基于队列调度算法的民机驾驶舱人机功能分配模型OA北大核心

The high complexity of the aircraft cockpit human-machine system(ACHMS)has resulted in increasing-ly heavy information flow loads for pilots.To address this challenge,a human-machine function allocation model is proposed based on queue scheduling algorithms.The operational complexity of flight procedures and pilot resource requirements during human-machine interactions are quantitatively evaluated using entropy analysis.A spatiotempo-ral dynamic factor-integrated metric is proposed to measure pilot information flow load intensity,serving dual pur-poses as directed edge weights in information interaction networks and scheduling criteria.These networks are sub-sequently constructed to visually represent information transmission processes and coupling relationships between pilots and cockpit interfaces.Building on the mapping relationship between ACHMS and computer operating sys-tems,the serial scheduling mechanism of the weighted round robin(WRR)algorithm is extended.A queue-weight-based cognitive resource differential allocation and information flow queuing scheduling mechanism is established,while a human-machine function allocation strategy for cockpits is proposed based on the improved WRR algorithm.The Boeing 737 takeoff procedure serves as a validation case,with information flows systematical-ly extracted throughout operational phases.A human-machine coupled information interaction network is construct-ed for takeoff procedures,with the enhanced WRR algorithm deployed for dynamic scheduling and function alloca-tion triggering.Post-allocation analysis reveals significant improvements:pilot node closeness centrality improves by 4.82 times,betweenness centrality rises by 0.47%,and network robustness enhances 4.24 times.Maximum reduc-tions of 86.8%in pilot load intensity and 93.5%in information coupling degree are achieved.The case verified the effectiveness of the proposed human-machine function allocation model in reducing the pilot information flow load at critical moments,thereby improve flight safety.