Unmanned Surface Vehicles (USVs) offer considerable advantages across various maritime applications. However, unlike manned vessels that benefit from the experience and decision making skills of mariners, USVs rely entirely on automated systems for navigation, making effective and safe voyage route planning essential for long-distance operations. This paper introduces a hybrid framework to enhance automated voyage route generation using Automatic Identification System (AIS) data, which provides extensive vessel trajectory information. By integrating pattern-based and region-based route discovery techniques, the framework generates optimized routes that capture navigational behaviors and traffic patterns while addressing the spatial discontinuities and data variability issues inherent in AIS data. Through a comprehensive case demonstration, we illustrate the effectiveness of the proposed approach in generating optimal voyage routes for USVs. The results highlight the framework’s potential to enhance the navigational capabilities of USVs, ensuring both safety and efficiency in maritime environments.