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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations

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Publication Number:  FHWA-HRT-13-022    Date:  August 2013
Publication Number: FHWA-HRT-13-022
Date: August 2013


Synthesis of Traveler Choice Research: Improving Modeling Accuracy for Better Transportation Decisionmaking

Objectives, Motivation, and Structure

The goal of this report is to organize the existing knowledge, the state of the art, and the current state of practice for transport modeling into a framework to give an overview of travel behavior research with particular relevance to traveler choice dimensions impacted through programs such as Active Transportation and Demand Management (ATDM), Managing Travel Demand (MTD), and Integrated Corridor Management (ICM), including weather-related dynamic system management. Because these programs entail a significant real-time operational element, choice models should enable understanding of users’ dynamic responses to information-rich environments and the interdependencies of users’ decisions over time. Some impacts of interventions applied as part of ATDM, MTD, and ICM projects are short-term, such as adjustments to a less congested route or departure time. Others appear over the long term, such as gradually shifting users’ behavior toward more environmentally friendly or reliable trajectories with feedback information. Also of interest are the effects of non-network factors on users’ decisions and responses to operational interventions, especially in terms of peak demand reduction and carbon-conscious behaviors.

Operational interventions offer substantial opportunity to optimize transportation networks, and they represent significant investment by agencies and contractors. Understanding user response at the facility, corridor, and network levels over short-, medium-, and long-term horizons is crucial to designing appropriate interventions. Without comprehensive knowledge of systems and user response, policies such as tolling and ramp metering may not lead to expected improvements or could cause externalities elsewhere in the network. The effects are complex, and such complexity demands a comprehensive look at how traveler behavior is studied and modeled. Adding to the complexity, geographic and human heterogeneity mean shared results and insights may not lead to similar outcomes in different locations. A comprehensive and easily transferable framework could overcome these issues to determine the structural causes and mechanisms of travel behavior.

This report is structured into five sections. First, a conceptual organizing framework is established and discussed. The framework links operational interventions associated with dynamic demand and traffic management programs, including information dissemination, to corresponding traveler choice dimensions and to network and non-network factors affecting user response.

Second, a literature review is presented, mainly covering relevant knowledge along the established conceptual framework. The review is composed of a general knowledge section, a discussion of models to capture travel behavior, and an overview of available relevant data sources. The review addresses the question: “What do researchers know about traveler behavior?”

Third, travel behavior models are examined. Modelers must be careful, asking the appropriate questions and recognizing effects that are observed only through the modeling process. This section discusses the strengths and limitations of the variety of models available, pointing to areas of potential improvement. Improved model integration is needed to understand feedback loops and ensure model consistency.

Fourth, traveler behavior data sources are briefly reviewed. This section asks what data are needed based on existing and potential knowledge and modeling practices in travel behavior as well as how relevant and important behaviors can be measured.

Finally, a summary is provided, examining conclusions about the current knowledge and opportunities to develop and advance traveler choice models, particularly in connection with
the motivating applications.



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