Co-investigators Andrew Liu , Charles Oman
In current operations in Iraq and elsewhere, the supervisory control of unmanned vehicles (UVs) involves multiple operators controlling single vehicles. As the demand for UVs increases with little or no gain in the number of trained operators available to control them, current research efforts are studying how a single operator can effectively control multiple, heterogeneous unmanned vehicles. However, there is a limit as to the number of UVs a single operator can effectively control and at some point, teams of operators, each of whom control teams of UVs, will eventually need to share a common area of interest and work together to obtain their goals. The question becomes, how will working in teams affect the operator's performance. The goal of the research is to develop a model of how teams of operators, each of whom are responsible for controlling multiple, heterogeneous unmanned vehicles, coordinate and collaborate, under time-critical, life-critical scenarios. Previous research at MIT has successfully modeled the supervisory control of multiple, heterogeneous unmanned vehicles by a single human operator based on queuing theory and implemented with a discrete event simulation (DES). This research will expand the existing single operator queuing model to describe multiple human operators collaborating and coordinating in a team environment, as they each control multiple, heterogeneous unmanned vehicles. From this model, performance metrics will be generated that will explain how teamwork affects the supervisory control of multiple, heterogeneous unmanned vehicles and recommendations will be made for team allocation and / or interface design.