The characteristics of an aircraft as a noise source changes as the pilots slow the aircraft down and extend flaps and landing gear in preparation for landing. In the OPNOP project, the possibility to use this variation in noise generation to minimize noise at a specified location is examined. Such analysis requires an increased understanding about aircraft noise generation as the aircraft changes configuration and speed during the approach, where theoretical models available can be overly simplistic and of little use for this purpose. Using flight data from 113 Airbus A321 flights, and corresponding noise measurements on the ground, this study reports on the findings forming the foundation on which further analysis will be conducted. Findings relate to: a comparison between models and actual measurements, the distance variability to the runway for various flap selections and extension of the landing gear as well as a comparison between flight data and on-ground noise measurements. Captured data suggest that it should be possible to use speed and configuration recommendations to reduce noise over selected approach areas. Future research will include scenario generation and incorporate flight data from an earlier study to increase validity.

This chapter explores several ways in which automation and preparation for future supervisory control work in cockpits could be meaningfully integrated in the stages where the groundwork for pilot competence is laid. It discusses ab initio training, the phase in which new recruits is brought up to commercial pilot status in about 200 hours of flying. The limited flying time received during ab initio training is mostly gained on aircraft whose level of automation has little resemblance to that of the pilot’s ultimate working environment. Even without advanced automation in training aircraft the future performance of the student could benefit from learning that manual flying is only one among other modes of flying while practising the basic flying skills. Although automation has fundamentally changed the roles of people on the flight deck, it has not reduced the need to invest in human expertise. Treating automation as a separate subject may misrepresent its place in the curriculum of modem flight training. 

Current methodologies in engineering relying on strict boundary definitions in order to be comprehensible are generally cost efficient and effective within those boundaries. However, in operational settings systems tend to operate outside those defined borders. The trend of coupling systems in greater constellations will increase the interactions between different systems and thus increase the non-defined behavior even further. Thus, there is a need to define new methods and models that to a larger extent allow the existence of non-nominal system behavior. The main goal of the present research is to improve system performance, by developing tool/model to assess important aspects of complexity which will improve design for operability (McDonald et al., 2009). The purpose of this paper is to identify relevant aspects for analysis in relation to complexity and Human Factors in an ATM future highly automated system. The present paper presents some existing models and principles in complexity theory related to socio-technical systems. The result expands on these to form a set of requirements for future model development.