What kind of cars do people drive? Including fuel type and emission standards in a car ownership model

Car ownership models are essential for understanding travel behavior and informing transportation policy decisions. However, previous research on car ownership modeling has not addressed the determinants of car ownership related to pollutant emissions such as fuel type or emission standard. This study seeks to fill this gap by comparing the performance of several classification models in predicting the number of cars owned by households, their fuel type and their Euro norm (i.e. car age), while also investigating the significance of explanatory variables. These variables include socioeconomic characteristics, as well as mobility-related variables such as commuting distance, parking availability, and public transportation accessibility to the home and workplace. The methodology is applied to the Paris region. We find that supervised learning models slightly outperform the multinomial logistic regression for the three models. Our results show that the main explanatory variables of the types of cars owned are related to the income, the household composition and the mobility-related characteristics of the household. For the fuel type, the household composition and regional accessibility of home city have a highly significant effect on petrol car ownership rather than diesel, while the income is an important predictor through non-linear relationships and interactions. Furthermore, the household income is the main determinant of the Euro norm, with a non-linear effect of the mobility-related variables (commuting distance and regional accessibility of home and work cities). This work paves the way for future research evaluating transportation policies related to household car ownership by allowing a deeper understanding of the determinants of the type of car owned by households and by providing the trained classifiers as open data.