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Until recently, data and technology have limited the ability of travel behavior research to uniquely capture details of the built environment that may influence a person's choice to walk or bicycle. Most previous studies have relied on aggregated zonal averages homogeneously attributed to unique individuals and have likely missed key subtleties of the built environment important to people traveling outside the protective enclosure of an automobile. Furthermore, most studies focus on the characteristics of the origin, not the critical components of the destination (such as parking, availability, and price). To understand better the choice of green and active modes, which is central to an understanding of how to achieve important environmental and health benefits, this paper presents methods to align detailed measures of the built environment (in sum, more finely disaggregated data of the built environment) more closely with the individual for disaggregated analyses of travel behavior. Through the use of a new, linear spatial unit of analysis—the individual access corridor—characteristics of the built environment are captured all the way from the origin to the destination for a group of individuals large enough to be statistically meaningful for policy and urban design guidance through the use of predictive, multinomial logit mode choice models. This study provides planning and design guidance on how to increase the likelihood that one will choose walking or bicycling over motorized modes and examines such elements as zoning, subdivision ordinances, and streetscape design as well as station policies for bicycle and auto parking.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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