Unmanned surface vehicles (USVs) scheduling method by a bi-level mission planning and path control

To enhance the operational efficiency of container terminals, we propose a bi-level scheduling method that employs unmanned surface vehicles (USVs) to transport containers exclusively between different berths on the waterside of terminals. In the upper level, Considering time windows, berth coordination, energy replenishment, etc., we formulate the mission decision model to obtain a cost-effective USVs shipping solution by minimizing unplanned delay and total execution cost. In the lower level, considering path distance, path smoothness, and motion constraints, we develop the USV path control model to achieve the USV path planning and reduce path tracking errors. Finally, we integrate the advantages of the chaotic Electron Search and multi-population Genetic Algorithm (ES-mGA) to solve the bi-level USVs scheduling model. Experimental results demonstrate the effectiveness of our approach and algorithm in guiding the USVs to efficiently accomplish container transshipment and acquire stable USV sailing states.

Automated summary

This study proposes a bi-level scheduling method that utilizes unmanned surface vehicles for container transportation. By formulating mission decision and path control models, efficient container transshipment and path planning are achieved. Experimental results demonstrate the effectiveness of the proposed approach in guiding unmanned surface vehicles to complete container transshipment tasks.