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VMT, energy consumption, and GHG emissions forecasting for passenger transportation

机译：旅客运输的VMT，能耗和温室气体排放预测

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摘要

Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technolo gies, and improved statistical modeling capabilities make the present moment an oppor tune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998-2008, the authors develop simulta neous equation models for predicting VMT on different road functional classes and exam ine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influ ence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influ ence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estima tion results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.
机译：全球化，温室气体排放和能源问题，新兴的车辆技术以及改进的统计建模功能使当前时刻成为重新调整乘客的总行驶里程（VMT），能耗和温室气体（GHG）排放预测的最佳时机运输。作者使用1998年至2008年期间48个大陆州的面板数据，开发了用于预测不同道路功能类别上的VMT的同时方程方程模型，并研究了不同的技术解决方案和燃油价格变化如何影响乘客VMT。此外，开发了一个随机系数面板数据模型来估计各种因素（例如人口统计，社会经济变量，燃油税和运力）对美国旅客VMT总量的影响。为了评估每个重要因素对VMT的影响，估计了弹性。此外，作者研究了有关燃油税和人口密度的不同政策对未来能源消耗和温室气体排放的影响。提出的方法和估计结果可以帮助运输规划人员和决策者确定未来的能源和运输基础设施投资需求。

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