A ship high-density area supervision method and system in a maritime mixed traffic scene

Abstract

This invention discloses a method and system for monitoring high-density areas of vessels in a mixed maritime traffic scenario. The method includes: S1, acquiring AIS data of vessels in a mixed maritime traffic scenario; S2, extracting the latitude and longitude coordinates of the vessel AIS data, calculating the ordered sequence of vessel core distances and reachable distances; calculating vessel areas of different densities using a slope threshold method; determining high-density vessel areas by calculating the average core density of each vessel area; S3, scheduling vessels with various driving modes posing a collision risk within the high-density vessel areas. This invention calculates areas of different vessel densities by calculating the distance relationships between vessel points and the slope threshold of the ordered sequence of vessel reachable distances, thereby determining the area with the highest vessel density. Different command dispatch methods are used for manned and unmanned vessels to assist shore-based monitoring personnel in scheduling and monitoring vessels with collision risks in mixed traffic scenarios.

Description

Technical Field

[0001] This invention relates to the fields of mixed maritime traffic scenarios and maritime vessel safety supervision, and more particularly to a method and system for supervising high-density areas of vessels in mixed maritime traffic scenarios. Background Technology

[0002] In the process of maritime vessel safety supervision, nearshore waters have high vessel density and a more complex navigation environment, making them a key area for vessel maritime supervision. Simultaneously, with the development of intelligent ships, maritime traffic is entering a transitional phase involving a mix of traditional vessels, remotely controlled vessels, and unmanned vessels. During this phase, maritime traffic scenarios will become more complex, increasing the burden on shore-based supervisory personnel. In traditional maritime supervision methods, supervisory personnel at the VTS (Vessel Traffic Service) center typically use radar or AIS equipment to identify densely populated areas within their jurisdiction. However, in mixed traffic scenarios with numerous vessels and more complex vessel navigation patterns, supervisory personnel often cannot promptly and accurately identify densely populated areas and further assess the risk status within those areas. To better assist shore-based supervisory personnel in controlling the safety situation in their supervised areas and promptly identify high-density, high-risk areas in mixed traffic scenarios, a method is urgently needed to extract areas with high vessel traffic density in the waters.

[0003] The density of ships can be calculated using density clustering algorithms, with DBSCAN being a representative example. In the DBSCAN algorithm, the settings of the neighborhood radius and minimum neighbor points significantly impact the final clustering result. Furthermore, each clustering process requires multiple manual calculations and adjustments of these parameters, making the algorithm lack sufficient intelligence in practical applications and failing to meet the needs of regulatory personnel for monitoring ships in mixed traffic scenarios. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method and system for monitoring high-density areas of vessels in mixed maritime traffic scenarios. The invention calculates areas with different vessel densities by analyzing the distance relationships between vessel points and the slope threshold of an ordered sequence of reachable distances from vessel points. This allows for the identification of areas with the highest vessel density. Different command assignment methods are employed for manned and unmanned vessels to assist shore-based monitoring personnel in scheduling and monitoring vessels at risk of collision in mixed traffic scenarios.

[0005] The technical means employed in this invention are as follows:

[0006] A method for monitoring high-density areas of vessels in a mixed maritime traffic scenario includes the following steps:

[0007] S1. Acquire ship AIS data in mixed maritime traffic scenarios;

[0008] S2. Extract the latitude and longitude coordinates of the ship's AIS data, and calculate the ordered sequence of ship core distance and reachability distance; calculate ship areas with different densities using the slope threshold method; determine high-density ship areas by calculating the average core density of each ship area.

[0009] S3. Dispatch vessels in multiple driving modes that pose a collision risk in high-density areas.

[0010] Furthermore, the aforementioned mixed maritime traffic scenario is a maritime traffic scenario that includes traditional vessels, remotely controlled vessels, and unmanned vessels.

[0011] Furthermore, the ordered sequence of ship core distances and reachable distances is calculated, including:

[0012] The ship location data is preprocessed using the OPTICS clustering algorithm. The neighborhood radius ε and the minimum number of neighboring points Minpts are set in the OPTICS algorithm to calculate the core density and reachability of ship points. In each iteration, the ship point with the smallest reachability within the neighborhood of the core ship point is selected as the core point of the next iteration. At the same time, the reachability value of the core point of the next iteration is added to the reachability ordered sequence. After the iteration is completed, the reachability ordered sequence of all ship points is obtained.

[0013] Furthermore, the neighborhood radius ε is set to a maximum value;

[0014] The latitude of the ship's latitude and longitude data is set to Dim, and the principle for setting the minimum neighbor number is as follows:

[0015] Minpts≥Dim+1.

[0016] Furthermore, different ship density zones were calculated using the slope threshold method, including:

[0017] Set the slope threshold based on the difference in reachable distances.

[0018] In the ordered sequence of reachable distances, find the intervals with downward and upward slopes. The point where the downward slope begins is taken as the starting point of a certain ship density region. After passing through a trough region, the maximum sequence point in the upward slope region where the reachable distance value is less than the starting point is taken as the ending point of the ship density region.

[0019] If the number of points contained within the interval between the starting point and the ending point is greater than Minpts, it is considered a ship density region; otherwise, it is not a ship density region.

[0020] Continue to determine other slope regions in the ordered sequence of reachable distances until all ship density regions are calculated.

[0021] Furthermore, the upslope region is composed of points with an upslope, which are defined as:

[0022]

[0023] The downslope region is composed of points with an upslope, and these points are defined as follows:

[0024]

[0025] Where p is the ship point in the ordered sequence of reachable distances, and r(p) is the reachable distance of the ship point. This is the slope threshold.

[0026] Furthermore, high-density areas of the ship are determined by calculating the average core density of each ship region, including by calculating the average core density in the following ways:

[0027] For the ship position dataset P = {p1, p2, ..., p...} n}, n∈N * After calculation, m ship density regions were obtained. For one of these regions, C... i =[s i ,e i The average core density of the ship points contained within the i∈m is calculated as follows:

[0028]

[0029] Where c i (p) represents the core distance value at point p in the i-th region. The average core density set M of the ship cluster is calculated for m clusters, where M = {Mcd1, Mcd2, ..., Mcd}. m}

[0030] Furthermore, the scheduling of vessels in various driving modes that pose a collision risk within high-density areas will be implemented, including:

[0031] For traditional vessels in the water, direct dispatch of traditional vessels is achieved via VHF.

[0032] For remotely controlled or unmanned vessels in waters, dispatch instructions are converted into short messages and sent to the shore-based remote control center of the vessel, which then dispatches the vessels at risk.

[0033] This invention also discloses a high-density area monitoring system for ships in a mixed maritime traffic scenario, comprising:

[0034] The data acquisition module is used to acquire ship AIS data in mixed maritime traffic scenarios;

[0035] The data processing module is used to extract the latitude and longitude coordinates of ship AIS data, calculate the ordered sequence of ship core distance and reachability distance; calculate ship areas with different density levels using the slope threshold method; and determine high-density ship areas by calculating the average core density of each ship area.

[0036] The instruction dispatch module is used to dispatch ships in various driving modes that pose a collision risk in high-density areas.

[0037] Compared with the prior art, the present invention has the following advantages:

[0038] 1. This invention proposes a method and system for monitoring high-density areas of ships in mixed maritime traffic scenarios. It can effectively assist ship monitoring personnel in discovering areas with high ship density in maritime traffic scenarios with mixed driving modes, enhance the ability of monitoring personnel to judge the navigation situation in the water, and further improve the level of monitoring of ships in mixed maritime traffic scenarios.

[0039] 2. This invention utilizes a slope threshold to calculate regions with different ship densities in an ordered sequence of reachable distances. When calculating ship density regions, the calculation parameters proposed in this invention do not need to be adjusted multiple times, which can reduce the degree of human involvement in the calculation process and indirectly improve the level of intelligence in ship supervision.

[0040] 3. This invention proposes using average core density to determine the clusters with the highest ship aggregation, further assisting regulators in identifying high ship density areas in mixed maritime traffic scenarios, reducing the effort required by regulators during the regulatory process, and improving the ability to assess the situation of the navigation environment in the water.

[0041] Based on the above reasons, this invention can be widely applied in fields such as mixed maritime traffic and maritime vessel safety supervision. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of a method for monitoring high-density areas of ships in a mixed maritime traffic scenario according to the present invention.

[0044] Figure 2 This is a schematic diagram of the reachable distance ordered sequence described in this invention.

[0045] Figure 3 The flowchart for calculating the slope threshold ship density region described in this invention.

[0046] Figure 4 The calculation results of the high-density ship area described in this invention are shown in the figure.

[0047] Figure 5 This is a schematic diagram of a high-density area monitoring system for ships in a mixed maritime traffic scenario, according to the present invention. Detailed Implementation

[0048] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0049] like Figures 1-4 As shown, this invention provides a method for monitoring high-density areas of ships in a mixed maritime traffic scenario, comprising the following steps:

[0050] S1. Acquire ship AIS data in mixed maritime traffic scenarios.

[0051] As a preferred embodiment of the present invention, the maritime mixed traffic scenario specifically refers to a maritime traffic scenario that includes traditional ships, remotely controlled ships, and unmanned ships.

[0052] S2. Extract the latitude and longitude coordinates of the ship's AIS data and calculate the ordered sequence of ship core distance and reachability distance; calculate ship areas with different densities using the slope threshold method; determine high-density ship areas by calculating the average core density of each ship area.

[0053] In a preferred embodiment of the present invention, the calculation of the ordered sequence of ship core distance and reachability distance is specifically as follows:

[0054] The ship location data is preprocessed using the OPTICS clustering algorithm. The neighborhood radius ε and the minimum number of neighboring points (Minpts) are set for the OPTICS algorithm to calculate the core density and reachability distance of ship points. In each iteration, the ship point with the smallest reachability distance within its neighborhood is selected as the core point for the next iteration, and its reachability distance value is added to the ordered reachability distance sequence. After iteration, an ordered reachability distance sequence for all ship points is obtained, as shown below.Figure 2 As shown.

[0055] The neighborhood radius of the ship point is ε, and the minimum number of neighborhood points is Minpts, specifically:

[0056] The neighborhood radius ε of the algorithm is set to a maximum value;

[0057] The latitude of the ship's latitude and longitude data is set to Dim, and the principle for setting the minimum neighbor number is as follows:

[0058] Minpts≥Dim+1.

[0059] As a further preferred embodiment of the present invention, the calculation of ship areas with different densities using the slope threshold method is illustrated in the flowchart below. Figure 3 As shown, specifically:

[0060] Step S21: Set the slope threshold as... The slope threshold is set to 0.05 by default, and the value of the slope threshold can be dynamically adjusted according to the difference between the data values.

[0061] Step S22: Find the intervals with downward and upward slopes in the ordered sequence of reachable distances. The point where the downward slope begins is taken as the starting point of a certain ship density region. After passing through a trough region, the maximum sequence point in the upward slope region where the reachable distance value is less than the starting point is taken as the ending point of the ship density region.

[0062] Step S23: If the number of points contained within the interval between the starting point and the ending point is greater than Minpts, then it is a ship density region; otherwise, it is not a ship density region.

[0063] Step S24: Continue to determine other slope regions in the reachable distance ordered sequence until all ship density regions are calculated.

[0064] The upward and downward slope intervals in step S22 are specifically as follows:

[0065] An uphill region is composed of points with an uphill slope, and these points are defined as follows:

[0066]

[0067] The downslope region is composed of points with an upslope, and these points are defined as follows:

[0068]

[0069] Where p is the ship point in the ordered sequence of reachable distances, and r(p) is the reachable distance of the ship point. This is the slope threshold.

[0070] As a further preferred embodiment of the present invention, the average core density calculation specifically involves: for the ship position dataset P = {p1, p2, ..., p...} n}, n∈N * After clustering using a density clustering algorithm, m dense clusters of ships are obtained. For one of these clusters, C... i =[s i ,e i The average core density of the ship points contained within the i∈m is calculated as follows:

[0071]

[0072] Among them, c i (p) represents the core distance value at point p in the i-th cluster; the average core density set M of the ship cluster is calculated for m clusters, where M = {Mcd1, Mcd2, ..., Mcd} m The final calculation results for the highest density ship area are shown in the diagram below. Figure 4 As shown.

[0073] S3. Dispatch vessels in multiple driving modes that pose a collision risk in high-density areas.

[0074] In a preferred embodiment of the present invention, the scheduling of ships with multiple driving modes specifically includes:

[0075] For traditional vessels in the water, the command dispatch module can directly dispatch traditional vessels via VHF;

[0076] For remotely controlled or unmanned vessels in waters, the instruction dispatch module can convert dispatch instructions into short messages and send them to the vessel's shore-based remote control center, which can then dispatch the vessels at risk.

[0077] like Figure 5 As shown, this invention also discloses a high-density area monitoring system for ships in a mixed maritime traffic scenario, comprising:

[0078] The data acquisition module is used to acquire ship AIS data in mixed maritime traffic scenarios;

[0079] The data processing module is used to extract the latitude and longitude coordinates of ship AIS data, calculate the ordered sequence of ship core distance and reachability distance; calculate ship areas with different density levels using the slope threshold method; and determine high-density ship areas by calculating the average core density of each ship area.

[0080] The instruction dispatch module is used to dispatch ships in various driving modes that pose a collision risk in high-density areas.

[0081] The embodiments of the present invention are described simply because they correspond to those in the embodiments above. For any similarities, please refer to the descriptions in the embodiments above, which will not be elaborated here.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring high-density areas of ships in a mixed maritime traffic scenario, characterized in that, The aforementioned mixed maritime traffic scenario refers to a maritime traffic scenario that includes traditional vessels, remotely controlled vessels, and unmanned vessels; the method includes the following steps: S1. Acquire ship AIS data in mixed maritime traffic scenarios; S2. Extract the latitude and longitude coordinates of the ship's AIS data, and calculate the ordered sequence of ship core distance and reachability distance; calculate ship areas with different densities using the slope threshold method; determine high-density ship areas by calculating the average core density of each ship area. S3. Dispatch vessels with multiple driving modes that pose a collision risk in high-density areas; The ordered sequence of ship core distances and reachable distances is calculated, including: The ship location data is preprocessed using the OPTICS clustering algorithm. The neighborhood radius ε and the minimum number of neighborhood points Minpts of the OPTICS algorithm are set to calculate the core density and reachability of ship points. In each iteration, the ship point with the smallest reachability within the neighborhood of the core ship point is selected as the core point of the next iteration. At the same time, the reachability value of the core point of the next iteration is added to the reachability ordered sequence. After the iteration is completed, the reachability ordered sequence of all ship points is obtained. Among them, the ship density zones with different concentrations were calculated using the slope threshold method, including: Set the slope threshold based on the difference in reachable distances. ; In the ordered sequence of reachable distances, find the intervals with downward and upward slopes. The point where the downward slope begins is taken as the starting point of a certain ship density region. After passing through a trough region, the maximum sequence point in the upward slope region where the reachable distance value is less than the starting point is taken as the ending point of the ship density region. If the number of points contained within the interval between the starting point and the ending point is greater than Minpts, it is considered a ship density region; otherwise, it is not a ship density region. Continue to identify other slope regions in the ordered sequence of reachable distances until all ship density regions are calculated. This includes scheduling vessels in various driving modes that pose a collision risk in high-density areas, including: For traditional vessels in the water, direct dispatch of traditional vessels is achieved via VHF. For remotely controlled or unmanned vessels in waters, dispatch instructions are converted into short messages and sent to the shore-based remote control center of the vessel, which then dispatches the vessels at risk. High-density areas of a ship are determined by calculating the average core density of each ship region, including by calculating the average core density in the following ways: For ship location datasets After calculation, m ship density zones were obtained. For one of these zones... The average core density of the ship points it contains is calculated as follows: in This represents the core distance value at point p in the i-th region. The average core density set M of the ship cluster is calculated for m clusters, where... .

2. The method for monitoring high-density areas of ships in a mixed maritime traffic scenario according to claim 1, characterized in that, The neighborhood radius ε is set to a maximum value; The latitude of the ship's latitude and longitude data is set to Dim, and the principle for setting the minimum neighbor number is as follows: Minpts≥Dim+1.

3. The method for monitoring high-density areas of ships in a mixed maritime traffic scenario according to claim 1, characterized in that, An uphill region is composed of points with an uphill slope, and these points are defined as follows: ； The downslope region is composed of points with an upslope, and these points are defined as follows: ； in p For the ship points in the ordered sequence of reachable distances, r(p) This represents the reachable distance corresponding to the ship's location. This is the slope threshold.

4. A high-density area monitoring system for ships in a mixed maritime traffic scenario, characterized in that, The aforementioned mixed maritime traffic scenario refers to a maritime traffic scenario that includes traditional vessels, remotely controlled vessels, and unmanned vessels; including: The data acquisition module is used to acquire ship AIS data in mixed maritime traffic scenarios; The data processing module is used to extract the latitude and longitude coordinates of ship AIS data, calculate the ordered sequence of ship core distance and reachability distance; calculate ship areas with different density levels using the slope threshold method; and determine high-density ship areas by calculating the average core density of each ship area. The instruction dispatch module is used to dispatch ships in various driving modes that pose a collision risk in high-density areas. The ordered sequence of ship core distances and reachable distances is calculated, including: The ship location data is preprocessed using the OPTICS clustering algorithm. The neighborhood radius ε and the minimum number of neighborhood points Minpts of the OPTICS algorithm are set to calculate the core density and reachability of ship points. In each iteration, the ship point with the smallest reachability within the neighborhood of the core ship point is selected as the core point of the next iteration. At the same time, the reachability value of the core point of the next iteration is added to the reachability ordered sequence. After the iteration is completed, the reachability ordered sequence of all ship points is obtained. Among them, the ship density zones with different concentrations were calculated using the slope threshold method, including: Set the slope threshold based on the difference in reachable distances. ; In the ordered sequence of reachable distances, find the intervals with downward and upward slopes. The point where the downward slope begins is taken as the starting point of a certain ship density region. After passing through a trough region, the maximum sequence point in the upward slope region where the reachable distance value is less than the starting point is taken as the ending point of the ship density region. If the number of points contained within the interval between the starting point and the ending point is greater than Minpts, it is considered a ship density region; otherwise, it is not a ship density region. Continue to identify other slope regions in the ordered sequence of reachable distances until all ship density regions are calculated. This includes scheduling vessels in various driving modes that pose a collision risk in high-density areas, including: For traditional vessels in the water, direct dispatch of traditional vessels is achieved via VHF. For remotely controlled or unmanned vessels in waters, dispatch instructions are converted into short messages and sent to the shore-based remote control center of the vessel, which then dispatches the vessels at risk. High-density areas of a ship are determined by calculating the average core density of each ship region, including by calculating the average core density in the following ways: For ship location datasets After calculation, m ship density zones were obtained. For one of these zones... The average core density of the ship points it contains is calculated as follows: in This represents the core distance value at point p in the i-th region. The average core density set M of the ship cluster is calculated for m clusters, where... .

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