城市空中交通通勤任务的全国需求建模

Q2 Social Sciences
Mark T. Kotwicz Herniczek, Brian J. German
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引用次数: 0

摘要

在本文中,我们提出了一个全面的、可重复的城市空中交通(UAM)需求模型,该模型以公共数据和开源工具为中心,能够在国家层面上进行需求估计。利用纵向始发目的地就业统计流量数据、美国社区调查经济数据和开源路由机(OSRM)开发了一个离散模式选择需求模型,以确定UAM通勤服务相对于其他交通方式的效用。使用实施的模型,我们确定纽约市、旧金山和洛杉矶是通勤需求潜力最大的城市,西雅图是对延误时间增加最具弹性的城市。对需求的敏感性研究表明,总延误时间短的短途旅行和每公里票价低的长途旅行存在强烈的需求,前者显示出对运营成本增加的弹性,后者显示出对延误增加的弹性。需求模型由速度流模型支持,该模型融合了公路性能监测系统数据和OpenStreetMap数据,为OSRM提供交通调整的路段速度。该速度流模型能够在不使用商业数据集或路由服务的情况下为美国各地的路段提供拥堵数据,并被证明可以提高拥堵地区的路由持续时间准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nationwide Demand Modeling for an Urban Air Mobility Commuting Mission
In this paper, we present a comprehensive and reproducible urban air mobility (UAM) demand model centered around publicly available data and open source tools capable of demand estimation at the national level. A discrete mode-choice demand model is developed using longitudinal origin–destination employment statistics flow data, American community survey economic data, and the Open Source Routing Machine (OSRM) to identify the utility of a UAM commuter service relative to other modes of transportation. Using the implemented model, we identify New York City, San Francisco, and Los Angeles as cities with the highest potential commuter demand, and Seattle as the city most resilient to increases in delay time. A sensitivity study of demand is performed and shows that strong demand exists for short trips with low total delay times and for longer trips with a low ticket price per kilometer, with the former showing resilience to increases in operational costs and the latter showing resilience to increases in delays. The demand model is supported by a speed-flow model, which fuses highway performance monitoring system data with OpenStreetMap data to provide traffic-adjusted road segment speeds to OSRM. The speed-flow model has the capability of providing congestion data for road segments across the United States without the use of commercial data sets or routing services and is shown to improve routing duration accuracy in congested regions.
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来源期刊
Journal of Air Transportation
Journal of Air Transportation Social Sciences-Safety Research
CiteScore
2.80
自引率
0.00%
发文量
16
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