The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler's purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler's purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized

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Electric propulsion and autonomy are technology frontiers that offer tremendous potential to achieve low operating costs for small-aircraft. Such technologies enable simple and safe to operate vehicles that could dramatically improve regional transportation accessibility and speed through point-to-point operations. This analysis develops an understanding of the potential traffic volume and National Airspace System (NAS) capacity for small on-demand aircraft operations. The results of this analysis projects very large trip numbers for an on-demand air transportation system competitive with automobiles in cost per passenger mile. The significance is this type of air transportation can enhance mobility for communities that currently lack access to commercial air transportation. Another significant finding is that the large numbers of operations can have an impact on the current NAS infrastructure used by commercial airlines and cargo operators, even if on-demand traffic does not use the 28 airports in the Continental U.S. designated as large hubs by the FAA. Some smaller airports will experience greater demand than their current capacity allows and will require upgrading. In addition, in future years as demand grows and vehicle performance improves other non-conventional facilities such as short runways incorporated into shopping mall or transportation hub parking areas could provide additional capacity and convenience.

This study aims to estimate passenger demand of Urban Air Mobility (UAM) for airport ground access trips while considering airspace restrictions in the Dallas-Fort Worth region. UAM is a concept mode of transportation designed to bypass ground congestion for timesensitive, price-inelastic travelers using autonomous, electric aircraft with Vertical Takeoff and Landing (VTOL) capabilities. Airport ground access trips constitute a trip purpose that can utilize this mode. This study analyzes originating ground access trips for two major airports in the Dallas-Fort Worth region: Dallas-Fort Worth International Airport (DFW) and Dallas Love Field Airport (DAL). First, a mode choice model is calibrated on the existing airport ground access behavior. UAM demand is then estimated using the developed model, airspace restrictions, and the results from UAM demand stated-preference surveys in literature. Airspace restrictions consist of unusable pieces of airspaces based on current air traffic patterns, where the placement of UAM vertiports and overflying of UAM vehicles are prohibited. The demand model considers the trajectories of the UAM vehicles, which navigate on pre-defined routes inside Class-B airspace to prevent Air Traffic Control (ATC) involvement requirements. This study includes sensitivity analyses of UAM demand to the cost per passenger mile (CPM), number of vertiports placed in the region, and other secondary factors like vertiport location, intermodal cost, fixed cost, and average speed. Corridors with significant UAM demand are identified from the spatial distribution of demand and potential bottlenecks in the UAM network. The findings predict up to 4% market share of UAM for trips to the airport at the optimistically lower fare of $2 per passenger mile (in addition to the fixed cost of $23) and a 50-vertiport UAM network. Average Value of Times (VOTs) for business and non-business travelers are estimated to be around $57/hr and $36/hr, respectively. Business travelers comprise three-quarters of the total UAM demand because of relatively higher VOTs. Airport access trips in Dallas-Fort Worth region have considerable potential for UAM if the trip's price is below $4 per passenger mile (in addition to the fixed cost of $23).