Modeling risk perception for mars rover supervisory control: Before and after wheel damage

The perception of risk can dramatically influence the human selection of semi-autonomous system control strategies, particularly in safety-critical systems like unmanned vehicle operation. Thus, the ability to understand the components of risk perception can be extremely valuable in developing either operational strategies or decision support technologies. To this end, this paper analyzes the differences in human supervisory control of Mars Science Laboratory rover operation before and after the discovery of wheel damage. This paper identifies four operational factors sensitive to risk perception changes including rover distance traveled, utilization frequency of the autonomous driving capability (AutoNav), terrain risk weighting, and changes in high-level mission planning. A resulting Rover Risk Perception Model illustrates how these operational factors relate to increased perception of risk. Based on these results, we propose aiding risk perception mitigation strategies such that risk can be appropriately anchored. Such strategies can include a change in system design including adding technology and decision support tools, or changing the training of operators who use the system.