Click for next page ( 14

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 13
13 suppose a group of four travelers has chosen to travel on a six- more useful information on trip origins and destinations than passenger light jet; statistical estimates of the likelihood of its successor survey that was conducted in 2001.11 choosing a three-passenger VLJ if it were available may then depend critically on whether the group of four is travelling Data Details together and whether the light jet or VLJ services are sold on a Airport Data per-seat basis or a traditional charter basis. This is discussed in more detail below. The universe of potential airports for handling VLJ activ- An important requirement in estimating a mode choice ity was restricted to public-use facilities in the lower 48 states model is that the attributes of all modes that are available (and with at least one 3,000-ft lighted runway and jet fuel availabil- not just the one that was actually chosen) must be measured. ity. For air taxi use, FAA medium- and large-hub commer- The essential output from the mode choice model gives statis- cial service airports were excluded from the database based tical coefficients for the mode attributes and individual char- on observed usage patterns from various air taxi operators acteristics that can then be used to estimate the probability that showing that such airports are avoided (presumably to avoid the individual will choose each available mode. These prob- airside and/or landside congestion at these facilities). These abilities then can be translated into "shares." For example, restrictions resulted in a "VLJ airport" universe totaling 1,842 suppose there are 1,000 observed trips involving commer- facilities. This list in fact includes a combination of commer- cial air as the mode of travel; this means that 1,000 individ- cial service, reliever, and GA airports; it is meant to represent uals actually chose commercial air as their preferred mode. the airports that are most likely to be impacted by growth in The statistical model will generate predictions about the the activity of VLJs and similar aircraft. probability that these trips are taken by each of the available It is likely that owners and operators of next-generation modes. It may indicate, say, an 80% probability that these equipment will want to take advantage of the advanced avion- trips will be taken by commercial air; an 8% probability for ics packages in their aircraft; this suggests that airports with the automobile mode; and a 4% probability for each of the precision approach capabilities will be most attractive to these three currently available air taxi modes (piston, prop, light users. In addition, airports with other amenities such as hangar jet). Multiplying the probabilities (shares) by the number of facilities, ground transportation services, de-icing and snow trips yields projected trip totals for each mode (i.e., 800 com- removal capabilities, mobile auxiliary power units, and so forth mercial air trips, etc.). will be attractive to VLJ air taxi operators. While sufficient data Then, to simulate the impact of the entry of VLJs into the on these latter attributes for the 1,842 identified facilities are market for the forecast years 2012 and 2017, a new "mode" not available, it is possible to assess airport "readiness" for VLJs is added with particular attributes representing VLJs, and the based on observed characteristics and some proxy measures. shares are recalculated based on the estimated coefficients. To Table 7 breaks out the airports regionally based on the avail- account for generic growth in travel over time, the overall num- ability of at least one precision runway, plus the number of ber of trips is grown for the forecast years 2012 and 2017 based based GA jet aircraft. It is reasonable to presume that airports on population growth projections assuming the overall per- that have precision approach runways and higher numbers of capita trip rate remains constant. Finally, estimates of passen- based GA jet aircraft are more likely to be "VLJ-ready" than gers per flight and annual aircraft utilization rates are applied to those that do not. transform these projected VLJ trips into fleet forecasts. As seen in the table, the highest number of airports with For present purposes, it was much more efficient to use ex- precision approaches and higher numbers of based jet aircraft isting survey data rather than to design and undertake a sur- are in the Southern, Southwestern, Eastern, and Great Lakes vey from scratch. For the existing air taxi and commercial air regions. It is not surprising that many industry observers modes, the best available data are those from mode-specific expect these areas to attract the highest number of VLJ oper- datasets: daily Enhanced Traffic Management System (ETMS) ations, and compatible assumptions are made below in the traffic in FY2007 collected by the FAA in the case of air taxi statistical analysis where projections of future operations are and quarterly Origin-Destination Survey (DB1B) for FY2007 estimated. collected by the U.S. DOT in the case of commercial air. For For each VLJ airport, the two closest commercial airports automobile traffic, the potential universe of trips is drawn (those with at least three daily scheduled departures) were from the 1995 American Travel Survey (ATS) conducted by the U.S.DOT. Although this survey covers all modes of per- 11 Clearly there is a need for more recent survey data--not only for this sonal transportation (including commercial air and charter study, but also for work in other areas. In 2008, U.S.DOT launched travel), it does not provide nearly the same level of geographic the most recent National Household Travel Survey; data will continue detail that the ETMS and DB1B datasets provide. However, it to be collected through the Spring of 2009, and the first set of results does provide a much larger sample of long-distance trips and is expected to be available late in 2009.