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Markov Model for Benefits Analysis of Air Traffic Technologies
| Content Provider | Semantic Scholar |
|---|---|
| Author | Mehta, Vineet Campbell, Scot S. Underhill, Ngaire DeLaura, Rich Chandra, Kavitha |
| Copyright Year | 2013 |
| Abstract | A critical step in the design and development of new tools and systems for air traffic management is the estimation of potential benefits of the added technology. The current methodology of estimating the added benefit of a new tool is based on a combination of simulation and field observations, requiring either an extensive model of the system or a fielded prototype. This paper contributes a Markov model for benefits estimation, which allows for quick assessment of benefit uncertainty and rapid evaluation of different operational scenarios. In this paper, a Markov model is employed to estimate the benefits of a strategic departure management tool. The model probabilities are derived from a historical archive of Route Availability Planning Tool (RAPT). Monte Carlo simulations are performed to estimate the range of benefit for uncertainties in model parameters and technology performance accuracy. Using this model we also provide an illustration of how different decision procedures can be accommodated, and their impact on benefits. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://morse.uml.edu/~kchandra/docs/AirTrafficMarkovMehta2013.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |