Analysis of Vehicles' Daily Fuel Consumption Frontiers with Long-Term Controller Area Network Data

The vehicle fuel consumption frontier (VFCF) is the unobserved maximum amount of fuel that an individual private car user is willing to consume for driving. This study incorporated interindividual and intraindividual variations into the modeling of VFCF. Long-term controller area network data collected from private cars during 10 months in Toyota City, Japan, were used. A stochastic frontier model with random parameters was applied as the modeling methodology to deal with the panel data. The data fit of the estimation results demonstrated that models with random coefficients were preferable and had better model fits than the ordinary linear regression models. VFCFs on working days were significantly affected by the departure time of the first trip, temperature, weather, home location, gender, age, and occupation. All explanatory variables, except weather and temperature, also significantly affected VFCFs on holidays. Predictions made with the estimated parameters showed that the expected VFCFs were about double the corresponding actual vehicle fuel consumption expenditures.