@article{4540,
  author = {Philipp Weiss, Sebastian Nagel, Andreas Weichslgartner, Sebastian Steinhorst},
  title = {Agent-Based Simulation Platform for Resilient Automotive Systems},
  journal = {Progress in Computing Applications},
  year = {2025},
  volume = {14},
  number = {2},
  doi = {https://doi.org/10.6025/pca/2025/14/2/84-89},
  url = {https://www.dline.info/pca/fulltext/v14n2/pcav14n2_3.pdf},
  abstract = {This paper introduces an adaptable demonstrator platform designed to simulate distributed agent-based
automotive systems, addressing the rising complexity of software-defined vehicles. As automotive electronic
control units (ECUs) consolidate, there is a shift toward modular software design with run-time adaptability,
especially to meet fail-operational and safety requirements in autonomous driving. The proposed platform
leverages a distributed, real-time simulation using the SimPy framework, enabling simulation of task execution
and network communication among ECUs via the SOME/IP middleware.
A key feature of the platform is its agent-based graceful degradation approach, which reallocates resources
from non-critical to safety-critical applications during failures. The demonstrator setup, implemented on
Raspberry Pi devices interconnected via Ethernet, effectively models real-world failover scenarios. The
middleware supports decentralized service discovery and publish/subscribe communication, enabling dynamic
task reallocation and reconfiguration.
Experimental results show strong alignment between simulated and actual network traffic, validating the
platform’s realism. Its hardware-agnostic, scalable architecture allows simulation on various configurations
and network topologies. While real-time constraints may limit scalability on low-power hardware, the platform
provides a valuable tool for evaluating emerging distributed automotive strategies in both academic and
industrial contexts. The study concludes that this flexible simulation environment facilitates rapid development
and testing of robust, fail-operational automotive systems.},
}