Geology Reports⌕ Search
Home/Archive/USGS

USGS · 70135628

Structural equation models of VMT growth in US urbanised areas.

Reid Ewing·Shima Hamidi·Frank Gallivan·Arthur C. Nelson·James B. Grace
View original source ↗Export metadata ↓

Abstract

Vehicle miles travelled (VMT) is a primary performance indicator for land use and transportation, bringing with it both positive and negative externalities. This study updates and refines previous work on VMT in urbanised areas, using recent data, additional metrics and structural equation modelling (SEM). In a cross-sectional model for 2010, population, income and freeway capacity are positively related to VMT, while gasoline prices, development density and transit service levels are negatively related. Findings of the cross-sectional model are generally confirmed in a more tightly controlled longitudinal study of changes in VMT between 2000 and 2010, the first model of its kind. The cross-sectional and longitudinal models together, plus the transportation literature generally, give us a basis for generalising across studies to arrive at elasticity values of VMT with respect to different urban variables.

Explore related subjects

Urban StudiesArticle

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Reid Ewing, Shima Hamidi, Frank Gallivan, Arthur C. Nelson, James B. Grace. 2014-02-10. Structural equation models of VMT growth in US urbanised areas.. https://doi.org/10.1177/0042098013516521

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2014

Urban sprawl as a risk factor in motor vehicle crashes

A decade ago, compactness/sprawl indices were developed for metropolitan areas and counties which have been widely used in health and other research. In this study, we first update the original county index to 2010, then develop a refined index that accounts for more relevant factors, and finally seek to test the relationship between sprawl and traffic crash rates using structural equation modelling. Controlling for covariates, we find that sprawl is associated with significantly higher direct and indirect effects on fatal crash rates. The direct effect is likely due to the higher traffic speeds in sprawling areas, and the indirect effect is due to greater vehicle miles driven in such areas. Conversely, sprawl has negative direct relationships with total crashes and non-fatal injury crashes, and these offset (and sometimes overwhelm) the positive indirect effects of sprawl on both types of crashes through the mediating effect of increased vehicle miles driven. The most likely explanation is the greater prevalence of fender benders and other minor accidents in the low speed, high conflict traffic environments of compact areas, negating the lower vehicle miles travelled per capita in such areas.

Urban Studies↗