Study of In-Vehicle Ethernet Message Scheduling Based on the Adaptive Frame Segmentation Algorithm.

With the rapid development of intelligent driving technology, in-vehicle bus networks face increasingly stringent requirements for real-time performance and data transmission. Traditional bus network technologies such as LIN, CAN, and FlexRay are showing significant limitations in terms of bandwidth and response speed. In-Vehicle Ethernet, with its advantages of high bandwidth, low latency, and high reliability, has become the core technology for next-generation in-vehicle communication networks. This study focuses on bandwidth waste caused by guard bands and the limitations of Frame Pre-Emption in fully utilizing available bandwidth in In-Vehicle Ethernet. It aims to optimize TSN scheduling mechanisms by enhancing scheduling flexibility and bandwidth utilization, rather than modeling system-level vehicle functions. Based on the Time-Sensitive Networking (TSN) protocol, this paper proposes an innovative Adaptive Frame Segmentation (AFS) algorithm. The AFS algorithm enhances the performance of In-Vehicle Ethernet message transmission through flexible frame segmentation and efficient message scheduling. Experimental results indicate that the AFS algorithm achieves an average local bandwidth utilization of 94.16%, improving by 4.35%, 5.65%, and 30.48% over Frame Pre-Emption, Packet-Size Aware Scheduling (PAS), and Improved Qbv algorithms, respectively. The AFS algorithm demonstrates stability and efficiency in complex network traffic scenarios, reducing bandwidth waste and improving In-Vehicle Ethernet's real-time performance and responsiveness. This study provides critical technical support for efficient communication in intelligent connected vehicles, further advancing the development and application of In-Vehicle Ethernet technology.