Safe-AR: Reducing Risk While Augmenting Reality

Augmented reality (AR) systems excel at offering users real-time, situation-aware information to support users' decision making. With AR, rich visualizations of relevant data can be displayed to users without blocking their view of the real world. For example, an AR-enabled automotive windshield can display a red outline around a pedestrian to alert a driver starting a turn into that cross street. Other critical uses of AR applications that are or will soon be deployed include surgery, emergency response, vehicle maintenance, and pilot training. Many of these applications can enhance operational safety. However, developing risk analysis methods to handle failure modes in the melded virtual and physical realities remains an open problem. This paper proposes a risk analysis method with which to study computer-generated AR visualizations of system and environment states. The analysis framework incorporates three levels at which AR interfaces with the user: perception, comprehension, and decision-making. This method enables broader risk analysis of the entire cyber-physical-human system that an AR application may indirectly control. Preliminary results show that this method yields improved coverage of user-involved failure modes over current approaches. While the focus here is on safety, the method also appears applicable to AR security risks.