자율주행 제어기의 이중화 구조를 고려한 IEEE 1588 동기화 프레임워크 설계Design of IEEE 1588-based Synchronization Framework Considering Redundancy Structure of Autonomous Driving Controller
- Other Titles
- Design of IEEE 1588-based Synchronization Framework Considering Redundancy Structure of Autonomous Driving Controller
- Authors
- 한준영; 김형준
- Issue Date
- Dec-2025
- Publisher
- 한국산업융합학회
- Keywords
- Autonomous Driving; Redundancy; Time Synchronization; IEEE 1588; PTP; Real-time System
- Citation
- 한국산업융합학회논문집, v.28, no.6, pp 2109 - 2116
- Pages
- 8
- Indexed
- KCI
- Journal Title
- 한국산업융합학회논문집
- Volume
- 28
- Number
- 6
- Start Page
- 2109
- End Page
- 2116
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/81795
- ISSN
- 1226-833x
2765-5415
- Abstract
- As autonomous vehicles advance to Level 3 and beyond, designing redundant controllers to ensure system safety has become a mandatory requirement. A redundant autonomous driving control sy stem typically consis ts of a Main-ADCU and a Sub-ADCU that execute identical computations and cross-verify results to eliminate single points of failure. However, if the clocks of the two physically separated controllers are not synchronized, timing mismatches can cause discrepancies in computation results even when processing identical sensor data, and asynchronous execution introduces waiting times for cross-verification, delaying the control loop and degrading real-time performance. To address these issues, this paper proposes a high-precision time-synchronization framework utilizing the IEEE 1588 Precision Time Protocol (PTP). The proposed framework minimizes overhead by directly accessing the PTP Hardware Clock in a Linux-based embedded system and controls application execution timing with sub-microsecond precision. Experiments conducted on the NXP S32G automotive processor platform show that the execution-timing error between two controllers is maintained within 248 ns, demonstrating that the proposed approach enhances real-time fault detection and contributes to building stable redundant control architectures for autonomous systems.
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