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How to decrease the gateway queue delay in the Train Communication Network (TCN) with heavy communication load is a key problem. This paper models the queue scheduling as a reinforcement learning process and presents a self-adaptive scheduling algorithm of vehicle gateway node based on self-adaptive weighted learning. The proposed algorithm can schedule the queues dynamically. We then compare the simulation results respectively under two circumstance: with enough band resource or with limited band resource. The proposed algorithm’s superiority is proved by simulation. Keywords-component; gateway queue, self-adaption weight, round -robin scheduling

A Round-robin Scheduling Algorithm of Vehicle Gateway Node Based on Self-adaptive Weighted Learning