The present embodiment relates to a navigation support method and the like.
In the navigation support technology, a navigation support system is known in which the performance of a vessel is estimated based on vessel voyage data and past meteorological and hydrographic data, and an optimal route for this vessel is computed based on the estimated performance of the vessel and meteorological and hydrographic data. In such a navigation support system, for example, when a user specifies the engine speed, the system estimates the performance of the vessel (the vessel navigation speed and the fuel consumption amount) under predicted meteorological and hydrographic conditions, and searches for an optimal route that enables the arrival with less fuel consumption amount.
Related art is disclosed in Japanese Patent No. 5281022 and Japanese Laid-open Patent Publication No. 2013-134089.
According to an aspect of the embodiments, a navigation support method executed by a computer includes: storing performance estimation models regarding speed of a vessel for each of vessel maneuvering patterns; accepting one of the vessel maneuvering patterns to be used in a navigation; calculating the speed of the vessel on a route of the vessel, based on one of the performance estimation models that corresponds to the accepted one of the vessel maneuvering patterns among the performance estimation models, and meteorological and hydrographic forecast data; and displaying an arrival time on the route that is optimal, based on the speed of the vessel that has been calculated.
The object and advantages of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the claims.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are not restrictive of the invention.
In such a navigation support system, for example, when a user specifies the engine speed, the system estimates the performance of the vessel (the vessel navigation speed and the fuel consumption amount) under predicted meteorological and hydrographic conditions, and searches for an optimal route that enables the arrival with less fuel consumption amount.
Incidentally, in the actual navigation, the captain of a vessel selects a route with low wind and wave resistance at a normal output prescribed at the time of designing the vessel. The normal output mentioned here is an output that is normally used to obtain navigation velocity, and refers to an economical output from the viewpoint of engine efficiency and maintenance. In many cases, a route selected at the normal output is a route that suits the captain's sense, and is deemed as a route that requires less fuel expense and takes less time.
However, a conventional navigation support system has a disadvantage that it is not possible to present an accurate optimal route at the normal output. For example, the conventional navigation support system searches for an optimal route by presuming a constant engine speed. As a result, the conventional navigation support system can calculate the arrival time when passing through the optimal route found by the search. However, in the actual navigation, it is difficult to keep the engine speed constant due to the influence of waves, wind, and ocean currents. It is known that keeping the engine speed constant will impose a load on the engine and lead to failure. Therefore, it can be said that the optimal route and arrival time found by the search in the conventional navigation support system do not match the reality. Accordingly, the conventional navigation support system cannot present an accurate optimal route at the normal output.
Note that the above-mentioned problem is a problem that arises not only in the normal output but also in other vessel maneuvering patterns similarly, such as a medium output that does not impose a load on the engine and a small output for reducing the fuel expense.
In one mode, an accurate optimal route according to a vessel maneuvering pattern may be presented.
Hereinafter, embodiments of a navigation support method, a navigation support device, and a navigation support program disclosed in the present application will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.
The vessel performance mentioned here includes the navigation speed, fuel consumption amount, and the like of the vessel.
The vessel maneuvering pattern mentioned here refers to a pattern that the captain actually selects when maneuvering the vessel. As the vessel maneuvering pattern, for example, “pattern a” in which the vessel is maneuvered at a normal output, “pattern b” in which the vessel is maneuvered with the engine output slightly lowered, “pattern c” in which the vessel is maneuvered on a voyage in deceleration, and the like are assumed. Hereinafter, the vessel maneuvering pattern is sometimes simply referred to as “pattern”.
“Pattern a” is a pattern in which a vessel is maneuvered by selecting a route with low wind and wave resistance at a normal output prescribed at the time of designing the vessel. “Normal output” refers to an economical output from the viewpoint of engine efficiency and maintenance. A route selected at the normal output is deemed as a route that requires less fuel expense and takes less time. The pattern a is referred to as a vessel maneuvering pattern at the normal output.
“Pattern b” is a pattern in which a vessel is maneuvered by lowering the output so as not to impose a load on the engine (not to cause a torque-rich phenomenon) under stormy weather. The pattern b is referred to as a vessel maneuvering pattern at a medium output. “Pattern c” is a pattern in which a vessel is decelerated and maneuvered in order to reduce fuel expense when there is no next navigation schedule and there is time to spare. The pattern c is referred to as a vessel maneuvering pattern at a small output. Note that the vessel maneuvering patterns are not limited to these patterns. As an example, the vessel maneuvering patterns may include a pattern d in which a vessel is maneuvered by increasing the output so as to impose a load on the engine when there is no time to spare. The pattern d is referred to as a vessel maneuvering pattern at a high output.
Here, an outline of navigation support according to the embodiment will be described with reference to
As illustrated in
Then, the navigation support device 1 obtains voyage data 21′ by aggregation for each pattern (<2>).
Subsequently, the navigation support device 1 learns the vessel performance using the voyage data 21′ aggregated for each pattern and actual meteorological/hydrographic data (actual/forecast) 22, and constructs an estimation model for the vessel performance for each pattern (<3>).
Thereafter, for example, when accepting the start point, start time, and goal point of the vessel from the vessel, the navigation support device 1 estimates the vessel performance from the start to the goal of the vessel for each pattern, on the basis of forecast meteorological/hydrographic data (actual/forecast) 22 and the estimation model for the vessel performance for each pattern. The vessel performance mentioned here indicates the navigation speed, fuel consumption amount, and the like of the vessel. Then, the navigation support device 1 calculates an optimal route for the vessel based on the estimated vessel performance for each pattern, and displays the arrival time on the optimal route, for example, to the vessel as a source of acceptance (<4>).
Returning to
The control unit 10 corresponds to an electronic circuit such as a central processing unit (CPU). Then, the control unit 10 includes an internal memory for storing programs defining various processing procedures and control data, and executes a variety of types of processing using the programs and the control data. The control unit 10 includes a data collection unit 11, a voyage data classification unit 12, a pattern extraction unit 13, a voyage data aggregation unit 14, and a performance estimation model generation unit 15. Furthermore, the control unit 10 includes a performance estimation unit 16 and an optimal route search unit 17. Note that the voyage data classification unit 12, the pattern extraction unit 13, the voyage data aggregation unit 14, and the performance estimation model generation unit 15 are functional units for a model learning phase. Furthermore, the performance estimation unit 16 and the optimal route search unit 17 are functional units for a service provision phase. In addition, the performance estimation unit 16 and the optimal route search unit 17 are an example of a calculation unit. The optimal route search unit 17 is an example of a display unit.
For example, the storage unit 20 is a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disc. The storage unit 20 has the voyage data 21, the meteorological/hydrographic data (actual/forecast) 22, voyage data (for each meteorological and hydrographic condition) 23, a pattern 24, voyage data (for each pattern) 25, and a performance estimation model 26. Note that the performance estimation model 26 is an example of a storage unit.
The voyage data 21 is data indicating, for example, when, where, at what speed, and in which direction the vessel was heading during voyage. In different terms, the voyage data 21 is data indicating the history of vessel maneuvering performed by the captain of the vessel. The voyage data 21 is collected using, for example, an automatic identification system (AIS), a voyage data recorder (VDR), and an engine logger.
Here, an example of the voyage data 21 will be described with reference to
Returning to
Here, an example of meteorological/hydrographic data (actual/forecast) 22 will be described with reference to
As illustrated in the upper figure in
Returning to
The pattern 24 is a vessel maneuvering pattern extracted from a plurality of vessel maneuvering patterns. Note that the pattern 24 is extracted by the pattern extraction unit 12.
The voyage data (for each pattern) 25 is voyage data obtained by aggregating the voyage data 21 for each pattern. Note that the voyage data (for each pattern) 25 is aggregated by the voyage data aggregation unit 14.
The performance estimation model 26 is an estimation model for the vessel performance for each pattern. Note that the performance estimation model 26 is generated by the performance estimation model generation unit 15.
The data collection unit 11 collects various types of data. For example, the data collection unit 11 collects the voyage data 21 using an AIS. The data collection unit 11 receives the meteorological data (actual/forecast) and the hydrographic data (actual/forecast) delivered from the weather forecast data provider, and collects the meteorological/hydrographic data (actual/forecast) 22.
The voyage data classification unit 12 classifies the voyage data 21 according to each meteorological and hydrographic condition.
Here, an example of voyage data classification will be described with reference to
The pattern extraction unit 13 clusters vessel speed data of the voyage data 23 for each meteorological and hydrographic condition, and extracts the vessel maneuvering pattern (pattern). For example, the pattern extraction unit 13 clusters the vessel speed data using data including at least the position (latitude and longitude), time, and vessel speed during voyage in the voyage data 23 for each meteorological and hydrographic condition. For clustering, the k-means method or the like can be used as an example. Then, as a result of clustering, the pattern extraction unit 13 extracts, as an example, a vessel maneuvering pattern (pattern a) at the normal output, a vessel maneuvering pattern (pattern b) at the medium output, a vessel maneuvering pattern (pattern c) at the small output, and the like. Subsequently, the pattern extraction unit 13 saves the extracted patterns in the pattern 24. Note that the pattern extraction unit 13 has been described to cluster the vessel speed data of the voyage data 23 for each meteorological and hydrographic condition to extract patterns, but is not limited to this example. The engine speed or horsepower may be used instead of the vessel speed data to perform clustering and extract patterns.
Returning to
Furthermore, the voyage data aggregation unit 14 divides the distribution into sections based on the frequency of occurrence in the distribution of vessel speed calculated for each meteorological and hydrographic condition. The divided sections are associated with the vessel maneuvering patterns. This allows the voyage data aggregation unit 14 to regard a section of vessel speed with the highest frequency of occurrence as the vessel maneuvering pattern at the normal output, by calculating the frequency of occurrence of vessel speed under the same meteorological and hydrographic condition. In other words, this is because it is assumed that the captain often selects the normal output, which is an economical output, when maneuvering a vessel. Similarly, the voyage data aggregation unit 14 can regard a section of the distribution obtained from the frequency of occurrence and the vessel speed, as a predetermined vessel maneuvering pattern, by calculating the frequency of occurrence of vessel speed under the same meteorological and hydrographic condition.
Furthermore, the voyage data aggregation unit 14 aggregates the voyage data 23 for each meteorological and hydrographic condition for each vessel maneuvering pattern, and generates the voyage data 25 for each vessel maneuvering pattern.
Note that the voyage data aggregation unit 14 may correct the voyage data 25 for each vessel maneuvering pattern when obtaining the voyage data 25 for each vessel maneuvering pattern by aggregation. For example, the voyage data aggregation unit 14 designates the vessel maneuvering pattern based on the frequency of occurrence of vessel speed for the same meteorological and hydrographic condition. However, if the voyage data aggregation unit 14 designates the vessel maneuvering pattern only according to the vessel speed, aggregation will result in the vessel maneuvering pattern to be switched in a very short period of time, but in reality, the vessel maneuvering pattern is not switched in a very short period of time. Accordingly, when the duration period of a vessel maneuvering pattern is within a predetermined period of time, it is desirable for the voyage data aggregation unit 14 to correct the voyage data of the vessel maneuvering pattern by employing a most frequent vessel maneuvering pattern contained in a predetermined period of time as a vessel maneuvering pattern for that period of time.
Here, an example of voyage data aggregation will be described with reference to
The voyage data aggregation unit 14 calculates a frequency distribution table of each vessel speed, using the voyage data 23 for each meteorological and hydrographic condition.
Then, the voyage data aggregation unit 14 divides the distribution into sections based on the frequency of occurrence in the calculated frequency distribution table of vessel speed. Here, a section of vessel speed with the highest frequency of occurrence is regarded as the vessel maneuvering pattern at the normal output. This is because it is assumed that the captain often selects the normal output, which is an economical output, when maneuvering a vessel.
Then, the voyage data aggregation unit 14 aggregates the voyage data 23 for each meteorological and hydrographic condition, and generates the voyage data 25 of the vessel maneuvering pattern at the normal output. Here, a section of vessel speed with the highest frequency of occurrence is regarded as the vessel maneuvering pattern at the normal output. Accordingly, the voyage data aggregation unit 14 aggregates the voyage data of the section of vessel speed with the highest frequency of occurrence from the respective frequency distribution tables calculated for each meteorological and hydrographic condition, and generates the voyage data 25 of the vessel maneuvering pattern at the normal output.
Note that a section of vessel speed with the next highest frequency of occurrence may be employed as the vessel maneuvering pattern at the medium output. In such a case, the voyage data aggregation unit 14 aggregates the voyage data of the section of the distribution of vessel speed with the next highest frequency of occurrence from the respective frequency distribution tables calculated for each meteorological and hydrographic condition, and generates the voyage data 25 of the vessel maneuvering pattern at the medium output. Furthermore, a section of the distribution with the slowest vessel speed may be employed as the vessel maneuvering pattern at the small output. In such a case, the voyage data aggregation unit 14 aggregates the voyage data of the section of the distribution with the slowest vessel speed from the respective frequency distribution tables calculated for each meteorological and hydrographic condition, and generates the voyage data 25 of the vessel maneuvering pattern at the small output. Furthermore, a section of the distribution with the fastest vessel speed may be employed as the vessel maneuvering pattern at the high output. In such a case, the voyage data aggregation unit 14 aggregates the voyage data of the section of the distribution with the fastest vessel speed from the respective frequency distribution tables calculated for each meteorological and hydrographic condition, and generates the voyage data 25 of the vessel maneuvering pattern at the high output.
As illustrated in
Returning to
y=β
0+β1x1+β2x2+β3x3+β4x4+β5x5+β6x6 Equation (1)
Here, an example of performance estimation model generation according to the embodiment will be described with reference to
Here, an idea of the performance estimation model generation processing according to the embodiment will be described with reference to FIG. 9.
As illustrated in
For example, the performance estimation model generation unit 15 works out parameters β0 and β1 that minimize equation (2), and works out a regression line y=β0+β1x1.
Note that, in
Returning to
The optimal route search unit 17 searches for an optimal route for the vessel based on the vessel performance estimated by the performance estimation unit 16. For example, the optimal route search unit 17 accepts navigation conditions of a vessel from a using side who uses the navigation support processing. As an example, the using side mentioned here includes a vessel on the sea or a shipping company on the shore that use the navigation support processing. As an example, the navigation conditions of a vessel includes the departure place, arrival place, departure time, and vessel maneuvering pattern. The optimal route search unit 17 searches for an optimal route for the entire section from the departure place to the arrival place when departure is made at the specified departure time and the specified vessel maneuvering pattern is selected. As an example, the optimal route search unit 17 searches for the optimal route based on the estimated vessel performance at each position (latitude and longitude) included in the entire section, and displays the arrival time on the optimal route to the using side. As an example, the Dijkstra method, which indicates an algorithm for solving the shortest path problem, can be used to search for the optimal route, but any conventional technology may be used as long as the estimated vessel performance is used.
Furthermore, the optimal route search unit 17 saves the optimal route and the arrival time of the specified vessel maneuvering pattern in the storage unit 20 as the optimal route search result.
Note that the optimal route is a route that consumes less fuel and takes less time in operation in each selected vessel maneuvering pattern. For example, when the vessel maneuvering pattern is the pattern a at the normal output, the optimal route is a route that consumes less fuel and takes less time when making a voyage in the pattern a. The same applies to a case where the vessel maneuvering pattern is the pattern b at the medium output and a case where the vessel maneuvering pattern is the pattern c at the small output.
Furthermore, after finding the optimal route for the entire section from the departure place to the arrival place, the optimal route search unit 17 may modify a partial section of the optimal route with another vessel maneuvering pattern according to an instruction from the using side, and display the arrival time in consideration of the modified optimal route to the using side. In such a case, the optimal route search unit 17 searches for an optimal route when the specified vessel maneuvering pattern is selected for a partial section in the entire section of the optimal route. As an example, the optimal route search unit 17 can modify a partial section of the optimal route based on the estimated vessel performance at each position (latitude and longitude) included in the partial section, and display the arrival time on the entire section of the optimal route.
When accepting the specification of the vessel maneuvering pattern and the target position, the performance estimation unit 16 acquires the performance estimation model 26 corresponding to the vessel maneuvering pattern. The performance estimation unit 16 estimates the vessel performance (for example, the vessel speed) at the target position (latitude and longitude) using the acquired performance estimation model 26 and the forecast meteorological/hydrographic data 22. Then, the performance estimation unit 16 feeds back with the estimated vessel performance (for example, the vessel speed) (S120). The performance estimation unit 16 repeatedly estimates the vessel performance for all the specified target positions, and feeds back with the estimated vessel performance.
Subsequently, the optimal route search unit 17 searches for an optimal route in the accepted vessel maneuvering pattern, based on the estimated vessel performance (for example, the vessel speed) at each position (latitude and longitude) included in the section, and displays the arrival time on the optimal route to the vessel (S130). Here, on the vessel side, the optimal route for each vessel maneuvering pattern is displayed. The optimal route whose vessel maneuvering pattern is the pattern a at the normal output is the route indicated by Optimal (normal). The optimal route whose vessel maneuvering pattern is the pattern b at the medium output is the route indicated by Optimal (slow x1). The optimal route whose vessel maneuvering pattern is the pattern c at the small output is the route indicated by Optimal (slow x2). Additionally, the arrival time when a voyage is made in each pattern is displayed.
Moreover, when a partial section in the entire section of the optimal route in any of the vessel maneuvering patterns is changed to another vessel maneuvering pattern, the optimal route search unit 17 accepts the partial section and the another vessel maneuvering pattern, for example, from the vessel (S100). The optimal route search unit 17 makes an inquiry about the vessel performance (for example, the vessel speed) when the vessel is maneuvered in the accepted another vessel maneuvering pattern for each position (latitude and longitude) included in the partial section (S110).
When accepting the specification of the another vessel maneuvering pattern and the target position, the performance estimation unit 16 acquires the performance estimation model 26 corresponding to the another vessel maneuvering pattern. The performance estimation unit 16 estimates the vessel performance (for example, the vessel speed) at the target position (latitude and longitude) using the acquired performance estimation model 26 and the forecast meteorological/hydrographic data 22. Then, the performance estimation unit 16 feeds back with the estimated vessel performance (for example, the vessel speed) (S120). The performance estimation unit 16 repeatedly estimates the vessel performance for all the specified target positions, and feeds back with the estimated vessel performance.
Subsequently, the optimal route search unit 17 modifies the partial section of the optimal route with the another vessel maneuvering pattern, based on the estimated vessel performance (for example, the vessel speed) at each position (latitude and longitude) included in the partial section. Thereafter, the optimal route search unit 17 displays the arrival time on the entire section of the optimal route to the vessel in consideration of the modified optimal route (S130).
Here, an operation example for an optimal route search when a partial section of an optimal route when a voyage is made on the entire route in a first pattern is changed to a second pattern will be described with reference to
As illustrated in
Here, an example of a simulation of an optimal route search when a partial section of an optimal route when a voyage is made on the entire route in a first pattern is changed to a second pattern will be described with reference to
As illustrated in the upper part of
Here, the user selects the pattern c option from the option screen G0 for the section c2 from the position p1 to the position p2.
Following the above, as illustrated in the middle part of
Then, as illustrated in the lower part of
As illustrated in
The pattern extraction unit 13 analyzes the pattern of vessel maneuvering from the voyage data 23 for each meteorological and hydrographic condition (step S12). As a result of the analysis, the voyage data aggregation unit 14 aggregates the voyage data 23 for each meteorological and hydrographic condition to obtain the voyage data by patterns of vessel maneuvering (step S13), and saves the voyage data 25 for each pattern. Then, the voyage data aggregation unit 14 corrects the voyage data aggregated by patterns of vessel maneuvering (step S14). Subsequently, the performance estimation model generation unit 15 generates the performance estimation model using the voyage data by patterns (the voyage data 25 for each pattern) (step S15). Thereafter, the performance estimation model generation unit 15 saves the generated performance estimation model in the performance estimation model 26.
As illustrated in
On the other hand, when it is determined that the navigation information has been accepted (step S21; Yes), the performance estimation unit 16 acquires a performance estimation model corresponding to the accepted pattern (step S22). The performance estimation unit 16 estimates the vessel performance using the forecast meteorological/hydrographic data 22 and the performance estimation model (step S23). Then, the optimal route search unit 17 searches for an optimal route for the vessel, based on the estimated vessel performance (step S24). Subsequently, the optimal route search unit 17 displays the optimal route found by the search to the using side (step S25).
Thereafter, the optimal route search unit 17 determines whether a change in the pattern for a partial section in the whole section of the optimal route has been accepted from the using side (step S26). When it is determined that a change in the pattern for a partial section has been accepted (step S26; Yes), the optimal route search unit 17 proceeds to step S22. For example, the optimal route search unit 17 proceeds to step S 22 in order to search for a route with a pattern changed for the partial section and to search for a route with the original pattern for a section succeeding the partial section.
On the other hand, when it is determined that a change in the pattern for a partial section has not been accepted (step S26; No), the optimal route search unit 17 ends the optimal route search processing.
Note that the optimal route search unit 17 has been described to, when accepting an instruction from the using side, search for an optimal route according to the instruction and display the optimal route found by the search to the using side. The using side may use the optimal route to cooperate the optimal route with autopilot control that automatically operates the rudder. For example, an autopilot cooperation unit 31 (not illustrated) on the vessel side can cooperate the optimal route found by search by the optimal route search unit 17 with the autopilot. For example, the autopilot cooperation unit 31 acquires the optimal route search result for the optimal route found by search by the optimal route search unit 17. The autopilot cooperation unit 31 acquires the current position of the vessel using a global positioning system (GPS). Then, the autopilot cooperation unit 31 calculates a direction in which the vessel is expected to move, using the current position of the vessel and the optimal route. Subsequently, the autopilot cooperation unit 31 calculates the steering angle indicating the angle between the calculated direction and the current direction, using the calculated direction and a direction sensor. Thereafter, the autopilot cooperation unit 31 instructs a steering unit of the vessel on the calculated steering angle. This allows the autopilot cooperation unit 31 to automatically operate the rudder of the vessel by cooperating the optimal route with the autopilot.
As illustrated in
On the other hand, when it is determined that the autopilot cooperation instruction has been accepted (step S31; Yes), the autopilot cooperation unit 31 acquires the optimal route search result for the displayed optimal route (step S32). Then, the autopilot cooperation unit 31 acquires the current position of the vessel using the GPS, and calculates a direction in which the vessel is expected to move, using the current position of the vessel and the optimal route search result (step S33).
Subsequently, the autopilot cooperation unit 31 performs autopilot using the calculated direction and the direction sensor, and calculates the steering angle (step S34). For example, the autopilot cooperation unit 31 acquires the direction in which the vessel is currently moving, using the direction sensor. The autopilot cooperation unit 31 calculates a steering angle indicating the angle between the currently moving direction and the calculated direction in which the vessel is expected to move.
Thereafter, the autopilot cooperation unit 31 operates the steering unit using the steering angle (step S35). As a result, the rudder of the vessel is operated.
The navigation support device 1 collects actual and forecast meteorological and hydrographic data from the provider of weather forecast data. The navigation support device 1 collects voyage data from the provider of AIS data. The collected meteorological and hydrographic data and voyage data are reflected in the voyage data 21 and the meteorological/hydrographic data (actual/forecast) 22.
Prior to the navigation, the captain or on-shore staff inquires of the navigation support device 1 about the optimal route. Furthermore, the captain can also inquire of the navigation support device 1 about the optimal route during the navigation.
Upon accepting navigation conditions contained in the inquiry, the navigation support device 1 searches for an optimal route for the section from the departure place to the arrival place of the vessel when the departure is made at the departure time and the specified vessel maneuvering pattern is selected. Then, the navigation support device 1 responds to the inquiry source with the optimal route found by the search. Consequently, the navigation support device 1 can present an accurate optimal route according to the vessel maneuvering pattern.
Furthermore, after having found the optimal route by the search, the navigation support device 1 further modifies a partial section of the optimal route with another vessel maneuvering pattern in response to an inquiry about a change in the partial section, and searches for a modified optimal route. Then, the navigation support device 1 responds to the inquiry source with the modified optimal route. Consequently, the navigation support device 1 can simulate the optimal route in which a partial section is replaced with another vessel maneuvering pattern.
In addition, an information processing device (a personal computer (PC) or a smartphone) in the vessel may include the autopilot cooperation unit 31. The autopilot cooperation unit 31 cooperates the simulated optimal route with the autopilot. For example, the autopilot cooperation unit 31 calculates the steering angle using the optimal route, the current position of the vessel, and the current direction of the vessel, and instructs the steering unit of the vessel to operate the rudder of the vessel. This allows the autopilot cooperation unit 31 to automatically operate the rudder of the vessel by cooperating the optimal route with the autopilot.
According to the above embodiment, the navigation support device 1 stores the performance estimation models 26 regarding speed of a vessel for each of vessel maneuvering patterns. The navigation support device 1 accepts one of the vessel maneuvering patterns to be used in a navigation. The navigation support device 1 calculates the speed of the vessel on a route of the vessel, based on the one of the performance estimation models corresponding to the accepted one of the vessel maneuvering patterns among the performance estimation models 26, and the meteorological/hydrographic data 22 of the usage. The navigation support device 1 displays the arrival time on the route that is optimal, based on the calculated speed of the vessel. According to such a configuration, the navigation support device 1 can present an accurate optimal route according to the vessel maneuvering pattern, by using the performance estimation model 26 for the speed of the vessel (vessel performance) for each vessel maneuvering pattern.
Furthermore, according to the above embodiment, for a partial section of the route that is optimal, the navigation support device 1 calculates the speed of the vessel in the partial section, based on one of the performance estimation models of another one of the vessel maneuvering patterns among the performance estimation models 26. The navigation support device 1 modifies the route for the entire section that is optimal, based on the calculated speed of the vessel in the partial section, and displays the arrival time on the route that is optimal and modified. According to such a configuration, the navigation support device 1 can execute a simulation of an optimal route when a partial section of the optimal route is changed to another vessel maneuvering pattern. As a result, the navigation support device 1 can present an accurate optimal route according to the vessel maneuvering pattern even when a partial section of the optimal route is changed to another vessel maneuvering pattern.
In addition, according to the above embodiment, the autopilot cooperation unit 31 calculates a direction in which the vessel is expected to move with respect to the current position of the vessel, from the route that is optimal. The autopilot cooperation unit 31 calculates the steering angle using a direction in which the vessel is currently being maneuvered and the direction in which the vessel is expected to move. The autopilot cooperation unit 31 controls the steering of the vessel based on the calculated steering angle. According to such a configuration, the autopilot cooperation unit 31 can automatically operate the rudder of the vessel by cooperating the route that is optimal, with the autopilot.
In addition, according to the above embodiment, the navigation support device 1 classifies the voyage data 21 according to each meteorological and hydrographic condition. The navigation support device 1 calculates the characteristic distribution of vessel maneuvering for each meteorological and hydrographic condition using the classified voyage data 23. The navigation support device 1 extracts a plurality of vessel maneuvering patterns from the calculated characteristic distribution of vessel maneuvering for each meteorological and hydrographic condition, and aggregates the voyage data for each vessel maneuvering pattern. The navigation support device 1 generates a learning model for each vessel maneuvering pattern from the voyage data aggregated for each vessel maneuvering pattern, using meteorological and hydrographic actual data as the explanatory variable and the vessel performance as the objective variable. According to such a configuration, the navigation support device 1 can accurately recommend an optimal route according to the vessel maneuvering pattern, by using the learning model for the vessel performance for each vessel maneuvering pattern. For example, the navigation support device 1 is allowed to estimate the optimal route that suits the captain's sense by learning the vessel maneuvering actually performed by the captain. As a result, the navigation support device 1 can obtain an economic effect by reducing the fuel expense cost and reducing the navigation time, and an environmental effect by reducing carbon dioxide CO2.
Note that each illustrated component of the navigation support device 1 is not necessarily physically configured as illustrated in the drawings. For example, specific aspects of separation and integration of the navigation support device 1 are not limited to the illustrated ones, and all or a part of the device can be functionally or physically separated and integrated in an optional unit according to various loads, use states, or the like. For example, the voyage data classification unit 12 and the pattern extraction unit 13 may be integrated as one unit. Furthermore, the voyage data aggregation unit 14 may be split into an aggregation unit that aggregates the voyage data 23 for each meteorological and hydrographic condition to generate the voyage data 25 for each vessel maneuvering pattern, and a correction unit that corrects the voyage data 25 for each vessel maneuvering pattern. In addition, the storage unit 20 may be connected by way of a network as an external device of the navigation support device 1.
Furthermore, various types of processing described in the above embodiment can be achieved by a computer such as a personal computer or a work station executing programs prepared in advance. Thus, in the following, an example of a computer that executes a navigation support program that achieves functions similar to the functions of the navigation support device 1 illustrated in
As illustrated in
The drive device 213 is a device for a removable disk 210, for example. The HDD 205 stores a navigation support program 205a and navigation support processing-related information 205b.
The CPU 203 reads the navigation support program 205a, and loads the navigation support program 205 a into the memory 201 to execute the navigation support program 205a as a process. Such a process corresponds to the respective functional units of the navigation support device 1. The navigation support processing-related information 205 b corresponds to the voyage data 21, the meteorological/hydrographic data (actual/forecast) 22, the voyage data (for each meteorological and hydrographic condition) 23, the pattern 24, the voyage data (for each pattern) 25, and the performance estimation model 26. Then, for example, the removable disk 210 stores each piece of information such as the navigation support program 205a.
Note that the navigation support program 205 a may not necessarily be stored in the HDD 205 from the beginning. For example, the program is stored in a “portable physical medium” such as a flexible disk (FD), a compact disk read only memory (CD-ROM), a digital versatile disk (DVD), a magneto-optical disk, or an integrated circuit (IC) card, which is inserted into the computer 200. Then, the computer 200 may read the navigation support program 205 a from these media to execute the navigation support program 205a.
All examples and conditional language provided herein are intended for the pedagogical purposes of aiding the reader in understanding the invention and the concepts contributed by the inventor to further the art, and are not to be construed as limitations to such specifically recited examples and conditions, nor does the organization of such examples in the specification relate to a showing of the superiority and inferiority of the invention. Although one or more embodiments of the present invention have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the invention.
This application is a continuation application of International Application PCT/JP2018/047101 filed on Dec. 20, 2018 and designated the U.S., the entire contents of which are incorporated herein by reference.
Number | Date | Country | |
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Parent | PCT/JP2018/047101 | Dec 2018 | US |
Child | 17342062 | US |