411). Berlin, Heidelberg: Springer Berlin Heidelberg.
2019 Clausen, U., & Klingner, M. . Automated Driving: Computers take the wheel. In Digital Transformation (pp. 371-396). Berlin, Heidelberg: Springer Berlin Heidelberg.
2019 Ziehn, J., Beyerer, F., Roschani, D. R., Flad, D. F., Hohmann, K., Lauber, P., & Sax, D. K. General Fail-Safe Emergency Stopping for Highly-Automated Vehicles. In 9. Tagung Automatisiertes Fahren.
2020 Ziehn, J. R., Roschani, M., Ruf, M., Bruestle, D., Beyerer, J., & Helmer, M. Imaging vehicle-to-vehicle communication using visible light. Advanced Optical Technologies, 9(6), 339-348.
2023 Baumann, M. V., Beyerer, J., Buck, H. S., Deml, B., Ehrhardt, S., Frese, C., … & Ziehn, J. R. Cooperative Automated Driving for Bottleneck Scenarios in Mixed Traffic. In 2023 IEEE Intelligent Vehicles Symposium (IV) (pp. 1-8). IEEE.
2024 Sielemann, A., Wolf, S., Roschani, M., Ziehn, J., & Beyerer, J. Synset Boulevard: a synthetic image dataset for VMMR. In 2024 IEEE International Conference on Robotics and Automation (ICRA) (pp. 9146-9153). IEEE.
2024 Eisemann, L., Fehling-Kaschek, M., Forkert, S., Forster, A., Gommel, H., Guenther, S., … & Ziehn, J. A Joint Approach Towards Data-Driven Virtual Testing for Automated Driving: The AVEAS Project. arXiv preprint arXiv:2405.06286.
2024 Sielemann, A., Loercher, L., Schumacher, M. L., Wolf, S., Roschani, M., Ziehn, J., & Beyerer, J. Synset Signset Germany: a Synthetic Dataset for German Traffic Sign Recognition. In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) (pp. 3383-3390). IEEE.