While bicycling is an essential mode of urban transportation, most parts of U.S. cities lack adequate infrastructure to keep bicyclists safe and allow them to travel efficiently. This research aims to model how psychological, street, and infrastructure characteristics influence bicyclist behavior in urban settings with inadequate bicycling infrastructure, such as in the Greater Houston area (Houston-The Woodlands-Sugar Land), Texas. This research will integrate quantitative and qualitative methods to develop a model that supports adaptive decision-making for bicycling in urban areas with limited infrastructure. The project will recruit 40 adult bicyclists to participate in surveys and bicycle simulator testing. A realistic urban network will be simulated in the bicycle simulator to replicate bicycling conditions under varying (infrastructure quality, traffic volume, visibility, etc.), psychological (risk perception, motivation, and attitudes, etc.), and operational (route choice, adaptation, and interaction with other modes of transportation, etc.) scenarios. Various techniques, including both qualitative and quantitative methods, can be used to identify key drivers of route choice and to develop optimal strategies for efficiency and safety. The findings will inform action-oriented urban planning and policy recommendations for enhancing bicycle infrastructure and safety. The outcomes have the potential to offer a replicable methodology for implementation in similarly challenged cities, providing active urban transportation and improved public health.