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The need to reduce congestion, enhance safety, and make the U.S. transportation system and cities more sustainable has given rise to various programs, technologies, and policies. The effectiveness of these interventions depends on how users eventually respond and, in some instances, modify their travel behavior. While significant advances have taken place over the past 50 years in the field of travel behavior research and travel demand forecasting, the ability to reliably predict the direction and magnitude of behavioral responses to various network and non-network factors and interventions remains limited. Many experts have called for better data collection and analysis methods and better integration of behavior models with supply analysis tools. This report provides a synthesis of the state of knowledge in travel behavior research and showcases how to improve current models with relevant behavior realism through six case studies. These case studies range from long-term policy interventions (e.g., urban design policy affecting land use and neighborhood walkability), to short-term en-route interventions (e.g., traveler information systems for weather-responsive system management). The case studies also include interventions aimed at environmental as well as congestion avoidance objectives. The applications provide an enhanced capability to capture traveler choices in both the main evaluation tools as well as in supporting the design process actively. This multifaceted research initiative cuts across several Federal Highway Administration (FHWA) programs such as the Office of Planning, Environment, and Realty; Office of Operations; Office of Safety; and Office of Research, Development, and Technology. This study will facilitate implementation of a balanced, cross-cutting effort to better understand the topic of traveler choice, and builds on current activities related to modeling and analysis across FHWA, professional associations, and academia.