Marine traffic macroscopic situation assessment model

  • DU Lei ,
  • WEN Yuan-qiao ,
  • LI Zheng-qiang ,
  • SUN Teng-da ,
  • XIAO Chang-shi ,
  • ZHOU Chun-hui
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  • (1 a.School of Navigation;1b. Hubei Inland Shipping Technology Key Laboratory, Wuhan 430063, China; 2. China Transport Telecommunications & Information Center, Beijing 100011, China)

Received date: 2015-05-28

  Revised date: 2015-07-03

  Online published: 2015-07-07

Abstract

To achieve quantitative description and analysis on marine traffic macroscopic status and its evolution trend in specific water area, and to have a deeper understanding and mastery of the interaction of water transport system internal factors, the model of marine traffic macroscopic situation assessment was built according to the intrinsic characteristics of marine traffic macroscopic situation. Firstly, according to the characteristics of macroscopic situation, the macroscopic situation assessment indicators were analyzed, and the macroscopic situation assessment model based on the integration of density factor and looming factor was built, as well as the spatial distribution model. Then, the situation change was analyzed by gridding the water area, and extends to time dimension to build the prediction model. Finally, marine traffic situation assessment and visual analysis were carried out with living cases. Taking Shenzhen Western Port as an example, situation assessment and visualization applications were analyzed by utilizing regional AIS data as situational awareness data, as well as the changes and relevance of macroscopic situation with the selected indicator. Results show a good correlation between marine traffic macroscopic situation and indicator factors selected, which can better reflect the status and trends of water traffic, and provide a measurement tool for marine traffic macroscopic situation assessment and system security research of maritime traffic systems.

Cite this article

DU Lei , WEN Yuan-qiao , LI Zheng-qiang , SUN Teng-da , XIAO Chang-shi , ZHOU Chun-hui . Marine traffic macroscopic situation assessment model[J]. Journal of Dalian Maritime University, 2016 , 42(1) : 27 -33 . DOI: 10.16411/j.cnki.issn1006-7736.2016.01.006

References

[1]严新平,吴兵,汪洋,等.海事仿真研究现状与发展综述[J]. 系统仿真学报,2015,27(1):13-28.
YAN Xin-ping,WU Bing,WANG Yang, et al. Overview of development and curt progress in maritime simulation research[J].Journal of System Simulation,2015,27(1):13-28(in Chinese)
[2]KUJALA P,HÄNNINEN M,AROLA T, et al. Analysis of the marine traffic safety in the Gulf of Finland[J].Reliability Engineering and System Safety(S0951-8320),2009,94(8): 1349-1357.
[3]CELIK M,LAVASANI S M, WANG Jin.A risk-based modelling approach to enhance shipping accident investigation[J].Safety Science,2010,48(1):18-27.
[4]HUNTINGTON H P,DANIEL R, HARTSIG A, et al.Vessels, risks, and rules: planning for safe shipping in Bering Strait[J].Marine Policy,2014,1(1):119-127.
[5] GOERLANDT F,KUJALA P.Traffic simulation based ship collision probability modeling[J].Reliability Engineering and System Safety,2011,96(1):91-107.
[6]韩延胜.长江水上交通安全评价指标体系研究[D].武汉:武汉理工大学,2006.
HAN Yan-sheng.Traffic safety appraisal target system of Changjiang river[D].Wuhan:Wuhan University of Technology,2006.(in Chinese)
[7]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.
DU Lei, WEN Yuan-qiao, XIAO Chang-shi, et al. Collision probability calculation for ship sailing in free navigational sea area[J].China Safety Science Journal,2015,25(1):53-59. (in Chinese)
[8]STANTON N A,CHAMBERS P R G, PIGGOTT J.Situational awareness and safety[J].Safety Science,2001,39(3):189-204.
[9]SNEDDON A, MEARNS K, FLIN P. Situation awareness and safety in offshore drill crews[J].Cognition Technology &Work,2006,8(4):255-267.
[10]CHEN Chun-hsien, KHOO Li-pheng,CHONG Yih-tng, et al.Knowledge discovery using genetic algorithm for maritime situational awareness[J].Expert System with Applications,2014,41(6):2742-2753.
[11]SNIDARO L, VISENTINI I, BRYAN K. Fusing uncertain knowledge and evidence for maritime situational awareness via Markov logic networks[J]. Information Fusion, 2015,21:159-172.
[12]赵嶷飞,周阳.五边到场交通态势安全评估研究[J].中国安全科学学报,2011,21(6):99-103.
ZHAO Yi-fei, ZHOU Yang.Safety evaluation on five-edge arrival traffic complexity[J].China Safety Science Journal, 2011,21(6):99-103. (in Chinese)
[13]朱琳.城市快速路交通态势评估理论与方法研究[D].北京: 北京交通大学,2013.
ZHU Lin.Theory and method studies on traffic situation assessment for urban expressways[D].Beijing:Beijing Jiaotong University,2013.(in Chinese)
[14]文元桥,吴定勇,张恒,等.水上交通系统安全模态定义与建模[J].中国安全科学学报,2013,23(6):32-38.
WEN Yuan-qiao, WU Ding-yong, ZHANG Heng, et al. Water traffic system safety modality:definition and modeling[J].China Safety Science Journal,2013,23(6):32-38.(in Chinese)
[15]DELAHAYE D, PUECHMOREL S.Air traffic complexity: towards intrinsic metrics[C]//Proceedings of the Third USA/Europe Air Traffic Management R & D Seminar,2000.
[16]胡甚平.船舶会遇过程中避碰阶段的划分与量化[J]. 中国航海,2001,24(2):83-87.
HU Shen-ping.Analysis of anti-collision stages during ships’encounter[J].Navigation of China,2001,24(2):83-87.(in Chinese)
[17]黄亚敏.水上交通复杂性测度研究[D].武汉:武汉理工大学,2014.
HUANG Ya-min.Study on marine traffic flow complexity metric[D].Wuhan:Wuhan University of Technology,2014,(in Chinese)
[18]王红勇,赵嶷飞,温瑞英.基于复杂网络的空中交通复杂性度量方法[J].系统工程,2014,32(3):112-118.
WANG Hong-yong, ZHAO Yi-fei,WEN Rui-ying.Air traffic complexity metrics based on complex network[J]. Syatems Engineering,2014,32(3):112-118.(in Chinese)
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