01479027

Component

Predicting the vehicle used for individual trips and tours can help improve the quantification of energy consumption, quality of emissions forecasts, and assess impacts of policies that vary by vehicle type. The focus of this study is to contribute to incorporating this aspect within current activity-based modeling frameworks. Data from the 2009 National Household Travel Survey are used in this analysis. The empirical scope of this study is limited to two-adult, two-car households in the context of social-recreational tours; however, this methodology can be directly extended to other cases as well. An exploratory analysis indicates that the “primary driver” variable is perhaps the strongest predictor of the vehicle allocated to independent tours and tours made by adults with children. In the case of joint tours, there is clearly a choice of vehicle to be made. Following the exploratory analysis, two models were developed. One allocates each vehicle to a primary driver in the household (long-term, household-level model). The second allocates a vehicle for the joint tours (short-term, tour-level model). Both models were estimated using the unlabeled binary-logit methodology. Several vehicle attributes (such as size/body type, fuel efficiency, age, and operating costs) and socio-economic variables (age, and presence of children) were estimated to be statistically-significant predicators of the vehicle-allocation patterns.

This paper was sponsored by TRB committee ADB40 Transportation Demand Forecasting.

01470560

13-4789

English

19p

2013

Transportation Research Board 92nd Annual Meeting

Digital/other

Figures; References; Tables

Choice models; Drivers; Households; Trip chaining

Vehicle choice

Data and Information Technology; Highways; Planning and Forecasting; I70: Traffic and Transport

Transportation Research Board Annual Meeting 2013 Paper #13-4789

TRIS, TRB, ATRI

Feb 5 2013 12:55PM