Travel demand estimates that derive from the traditional sequential process often derive their values from some consideration of household car ownership. This variable may be misleading in that not all who live in households with cars may have access to a car, conversely, not all in households without cars are captive solely to other modes.
It is proposed that another variable, car availability, be used in planning studies, to provide more accurately a description of an individual's access to a car. In a recent study, this variable took a two-dimensional form. One dimension considers how the car is available (driver, rider, or not at all) and the other describes the frequency with which it is available (from always to never). From this description, it is noted that a small percentage of people in car owning households have little access to cars, while a significantly high percentage of those in autoless households do have access to cars a great deal of the time (albeit as passengers only).
The constrictions of availability affect the frequency with which someone will do a set of activities, and the mode by which he travels to his activities. Distinctions are shown to exist between car owners, non-car owners, those to whom a car is available and those to whom it is not, using activity frequency as a discriminator. It is seen that as car becomes less available a greater percentage of trips are used for fewer activities. Further as car becomes less available the selection of modes for these activities becomes more apparent. Car is used exclusively for a few selected purposes, then there are trade-offs to bus and walking depending on both car availability and trip purpose. No group then can be thought of as singularly transit captive. Comparisons are made between levels of availability and also between availability and ownership. * The work reported here was sponsored by the United States Department of Transportation (Contract DOT-OS-30098) and the Greater Buffalo Development Foundation. The views expressed are those of the authors and do not necessarily reflect those of the sponsors. Sue Knapp and Peter Edelstein assisted with the data analysis.