Citation

Chi G, Wang D, Hagedorn ADJ. Case Stud. Transp. Policy 2019; 7(2): 384-394.

Copyright

(Copyright © 2019, World Conference on Transport Research Society, Publisher Elsevier Publishing)

DOI

10.1016/j.cstp.2019.03.001

PMID

32542178 PMCID

Abstract

The Interstate Highway System (IHS) used to be a symbol of American growth and its economic machine, but the IHS has not been expanded much since its inception. Recently there are both executive and legislative desires to restore and upgrade the IHS to its role as a premier system that can meet the growing and changing demands of the twenty-first century. Demographic forecasting is a precursor to rational transportation planning and decision activities. This paper provides population projections into 2060 at the county level for the entire US using cohort-component methods. We found that the US is projected to experience population growth across all age groups over the next 50 years. The projected growth, however, varies across the entire US. Population growth areas are in the west/south/east border states and the Atlanta-NC-Nashville triangle. Population decline areas include many counties from the northeast corner to the Appalachian region, counties bordering the five Great Lakes, counties along the Mississippi River, the Deep South states, and Alaska. We also identified the counties that may need additional or less transport capacity based on projected population change and proximities to IHS. We further identified the counties with high population density but without the IHS network that are projected to experience rapid population growth. IHS demands will be affected by the aging population, the young population, baby boomers, millennials, immigrants, telecommuting, and autonomous vehicles. This study provides the necessary demographic forecasting for decision and policy makers in better deciding whether and where to expand or invest in the IHS when the resources become available.

Language: en

Keywords

population change; Interstate Highway System; cohort component method; demographic forecasting; population projection; spatial overlay