A Cognitive Systems Engineering Approach to Developing HMI Requirements for New Technologies

Abstract

This document examines the challenges inherent in designing and regulating to support human-automation interaction for new technologies that will deployed into complex systems. A key question for new technologies, is how work will be accomplished by the human and machine agents. This question has traditionally been framed as how functions should be allocated between humans and machines. Such framing misses the coordination and synchronization that is needed for the different human and machine roles in the system to accomplish their goals. Coordination and synchronization demands are driven by the underlying human-automation architecture of the new technology, which are typically not specified explicitly by the designers. The human machine interface (HMI) which is intended to facilitate human-machine interaction and cooperation, however, typically is defined explicitly and therefore serves as a proxy for human-automation cooperation requirements with respect to technical standards for technologies. Unfortunately, mismatches between the HMI and the coordination and synchronization demands of the underlying human-automation architecture, can lead to system breakdowns. A methodology is needed that both designers and regulators can utilize to evaluate the expected performance of a new technology given potential human-automation architectures. Three experiments were conducted to inform the minimum HMI requirements a detect and avoid system for unmanned aircraft systems (UAS). The results of the experiments provided empirical input to specific minimum operational performance standards that UAS manufacturers will have to meet in order to operate UAS in the National Airspace System (NAS). These studies represent a success story for how to objectively and systematically evaluate prototype technologies as part of the process for developing regulatory requirements. They also provide an opportunity to reflect on the lessons learned from a recent research effort in order to improve the methodology for defining technology requirements for regulators in the future. The biggest shortcoming of the presented research program was the absence of the explicit definition, generation and analysis of potential human-automation architectures. Failure to execute this step in the research process resulted in less efficient evaluation of the candidate prototypes technologies in addition to the complete absence of different approaches to human-automation cooperation. For example, all of the prototype technologies that were evaluated in the research program assumed a human-automation architecture that relied on serial processing from the automation to the human. While this type of human-automation architecture is typical across many different technologies and in many different domains, it ignores different architectures where humans and automation work in parallel. Defining potential human-automation architectures a priori also allows regulators to develop scenarios that will stress the performance boundaries of the technology during the evaluation phase. The importance of adding this step of generating and evaluating candidate human-automation architectures prior to formal empirical evaluation is discussed.