Training for Unmanned Vehicle Allocation with Automation in a Dynamic Microworld

Abstract

Recently, questions about the nature of automation use during training have emerged. Several studies have shown that at best, training with automation does not aid learning, but this has not yet been examined in supervisory control tasks. Using a dynamic microworld program, Networked Fire Chief, we show that vehicle allocation training significantly interacts with automation during training, impacting not only performance, but also situation awareness and the absolute number of vehicles users can allocate.