桥区船舶交通流可视分析系统

doi:10.16183/j.cnki.jsjtu.2017.07.011

摘要/Abstract

摘要： 以武汉长江大桥桥区水域为研究对象，针对数据分析能力不足而造成海量AIS(Automatic Identification System)数据不仅无法更好地助力水上交通安全，反而为监管决策带来困扰的现状，研究了多维AIS数据的可视化表达和人机交互方法.提出了以电子航道图为载体的内河船舶交通状态平行坐标图模型，并针对传统网格划分法的不足，采用高斯密度函数为核函数利用二维核密度估计法生成热力图模型.在此基础上研发了船舶交通可视化系统，通过3组实例证明该系统有助于桥区船舶数据的异常分析和船舶行为模式识别，为海事管理人员提供有效的决策依据.

关键词: , 桥区船舶交通, 可视分析, 自动识别系统可视化, 水路运输

Abstract: Current practice shows that working with bridge waterway automatic identification system (AIS) data often does not lead to insight but rather confusion because large data volume without further being processed is hard to understand. In order to deal with this issue, bridge waterway of Wuhan section in Yangtze River was selected as research area for the study of AIS visualization model and humancomputer interaction method. Additionally, two dimensional kernel density estimation approach was adopted in the heatmap generation to overcome the defects of traditional grid method. Furthermore, based on electric navigation charts, a visual analytics system was built. Finally, three instances were illustrated and results demonstrated that it is conductive to the users in maritime department to make decisions depending on the knowledge they discovered from the visual analytics system.

Key words:
vessel traffic in bridge waterway, visual analytics, automatic identification system (AIS) visualization, waterway transportation

中图分类号:

U 664.5

雷进宇1,2,3，初秀民1,2，何伟4，周映萍1,2. 桥区船舶交通流可视分析系统[J]. 上海交通大学学报（自然版）, 2017, 51(7): 840-845.

LEI Jinyu1,2,3,CHU Xiumin1,2,HE Wei4,ZHOU Yingping1,2. Visual Analytic System of Vessel Traffic in Bridge Waterway[J]. Journal of Shanghai Jiaotong University, 2017, 51(7): 840-845.

参考文献

［1］徐武雄, 初秀民, 刘兴龙. 水上交通信息可视化技术研究进展［J］. 中国航海, 2015, 38(1): 3438.
XU Wuxiong, CHU Xiumin, LIU Xinglong. Advances of maritime traffic information visualization techniques［J］. Navigation of China, 2015, 38(1): 3438.
［2］ANDRIENKO G, ANDRIENKO N, BAK P, et al. Visual analytics of movement［M］. Berlin: Springer, 2013: 13.
［3］熊振南, 程俊康, 翁跃宗. 点统计法在船舶交通流分析中的应用［J］. 中国航海, 2009, 32(1): 6467.
XIONG Zhennan, CHENG Junkang, WENG Yuezong. Application of pointstatistic method in the analysis of vessel traffic flow［J］. Navigation of China, 2009, 32(1): 6467.
［4］徐武雄，初秀民，刘兴龙. 多桥水域航道通过能力仿真研究［J］. 交通运输系统工程与信息， 2015， 15(3): 127133.
XU Wuxiong, CHU Xiumin, LIU Xinglong. Simulation for transit capacity of a multibridge waterway［J］. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(3): 127133.
［5］SILVEIRA P A M, TEIXEIRA A P, SOARES C G. Use of AIS data to characterise marine traffic patterns and ship collision risk off the coast of Portugal［J］. Journal of Navigation, 2013, 66(6): 879898.
［6］甘浪雄, 张磊, 邹早建, 等. 基于场方法的船舶交通流分析［J］. 上海交通大学学报, 2014, 48(4): 551557.
GAN Langxiong, ZHANG Lei, ZOU Zaojian, et al. Analysis of vessel traffic flow based on field method［J］. Journal of Shanghai Jiao Tong University, 2014, 48(4): 551557.
［7］GUO H, WANG Z, YU B, et al. Tripvista: Triple perspective visual trajectory analytics and its application on microscopic traffic data at a road intersection［C］∥Pacific Visualization Symposium. USA: IEEE, 2011: 163170.
［8］何兆成，周亚强，余志. 基于数据可视化的区域交通状态特征评价方法［J］. 交通运输工程学报, 2016, 16(1): 133140.
HE Zhaocheng, ZHOU Yaqiang, YU Zhi. Regional trafic state evaluation method based on data visualization［J］. Journal of Traffic and Transportation Engineering, 2016, 16(1): 133140.
［9］ANDRIENKO G, ANDRIENKO N. Spatiotemporal aggregation for visual analysis of movements［C］∥Proceedings of IEEE Symposium on Visual Analytics Science & Technology IEEE Comput. Columbus, Ohio, USA: IEEE, 2008: 5158.
［10］WILLEMS N, SCHEEPENS R, VAN DE WETERING H, et al. Visualization of vessel traffic［M］. New York: Springer, 2013: 7387.
［11］SCHEEPENS R, WILLEMS N, HUUB V D W, et al. Interactive visualization of multivariate trajectory data with density maps［C］∥Pacific Visualization Symposium. USA: IEEE, 2011: 147154.
［12］SCHEEPENS R, HURTER C, VAN DE WETERING H, et al. Visualization, selection, and analysis of traffic flows［J］. IEEE Transactions on Visualization and Computer Graphics, 2016, 22(1): 379388.
［13］WANG Z, LU M, YUAN X, et al. Visual traffic jam analysis based on trajectory data［J］. IEEE Transactions on Visualization and Computer Graphics, 2013, 19(12): 21592168.
［14］姜晓睿, 郑春益, 蒋莉, 等. 大规模出租车起止点数据可视分析［J］. 计算机辅助设计与图形学学报, 2015, 27(10): 19071917.
JIANG Xiaorui, ZHENG Chunyi, JIANG Li, et al. Visual analysis of large taxi origindestination data［J］. Journal of ComputerAided Design & Computer Graphics, 2015, 27(10): 19071917.
［15］SILVERMAN B W. Density estimation for statistics and data analysis［M］. London: CRC Press, 1986: 711.

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