Abstract
In the United States, several studies have looked at the association between automobile ownership and sociodemographic factors and built environment qualities, but few have looked at household travel characteristics. Their interactions and nonlinear linkages are frequently overlooked in existing studies. Utilizing the 2017 US National Household Travel Survey, the authors employed an extreme gradient boosting tree model to evaluate the nonlinear and interaction impacts of household travel characteristics and built environment factors on vehicle ownership in three states of the United States (California, Missouri, and Kansas) that are different in population size. To develop these models, three main XGBT parameters, including the number of trees, maximal depth, and minimum rows, were optimized using a grid search technique. In California, the predictability of vehicle ownership was driven by household travel characteristics (cumulative importance: 0.62). Predictions for vehicle ownership in Missouri and Kansas were dominantly influenced by sociodemographic factors (cumulative importance: 0.53 and 0.55, respectively). In all states, the authors found that the number of drivers in a household plays a vital role in the vehicle ownership decisions of households. Regarding the built environment attributes, deficiencies in cycling infrastructure were the most prominent attribute in predicting household vehicle ownership in California. This variable, however, has threshold connections with vehicle ownership, but the magnitude of these relationships is small. The outcomes imply that improving the condition of cycling infrastructure will help reduce the number of vehicles. In addition, incentives that encourage the households’ drivers not to buy new vehicles are helpful. The outcomes of this study might aid policymakers in developing policies that encourage sustainable vehicle ownership in the United States.
Highlights
In the United States, each household has an average of 1.88 vehicles [1]
To the best of the authors’ knowledge, to date, no study has employed XGBT to reveal the complex relationships between built environment attributes, household travel characteristics, and sociodemographic characteristics in predicting household vehicle ownership
The main goal of this present study is to reveal the nonlinear relationship between the count of household vehicles and sociodemographic, household travel characteristics, and built environment attributes
Summary
While sociodemographic and built-environment attributes have been widely utilized to predict vehicle ownership globally, studies have rarely employed household travel characteristics indicators, such as household drivers’ count, household members’ count on the trip, and household vehicle used on the trip These variables are important because they can be assumed as indicators of independent trips. The following are the questions that this research aims to answer: (1) How important are built environment attributes, household travel characteristics, and sociodemographic characteristics in influencing household vehicle ownership decisions in the United States? This research shows how important household travel characteristics, as well as their interactions with major built-environment variables, play a significant role in limiting vehicle expansion in each state. To the best of the authors’ knowledge, to date, no study has employed XGBT to reveal the complex relationships between built environment attributes, household travel characteristics, and sociodemographic characteristics in predicting household vehicle ownership.
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