基于脑力负荷预测技术的多乘员舱任务分配方案优选方法

针对信息化条件下装甲车辆舱室乘员人数逐渐减少的基本趋势，对乘员的操作特性进行了分析，并运用多资源理论（MRT）构建了乘员脑力负荷预测模型，提出了基于脑力负荷预测技术的乘员舱任务分配优选方法，并以装甲车辆三乘员减少为两乘员作为实例对方法进行了仿真验证，旨在为解决应急任务条件下的装甲车辆舱室任务分配问题探索新的途径.结果表明，该方法能够清楚地描述乘员全任务过程中脑力负荷的变化情况，对任务分配方案进行量化动态优选，具有较好的优选精度和可重用性. 

Optimal Selection of Task Allocation Schemes for the Multi-Crew Cabin Based on Mental Workload Prediction Technology

In view of the basic trend that the number of armored vehicle cabin crew gradually has reduced under the informationized condition, the operational characteristic for armored vehicle cabin crew was analyzed and the mental workload prediction model was built based on multiple resource theory (MRT). A task allocation method under the mental workload prediction theory was proposed and the effectiveness of this method was illustrated by a case simulation analysis to solve the problem of armored vehicle crew cabin task allocation under the emergency condition for the warship formation. The results indicate that this method can describe the change of crew''s mental workload clearly during the whole task. With this method, the selection of task allocation schemes can be quantized. It is an effective and feasible approach for scheme selection.