Abstract:In recent decades, the mixing of complementary land uses has become an increasingly important goal in transportation and land use planning. Land uses mix has been shown to be an influential factor in travel behavior (mode choice and distance traveled), improved health outcomes, and neighborhood-level quality of life. However, quantifying the extent to which a given area is mixed-use has proven difficult. Much of the existing research on the mixing of land uses has focused on the presence and proportion of different uses as opposed to the extent to which they actually interact with one another. This study proposes a new measure of land use mix, a land use interaction method-which accounts for the extent to which complementary land uses adjoin one another-using only basic land use data. After mapping and analyzing the results, several statistical models are built to show the relationship between this new measure and reported travel behavior. The models presented show the usefulness of the approach by significantly improving the model fit in comparison to a commonly-used land use mix index, while controlling for socio-demographic and built form factors in three large Canadian cities (Vancouver, Toronto, and Montreal). Our results suggest that simple, area-based, measures of land use mix do not adequately capture the subtleties of land use mix. The degree to which an area shows fine-grained patterns of land use is shown to be more highly correlated with behavior outcomes than indices based solely on the proportions of land use categories.

This paper describes an attempt to understand better the endogenous relationships between urban form, accessibility to public transit, and daily travel distance. A model of two simultaneous equations was implemented. The model took into account the interaction between the ownership of vehicles and the choice of household location as explanatory endogenous variables for total distance traveled by respondents. Choice of household location was defined on the basis of cluster analysis (neighborhood typology) driven by land use mix, population density, and accessibility to transit. With socioeconomic variables controlled for, the impacts of neighborhood typologies combined with car ownership levels as endogenous choices were estimated with the use of a model with simultaneous equations. This research used data from the Quebec City, Quebec, Canada, origin–destination survey conducted in 2001. The data set included responses from more than 50,000 individuals. Among other results, the presence of endogeneity was confirmed. When endogeneity was not taken into account, the joint effects of car ownership and household location choices were underestimated. According to the model with simultaneous equations, the total distance traveled by individuals was primarily influenced by employment status and household structure. In fact, the total distance per individual had an average rate of growth of 50% when the individual was working full-time. The distance also increased by 5.7% per child and decreased by 2.4% per person. Although the elasticities of urban form and transit supply variables introduced individually into the model were small, the elasticities of neighborhood type as endogenous variables were much more relevant.

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