A Method and System for Rapid Route Generation Oriented to Complex Maritime Environments

Abstract

The present invention discloses a method and system for quickly generating a shipping route for a complex maritime environment, which relates to the technical field of maritime traffic management. The method includes: S1, collecting and integrating real-time marine environment data and ship dynamic information; S2, performing congestion analysis and prediction based on the traffic flow data of the water area; S3, generating an optimized shipping route planning scheme according to the analysis results; S4, dynamically adjusting the shipping route plan to cope with unexpected maritime environments. The method and system for quickly generating a shipping route for a complex maritime environment enable ships to avoid high-density or congested areas in complex waters, thereby improving the overall utilization efficiency of waterway resources and avoiding the problem of decreased overall efficiency due to local dredging. It can quickly respond to complex environmental changes such as tidal changes, sudden changes in meteorological conditions, and sudden increases in traffic flow, and solves the problem of how to analyze and schedule traffic flow in complex waters to solve waterway congestion in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of maritime traffic management, and particularly to a method and system for quickly generating a shipping route for a complex maritime environment. Background Art

[0002] In a complex maritime environment, the efficient utilization of waterway resources is crucial for ensuring the safety and smoothness of waterborne traffic. Especially in the areas around ports, estuary confluences, and other high-density ship areas, the problem of waterway congestion frequently occurs, directly affecting shipping efficiency and ship safety.

[0003] The existing technologies mainly analyze and dispatch traffic flow in the following ways: Radar and Automatic Identification System (AIS) are used to obtain information such as the position, speed, and heading of ships. Through data visualization technology, a maritime traffic situation map is generated to provide basic data for traffic flow analysis. However, this method has the problem of data redundancy in the case of overly dense traffic flow and is difficult to quickly identify abnormal situations; Regularized waterway design, traditional waterway design relies on fixed or regularized shipping routes to ensure that ships sail along the established paths. Although this method avoids the risk of collision between ships to a certain extent, it lacks the ability of dynamic dispatching in complex waters and cannot cope with sudden situations or traffic surges; Traffic dispatchers conduct manual intervention by observing the real-time traffic conditions of the waterway and combining with the pre-determined sailing plan. This method is overly dependent on the experience and judgment of dispatchers, with low processing efficiency, and is prone to errors when facing complex or large-scale traffic management. Although the above technologies can monitor and manage the waterway traffic flow to a certain extent, when dealing with high-density traffic in a complex maritime environment, there are still the following limitations: The existing methods are usually based on static rules or manual experience and lack the ability to adapt to dynamic changes in real time, especially in scenarios such as tidal changes and sudden meteorological conditions; The data processing and optimization decision-making for large-scale traffic flow rely on manual intervention, with low automation and intelligence levels, and it is difficult to quickly respond to waterway congestion problems; The existing technologies focus more on local traffic flow management and lack the ability to optimize and dispatch multiple shipping routes and multiple nodes in complex waters, which is likely to lead to the problem of unclogging local waterways while reducing the overall traffic efficiency. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for quickly generating a shipping route for a complex maritime environment, and to solve the problem of how to analyze and dispatch traffic flow in complex waters to solve waterway congestion in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A method for quickly generating a shipping route for a complex maritime environment, the method comprising:

[0006] S1. Collect and integrate real-time marine environmental data and ship dynamic information. S1 includes: assigning initial weights to each type of data, setting the importance factors of the data, calculating the final weights of the data using the time update frequency, and fusing multi-source data with these to generate a unified environmental data input.

[0007] S2. Conduct congestion analysis and prediction based on the traffic flow data of water areas, including modeling the traffic flow and calculating the traffic pressure of each water area. The specific formula is:

[0008] × ;

[0009] Among them, V x represents the traffic flow load degree value of the water area, V represents the total global traffic load value, R x represents the degree of obstruction of ship traffic flow within the water area, R 1 , R 2 , ……, R n represents the flow resistance values of each water area, n represents the number of water areas, and x represents the index of different water areas.

[0010] S3. Generate an optimized route planning scheme according to the analysis results, including dividing the route planning water area into multiple sections, setting the navigation speed for each section, calculating the course angle of the path in different water areas based on the starting point and ending point of the target path, and optimizing the route to ensure the minimum total path cost. The specific formula is: ;

[0011] Among them, θ 1 represents the angle between the initial course and the boundary normal when the route enters from one area to another, θ 2 represents the angle between the adjusted course and the boundary normal after the route enters the new area, v 1 represents the navigation speed of the ship in the current area, v 2 represents the navigation speed of the ship when entering the new area.

[0012] S4. Dynamically adjust the route planning to cope with the sudden maritime environment.

[0013] Preferably, S1 includes:

[0014] Assigning initial weights to each type of data, setting the importance factors of the data, calculating the final weights of the data using the time update frequency, and fusing multi-source data with these to generate a unified environmental data input. The specific formula for calculating the final weight of the data is: Q = m×c×Δt;

[0015] Among them, Q represents the importance weight of the data, m represents the credibility value of the data collection source, c represents the importance factor value of the data, Δt represents the update time interval of data collection, and t represents time.

[0016] Preferably, the S4 includes:

[0017] Establish a route adaptability model, adjust the response speed and environmental carrying capacity according to environmental changes, dynamically update the route parameters, and generate a new route plan to adapt to environmental changes. The specific formula for dynamically updating the route parameters is: P t+1 =P t +r×P t ×(1-P t / K);

[0018] Among them, P t+1 represents the route adaptability value at the next moment, P t represents the route adaptability value at the current moment, r represents the reaction speed of the route adaptability to external environmental changes, K represents the maximum route adaptability value allowed by the current maritime environment, and t represents time.

[0019] Preferably, the value R x of the obstruction degree of ship traffic flow in the water area in the S2 is calculated by the formula:

[0020] R x =D / (W×S);

[0021] Among them, R x represents the value of the obstruction degree of ship traffic flow in the water area, D represents the number of ships per unit area, W represents the width of the navigable channel in the area, and S represents the average sailing speed of the ships.

[0022] Preferably, the calculation formula for the sailing speed in the S3 is: ;

[0023] Among them, v represents the sailing speed of the area, F represents the comprehensive driving force of the regional environment, and h represents the unit mass of the ship.

[0024] Preferably, the calculation formula for the credibility value m of the data collection source in the S1 is:

[0025] m=A / B;

[0026] Among them, m represents the credibility value of the data collection source, A represents the accuracy of the collection device, and B represents the failure rate of the device.

[0027] Preferably, the calculation formula for the importance factor value c of the data in the S1 is: c=G 1 / G;

[0028] Among them, c represents the importance factor value of the data, and G 1 represents the data impact weight, and G represents the total weight.

[0029] Preferably, the calculation formula for the response speed r of the route adaptability to external environmental changes in S4 is: r = ΔP 环境 / ΔT;

[0030] Among them, r represents the response speed of the route adaptability to external environmental changes, and ΔP 环境 represents the impact degree value of environmental condition changes on the route adaptability, and ΔT represents the time interval of environmental changes.

[0031] Preferably, the calculation formula for the maximum route adaptability value K allowed by the current maritime environment in S4 is: K = C 航道 ×C 流量 / C 风险 ;

[0032] Among them, K represents the maximum route adaptability value allowed by the current maritime environment, and C 航道 represents the channel capacity, C 流量 represents the maximum allowable traffic flow of ships in the current channel, and C 风险 represents the environmental risk factor.

[0033] A route rapid generation system for a complex maritime environment, which is used to implement the steps of the route rapid generation method for a complex maritime environment. The system includes:

[0034] A data acquisition module, which is used to collect and integrate real-time marine environment data and ship dynamic information;

[0035] A congestion analysis module connected to the data acquisition module, which is used to perform congestion analysis and prediction based on the traffic flow data provided by the data acquisition module;

[0036] A route planning module connected to the congestion analysis module, which is used to generate an optimized route planning scheme according to the results of congestion analysis and prediction;

[0037] A dynamic adjustment module connected to the data acquisition module and the route planning module, which is used to receive the real-time updated data of the data acquisition module and the initial planning scheme of the route planning module, and dynamically adjust the route planning to cope with the sudden maritime environment.

[0038] It can be seen from the above technical solutions that the present invention has the following beneficial effects:

[0039] The method and system for rapid route generation for complex maritime environments collect and integrate real-time marine environment data and ship dynamic information, conduct congestion analysis and prediction based on water area traffic flow data, generate an optimized route planning scheme according to the analysis results, and dynamically adjust the route plan to cope with unexpected maritime environments, enabling ships to avoid high-density or congested areas in complex waters, thereby improving the overall utilization efficiency of waterway resources, avoiding the problem of overall efficiency decline due to local dredging, being able to quickly respond to complex environmental changes such as tidal changes, sudden meteorological conditions, and traffic surges, effectively avoiding the limitations of static rules or manual experience, being able to significantly reduce the risk of ship collisions, enhancing the navigability and smoothness in high-density areas, effectively reducing the dependence on manual experience and scheduling, reducing the risk of human judgment errors, while improving traffic flow processing efficiency, significantly enhancing the overall shipping efficiency in complex waters, being able to avoid the problem of low processing efficiency caused by data redundancy, quickly identifying abnormal situations, assisting in accurate decision-making, being able to provide a real-time optimized route planning scheme according to the actual situation, and solving the problem of how to analyze and schedule traffic flow in complex waters to solve waterway congestion in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a flowchart of the method of the present invention;

[0041] Figure 2 It is a schematic diagram of the connection of system modules of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] As Figure 1 shown, the present invention provides a technical solution: a method for rapid route generation for complex maritime environments, the method includes:

[0044] S1. Collect and integrate real-time marine environment data and ship dynamic information;

[0045] S2. Conduct congestion analysis and prediction based on the traffic flow data of the water area, including modeling the traffic flow and calculating the traffic pressure of each water area. The specific formula is:

[0046] × ;

[0047] Wherein, V xrepresents the traffic flow load degree value of the water area, V represents the total global traffic load value, R x represents the degree of obstruction to the ship traffic flow within the water area, R 1 , R 2 , ……, R n represents the flow resistance value of each water area, n represents the number of water areas, and x represents the index of different water areas;

[0048] S3. According to the analysis results, generate an optimized route planning scheme, including dividing the route planning water area into multiple sections, setting the navigation speed for each section, calculating the course angle of the path in different water areas based on the starting point and ending point of the target path, and optimizing the route to ensure the minimum total path cost. The specific formula is: ;

[0049] where, θ 1 represents the angle between the initial course and the boundary normal when the route enters from one area to another area, θ 2 represents the angle between the adjusted course and the boundary normal after the route enters the new area, v 1 represents the navigation speed of the ship in the current area, v 2 represents the navigation speed of the ship when entering the new area;

[0050] S4. Dynamically adjust the route planning to cope with the maritime environment of emergencies.

[0051] This method determines the traffic pressure distribution of each water area and the optimal navigation speed of the ship by obtaining marine environment data and ship dynamic information in real time, including reefs, navigation obstacles, restricted areas, wind, current, waves, swells, etc., and combining traffic flow analysis and prediction. Through the resistance modeling formula and optimization algorithm, a route planning with the minimum total path cost is generated. At the same time, according to the course adjustment formula, the connection of cross-region routes is optimized to ensure the smooth transition of the navigation speed and course. The dynamic adjustment mechanism further enhances the adaptability of the method to maritime emergencies. Compared with the existing technologies, this method can significantly improve the speed and accuracy of route planning. By integrating and analyzing real-time data, the traffic pressure distribution in a complex maritime environment is quickly evaluated, and an optimized route plan is provided for the ship. Using the optimization formula reduces the path cost and ensures the efficient and safe passage of the ship. At the same time, the dynamic adjustment mechanism ensures the flexibility and adaptability of the method and can maintain efficient operation even in case of emergencies.

[0052] S1 includes assigning initial weights to each type of data, setting the importance factor of the data, calculating the final weight value of the data using the time update frequency, and generating a unified environmental data input by fusing multi-source data. The specific formula for calculating the final weight value of the data is: Q = m × c × Δt;

[0053] Among them, Q represents the importance weight of the data, m represents the credibility value of the data collection source, c represents the importance factor value of the data, Δt represents the update time interval of the data collection, and t represents time.

[0054] In this embodiment, initial weights are assigned to multi-source data, and by combining the importance factor of the data and the credibility of the collection source, the data is weighted using the update time interval to calculate the final weight Q. This method effectively unifies the input format of multi-source data, making the environmental data more representative and accurate in subsequent analysis, ensuring the reliability and applicability of the basic data for route planning. By comprehensively considering the credibility and importance of the data source, the weights of various types of data are dynamically adjusted, avoiding the interference of low-quality data on the overall accuracy of environmental data. The real-time updated weight calculation method enables this method to adapt to the rapidly changing maritime environment, providing efficient data support for route optimization. This embodiment unifies and integrates multi-source data, effectively reducing the computational complexity brought by the diversity of data sources and improving the overall operating efficiency of the system.

[0055] S4 includes establishing a route adaptability model. According to environmental changes, the response speed and environmental carrying capacity are adjusted, and the route parameters are dynamically updated to generate a new route plan to adapt to environmental changes. The specific formula for dynamically updating the route parameters is: P t+1 =P t +r×P t ×(1-P t / K);

[0056] Among them, P t+1 represents the route adaptability value at the next moment, P t represents the route adaptability value at the current moment, r represents the response speed of the route adaptability to external environmental changes, K represents the maximum route adaptability value allowed by the current maritime environment, and t represents time.

[0057] In this embodiment, by constructing a route adaptability model and combining the self-growth logic in the formula, the adaptability value of the route is dynamically adjusted. When the current environmental change affects the route adaptability, according to the response speed r of the route to the environment and the maximum carrying capacity K of the environment, the route adaptability value P tThrough non - linear adjustment, the model gradually approximates the optimal state of route adaptability, ensuring the efficiency and reliability of route planning in a dynamically changing maritime environment. By dynamically adjusting route parameters, this method can quickly respond to changes in the external environment, generate a more adaptable route plan, reduce navigation risks, rationally utilize the maximum carrying capacity K of the maritime environment, avoid resource waste or potential environmental pressure caused by over - planning, improve the operating efficiency and environmental friendliness of the route. The self - adjusting characteristics of the route adaptability model enhance the robustness of the system, enabling it to maintain efficient operation in an uncertain maritime environment.

[0058] The degree - of - obstruction value R of ship traffic flow in the waters of S2 x The calculation formula is: R x = D / (W × S);

[0059] Among them, R x represents the degree - of - obstruction value of ship traffic flow in the waters, D represents the number of ships per unit area, W represents the navigable channel width in the area, and S represents the average navigation speed of ships.

[0060] In this embodiment, by calculating the degree - of - obstruction value R of traffic flow in the waters x , it provides basic parameter support for route planning. In the formula, the ship density D represents the degree of traffic congestion in the waters, while the channel width W and the average ship speed S reflect the traffic capacity of the waters. By comprehensively considering these factors, the formula can quantify the degree of obstruction in the waters, thus providing a key basis for subsequent traffic flow analysis and route optimization. The formula combines multi - dimensional factors such as water traffic density, channel width, and ship speed, and can accurately reflect the traffic obstruction degree of different waters, laying a data foundation for route optimization. By quickly calculating R x , it can analyze the traffic flow conditions of different waters in real - time, speed up the route planning process, adapt to the dynamically changing maritime environment. The quantitative assessment of the degree of obstruction helps to avoid high - traffic - obstruction areas, reduce navigation risks, and improve the overall safety and efficiency of navigation.

[0061] The calculation formula for the navigation speed in S3 is: ;

[0062] Among them, v represents the navigation speed of the area, F represents the comprehensive driving force of the regional environment, and h represents the unit mass of the ship.

[0063] This embodiment provides precise parameter support for route optimization by calculating the navigation speed v of the ship within a region. The formula is based on the principles of dynamics and takes into account the comprehensive environmental driving force F and the unit mass h of the ship on the navigation speed. The comprehensive driving force F includes environmental factors (such as tidal currents, wind) and factors such as the output power of the ship's propulsion system. Through formula calculation, the optimal navigation speed of the ship within a specific region can be quickly determined, thereby realizing the efficient planning of the route. By introducing two key parameters, the comprehensive environmental driving force and the unit mass of the ship, the optimal navigation speed of the ship in different regions can be scientifically calculated, improving the navigation efficiency. The speed calculation formula fully considers the balance between the ship's mass and the driving force, avoiding energy waste caused by excessive or too slow navigation, contributing to energy conservation and emission reduction. By reasonably planning the navigation speed, it is possible to avoid ship out-of-control or navigation deviation caused by inappropriate speed, improving the overall navigation safety.

[0064] The calculation formula for the credibility value m of the data collection source in S1 is: m = A / B;

[0065] Among them, m represents the credibility value of the data collection source, A represents the accuracy of the collection device, and B represents the failure rate of the device.

[0066] This embodiment calculates the credibility value m of the data collection source through the formula m = A / B. The accuracy A of the device reflects the accuracy of the data collected by the device, and the failure rate B represents the probability that the device may produce errors or interruptions. By combining the two, the credibility value m reflects the comprehensive reliability of the device in the data collection process. The credibility value is used for weight allocation to ensure that data from high-credibility sources is preferentially adopted when fusing multi-source data. By quantifying the collection accuracy and failure rate of the device, the reliability of the data source is comprehensively evaluated, effectively filtering low-credibility data, assigning higher weights to high-credibility data, ensuring that the fused environmental data has higher accuracy and representativeness, providing high-quality data support for subsequent route planning, calculating the credibility value m in real time, dynamically adjusting the data weights, enabling the system to adapt to changes in device status or environment, and improving the stability of data processing.

[0067] The calculation formula for the importance factor value c of the data in S1 is: c = G 1 / G;

[0068] Among them, c represents the importance factor value of the data, G 1 represents the data impact weight, and G represents the total weight.

[0069] This embodiment determines the importance factor value c of the data through the calculation formula c = G 1 / G. Among them, the data impact weight G 1It reflects the influence degree of a certain type of data on route planning. For example, the criticality of weather data for path selection, while the total weight G is the sum of the influence weights of all data. Through this calculation method, the importance of different data is quantified as the factor value c and introduced in the data fusion and weight allocation process to guide the processing and utilization of environmental data. By accurately calculating the importance factor value c of various data, a quantitative analysis of the roles of different data in route planning is achieved, thereby optimizing the utilization efficiency of data, assigning higher weights to key data, ensuring the priority processing of important data in the route planning process, improving the rationality and accuracy of the planning, and by adjusting the influence weight G 1 and the total weight G in real time to adapt to the changing requirements of different maritime environments and ensure the flexibility of data processing.

[0070] In S4, the calculation formula for the response speed r of route adaptability to external environmental changes is: r = ΔP 环境 / ΔT;

[0071] where r represents the response speed of route adaptability to external environmental changes, and ΔP 环境 represents the degree of influence value caused by environmental condition changes on route adaptability, and ΔT represents the time interval of environmental changes.

[0072] In this embodiment, by calculating the response speed r of route adaptability to external environmental changes, the dynamic influence of environmental condition changes on route adaptability is quantified. The degree of influence ΔP of environmental condition changes 环境 includes the requirements for route adjustment due to factors such as tidal current, wind speed, and visibility, while the time interval ΔT reflects the frequency and rate of environmental changes. The formula combines the intensity and time span of environmental changes to calculate the response speed of route adaptability, thereby providing support for dynamically adjusting route parameters. By quantitatively calculating the response speed r of route adaptability to environmental changes, a scientific basis is provided for quickly adjusting route planning, enhancing the real-time and flexibility of the planning, using the numerical changes of the response speed r to quickly judge the urgency of route adaptability adjustment requirements, improving the efficiency and effect of route adjustment, and by quickly responding to environmental changes, avoiding navigation risks caused by lagged adjustment, and improving the adaptability and safety of the route in complex maritime environments.

[0073] In S4, the calculation formula for the maximum route adaptability value K allowed by the current maritime environment is: K = C 航道 ×C 流量 / C 风险 ;

[0074] where K represents the maximum route adaptability value allowed by the current maritime environment, C 航道 represents the channel capacity, C 流量 represents the maximum allowable flow of ships in the current channel, C 风险Represents an environmental risk factor.

[0075] In this embodiment, by calculating the maximum route adaptability value K allowed by the current maritime environment, the environmental carrying capacity of the route planning is quantitatively evaluated. The channel capacity C 航道 Represents the traffic capacity of a specific water area. The maximum flow that the current channel can accommodate is C 流量 Reflects the upper limit of the actual traffic flow. The environmental risk factor C 风险 Then comprehensively evaluate the impact of risks such as bad weather and maritime incidents on the route. Through the calculation formula, combine the channel characteristics and environmental risks to provide a reference for dynamically adjusting the route planning. By introducing the channel capacity, flow rate, and risk factor, comprehensively evaluate the impact of the maritime environment on the route adaptability, provide accurate data support for route optimization, quickly identify high-risk areas by real-time adjusting the calculated value of K, avoid route congestion or navigation accidents caused by over-planning, dynamically calculate K in combination with the current environmental conditions, enable the route planning to flexibly respond to changes in the complex maritime environment, and improve the real-time and flexibility of the planning.

[0076] A route rapid generation system for complex maritime environments is also provided, which is used to implement the steps of the route rapid generation method for complex maritime environments. The system includes:

[0077] A data acquisition module, which is used to collect and integrate real-time marine environment data and ship dynamic information;

[0078] A congestion analysis module connected to the data acquisition module, which is used to perform congestion analysis and prediction based on the traffic flow data provided by the data acquisition module;

[0079] A route planning module connected to the congestion analysis module, which is used to generate an optimized route planning scheme according to the results of congestion analysis and prediction;

[0080] A dynamic adjustment module connected to the data acquisition module and the route planning module, which is used to receive the real-time updated data of the data acquisition module and the initial planning scheme of the route planning module, and dynamically adjust the route planning to cope with the sudden maritime environment.

[0081] This system realizes the rapid generation of routes in complex maritime environments through the collaborative work of each module. The data acquisition module provides high-quality environmental and ship dynamic data in real time. The congestion analysis module uses traffic flow data to model and analyze the obstruction degree of each area. The route planning module generates an initial route plan based on the analysis results. The dynamic adjustment module dynamically optimizes the initial plan by monitoring the real-time changing data to ensure the adaptability and efficiency of the route plan to sudden environments. The system can quickly collect and process real-time data, provide high-quality basic data for route planning, and improve the accuracy of the planning scheme. Combining traffic flow analysis and dynamic adjustment functions, the system can quickly respond to sudden changes in the maritime environment, ensuring the efficiency and safety of the route. The functions of each module are clearly defined, supporting expansion and upgrade. The functions can be adjusted or new modules can be added according to specific requirements to adapt to different application scenarios.

[0082] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for quickly generating routes in complex maritime environments, characterized in that: The method comprises: S1, collect and integrate real-time marine environmental data and ship dynamic information, S1 includes: assigning initial weights to each type of data, setting the importance factor of the data, calculating the final weight of the data using the time update frequency, and fusing multi-source data to generate a unified environmental data input; S2. Congestion analysis and prediction based on water area traffic flow data, including modeling traffic flow and calculating traffic pressure in each water area. The specific formula is: × ； Among them, V x represents the traffic flow load value of the water area, V represents the total global traffic load value, R x Indicates the degree of obstruction to ship traffic flow in the water area, R1, R2, ..., R n represents the flow resistance value of each water area, n represents the number of water areas, and x represents the index of different water areas; S3. Generate an optimized route planning scheme based on the analysis results, including dividing the route planning waters into multiple areas, setting the navigation speed for each area, calculating the heading angle of the path in different waters according to the starting and ending points of the target path, optimizing the route, and ensuring the minimum total path cost. The specific formula is: ; Among them, θ1 represents the angle between the initial heading and the boundary normal when the route enters from one area to another, θ2 represents the angle between the adjusted heading and the boundary normal after entering the new area, v1 represents the navigation speed of the ship in the current area, and v2 represents the navigation speed of the ship when entering the new area; S4. Dynamically adjust route planning to cope with unexpected maritime environments.

2. The method for quickly generating routes in a complex maritime environment according to claim 1, characterized in that: The specific formula for the final weight of the data calculated by S1 is: Q=m×c×Δt; Among them, Q represents the importance weight of the data, m represents the credibility value of the data collection source, c represents the importance factor value of the data, and Δt represents the update time interval of data collection.

3. The method for quickly generating routes in a complex maritime environment according to claim 1, characterized in that: The S4 includes: Establish a route adaptability model, adjust the response speed and environmental carrying capacity according to environmental changes, dynamically update route parameters, generate new route planning to adapt to environmental changes, and dynamically update route parameters. The specific formula is: P t+1 =P t +r×P t × (1-P t / K); Among them, P t+1 Indicates the route adaptability value at the next moment, P t It represents the route adaptability value at the current moment, r represents the reaction speed of route adaptability to changes in the external environment, K represents the maximum route adaptability value allowed by the current maritime environment, and t represents the time.

4. The method for quickly generating routes in a complex maritime environment according to claim 1, characterized in that: The obstruction value R of the ship traffic flow in the water area S2 x The calculation formula is: R x =D / (W×S); Among them, R x It represents the degree of obstruction to the flow of ship traffic in the water area, D represents the number of ships per unit area, W represents the width of the channel available for navigation in the area, and S represents the average sailing speed of ships.

5. The method for quickly generating routes in a complex maritime environment according to claim 1, characterized in that: The calculation formula of the navigation speed in S3 is: ; Among them, v represents the navigation speed of the area, F represents the comprehensive driving force of the regional environment, and h represents the unit mass of the ship.

6. The method for quickly generating routes in a complex maritime environment according to claim 2, characterized in that: The calculation formula of the credibility value m of the data collection source in S1 is: m = A / B; Among them, m represents the credibility value of the data collection source, A represents the accuracy of the collection equipment, and B represents the failure rate of the equipment.

7. The method for quickly generating routes in a complex maritime environment according to claim 2, characterized in that: The calculation formula of the importance factor value c of the data in S1 is: c=G1 / G; Among them, c represents the importance factor value of the data, G1 represents the data impact weight, and G represents the total weight.

8. The method for quickly generating routes in a complex maritime environment according to claim 3, characterized in that: The calculation formula of the reaction speed r of the route adaptability to the external environment change in S4 is: r = ΔP 环境 / ΔT; Among them, r represents the response speed of route adaptability to changes in the external environment, ΔP 环境 It indicates the impact of environmental changes on route adaptability, and ΔT indicates the time interval of environmental changes.

9. The method for quickly generating routes in a complex maritime environment according to claim 3, characterized in that: The calculation formula of the maximum route adaptability value K allowed by the current maritime environment in S4 is: K = C 航道 ×C 流量 / C 风险 ; Among them, K represents the maximum route adaptability value allowed by the current maritime environment, C 航道 represents the waterway capacity, C 流量 Indicates the maximum flow rate that can be accommodated by ships in the current channel, C 风险 Represents environmental risk factors.

10. A system for quickly generating routes in a complex maritime environment, used to implement the steps of the method for quickly generating routes in a complex maritime environment as described in any one of claims 1 to 9, characterized in that: The system comprises: Data acquisition module, used to collect and integrate real-time marine environment data and ship dynamic information; A congestion analysis module connected to the data acquisition module, for performing congestion analysis and prediction based on the traffic flow data provided by the data acquisition module; A route planning module connected to the congestion analysis module is used to generate an optimized route planning solution based on the results of congestion analysis and prediction; The dynamic adjustment module connected to the data acquisition module and the route planning module is used to receive the real-time update data of the data acquisition module and the initial planning scheme of the route planning module, and dynamically adjust the route planning to cope with the maritime environment of emergencies.

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