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Miles-in-Trail (MIT) restrictions are one of the most commonly used traffic management initiatives. They are most often used to manage arrival flows into airports. Traffic managers often use MIT restrictions to protect a destination airport, particularly when capacity has been reduced due to weather or during periods of high volume. They also use MIT restrictions to smooth out flows to support merging streams. Currently, traffic managers must rely largely on experience to determine if a proposed MIT restriction will have the intended effect on traffic demand, as no tool is available to specifically assess the impact of proposed MIT restrictions. The inability to assess the impact of such a widely used traffic management initiative can sometimes result in inefficient restrictions that increase impacts on flights as well as controller effort. The MITRE Corporation's CAASD has developed a prototype MIT Impact Assessment (MIA) capability which allows traffic managers to evaluate the impact of proposed MIT restrictions on resources and flights before implementing them. This paper proposes an operational concept for arrival MIT restrictions using the MIA capability. This paper also provides an analysis to identify the type of situations when the proposed MIA capability can be used in the future to employ less restrictive MIT restrictions and to determine the impact of MIT restrictions on flying times.

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The goal of data analysis in aviation safety is simple: improve safety. However, the path to this goal is hard to identify. What data mining methods are most applicable to this task? What data are available and how should they be analyzed? How do we focus on the most interesting results? Our answers to these questions are based on a recent research project we completed. The encouraging news is that we found a number of aviation safety offices doing commendable work to collect and analyze safety-related data. But we also found a number of areas where data mining techniques could provide new tools that either perform analyses that were not considered before, or that can now be done more easily.