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Predicting passenger trips for future energy and transportation investment planning.

机译：预测旅客旅行，以进行未来的能源和运输投资规划。

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摘要

Passenger Transportation is one of the two major components of transportation sector (the other being freight) and it is one of the major factors affecting the energy demand and the need for transportation infrastructure investments. Specifically, 12% of energy consumption and almost 17% of total greenhouse gas emissions in the United States are attributed to passenger transportation, while the energy consumption due to passenger transportation is almost 60% of the total energy consumption in transportation sector. These statistics indicate the importance of predicting passenger transportation for future energy and transportation infrastructure investment planning. Vehicle Miles Traveled (VMT) is one of the most common measure estimating passenger trips in the United States and has been traditionally used to determine the need for new infrastructure. As the availability of energy resources and the funding for new infrastructure decrease, the need of forecasting VMT in the future for energy and transportation investment planning becomes vital.;Various studies in the past have determined the factors affecting VMT. Demographic and socioeconomic characteristics, road infrastructure, and land use influence the amount of passenger trips, but also fuel prices and government policy. Increase of population and income per capita has been traditionally the factor resulting directly to the increase of VMT while areas with higher density result to lower per capita single vehicle travel demand. Moreover, the increase of fuel cost decreases VMT while the impact of lane miles is totally opposite.;While previous studies have investigated the effect of demographic and socioeconomic characteristics, or the effect of land use and road capacity, or the effect of fuel prices on VMT, the effect of these factors has not been fully examined in a multivariate context. The objective of this thesis is to determine the factors that influence passenger trips and develop a prediction model of VMT in the future. Using panel data for the 48 continental states during the period 1998-2008, simultaneous equation models were developed for predicting VMT on different road functional classes and examining how new technology (telecommuting, alternative fuel vehicles) but also changes in fuel prices can affect the amount of passenger trips across the nation. Moreover, a panel data regression model with random coefficients was developed to identify the factors affecting total VMT. The use of panel data allows for the determination of the influence of different factors but also the effect of these factors across different states and years. To assess the influence of each significant factor on VMT, elasticities were estimated.;Further, the effect of innovations in technology (such as telecommuting and alternative fuel vehicles) and various government policies on energy consumption and greenhouse emissions was investigated. Different scenarios for high speed rail network, alternative fuel vehicle market share, fuel tax and density in the future were developed in order to quantify that impact. The estimation results of the model for total VMT were used to estimate the influence of each policy and scenario on the amount of total VMT, while the reduction of energy consumption and greenhouse gas emissions was estimated using the software VISION, developed by the Argonne National Laboratory.;The estimated models of passenger trips can assist transportation planners and policy-makers to determine the energy and transportation infrastructure investment needs in the future.;Key words: Passenger trips, energy consumption, infrastructure plan, policy, new technology.
机译：客运是运输部门的两个主要组成部分之一（另一个是货运），它是影响能源需求和运输基础设施投资需求的主要因素之一。具体来说，美国的能源消耗量占总能耗的12％，温室气体排放量几乎占总排放量的17％，而客运引起的能耗几乎占交通运输部门总能耗的60％。这些统计数据表明，预测客运对未来能源和交通基础设施投资计划的重要性。车辆行驶里程（VMT）是估算美国旅客旅行量的最常用方法之一，传统上一直用于确定对新基础设施的需求。随着能源的可获得性和新基础设施资金的减少，对能源和运输投资计划的未来VMT进行预测的需求变得至关重要。过去的各种研究已经确定了影响VMT的因素。人口和社会经济特征，道路基础设施和土地使用会影响旅客旅行的数量，但也会影响燃油价格和政府政策。传统上，人口和人均收入的增长是直接导致VMT增加的因素，而人口密度较高的地区则导致人均单车旅行需求降低。此外，燃料成本的增加降低了VMT，而车道里程的影响却完全相反。;尽管先前的研究已经调查了人口和社会经济特征的影响，土地使用和道路通行能力的影响或燃料价格对VMT，这些因素的影响尚未在多变量环境中进行全面检查。本文的目的是确定影响旅客出行的因素，并建立未来的VMT预测模型。利用1998-2008年期间48个洲际州的面板数据，开发了联立方程模型，用于预测不同道路功能类别的VMT，并研究新技术（通勤，代用燃料汽车）以及燃料价格的变化如何影响数量全国的旅客旅行此外，开发了具有随机系数的面板数据回归模型以识别影响总VMT的因素。面板数据的使用可以确定不同因素的影响，也可以确定这些因素在不同州和不同年份的影响。为了评估每个重要因素对VMT的影响，我们估算了弹性。此外，还研究了技术创新（例如远程办公和替代燃料车辆）和各种政府政策对能源消耗和温室气体排放的影响。为了量化这种影响，针对未来的高速铁路网络，替代燃料汽车的市场份额，燃料税和密度制定了不同的方案。 VMT总量模型的估算结果用于估算每种政策和方案对VMT总量的影响，而能源消耗和温室气体排放量的减少是使用由阿贡国家实验室开发的VISION软件估算的关键词：旅客出行，能源消耗，基础设施计划，政策，新技术。旅客出行的估计模型可以帮助运输规划人员和决策者确定未来的能源和交通基础设施投资需求。

著录项

  • 作者

    Rentziou, Aikaterini.;

  • 作者单位

    Iowa State University.;

  • 授予单位 Iowa State University.;
  • 学科 Engineering Civil.;Transportation.;Energy.
  • 学位 M.S.
  • 年度 2010
  • 页码 125 p.
  • 总页数 125
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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