AVTP-Based CAN-TSN Scheduling Through Constructive Heuristic and Hybrid Iterative Greedy Algorithm for High-Load Automotive Network

In modern automotive zonal electrical/electronic architectures, Time-Sensitive Networking (TSN) serves as the communication backbone, while Controller Area Network (CAN) operates as regional communication branches. The cross-domain communication requirements among CAN nodes distributed across different zones make CAN-TSN scheduling critically important. However, existing scheduling methods struggle to simultaneously meet CAN messages' real-time constraints and achieve efficient TSN bandwidth utilization, especially under high-load conditions with multiple CAN domains. To address these challenges, this paper introduces a comprehensive system model for CAN-TSN scheduling and, for the first time, establishes an aggregation theorem, providing a rigorous theoretical foundation for efficient CAN frame aggregation based on the AVTP protocol. Leveraging this theoretical result, a Constructive Heuristic Algorithm for AVTP-based CAN-TSN scheduling (CHAC) is proposed to produce initial high-quality scheduling solutions. Further optimization is conducted using a Hybrid Iterative Greedy Algorithm (HIGA), which integrates tabu list strategies and the Metropolis acceptance criterion to explore and refine solutions effectively. Simulation studies and prototype experiments conducted under heavy traffic scenarios demonstrate the effectiveness of the proposed methods. Compared to state-of-the-art approaches, the TSN link load is reduced by 41.7%, gateway CPU utilization decreases by 60.3%, and the CAN frame reception rate increases to 93.6%. These outcomes highlight the significant contribution of this research in advancing CAN-TSN scheduling performance, particularly under high-load scenarios, by achieving superior bandwidth utilization and robust real-time communication performance.