Chain-Aware Runnable Scheduling in AUTOSAR: A Case Study in Automotive Systems
The increasing complexity of functional operations, combined with the automotive industry's extensive collaboration with multiple vendors, presents significant challenges in man-aging software components within automotive systems. While AUTOSAR (AUTomotive Open System ARchitecture) aims to address these issues by enhancing software modularity and reusability, comprehensive studies on end-to-end latency, real-time capability, and timing analysis for safety-critical applications remain limited. This study proposes a chain-aware runnable scheduling framework to enhance real-time performance and reduce end-to-end latency in AUTOSAR-based automotive systems. Experimental results, incorporating priority assignment and runnable allocation, and a case study on real vehicle control units (VCU) of commercial vehicles, conducted using practical scenarios, indicate that the proposed framework reduces the end-to-end latency of the most safety-critical chain by 82% compared to the existing AUTOSAR schedulers.
Authors
- Hong-Gi Park (ORCID: https://orcid.org/0000-0002-9990-6237)
- Hyunjong Choi (ORCID: https://orcid.org/0000-0001-8253-7028)
Institutions
- San Diego State University (US)
- Hyundai Motors (South Korea) (KR)
Publication Details
- Published
- 2024-10-23
- DOI
- https://doi.org/10.1109/sies62473.2024.10767943
- Primary Topic
- Real-Time Systems Scheduling
- Type
- article
- Field-Weighted Citation Impact
- 0.00