Review and Prospect on System Operation Supervision
Technology of Inland River Navigation System

doi:10.16097/j.cnki.1009-6744.2022.06.001

Abstract

Abstract: Digital, automatic, and intelligent supervision is the key technology to ensure the safe, efficient, and green operation of the inland river navigation system. We elaborate on the research status of inland river navigation technology in three aspects, i.e., situational awareness, event monitoring, and organizational optimization. The evolution and trend of technology development are summarized, and the deficiencies of supervision technology are analyzed. The research on the situation awareness of inland river shipping supervision makes adaptive progress with the development of advanced information perception technology, which capture ship physical appearance features using maritime radar technology and intelligent and now focus on multi-ship situation awareness combining multisource information and data mining method. As for event monitoring, it is mainly oriented to post-event analysis due to the lack of sensor equipment perception level, and it gradually develops towards in-event detection and pre-event prediction. The research on organizational optimization mainly includes space and time optimization of ship operation.In the future, the organizational optimization model should consider the impact of channel emergencies, which can promote the practical application of organizational operation and serve maritime affairs supervision better. We extract the corresponding key technologies in three aspects, i.e., construction of multi-mode integration and fusion perception network of inland waterway navigation system, holographic scene map, and intelligent control system. Oriented to the next generation of navigation systems, we propose a novel inland waterway transport management and control framework, named parallel control system. We summarize the key contents of system construction, i.e., physical modeling and dynamic coupling relationship modeling of inland river elements, parallel data set building and information mining, parallel supervision, and interactive visualization. We aim to use closed-loop interaction mechanisms between virtual and real transport systems based on digital twin technology to realize the efficient operation of the inland river navigation system. This paper puts forward the innovative direction for the research and development of operation supervision of the inland river navigation system.

Key words: waterway transportation, current status of supervision research, inland river navigation system, technology overview, parallel supervision system of inland navigation transportation

摘要： 数字化、自动化及智能化监管技术是保障内河航运系统安全、高效及绿色运行的关键。从态势感知、事件监视及组织优化这3方面阐述内河航运系统监管技术研究现状，总结技术发展沿革与趋势，分析监管技术存在的不足。研究表明：内河航运监管态势感知研究伴随先进信息感知技术发展做适应性进步，从利用海事雷达技术捕捉船舶物理表象特征，逐步结合数据挖掘方法融合多源信息向多船态势感知和智能感知方向发展；事件监视研究起初受限于传感器设备感知水平不足而主要面向事件后分析，结合先进传感器技术和智能技术，逐渐向事件中检测和事件前预测方向发展；组织优化研究主要包括船舶运行空间优化方案和时间优化方案的制定，未来组织优化模型需考虑航道突发事件的影响，有利于推进组织运行方案的实际应用，更好地服务于海事监管需求。提炼内河航运系统多模式一体化融合感知网、全息场景图及智能管控系统构建的关键技术，面向未来新一代航运系统，探索内河航运平行监管模式，阐述内河要素物理及耦合关系平行建模和平行数据集建立与信息挖掘、平行监管及交互可视化等方面建设的核心内容，旨在采用基于数字孪生技术的虚实闭环交互机制实现内河航运系统的高效运行，为内河航运系统监管技术的研究与发展提出了创新方向。

关键词: 水路运输, 监管研究现状, 内河航运系统, 技术概述, 内河航运平行监管系统

CLC Number:

U692.3

CHEN De-shan, FAN Teng-ze, YUAN Hai-wen, YAN Xin-ping. Review and Prospect on System Operation Supervision Technology of Inland River Navigation System[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(6): 1-14.

陈德山, 范腾泽, 元海文, 严新平. 内河航运系统监管技术现状与展望[J]. 交通运输系统工程与信息, 2022, 22(6): 1-14.

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References

[1] KOTOWSKA I, MAŃKOWSKA M, PLUCIŃSKI M. Inland shipping to serve the hinterland: The challenge for seaport authorities[J]. Sustainability, 2018, 10(10): 103468.

[2] 严新平. 内河新一代航运系统构建的思考[J]. 中国水运, 2021, 5: 6-8. [YAN X P. Thinking on the construction of a new generation of inland river shipping system[J]. China Water Transport, 2021, 5: 6-8.]

[3] 中华人民共和国交通运输部.内河航运发展纲要[R].北京: 交通运输部, 2020. [Ministry of Transport of the People's Republic of China. Outline of inland waterway navigation development[R]. Beijing: Ministry of Transport, 2020.]

[4] 何新华. 内河航运系统体系框架设计的关键问题研究[D]. 上海: 同济大学, 2007. [HE X H. Study on key issues in the framework design of inland river shipping system[D]. Shanghai: Tongji University, 2007.]

[5] WANG J, LI J Y. Inland waterway transport in the pearl river basin, China[J]. Lespace Géographique, 2012, 41 (3): 196-209.

[6] STYHRE L, WINNES H. Energy efficient port calls: A study of Wedish shipping with international outlooks[R]. Sweden: IVL Swedish Environmental Research Institute, 2016.

[7] SANTOS T A, FONSECA M Â, MARTINS P, et al. Integrating short sea shipping with trans-European transport networks[J]. Journal of Marine Science and Engineering, 2022, 10: 10020218.

[8] JOHN O, BURMEISTER H C, BRODJE A, et al. Assessing the MONALISA 2.0 Concept: Establishment of the european maritime simulation network[C]. Hamburg: International Symposium on Information on Ships, 2014.

[9] WU Z, REN C, WU X, et al. Research on digital twin construction and safety management application of inland waterway based on 3D video fusion[J]. IEEE Access, 2021, 99: 1-1.

[10] LI L, LU W, NIU J, et al. AIS data-based decision model for navigation risk in sea areas[J]. Journal of Navigation, 2018, 71(3): 664-678.

[11] 黄亮, 文元桥, 周春辉, 等. 基于GIS和AIS的水上交通宏观态势评估系统[J]. 中国航海, 2017, 40(1): 53-57. [HUANG L, WEN Y Q, ZHOU C H, et al. Water traffic macro situation assessment system based on GIS and AIS [J]. Navigation of China, 2017, 40(1): 53-57.]

[12] FUJI J, TANAKA K. Traffic capacity[J]. Journal of Navigation, 1971, 24(4): 543-652.

[13] WANG N, MENG X, XU Q, et al. An intelligent spatial collision risk based on the quaternion ship domain[J]. Journal of Navigation, 2010, 63: 733-749.

[14] GOERLANDT F, MONTEWKA J, ZHANG W, et al. An analysis of ship escort and convoy operations in ice conditions[J]. Safety Eence, 2017, 95: 198-209.

[15] BUKHARI A C, TUSSEYEVA I, LEE B G, et al. An intelligent real-time multi-vessel collision risk assessment system from VTS view point based on fuzzy inference system[J]. Expert Systems with Applications, 2013, 40(4): 1220-1230.

[16] KANG L J, LU Z Y, MENG Q, et al. Maritime simulator based determination of minimum DCPA and TCPA in head-on ship-to-ship collision avoidance in confined waters[J]. Transportmetrica A: Transport Science, 2019, 15(2): 1124-1144.

[17] 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 Y Q, WU D Y, ZHANG H, et al. Safety modal definition and modeling of water transportation system[J]. China Safety Science Journal, 2013, 23(6): 32-38.]

[18] BUKHARI A C, TUSSEYEVA I, LEE B G, et al. An intelligent real-time multi-vessel collision risk assessment system from VTS view point based on fuzzy inference system[J]. Expert Systems with Applications, 2013, 40(4): 1220-1230.

[19] YU H C, FANG Z, MURRAY A T, et al. A directionconstrained space-time prism-based approach for quantifying possible multi- ship collision risks[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 99: 1-11.

[20] JIA C F, MA J, HE M R, et al. Motion primitives learning of ship-ship interaction patterns in encounter situations [J]. Ocean Engineering, 2022, 247: 110708.

[21] WANG S, ZHANG Y, ZHENG Y. Multi-ship encounter situation adaptive understanding by individual navigation intention inference[J]. Ocean Engineering, 2021, 237: 109612.

[22] ZHEN R, SHI Z Q, LIU J L, et al. A novel arena-based regional collision risk assessment method of multi-ship encounter situation in complex waters[J]. Ocean Engineering, 2022, 246: 110531.

[23] SUI Z Y, WEN Y Q, HUANG Y M, et al. Node importance evaluation in marine traffic situation complex network for intelligent maritime supervision[J]. Ocean Engineering, 2022, 247: 110742.

[24] 兰培真, 刘旺盛, 刘晓佳, 等. 低轨卫星自动识别系统在海事监管中的应用[J]. 中国航海, 2012, 35(2): 11- 14. [LAN P Z, LIU W S, LIU X J, et al. Application of low orbit satellite automatic identification system in maritime supervision[J]. Navigation of China, 2012, 35(2): 11-14.]

[25] 张绍明, 桂坡坡, 刘伟杰, 等. 基于高分辨率遥感影像的内河航标自动检测方法[J]. 同济大学学报自然科学版, 2014, 1: 136-143. [ZHANG S M, GUI P P, LIU W J, et al. Automatic detection method of river navigational markers based on high resolution remote sensing image [J]. Journal of Tongji University Natural Science Edition, 2014, 1: 136-143.]

[26] GERBEN P, MARCUS K, AFZAL M R, et al. An unmanned inland cargo vessel: Design, build, and experiments[J]. Ocean Engineering, 2020, 201: 107056.

[27] 严新平, 柳晨光. 智能航运系统的发展现状与趋势[J]. 智能系统学报, 2016, 11(6): 807-817. [YAN X P, LIU C G. Development status and trend of intelligent shipping system[J]. CAAI Transactions on Intelligent Systems, 2016, 11(6): 807-817.]

[28] ZHANG J, WAN C, HE A, et al. A two-stage black-spot identification model for inland waterway transportation [J]. Reliability Engineering and System Safety, 2021, 9: 107677.

[29] XUE J, PAPADIMITRIOU E, RENIERS G, et al. A comprehensive statistical investigation framework for characteristics and causes analysis of ship accidents: A case study in the fluctuating backwater area of three gorges reservoir region[J]. Ocean Engineering, 2021, 229: 108981.

[30] 王莹, 欧阳文全, 赵建, 等. 船舶防撞预警视频监测技术在淮河入海航道的应用[J]. 中国水运, 2018, 18(2): 51-52. [WANG Y, OUYANG W Q, ZHAO J, et al. Application of video monitoring technology for ship collision prevention in Huaihe river channel[J]. China Water Transport, 2018, 18(2): 51-52.]

[31] CHEN X, WANG S, SHI C, et al. Robust ship tracking via multi-view learning and sparse representation[J]. Journal of Navigation, 2019, 72(1): 176-192.

[32] YU Q, TEIXEIRA A P, LIU K, et al. Framework and application of multi-criteria ship collision risk assessment [J]. Ocean Engineering, 2022, 250: 111006.

[33] CAI M, ZHANG J, ZHANG D, et al. Collision risk analysis on ferry ships in Jiangsu section of the Yangtze river based on AIS data[J]. Reliability Engineering & System Safety, 2021, 215: 107901.

[34] BOTTS C H. A novel metric for detecting anomalous ship behavior using a variation of the DBSCAN clustering algorithm[J]. SN Computer Science, 2021, 2(5): 1-16.

[35] HUANG G, LAI S, YE C, et al. Ship trajectory anomaly detection based on multi-feature fusion[C]. Chicago: IEEE International Conference on Smart Data Services (SMDS), 2021.

[36] VRIES G D, SOMEREN M V. Recognizing vessel movements from historical data[M]. Springer New York, 2013.

[37] KELLY P. A novel technique to identify AIS transmissions from vessels which attempt to obscure their position by switching their AIS transponder from normal transmit power mode to low transmit power mode[J]. Expert Systems with Applications, 2022, 202: 117205.

[38] ABEBE M, NOH Y, KANG Y J, et al. Ship trajectory planning for collision avoidance using hybrid ARIMALSTM models[J]. Ocean Engineering, 2022, 256: 111527.

[39] WU B, YIP T L, YAN X P, et al. Fuzzy logic based approach for ship-bridge collision alert system[J]. Ocean Engineering, 2019, 187: 106152.

[40] GAO M, SHI G Y. Ship collision avoidance anthropomorphic decision-making for structured learning based on AIS with Seq-CGAN[J]. Ocean Engineering, 2020, 217: 107922.

[41] 刘铁君, 郭小飞. 基于“北斗+物联网+AIS技术”的水上安全监管系统研发与应用[J]. 中国海事, 2021, 6: 61- 63. [LIU T J, GUO X F. Research and application of water safety supervision system based on“Beidou + Internet of Things + AIS technology”[J]. China Maritime Safety, 2021, 6: 61-63.]

[42] FEI P, CHU X, GENG X, et al. A inland waterway monitoring virtual-GIS system based on multi heterogeneous navigation data fusion[C]//2021 3rd International Academic Exchange Conference on Science and Technology Innovation (IAECST), Guangzhou, China: IEEE, 2021, 15: 618-621.

[43] 魏丹. 基于机器学习的交通状态判别与预测方法[D]. 长春: 吉林大学, 2020. [WEI D. Traffic state discrimination and prediction method based on machine learning[D]. Changchun: Jilin University, 2020.]

[44] 人民交通. 破除“肠梗阻”建设三峡水运新通道[DB/ OL]. 北京: 人民交通网, (2021-07-27) [2022-07-14]. http: //www. rmjtxw. com/news/shuiyun/160560. html. [People's Traffic. A new water transport channel for the Three Gorges will be built by removing intestinal obstruction[DB/OL]. Beijing: People's Transportation Network, (2021-07-27) [2022-07-14]. http: //www. rmjtxw.com/news/shuiyun/160560.html.]

[45] 范中洲. 船舶定线制优选方法的研究[D]. 大连: 大连海事大学, 2013. [FAN Z Z. Research on optimization method of ship alignment system[D]. Dalian: Dalian Maritime University, 2013.]

[46] ZHANG X, LI R, CHEN X, et al. Multi-object-based vessel traffic scheduling optimisation in a compound waterway of a large harbour[J]. Journal of Navigation, 2018, 72(3): 1-19.

[47] BUKHARI A C, TUSSEYEVA I, LEE B G, et al. An intelligent real-time multi-vessel collision risk assessment system from VTS view point based on fuzzy inference system[J]. Expert Systems with Applications, 2013, 40(4): 1220-1230.

[48] ZHANG X, LIN J, GUO Z, et al. Vessel transportation scheduling optimization based on channel-berth coordination[J]. Ocean Engineering, 2016, 112: 145-152.

[49] 郑红星, 朱徐涛, 李振飞. 双向航道集装箱港口船舶调度优化算法[J]. 计算机应用, 2021, 41(10): 3049-3055. [ZHENG H X, ZHU X T, LI Z F. Optimization algorithm of vessel scheduling in container port of bidirectional channel[J]. Computer Application, 2021, 41(10): 3049- 3055.]

[50] LIU B L, LI Z C, WANG Y D, et al. Short-term berth planning and ship scheduling for a busy seaport with channel restrictions[J]. Transportation Research Part E: Logistics and Transportation Review, 2021, 154: 102467.

[51] DENG Y, SHENG D, LIU B. Managing ship lock congestion in an inland waterway: A bottleneck model with a service time window[J]. Transport Policy, 2021, 112: 142-161.

[52] 徐晓帆, 王妮炜, 高璎园, 等. 陆海空天一体化信息网络发展研究[J]. 中国工程科学, 2021, 23(2): 39-45. [XU X F, WANG N W, GAO Y Y, et al. Research on the development of land based, sea based, air based and space based integrated information network[J]. Strategic Study of CAE, 2021, 23(2): 39-45.]

[53] BONNIN P F, ORTIZ A. On the use of robots and vision technologies for the inspection of vessels: A survey on recent advances[J]. Ocean Engineering, 2019, 190: 106420.

[54] MOU J M, ZHOU C, DU Y, et al. Evaluate VTS benefits: A case study of Zhoushan port[J]. International Journal of e-Navigation and Maritime Economy, 2015, 3: 22-31.

[55] 中华人名共和国交通运输部. 全要素水上“大交管”建设方案发布[DB/OL]. 北京: 中国交通新闻网, (2021- 09-28) [2022-07-14]. http: //big5. mot. gov.cn/gate/big5/ www. mot. gov. cn/jiaotongyaowen/202109/t20210928_ 3620220. html. 2021. [Ministry of Transport of the People's Republic of China. The construction plan of "large traffic control" on all-factor water was released[DB/ OL]. Beijing: China Transportation News Network, (2021-09-28) [2022-07-14]. http://big5.mot.gov.cn/gate/ big5/ www. mot. gov. cn/ jiaotongyaowen/ 202109/ t20210928_3620220.html. 2021.]

[56] 魏曦, 杨保岑, 叶劲松, 等. 基于内河电子航道图制作和应用的内河航道要素分类体系研究[J]. 中国水运, 2015, 15(8): 41-43. [WEI X, YANG B C, YE J S, et al. Study on classification system of inland waterway elements based on making and application of inland waterway electronic waterway map[J]. China Water Transport, 2015, 15(8): 41-43.]

[57] SZLAPCZYNSKI R, SZLAPCZYNSKA J. A ship domainbased model of collision risk for near-miss detection and collision alert systems[J]. Reliability Engineering & System Safety, 2021, 214: 107766.

[58] CAO Y, ZHANG W, ZHU Y, et al. Impact of trends in river discharge and ocean tides on water level dynamics in the Pearl river delta[J]. Coastal Engineering, 2020, 157: 103634.

[59] LEE K, HUI P M, WANG B H, et al. Effects of announcing global information in a two-route traffic flow model[J]. Journal of the Physical Society of Japan, 2003, 70(12): 3507-3510.

[60] 严新平, 李晨, 刘佳仑, 等. 新一代航运系统体系架构与关键技术研究[J]. 交通运输系统工程与信息, 2021, 21(5): 22-29. [YAN X P, LI C, LIU J L, et al. Research on architecture and key technology of new generation shipping system[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 22-29.]

[61] 王飞跃. 平行系统方法与复杂系统的管理和控制[J]. 控制与决策, 2004, 5: 485-489. [WANG F Y. Parallel systems approach and management and control of complex systems[J]. Control and Decision, 2004, 5: 485- 489.]

[62] TAO F, ZHANG H, QI Q L, et al. Ten questions towards digital twin: Analysis and thinking[J]. Computer Integrated Manufacturing Systems, 2020, 26(1): 1-17.

[63] 严新平, 褚端峰, 刘佳仑, 等. 智能交通发展的现状, 挑战与展望[J]. 交通运输研究, 2021, 7(6): 2-10. [YAN X P, CHU D F, LIU J L, et al. Current situation, challenge and prospect of intelligent transportation development[J]. Transport Research, 2021, 7(6): 2-10.]

[64] 陈圆圆. 基于平行数据的交通预测和社会交通信息提取方法研究[D]. 北京: 中国科学院大学, 2018. [CHEN Y Y. Research on traffic prediction and social traffic information extraction based on parallel data[D]. Beijing: University of Chinese Academy of Sciences, 2018.]

[65] 刘腾, 于会龙, 田滨, 等. 智能车的智能指挥与控制:基本方法与系统结构[J]. 指挥与控制学报, 2018, 4(1): 22-31. [LIU T, YU H L, TIAN B, et al. Intelligent command and control for intelligent vehicles: Basic methods and system architecture[J]. Journal of Command and Control, 2018, 4(1): 22-31.]

[66] 严新平, 王树武, 马枫. 智能货运船舶研究现状与发展思考[J]. 中国舰船研究, 2021, 16(1): 1-6. [YAN X P, WANG S W, MA F. Intelligent cargo ship research status and development thinking[J]. Chinese Journal of Ship Research, 2021, 16(1): 1-6.]

Review and Prospect on System Operation Supervision Technology of Inland River Navigation System

内河航运系统监管技术现状与展望

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