基于改进DBSCAN的船舶会遇识别模型

为解决大数据下船舶会遇识别算法效率不高且存在误判等问题,提出一种融合国际海上避碰规则(International Regulations for Preventing Collisions at Sea,COLREGs)的带噪声的基于密度的空间聚类(density-based spatial clustering of applications with noise,DBSCAN)算法,建立船舶会遇识别模型。在DBSCAN算法对邻域内的船舶数量进行统计时,计算船舶间的最近会遇距离(distance to closest point of approach,DCPA)和最近会遇时间(time to closest point of approach,TCPA),初步筛选邻域内的噪声点;基于模糊综合评价模型计算船舶会遇风险,对邻域内的船舶进行二次筛选,实现船舶会遇态势的提取。结果表明:改进后的DBSCAN算法过滤掉传统DBSCAN算法识别到的非会遇局面,并且在同一会遇局面下的船舶数量均保持在4艘以内;输出的会遇船舶风险演变趋势对实际水域内高风险船舶的监控适用性较好,能有效辅助船舶避碰。所提识别模型对保障航行安全和提高海事监管效率具有重要意义。

Collision-avoidance path planning for multi-ship encounters considering ship manoeuvrability and COLREGs

Ship collision prevention has always been a hot topic of research for navigation safety.Recently,autonomous ships have gained much attention as a means of solving collision problems by machine control with a collision-avoidance algorithm.An important question is how to determine optimal path planning for autonomous ships.This paper proposes a path-planning method of collision avoidance for multi-ship encounters that is easy to realize for autonomous ships.The ship course-control system uses fuzzy adaptive proportion-integral-derivative(PID)control to achieve real-time control of the system.The automatic course-altering process of the ship is predicted by combining the ship-motion model and PID controller.According to the COLREGs,ships should take different actions in different encounter situations.Therefore,a scene-identification model is established to identify these situations.To avoid all the TSs,the applicable course-altering range of the OS is obtained by using the improved velocity obstacle model.The optimal path of collision avoidance can be determined from an applicable course-altering range combined with a scene-identification model.Then,the path planning of collision avoidance is realized in the multi-ship environment,and the simulation results show a good effect.The method conforms to navigation practice and provides an effective method for the study of collision avoidance.

基于改进动态窗口法的无人水面艇自主避碰算法

为研究避碰规则、无人水面艇(unmanned surface vessel,USV)运动学特点和海上交通复杂度等因素约束下的USV自主避碰技术,在分析初始动态窗口法的基础上,考虑《国际海上避碰规则》(International Regulations for Preventing Collisions at Sea,COLREGs)关于避碰行动时机、避让幅度、复航时机等方面的要求,建立融合避碰规则的动态窗口模型,设计融合避碰规则的动态窗口法。通过对比仿真实验验证该方法的可行性和有效性,具有一定的现实意义。

复杂水域慎思型避碰轨迹规划

为解决复杂水域的船舶自主避碰问题,提出一种基于A*算法的慎思型避碰轨迹规划算法,旨在满足船舶操纵性约束、静态与动态障碍物约束和《国际海上避碰规则》(International Regulations for Preventing Collisions at Sea,COLREGs)约束下,规划出一条最经济的航行轨迹。通过无人三体船自主避碰试验和模拟试验,验证算法的有效性,具有较高的参考价值。

水面无人艇多船障碍智能避碰

为尽可能在无人艇避碰规划时兼顾《国际海上避碰规则公约》,提出对障碍船进行符合《公约》的偏心膨胀,对偏心膨胀建立统一的运动模型.为实现宽阔水域的水面无人艇多船障碍智能避碰,提出基于避障紧迫程度、安全性预测以及调整可行性的模糊规划方法.对同时具有对遇、交叉及追越情况的多个复杂运动障碍进行避碰规划仿真,结果证明了该方法的智能性.

多船会遇自主避碰算法

船舶自主避碰技术已成为当前船舶与航运领域研究的热点问题。文章提出了一种满足COLREGs避碰规则的多船会遇自主避碰算法,以经典速度障碍法为基础设计自适应采样避碰轨迹生成算法,并应用运动基元理论对避碰轨迹进行调整,使轨迹满足船舶操纵性约束条件。针对案例三体船模型,完成多船会遇场景下的船模自主避碰航行试验,验证了所提算法的有效性和实用性,对船舶自主避碰系统的研发具有重要借鉴意义。