Identifying Information Requirements for Air Traffic Control Problem Solving

Abstract

One of the most important questions facing developers of “human-centered” automation in air traffic control (ATC) is what and how much information does an ATC controller need to take an appropriate action or to make an appropriate decision, especially those with potentially catastrophic failure modes. To obtain such information one must develop a methodology that can be used to evaluate different information attributes and thereby collect data regarding what attributes the most experienced ATC controllers consider most/least important for decision making. A combination of methodologies for evaluating a set of information attributes required to identify and resolve aircraft conflicts and most importantly, specifying the interrelationships between these attributes for ATC problem solving is described. Eighteen attributes were chosen which covered those elements of information deemed most important in conflict identification and resolution and which reflected the thinking of a cross section of experienced ATC controllers. Multidimensional scaling (MDS) and rank-ordering techniques were used to determine the relative importance and interrelationships between attributes. The MDS and ordering results were then integrated into a unified conceptual framework. This framework reflected the importance of each attribute and thus, specified the way ATC controllers think about identifying and resolving conflicts. These results represent a step toward developing an empirical knowledge base for understanding the cognitive processes brought into action by controllers and also becomes a reference point for designing effective displays and decision support systems for ATC automation and to predict their value.