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Other models that could be considered for use in this analysis include the Reorganized
ATC Mathematical Simulator (RAMS), the National Airspace Resource Investment
Model (NARIM), SIMMOD (the FAA’s Airport/Airspace Simulation Model), and the
Total Airspace and Airport Modeller (TAAM). These models are briefly described in the
following paragraphs.
RAMS, a model developed under the auspices of Eurocontrol, is perhaps better suited to
model Free Flight operations including aircraft-to-aircraft interactions. However, RAMS
will need to be examined for adequacy in this modeling process, because it lacks a detailed
representation of the airport resource infrastructure ¾ only runway resources are
represented in the model and those with little detail. For a macroscopic view of NAS en
route operations, this limitation should not prevent the use of RAMS to gain insight about
capacity enhancements derived from reduced separations in a Free Flight structure.
SIMMOD, the FAA airspace and airfield simulation model, might also be capable of
estimating capacity and delay changes in NAS once separation criteria are modified. This
model is better suited for regional analyses and could, in principle, include a detailed
MODELING CRITERIA
4-7
description of airspace and airports. SIMMOD, however, has many of the same
limitations as NASPAC in modeling Free Flight operations given its rigid link-node
structure of depicting flight paths. Further analysis will have to be conducted to test
whether or not this model is suitable for this collision risk study.
TAAM, the Total Airspace and Airport Modeller, is a tool developed by The Preston
Group Ltd., an Australian company based in Melbourne, Victoria. TAAM is described
as a full “gate-to-gate” model capable of modelling a complete flight in 4D. It includes
capabilities for modeling “Free Flight” scenarios and has a sophisticated conflict
detection algorithm, as well as a flexible rule-based expert system for conflict
resolution. This tool has been used in a number of “Free Flight” and collision risk
studies by government and private organizations, and is used in studies to improve
ground/airborne operations and in AT planning. A Beta Version 3, which corrects
some problems in the previous version, is currently being tested.
NARIM, the National Airspace Resource Investment Model, contains an operational
component that also can be used in capacity and related studies. A fuller description of
this model is presented in Chapter 6.
Regardless of the model used to assess benefits and costs of reduced separation in en
route airspace, it is important to recognize that almost all of the capacity and delay models
available today will have to be tailored to address the needs of this working group.
SEPARATION SAFETY MODELING
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APPROACHES TO COLLISION RISK ANALYSIS
5-1
5.0 APPROACHES TO COLLISION RISK ANALYSIS
5.1 INTRODUCTION
Collision risk modeling for air transportation was initially developed in the 1960s to
address the safety of proposed separation standard reductions in the North Atlantic
Organized Track Structure (NAT OTS). The methodology developed focused on the
environment of oceanic operations, out of range of radar surveillance. In this
environment, safety assurance is dependent on planned or procedural separations, periodic
HF (high frequency) voice position reporting, reliable navigation, and large separations.
The collision risk modeling effort culminated in the development and acceptance of the socalled
Reich Model [R5.1, R5.2] which is still in use today. A history of the early
developments and applications of risk modeling can be found in the survey of Machol
[R5.3]. The most recent application of the Reich Model has been to develop technical
requirements for the Required Vertical Separation Minima (RVSM) for application in the
North Atlantic Minimum Performance Standards (MNPS) airspace.
While the Reich Model provides a widely accepted tool for evaluation of collision risk in
its intended environment, a number of shortcomings of the methodology have been
acknowledged. The model uses convolutions of distributions (including “heavy tailed”
double exponential distributions) representing “expected” deviations (due to flight
technical errors, allowable inaccuracies in navigation equipment, etc.) and “unexpected”
deviations (due to pilot blunders, avionics failures, etc.).
Difficulties in the application of the Reich Model include: (1) the assumption of fixed,
usually parallel track operations, (2) the exclusion of communication, surveillance and
ATC “control loop” performance, and (3) difficulty in modeling the “tails” of navigation
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