The vehicle miles of travel for each vehicle in multi-vehicle households is modeled as a function of household characteristics, vehicle characteristics, and the matches of vehicle to driver in the satisfaction of travel desires. A structural equations model is developed in which principal driver characteristics, as well as vehicle miles of travel, are endogenous. There are links between how each vehicle is used and who in the household is each vehicle’s principal driver. Each vehicle’s usage can then be expressed in reduced-form equations as a function of exogenous household and vehicle type variables for forecasting purposes. The model is estimated on a 1993 sample of approximately 2000 multi-vehicle households in California.

This research is part of the project aimed at developing a model system to forecast demand for clean fuel vehicles in California, conducted by researchers at the University of California, Irvine and University of California, Davis. The objective of the research reported here is to explain annual vehicle miles of travel for each of the two vehicles in two-vehicle households as a function only of household characteristics that can be forecasted using the household sociodemographic updating model being developed as part of the personal vehicle submodel (brownstone, Bunch and Golob, 1994). The household's choice of the number of vehicles to own and the types of these vehicles, in terms of the class and vintage of each vehicle, are taken as given in this model.

A discrete choice model has been developed in which the choice alternative consist of vehicle transactions rather than portfolios of vehicle holdings. The model is based on responses to customized stated preference questions involving both hypothetical future vehicles and the household's current vehicle holdings. The stated choices were collected from 4747 survey respondents located throughout most of the urbanized portions of the state of California. Respondents were asked what their next vehicle transaction would most likely be (replace a current vehicle, add another vehicle, or dispose of a current vehicle), and respondents who wanted to replace or add vehicles were asked to indicate their most preferred vehicle from a set of six hypothetical vehicles. The hypothetical vehicles were described in terms of fourteen attributes, manipulated according to an experimental design. 

The transactions model is a multinomial logit model of the choice of the hypothetical vehicles and whether or not the hypothetical vehicle will be a replacement or addition to the household fleet. The model is conditioned on the household's current vehicle stock. and the characteristics of the current vehicles are important explanators of the stated preference choices. In addition to the model estimates, forecasts are given for a base case scenario in 1998. 

This model is one component in a micro-simulation demand forecasting system being designed to produce annual forecasts of new and used vehicle demand by type of vehicle and geographic area. The system will also forecast annual vehicle miles traveled for all vehicles and recharging demand by time of day for electric vehicles. These results are potentially useful to utility companies in their demand-side management planning, to public agencies in their evaluation incentive schemes, and to manufacturers faced with designing and marketing alternative-fuel vehicles. 

The vehicle miles of travel for each vehicle in multi-vehicle households is modeled as a function of household characteristics, vehicle characteristics, and the matches of vehicle to driver in the satisfaction of travel desires. A structural equations model is developed in which principal driver characteristics, as well as vehicle miles of travel, are endogeneous. There are links between how each vehicle is used and who in the household is each vehicle's principal driver. Each vehicle's usage can then be expressed in reduced-form equations as a function of exogeneous household and vehicle type variables for forecasting purposes. The model is estimated on a 1993 sample of approximately 2000 multi-vehicle households in California.

The vehicle choice model developed here is one component in a micro-simulation demand forecasting system being designed to produce annual forecasts of new and used vehicle demand by vehicle type and geographic area in California. The system will also forecast annual vehicle miles traveled for all vehicles and recharging demand by time of day for electric vehicles. The choice model specification differs from past studies by directly modeling vehicle transactions rather than vehicle holdings. The model is calibrated using stated preference data from a new study of 4,747 urban California households. These results are potentially useful to public transportation and energy agencies in their evaluation of alternatives to current gasoline-powered vehicles. The findings are also useful to manufacturers faced with designing and marketing alternative-fuel vehicles as well as to utility companies who need to develop long-run demand-side management planning strategies.