船舶AIS轨迹聚类方法研究进展综述
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摘要
围绕船舶聚类算法这一关键问题,在对国内外相关文献进行系统研究的基础上,归纳了船舶轨迹聚类的方法,评述了各聚类方法在船舶轨迹聚类上应用的优点和不足,讨论了船舶轨迹聚类在数据属性多和可视化大等方面临的挑战和未来的发展趋势.
Based on systematic study for relevant articles of both home and abroad,the key problem of clusting algorithm is disscussed and summarized,thd advantage and disadvantages of each clustering method in ship track clustering are review the challenges and future development trend of ship track clustering in data attribute and visualization are discussed. This Essay focused on the core of clustering algorithms.
Based on systematic study for relevant articles of both home and abroad,the key problem of clusting algorithm is disscussed and summarized,thd advantage and disadvantages of each clustering method in ship track clustering are review the challenges and future development trend of ship track clustering in data attribute and visualization are discussed. This Essay focused on the core of clustering algorithms.
引文
[1] KIM J,MAHMASSANI H S.Spatial and Temporal Characterization of Travel Patterns in a Traffic Network Using Vehicle Trajectories[J].Transportation Research Part C Emerging Technologies,2015,9:164-184.
[2] 任建强,陈阳舟,辛乐,等.基于时空轨迹跟踪的交通流特性参数检测分析[J].交通运输系统工程与信息,2015,15(1):62-68.
[3] 韩莹,芮小平,程晓,等.基于时空轨迹法的近10年间北极地区海冰的时空变化[J].中国科学院大学学报,2015,32(6):743-750.
[4] 龚玺,裴韬,孙嘉,等.时空轨迹聚类方法研究进展[J].地理科学进展,2011,30(5):522-534.
[5] HAN J,PEI J,Kamber M.Data mining:concepts and techniques[M].Elsevier,2011.
[6] 吉根林,赵斌.时空轨迹大数据模式挖掘研究进展[J].数据采集与处理,2015,30(1):47-58.
[7] 廖律超,蒋新华,邹复民,等.一种支持轨迹大数据潜在语义相关性挖掘的谱聚类方法[J].电子学报,2015,43(5):956-964.
[8] HUTTENLOCHER D P,KLANDERMAN G A,et al.Comparing images using the Hausdorff distance[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1993,15(9):850-863.
[9] 魏龙翔,何小海,滕奇志,等.结合Hausdorff距离和最长公共子序列的轨迹分类[J].电子与信息学报,2013,35(4):784-790.
[10] ZHENG B,CHEN J B,XIA S H,et al.Data Analysis of Vessel Traffic Flow Using Clustering Algorithms[C]//Proc of the Int Conf.on Intelligent Computation Technology and Automation,Hunan,2008:243-246.
[11] 陈兴蜀,吴小松,王文贤,等.基于特征关联度的K-means初始聚类中心优化算法[J].四川大学学报:工程科学版,2015,47(1):13-19.
[12] VRIES G D,SOMEREN M V..Unsupervised Ship Trajectory Modeling and Prediction Using Compression and Clustering.[C]//Proceedings of the 18th Annual Belgian-Dutch Conference on Machine Learning,2009:7-12.
[13] 马文耀,吴兆麟,杨家轩,等.基于单向距离的谱聚类船舶运动模式辨识[J].重庆交通大学学报(自然科学版),2015,34(5):130-134.
[14] 袁冠,夏士雄,张磊,等.基于结构相似度的轨迹聚类算法[J].通信学报,2011,32(9):103-110.
[15] 刘坤,杨杰.基于编辑距离的轨迹相似性度量[J].上海交通大学学报,2009,43(11):1725-1729.
[16] ESTER M,KRIEGEL H P,SANDER J,et al.A density-based algorithm for discovering clusters in large spatial databases with noise[C]//KDD.1996,96(34):226-231.
[17] YING Y S,SHWU J C.Spatial Cluster Detection for the Fishing Vessel Monitoring Systems [C]//OCEANS′08 MTS/IEEE KOBE-TECHNO,KOBE,2008:1-4.
[18] 刘涛,胡勤友,杨春.水上交通拥挤区域的聚类分析与识别[J].中国航海,2010,33(4):75-78.
[19] PALLOTTA G,VESPE M,BRYAN K.Vessel pattern knowledge discovery from AIS data:a frame work for anomaly detection and route prediction[J].Entropy,2013,15(6):2218-2245.
[20] PALLOTTA,G.;VESPE,M.BRYAN,K.Traffic Route Extraction and Anomaly Detection (TREAD):Vessel Pattern Knowledge Discovery and Exploitation for Maritime Situational Awareness;NATO Formal Report CMRE-FR-2013-001,NATO Unclassified;NATO:Brussels,Belgium,2013.
[21] PALLOTTA G,VESPE M,BRYAN K.Traffic knowledge discovery from AIS data[C]//International Conference on Information Fusion.2013:1996-2003.
[22] LIU B,DE SOUZA E N,MATWIN S,et al.Knowledge-based clustering of ship trajectories using density-based approach[C]//IEEE International Conference on Big Data.2014:603-608.
[23] 周水庚,周傲英.基于数据分区的DBSCAN 算法[J].计算机研究与发展,2000,37(10):1153-1159.
[24] WEN Y T,LAI C H,LEI P R,et al.RouteMiner:Mining Ship Routes from a Massive Maritime Trajectories[C]//IEEE,International Conference on Mobile Data Management.IEEE,2014:353-356.
[25] PEI J,HAN J,MORTAZAVI-ASL B,et al.Mining sequential patterns by pattern-growth:the PrefixSpan approach[J].IEEE Transactions on Knowledge & Data Engineering,2004,16(11):1424-1440.
[26] PEEL D,GOOD N M.A hidden Markov model approach for determining vessel activity from vessel monitoring system data[J].Canadian Journal of Fisheries and Aquatic Sciences,2011,68(7):1252-1264.
[27] LAXHAMMAR R.Artificial intelligence for situation assessment[M].Numerisk analys och datalogi,Kungliga Tekniska h?gskolan,2007.
[28] RIVEIRO M J.Visual analytics for maritime anomaly detection[D].Sweden:University of Sk?vde,2011.
[29] KRAIMAN J B,AROUH S L,WEBB M L.Automated anomaly detection processor[C]//AeroSense 2002 International Society for Optics and Photonics,2002:128-137.
[30] LAXHAMMAR R,FALKMAN G,SVIESTINS E.Anomaly detection in sea traffic-a comparison of the gaussian mixture model and the kernel density estimator[C]//Information Fusion,2009.FUSION′09.12th International Conference on.IEEE,2009:756-763.
[31] RIVEIRO M,FALKMAN G.Interactive visualization of normal behavioral models and expert rules for maritime anomaly detection[C]//Computer Graphics,Imaging and Visualization,2009.CGIV′09.Sixth International Conference on.IEEE,2009:459-466.
[32] 陈金海,陆锋,彭国均.海洋运输船舶轨迹分析研究进展[J].中国航海,2012,35(3):53-57.
[33] 李存华,孙志挥,陈耿,等.核密度估计及其在聚类算法构造中的应用[J].计算机研究与发展,2004,41(10):1712-1719.
[34] RISTIC B,LA SCALA B,MORELANDE M,et al.Statistical analysis of motion patterns in AIS data:Anomaly detection and motion prediction[C]//information fusion,2008 11th international conference on.IEEE,2008:1-7.
[35] LAXHAMMAR R,FALKMAN G,SVIESTINS E.Anomaly detection in sea traffic-a comparison of the gaussian mixture model and the kernel density estimator[C]//Information Fusion,2009.FUSION′09.12th International Conference on.IEEE,2009:756-763.
[36] LAMPE O D,KEHRER J,HAUSER H.Visual Analysis of Multivariate Movement Data using Interactive Difference Views[C]//VMV.2010:315-322.
[37] CHEN J H,LU F,PENG G J.A quantitative approach for delineating principal fairways of ship passages through a strait[J].Ocean Engineering,2015,103:188-197.
[38] 陈金海,陆锋,李明晓.海上主航迹带边界统计推断与海西航路警戒区布局优化分析[J].地球信息科学学报,2015,17(10):1196-1206.
[39] 杜磊,文元桥,肖长诗,等.自由航行海域船舶碰撞概率计算[J].中国安全科学学报,2015,25(1):53-59.
[40] GONZALEZ J,BATTISTELLO G,SCHMIEGELT P,et al.Semi-automatic extraction of ship lanes and movement corridors from AIS data[C]//2014 IEEE Geoscience and Remote Sensing Symposium.IEEE,2014:1847-1850.
[41] ETIENNE L,DEVOGELE T,BOUJU A.Spatio-temporal trajectory analysis of mobile objects following the same itinerary[J].Advances in Geo-Spatial Information Science,2012,10:47-57.
[42] ROCHA J A M R,TIMES V C,OLIVEIRA G,et al.DB-SMoT:A direction-based spatio-temporal clustering method[C]//2010 5th IEEE International Conference Intelligent Systems.IEEE,2010:114-119.
[43] KROODSMA D A,Mayorga J,Hochberg T,et al.Tracking the global footprint of fisheries[J].Science,2018,359(6378):904-908.
[44] OSEKOWSKA E,Carlsson B.Learning Maritime Traffic Rules Using Potential Fields[C]//International Conference on Computational Logistics.Springer International Publishing,2015:298-312.
[45] OSEKOWSKA E,Axelsson S,Carlsson B.Potential Fields in Modeling Transport over Water[M].Springer International Publishing,2015:259-280.
[46] OSEKOWSKA E,Johnson H,Carlsson B.Grid size optimization for potential field based maritime anomaly detection[C]//17th Meeting of the EURO Working Group on Transportation.Spain,2014:720-729.
[2] 任建强,陈阳舟,辛乐,等.基于时空轨迹跟踪的交通流特性参数检测分析[J].交通运输系统工程与信息,2015,15(1):62-68.
[3] 韩莹,芮小平,程晓,等.基于时空轨迹法的近10年间北极地区海冰的时空变化[J].中国科学院大学学报,2015,32(6):743-750.
[4] 龚玺,裴韬,孙嘉,等.时空轨迹聚类方法研究进展[J].地理科学进展,2011,30(5):522-534.
[5] HAN J,PEI J,Kamber M.Data mining:concepts and techniques[M].Elsevier,2011.
[6] 吉根林,赵斌.时空轨迹大数据模式挖掘研究进展[J].数据采集与处理,2015,30(1):47-58.
[7] 廖律超,蒋新华,邹复民,等.一种支持轨迹大数据潜在语义相关性挖掘的谱聚类方法[J].电子学报,2015,43(5):956-964.
[8] HUTTENLOCHER D P,KLANDERMAN G A,et al.Comparing images using the Hausdorff distance[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1993,15(9):850-863.
[9] 魏龙翔,何小海,滕奇志,等.结合Hausdorff距离和最长公共子序列的轨迹分类[J].电子与信息学报,2013,35(4):784-790.
[10] ZHENG B,CHEN J B,XIA S H,et al.Data Analysis of Vessel Traffic Flow Using Clustering Algorithms[C]//Proc of the Int Conf.on Intelligent Computation Technology and Automation,Hunan,2008:243-246.
[11] 陈兴蜀,吴小松,王文贤,等.基于特征关联度的K-means初始聚类中心优化算法[J].四川大学学报:工程科学版,2015,47(1):13-19.
[12] VRIES G D,SOMEREN M V..Unsupervised Ship Trajectory Modeling and Prediction Using Compression and Clustering.[C]//Proceedings of the 18th Annual Belgian-Dutch Conference on Machine Learning,2009:7-12.
[13] 马文耀,吴兆麟,杨家轩,等.基于单向距离的谱聚类船舶运动模式辨识[J].重庆交通大学学报(自然科学版),2015,34(5):130-134.
[14] 袁冠,夏士雄,张磊,等.基于结构相似度的轨迹聚类算法[J].通信学报,2011,32(9):103-110.
[15] 刘坤,杨杰.基于编辑距离的轨迹相似性度量[J].上海交通大学学报,2009,43(11):1725-1729.
[16] ESTER M,KRIEGEL H P,SANDER J,et al.A density-based algorithm for discovering clusters in large spatial databases with noise[C]//KDD.1996,96(34):226-231.
[17] YING Y S,SHWU J C.Spatial Cluster Detection for the Fishing Vessel Monitoring Systems [C]//OCEANS′08 MTS/IEEE KOBE-TECHNO,KOBE,2008:1-4.
[18] 刘涛,胡勤友,杨春.水上交通拥挤区域的聚类分析与识别[J].中国航海,2010,33(4):75-78.
[19] PALLOTTA G,VESPE M,BRYAN K.Vessel pattern knowledge discovery from AIS data:a frame work for anomaly detection and route prediction[J].Entropy,2013,15(6):2218-2245.
[20] PALLOTTA,G.;VESPE,M.BRYAN,K.Traffic Route Extraction and Anomaly Detection (TREAD):Vessel Pattern Knowledge Discovery and Exploitation for Maritime Situational Awareness;NATO Formal Report CMRE-FR-2013-001,NATO Unclassified;NATO:Brussels,Belgium,2013.
[21] PALLOTTA G,VESPE M,BRYAN K.Traffic knowledge discovery from AIS data[C]//International Conference on Information Fusion.2013:1996-2003.
[22] LIU B,DE SOUZA E N,MATWIN S,et al.Knowledge-based clustering of ship trajectories using density-based approach[C]//IEEE International Conference on Big Data.2014:603-608.
[23] 周水庚,周傲英.基于数据分区的DBSCAN 算法[J].计算机研究与发展,2000,37(10):1153-1159.
[24] WEN Y T,LAI C H,LEI P R,et al.RouteMiner:Mining Ship Routes from a Massive Maritime Trajectories[C]//IEEE,International Conference on Mobile Data Management.IEEE,2014:353-356.
[25] PEI J,HAN J,MORTAZAVI-ASL B,et al.Mining sequential patterns by pattern-growth:the PrefixSpan approach[J].IEEE Transactions on Knowledge & Data Engineering,2004,16(11):1424-1440.
[26] PEEL D,GOOD N M.A hidden Markov model approach for determining vessel activity from vessel monitoring system data[J].Canadian Journal of Fisheries and Aquatic Sciences,2011,68(7):1252-1264.
[27] LAXHAMMAR R.Artificial intelligence for situation assessment[M].Numerisk analys och datalogi,Kungliga Tekniska h?gskolan,2007.
[28] RIVEIRO M J.Visual analytics for maritime anomaly detection[D].Sweden:University of Sk?vde,2011.
[29] KRAIMAN J B,AROUH S L,WEBB M L.Automated anomaly detection processor[C]//AeroSense 2002 International Society for Optics and Photonics,2002:128-137.
[30] LAXHAMMAR R,FALKMAN G,SVIESTINS E.Anomaly detection in sea traffic-a comparison of the gaussian mixture model and the kernel density estimator[C]//Information Fusion,2009.FUSION′09.12th International Conference on.IEEE,2009:756-763.
[31] RIVEIRO M,FALKMAN G.Interactive visualization of normal behavioral models and expert rules for maritime anomaly detection[C]//Computer Graphics,Imaging and Visualization,2009.CGIV′09.Sixth International Conference on.IEEE,2009:459-466.
[32] 陈金海,陆锋,彭国均.海洋运输船舶轨迹分析研究进展[J].中国航海,2012,35(3):53-57.
[33] 李存华,孙志挥,陈耿,等.核密度估计及其在聚类算法构造中的应用[J].计算机研究与发展,2004,41(10):1712-1719.
[34] RISTIC B,LA SCALA B,MORELANDE M,et al.Statistical analysis of motion patterns in AIS data:Anomaly detection and motion prediction[C]//information fusion,2008 11th international conference on.IEEE,2008:1-7.
[35] LAXHAMMAR R,FALKMAN G,SVIESTINS E.Anomaly detection in sea traffic-a comparison of the gaussian mixture model and the kernel density estimator[C]//Information Fusion,2009.FUSION′09.12th International Conference on.IEEE,2009:756-763.
[36] LAMPE O D,KEHRER J,HAUSER H.Visual Analysis of Multivariate Movement Data using Interactive Difference Views[C]//VMV.2010:315-322.
[37] CHEN J H,LU F,PENG G J.A quantitative approach for delineating principal fairways of ship passages through a strait[J].Ocean Engineering,2015,103:188-197.
[38] 陈金海,陆锋,李明晓.海上主航迹带边界统计推断与海西航路警戒区布局优化分析[J].地球信息科学学报,2015,17(10):1196-1206.
[39] 杜磊,文元桥,肖长诗,等.自由航行海域船舶碰撞概率计算[J].中国安全科学学报,2015,25(1):53-59.
[40] GONZALEZ J,BATTISTELLO G,SCHMIEGELT P,et al.Semi-automatic extraction of ship lanes and movement corridors from AIS data[C]//2014 IEEE Geoscience and Remote Sensing Symposium.IEEE,2014:1847-1850.
[41] ETIENNE L,DEVOGELE T,BOUJU A.Spatio-temporal trajectory analysis of mobile objects following the same itinerary[J].Advances in Geo-Spatial Information Science,2012,10:47-57.
[42] ROCHA J A M R,TIMES V C,OLIVEIRA G,et al.DB-SMoT:A direction-based spatio-temporal clustering method[C]//2010 5th IEEE International Conference Intelligent Systems.IEEE,2010:114-119.
[43] KROODSMA D A,Mayorga J,Hochberg T,et al.Tracking the global footprint of fisheries[J].Science,2018,359(6378):904-908.
[44] OSEKOWSKA E,Carlsson B.Learning Maritime Traffic Rules Using Potential Fields[C]//International Conference on Computational Logistics.Springer International Publishing,2015:298-312.
[45] OSEKOWSKA E,Axelsson S,Carlsson B.Potential Fields in Modeling Transport over Water[M].Springer International Publishing,2015:259-280.
[46] OSEKOWSKA E,Johnson H,Carlsson B.Grid size optimization for potential field based maritime anomaly detection[C]//17th Meeting of the EURO Working Group on Transportation.Spain,2014:720-729.