A human-in-the-loop evaluation of the Operational Airspace Sectorization Integrated System (OASIS) was conducted in the Airspace Operations Laboratory at NASA Ames Research Center. OASIS is an advisory tool built on an Android touch tablet, designed to assist Federal Aviation Administration (FAA) En Route Area Supervisors in their planning of sector combine/split operations as well as opening/closing of radar associate control positions over the subsequent two hours. During the experiment, eight retired FAA personnel served as participants for a part-task evaluation of the OASIS user interface and the underlying mathematical algorithm that provided the advisories. There were three experimental conditions: Baseline, Computer Recommend Plan (CRP), and User Generated Plan (UGP). In the Baseline condition, participants were presented with four different traffic scenarios and were asked to generate their own sector configuration plan solutions without OASIS. In the CRP condition, they evaluated the multiple advisory solutions that were generated by OASIS. In the UGP condition, they modified the OASIS advisory solutions to make their own solutions with the support of the OASIS tool. The participants considered the OASIS advisory solutions at least as good as their own, suggesting that the underlying algorithm provided good solutions for the Area Supervisors. In the UGP condition, the participants could not improve on the OASIS advisories by further tweaking the solutions. Participants gave positive feedback on both the user interface and the algorithm solutions, including an excellent average rating above 90% on the tool usability scales. They also suggested various enhancements to be incorporated into the next tool development cycle. The development of OASIS is a major activity of the Dynamic Airspace Configuration (DAC) research focus area within the Airspace Systems Program.
ResultsAlthough Figures 1 and 2 show apparent differences between the generic airspace factors for each question, it was not feasible to evaluate this by conducting statistical testing between all factors for all three geographical areas. A Spearman rank-order correlation test was conducted to compare the ranking of the factors between the two CCs. The results were not statistically significant, indicating that the rank orders of the factors between the CCs are not similar.Pearson product-moment correlations were computed between the three sets of factor ratings for the two CCs. This was to determine if the pattern of ratings between each pair of areas (West versus Central, Central versus East, and West versus East) were related. Statistically significant correlations were obtained for each CC, as shown in Table 2. The correlation results show that the patterns of ratings between the areas for each CC are not identical, but similar overall. Controllers rated the importance of the factors generally the same within each CC. However, correlations of the ratings between the CCs (e.g., West: memorization vs. specialized skills) were not statistically significant, indicating that the patterns of ratings between the CCs for each area are not similar.
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