Offshore Unmanned Fleet Collaborative Cruise Control Instruction Document Dataset

Currently, the maritime logistics industry faces challenges such as inefficiency and lack of safety, especially in offshore environments where traditional manual control and monitoring methods cannot meet the growing demand for transportation. Existing solutions often rely on experienced personnel for manual control, resulting in high labor costs and inflexibility. This dataset aims to address the problem of instruction generation and optimization in collaborative cruise control of unmanned fleets, meeting the needs for rapid and precise transportation scheduling. The data is collected in document form, mainly gathered from the voyage logs of unmanned fleets and command center instruction records, using specialized maritime equipment in a real navigational environment. Quality control includes multi-round instruction review and consistency comparison, and is annotated and reviewed by a team of shipping experts. The annotation team consists of professionals with a maritime background, and is composed of 10 members. The data undergoes preprocessing procedures including cleaning, format conversion, and deduplication, and is finally stored in TXT format and organized by voyage segment and date.