Assessing the Effects of Drone Control Interfaces on Situational Awareness and Digital Twin Environment Updates

Drone swarms are an attractive emerging technology for a wide range of application domains. In particular, mounting cameras on drones allows operators to capture live aerial video feeds to gain situational awareness in regions of interest. Effective visualizations of these video feeds and efficient drone control interfaces are crucial for use cases from emergency zone monitoring over facility surveillance to search and rescue. Recent advances in this field have seen the introduction of 3D digital twin models and real-time visualizations, which impose new possibilities but also challenges for manual and autonomous control interfaces, especially when multiple drones are employed.In this paper, we present a user study (N=23) in which we evaluated and compared different approaches for their usability, artifacts, preference, and resulting situational awareness in a region of interest. Therefore, we used a virtual drone simulation framework in which we modeled five drone control methods: two manually controlled by the user and three autonomously controlled. Our results show a general preference of manual drone control interfaces for tracking single moving targets and autonomous control interfaces for keeping track of regions of interest. Further, regional and coordinated autonomous control interfaces significantly improved situational awareness in regions of interest. We discuss the different trade-offs, implications, and guidelines for choosing effective drone control interfaces in this field.