Measuring Autonomous UAV Surveillance Performance

We describe an approach to evaluating algorithmic and human performance in directing UAV-based surveillance. Its key elements are a decision-theoretic framework for measuring the utility of a surveillance schedule and an evaluation testbed consisting of 243 scenarios covering a well- defined space of possible missions. We apply this approach to two example UAV-based surveillance methods, an algorithms called 2- opt and a human-directed approach, then compare them to identify general strengths and weaknesses of each method.