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Determining a Maximum Allowable TCV Rate
Since the only undefined variable in equation (2) [Section 5.4.4, pg. 26] used to compute
the maximum acceptable blunder rate, is the TCV rate, it is possible to determine the
maximum allowable TCV rate which would meet the target level of safety. Knowledge of
this number would permit a quick decision regarding the acceptability of the simulated
operation. The maximum allowable TCV rate may be found from the following analysis.
Given the target level of safety, P(Accident) = 4 x 10-8, then from equation (2) one has
P(TCV|At-risk and WCB and Blunder) x P(At-risk|WCB and Blunder)
x P(WCB|Blunder) x P(Blunder) x 2 = 4 x 10-8 ,
or
(3) P(TCV|At-risk and WCB and Blunder)
= 4 x 10-8 x 1 x 1
1 P(At-risk|WCB and Blunder) P (WCB|Blunder)
x 1 x 1
P(Blunder) 2
Values from equation (2) can be substituted into equation (3) to obtain a maximum
acceptable TCV rate. After completion of the simulation, the acceptability of the
simulated operation can be easily determined.
SEPARATION SAFETY MODELING
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It should be remarked that no matter how small a target level of safety is chosen for a new
operation, procedure, etc., the overall level of risk will increase unless the new operation
has the effect of reducing the risk of one or more current operations.
5.4.6 Summary
A real-time simulation uses human subjects such as pilots and air traffic controllers to
operate equipment, either simulated or real, such as aircraft and radar facilities. A realtime
simulation is typically an extremely complex and costly endeavor, but it provides
insight into possible operational problems and it provides human factors and aircraft
performance data. Acceptance criteria based solely on a real-time simulation may be
difficult to apply because of the small size of the sample provided by the simulation.
The purpose of a fast-time (Monte Carlo) simulation is to provide a more accurate
estimate of the acceptance parameter than the estimate derived from the real-time
simulation. Data derived from the real-time simulation are used to develop probability
distributions of human factors and aircraft performance. These probability distributions
are used in a fast-time simulation to explore the probability of events which would not
likely be covered by the real-time simulation. In addition, the large sample sizes attainable
in a fast-time simulation will result in a more precise estimate of the acceptance parameter.
5.5 HUMAN FACTORS IN ATM SAFETY MODELING: THE VARIABILITY
IN HUMAN ACTIONS
When assessing safety in present or future ATM environments, a key role is played by
human operators (air traffic controllers and pilots). This is because safety critical tasks,
like solving conflicts between aircraft, involve a lot of human activity, from conflict
detection to maneuvering the aircraft to a different flight-level.
Due to the presence of human operators in the ATM environment, the behavior of the
ATM environment cannot be looked upon as a deterministic process. Where machines in
general take one course of action, humans can (and will) select a solution to the current
problem from a range of possibilities, where the specific choice of action also depends on
subjective parameters as workload, subjectively available time, and operator level of
performance. Thus, the presence of human operators causes a variety of possibilities for
the evolution of the traffic flow.
If we relate this to safety, we argue that we cannot speak of a ‘human error’ when an
unsafe situation originates from certain actions of the human operator. Regarding these
operator actions as ‘erroneous’ does not pay proper respect to, for example, situations
where the operator (e.g., an air traffic controller) chooses to let an even more urgent
problem receive attention when the subjectively available time is short or when high
workload (e.g., many conflicts to be resolved) causes one to make quick decisions,
without bothering too much about the quality of those decisions. Note that these effects
APPROACHES TO COLLISION RISK ANALYSIS
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are inextricably bound up with human flexibility and the ability of humans to deal with
unforeseen situations.
When assessing ATM safety, it is necessary to take these aspects of human performance
into account. For this purpose, NLR has developed a high-level model of human
performance that has been implemented into TOPAZ (Traffic Organization and
Perturbation AnalyZer) that can be adjusted to the specific ATM situation under
consideration. The model has been developed in cooperation with NLR’s Human Factors
Department and is based upon the cognitive model of the well-known human factors
　
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