Destination Choice Modeling of Trip Distribution for the Raleigh-Durham International Airport

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Title: Destination Choice Modeling of Trip Distribution for the Raleigh-Durham International Airport
Author: Runey, Elizabeth Michelle
Advisors: Dr. John R. Stone, Committee Chair
Dr. Nagui M. Rouphail, Committee Member
Dr. Billy M. Williams, Committee Member
Abstract: This research develops a sub-model of the Raleigh-Durham International Airport (RDU) for the Triangle Region Travel Demand Model (TRM). The focus of the sub-model is on trip distribution using multinomial logit (MNL) models to explain the relationship between the airport trip makers (air passenger and employees) and destinations of the study area. The MNL models reflect the unique travel patterns of airport trips more than the gravity model by incorporating destination characteristics (number of households, employment type, and travel time) as well as trip maker characteristics (household income and household size). These characteristics are important to airport trip maker's choice of destination besides travel time and travel distance, especially when there are no major competing airports in the area. RDU airport surveys, RDU airport activity data, and TRM zonal data were used to develop MNL models for the HB, NHB, and J-to-W trip purposes. The airport surveys were the main data sources used in this research and the most challenging to format for trip distribution. Since the surveys were conduced for rail analysis and not for trip distribution, they did not capture enough complete observations trip distribution at the zonal level. Thus, the TAZ destinations were grouped by socio-economic (SE) group segment, and the MNL models were estimated using the Biogeme software. The resulting MNL model probabilities of airport trip makers choosing the SE group segment destinations were applied to the 2002XP TRM zones using relative attraction factors, and the trip interchanges between the RDU airport zone and all other zones in the study area were estimated. Finally, the RDU airport sub-model trip interchanges were input into the 2002XP TRM and traffic assignment of the RDU airport sub-model was estimated using the TransCAD software. The RDU airport trip interchanges of the sub-model compared to the TRM trip estimates show that the RDU sub-model estimates approximately 2,000 more trips per weekday than the 2002XP TRM. This is reasonable since the sub-model considers both air passenger and airport employee trips, where as the 2002XP TRM considers only employee trips. Additionally, the distribution of trips show that the RDU airport sub-model estimates more trips at destinations farther away from the RDU airport and more dispersed throughout the study area than the 2002XP TRM. This is logical since the RDU airport trip makers? travel farther to get to the airport than other types of trips such as grocery store trips and since most zones do not have a large number of weekday airport trips. The traffic assignment results of the two methods shows that the RDU airport sub-model traffic volumes are lower compared to the 2002XP TRM estimates and to the year 2002 AADT counts both in the vicinity of the RDU airport and the entire TRM study area. However, calibration of traffic assignment is not in the scope of this study, and additional data sources of the time of day and directional split factors for the RDU airport trips can improve traffic assignment. The benefits of this research provide a framework and methodology to develop and apply a sub-model for unique land uses such as an airport. The destination choice MNL model framework facilitates the modeling of airport trips in travel demand models, and it allows planners to focus limited resources of observed data in order to more precisely distribute airport trips. The RDU airport sub-model provides accurate estimates of RDU airport trips and it has potential to provide enhanced traffic assignment and air quality conditions in the Triangle Region. The foregoing results of this research have implications for transportation planning, airport modeling, air quality analysis and land use planning.
Date: 2007-07-24
Degree: MS
Discipline: Civil Engineering

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