Experimental Study of Information Load on Operators of Semi-Autonomous Systems

Abstract

A set of experimental results studying the relationship between Human in the Loop performance and user workload in the RoboFlag test environment is presented, with accompanying analysis and conclusions. RoboFlag is an experimental hardware/software test-bed with two teams of 2-6 semiautonomous vehicles each with Human in the Loop oversight (one or more human operators per team) designed to play games structured around the rules of “Capture the Flag”. RoboFlag utilizes small robots based on Cornell University’s award winning RoboCup hardware. The objective of RoboFlag is to locate and capture a “flag ” by venturing into enemy territory and return the flag to home base without having robots “tagged”. Human operators have varying degrees of control over the robots ranging from direct “joystick” control to complete reliance on automation. Operators played a series of games to evaluate performance as a function of information load (speed and number of vehicles). Results showed a positive relationship between game speed and total score. In addition operators reported using more automation as number of robots increased but trusting automation less as game speed increased.