Assessing
the Impact of Stochastic Capacity Variation on Coordinated Air Traffic Flow
Management.
Transportation Research
Record 2214,
pp. 111–116.
For decisions about air traffic flow management (ATFM), an accurate characterization
of resource capacities at a lead time useful for planning is paramount.
Unfortunately, this description is difficult to develop because of the complex
nature of the airspace system and the unpredictable nature of the weather
phenomena that often influence capacities. Capacity disruptions may be
characterized simply by onset, duration, and severity; each of these parameters
has a different effect on planning. Having a better understanding of the
sensitivity of the air traffic system to uncertainty in each of these
parameters can enhance decision making and improve model building. To help
characterize the sensitivity of ATFM models to uncertainty in various capacity
parameters, this research applies a modified Monte Carlo framework to a simplified
model of capacity to identify output effects. In addition to the variations
induced in resource capacities, randomness is included on demand profiles to
avoid dependencies on a single demand scenario. The results demonstrate that
ATFM decision making is quite sensitive to variations in each of the parameters
used to characterize capacity. Typically, the impact of capacity variations is
marginally increasing. The results of this type of analysis have several
applications. First, the particular sensitivities of this deterministic model
suggest that benefits may be realized by reformulating the model to explicitly
consider stochasticity in resource capacity. Also, results suggesting greater
sensitivity to specific capacity parameters may help to motivate research on
mitigating uncertainty. Finally, this analysis presents an interesting
application of the interplay between simulation and optimization techniques.