首页> 外文OA文献 >NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts
【2h】

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

机译:NAS需求预测,运输系统分析模型(TSAM)与其他预测的比较

摘要

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 and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.
机译:当前的工作结合了运输系统分析模型(TSAM)来预测航空旅行的未来需求。 TSAM是一种多模式的国家模型,可根据人口和人口统计学预测县级所有长途旅行的需求。该模型进行模式选择分析,以根据旅行者的旅行目的,时间价值,花费和时间,计算出对商业航空公司旅行的需求。然后将县对航空旅行的需求汇总(或分配)到机场级别,并对商业机场的飞机起降需求进行建模。随着航班需求的增长,并利用当前的航空公司航班时刻表,Frtar算法用于在NAS中制定未来的航班时刻表。然后可以通过空中运输模拟器飞行预计的飞行,以量化NAS满足未来需求的能力。 TSAM分析的主要优势在于,可以根据不同的未来方案进行方案规划,以量化各个机场的运力需求。可以分析不同的人口场景以对它们的需求敏感性进行建模。同样,众所周知,但没有在机场级别上很好地建模,对旅行的需求高度依赖于旅行成本或航空业的票价收益。美国联邦航空局(FAA)预计票价收益率(以年不变美元计)将在未来持续下降。鉴于普遍缺乏航空公司利润和航空公司燃油成本的大幅上涨,这些预测的幅度和/或方向可能令人怀疑。同样,旅行时间和便利性的变化也会影响航空旅行的需求,尤其是商务旅行。未来的计划者无法轻松利用FAA TAF数据,波音或空中客车的预测结果对未来需求进行敏感性研究。在TSAM中,可以对许多因素进行参数化,并且可以预测未来旅行的各种需求敏感性。这些产生的需求情景可以合并到将来的航班时刻表中,从而为一系列期货提供了NAS中航班的可量化需求。此外,还研究了新的未来航空公司业务场景,这些场景说明了只有在需求合理的情况下,直飞航班才能代替转机航班而大飞机可以替代。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号