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WO2011027037A1 - Système d'indication de risque de voie navigable intelligent et procédé associé - Google Patents

Système d'indication de risque de voie navigable intelligent et procédé associé Download PDF

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Publication number
WO2011027037A1
WO2011027037A1 PCT/FI2010/050688 FI2010050688W WO2011027037A1 WO 2011027037 A1 WO2011027037 A1 WO 2011027037A1 FI 2010050688 W FI2010050688 W FI 2010050688W WO 2011027037 A1 WO2011027037 A1 WO 2011027037A1
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WIPO (PCT)
Prior art keywords
maritime traffic
risk
data
vessel
indication system
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Ceased
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PCT/FI2010/050688
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English (en)
Inventor
Tony Rosqvist
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VTT Technical Research Centre of Finland Ltd
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VTT Technical Research Centre of Finland Ltd
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Publication of WO2011027037A1 publication Critical patent/WO2011027037A1/fr
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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G3/00—Traffic control systems for marine craft
    • G08G3/02—Anti-collision systems

Definitions

  • VTS vessel traffic service
  • AIS Automat- ic Identification System
  • CCTV Camera-Circuit Television
  • VHF Very High Frequency radiotelephony or other co-operative systems and services.
  • An example of a VTS traffic image is presented in Fig. 1. Vessels equipped with AIS between Helsinki and Tallinn are presented in real time in the figure with different colors' representing different vessel types.
  • Fig. 2 illustrates AIS system and data send by it.
  • AIS is intended to assist the vessel's officers of watch and allow maritime authorities to track and monitor vessel movements, and integrates a standardized VHF transceiver system such as a LO AN-C or Global Positioning System receiver, with other electronic navigation sensors, such as a gyrocompass or rate of turn indicator.
  • VHF transceiver system such as a LO AN-C or Global Positioning System receiver
  • other electronic navigation sensors such as a gyrocompass or rate of turn indicator.
  • GT gross tonnage
  • a comprehensive traffic image is formed of all factors influencing the traffic as well as information about all participating vessels and their intentions. By means of the traffic image, situations that are developing are evaluated by VTS personnel.
  • the data evaluation depends to a great extent on the quality of the data that is collected and the ability of the operator to combine this with an actual or developing situa- tion. Because the monitoring and the evaluation of the maritime traffic are performed by the VTS personnel, there is always an influence of a human factor and the possibility of a human error.
  • the objective of the embodiments of the present invention is to at least alleviate one or more of the aforesaid drawbacks evident in the prior art systems in the context of maritime safety.
  • the objective is generally met by a risk indication system and a related method in accordance of the present invention.
  • the system and the related method are used to learn and predict the movement of vessels in order to prevent collision or grounding in maritime traffic and/or observing the deviation from a route.
  • the method of continuous learning utilizes a dynamic computation algorithm for calculating probabili- ties about future vessel positions in order to recognizing possible incidence zones of vessels moving on a two-dimensional surface, in where position data projected in time, is used in current time, to update incident zones and incident probabilities.
  • a method for providing an incident probability indication of a collision or grounding in maritime traffic is characterized by the features disclosed in a corresponding method claim 9.
  • the utility of the present invention arises from a plurality of issues.
  • the risk indica- tion system of the present invention may improve the efficiency and reliability of, for example, VTS accident prevention by means of automatic monitoring, identification, classification and alarming of the risk of collision or grounding on a large sea area.
  • the risk indication system may assist e.g. VTS personnel to evaluate maritime traffic situations and recognize developing risks of collision and grounding.
  • the system may also be used as a standalone system, for example, in a vessel. Some embodiment of the system may eliminate collision or grounding of vessel(s) on condition that e.g. VTS personnel and officers of watch in the vessel(s) react to indicate risk development by the arrangement.
  • the risk indication system of the present invention may also be used for observing the deviation of a vessel from the route, which may indicate malfunction of steering systems, e.g. power failure, or in some case even hijacking of the vessel.
  • the expression “vessel” may refer herein to passenger vessels, cargo vessels, tankers, high speed crafts, tugs, pilot vessels, yachts and other maritime vessels.
  • the vessels advantageously contain equipment for sending at least identification infor- mation as well as position, speed and course data.
  • course data refers herein the direction information of a vessel.
  • maritime traffic refers herein to waterway traffic of vessels at sea or in some other water area capable for boat traffic.
  • incident zone may refer herein to an area, where a collision or grounding of vessel/vessels may occur or where the distance(s) between two or more vessels is/are too short in accordance of maritime safety regulations.
  • data related to vessels in maritime traffic may refer herein to the information a vessel transmits about its state via one or more known transmission system.
  • data related to maritime traffic may refer herein the information about vessels in maritime traffic the risk indication system obtains, e.g. from database, or by some other ways.
  • transmission system refers herein to systems or arrangements, such as AIS, in a vessel used to exchange data related to the vessel in maritime traf- fic with other nearby ships and VTS stations.
  • monitoring system refers herein to systems or arrangements, such as VTS station, utilized by harbor or port authorities for monitoring maritime traffic.
  • initialization material refers herein to data related to maritime traffic, which is collected before introducing the risk indication system with desired parameters, such as vessel type, with or without cargo, cargo type, sea- son, weather condition and time of day, used for initializing the risk indication system.
  • Fig. 1 illustrates an example of a VTS traffic image.
  • Fig. 4 depicts a concept of the present invention in general.
  • Fig. 5 illustrates the gathering of the position data of particular vessels in particular route.
  • Fig. 7 illustrates a flow diagram of an embodiment of a method according to the present invention.
  • Figure 4 discloses, by way of example only, a sketch of the present invention, wherein an internal of a risk indication system 400 in accordance with the present invention comprises a processor 402, a memory 404, one or more logic blocks 406, a user interface (UI) 408 and, optionally, one or more additional transceivers 410.
  • the logic blocks can be additional, too.
  • the basis of the present invention is the data related to vessels in maritime traffic.
  • the vessels with transmission system send information about their position and status.
  • the information the vessel may send is listed in the table in Fig. 3.
  • identification information, position, course, and speed information of a vessel are used in the present invention.
  • the vessel may also send another information, such as vessel type, cargo type, timestamp and destination information.
  • the data transmitted by vessels may be compiled to a database, which can be part of or, at least, functionally connected to the risk indication system.
  • the data related to maritime traffic is used for calculating risk probabilities for vessels about the real time position, speed and course data, but it is also used as a learning material for the risk indication system.
  • the data transmission between base stations or vessels 416 and the monitoring system 414 may also be arranged via the risk indication system 400 with its optional transceivers) 410.
  • the risk indication system 400 may use a database for data related to maritime traffic of the monitoring system 414 it is connected to or it may have the database of its own.
  • the processor 402 of the risk indication system comprises at least one processor, such as one or more microprocessors, micro-controllers, DSP's (digital signal processor), programmable logic chips, etc., or any desired combination thereof.
  • the processor 402 may comprise a plurality of cooperating proces- sors or sub-processors.
  • the processor 402 is configured to execute the code stored in the memory 404, which may imply processing instructions and data related to the risk indication system functionalities of the present invention and optionally other functionalities, such as OS related functionalities, I/O-related functionalities, and other applications. Likewise, the processor 402 controls the logic blocks 406.
  • the memory 404 may be divided between one or more physical memory chips or other memory elements, and it may comprise code, e.g. in a form of a computer program/application for the risk indication system, and other data.
  • the memory 404 may further include other storage media, such as a preferably detachable memory card, a floppy disc, a CD-ROM, fixed storage medium such as hard drive.
  • the memory 404 may be non- volatile, e.g. ROM, PROM, EEPROM or flash memory, and/or volatile, e.g. RAM, by nature.
  • the risk indication system may comprise optional logic blocks 406, such as a math block, for processing data related to a maritime traffic.
  • the logic blocks 406 are typically stored in the memory 404 of the risk indication system and they can be executed by the processor 402.
  • the logic blocks 406, especially math blocks, can be used to, for example, Bayesian statistical estimation utilized in this invention.
  • the UI (user interface) 408 may comprise a display, or a connector to an external display or data projector, and keyboard/keypad or other applicable control input means (e.g. touch screen or voice control input, or separate keys/buttons/knobs) configured so as to provide the user of the system 400 with practicable data visualization and device control means.
  • keyboard/keypad or other applicable control input means e.g. touch screen or voice control input, or separate keys/buttons/knobs
  • the risk indication system 400 may contain one or more the transceivers 410, complying with predetermined wired or wireless technology, for receiving data related to vessels maritime traffic sent by, for example, vessels equipped with AIS devices.
  • the data related to maritime traffic may be obtained from some other way; for instance, it may be provided by satellite(s) or radar(s).
  • the optional transceiver 410 can be a device that has both transmitting and receiving capabilities or the transceiver may consist of a separate transmitter and receiver, or the risk indication system 400 may contain only receiver(s).
  • Optional transceiver(s) 410 in the risk indication system 400 may be implemented for wireless network technology typically used in maritime data communications.
  • the risk indication system may, in practice, comprise numerous further functional and/or structural elements for providing various beneficial communication, processing, or other features, whereupon this disclosure is not to be constructed as limiting the presence of potential additional elements in any manner.
  • the risk indication system has to go through an initialization phase.
  • data related to maritime traffic is collected from the area the risk indication system is supposed to use as an initialization material for the risk indication system.
  • the initialization material is divided into several probability matrix categories according to various parameters, which depend on embodiments.
  • Figure 5 illustrates the gathering of the position data of particular vessels in particular routes.
  • the initialization material comprises position, course and speed data of different vessel types in maritime traffic with and without cargo and/or wherein the initialization material further comprises vessel type, circumstance, weather condition and light information.
  • a sufficiently large initialization material is needed for reliable developing and verifying the calculation routine of the risk indication system of the present invention.
  • the data is collected in normal situations, i.e. data of abnormal occasions is removed from the initialization material. For example, if the observed vessel is waiting for some other vessel to pass, there will be several data points in that location and these "noisy" data points are removed from the initialization material. For example, about ten trips via some particular route for each vessel types are needed for the initialization material. However, the initialization material will be bigger if different circumstance, light and weather conditions are included in the material.
  • the number of vessel types in the initialization material may vary depending on embodiments.
  • the vessel types may be, for example, passenger vessel and cargo vessel.
  • the data of another kind of vessel can also be included. There may be for example 1-6 typical vessel categories. Types related to vessels may also be divided into different weight categories so that vessels are also categorized according to their weight. The weight categories can be divided, for example 1-6 weight categories. It is also possible to define the categories by some other way.
  • the data is collected with and without cargo, for example for vessels such as O O ships, cargo vessels and tankers, because the weight of the cargo affects the movements of a vessel. It is possible to do that also to passenger vessels, but because they usually do not travel without passenger, the benefit of collecting data of passenger vessels without passenger is minor.
  • the initialization material is collected in different weather conditions and in different time of year for collecting information, for example, on the impact of the wind and ice to the route of vessels.
  • the data is also collected separately for a days and nights, because light may also have an effect on the route of a vessel.
  • the initialization material can be divided into categories according to vessel type, weight category, with or without cargo, season of year, weather condition and time of day.
  • Fig. 6 illustrates an example of expected routes of vessels and simulated routes produced with a Markov model.
  • First and second orders Markov model are used to replicate the "true" movements of vessels on the grid.
  • the first vessel moves from point A to point B.
  • the expected route is a straight line 602 from point A to point B.
  • the Markov model used on the basis of the initialization material simulates routes 604 and 606 for the first vessel as a true route.
  • the ex- pected route for the second vessel from point D to point C is a line 608 and the simulated route performed with Markov model is a route 610. It can be seen in Fig. 6 that the expected incident zone is only in the centre of the grid, but true incident zone might be much wider.
  • the two dimensional surface is sliced into a grid, i.e. squares, which cover the area to be monitored.
  • the size of the squares in the grid does not have to be equal.
  • the grid can be finer in the area of routes and crossing traffic and coarser elsewhere.
  • the size of squares is a compromise; the finer the grid, the more number-crunching power is needed.
  • large square size increases the inaccuracy of the prediction.
  • the appropriate grid size would be about 2-4 times the monitored vessel size, for example.
  • the squares are indexed ⁇ 1 ,..., N ⁇ .
  • a square of the grid is interpreted as a possible state 'X' of a vessel.
  • the state sequence X ⁇ xl, ... , xq > of -step is defined for the vessel.
  • the data is assumed to follow Markov chain.
  • the probability of the sequence is where ⁇ is the probability matrix and the transition probabilities are
  • Fig. 7 illustrates a flow diagram of an embodiment of a method according to the present invention.
  • the initialization phase has been performed before the risk indication system is delivered, so that step is excluded from the flow diagram and the method starts calculating and indicating an incident probability of a collision or grounding in maritime traffic at step 700.
  • the user performs the initialization phase before starting to calculate and indicate the incident probability of a collision or grounding.
  • the settings of the risk indication system is adjusted with adjusting parameters, such as grid size, vessel types and filter thresholds.
  • the size and shape of squares in the grid may vary so that the grid may be finer e.g. on routes and crossing of routes.
  • the filter threshold defines the value when an incident probability is indicated.
  • the threshold value may vary according to different vessel type combinations so that, for example, vessel with cargo and/or passenger vessel have lower threshold value than e.g. cargo vessel without cargo, or during nights and/or in ice condition the threshold value may be lower than during day in open water.
  • the threshold value may be e.g. 2%-25%, more preferably 5%-15%.
  • Some other parameters may also be used.
  • the other adjusting parameters may be, for example, circumstance and weather condition as well as time of day. These parameters have an effect on selecting and updating probability matrices, for example, ice condition during winter time as well as wind speed and direction may be parameters determining the probability matrices.
  • the amount of data provided by vessels in maritime traffic is enormous; since each vessel with transmission system transmits data related to the vessel several, approximately ten or more, times per hour.
  • the data e.g. of one week period is stored in a database and then replaced with a newer data.
  • the replacement of the data is performed as a continuous process, but in some embodiments the old data may be removed e.g. every week or every month.
  • vessel's identification information, position, course and speed are needed for statistical prediction and learning of the present system.
  • vessel type, cargo type, with or without cargo, timestamp and destination information can also be utilized.
  • the probability matrices may be defined for each vessel type, cargo type and/or with or without cargo.
  • vessel type, cargo type and/or with or without cargo information may have an effect on e.g. the filtering of the risk.
  • Destination information may be used for e.g. observing the deviation from the route.
  • the data related to maritime traffic may be obtained from the database e.g. every sixth minute. Further, the data of the tracked vessels is assumed to be synchronous with each other or the optional timestamp information may be used to synchronize obtained data.
  • new values are calculated for probability matrixes by using data related to maritime traffic in the database, which is thus used as a learning material. The calculation is performed by using Bayesian estimation described hereinbefore. Generally, only the probability matrixes are updated, which categories the data related to maritime traffic and/or adjusting parameters fall into. The updating of the proba- bility matrixes with new material, which replaces old material, enables continuous learning of the system.
  • the effect of middle data is weighted more in the learning material than the effect of old and/or new data.
  • the portion of the middle data may be for example 50% and, correspondingly, the portion of old and new data 25% each.
  • the portion of the middle data may also be bigger or smaller.
  • the utility of weighing the middle data more is that the old data may be outdated and new data may contain errors.
  • new data is weighted more than old data.
  • the portion of old and new data may be e.g. 25% each.
  • a probability matrix for each vessel to be monitored is selected.
  • a probability matrix is chosen for a vessel depending on the grouping of vessels, for example, vessel type, cargo type, with or without cargo, season of year, weather conditions and time of day.
  • a local risk and global risk of a collision or grounding is calculated by using selected probability matrixes and newest position data of each vessel to be monitored.
  • the local risk is a risk of a collision or grounding on a particular square of the grid.
  • the global risk is the risk for collision or grounding in a sub-area comprised of squares with non-zero local risk. As new position data arrives, these risk measures change, as well as, the related sub-area.
  • the risk calculation performed by using Bayesian estimation of a Markov chain, has been de- scribed in more detail hereinbefore. Preferably up to e.g.
  • 30 order Markov model can be used, so that a possible risk of collision and/or grounding can be estimate preferably 30 minutes - 2 hours before.
  • a standalone system where the system may not have a processor as efficient as processors in control centers, such as VTS, it is possible use e.g. 20 25 order Markov model.
  • an indication of the increased in- cident probability is generated at step 714.
  • the risk indication is a warning indication, such as blinking and/or colored square on the map and/or audible signal, delivered to monitoring and controlling personnel and/or personnel in the vessel or vessels the risk is concerned to.
  • a color chart may be used for indicating the risk level. Generally, in that case the risks under the threshold value are presented with ground color of the map. The colored chart may be divided in e.g. 5-10 risk levels or the risk is presented with sliding color scale from e.g. yellow to red. Alternatively, some other way may also be used to indicate the increased risk.
  • the highest risk level may be e.g. 50% and up.
  • the risk indication system may be configured, in order to avoid collision or grounding of vessel(s), to calculate a steering suggestion, i.e. a suggestion to change the course some particular degrees to some particular direction, for the vessel or the vessels, which the increased risk concern(s) to.
  • the steering suggestion to execute an evasive action is typically calculated for a give-way vessel, i.e. the vessel which is obligated to give way according to maritime regulations, and a stand-on vessel is assumed to keep its course.
  • the steering suggestion is calculated so that the evasive vessel does not end up right away in a new risk situation in its new course.
  • the steering suggestion may then be calculated for the stand-on vessel or for both vessels. However, this is an especially exceptional case and the navigators of both vessels, and typically VTS operator as well, are informed of the situation.

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  • Engineering & Computer Science (AREA)
  • Ocean & Marine Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)

Abstract

L'invention concerne un système d'indication de risque (400) destiné à fournir une indication de probabilité d'incident pour une collision ou un échouage dans un trafic maritime. Le système d'indication de risque (400) est configuré pour obtenir des données associées à un trafic maritime. Les données peuvent comprendre des informations d'identification, une position, une trajectoire et des informations de vitesse d'un ou de plusieurs navires. Le système est configuré pour effectuer un calcul de probabilité d'incident à l'aide des données relatives au trafic maritime, et pour générer une indication de la probabilité d'incident.
PCT/FI2010/050688 2009-09-04 2010-09-06 Système d'indication de risque de voie navigable intelligent et procédé associé Ceased WO2011027037A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FI20095914 2009-09-04
FI20095914A FI20095914A0 (fi) 2009-09-04 2009-09-04 Älykäs vesiväylän riskien indikoimisjärjestelmä ja siihen liittyvä menetelmä

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WO2011027037A1 true WO2011027037A1 (fr) 2011-03-10

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CN102890875A (zh) * 2012-10-15 2013-01-23 浙江大学 一种获取海上智能交通网络的系统碰撞风险的方法
CN103177172A (zh) * 2011-12-22 2013-06-26 中华人民共和国山东海事局 客滚船单船安全评价方法
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WO2017097848A1 (fr) * 2015-12-10 2017-06-15 Hochschule Wismar Procédé et systeme de prévisions de trafic dans des zones maritimes délimitées
WO2017167905A1 (fr) * 2016-03-31 2017-10-05 A.P. Møller - Mærsk A/S Bateau ou navire ayant un système de prévention de collision
US10032381B2 (en) 2011-05-23 2018-07-24 Ion Geophysical Corporation Marine threat monitoring and defense system
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US10071791B2 (en) 2013-11-12 2018-09-11 Ion Geophysical Corporation Comparative ice drift and tow model analysis for target marine structure
US10200113B2 (en) 2017-01-17 2019-02-05 Harris Corporation System for monitoring marine vessels providing expected passenger determination features and related methods
US10302769B2 (en) 2017-01-17 2019-05-28 Harris Corporation System for monitoring marine vessels using fractal processing of aerial imagery and related methods
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CN110598969A (zh) * 2019-06-25 2019-12-20 大连海事大学 一种海上通道突发事件风险预警方法
EP3614363A4 (fr) * 2017-04-20 2020-05-06 Fujitsu Limited Programme de calcul de point dangereux, procédé de calcul de point dangereux et dispositif de calcul de point dangereux
CN111401702A (zh) * 2020-03-06 2020-07-10 南京大学 一种海上交通风险评估方法
US10854090B2 (en) * 2018-09-27 2020-12-01 United States Of America As Represented By The Secretary Of The Navy Collision avoidance system and method for a watercraft
CN112967526A (zh) * 2021-02-01 2021-06-15 上海海事大学 一种基于ais数据的海上交通流基本图绘制方法
CN113012472A (zh) * 2021-03-17 2021-06-22 武汉理工大学 一种适用于vts系统的船舶预警方法、设备及存储介质
CN113128826A (zh) * 2021-03-03 2021-07-16 武汉理工大学 通航风险预测方法、装置和存储介质
CN113851019A (zh) * 2021-09-29 2021-12-28 北京中交通信科技有限公司 一种基于北斗定位的船舶碰撞预警方法及装置
WO2023105260A1 (fr) * 2021-12-09 2023-06-15 Totalenergies Onetech Procédé et dispositif informatique pour générer une carte spatio-temporelle d'un trafic de navires estimé dans une zone
CN116597693A (zh) * 2023-05-25 2023-08-15 广州航海学院 一种内河航运监控系统及方法
RU2808849C1 (ru) * 2023-05-22 2023-12-05 Общество С Ограниченной Ответственностью "Смартгеосистемс" Морская геоинформационная интегрирующая платформа реального времени
CN117437754A (zh) * 2023-10-23 2024-01-23 广州嘉泰软件有限公司 一种水上监测设备及其信息系统
CN118863166A (zh) * 2024-07-25 2024-10-29 三峡电能金舟能源(湖北)有限公司 一种基于历史数据的内河航运多因素会船风险预测方法
WO2024242583A1 (fr) * 2023-05-22 2024-11-28 Общество С Ограниченной Ответственностью "Смартгеосистемс" Plateforme d'intégration de géo-informations maritimes en temps réel
CN120182331A (zh) * 2025-05-23 2025-06-20 中国水产科学研究院渔业工程研究所 一种基于ai的渔船撞击力预测方法

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