科研之友
微信
新浪微博
Facebook
分享链接
摘要
Policymakers, transport planners, automobile manufacturers, and others are interested in the factors that affect adoption rates of electric vehicles and other fuel-efficient vehicles. With tract-level data from the 2010 census and registered vehicle counts from Texas counties in 2010, this study investigated the impact of various built environment and demographic attributes, including land use balance, employment density, population density, median age, gender, race, education, household size, and income. Spatial autocorrelation (across census tracts) in unobserved components of vehicle counts by tract and cross-response correlation (both spatial and local-aspatial in nature) was allowed for by the estimation of models of ownership levels (vehicle counts by vehicle type and fuel economy level) with bivariate and trivariate Poisson-lognormal conditional autoregressive models. The presence of high spatial autocorrelations and local cross-response correlations was consistent in all models across all counties studied. Ownership rates for fuel-efficient vehicles were found to rise with household income, resident education levels, and the share of male residents and to fall in the presence of larger household sizes and higher job densities. The average fuel economy of each tract's light-duty vehicles was also analyzed with a spatial error model across all Texas tracts, and this variable was found to depend most on educational attainment levels, median age, income, and household size variables, though all covariates used were statistically significant. If households registering more fuel-efficient vehicles, including hybrid electric vehicles, are also more inclined to purchase plug-in electric vehicles, these findings can assist in spatial planning of charging infrastructure as well as other calculations (such as implications for the revenue from gas tax).
- 出版日期2015
