With the increasing size of ships and increasing demand for autonomous navigation, ensuring ship safety is not the only concern; the efficiency of anti-collision technology should be enhanced. In this paper, we propose a novel hybrid anti-collision path planning method called VO-PATH. This method combines the advantages of the Velocity Obstacle (VO) algorithm, which guarantees anti-collision for autonomous ships, with the A* algorithm, which is known for its capacity to optimize paths. To assess the effectiveness of the proposed method, we conducted anti-collision simulations for both single- and multiple-encounter scenarios, all of which adhered to COLREGs-defined avoidance obligations. Furthermore, we evaluated the performance of the proposed method by comparing its results with those obtained using conventional VO and A* algorithms. The findings indicate that the proposed method is superior to the A* algorithm in terms of steering away from collisions in complex multiple-encounter scenarios. Additionally, the proposed method significantly reduces the distance traveled by the ship to avoid potential collisions, with improvements of up to approximately 6.6% compared with alternative algorithms. We expect that this reduction will enhance safety and provide a more efficient anti-collision path.

中文翻译：

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海上自主水面舰艇速度障碍与A*算法防碰撞路径规划方法

随着船舶规模的不断增大和自主航行需求的不断增加，确保船舶安全不再是唯一的问题；应提高防碰撞技术的效率。在本文中，我们提出了一种新颖的混合防碰撞路径规划方法，称为 VO-PATH。该方法结合了保证自主船舶防碰撞的速度障碍（VO）算法和以其优化路径能力而闻名的A*算法的优点。为了评估所提出方法的有效性，我们对单次和多次遭遇场景进行了防碰撞模拟，所有这些都遵守 COLREG 定义的回避义务。此外，我们通过将其结果与使用传统 VO 和 A* 算法获得的结果进行比较来评估该方法的性能。研究结果表明，在复杂的多次遭遇场景中避免碰撞方面，所提出的方法优于 A* 算法。此外，所提出的方法显着减少了船舶行驶的距离，以避免潜在的碰撞，与替代算法相比，改进幅度高达约 6.6%。我们预计这种减少将提高安全性并提供更有效的防碰撞路径。