Thesis. 1978. M.C.P.--Massachusetts Institute of Technology. Dept. of Urban Studies and Planning. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. / Bibliography: leaves 88-91. / M.C.P.

Thesis. 1975. M.C.P.--Massachusetts Institute of Technology. Dept. of Urban Studies and Planning. / Bibliography: leaves 178-180. / M.C.P.

Thesis. 1975. Ph.D.--Massachusetts Institute of Technology. Dept. of Civil Engineering. / Bibliography: leaves 329-336. / Ph.D.

Thesis. 1975. Ph.D.--Massachusetts Institute of Technology. Dept. of Civil Engineering. / Vita. / Bibliography: leaves 325-329. / Ph.D.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1982. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH / Bibliography: leaves 177-180. / by Peter Paul Belobaba. / M.S.

The continuing evolution of urban travel patterns and changing policy goals and priorities requires that transportation researchers and practitioners improve their abilities to plan and forecast the demand for travel. Walking and bicycling - the primary forms of active travel - are generating increasing interest for their potential to reduce automobile use, save governmental and consumer costs, and improve personal and social health outcomes. Yet, current transportation planning tools, namely regional travel demand forecasting models, poorly represent these active travel modes, if at all. More broadly, travel models do an incomplete job of representing the decision-making processes involved in travel choices, especially those factors influencing walking and bicycling. In addition to limitations of data and statistical analysis methods, the research upon which modeling tools are based has yet to settle on a comprehensive theory of travel behavior that accounts for complex relationships around a variety of personal, social, and environmental factors. While modeling tools have explained travel primarily through economic theories, contributions from the geography and psychology fields prove promising. A few scholars have attempted to link these travel behavior explanations together, some with a focus on walking and bicycling, but these theories have yet to make a significant impact on travel modeling practice. This thesis presents a unifying interdisciplinary framework for a theory of travel decision-making with applications for travel demand modeling and forecasting and a focus on walking and bicycling. The framework offers a guide for future research examining the complex relationships of activities, built environment factors, demographic and socioeconomic characteristics, attitudes and perceptions, and habit and exploration on individual short-term travel decisions (with considerations of the influence of medium- and long-term travel-related decisions). A key component of the theory is a hierarchy of travel needs hypothesized to be considered by travelers in the course of their decision-making processes. Although developed to account for the factors that particularly influence decisions surrounding walking and bicycling, the framework is postulated to apply to all travel modes and decisions, including frequency, destination, mode, time-of-day, and route. The first section of the thesis reviews theories from the fields of economics, geography, psychology, and travel behavior that have a large influence on the development of the theory of travel decision-making. In the next and largest chapter, the components and relationships in this theory, including the hierarchy of travel needs, are defined and presented with supporting empirical evidence from travel behavior research. This thesis's final section views the theory of travel decision-making through the lens of applicability to travel demand modeling and forecasting. The state of current travel forecasting tools, travel behavior research, data, and analysis methods with respect to each aspect of the theory is reviewed. Research and data needs are identified. In closing, some opportunities for operationalizing the theory in travel demand models and using these transportation planning tools for analyzing walking, cycling, and other policies are hypothesized and discussed. This thesis, and the theory and applications discussed within, contribute to the academic study of travel behavior, the practical modeling of travel demand, and walking and bicycling research and planning.

Smart growth policies have often emphasized the importance of land use mix as an intervention beholding of lasting urban planning and public health benefits. Past transportation-land use research has identified potential efficiency gains achieved by mixed-use neighborhoods and the subsequent shortening of trip lengths; whereas, public health research has accredited increased land use mixing as an effective policy for facilitating greater physical activity. However, despite the celebrated transportation, land use, and health benefits of improved land use mixing and the extent of topical attention, no consensus has been reached regarding the conceptualization and measurement of this key smart growth principle or the magnitude of its link to walking. This dissertation, comprised of three empirical studies, explores this topic in detail. In the first study, activity-based transportation and landscape ecology theory contributed to the introduction of a multifaceted land use mix construct reflected by a set of composition and configuration indicators. This activity-related land use mix construct, and not the commonly used entropy index, was a significant built environmental determinant of walk mode choice and home-based walk trip frequency. In the second study, structural equation modeling was used to establish a connection between residing in a smart growth neighborhood and home-based pedestrian travel. This study discovered a multidimensional depiction of the traveler's residential environment that was reflective of local land use mix, employment concentration, and pedestrian-oriented design. The second-order factor, which described a smart growth neighborhood, had a strong and positive effect on the household-level decision to walk for transportation-related and discretionary travel when assessed in a multidirectional conceptual framework. In the final study, the influence of geographic scale selection on the connection between the built environment and active and auto-related travel was explored. Informed by this sensitivity analysis, which underlined the existence of scaling and zoning effects, mode choice for both work and nonwork travel as a function of individual, household, transportation, and built environment features at the home location and destination was modeled. These discrete choice analysis results found that measures of land use mix and density at each trip end had the strongest effect on the decision to walk rather drive or ride in a vehicle for nonwork trips. In all, the findings from this dissertation provide policymakers and practitioners greater specificity in the measurement of land use mix and its connection to pedestrian travel behavior.

In recent years research and planning efforts to enhance the conditions and opportunities for active transportation modes have increased significantly; however, these efforts have primarily focused on pedestrians and bicyclists. Skateboarding and other alternative modes of mobility remain an untapped potential for healthy and sustainable travel. This research addresses numerous knowledge gaps in the literature on utilitarian skateboarding under the larger umbrella of active transportation. Analysis of online survey results and semi-structured interviews with skateboarders in Portland, OR provides insight into the motivations and barriers of traveling by skateboard and the demographics and perceptions of skateboard commuters. Like bicyclists and pedestrians, skateboarders value safe, comfortable, and aesthetically pleasing places to travel and are sensitive to surface conditions, distance, and slope. These similarities present a unique opportunity for cities to create facilities that accommodate diverse users. Disaggregating results by the respondents' gender, skill level, and frequency of transportation-oriented skateboarding highlights significant differences in levels of perceived safety and the practicality of utilitarian skateboarding. The findings have implications for the future of active transportation planning which support Elaine Stratford's vision of "generous geographies that allow for more, and playful, mobilities in the city."

Pedestrians and bicyclists are the most vulnerable road users and suffer the most severe consequences when crashes take place. An extensive literature is available for crash severity in terms of driver safety, but fewer studies have explored non-motorized users' crash severity. Furthermore, most research efforts have examined pedestrian and bicyclist crash severity in urban areas. This study focuses on state roads (mostly outside major urban areas) and aims to identify contributing risk factors of fatal and severe crashes involving pedestrians and bicyclists in state roads. Two ordinal regression models were developed (one for pedestrian and the other for bicyclist crashes) to examine crash severity risk factors. Additional models were developed to investigate road and traffic characteristics that could increase the likelihood of fatal crashes. In the model for pedestrian crash severity risk factors such as age, vehicle type and movement, light conditions, road classification, traffic control device, posted speed limit, location of the pedestrian and wet road surface during clear weather conditions are statistically significant. The bicyclist crash severity model indicates that age, crash location, vehicle movement and alcohol intoxication during dark conditions are statistically significant. In terms of road characteristics and traffic conditions, the models suggested risk factors such as arterials, light conditions, posted speed limit, roadways, and high heavy vehicle volume, increased the odds of a crash being fatal. The results seem to suggest that besides improvements in roadway characteristics, additional countermeasures to reduce crash severity for vulnerable users should include separation of vulnerable users from traffic, educational campaigns, more strict control of alcohol intoxicated drivers, and protection strategies of senior pedestrians.

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