A method for obtaining marine traffic flow complexity based on field theory

Abstract

The application relates to a field theory-based marine traffic flow complexity acquisition method, which comprises the following steps: acquiring position information and size information of a current ship, establishing a ship self attribute field according to the position information and the size information; acquiring channel line position information of current ship navigation, establishing a channel boundary field according to the position information and the channel line position information; acquiring speed information of each ship in a sea area where the current ship is located, and establishing a ship speed field according to the speed information of each ship in the sea area where the current ship is located; acquiring essential complexity according to the position information, the ship self attribute field, the channel boundary field and the ship speed field; acquiring essential complexity of each ship in a current sea area, acquiring a complexity threshold according to the essential complexity of each ship, and acquiring a cognitive complexity evaluation index in the current sea area according to the essential complexity and the complexity threshold. Compared with the prior art, the traffic flow complexity obtained by the application can more accurately represent an actual traffic flow state.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ship control, in particular to a method for obtaining sea traffic flow complexity based on field theory. BACKGROUND

[0002] With the deepening of globalization, the development of foreign trade is driven, and then the sea transportation industry has become the first choice for logistics trade. Water transportation industry has the advantages of low cost and large freight volume, and continues to grow under the promotion of global economicization and Internet economy. The trend of waterway traffic flow intensification, diversification, and ship large-scale and high-speed development not only increases the difficulty of waterway traffic management, but also makes the waterway navigation environment increasingly complex. The increasing number of ships and types of ships in the channel increase the complexity of traffic flow, increase the risk of navigation, and increase the number of accidents. Therefore, developing and verifying the traffic flow complexity tool is a necessary means to improve the safety of sea transportation. Therefore, the research on the complexity of sea transportation is particularly important.

[0003] In the existing sea safety analysis method, the complexity of sea traffic flow is an important evaluation index. The complexity of traffic system is used to measure the complexity of a certain traffic system and the capacity of the system. It is divided into cognitive complexity and essential complexity, that is, the difference between macro and micro analysis angles. The essential complexity is the influence ability of the ship behavior, the higher the complexity value, the greater the influence of the ship behavior on the traffic system. Cognitive complexity is from a macro perspective, and recognizes the water traffic situation through density. The higher the complexity of sea traffic flow, the greater the influence on sea ship navigation, and it is more likely to cause dangerous situations or difficult collision avoidance operations, which hinders the monitoring of the sea area. The macro traffic flow complexity model determines the complexity by considering the position of the ship, the congestion degree and the scattering state.

[0004] Traffic flow complexity estimation is still an active research area. However, there are many challenges in identifying the natural properties of sea traffic and estimating the complexity of traffic flow at different geographical locations and time intervals. The current research on the complexity of sea traffic flow does not consider the correlation between traffic participants, so it is difficult to describe the complexity of the entire traffic system generated by the interaction of each traffic participant in the traffic flow system.

[0005] The current research model of sea traffic flow complexity is divided into macro and micro models. The movement of the ship has certain limitations in the inland waterway, and the macro model will blur the ship speed, ship turning angle and other ship traffic flow elements. The micro model often underestimates the influence of the channel on the ship and the influence of the interaction between each ship traffic participant on the traffic situation in the real situation. Therefore, the research on the complexity of sea traffic flow is slightly insufficient.

[0006] Chinese patent application No. CN201711279174.6 discloses a ship scheduling method based on a traffic capacity limited waterway. The ship scheduling method uses the concept of "time slot" in the communication industry to realize the segmentation of waterway resources. When allocating waterway resources, the principle of prioritizing key ships and considering fairness is adopted, and factors such as ships, waterways, and tides are comprehensively considered. The system automatically prepares a ship scheduling plan according to the scheduling scheme, greatly improving the efficiency of ship scheduling and ensuring the overall efficiency of the port. However, this method does not consider the relationship between ships and the boundary line between ships and waterways.

[0007] In summary, the existing method does not consider the influence of the characteristic relationship between ships and the boundary line between ships and waterways on traffic complexity, as well as the influence of the characteristics of different ships on traffic complexity. SUMMARY

[0008] The purpose of the present application is to overcome the shortcomings of the prior art and provide a field-based maritime traffic flow complexity acquisition method. The method considers the influence of the characteristic relationship between ships and the boundary line between ships and waterways on traffic complexity, as well as the influence of the characteristics of different ships on traffic complexity, so that the traffic flow complexity can more accurately reflect the actual traffic situation.

[0009] The purpose of the present application can be achieved by the following technical solutions:

[0010] In one aspect of the present application, a field-based maritime traffic flow complexity acquisition method is provided, comprising the following steps: obtaining the position information and size information of the current ship, establishing a ship attribute field according to the position information and size information; obtaining the waterway line position information of the current ship, establishing a waterway boundary field according to the position information and waterway line position information; obtaining the speed information of each ship in the current sea area, establishing a ship speed field according to the speed information; obtaining the essential complexity according to the position information, the ship attribute field, the waterway boundary field, and the ship speed field; obtaining the essential complexity of each ship in the current sea area, obtaining the complexity threshold of the current sea area according to the essential complexity of each ship, and obtaining the cognitive complexity evaluation index in the current sea area according to the essential complexity and the complexity threshold.

[0011] As a preferred technical solution, the establishment process of the ship attribute field includes the following steps: obtaining the radiation factor of the current ship in the x and y axis directions according to the size information; and obtaining the ship attribute field using the following formula:

[0012]

[0013] Wherein, (x, y) is the longitude and latitude coordinate of the ship, (x i , y i ) is the longitude and latitude coordinate of other ships at a certain time, σ x , σ y is the radiation factor of the current ship in x, y axis direction respectively.

[0014] As a preferred technical solution, the establishment process of the channel boundary field comprises the following steps: according to the position information and the channel line position information, the transverse distance information of the ship from the two sides of the channel is obtained; according to the angle information between the ship speed and the channel cross section, the boundary radiation factor of the left and right channels is obtained, and the channel boundary field is obtained by using the following formula:

[0015]

[0016] Wherein, r a1 =(y ship -y lane1 ), r a2 =(y ship -y lane2 ), y ship is the ship position, y lane1 is the left channel boundary position, y lane2 is the right channel boundary position, σ l1 , σ l2 is the boundary radiation factor of the left and right channels respectively.

[0017] As a preferred technical solution, the establishment process of the ship speed field comprises the following steps: according to the speed information of each ship, the average speed of each ship in the current sea area is obtained; according to the average speed, the radiation factor of the speed field of the current ship is obtained; the ship speed field is obtained by using the following formula:

[0018]

[0019] Wherein, σ is the radiation factor of the speed field of the current ship, v is the speed of the current ship, is the average speed of each ship in the current sea area.

[0020] As a preferred technical solution, the acquisition process of the intrinsic complexity comprises the following steps: according to the ship attribute field, the channel boundary field and the ship speed field, the total field of the current ship is obtained; according to the total field and the position information, the intrinsic complexity of the current ship is obtained.

[0021] As a preferred technical solution, the complexity threshold is obtained by using the following method:

[0022] The maximum complexity that can be accommodated after limiting the number of maximum ships in the current sea area is obtained through traffic state investigation as the complexity threshold.

[0023] As a preferred technical solution, the obtaining process of the cognitive complexity evaluation index comprises the following steps: according to the complexity threshold, the ship essential complexity is divided into multiple grade intervals; the ships in the current sea area belonging to each of the grade intervals are counted to obtain the proportion in each of the grade intervals; and according to the proportion, the cognitive complexity evaluation index is obtained according to a preset rule.

[0024] As a preferred technical solution, the preset rule comprises the following rules: when the essential complexity is divided into four grade intervals A, B, C and D, if P A > 0.5, the cognitive complexity evaluation index is very complex, if P A < 0.5, P B > 0.5, the cognitive complexity evaluation index is relatively complex, if P A < 0.5 and P B < 0.5 and P C > 0.5, the cognitive complexity evaluation index is not complex, if P A < 0.5 and P B < 0.5 and < 0.5, the cognitive complexity evaluation index is very easy, wherein P A , P B , P C are the ratios of the number of essential complexity falling into A, B and C intervals to the total number respectively.

[0025] As a preferred technical solution, it further comprises the following steps: according to the cognitive complexity evaluation index, ship diversion suggestion information is sent out.

[0026] Compared with the prior art, the present application has the following advantages:

[0027] (1) The mutual influence between ships, the influence of channel boundary on ships, and the influence of speed and angle of ships are comprehensively considered at the micro level of traffic flow, each field is built according to the above traffic participants, and then each field is superimposed to obtain the essential complexity, so that the traffic flow complexity can more accurately reflect the actual traffic situation.

[0028] (2) For each ship complexity in the water area, draw the location distribution of traffic complexity and visualize it with different colors representing different complexity values. Use the computer to get the complexity threshold value of this area, and then divide the complexity value of the entire measured sea area into regions according to the threshold value, calculate the proportion of each complexity value region, and get the system cognitive complexity of the measured sea area. This helps maritime traffic surveillance personnel to more intuitively and conveniently understand the distribution of traffic complexity, assist decision-making and contribute to navigation safety. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 Flowchart of the method for obtaining maritime traffic flow complexity based on field theory in the embodiment;

[0030] Figure 2 Schematic diagram for description of ships in different motion states;

[0031] Figure 3 Schematic diagram of complexity difference under different traffic densities;

[0032] Figure 4 Schematic diagram of complexity difference under the same traffic density;

[0033] Figure 5a Schematic diagram of the ship's own attribute field strength function in the embodiment when the complexity value has a large influence;

[0034] Figure 5b Schematic diagram of the ship's own attribute field strength function in the embodiment when the complexity value has a small influence;

[0035] Figure 6a Schematic diagram of the ship's unilateral channel field strength function in the embodiment when the complexity value has a large influence;

[0036] Figure 6b Schematic diagram of the ship's unilateral channel field strength function in the embodiment when the complexity value has a small influence;

[0037] Figure 7a Schematic diagram of the ship's speed field strength function in the embodiment when the complexity value has a large influence;

[0038] Figure 7b Schematic diagram of the ship's speed field strength function in the embodiment when the complexity value has a small influence. DETAILED DESCRIPTION

[0039] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort should fall within the protection scope of the present application.

[0040] Embodiments

[0041] As Figure 1 described, the embodiment provides a sea traffic flow complexity acquisition method based on field theory. The sea traffic flow complexity influencing factors are the mutual influence between ships, the influence of channel boundaries on ships, and the speed and included angle of ships from a micro level. It can be found that the artificial potential field theory can effectively depict the influence state of traffic participants on ships in the sea traffic environment, and the comprehensive influence of the entire traffic environment is obtained through vector superposition. Therefore, the embodiment considers the influence of ship speed, position, and direction angle on traffic complexity. Therefore, the theory based on potential field is considered to establish a field strength model of sea ships and traffic participants on the sea area, then the superposition of fields is performed to form a comprehensive field strength model, and the comprehensive field strength of the ship is obtained to represent the essential complexity of the traffic system. The method includes the following steps:

[0042] Step S1, a ship itself attribute field, a channel boundary field, and a ship speed field are respectively established, and the details are as follows:

[0043] Step S101, a ship itself attribute field is established: an influence function form consistent with the change trend of the sea traffic flow complexity is selected, and a Gaussian influence function is selected:

[0044]

[0045] According to the ship length and ship width data of the ships in the entire selected research sea area, the average ship length and ship width of the sea area are calculated.

[0046]

[0047] wherein n is the total number of ships in the test sea area, and l i and w i respectively represent the ship length and ship width of each ship in the sea area.

[0048] According to and , the radiation factors σ x and σ y in the x and y axis directions are defined:

[0049]

[0050]

[0051] The complexity of the ship traffic flow is constructed based on the spatial-based potential field intensity function, i.e. the self attribute field intensity:

[0052]

[0053] Where x, y are the longitude and latitude of the ship, x i , y i are the longitude and latitude of other ships in the water area at a certain time. As Figure 5a , Figure 5b described is the schematic diagram of different field intensity formed by different ships, different ship lengths and different ship widths, Figure 5a The ship length and ship width described in the figure are more different from the average ship length and ship width of the test area, and the three-dimensional curve is steeper, and the complexity value is higher, and Figure 5b The ship length and ship width described in the figure are less different from the average ship length and ship width of the test area, and the trend is more gentle, and the complexity value is lower. In the figure, the x-axis and y-axis are the ship coordinates, and the z-axis is the field intensity.

[0054] Step S102, establish the channel boundary field: when the ship is sailing in the channel, the channel sets the navigation mark to ensure the safe navigation of the ship. The channel is divided into different levels, and the minimum channel depth, width, curvature radius and clearance (net height and net span) above the water surface are respectively specified. As Figure 2 described is the description schematic diagram of the ship in different motion states in the embodiment, the dotted line in the figure is the channel boundary, which prevents the ship from crossing it and sailing out of the divided channel to cause an accident. In principle, the ship is not allowed to cross, so we think that the potential field force increases faster when it is closer to the channel boundary. If it is necessary to approach the boundary line due to the channel situation, it is considered that the traffic condition is complex, and the change trend of the field intensity is considered to be consistent with the change trend of the Gaussian function. Therefore, the Gaussian function is considered to be selected to depict the channel boundary field.

[0055] According to the ship position y ship and the channel line position y lane , the lateral distance r a of the ship to the channel boundary is calculated:

[0056] r a =(y ship -y lane )

[0057] The lateral distances of the ship to the left and right channel boundaries y lan , y lane2 are r a1 , r a2 respectively.

[0058] r a1 = (y ship -y lane1 )

[0059] r a2 = (y ship -y lane2 )

[0060] Introducing the radiation factor σ l representing the channel boundary field, which is considered to be related to the angle between the ship's running direction and the channel cross section. Let θ represent the angle between the ship's speed and the channel cross section. In actual situations, the smaller the angle between the speed angle and the channel cross section, i.e. the smaller θ, the smaller sin(θ), which indicates that the ship's position is more complex and the traffic complexity is higher.

[0061] The left and right channel boundary radiation factors are σ l1 and σ l2 , respectively.

[0062] σ l1 = sin(θ1)

[0063] σ l2 = sin(θ2)

[0064] The channel boundary field strength functions E L1 and E L2 are established for the left and right sides of the channel, respectively.

[0065]

[0066]

[0067] The channel boundary field is constructed based on the complexity of the ship traffic flow.

[0068] E L = E L1 + E L2

[0069] As Figure 6a , Figure 6b described is a field strength diagram formed by a single side channel, Figure 6a describes the field strength formed when the angle between the ship's sailing angle and the channel vertical section is smaller, at which time the ship has a greater impact on the complexity of the channel, so the image is steeper, and the Figure 6b described ship position has a smaller impact on the complexity, and the curve trend is more moderate. In the figure, the x-axis and y-axis are the ship coordinates, and the z-axis is the field strength of the field.

[0070] Step S103, establishing a ship speed field: first, the average speed of the ship is calculated by calculating the speed of all ships in the studied sea area

[0071]

[0072] Radiation factor σ introduced into the ship speed field v , which is related to the speed dispersion degree of ships in the sea area, v i is the speed of other ships in the sea area at a certain time

[0073]

[0074] The ship speed field strength function based on the complexity of ship traffic flow is constructed.

[0075]

[0076] Where x, y are the longitude and latitude of the ship, x i , y i are the longitude and latitude of other ships in the sea area at a certain time.

[0077] As Figure 7a , Figure 7b The figure shows the influence of ship speed on field strength, Figure 7a The difference between the ship speed and the average ship speed in the test area is larger, which means that the ship complexity value is larger, and the three-dimensional curve is steeper, and Figure 7b The ship speed is closer to the average ship speed, the ship complexity value is lower, and the trend is more gentle. In the figure, the x-axis and y-axis are the ship coordinates, and the z-axis is the field strength.

[0078] Steps S2, S3, superimpose the ship's own attribute field, the channel boundary field and the ship speed field to establish the total field:

[0079] When considering the traffic complexity of a certain sea area, the traffic participants in the area mainly include the position relationship and speed relationship of a single ship, and the channel line, so the total potential field strength is superimposed by the ship's own attribute field E S , the channel boundary field E L , and the ship speed field E V , and the value is the essential complexity value C i . The total field strength expression is:

[0080] E=E S +E L +E V

[0081] C i =F i

[0082] In the case of setting the maximum value of the number of ships in the region, the complexity threshold of the region, i.e., the maximum complexity that the region can withstand, is calculated by computer. For example, Figure 3 The above is a schematic diagram of complexity difference under different traffic densities. Figure 4 The above is a schematic diagram of complexity difference under the same traffic density.

[0083] Step S4: Visualization of ship intrinsic complexity. The unknown data points are estimated by using the known discrete data points in space to form a continuous surface passing through all data points. The spatial interpolation method used is spline interpolation. After interpolating the traffic complexity values of all positions in the water area, the geographical distribution of traffic complexity can be plotted.

[0084] According to the comprehensive field intensity distribution of different ships, the complexity of different ships in the sea area is obtained. Since the field intensity in this paper is dimensionless, the potential field in the figure only represents the complexity value, so there is no specific unit. In order to better describe the complexity of ships in the sea area, the color depth represents the relationship between the comprehensive field intensity, and the darker color represents higher complexity, and the lighter color represents smaller complexity. The traffic complexity of the sea area in a certain period of time is marked with different colors, which can be used for induction and diversion of sea navigation, and can help them make decisions. It is also helpful for the application of unmanned ship system, and helps to make sea navigation safer and play an early warning role.

[0085] Step S5: Traffic system cognitive complexity calculation and rating. According to the intrinsic complexity calculated by each ship in the measured sea area, the complexity value region is divided. The intrinsic complexity of the entire system is divided into four intervals A, B, C, and D, and the interval range is as follows:

[0086] A: C A ≤C i <C max

[0087] B: C B ≤C i <C A

[0088] C: C C ≤C i <C B

[0089] D: C min ≤C i <C C

[0090] Among them, C iC represents the essential complexity of ship calculations. max This indicates that, using a computer, and limiting the maximum number of ships, the maximum complexity that this area can theoretically accommodate is calculated. (C) min The minimum complexity is generally taken as 0, C A C B C C Let represent the thresholds for complexity partitioning, calculated as follows:

[0091] C A =C max -0.25*(C max -C min )

[0092] C B =C max -0.5*(C max -C min )

[0093] C C =C max -0.75*(C max -C min )

[0094] Calculate the percentage of inherent complexity of ships in four zones within the sea area. Calculate the percentage for zones A, B, C, and D respectively, denoted as P. A P B P C P D :

[0095]

[0096] N = n A +n B +n C +n D

[0097] Where N is the total number of ship inherent complexity values ​​in the measured sea area, n A n B n C n D These represent the number of ships in each zone within this sea area whose complexity value belongs to that zone.

[0098] P A A value greater than 0.5 indicates that the transportation system in this sea area is extremely complex. A <0.5, P B >0.5 indicates more complex, P A <0.5, P B <0.5, P C >0.5 indicates that it is not complex, P A <0.5, PB <0.5, P C <0.5 indicates that the traffic situation is very relaxed.

[0099] When the overall area complexity is rated as A, it indicates that the maritime traffic control personnel need to intervene to control the entry of ships in this area. When rated as B, it indicates that the area is relatively complex, and ships can be released to enter the area as appropriate, and the highest complexity ship in the area at this moment can be locked, because it is the ship that has the greatest impact on the complexity of the area, and it should be monitored in real time, and appropriate decisions can be made if necessary. When rated as C, it indicates that the area is not complex, and the monitoring personnel can keep an eye on it. When rated as D, it indicates that the traffic control personnel can release ships to enter the area to reduce the complexity of other areas, so as to achieve the effect of guiding and inducing flow.

[0100] This embodiment considers using the theory of ship potential field to calculate the intrinsic complexity of maritime traffic flow, and realizes the optimization and improvement of the calculation of maritime traffic flow complexity. Borrowing from field theory to study the motion law of waterborne ships, a new ship intrinsic complexity field is established. From a new perspective, the calculation method of maritime traffic flow complexity is understood. Through comprehensive analysis of the complexity of maritime traffic flow from a micro perspective, the complexity of each ship in each time period in the water area is obtained, and it is visualized, which can be used for traffic flow system diversion and induction. Set the complexity value interval range, calculate the proportion of each complexity interval in the measured sea area to get the overall cognitive complexity of the measured sea area. From micro research to macro research, both macro and micro are considered, making the control of maritime traffic complexity more comprehensive. It can help maritime traffic monitoring personnel to intuitively and conveniently understand the distribution of traffic complexity, and help them make decisions. It can also release their identification pressure and contribute to navigation safety.

[0101] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for obtaining marine traffic flow complexity based on field theory, characterized in that, It comprises the following steps: Obtain the position information and scale information of the current ship, and establish a ship self attribute field according to the position information and scale information; Obtain the channel line position information of the current ship's current navigation, and establish a channel boundary field according to the position information and channel line position information; Obtain the speed information of each ship in the current sea area, and establish a ship speed field according to the speed information; Obtain the essential complexity according to the position information, the ship self attribute field, the channel boundary field and the ship speed field; Obtain the essential complexity of each ship in the current sea area, obtain the complexity threshold of the current sea area according to the essential complexity of each ship, and obtain the cognitive complexity evaluation index in the current sea area according to the essential complexity and the complexity threshold, The establishment process of the ship self attribute field comprises the following steps: According to the scale information, the radiation factor of the current ship in the axial direction is obtained , axial direction The ship self attribute field is obtained by using the following formula: wherein, is the latitude of the ship, is the latitude of the other ship at the time, , are the longitudinal and latitude of the current ship, 、 the radiation factor in the axial direction, The establishment process of the channel boundary field comprises the following steps: Obtain the lateral distance information of the ship from the two sides of the channel according to the position information and the channel line position information; Obtain the boundary radiation factor of the left and right channels according to the angle information between the ship speed and the channel cross section, The channel boundary field is obtained by using the following formula: wherein , , is a ship position, is a left lane boundary position, is a right lane boundary position, 、 are left and right lane boundary radiation factors, respectively, The establishment process of the ship speed field comprises the following steps: Obtain the average speed of each ship in the current sea area according to the speed information of each ship; Obtain the radiation factor of the speed field of the current ship according to the average speed; The ship speed field is obtained by using the following formula: wherein, is the radiation factor for the speed field of the current ship, is the speed of the current ship, is the average speed of the ships in the current sea area, The obtaining process of the essential complexity comprises the following steps: Obtain the total field of the current ship according to the ship self attribute field, the channel boundary field and the ship speed field; Obtain the essential complexity of the current ship according to the total field and the position information.

2. The method for obtaining marine traffic flow complexity based on field theory according to claim 1, characterized in that, The complexity threshold is obtained by using the following method: Through traffic status investigation, obtain the maximum complexity that can be accommodated after limiting the maximum number of ships in the current sea area as the complexity threshold.

3. The method for obtaining marine traffic flow complexity based on field theory according to claim 1, characterized in that, The obtaining process of the cognitive complexity evaluation index comprises the following steps: Divide the ship essential complexity into multiple grade intervals according to the complexity threshold; Statistically analyze the ships in each grade interval in the current sea area to obtain the proportion of each grade interval; Obtain the cognitive complexity evaluation index according to the proportion and the preset rule.

4. The method for obtaining marine traffic flow complexity based on field theory according to claim 3, characterized in that, The preset rule comprises the following rule: When the essential complexity is divided into four intervals of A, B, C, D, if , the cognitive complexity evaluation index is very complex, if , the cognitive complexity evaluation index is relatively complex, if , the cognitive complexity evaluation index is not complex, if , the cognitive complexity evaluation index is very easy, wherein , , respectively are the ratio of the number of the essential complexity falling into A, B, C interval to the total number.

5. The method for obtaining marine traffic flow complexity based on field theory according to claim 1, characterized in that, It further comprises the following steps: According to the essential complexity of each ship, estimate other unknown points in the current sea area by using interpolation method to obtain the cognitive complexity distribution information in the current sea area; According to the cognitive complexity distribution information and the essential complexity, send a visualization signal to the visualization terminal.

6. The method for obtaining marine traffic flow complexity based on field theory according to claim 1, characterized in that, It further comprises the following steps: According to the cognitive complexity evaluation index, send ship diversion suggestion information.

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