자율주행 대형버스의 이더넷-CAN/CAN FD 프로토콜 변환 절차 개발

초록

With the advancement of autonomous driving technology, the adoption of Level 4 or higher autonomous driving systems in heavy commercial vehicles has been actively investigated. In particular, large buses require the integration of multiple high-precision sensors due to their long body length and extensive blind spots. As a result, a heterogeneous in-vehicle communication network combining automotive Ethernet for high-bandwidth data transmission with CAN and CAN FD for highly reliable control communication is essential. However, the structural differences among these communication protocols, particularly in terms of payload capacity and transmission mechanisms, can lead to computational delays and memory overload during data fusion, thereby posing a serious challenge to the real-time control requirement of autonomous vehicles within 10 ms. To address these issues, this paper proposes and experimentally validates a protocol conversion procedure optimized for heterogeneous communication among Ethernet, CAN, and CAN FD in a large bus environment. A three-stage conversion rule consisting of identification, conversion, and transmission is defined to minimize communication latency. In addition, a memory-clearing technique is applied to optimize the software and prevent data distortion that may occur when multiple protocol conversions are executed within a single electronic control unit. Hardware-based performance evaluation demonstrates that the proposed protocol conversion process requires between 38.2 μs and 66.4 μs across all protocol combinations, which satisfies the real-time requirements of autonomous driving control. The results indicate that the proposed method can effectively alleviate bottlenecks in heterogeneous in-vehicle networks and ensure the integrity of control data in autonomous driving platforms that generate large volumes of data. This study therefore provides practical design guidelines for implementing reliable and efficient communication architectures in large autonomous buses.

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