This study aims to explore the relationship between the objective (actual) environment and people's perceptions of the environment, and their relative effects on active travel behavior, particularly bicycling behavior. This is an important research gap in the current literature linking the built environment and active travel. Better understanding this relationship will help to explore the mechanism underlying the built environment- behavior relationship and identify potential interventions to promote active travel. Relying on the data from Portland, OR, this study investigated the following four research questions: (1) How does the objectively measured environment correspond to the perceived environment? And what factors contribute to the mismatch between the objective and perceived environment? (2) What are the different effects of the perceived and objective environment on active travel behavior? (3) Do perceptions mediate the effects of the objective environment on active travel behavior? (4) Do changes in the built environment change perceptions, and in turn change travel behavior? Through various statistical methods, this study found that there was a mismatch between perceptions and objectively measured environment, and such factors as socio-demographics, attitudes, social environment, and behavior could contribute to this mismatch. This study also found the perceived environment and objective environment had independent effects on bicycling. Further, this study found the objectively measured bicycling environment had only an indirect effect on bicycling behavior through influencing one's perceptions of the environment. Finally, this study found changes in the actual built environment may change the perceptions of the walking environment, but not the perceptions of the bicycling environment, at least in the short term.

Research in urban transportation has been of many facets. Some have emphasized modes and routes while others have attempted to isolate and look at small segments of the transportation market with specific demands. Such segments include workers, recreation riders, and to a less extent, students. In the "journey-to-work" studies, a major finding has been that as income of workers increases, the distance between residence and work-place also increases. This thesis starts with a series of hypotheses generated as a result of the findings of other studies reviewed in the literature. In testing the hypotheses, variables that are likely to influence student transportation cost and mode-choice in the Portland State situation were identified and included in a survey questionnaire administered among Portland State University students. The identified variables include, among others, student income, course load, duration of occupancy of dwelling unit, distance from school, time taken to cover that distance, and type of mode commonly used. In addition to the questionnaire survey, informal interviews were held with school and public transit authorities.

This dissertation examines unequal outcomes of urban transportation policies in the neoliberal era. It focuses on inequalities in the Portland, Oregon metro area between 1994 and 2011 as measured in three key areas: 1) access to public transit; 2) the journey-to-work; and 3) "household-serving" trips. Growing concern over the harmful impacts from an increasing dependence on cars has led planners in the U.S. to encourage a modal shift from private car to public transit, bicycling, and walking. The required policies to make this modal shift possible, however, might inadvertently be benefiting "choice" riders at the cost of transport disadvantaged groups. Other contributing factors to this unequal benefit appear to be the suburbanization of poverty, an ongoing gentrification of central areas, and market forces that make it difficult for low income groups to afford housing in transit-rich neighborhoods. The Oregon Household Activity and Travel surveys are used to answer the three major research questions in this dissertation: what has been the effect of neoliberalism on access to public transit?, how do gender, race/ethnicity, and income inequality affect the journey-to-work in Portland?, and how do household-serving trips vary by gender in Portland? Six hypothesis are tested in answering these questions. Those related to access to transit draw on Fred Block's theory of the capitalist state and the "urban growth machine" concept, both of which predict spatially unequal outcomes from neoliberal ideology. Hypotheses about the journey to work draw on a rich body of literature around social relations in the household and the job market, as well as residential location. The final question, about household-serving trips, draws on theories of gender socialization. Findings showed that: (i) individuals in the Portland metro area had less access overall to bus public transit in 2011 than in 1994; (ii) impoverished dependent riders have lost access to transit service over time, whereas choice dependent riders increased their access to public transit; (iii) low income groups have been "forced" into greater car-ownership, in part due to the lower access to public transit; (iv) women in Portland have shorter journey-to-work trips than men; (v) Blacks have longer journey-to-work trips than Whites and Latinos; (vi) low-income individuals have shorter journey-to-work trips than higher income individuals; and (vii) women with children make more household-serving trips than men in similar family structures.

American urban neighborhoods are a patchwork; the spatial arrangement of types is a reflection of the dominant transportation technology at the time of their development. The earliest suburban areas were made accessible by fixed route systems such as the electric streetcar, followed by the widespread adoption of the automobile; each transportation epoch resulted in characteristic patterns of land use. This study uses aerial photographic coverage of Portland, Oregon from the years 1925, 1936, and 1945, a time of decline for the once popular trolley lines and dramatic increase in automobile usage, to monitor change within the residential areas of Portland's east side over a twenty year period. Classic economic models of the time acknowledged transportation as a force shaping the city; modem ideas in urban planning such as Traditional Neighborhood Design and Transit Oriented Development look to pre-automobile urban form as a means to reduce automobile use and its negative implications. This study uses variables of housing density and street connectivity derived from the aerial photography; the measured values of these variables are then considered for their spatial and temporal distribution using statistical comparisons. The results are compared to ideas within the urban models and current thinking about urban morphology. While generally consistent with the expected patterns, deviations and differences between the two variables are considered for their implications. Models offer a simplified version of the growth of American cities, considering only a few of the many aspects of a dynamic environment. By isolating on these variables of density and connectivity, a greater understanding of their role in arriving at the modem residential urban environment may be reached, and this understanding can add to the discourse in current planning debates.

Transportation availability and land use intensity demonstrate a strong relationship, with intense development concentrated near significant transportation investment. Transportation networks evolved in response to emergent transportation technologies and changing urban land uses. The irregular distribution of transportation systems reinforced patterns of land use development, shaping urban form. Understanding the relationships between transportation and the intensity of land uses allows urban geographers and city planners to explain the urbanization processes, as well as to identify areas historically susceptible to future development. The goal of this research is to develop a quantitative framework for the analysis of the development of urban form and its relationship to urban transportation systems. This research focuses on transportation accessibility, building density, and the structural massing as the basic metrics in the categorization of urban form. Portland, Oregon serves as the case study environment, while the research methodology examines the spatial and statistical relationship between these metrics for much of the city's urban area. Applying geographic information systems (GIS) and k-means cluster analysis, urban form metrics are compared within the ADaM (Accessibility, Density, and Massing) cube, a model demonstrating comparative relationships, as well as the geographic distribution and patterns of urban form in Portland, Oregon's neighborhoods. A finalized urban form catalog describes existing urban environments, but also indicates areas of impending transition, places having the strong potential for reorganization with respect to higher levels of transportation accessibility. The ADaM Cube is a tool for characterizing Portland's existing urban form, and describing the vulnerabilities of urban neighborhoods to the pressure of redevelopment.

Geographic Information System (GIS) address-matching combined with other GIS processing offers new analytical opportunities in the area of transportation planning and analysis. Address-matching, an automated method for generating geographically-referenced (geocoded) point locations on a map from common tabular databases, can facilitate transportation analysis by providing a planning tool based on individual rather than aggregated spatial distributions more common to transportation issues.

For a number of reasons--congestion, public health, greenhouse gas emissions, energy use, demographic shifts, and community livability to name a few--the importance of walking and bicycling as transportation options will only continue to increase. Currently, policy interest and infrastructure funding for nonmotorized modes far outstrip our ability to model bike and walk travel. To ensure scarce resources are used most effectively, accurate models sensitive to key policy variables are needed to support long-range planning and project evaluation, and to continue adding to our growing understanding of key factors driving walk and bike behavior. This research attempts to synthesize and advance the state of the art in trip-based, nonmotorized mode choice modeling. Over the past fifteen years, efforts to model the decision to walk or bike on a given trip have been hampered by the lack of a comprehensive behavioral framework and inconsistency in measurement scales and model specification. This project develops a mode choice behavioral framework that acknowledges the importance of attributes along the specific walk and bike routes that travelers are likely to consider, in addition to more traditional area-based measures of travel environments. The proposed framework is applied to a revealed preference, GPS-based travel dataset collected from 2010-2013 in Portland, Oregon. Measurement of nonmotorized trip distance, built environment, tour-level variables, and attitudinal attributes as well as mode availability are explicitly addressed. Route and mode choice models are specified using discrete choice techniques, and predicted walking and bicycling routes are tested as inputs to various mode choice models. Results suggest strong potential for predicted route measures to enhance walk and bicycle mode choice modeling. Findings also support the specific notion that bicycle and pedestrian infrastructure contribute not only to route choice but also to the choice of whether to bike or walk. For decisions to bicycle, availability of low-traffic routes may be particularly important to women. Model results further indicate that land use and built environments around trip ends and a person’s home still have important effects on nonmotorized travel when controlling for route quality. Both route and area travel environment impacts are mostly robust to the inclusion of residential self-selection variables, consistent with the idea that built environment differences matter even for households that choose to live in a walkable or bikeable neighborhood. The combination of area and route-based built environment measures alongside trip context, sociodemographic, and attitudinal attributes provides a new perspective on nonmotorized travel behavior relevant to both policy and practice.

During the past three decades, research in travel behavior has generally proceeded from broad-level, aggregate analysis of mode share--the proportions of walking, bicycling, transit, and vehicle travel occurring in traffic analysis zones, census tracts, neighborhood, or other geographical units--to fine-grained, disaggregate analysis of mode choices and other trip-making attributes at the individual level. One potential issue is whether there are differences in the types of conclusions drawn from results of analyses performed at these different levels, as these results directly inform transportation planning and policy. This thesis aims in part to confirm whether the types of conclusions drawn from different levels of analysis are different, and to what extent. We also examine the relationships between the built environment and non-work travel choices from a unique analysis perspective. To do this, we use data from a 2011 travel intercept survey in the Portland, Oregon metropolitan region that was administered at convenience store, bar, and restaurant establishments. We estimate, for each of the travel modes--walk, bicycle, and automobile--two analysis models: one binary logistic regression model for mode choice of the individual traveler going to the establishment and one multiple linear regression model for mode share of shoppers at the establishment. Both models control for socio-demographics, trip characteristics, and built environment measures of travelers. For the binary logistic regression models, the data are disaggregate and particular to the individual traveler. These models also controlled for attitudes and preference towards travel modes. For the multiple regression models, data are aggregated to the establishment. The built environment data in each model represent characteristics of urban form surrounding the establishment. The data being oriented to the destination-end of the trip, as well as providing controls on land use make this analysis unique in the literature, as most non-work travel studies use residential-based data. Results suggest that analyses performed at the two different levels provide policy-relevant but somewhat different conclusions. In general, characteristics of the individual and the trip have stronger associations with mode choices of individuals than when aggregated to the establishment and analyzed against the mode share patterns of shoppers. Instead, mode shares have stronger relationships with characteristics of the built environment. The built environment surrounding the destination has a much more pronounced association with mode shares at the establishment than with mode choices of individuals. The results highlight the usefulness of simple aggregate analysis, when appropriate. We also find large differences between modes in which characteristics are important for mode choice and mode share. Walking and automobile models behave somewhat similarly but in opposite directions, while bicycling behaves quite differently. These differences suggest on their own a move away from non-motorized travel to be considered as equivalent or assessed as one item in research and in practice.