Advisor

Kelly J. Clifton

Date of Award

Fall 12-4-2013

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Civil & Environmental Engineering

Department

Civil and Environmental Engineering

Physical Description

1 online resource (viii, 245 pages)

Subjects

Choice of transportation -- Decision making, Commuting -- Forecasting, Walking -- Forecasting, Cycling -- Forecasting, Urban transportation -- Planning

DOI

10.15760/etd.1493

Abstract

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.

Persistent Identifier

http://archives.pdx.edu/ds/psu/10370

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