Travel Behavior as Function of Accessibility, Land Use Mixing, and Land Use Balance: Evidence from San Francisco Bay Area

Abstract

By incorporating characteristics of the built environment into models of travel behavior, much can be said about household travel distances, automobile ownership, and mode choice. This research investigates the relative significance of a variety of measures of urban form, both at trip-makers' home neighborhoods and at trip ends. The travel data come from the 1990 San Francisco Bay Area Travel Surveys, and the land-use data are largely constructed from hectare-level descriptions provided by the Association of Bay Area Governments. After controlling for demographic characteristics, the measures of accessibility, land use mixing, and land use balance proved to be highly statistically significant and influential in their impact on household vehicle miles traveled (VMT), automobile ownership, and mode choice. In contrast, under the majority of models (with the important exception of the vehicle-ownership models), density's impact was

Car ownership as a mediating variable in car travel behaviour research using a structural equation modelling approach to identify its dual relationship

“…However, some confounding results exist related to the influence of accessibility by car on car use. Some studies (e.g., Rajamani et al, 2003) found that better accessibility by car results in more car use, whereas other studies state the opposite (e.g., Kockelman, 1997). Despite high levels of car accessibility, Kockelman (1997) argued that less car use might still occur since higher accessibility is generally associated with higher land prices, less convenient parking options and more roadway congestion.…”

“…Most studies pointed out that accessibility is negatively associated with car ownership (e.g., Chen et al, 2008;Gao et al, 2008;Kockelman, 1997;Simma and Axhausen, 2003). Rajamani et al (2003) found that higher accessibility by a given mode is likely to result in higher usage of that mode.…”

“…Several indicators have been developed to measure diversity: among others, a jobs/housing ratio (Boarnet and Sarmiento, 1998;Ewing et al, 1994), an entropy index to quantify the degree of balance across various land use types (Frank and Pivo, 1994;Kockelman, 1997) or a (dis)similarity index to indicate the degree to which different land uses lie within a person's surrounding (Kockelman, 1997). The effects of more diversity on car ownership and (car) travel behaviour are comparable to the effects of higher densities.…”

Does neighborhood design influence travel?: A behavioral analysis of travel diary and GIS data

“…These studies, and others, depend on a definition of neighborhood that either is dependent on census geography (Cervero and Gorham, 1995;Frank, 1994;Holtzclaw, 1994;Kitamura et al, 1994;Kockelman, 1996) or on the delineation of a neighborhood (Handy 1996a). The danger of depending on census geography is that many of the household, travel and demographic characteristics are summary data and don't necessarily relate to the households in question that reside in that tract.…”

Association between residents’ perception of the neighborhood’s environments and walking time in objectively different regions

“…To date, many studies have examined how psychological and social variables are associated with physical activity, but little is known about the correlation between neighborhood's physical environmental factors and physical activity level (6,7). High walkable neighborhood's environmental characteristics suggest a high residential density and mixed land use (e.g., close proximity of houses, shops, work, and other nonresidential land uses) (8,9), and neighborhood street connectivity (10) positively correlates with walking time among residents (8,9). The presence and characteristics of walking trails are associated with increased physical activity (11,12).…”