The Research on Collision Avoidance Algorithm of Autonomous Surface Vessel using Vector Field Histogram and Velocity Obstacle Method

In the maritime industry, various research is underway to address issues such as labor shortages and increasing labor costs by developing unmanned operating systems. The Navy is also showing interest in unmanned systems to cope with manpower reduction and ensure the safety of crew members. This paper aims to develop collision avoidance algorithms, a key technology in autonomous navigation systems for unmanned surface vehicles. The collision avoidance algorithm should be able to avoid both static and dynamic obstacles that may be encountered during navigation, even in situations where sensor use is limited. To develop such an algorithm, ACDIS extraction data and AIS data were utilized, and a collision avoidance algorithm was developed by integrating the Vector Field Histogram (VFH) and Velocity Obstacle method (VO). To validate the proposed algorithm, a simulation environment was created using the MMG mathematical model, and through simulations, it was confirmed that collision avoidance is possible even in situations where static obstacles, dynamic obstacles, and both types of obstacles are encountered simultaneously.