Controlling Unmanned Systems in a Simulated Counter-Insurgency Environment

Report No. ARL-TR-4145
Authors: Bruce S. Sterling and Chuck H. Perala
Date/Pages: July 2007; 45 pages
Abstract: The U.S. Army is planning for future operations in a counter-insurgency (COIN) environment. A characteristic of this environment is random encounters with small bands of insurgents who are conducting hit-and-run missions, versus more conventional enemy formations (e.g., brigades, battalions) or more conventional terrain-oriented missions (e.g., attack, defend). In a virtual reality experiment at the Unit of Action Maneuver Battle Lab at Fort Knox, Kentucky, we examined the workload and stress of participants controlling unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and unmanned ground sensors in a COIN environment. Results showed that workload and stress for all the independent variables that we examined were less than half the possible scale level. Workload and mental stress were higher for specific COIN-type missions (e.g., over-watch raid on safe house, locate vehicle-borne improvised explosive devices) than for more conventional missions (e.g., route or site reconnaissance). Workload was higher for participants in combat vehicles than at headquarters and for participants in infantry vehicles in particular. Mental stress was highest for participants in mounted combat vehicles. Workload was higher for participants controlling both UAVs and UGVs. Stress was about equally high for operation of one or both types of sensors. Workload and stress were about equally high for simultaneous versus sequential operation of sensors, but because of the type of control involved, participants could only view images from one camera at a time in both types of operations. Recommended interface improvement included the ability to easily change unmanned vehicle (UV) routes, automatically track a target, rotate the camera while flying, send a UV to a given grid coordinate, see grid coordinates more easily, improve simulated night vision, provide multiple simultaneous video camera feeds, and provide an interface to improve situation awareness (e.g., mission overlays, chat capability).
Distribution: Approved for public release
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Last Update / Reviewed: July 1, 2007