  With the forecast increase in air traffic demand over the next decades, it is
imperative to develop tools to provide traffic flow managers with the
information required to support decision making. In particular,
decision-support tools for traffic flow management should aid in limiting
controller workload and complexity, while supporting increases in air traffic
throughput. While many decision-support tools exist for short-term traffic
planning, few have addressed the strategic needs for medium- and long-term
planning for time horizons greater than 30 minutes. This paper seeks to address
this gap through the introduction of 3D aircraft proximity maps that evaluate
the future probability of presence of at least one or two aircraft at any given
point of the airspace. Three types of proximity maps are presented: presence
maps that indicate the local density of traffic; conflict maps that determine
locations and probabilities of potential conflicts; and outliers maps that
evaluate the probability of conflict due to aircraft not belonging to dominant
traffic patterns. These maps provide traffic flow managers with information
relating to the complexity and difficulty of managing an airspace. The intended
purpose of the maps is to anticipate how aircraft flows will interact, and how
outliers impact the dominant traffic flow for a given time period. This
formulation is able to predict which "critical" regions may be subject to
conflicts between aircraft, thereby requiring careful monitoring. These
probabilities are computed using a generative aircraft flow model. Time-varying
flow characteristics, such as geometrical configuration, speed, and probability
density function of aircraft spatial distribution within the flow, are
determined from archived Enhanced Traffic Management System data, using a
tailored clustering algorithm. Aircraft not belonging to flows are identified
as outliers.
