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Until recently, data, technology, and practice have limited travel behavior research in its ability to uniquely capture individual-level details of urban environments. While previous studies have relied primarily on aggregate, zonal averages homogeneously attributed to unique individuals, this dissertation presents methods to more closely align measures of the urban environment with the individual as the unit of analysis. In short, disaggregated data for disaggregated analyses.Furthermore, previous studies have often focused on the immediate areas (1/4- to 1/2-mile radii) around trip origins and destinations, while little focus has been paid to the unique characteristics of the urban environment in between. In response, this research pioneers the use of a new spatial unit of analysis, the "individual access corridor" (IAC), to better understand how people may be influenced by certain urban design, land use, or transport characteristics experienced along their journey to a certain destination (e.g., stores, mixed use developments, schools, and transit stations). The primary goal of this research is to develop and test new methods to measure the urban environment. Three core principles (resolution, respondent, replicability) comprise the central evaluative framework guiding the exploration and development of these new methods. They are introduced in this dissertation as the "3R principles of methodological development." They guide the use of the IAC to capture high-resolution information about the urban environment (land use activity, transport access, and traveler perceptions) that can be uniquely attributed to each individual survey respondent in a replicable manner. This information, in turn, can support reliable and valid analyses of the influence of the urban environment on consumer behavior that are meaningful, rigorous, and generalizable. The secondary goal of this research is to test these new measures as inputs for travel behavior analyses of a relatively standard intercept travel survey--the 2008 Station Profile Survey for the San Francisco Bay Area Rapid Transit (BART) system. Improving measures for these analyses is important because substantial effort and money is currently being spent on influencing traveler behavior in suburban/non-CBD areas, and for trips to transit. As most morning commuters across the U.S. drive to rapid transit stations, and over relatively short distances, substantial sustainability benefits could be realized by coaxing even a small fraction of these drivers to use "green" non-motorized travel (NMT) modes of bicycling and walking. As well as providing useful insights into designs and policies that support NMT, this study of rapid transit access behavior serves as a "proof of concept" for the development and application of the new methods to measure the urban environment explored in this research.In terms of its primary goal, this research shows that capturing high-resolution information of the urban environment can be uniquely attributed to each individual survey respondent in a replicable manner to support both reliable and valid analyses of consumer behavior. Reliability of these new methods and measures is determined by: 1) their ability to objectively and uniformly capture and calculate factors of interest; and 2) their provision of similar results through repeated experiments. Validity is established via: 1) a thorough in-depth review of empirical research, literature, and urban theory to identify particular aspects of the urban environment they represent; and 2) an examination of the findings emerging from numerous models, with respect to interpretability, sensibility and usefulness. Specific achievements include the following:*This research supports the use of the IAC to examine the unique intermediate area of a trip between its origin and destination, especially when examining NMT behavior (bicycling and walking).*This research enriches our understanding of how to measure and analyze land use activity, beyond the currently used measures of "diversity", where entropy indices have been widely used as a proxy for land use mixture. Specifically, this research tests the best methods for managing vast amounts of complicated land use information, classified at the parcel-level, to be meaningfully applied to analyses of consumer behavior. *This research complements the current body of literature on travel behavior and the built environment by more formally recognizing and including measures of the functional/operational qualities of urban environments, as well as measures of physical infrastructure, urban form, and "perceptual qualities" (Ewing et al., 2006; Ewing & Handy, 2009).*This research provides valuable insight on transportation policies and urban design practices that will help communities and regions move more deliberately toward sustainability objectives, such as reducing auto use, GHG emissions, and congestion, while simultaneously improving air quality, street livability, the building of social capital, and enhancing opportunities for physical activity. In terms of the second goal of this research--testing the relationship of these new measures of the urban environment to rapid transit access travel behavior--they are proven to support reliable and valid findings that provide useful, nuanced insight into the influence of the urban environment on rapid transit access mode choice. Specifically, the findings suggest that certain policies and design characteristics of the individual access corridors (IACs) to rapid transit could increase the likelihood that one will either walk or bicycle (thus supporting the achievement of sustainability benefits) if:*Access corridors are composed of buildings that are at a human scale, are located close to the street (giving them a stronger sense of enclosure), and have distinct, "visually rich" urban form characteristics that express both complexity and imageabilty. oThis is supported by the finding of a strong negative relationship between the use of an NMT mode to access rapid transit, and the presence of larger ("big box") parcels, and auto-supporting land uses, such as parking lots, and road & freeway rights-of-way (ROW) along a commuter's IAC. *Communities are designed with narrower, well connected streets and/or more direct walking and bicycling paths. oThis is supported by the finding of a strong positive association between the use of an NMT mode to access rapid transit with route directness. It is also supported by strong negative relationship between NMT rapid transit access and the amount of land in auto-supporting land uses such as parking lots, and road & freeway rights-of-way (ROW), along a commuter's IAC.*Small, personal service retail opportunities are provided.oThis supported by the finding of a strong positive relationship between NMT access and small retail/mixed uses along a commuter's IAC.Finally, the methods and measurements explored and developed in this dissertation can be applied in a wide range of urban settings and toward a better understanding of the influence of important characteristics of the urban environment on consumer behavior as it relates to a broad array of sustainability objectives.

Between 2009 and 2016, the number of pedestrian and bicyclist fatalities saw a marked trend upward. Taken together, the overall percentage of pedestrian and bicycle crashes now accounts for 18% of total roadway fatalities, up from 13% only a decade ago. Technological advancements in transportation have created unique opportunities to explore and investigate new sources of data for the purpose of improving safety planning. This study investigated data from multiple sources, including automated pedestrian and bicycle counters, video cameras, crash databases, and GPS/mobile applications, to inform bicycle and pedestrian safety improvements. Data mining techniques, a new sampling strategy, and automated video processing methods were adopted to demonstrate a holistic approach that can be applied to identify facilities with highest need of improvement. To estimate pedestrian and bicyclist counts at intersections, exposure models were developed incorporating explanatory variables from a broad spectrum of data sources. Intersection-related crashes and estimated exposure were used to quantify risk, enabling identification of high-risk signalized intersections for walking and bicycling. The modeling framework and data sources used in this study will be beneficial in conducting future analyses for other facility types, such as roadway segments, and also at more aggregate levels, such as traffic analysis zones.