Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune 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 simultaneous equation models for predicting VMT on different road functional classes and examine 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 influence 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 influence 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 estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.
|Number of pages||14|
|Journal||Transportation Research Part A: Policy and Practice|
|State||Published - Mar 2012|
Bibliographical noteFunding Information:
This material is based upon work supported by the National Science Foundation under Grant No. 0835989. The authors would like to thank Anant Vyas of Argonne National Laboratory for his assistance with the VISION software, and Robert Rozycki of Federal Highway Administration for providing the HPMS data for this study.
- Energy consumption
- Passenger transportation
- Random parameters
ASJC Scopus subject areas
- Civil and Structural Engineering
- Management Science and Operations Research