基于改进DP算法的船舶轨迹自适应压缩方法  

An Adaptive Compression Method of Ship Trajectory Based on Improved DP Algorithm

作　　者：舒田伦 刘奕[1,2] 刘敬贤[1,2] 张贵平[3] 周备 SHU Tianlun;LIU Yi;LIU Jingxian;ZHANG Guiping;ZHOU Bei(School of Navigation,Wuhan University of Technology,Wuhan 430063,China;Hubei Inland Shipping Technology Key Laboratory,Wuhan 430063,China;Jiangsu Maritime Safety Administration,Nanjing 210009,China;School of Transportation Engineering,Chang’an University,Chang’an 710064,China)

机构地区：[1]武汉理工大学航运学院,武汉430063 [2]武汉理工大学内河航运技术湖北省重点实验室,武汉430063 [3]江苏海事局,长安710064 [4]长安大学运输工程学院,南京210009

出　　处：《武汉理工大学学报（交通科学与工程版）》2024年第5期1005-1010,共6页Journal of Wuhan University of Technology（Transportation Science & Engineering）

基　　金：国家自然科学基金(51709219)。

摘　　要：文中通过结合滑动窗算法.考虑船舶轨迹几何特性与船舶转向角动态因素,自适应分割船舶轨迹中的弯曲段与直线段部分,并自适应选取各自对应的压缩阈值.实现对轨迹数据的压缩.在保留更多重要特征点的前提下,提高了轨迹压缩率.利用尹公洲水域的船舶轨迹数据,通过对比改进压缩方法与传统方法,验证了文中方法能够在保留较多轨迹特征点的前提下,对轨迹数据进行大幅度压缩.By combining the sliding window algorithm and considering the geometric characteristics of ship trajectory and the dynamic factors of ship steering angle,the curved section and straight section of ship trajectory were adaptively segmented,and their corresponding compression thresholds were adaptively selected to realize the compression of trajectory data.On the premise of retaining more important feature points,the trajectory compression rate was improved.By comparing the improved compression method with the traditional method,it is verified that the proposed method can greatly compress the trajectory data on the premise of retaining more trajectory feature points.

关 键 词：船舶交通 船舶轨迹 AIS 自适应 轨迹压缩 

分 类 号：U675.7[交通运输工程—船舶及航道工程]