Future Air Traffic Timetable Estimator Term Paper

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Future Air Traffic Timetable Estimator

As Wall Street and the media make us very well aware, profits within the airline industry have been steadily declining due to the fact that passenger travel miles have been regularly plummeting. One major problem was the infamous hijackings and attacks on September 11, 2001. These terroristic events single-handedly ruined a major level of trust on commercial aviation carriers and since these carriers have been on the brink of either shutting their doors forever or experiencing their worst financial difficulties in their corporate histories. Although some smaller and more technologically advanced airlines have been showing that success can be had in the airline industry, it is vital for companies, the industry and the federal overseers to conduct detailed research and analysis of scenarios and phenomenon such as new predicating the airport and airspace traffic patterns and settings. In regard to these industry needs, this report is an attempt to review a recent article in the March -- April 2005 Journal Of Aircraft entitled Future Air Traffic Timetable Estimator by Dipasis Bhadra, Michael Wells, Jennifer Gentry and Brendan Hogan. The objective of this work is to assess and list the important facts used in the article by the authors to support the overall main idea of their piece.

The goal therefore is not to justify those facts but to explain if and when the author utilized good research methodologies, research processes or if they thoroughly explained what it was they were writing about. The main idea of the article, in my opinion, was for the authors to justify and explain a set of new methodologies for creating simulation tables for airport and airspace traffic patterns and settings. As noted, these types of testing situations are vital to the future success of the industry so it is crucial that any new methodology be conducted in a scientifically acceptable manner and that any process meets the needs of all end users. With that being said, the authors' work seemed very scientific up front because they used many industry related terminologies and concepts that an average person may not know. But, that does not necessarily mean that the information was clear, accurate or scientifically obtained and measurable. This report will look at the content of the article from this perspective; how, in my opinion, did the authors do in regard to these criteria?

In my opinion, this article did not represent sound or 'good' research methods because there were just too many instances throughout the piece where the authors were unclear about the input data they were using or how they justified their inputs. For example: "There are various ways to assign passengers to routes. Currently, using itinerary data from the10% ticket sample we assign passengers based on the most recent historical distribution. Thus, the routes available for passengers to choose from are those that are observed in the actual data. Finally, when forecasts on route segments are rolled up for a particular airport, they can provide us with activity measures that are comparable to the TAF." (Bhadra, Wells, Gentry, & Hogan, 2005)

There is no way of knowing if the authors are correct in assuming if there are various ways of assigning routes or if this is some impossible task. The key is that to start of this way leaves many additional questions on the rest of the quote. Consider that assigning the routes available for passengers may or may not be correct or may actually be considered to be more of an assumption made be the authors instead of some actual scientific option.

Although the scientific assumptions made seem, well, unscientific, the overall purpose of the article seems pretty clearly defined. In a similar sense, if we do not try to actually read too much into the how factual the data is, there is clear evidence as well that the authors have a reasonable base of knowledge on the topic and they seem to have done an amount of research because their process seems relatively detailed.

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"Using quarterly data starting from 1995, O& D. demand is estimated, on average for 38,000 -- 42,000 markets, based on local metropolitan variables as opposed to national economic and demographic conditions, and hence is called bottom-up demand. Notice that this methodology focuses on estimating O& D. passenger flows, as opposed to airport-centric activity, as found in the terminal area forecast." (Bhadra, Wells, Gentry, & Hogan, 2005)

From this presentation however, it is not clear if the authors did a thorough job during the research design planning phase. They present a plethora of insights that may not have been the best data sources for example. "Historical data for commercial traffic are obtained from the OAG. To get arrival and departure distributions, we use OAG data from five different historical years: 1995, 1997, 1999, 2001, and 2002, and the current year of 2003. These data are then transformed into arrival and departure distributions of operations over a given day. Several different "days" were obtained; one week day and one weekend, from each of the four quarters, for a total of eight representative days. These different days were designed to capture specific seasonal patterns spanning across weekdays and weekends." (Bhadra, Wells, Gentry, & Hogan, 2005)

I would think that because so many assumptions were made throughout the work, it can be assumed that high ethical standards were not applied. If a scientist is working on an incorrect assumption and he goes to the scientific world stating his discovery is correct, I believe it would be unethical. "People fly because they want to go to places for business and leisure. These decisions are primarily driven by local economic and demographic characteristics. In addition, characteristics such as fare, market share of major carriers, presence of low-cost carriers, seasonality, and the structure of airport hubs all play important roles in eventually determining the O& D. demand. Differentiating the NAS by distances, we estimate a set of econometric relationships that define these relationships on O& D. data." (Bhadra, Wells, Gentry, & Hogan, 2005) There is no way an ethical approach could overlook the statement that People fly for only two reasons. Just off the top of my head I can think of several other reasons to fly such as a death in a family. These are the types of limitations that are easily uncovered in this article.

With these flaws in the methodology, we can assume that there was not enough or adequate analysis for a decision maker's needs presented by the authors. Although, once again, this report looks very scientific and has many references to highly scientific concepts, there were many references that the authors just assumed a decision maker would understand to be true. For example, the following statement might have many variables to make it true or false and the authors presented as fact. "Once an arrival or departure time is established at an airport for a given flight, there is very little slack left in the schedule on the other end because the equation -- departure time, plus block time, equals arrival time -- is fairly tight. This causes a problem when a departure is created at an airport that then dictates an arrival at the destination airport during an unlikely time or vice versa." (Bhadra, Wells, Gentry, & Hogan, 2005)

In one sense then, the authors may seem unambiguous but in another sense they sound or seem too vague. "Current baseline OAG operations are used as the timetable starting point for scheduled times between city pairs. These data are processed and altered to accommodate changes in forecasted equipment and international traffic. The historical airport operational distributions are used to determine time assignment for additional flights. For example, if eight flights currently operate between LaGuardia and O'Hare each day, and 10 frequencies are predicted,….....

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