01337606

Component

https://doi.org/10.3141/2214-14

http://scholar.google.com...vell&publication_year=2011

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.

01351429

11-0138

English

pp 111-116

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309167284

Print

Figures (4) ; References (17) ; Tables (3)

Air traffic; Airport capacity; Airspace (Aeronautics); Aviation; Decision making; Monte Carlo method; Optimization; Planning; Sensitivity analysis; Simulation; Stochastic processes; Traffic flow; Uncertainty; Weather conditions

Aviation; Operations and Traffic Management; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Feb 17 2011 5:20PM

• Addressing and Benchmarking Variations in Airport Demand in the U.S. Domestic Market
• Airborne Laser Survey Specifications and Quality Management Protocols for Airport Obstruction Surveys
• Application of Complex Network Theory and Genetic Algorithm in Airline Route Networks
• Capacity, Delay, and Schedule Reliability at Major Airports in Europe and the United States
• Computation of Aircraft Braking Distances
• Critical Factors for Development of Airport Cities
• Critical Flights Detected with Time Windows
• Economic and Institutional Impacts of Introduction of Self-Separation Concept of Operations in Air Traffic Management
• Effect of Disruptions on Service Quality and Market Share: Evidence from the U.S. Domestic Airline Industry
• Eruption of Eyjafjallajökull in Iceland: Experience of European Air Traffic Management
• Exploring the Impact of Introducing Scheduled Flights on Aviation Markets: Experience from Opening of China–Taiwan Nonstop Flights
• Heterogeneity in Preferences of Air Travel Itinerary in a Low-Frequency Market
• Impacts and Responses of Icelandic Aviation to the 2010 Eyjafjallajökull Volcanic Eruption: Case Study
• Measuring Quality of Service in Airport Passenger Terminals
• Modeling and Forecasting Passenger Demand for a New Domestic Airport with Limited Data
• Simple Sensors Used for Measuring Service Times and Counting Pedestrians: Strengths and Weaknesses
• Using Smeed’s Law to Estimate Number of Bird Strikes in Utah