Abstract: Meeting truck parking demand along high-volume freight corridors requires accurate demand estimation and strategic infrastructure planning. This study applies the FHWA truck parking demand model to estimate peak-hour parking needs by driver class through traffic exposure and behavioral parameters across North Carolina and Florida. In North Carolina, candidate facility locations are evaluated under mixed-integer linear programming with lexicographic optimization across capacity-based and fixed-cost investment models. A choice-based competitive framework, where drivers select facilities through utility maximization, is explored as a direction toward behaviorally realistic solutions. Reservation-based operations comparing static, myopic-reactive, and first-come-first-served policies show structured systems substantially outperforming reactive approaches. In Florida, the model is calibrated against observed utilization data, confirming transferability across regional contexts. Future work advances reservation-based dynamic programming for North Carolina and extends spatial site selection, safety, economic, and environmental analyses to Florida freight corridors.