KR20090008107A - Method and system for forecasting arrival time of ship - Google Patents

Abstract

A method for forecasting arrival time of ship with data of AIS and system thereof are provided to inform driver or delivery trader delay time by confirming delay time of ship. A receiving station device(42) receives AIS(Automatic Identification System) information, and is connected to an electric communications circuit(41). A processing device(43) is connected through the receiving station device and the electric communications circuit, builds an AIS database(44) by remembering AIS receiving information, divides a sea region in which a ship is sailed into a plurality of regions(A1-A6), writes standard sailing information(45d) about a divided region using the AIS information, builds a standard sailing database(45) by using written standard sailing information, builds a correction database(46) by using a correction table(46d), detects an entry region(A4) of the ship by using the AIS information, and calculates an arrival time of the ship by using the standard sailing information and the correction table.

Description

Ship identification method and system {METHOD AND SYSTEM FOR FORECASTING ARRIVAL TIME OF SHIP}

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a ship identification method and system capable of providing in real time an estimated time of arrival of a ship's destination, particularly a ship equipped with a ship automatic identification system (AIS). The present invention relates to a method and system for predicting ship identification.

In the surrounding waters of various countries around the world, various vessels that serve various purposes come and go, and marine traffic is congested. In particular, ships are concentrated in the Gulf region and the Inland Sea where waters are limited, which is very crowded. Also, due to changes in weather conditions or visibility on the route, it may not be possible to operate according to the sailing plan. Because of this situation, it is very difficult for even a skilled captain or sailor to bring a ship to its destination at a predetermined time. When a delay time occurs when the ship arrives, for example, for cargo ships such as container ships, trucks are dispatched from various places to collect containers loaded in the cargo terminal of the port. Congestion occurs near the gate entrance of the terminal. As a result, in addition to the delay of the ship, there is a vicious cycle of delay caused by the congestion of the truck.

In order to solve such a problem, the invention described, for example in patent document 1 (a vehicle call method and a vehicle call system) is proposed. The invention described in Patent Literature 1 relates to a vehicle call system for calling a vehicle waiting to receive a cargo in a vehicle storage station located at a site separate from the cargo receiving station for receiving the arrived cargo. will be. This invention provides a vehicle waiting place to alleviate the congestion occurring at the cargo terminal. However, when a delay of a ship occurs, there is a problem that the waiting vehicles increase, resulting in congestion.

Moreover, the invention which aims at preventing the delay of a ship itself is also proposed. For example, the invention described in Patent Document 2 (environmental load reduction type sailing plan providing system) allows arrival time to the target port by allowing the passing time within the allowable error for each passing point set in advance along the route at the time of operation of the ship. It is to maintain the timeliness of time. Although the present invention intends to prevent a delay to the ship's destination by newly setting a route or ship speed for a ship bypassed by weather conditions, etc., it is possible to observe the route or ship speed reset by the current weather condition or runaway degree. In some cases, there is a problem that the delay of the ship cannot be prevented as a result.

In addition, an invention for providing real-time driving information of a moving object is also proposed. For example, the invention described in Patent Document 3 (mobile vehicle information providing system and method, and mobile vehicle service information service center) collects position information and time information of a mobile object (database), and thus average speed in a travel path section. And the estimation of the required time are collectively performed in the moving object driving information service center. This invention assumes the vehicle which mainly runs on the road, and it is difficult to apply to the ship which can select an arbitrary route.

By the way, from the point of view of collision prevention and human safety, under the SOLAS Treaty (International Convention for the Safety of Life at Sea), after July 1, 2008, in principle, all passenger ships and international sailing ships with a total tonnage of 300 tons or more and For ships not engaged in international voyages with a total tonnage of 500 tons or more, it is mandatory to mount an automatic identification system (hereinafter referred to as "AIS").

AIS can be obtained from conventional radar and automatic collision avoidance aids (ARPA devices) such as ship position, IMO number, clearness, type of ship, current land course, land speed, bow direction, and operation status by GPS. Various information on the navigation of ships that were not available can be monitored and observed in real time, and more than 100 ships can be captured and tracked at the same time, so that the influence of weather and sea conditions is less, and the target ship can be received within a range that can be received. It is an effective means of monitoring the navigation of a ship since it is low risk of missing it. In addition, if there is no object blocking the radio wave, the AIS can receive information from a ship in the vicinity of the bent part or hidden from the island, and can receive the information in the range of about 20 to 30 nautical miles at sea. In addition, AIS is disclosed in detail in Nonpatent literature 1.

Such AIS can be used to acquire information such as ship position, clearness, type of ship, ship speed, etc., but AIS is for the purpose of monitoring the ship. There is a problem that cannot be done.

[Patent Document 1] Japanese Patent Application Laid-Open No. 2000-123280

[Patent Document 2] Japanese Patent Application Laid-Open No. 2007-45338

[Patent Document 3] Japanese Patent Application Laid-Open No. 2002-117491

[Non-Patent Literature 1] Japan Foundation Library (Electronic Library) 「15 Years of Communication Electrical Engineering Technical Course for Radar (Radar, AIS, VDR, GPS Edition)」 Chapter 3 Automatic Vessel Identification System (AIS) http: // nippon.zaidan.info/seikabutsu/2003/00139/contents/0011.htm

SUMMARY OF THE INVENTION The present invention has been made in view of the above-described problems, and an object thereof is to provide a ship identification prediction method and system that can provide, in real time, an estimated time of arrival at a destination of a ship navigating a sea area using data of an AIS. do.

According to the present invention, there is provided a ship identification prediction method for predicting the identification of the ship by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), and a plurality of sea areas in which the ship sails to a predetermined destination. Divided into zones, setting a standard navigation time to the destination for each of the zones, detecting an entry zone into which the vessel entered by the AIS information, and passing the vessel passing before the entry zone by the AIS information; Compute the transit time required for navigation of the area, calculate the delay time or delay coefficient of the transit area from the transit time and the standard navigation time, and calculate the delay time or delay coefficient to the entry area of the ship by the delay time or delay coefficient. Modifying the standard navigation time in order to predict the estimated time of arrival to the destination This vessel is offered sympathy prediction method.

Further, according to the present invention, a ship identification prediction method for predicting the identification of the vessel by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), the sea area in which the vessel sails to a predetermined destination It divides into a plurality of areas, sets a standard navigation time to the destination for each area, detects an entry area into which the vessel enters by the AIS information, and from the entry area to the destination by the AIS information. Calculates the transit time required for the navigation of other ships in the preliminary transit zone, calculates the delay time or delay coefficient for each of the predetermined transit zones from the transit time and the standard navigation time; Modify the standard navigation time in the entry zone of the vessel by the coefficient to the destination Ship Identification prediction method according to claim to predict the estimated time of arrival is provided.

Here, the said area may be partitioned by the some dividing line toward the said destination, and may be divided | segmented into the cell shape along the standard track of the said ship.

In addition, the standard navigation time is preferably a navigation time calculated by analyzing the navigation time of another ship that has reached the destination just before or the AIS information of a plurality of other ships that have reached the destination in the past. The standard navigation time may be set for each type, scale, or combination thereof. In addition, you may set the standard passage time required for the passage of each area | region instead of the said standard navigation time. It is preferable that the said standard transit time is the transit time calculated by analyzing the transit time of the other ship which passed each area | region immediately before, or the AIS information of the some other ship which passed each area in the past.

In addition, a standard track when the ship sails to the destination is set, a distance correction factor according to the distance from the standard track is set for each of the areas, and in the entry area of the ship by the AIS information. The separation distance from the standard track of may be calculated, and the estimated arrival time may be corrected based on the separation correction coefficient according to the separation distance. Here, the standard track is calculated by analyzing the tracks of other ships that have passed through each area or reached the destination, or AIS information of a plurality of other ships that have passed through each area or reached the destination in the past. It is desirable to keep track. The standard track may be set for each type, scale, or combination thereof.

In addition, the influence coefficient according to the distance from the destination may be set in advance for each of the regions, and the estimated arrival time may be corrected using the influence coefficient. Moreover, you may make it predict the ship position at the arrival time or the present time of the said destination using the said estimated time of arrival.

Further, according to the present invention, a ship identification prediction method for predicting the identification of the vessel by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), the sea area in which the vessel sails to a predetermined destination The AIS information is divided into a plurality of regions, and the standard navigation time to the destination is set for each region, and the correlation between the delay phenomenon occurring in each region and the navigation time to the destination of the ship existing in each region is stored in the AIS information. By analyzing and setting a correlation coefficient for each of the areas, detecting an entry area into which the vessel enters by the AIS information, and detecting a delay area where a delay phenomenon occurs by the AIS information. Compute a delay rate from the standard state and the delay state of, and using the delay rate and the correlation coefficient A ship identification prediction method is provided, characterized in that the estimated time of arrival to the destination is estimated by modifying the standard navigation time.

The area may be partitioned into a mesh shape, may be partially partitioned, and may have a delay observation area for observing a delay phenomenon and a target vessel detection area for detecting a ship for predicting the estimated arrival time, respectively. . The correlation coefficient may be set for each type, scale, or combination thereof. The delay phenomenon may be observed by the ship's ship speed, density or a combination thereof existing in each area. The delay rate may be calculated by the ratio of the standard ship speed or standard density in the delay area and the current ship speed or density in the delay area.

The standard navigation time may be a navigation time of another ship that has reached the destination just before, or may be a navigation time calculated by analyzing AIS information of a plurality of other ships that have reached the destination in the past. The standard navigation time and the correlation coefficient may be set for each type, scale, or combination thereof. Moreover, you may make it predict the ship position at the arrival time or the present time of the said destination using the said estimated time of arrival.

According to the present invention, there is also a ship identification prediction system that receives AIS information transmitted from a ship equipped with a ship automatic identification device (AIS) and predicts the identification of the ship. And a processing apparatus connected with the receiving station apparatus via a telecommunication line, wherein the processing apparatus stores the AIS information to construct an AIS database, and the vessel sails to a predetermined destination. The sea area is divided into a plurality of areas, the standard navigation information is created for each area by using the AIS information, the standard navigation database is constructed, and the standard navigation information is modified using the AIS information to a predetermined condition. Create a correction table to build the correction database, and the vessel by the AIS information Detects an entry area of the vehicle, calculates an estimated time of arrival to the destination of the ship by using the standard navigation information and the correction table corresponding to the entry area, and the correction table is included in the entry area set for each area; There is provided a ship identification prediction system comprising a distance correction coefficient set in accordance with a distance from a standard track of the ship or an influence coefficient set in accordance with a distance from the destination for each region. Here, the standard navigation information may include a standard navigation time to the destination set for each region or a standard passage time required for passing each region set for each region. The processing apparatus may output the estimated arrival time in a state that can be obtained from a terminal device connected to a telecommunication line, and the vessel position at the arrival time or the current time of the destination using the estimated arrival time. May be calculated, and the ship position at the arrival time or the present time of the destination may be output in a state that can be obtained from the terminal equipment connected to the telecommunication line.

According to the present invention, there is also a ship identification prediction system that receives AIS information transmitted from a ship equipped with a ship automatic identification device (AIS) and predicts the identification of the ship. And a processing apparatus connected with the receiving station apparatus via a telecommunication line, wherein the processing apparatus stores the AIS information to construct an AIS database, and the vessel navigates to a predetermined destination. The sea area is divided into a plurality of areas, the standard navigation information is created for each area by using the AIS information, the standard navigation database is constructed, and the standard navigation information is modified using the AIS information to a predetermined condition. Create a correction table to build the correction database, and the vessel by the AIS information Detects an entry area and a delay area in which a delay phenomenon occurs, calculates an estimated time of arrival to the destination of the ship by using the standard navigation information corresponding to the entry area and the correction table, and corrects the correction table Ship identification characterized in that it comprises a correlation coefficient set for each area by analyzing the correlation between the delay phenomenon occurring in an arbitrary area and the navigation time to the destination of the ship existing in each area by the AIS information. A prediction system is provided. Here, the standard navigation information may include a standard navigation time to the destination set for each region or a standard passage time required for passing each region set for each region. The processing apparatus may output the estimated arrival time in a state that can be obtained from a terminal device connected to a telecommunication line, and the vessel position at the arrival time or the current time of the destination using the estimated arrival time. May be calculated, and the ship position at the arrival time or the present time of the destination may be output in a state that can be obtained from the terminal equipment connected to the telecommunication line.

According to the present invention, there is also a ship identification prediction system that receives AIS information transmitted from a ship equipped with a ship automatic identification device (AIS) and predicts the identification of the ship. And a processing apparatus connected with the receiving station apparatus via a telecommunication line, wherein the processing apparatus stores the AIS information to construct an AIS database, and the vessel sails to a predetermined destination. The sea area is divided into a plurality of areas, the standard navigation information is created for each area by using the AIS information, the standard navigation database is constructed, and the standard navigation information is modified using the AIS information to a predetermined condition. Create a correction table to build the correction database, and the vessel by the AIS information Detecting an entry area, and using the standard navigation information corresponding to the entry area and the correction table to detect an estimated time of arrival to the destination of the ship, wherein the standard navigation database and the correction database are type of ship, A ship identification prediction system is provided which is classified according to the size of the ship or a combination thereof. Here, the standard navigation information may include a standard navigation time to the destination set for each region or a standard passage time required for passing each region set for each region. The processing apparatus may output the estimated arrival time in a state that can be obtained from a terminal device connected to a telecommunication line, and the vessel position at the arrival time or the current time of the destination using the estimated arrival time. May be detected, and the ship position at the arrival time or the present time of the destination may be output in a state that can be obtained from a terminal device connected to the telecommunication line.

According to the ship identification method and system of the present invention described above, it is possible to provide in real time the estimated time of arrival of the destination of the ship navigating the sea area. Therefore, the delay time of a ship can be grasped | ascertained, for example, by providing such a delay time to a driver, a delivery company, etc. of a truck, a truck can be dispatched to the cargo terminal according to the arrival of a ship, and the congestion can be alleviated. In addition, when the present invention is applied to a ferry such as a ferry, the mental pain of the user can be alleviated by making the delay time clear. In addition, when the AIS information cannot be received or when the current ship position is to be determined, the ship at the current time is estimated by using the estimated time of arrival, the AIS information (for example, the last received), and the standard track. It can also be inverted and estimated. Moreover, the delay time and the track data can be used to grasp the delay tendency of each ship after the fact, to grasp the master's or crew's skill level, or to use it as a textbook for improving the master's or crew's steering skills.

EMBODIMENT OF THE INVENTION Hereinafter, embodiment of this invention is described using FIGS. 1 is a diagram showing a first embodiment of a ship identification prediction method according to the present invention, in which FIG. 1A is a basic example, and FIG. 1B is a first modification. 2 is a diagram showing a modification of the first embodiment shown in FIG. 1A, FIG. 2A is a second modification, and FIG. 2B is a third modification. to be.

As shown in Fig. 1A, the first embodiment of the ship identification prediction method of the present invention receives the AIS information transmitted from the ship S equipped with the ship automatic identification device AIS, A ship identification prediction method for predicting identification of S), wherein the sea area [port (1)] in which the ship S sails to the destination D is divided into a plurality of regions A (for example, A1 to A6), For each zone A, the standard navigation time T (for example, T1 to T6) to the destination D is set, and the entry area into which the ship S enters (for example, A4) by the AIS information of the ship S. ) And the transit time Δt (e.g. Δt5) required for navigation of the transit zones (e.g., A5, A6) that the vessel S has passed before the entry zone based on the AIS information of the ship S. , Δt6) is calculated, and the delay time td of the passage area is calculated from the passage time Δt and the standard navigation time T, and the delay time td is applied to the entry area of the ship S. Come to modify the time T of the standard navigation and features to predict the estimated time of arrival [ETA (Estimated Time of Arrival)] to the destination (D).

The AIS information includes static information, dynamic information, navigation information and safety information. The static information is information for identifying what kind of ship the target ship is, such as sharpening or gimmick, and includes information such as MMSI number, call sign, sharpness, IMO number, hull length, hull width, ship type, antenna position and the like. The MMSI number is an abbreviation of Maritime Mobile Service Identity and is an identification number assigned to each AIS device. The IMO number is a ship identification number assigned by IMO (International Maritime Authority), and the call sign is a signal rich person. Also called a kanji or call sign, a combination of alphabets and numbers. These MMSI numbers, IMO numbers, call signs and clear lines serve to identify the ship. Dynamic information is information indicating the latest shipbuilding status, such as the target ship position and speed, and includes latitude, longitude, position accuracy, time, earth course, earth speed, bow direction, head angle, and navigation status. Navigation, stranding, out of control, etc.). The navigation information is information about the route and cargo onboard of the vessel, and includes information such as draft, types of dangerous goods, destinations, arrival times, and the like. Safety information is supplementary information about safety. In addition, the AIS information transmitted from the ship does not always include the above four kinds of information, and each information is often transmitted as AIS information individually. For example, dynamic information is typically transmitted every three minutes and static information is transmitted every six minutes. The present invention seeks to predict in real time the estimated time of arrival ETA to the destination D of the ship S based on the AIS information.

The above sea area shown in FIG. 1A shows the case of the port 1, and the areas A1 to A6 are drawn by drawing the dividing lines L0 to L6 from the vicinity of the entrance of the port 1 toward the destination D. FIG. Is setting. In this way, a system of dividing the entire sea area into a plurality of regions by the dividing line is called a line dividing method. The information of the destination D can be obtained from the AIS information. The intervals of the dividing lines L for setting the respective regions A are arbitrary and need not be equal intervals, nor are they limited to the number shown. In addition, the division line L may be drawn so that the area A may be set to the sea off the harbor 1, or the area A may be set from the starting point to the destination D. FIG. In addition, as shown in the third modification of FIG. 2B, when the destination D exists in the coastal portion 21, the dividing line L1 for setting the plurality of regions A1 to A4. To L4) may be curved.

The standard navigation time T1 to T6 is the standard navigation time T from the point of entry to each of the areas A1 to A6 to the destination D, and is the destination D from each of the division lines L1 to L6. It can also be called standard navigation time (T). Each standard navigation time T1-T6 is set as the navigation time of the other ship which reached the destination D just before ship S, for example. The navigation time of other ships can be calculated from AIS information. By using the data of the other ship just before, the standard navigation time (T1 to T6) which simulates the runaway degree on the route of ship S and the state near weather conditions can be obtained. Moreover, since a ship speed differs according to the kind and magnitude | size of a ship, the ship just before you may make it the ship S and the ship of the same type. For example, as a kind of ship, a container ship, a tanker, a passenger ship, a car exclusive ship, a bulk carrier, a cargo ship, LNG ship, etc. are considered. The size of the ship can also be determined by the length of the ship or by the total tonnage. These information can basically be obtained from AIS information. In addition, even when the AIS information lacks information necessary for specifying the type and size of the ship, as described above, the AIS information has static information for specifying the ship such as an MMSI number or an IMO number. The required information can also be obtained from a separate route in contrast to the separately prepared vessel information master data.

In addition, you may set each standard navigation time T1-T6 by the navigation time calculated by analyzing the AIS information of several other ship which reached the destination D in the past. For example, each standard navigation time T1 to T6 may be set by the average value, or may be set in consideration of the standard deviation statistically. Also in this case, the standard navigation times T1 to T6 may be set according to the type and scale of the vessel.

The entry area A4 can be grasped from the AIS information of the ship S that is periodically transmitted. Specifically, AIS information (position, latitude, bow direction, etc.) of the ship S is compared with the position of the dividing lines L1 to L6, and which dividing line L has crossed the ship S? You can figure it out. In the embodiment shown in FIG. 1A, the case where the ship S crosses the dividing line L4 while taking the track R, that is, enters the area A4, is illustrated.

The passage area A5 is an area where the ship S has passed before the entry area A4, and can easily grasp the passing areas A5 and A6 if the entry area A4 can be grasped. And the transit time (DELTA) t5, (DELTA) t6 which the ship S actually needed for navigation of the passage area | region A5, A6 is calculated using AIS information of the ship S. Since the AIS information is periodically transmitted as described above, when the AIS information at the point closest to the dividing lines L4 and L5 forming the passage area A5 is used, the passage times? T5 and? T6 can be calculated.

In addition, in the passage region A5, since the standard navigation times T4, T5, and T6 are set for each of the division lines L4, L5, and L6, the standard passage time ΔT5 of the passage region A5 is ΔT5 = T5-T4. By the calculation formula, the standard passage time ΔT6 of the passage region A6 can be obtained by the formula of ΔT6 = T6-T5, respectively. If the difference between the standard passing times ΔT5 and ΔT6 and the passing times Δt5 and Δt6 is obtained, the delay times td5 and td6 of each passing area can be calculated, and the sum of the respective delay times td5 and td6 is calculated. By calculating | requiring, the delay time td of the ship S can be calculated. If the value of the delay time td is positive, the vessel S is delayed from the standard navigation time T. If the value of the delay time td is negative, the vessel S is standard. The case of advancing earlier than the navigation time T is shown.

The estimated time of arrival ETA of the ship S is a time calculated by modifying the standard navigation time T4 in the entry area A4 to the delay time td, that is, ETA = T4 + td. The first embodiment of the present invention is characterized by predicting the estimated arrival time ETA based on the actual delay in the magnetic vessel S. FIG. In this way, by calculating the actual delay time td of the ship S, it is expected to arrive with high accuracy without analyzing the delay phenomenon (weather conditions, visibility, congestion degree, etc.) in which the ship S is complicated. ETA can be predicted in real time. In addition, instead of the delay time td, it is calculated by the formula of the delay coefficient which is the ratio of the passage time Δt to the standard passage time ΔT, that is, the delay coefficient = the passage time Δt / standard passage time ΔT. The standard navigation time T may be corrected by the numerical value. For example, in the above-mentioned embodiment, the estimated time of arrival ETA of the ship S is predicted by the calculation formula of ETA = delay coefficient x T4.

In addition, if such highly accurate ETA can be predicted, for example, the ETA is provided to the driver of the truck, the delivery company, etc., so that the truck can be placed at the cargo terminal in accordance with the arrival of the ship. Can be dispatched to alleviate congestion. In addition, by providing such an estimated arrival time (ETA) to the operating company, such as ferry, or the user, the mental pain of the user can be alleviated. In addition, when the AIS information cannot be received or when the current ship position is to be confirmed, the ship position at the current time can be inverted using the estimated arrival time (ETA) and the AIS information (heading direction, ship speed, etc.). have. ETA and track data can also be used to grasp the delay tendency of each ship afterwards, to grasp the master's or crew's proficiency, or to improve the master's or crew's steering skills. .

Next, a first modification of the first embodiment described above will be described. In the first modification shown in Fig. 1B, the standard track Rs when the ship S sails to the destination D is set, and the standard track Rs is provided for each of the areas A1 to A6. Set the separation correction coefficient β according to the separation distance G (for example, G1 to G3) from the standard track, and from the standard track Rs in the entry area A4 by the AIS information of the ship S The separation distance g is calculated and the estimated arrival time ETA is corrected based on the separation correction coefficient β according to the separation distance g.

The standard track Rs is set by, for example, the track of another ship that has just passed each area A1 to A6 or the track of another ship that has reached the destination D just before. Since the route may differ depending on the ship type and scale of the ship S, the immediately preceding ship may select the ship of the same type as the ship S. Specifically, information about the type and scale of the ship is extracted from the AIS information of the ship S, the same type ship that has just passed from the AIS information of another ship is selected, and the wake is drawn from the AIS information of the same type ship. Set as the standard track Rs. When drawing a track, it is enough to connect the ship's position (latitude, longitude, etc.) of AIS information. In addition, the standard track Rs does not necessarily have to be continued between each area | region A1-A6.

The standard track Rs may be a track calculated by analyzing the AIS information of a plurality of other ships that have passed through each of the areas A1 to A6 or have reached the destination D in the past. For example, the standard track Rs may be set by an average value or may be set statistically in consideration of the standard deviation. Also in this case, the standard tracks Rs may be set according to the type and scale of the vessel. In addition, when setting the standard track Rs, when the track of the same ship overlaps in each area | region A1-A6, by using this invention proposed by this inventor (patent 3882025), a single track can be used. You can get it.

The spacing correction coefficient β adds a delay that occurs from the deviation of the ship S and the standard track Rs (spacing distance g), and more accurately predicts the estimated time of arrival ETA. Correction factor. The standard track (Rs) is basically a track close to the scheduled route established before the voyage, and if the ship's track (R) deviates from the scheduled route, the standard route is basically returned to the scheduled route, so the route tends to be long. There is a delay in. The delay correction factor β is added to this delay. The separation correction coefficient β is set for each separation distance G1 to G3 from the standard track Rs, as shown in FIG. 1B. For example, when the ship S enters the area A4, when the entry position of the ship S is in the area between the distance G1 from the standard wake Rs, β41, the distance ( When it is in the area between the separation distance G2 and G1), it is set as (beta) 42 when it exists in the area between the separation distance G3 and the separation distance G2.

The separation distances G1 to G3 are set based on a normal distribution, for example, as shown in FIG. 3 is a diagram showing a method for setting the separation correction coefficient, in which FIG. 3A shows a case of dividing line L4, and FIG. 3B shows a case of dividing line L3. First, the entry position on the dividing line L when entering each area | region A from the past AIS information of the ship is detected, and the normal distance is calculated by calculating the distance G with respect to the standard track Rs. FIG. 3A shows a normal distribution when entering the area A4 (divided line L4), and FIG. 3B shows a normal distribution when entering an area A3 (divided line L3). Accordingly, it can be seen that the dispersion is large in the case shown in FIG. 3A and the dispersion is small in the case shown in FIG. In each case, the separation distances G1 to G3 are set using the standard deviation σ. In other words, the separation distance G1 is set to 1σ, the separation distance G2 is set to 2σ, and the separation distance G3 is set to 3σ. If it is set to 3 sigma, 99.73% of the whole will be contained, and it will be enough, but you may set the space | interval correction coefficient (beta) to the part more than 3 sigma.

The separation correction coefficient β analyzes (average or statistically analyzes) the relationship between the separation distances G1 to G3 and the delay time td of the time of arrival at the destination D of the ship entering each region. Set the value. The separation correction coefficient beta in the case where it is on the standard track Rs is 1, and it is guessed that it will become a value larger than 1 as the separation distance g of the ship S becomes large. Of course, depending on the entry position, the standard track Rs may be short cut, but in such a case, the value becomes smaller than one. Then, the estimated arrival time ETA is corrected by multiplying the estimated arrival time ETA by the method shown in the first embodiment by the separation correction coefficient β.

In the above-described first embodiment and variations thereof, when estimating the estimated time of arrival ETA, the standard navigation times T1 to T6 from the point of entry to each of the areas A1 to A6 to the destination D are determined. Although used, it is also possible to predict the estimated arrival time ETA by setting the standard transit times DELTA T1 to DELTA T6 as in the second modification shown in Fig. 2A. In the first embodiment, for example, the standard transit time ΔT5 was calculated as the difference between the standard navigation time T5 and the standard navigation time T4, but in the second modification shown in FIG. The standard transit times (ΔT1 to ΔT6) of each region are set in advance from the AIS information, and the standard navigation time (T4) is calculated as the sum of the standard transit times (ΔT1 to ΔT4). Of course, you may set both the standard passing time (DELTA) T1-(DELTA) T6 and the standard navigation time (T1-T6) beforehand, and if one is set previously, the other can be calculated by calculating.

In addition, in 1st Embodiment mentioned above and its modification, the influence coefficient (alpha) according to the distance from the destination D is set previously for every area | region A1-A6, and it arrives using the influence coefficient (alpha). The estimated time ETA may be corrected. This influence coefficient has a greater effect on the estimated arrival time ETA as the delay in the area A closer to the destination D, and a larger effect on the estimated arrival time ETA as the delay in the far area A. The correction factor is set in consideration of the small influence. It becomes 1 when the delay in the arbitrary area A is reflected in the arrival estimated time ETA as it is. And when the influence coefficient (alpha) is closer to the destination D than the area | region A which is 1, it becomes a value larger than 1, and when the influence coefficient (alpha) is farther from the destination D than the area | region A which is one. Is less than 1. However, at the confluence point where the plurality of routes runaway, the influence on the estimated arrival time ETA is large, so the influence coefficient may be set to a value larger than one. The influence coefficient α may be statistically analyzed and set from, for example, AIS information of past vessels.

Next, the ship identification prediction system which concerns on the 1st modified example of 1st Embodiment mentioned above is demonstrated. 4 is a configuration diagram showing a ship identification prediction system according to a first modification of the first embodiment shown in FIG. 1B.

The ship identification prediction system of this invention shown in FIG. 4 is a ship identification prediction system which receives AIS information transmitted from ship S equipped with ship automatic identification apparatus AIS, and predicts identification of ship S. FIG. And a receiving station apparatus 42 capable of receiving AIS information and distributing it by the telecommunication line 41, and a processing unit 43 connected to the receiving station apparatus 42 via the telecommunication line 41. The processing unit 43 stores the AIS reception information to construct the AIS database 44, divides the sea area where the ship S sails to a predetermined destination into a plurality of areas A1 to A6, and divides the AIS information. Correction table 46d for creating a standard navigation database 45d for each area A1 to A6 to construct a standard navigation database 45, and modifying the standard navigation information 45d to predetermined conditions using the AIS information. Build a calibration database (46). , The entry area A4 of the ship S is detected by the AIS information, and to the destination D of the ship S using the standard navigation information 45d and the correction table 46d corresponding to the entry area A4. ETA is calculated.

The telecommunications line 41 is a distributed type that is constructed by connecting various communication lines (a public line such as a telephone line, an ISDN line, an ADSL line, a dedicated line, and a wireless communication network) using a communication protocol (TCP / IP). It is an IP network, and this IP network also includes a LAN such as an intranet (network within an enterprise) or a home network by 10BASE-T or 100BASE-TX. 4, various terminal devices 47, such as a server terminal, a personal computer terminal, and a mobile telephone terminal, may be connected to this telecommunication line 41. FIG.

Although not shown, the receiving station apparatus 42 is generally composed of an antenna, an AIS signal receiver, and a computer. The antenna has the functions of an AIS receiving antenna and a GPS receiving antenna and may be integrated or separate. The AIS signal receiver has a function of data processing so that the AIS information received by the antenna can be used in a downstream system. Hereinafter, the AIS information downstream from this AIS signal receiver is called "AIS reception data." The computer is a device for transmitting AIS received data sent from the AIS signal receiver to the processing device 43 in real time, and for establishing a local database for data backup in case of communication failure. In addition, in this computer, the reception date and time are added to the AIS reception data at the AIS receiving apparatus in case the delivery date and time information is missing in the AIS reception data or the delivery date and time cannot be read without decoding. You may give it. In addition, the receiving station apparatus 42 may be arrange | positioned so that the sea area required for the estimation of arrival estimated time ETA may be covered, and one or more may be sufficient as it. Of course, the far-reaching AIS receiver apparatus which could receive AIS information worldwide using a satellite etc. may be sufficient.

The processing device 43 includes a CPU (central processing device), a storage device such as a RAM, a ROM, a hard disk, an input device such as a keyboard, and an output device such as a display. The storage device stores an AIS database 44, a standard navigation database 45, a calibration database 46, a program for constructing each of the databases 44, 45, 46, a program for calculating an estimated time of arrival (ETA), and the like. By storing a predetermined program in a CPU, each database 44, 45, 46 is constructed, the estimated arrival time ETA is calculated, or the estimated estimated arrival time ETA is output. Although only one processing apparatus 43 is shown here, a plurality of processing apparatuses 43 (for example, for each database) may be arranged to share the function. The storage device for storing each database 44, 45, 46 may be a storage medium external to the processing device 43 or connected via the telecommunication line 41.

The AIS database 44 is a database of AIS received data distributed from the receiving station apparatus 42 and accumulated. When making database, so-called relational database management system (RDBMS) is used. This AIS database 44 is a database on which the standard navigation database 45 and the correction database 46 are based, and is a database in which all AIS information of the ship in the range where the AIS information can be received is collected. When constructing the AIS database 44, the invention proposed by the inventors of the present invention (Patent No. 3882025) is used to store the AIS received data of the same vessel at the time of obtaining the AIS received data without combining them. It is also possible to exclude duplicate data when using the data. By using this invention, the data processing at the time of data accumulation can be greatly reduced, and the system can be simplified and the processing can be speeded up.

In addition, the processing apparatus 43 may be connected to the ship information master database (not shown) databased separately from the AIS database 44. The vessel information master database may be stored in the hard disk of the processing apparatus 43 similarly to the AIS database 44, or may be a database stored in an external computer connected via the telecommunication line 41. This ship information master database considers that not all data is necessarily entered in the static information of the AIS information transmitted from the ship, and that the information that cannot be obtained from the AIS information may be necessary. It is used to supplement.

The standard navigation database 45 extracts AIS received data of the AIS database 44 under predetermined conditions and, if necessary, performs a predetermined calculation to database and accumulate the standard navigation information 45d. For example, as shown in FIG. 4, the standard navigation database 45 stores the standard navigation times T1 to T6 for each of the areas A1 to A6 according to the type and scale of the vessel. Here, the table of the standard navigation information 45d in the case where the ship type is a container ship and the total tonnage is 90,000 to 100,000 tons is shown. This table may be prepared for each ship type or for each total tonnage. As the ship type, container ships, tankers, passenger ships, car charters, bulk carriers, cargo ships, LNG carriers and the like are considered. In addition, the size of the vessel may be determined using the length of the vessel in addition to the total tonnage. In the first embodiment, the standard navigation times T1 to T6 are the standard navigation times from the point of entry to each of the areas A1 to A6 to the destination D (or the destination (from each division line L1 to L6). Standard navigation time up to D), the standard navigation database 45 is set for the standard navigation time T1 to T6 for each region A1 to A6 or for each of the division lines L1 to L6.

Here, the standard navigation times T1 to T6 are, for example, the navigation time of another ship that has reached the destination D just before the ship S, or the plurality of other ships that have reached the destination D in the past. It is set by the navigation time calculated by analyzing the AIS information. Based on these standard navigation time T1 to T6 setting methods, the processing apparatus 43 performs search, calculation, analysis, etc. using the AIS received data of the AIS database 44, and the standard navigation time T1. To T6). In addition, about the setting method of the standard navigation time T1-T6, since it was as having demonstrated in description of the ship identification method, detailed description is abbreviate | omitted here.

The correction database 46 corrects the estimated arrival time ETA calculated by the processing apparatus 43 so that the accuracy is higher, and the correction coefficients (the influence coefficient α and the spacing generated using the AIS received data) are separated. The correction coefficient β is a database and accumulated. The correction database 46 is, for example, a correction table 46d in which the influence coefficient α and the distance correction coefficient β are set for each of the regions A1 to A6 according to the type and scale of the vessel, as shown in FIG. Has Here, the correction table 46d is shown when the ship type is a container ship and the total tonnage is 90,000 to 100,000 tons. This correction table 46d may be created for each ship type or may be created for each total tonnage. As the ship type, a container ship, a tanker, a passenger ship, a car exclusive ship, a bulk carrier, a cargo ship, an LNG carrier, etc. are considered. In addition, the size of the vessel may be determined using the length of the vessel in addition to the total tonnage. In the first embodiment, the estimated arrival time ETA is calculated at the time when the ship S enters each of the regions A1 to A6, that is, at the time when the ship S crosses each of the dividing lines L1 to L6. Since the influence coefficient (alpha) and the space | interval correction coefficient (beta) are set for every area | region A1-A6 or every division line L1-L6. The method of setting the influence coefficient α and the separation correction coefficient β is the same as described in the description of the ship identification predicting method, and thus detailed description thereof is omitted.

The case where the estimated arrival time ETA of the ship S in the state shown in FIG. 1B is calculated using the ship identification prediction system of this invention shown in FIG. 4 is demonstrated, for example.

(1) The AIS information of the ship S is transmitted to the processing apparatus 43 via the receiving station apparatus 42 and the telecommunication line 41.

(2) The processing apparatus 43 stores the AIS reception data of the ship S in the AIS database 44, and the ship S enters the area A4, that is, the ship S divides the line. Detects beyond L4.

(3) The processing device 43 calculates a predetermined standard track Rs using the AIS received data of the AIS database 44, and separates the distance g from the standard track Rs of the ship S. It calculates and detects that the ship S entered the area | region which is the separation distance G2.

(4) The processing apparatus 43 accesses the AIS database 44 and calculates passage times Δt5 and Δt6 of the passage areas A5 and A6 of the ship S. FIG.

(5) The processing apparatus 43 accesses the standard navigation database 45, calculates the standard transit times DELTA T5 and DELTA T6 of the transit areas A5 and A6 from the standard navigation times T4 to T6, and enters the entry area. The standard navigation time (T4) of A4 is extracted.

(6) The processing apparatus 43 calculates the delay times td5 and td6 of the respective passage regions A5 and A6 from the standard passage times ΔT5 and ΔT6 and the passage times Δt5 and Δt6 to delay the ship S. Calculate the time td (= Δt5 + Δtd6).

(7) After accessing the correction database 46, the processing apparatus 43 extracts the separation correction coefficient β42 which is the influence coefficient α4 and the separation distance G2 in the area A4.

(8) The processing apparatus 43 calculates the estimated arrival time ETA by the formula of ETA = T4 × β42 + td × α4.

(9) The processing device 43 outputs the estimated arrival time ETA to a predetermined medium (display device, terminal device 47, etc.).

According to the ship identification prediction system of the present invention described above, it is possible to provide the estimated time of arrival ETA of the destination D of the ship S sailing in the sea area in real time. In addition, when the estimated time of arrival (ETA) is displayed on a web that can be viewed through a telecommunication line, or when it is posted and delivered in an e-mail, the operator, passenger, etc. of the truck driver, delivery company, ferry, etc. ETAs can be easily obtained by using terminal devices 47 such as mobile phone terminals, car navigation terminals, personal computer terminals, and server terminals to ease congestion of cargo terminals or It can relieve pain. In addition, when the AIS information cannot be received or when the current ship position is to be confirmed, the ship position at the current time can be inverted using the estimated arrival time (ETA) and the AIS information (heading direction, ship speed, etc.). have. In addition, when the estimated arrival time (ETA) and the track data are stored in the storage device of the processing unit 43 or the like, the delay tendency is identified for each ship afterwards, the master's or sailor's skill level is mastered, or the master's or sailor's steering technique. It can also be used as a textbook for improvement.

Next, a second embodiment of a ship identification prediction method according to the present invention will be described. 5 is a diagram showing a second embodiment of a ship identification prediction method according to the present invention, in which FIG. 5A is a basic example, and FIG. 5B is a first modified example. 6 is a diagram showing a modification of the second embodiment, FIG. 6A is a second modification, and FIG. 6B is a third modification. In addition, in 2nd Embodiment, description is abbreviate | omitted about the content overlapping with 1st Embodiment.

As shown in Fig. 5A, the second embodiment of the ship identification predicting method of the present invention receives the AIS information transmitted from the ship S equipped with the ship automatic identification device AIS, and the ship ( A ship identification prediction method for predicting identification of S), wherein the sea area [port 1] in which the ship S sails to the destination D is divided into a plurality of regions A (for example, A1 to A11), Standard transit time ΔT (for example, ΔT1 to ΔT11) is set for each region A, and the entry area (for example, A7) in which the ship S enters is detected by the AIS information, and the AIS information is detected. Pass required for navigation of other ships (eg, Sd, S1, S2, S3, S5) in the predetermined passage area (for example, A1 to A7) from the entry area to the destination D by The time Δt is calculated, and the delay coefficient γ for each predetermined pass area is calculated from the pass time Δt and the standard pass time ΔT, and the delay coefficient ( ) Predicts the estimated time of arrival (ETA) to the destination (D) by modifying the standard navigation time (T) (sum of the standard transit times (ΔT)) in the entry area of the ship (S). do.

In this second embodiment, the delay coefficient γ of the other vessels Sd, S1, S2, S3, S5 is different from the delay time td of the own vessel S. The main feature is to predict the ETA. In this way, the estimated arrival time (ETA) of the own ship S is estimated in consideration of the delay situation of other ships, thereby predicting the arrival of weather conditions, visibility, congestion degree, etc. immediately before on the route to the destination D. Can be reflected in time ETA. In addition, the division | segmentation method of the area | region A is employ | adopted here (it is called cell division system) which divides into the cell shape along the standard track Rs.

Although the size of the cells in each area A is arbitrary, for example, if the AIS information of a ship that has arrived at the destination D in the past is statistically analyzed, the width of the cell is set to be within a range of ± 3σ when expressed as a normal distribution. do. At this time, the shape of the cell may be changed according to the type or scale of the ship, or the shape of the cell common to all types of ships may be set using the AIS information of all the ships. In the basic example shown in Fig. 5A, the cells have a rectangular shape and are aligned in a constant direction, and the regions A1 to A11 are set so that the center of each cell follows the standard track Rs. In addition, the cell may have a rectangular shape aligned along the traveling direction of the standard drop Rs, as in the first modification shown in FIG. 5B. In this case, the shape of the cell in the straight portion of the standard track Rs is set to be rectangular, and the shape of the cell in the curved portion is set to be trapezoidal.

In the second embodiment, it is determined in which cell (regions A1 to A11) the detection position according to the AIS information of the vessel S exists, and the vessel S is to each of the regions A1 to A11. In this case, it is determined that the area has been entered at the time of the first detection. That is, in the state shown in Fig. 5A, the area A7 is set as the entry area A7 at the time when the ship S is first detected in the area A7. When the entry area A7 is determined, the predetermined passing areas A1 to A7 to the destination D are determined. Therefore, the standard navigation time T of the ship S can be calculated as the sum of the standard transit times ΔT1 to ΔT7. In addition, although the case where the standard passage time (DELTA) T1-(DELTA) T11 is set for every area | region A1-A11 was demonstrated, the standard navigation time T1-T11 is set for every area | region A1-A11, and area | region A1-A11 is carried out. The standard transit times ΔT1 to ΔT11 for each A11) may be calculated from the standard navigation times T1 to T11. For example, the standard passage time DELTA T7 in the entry area A7 is calculated by the formula of DELTA T7 = T7-T6.

After the predetermined passing areas A1 to A7 are determined, the delay coefficient γ of each of the predetermined passing areas A1 to A7 is calculated. For example, suppose that there are other ships Sd and S1 in the area A1, another ship S2 in the area A2, another ship S3 in the area A3, and another ship S5 in the area A5, as shown in Fig. 5A. . In addition, the other ship Sd is a ship already arriving at the destination (D). First, the ship which passed each predetermined | prescribed passage area | region A1-A7 immediately before ship S is identified. The other ship Sd for the area A1, the other ship S1 for the area A2, the other ship S2 for the area A3, the other ship S3 for the area A4, and the other ship S5 for the area A6 can be specified. Here, about the areas A5 and A7, no other ship exists in the areas A4 and A6 adjacent to the destination D side. In this case, a method of selecting another vessel that has just passed through areas A5 and A7, that is, another vessel S3, S5 as a vessel that has just passed, a vessel that has just passed the vessel Sd arriving at the destination D As a selection method, a method of treating as a vessel which passed immediately before it does not exist is considered.

Next, after specifying other ships Sd, S1, S2, S3, and S5 of the ship S, the passage times Δt1 to Δt7 of the respective scheduled passage areas A1 to A7 are calculated. The passage times Δt1 to Δt7 can be easily calculated from the AIS information of the other ships Sd, S1, S2, S3, and S5. Here, when "the ship which passed just before" does not exist, the standard passing time (DELTA) T is substituted as the passing time (DELTA) t. And the delay coefficient (gamma) is computed by the ratio of each passing time (DELTA) t1-(DELTA) t7 with respect to each standard passing time (DELTA) T1-(DELTA) T7, ie, (gamma) = (DELTA) t / (DELTA) T. For example, suppose that another ship S5 requires the passage time Δt6 of the predetermined passage area A6 to be twice as long as the standard passage time ΔT6, and γ6 = 2.0. The delay coefficient γ in the case of substituting the standard passage time ΔT for the passage time Δt is set to γ = 1.0.

The estimated time of arrival ETA of the ship S is calculated by the formula of ETA = ΔT1 × γ1 + ΔT2 × γ2 + ΔT3 × γ3 + ΔT4 × γ4 + ΔT5 × γ5 + ΔT6 × γ6 + ΔT7 × γ7. Instead of the delay coefficient γ, similarly to the first embodiment, the delay times td1 to td7 of the other ships Sd, S1, S2, S3, and S5 in the respective scheduled passage areas A1 to A7 are calculated and ETA may be calculated. In this case, the estimated time of arrival (ETA) of the ship S is calculated by the formula of ETA = ΔT1 + td1 + ΔT2 + td2 + ΔT3 + td3 + ΔT4 + td4 + ΔT5 + td5 + ΔT6 + td6 + ΔT7 + td7 .

Next, the second modification and the third modification of the above-described second embodiment will be described. 6A and 6B show the modification according to the separation distance g from the standard track Rs (for example, G1 to G3) for each of the regions A1 to A11. The separation distance correction coefficient β is set, the distance distance g from the standard track Rs in the entry area A7 is calculated from the AIS information of the ship S, and the distance correction according to the separation distance g is calculated. The estimated time of arrival ETA is modified based on the coefficient β. 6A is a modification in which the spacing correction coefficient β is introduced into the basic example of the second embodiment shown in FIG. 5A, and FIG. It is a modification which introduce | transduced the space | interval correction coefficient (beta) into the 1st modification of 2nd Embodiment shown in B). Since the space | interval correction coefficient (beta) is as having demonstrated in description of 1st Embodiment, detailed description is abbreviate | omitted here.

In addition, in 2nd Embodiment mentioned above and its modification, the influence coefficient (alpha) according to the distance from the destination D is set previously for every area | region A1-A11, and it arrives using the influence coefficient (alpha). The estimated time ETA may be corrected. Since the influence coefficient (alpha) is as having demonstrated in description of 1st Embodiment, detailed description is abbreviate | omitted here.

Next, the ship identification prediction system which concerns on 2nd Embodiment mentioned above is demonstrated. Here, FIG. 7 is a block diagram which shows the ship identification prediction system which concerns on the 2nd modified example of 2nd Embodiment shown to FIG. 6 (A). In addition, the same code | symbol is attached | subjected to the same part as the ship identification prediction system shown in FIG. 4, and the overlapping description is abbreviate | omitted.

The ship identification prediction system of this invention shown in FIG. 7 is a ship identification prediction system which receives AIS information transmitted from ship S equipped with ship automatic identification apparatus AIS, and predicts identification of ship S. FIG. And a receiving station apparatus 42 capable of receiving AIS information and distributing it by the telecommunication line 41, and a processing unit 43 connected to the receiving station apparatus 42 via the telecommunication line 41. The processing unit 43 stores the AIS information, constructs an AIS database 44, divides the sea area where the ship S sails to a predetermined destination into a plurality of areas A1 to A11, and uses the AIS information. A standard navigation information 45d for each area A1 to A11 to construct a standard navigation database 45, and a correction table 46d for modifying the standard navigation information 45d to predetermined conditions using the AIS information. A correction database 46 by creating a Detecting the entry area A7 of the ship S by the S information, predicting the arrival to the destination D of the ship S using the standard navigation information 45d and the correction table 46d corresponding to the entry area A7. The time ETA is being calculated.

The standard navigation information 45d of the standard navigation database 45 shown in FIG. 7 shows a table in which the ship type is a container ship and the total tonnage is 90,000 to 100,000 tons. In the table of the standard navigation information 45d, the standard passage times DELTA T1 to DELTA T11 are set for each of the areas A1 to A11. These standard transit times ΔT1 to ΔT11 are calculated by the AIS received data of the AIS database 44. Further, the standard transit times ΔT1 to ΔT11 are, for example, navigation times of other ships Sd, S1, S2, S3, and S5 that have passed through the respective areas A1 to A11 just before the vessel S, It is set by the navigation time calculated by analyzing the AIS information of several other ship which passed each area | region A1-A11 in the past.

The correction table 46d of the correction database 46 shown in FIG. 7 shows the correction table 46d when the ship type is a container ship and the total tonnage is 90,000 to 100,000 tons. In the correction table 46d, the influence coefficient α and the separation correction coefficient β are set for each of the regions A1 to A11.

The case where the estimated arrival time ETA of the ship S in the state shown in FIG. 6A is calculated using the ship identification prediction system of this invention shown in FIG. 7 is demonstrated, for example.

(1) The AIS information of the ship S is transmitted to the processing apparatus 43 via the receiving station apparatus 42 and the telecommunication line 41.

(2) The processing apparatus 43 stores the AIS reception data of the ship S in the AIS database 44 and detects that the ship S has entered the area A7.

(3) The processing device 43 calculates a predetermined standard track Rs using the AIS received data of the AIS database 44, and calculates the separation distance g from the standard track Rs of the ship S. It calculates and detects that the ship S entered in the area | region which is the separation distance G2.

(4) The processing apparatus 43 specifies the predetermined passage areas A1 to A7 from the entry area A7 of the ship S, and precedes other ships Sd, S1, and S2 from the AIS received data of the AIS database 44. , S3, S5) is specified.

(5) The processing apparatus 43 calculates the passage time (Δt1 to Δt7) of each of the predetermined passage areas A1 to A7 from the AIS received data of the other ships Sd, S1, S2, S3, and S5.

(6) The processing apparatus 43 accesses the standard navigation database 45, and extracts the standard passage times ΔT1 to ΔT7 of the predetermined passage areas A1 to A7.

(7) The processing apparatus 43 calculates delay coefficients γ1 to γ7 from the passage times Δt1 to Δt7 and the standard passage times ΔT1 to ΔT7.

(8) The processing apparatus 43 accesses the correction database 46 to extract the influence coefficients α1 to α7 of the predetermined passage areas A1 to A7 and the separation correction coefficient β72 of the separation distance G2 in the entry area A7. do.

(9) The processing apparatus 43 determines the estimated time of arrival ETA by ETA = ΔT1 × γ1 × α1 + ΔT2 × γ2 × α2 + ΔT3 × γ3 × α3 + ΔT4 × γ4 × α4 + ΔT5 × γ5 × α5 + It calculates by the formula of (DELTA) T6 * (gamma) 6 * (alpha) 6+ (DELTA) T7 * (gamma) 7 * (alpha) 7 * (beta) 72.

(10) The processing device 43 outputs the estimated arrival time ETA to a predetermined medium (display device, terminal device 47, etc.).

In the calculation of the estimated arrival time ETA described above, by analyzing past AIS reception data, for example, the ship S that has entered the area that is the separation distance G2 of the entry area A7 is separated from the next area A6. ETA = ΔT1 × γ1 × α1 + ΔT2 × γ2 × α2 + ΔT3 × γ3 × α3 + ΔT4 × γ4 × α4 + ΔT5 × γ5 × α5 + ΔT6 × γ6 × α6 × The estimated arrival time ETA may be calculated by a calculation formula of β61 + ΔT7 × γ7 × α7 × β72.

Next, a third embodiment of a ship identification prediction method according to the present invention will be described. 8 is a diagram showing a third embodiment of a ship identification prediction method according to the present invention. 9 is a diagram showing a modification of the third embodiment, in which FIG. 9A shows a first modification and FIG. 9B shows a second modification.

As shown in Fig. 8, the third embodiment of the ship identification prediction method according to the present invention receives ship AIS information transmitted from a ship equipped with a ship automatic identification device (AIS) and identifies the ship by identifying ship identification. It is a prediction method and divides the sea area which the ship S sails to the predetermined destination D into several area | region A (for example, A1-A169), and the standard navigation time to the destination D for every area | region A ( T) (for example, T1 to T169) is set, and the correlation between the delay phenomenon occurring in each area A and the navigation time t to the destination D of the ship existing in each area A is recorded in the AIS information. The correlation coefficient δ is set for each area A, the entry area (for example, A56) in which the ship S enters is detected by the AIS information, and the delay in which the delay phenomenon is generated by the AIS information. Detect an area (e.g., A37, A59, A86, A116, A140) The delay rate (ε) is calculated from the standard state and the delay state of the system, and the standard navigation time T (for example, T56) of the entry area is modified by using the correlation coefficient (δ) and the delay rate (ε). It is characterized by estimating the estimated arrival time (ETA) up to D).

In this third embodiment, the entire sea area is divided into a mesh shape, the delay phenomenon occurring in each of the regions A1 to A169 and the navigation time t to the destination D of the ship existing in each of the regions A1 to A169. ) Is mainly analyzed by setting the correlation coefficient δ for each of the areas A1 to A169 by analyzing the correlation with AIS information. In addition, in the third embodiment shown in Fig. 8, although the sea area is a sea area around Japan, when the invention proposed by the present inventors (Patent No. 3882025) is used, AIS information of a wide area can be easily obtained. It may also be targeted at wider seas. In addition, a wide range of AIS information may be obtained by using a satellite or the like.

The delay phenomenon can be grasped | ascertained by the ship's ship speed existing in each area | region A1-A169, for example. In addition, the density of the ship existing in each of the areas A1 to A169 may be taken into consideration. The delay phenomenon has various causes such as weather conditions, visibility, runaway degree, and the like, and these delays are complicatedly intertwined, resulting in a delay in the ship. Conventionally, it was common to find out the causes of these delay phenomena and to find out the delay time of the ship for each cause, but it was necessary to install an observation system for each delay phenomena, make it difficult to observe or predict a wide area, It was very difficult to predict the impact. Therefore, the present invention is intended to grasp only the fact that a delay occurs by using information such as ship speed and ship density, which are easily obtained by AIS information, without revealing a specific delay phenomenon.

For example, in order to grasp the delay phenomenon by the ship speed, AIS information of a plurality of ships is obtained, the average ship or the ship is analyzed by setting the standard ship speed, and how long the ship ship's ship speed is delayed from the standard ship speed. It is good to know. In addition, you may be able to grasp the delay phenomenon from the spinal cord (ship density) of the ship which exists in each area | region A1-A169. This is because the ship may be avoiding navigation due to the effects of the delay phenomenon (typhoon, etc.). In this case, the standard ship density is calculated for each of the areas A1 to A169 using the AIS information, and the delay phenomenon can be grasped by monitoring the decrease in the ship density. In addition, the present invention does not reveal the cause of the delay phenomenon, but the statistical method determines how much the delay phenomenon in each of the regions A1 to A169 affects the navigation time of the ship S in what state. The above-mentioned delay phenomenon includes the case where the ship speed is faster than the standard navigation state and the case where the ship density increases.

Here, the effect of the delay phenomenon which occurred in the area | region A140 at the time of the ship S which exists in the area | region A56 of FIG. 8 to the destination D is demonstrated. Assume that a typhoon exists in the area A140 and is proceeding northeast. While ship S sails to the periphery of the typhoon degree region A86 while sailing to the periphery of the region A86, the vessel S is affected by the typhoon in the periphery of the region A86. Therefore, the ship S needs to cope with such a typhoon, and the arrival time to the destination D is greatly delayed. That is, the delay phenomenon of the area A140, which seems to have nothing to do with the area A56 at first glance, may in fact significantly affect the arrival time of the ship S existing in the area A56. The present invention does not grasp the presence of a typhoon or the like in the area A140 from the weather data, but rather from the delay phenomenon of the ship sailing the area A140 as described above.

The standard navigation time T1-T169 of each area | region A1-A169 can be computed from AIS information similarly to the standard navigation time of 1st Embodiment. The navigation time t to the destination D of the ship existing in each of the areas A1 to A169 can also be calculated by the AIS information. The delay phenomenon can also be grasped from the AIS information as described above. For example, assume that the ship S has entered the area A56 as shown in FIG. In this case, it is assumed that the delay areas where the delay phenomenon occurs (that is, the area where the ship speed is slower than the standard ship speed) are colored areas A37, A59, A86, A116, and A140. Then, the delay time td when the ship S entering the area A56 arrives at the destination D is calculated by comparing the navigation time t56 and the standard navigation time T56. This operation is performed for all ships and all areas A1 to A169, and the data are accumulated and statistically analyzed to determine the correlation coefficients δ1 to δ169 of each area A1 to A169 for each area A1 to A169. Set it. In addition, the correlation coefficient δ in the region where the delay phenomenon does not occur is set to zero. You may set this correlation coefficient (delta) according to the kind and magnitude | size of a ship.

In this way, when the correlation coefficient δ is set, it is easy to use the correlation coefficient δ by detecting the entry area of the ship S and the delay area where the delay phenomenon occurs at that time by the AIS information. It is possible to calculate the estimated arrival time (ETA). In addition, not only the correlation coefficient δ between the regions but also the fact that how much delay occurs in the delay region affects the estimated arrival time ETA. Therefore, it is necessary to calculate the delay rate? In the delay area from the standard state and the delay state. For example, in the case of calculating the delay rate ε by the line speed, from the ship speed (delay rate v) and the standard ship speed V in the delay area, ε = [delay rate v / standard ship speed ( V)]-1 is used to calculate the delay rate ε. Here, the standard ship speed V is an average ship speed or statistical process calculated by the AIS information of the ship which passed each area | region A1-A169 in the past. In addition, the delay speed v is the current average ship speed or the ship speed which performed statistical processing computed by the AIS information of the ship which exists in each area | region A1-A169. In addition, the delay rate (epsilon) is not limited to the said calculation formula, You may transform into the calculation formula suitable for calculation of the estimated arrival time ETA. For example, it may be set by (epsilon) = retardation speed (v) / standard line speed (V), may take logarithm, and may be made into the inverse. The delay rate ε may be calculated based on the ship density. For example, from the current ship density (current density) in the delay area and the standard ship density (standard density) calculated from the AIS information, ε = ( The present density / standard density) + 1 and ε = (standard density / current density)-1 may be calculated by a formula.

In addition, as shown in FIG. 8, instead of dividing the entire sea area into a plurality of regions, when an area where a delay phenomenon occurs can be determined empirically or when a region where a delay phenomenon occurs statistically is limited. As in the first modification shown in Fig. 9A, the regions A1 to A4 may be partially partitioned. Therefore, here, the target ship observation area which detects the entry area of ship S and the delay observation area which detects a delay phenomenon are set to area | region A1-A4. In this case, the frequency of updating the estimated arrival time ETA is set by the number of partitioned areas. Thus, as in the second modification shown in Fig. 9B, the target ship observation areas P1 to P5 for detecting the entry area of the ship S and the delay observation areas Q1 to Q3 for detecting the delay phenomenon are set respectively. You may do so. In this case, by setting the number of the target ship observation areas P1 to P5 to be larger than the delayed observation areas Q1 to Q3, or by setting the target ship observation areas P1 to P5 to be connected to the destination D, the estimated arrival time ETA is updated. Can be set arbitrarily.

Next, the ship identification prediction system which concerns on 3rd Embodiment mentioned above is demonstrated. 10 is a configuration diagram showing a ship identification prediction system according to the third embodiment shown in FIG. In addition, the same code | symbol is attached | subjected to the same part as the ship identification prediction system shown in FIG. 4, and the overlapping description is abbreviate | omitted.

The ship identification prediction system of this invention shown in FIG. 10 is a ship identification prediction system which receives AIS information transmitted from ship S equipped with ship automatic identification apparatus AIS, and predicts identification of ship S. FIG. And a receiving station apparatus 42 capable of receiving AIS information and distributing it by the telecommunication line 41, and a processing unit 43 connected to the receiving station apparatus 42 via the telecommunication line 41. The processing apparatus 43 stores the AIS information, constructs an AIS database 44, divides the sea area where the ship S sails to a predetermined destination D into a plurality of areas A1 to A169, and AIS. Correction of creating standard navigation information 45d for each area A1 to A169 by using the information to construct a standard navigation database 45, and modifying standard navigation information 45d to predetermined conditions using AIS information. Create a table 46d to build the calibration database 46 The AIS information detects the entry area A56 of the ship S and the delay areas A37, A59, A86, A116, and A140 in which the delay phenomenon occurs, and the standard navigation information 45d corresponding to the entry area A56. And the estimated time of arrival ETA to the destination D of the ship S using the correction table 46d. Here, the correction table 46d correlates the correlation between the delay phenomenon occurring in any area of the areas A1 to A169 and the navigation time to the destination D of the ship S existing in each area A1 to A169. The correlation coefficient δ set for each of the regions A1 to A169 is analyzed by information.

The standard navigation information 45d of the standard navigation database 45 shown in FIG. 10 shows a table in which the ship type is a container ship and the total tonnage is 90,000 to 100,000 tons. In the table of the standard navigation information 45d, the standard navigation times T1 to T169 and the standard ship speeds V1 to V169 are set for each of the areas A1 to A169. These standard navigation times T1 to T169 and standard ship speeds V1 to V169 are calculated by the AIS received data of the AIS database 44. In addition, the standard navigation time T1-T169 passes the navigation time of the other ship which passed each area | region A1-A169 immediately before ship S, for example, or passes each area A1-A169 in the past. It is set by the navigation time calculated by analyzing the AIS information of a plurality of other ships.

The correction table 46d of the correction database 46 shown in FIG. 10 shows a correction table 46d when the ship type is a container ship and the total tonnage is 90,000 to 100,000 tons. In the correction table 46d, correlation coefficients δ11 to δ169169 are set for each of the target ship observation areas A1 to A169 and the delay observation areas A1 to A169.

The case where the estimated arrival time ETA of the ship S in the state shown in FIG. 8 is computed using the ship identification prediction system of this invention shown in FIG. 10 is demonstrated, for example.

(1) The AIS information of the ship existing in each of the areas A1 to A169 including the ship S is transmitted to the processing device 43 via the receiving station apparatus 42 and the telecommunication line 41.

(2) The processing apparatus 43 stores the AIS reception data of each ship in the AIS database 44 and detects that the ship S has entered the area A56.

(3) The processing apparatus 43 detects the delay areas A37, A59, A86, A116, and A140 in which the delay phenomenon occurs.

(4) The processing apparatus 43 accesses the standard navigation database 45 to determine the standard navigation time T56 and the standard ship speeds V37, V59, V86, V116, V140 from the entry area A56 to the destination D. Extract.

(5) The processing device 43 accesses the correction database 46 to determine the correlation coefficients δ3756, δ5956, δ8656, δ11656, δ14056 of the delay areas A37, A59, A86, A116, and A140 with respect to the entry area A56. Extract

(6) The processing apparatus 43 accesses the AIS database 44 to extract delayed fluxes v37, v59, v86, v116, v140 in the delay areas A37, A59, A86, A116, and A140, and standardize. Delay rates? 37,? 59,? 86,? 116 and? 140 are calculated from the line speeds V37, V59, V86, V116, V140.

(7) The processing apparatus 43 calculates the estimated arrival time ETA by the formula of ETA = T56 × δ 3756 × ε 37 × δ 5956 × ε 59 × δ 8656 × ε 86 × δ 11656 × ε 116 × δ 14056 × ε 140.

(8) The processing device 43 outputs the estimated arrival time ETA to a predetermined medium (display device, terminal device 47, etc.).

In the calculation of the estimated arrival time ETA described above, the calculation formula is not limited to the above-mentioned one, for example, ETA = T56 × (1 + δ3756 × ε37 + δ5956 × ε59 + δ8656 × ε86 + δ11656 × ε116 + δ14056 × ε140) may be used, or ETA = T56 × (1 + δ3756 × ε37) × (1 + δ5956 × ε59) × (1 + δ8656 × ε86) × (1 + δ11656 × ε116) × 1 + δ14056 × 140 .

The present invention is not limited to the above-described embodiments, and the division method of the region is arbitrary in each embodiment, and the line dividing method (first embodiment), the cell dividing method (second embodiment), or the mesh dividing method (first) 3 embodiments) may be selected and applied, or when the estimated arrival time (ETA) is shorter than the scheduled time of the navigation plan, it may be assumed that the time adjustment will be entered during the navigation, and the display may be output as expected. It is a matter of course that various changes can be made without departing from the spirit of the present invention.

1 is a diagram showing a first embodiment of a ship identification prediction method according to the present invention, in which FIG. 1A is a basic example, and FIG. 1B is a first modified example.

Fig. 2 is a diagram showing a modification of the first embodiment shown in Fig. 1A, Fig. 2A is a second modification, and Fig. 2B is a third modification.

Fig. 3 is a diagram showing a method of setting the separation correction coefficient, in which Fig. 3A shows the case of the dividing line L4, and Fig. 3B shows the case of the dividing line L3.

4 is a configuration diagram showing a ship identification prediction system according to a first modification of the first embodiment shown in FIG. 1B.

5 is a diagram showing a second embodiment of a ship identification prediction method according to the present invention, in which FIG. 5A is a basic example, and FIG. 5B is a first modified example.

6 is a diagram showing a modification of the second embodiment, in which FIG. 6A is a second modification, and FIG. 6B is a third modification.

FIG. 7 is a configuration diagram showing a ship identification prediction system according to a second modification of the second embodiment shown in FIG. 6A.

8 is a diagram showing a third embodiment of a ship identification predicting method according to the present invention;

9 is a diagram showing a modification of the third embodiment, in which FIG. 9A is a first modification, and FIG. 9B is a second modification.

FIG. 10 is a block diagram showing a ship identification prediction system according to the third embodiment shown in FIG. 8; FIG.

<Explanation of symbols for the main parts of the drawings>

1: harbor

21: Coastal part

41: telecommunication line

42: recipient device

43: processing unit

44: AIS database

45: standard navigation database

45d: standard navigation information

46: calibration database

46d: calibration table

47: terminal equipment

S: Ship

A: area

P: target vessel observation area

Q: delayed observation area

L: dividing line

T: standard flight time

ΔT: Standard pass time

t: time of flight

Δt: transit time

Rs: standard wake

R: Wake

G, g: separation distance

V: standard speed

v: ship speed

α: influence factor

β: separation correction factor

γ: delay coefficient

δ: correlation coefficient

ε: delay rate

Claims (25)

A ship identification prediction method for receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS) and predicting the identification of the ship, wherein the ship navigates to a predetermined destination in a plurality of areas. Partitions, sets a standard navigation time to the destination for each of the areas, detects an entry area into which the vessel enters by the AIS information, and determines a passing area that the vessel has passed before the entry area by the AIS information. The transit time required for navigation is calculated, and the delay time or delay coefficient of the transit zone is calculated from the transit time and the standard navigation time, and the delay time or delay coefficient is used in the entry area of the ship. Modifying the standard navigation time to predict the estimated time of arrival to the destination; Forecasting methods. A ship identification method for predicting the identification of the ship by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), and divides the sea area where the ship sails to a predetermined destination into a plurality of areas, The standard navigation time to the destination is set for each of the areas, the entry area into which the ship enters is detected by the AIS information, and the other area in the scheduled passage area from the entry area to the destination is determined by the AIS information. Calculate a transit time required for navigation of the ship, calculate a delay time or delay coefficient for each of the predetermined transit zones from the transit time and the standard navigation time, and enter the vessel by the delay time or delay coefficient Predict the estimated time of arrival to the destination by modifying the standard navigation time in the area. Vessel Identification prediction method wherein the. The ship identification according to claim 1 or 2, wherein the area is partitioned by a plurality of dividing lines toward the destination, or divided into a cell shape along a standard track of the ship. Forecast method. The ship identification prediction method according to claim 1 or 2, wherein a standard passage time required for passage of each region is set instead of the standard navigation time. The method of claim 4, wherein the standard transit time is a transit time calculated by analyzing the transit time of another ship passing through each area immediately before, or the AIS information of a plurality of other ships passing through each area in the past. Ship identification prediction method. The method according to claim 1 or 2, wherein a standard track when the vessel sails to the destination is set, a distance correction coefficient is set according to the distance from the standard track for each of the regions, and the AIS information is used. The ship identification prediction method of calculating the separation distance from the said standard track in the said entry area of the said ship, and correct | amends the estimated arrival time based on the said separation correction coefficient according to the said separation distance. The ship according to claim 6, wherein the standard track is a track of another ship that has passed through each area or has reached the destination just before, or AIS information of a plurality of other ships that have passed through each area or have reached the destination in the past. Ship identification method characterized in that the tracks calculated by analyzing. The ship identification prediction method according to claim 6, wherein the standard track is set for each type, scale, or combination thereof. The ship identification prediction method according to claim 1 or 2, wherein an influence coefficient according to a distance from the destination is set in advance for each of the regions, and the estimated arrival time is corrected using the influence coefficient. A ship identification method for predicting the identification of the ship by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), and divides the sea area where the ship sails to a predetermined destination into a plurality of areas, The standard navigation time to the destination is set for each of the areas, and the correlation between the delay phenomenon occurring in each area and the navigation time to the destination of the ship existing in each area is analyzed by the AIS information and correlated for each area. Setting a coefficient, detecting an entry area into which the ship has entered based on the AIS information, detecting a delay area in which a delay phenomenon occurs by the AIS information, and detecting the delay area from the standard state and the delay state in the delay area. Calculate a delay rate and modify the standard navigation time of the entry area using the delay rate and the correlation coefficient Open Ship Identification prediction method according to claim to predict the estimated time of arrival to the destination. The ship identification method according to claim 10, wherein the area is partitioned into a mesh shape or partially partitioned. The ship identification prediction according to claim 10 or 11, wherein the area includes a delay observation area for observing a delay phenomenon and a target ship detection area for detecting a ship for predicting the estimated arrival time. Way. The ship identification method according to claim 10, wherein the correlation coefficient is set for each type, scale, or combination thereof. The ship identification prediction method according to claim 10, wherein the delay phenomenon is detected by ship speed, density, or a combination thereof of ships existing in each region. The ship identification prediction method according to claim 10, wherein the delay rate is calculated by a ratio of a standard ship speed or standard density in the delay area and a current ship speed or density in the delay area. The said standard navigation time is the navigation time of the other ship which reached the said destination just before, or the AIS of the several other ships which reached the said destination in the past. Vessel identification prediction method characterized in that the navigation time calculated by analyzing the information. The ship identification prediction method according to any one of claims 1, 2, and 10, wherein the standard navigation time is set for each type, scale, or combination thereof. The ship identification prediction method according to any one of claims 1, 2, and 10, wherein the ship position is predicted at the arrival time or the current time of the destination using the estimated arrival time. A ship identification system for predicting identification of the vessel by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), and receiving station apparatus capable of receiving the AIS information and distributing it by a telecommunication line; And a processing device connected to the receiving station apparatus through a telecommunication line, wherein the processing device stores the AIS information to construct an AIS database, and a plurality of areas in the sea area where the ship sails to a predetermined destination. A standard navigation database by creating standard navigation information for each area using the AIS information, and creating a correction table for modifying the standard navigation information to a predetermined condition using the AIS information. Constructing the vehicle, detecting the entry area of the ship by the AIS information, and The estimated time of arrival to the predetermined destination of the ship is calculated using the standard navigation information corresponding to the area and the correction table, and the correction table is the standard track of the ship in the entry area set for each area. And a separation correction coefficient set according to the separation distance from the control unit or an influence coefficient set according to the distance from the predetermined destination for each of the regions. A ship identification system for predicting identification of the vessel by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), and receiving station apparatus capable of receiving the AIS information and distributing it by a telecommunication line; And a processing apparatus connected to the receiving station apparatus via a telecommunication line, wherein the processing apparatus stores the AIS information to construct an AIS database, and the sea area in which the vessel sails to a predetermined destination is divided into a plurality of regions. A standard navigation database is constructed by creating standard navigation information for each region using the AIS information, and a correction table is created by modifying the standard navigation information to a predetermined condition using the AIS information. And the entry area and delay phenomenon of the ship is generated by the AIS information. Detects a delayed area, calculates an estimated time of arrival to the predetermined destination of the ship by using the standard navigation information and the correction table corresponding to the entry area, and the correction table is generated in an arbitrary area. And a correlation coefficient set for each region by analyzing the correlation between the delay phenomenon and the navigation time to the predetermined destination of the vessel existing in each region by the AIS information. A ship identification system for predicting identification of the vessel by receiving AIS information transmitted from a ship equipped with a ship automatic identification device (AIS), and receiving station apparatus capable of receiving the AIS information and distributing it by a telecommunication line; And a processing apparatus connected to the receiving station apparatus via a telecommunication line, wherein the processing apparatus stores the AIS information to construct an AIS database, and the sea area in which the vessel sails to a predetermined destination is divided into a plurality of regions. A standard navigation database is constructed by creating standard navigation information for each region using the AIS information, and a correction table is created by modifying the standard navigation information to a predetermined condition using the AIS information. Build up, detect the entry area of the ship according to the AIS information, The estimated time of arrival to the predetermined destination of the ship is calculated using the standard navigation information and the correction table corresponding to the area, and the standard navigation database and the correction database are used for the type of ship, the size of the ship or A ship identification prediction system characterized by being classified by their combination. 22. The standard navigation information according to any one of claims 19 to 21, wherein the standard navigation information includes a standard navigation time to the predetermined destination set for each region or a standard transit time required for the passage of each region set for each region. Vessel identification prediction system comprising a. The ship identification system according to any one of claims 19 to 21, wherein the processing device outputs the estimated time of arrival in a state that can be obtained from a terminal device connected to a telecommunication line. The ship identification according to any one of claims 19 to 21, wherein the processing device calculates a ship position at the arrival time or the present time of the predetermined destination using the estimated arrival time. Prediction system. 25. The ship identification according to claim 24, wherein the processing device outputs the ship position at the arrival time or the present time of the predetermined destination in a state that can be obtained from a terminal device connected to a telecommunication line. Prediction system.

Images