@article{4539,
  author = {Philipp Mundhenk, Enrique Parodi, Roland Schabenberger},
  title = {A Modular and Secure Software Fusion Platform for Autonom -ous Driving Systems},
  journal = {Progress in Computing Applications},
  year = {2025},
  volume = {14},
  number = {2},
  doi = {https://doi.org/10.6025/pca/2025/14/2/77-83},
  url = {https://www.dline.info/pca/fulltext/v14n2/pcav14n2_2.pdf},
  abstract = {This paper introduces Fusion, a next-generation software platform designed to meet the complex safety,
performance, and architectural demands of autonomous driving systems. Fusion uses a microkernel approach
and blends service-oriented with component-based designs to ensure modularity, scalability, and robustness.
It features an Object Specification Language (OSL) to define object behaviors and interactions, which are
instantiated and configured through manifests, enabling clear and flexible system modeling. The architecture
supports concurrency via execution contexts and offers transparent communication across distributed systems
using a pluggable transport mechanism. Key challenges addressed include managing system complexity,
achieving high performance with low latency, ensuring safety and fault tolerance in Level 4 autonomy, and
securing sensitive data and communication. Design-time verification, enabled by Fusion’s modeling capabilities,
aids in early error detection and system optimization. Fusion also incorporates built-in services for health
monitoring, logging, and scheduling, supporting a wide range of deployment environments from vehicles to
simulation and cloud platforms. Currently used by Autonomous Intelligent Driving GmbH (AID), Fusion lays
a foundational framework for developing safe, efficient, and adaptable autonomous driving applications.
Future work aims to enhance the platform’s predictability, real-time capabilities, and resilience to support
continued evolution in autonomous vehicle technology.},
}