Intelligent route recommendation method and system based on S-100 standard

Abstract

The invention relates to the technical field of marine surveying and mapping, and particularly discloses an intelligent route recommendation method and system based on an S-100 standard, and the method comprises the steps: collecting real-time information data, historical route data, environmental protection data and cargo data; processing to obtain a route safety evaluation index, and processing the environmental protection data to obtain a route environmental protection evaluation index; according to the cargo data and the real-time information data, carrying out comprehensive analysis to obtain an airline timeliness evaluation index; and performing comprehensive analysis to obtain an intelligent route recommendation coefficient, and recommending an optimal intelligent route by using the intelligent route recommendation coefficient. By evaluating the intelligent route recommendation coefficient, it can be ensured that the recommended route meets the safety standard, the accident occurrence possibility is reduced, route transportation can arrive on time, delay is reduced, the influence on the environment is reduced, carbon emission is reduced, safer, more efficient and more environment-friendly route selection is provided for a user, and the user experience is improved. And meanwhile, the goal of sustainable development is supported.

Description

Technical Field

[0001] The present invention relates to the field of marine surveying and mapping technology, and in particular to an intelligent route recommendation method and system based on the S-100 standard. Background Art

[0002] At present, intelligent route recommendation is a very important part of the field of marine surveying and mapping. With the advancement of technology and the accumulation of data, recommending a more economical and environmentally friendly route has become the norm. Efficient and safe intelligent routes are of great significance for reducing transportation costs and improving logistics efficiency.

[0003] For example, the invention patent with announcement number CN111536962B is a route planning method and device, storage medium, and computer equipment for intelligent ships, including: if the target ship determines that it is within the preset range of the narrow waterway according to the current electronic chart information, it plans the first route set for the target ship to pass through the narrow waterway, and calculates the risk value of each route in the set, so that the target ship executes the navigation path with the minimum risk value; the target ship obtains its own ship information and surrounding obstacles information in real time to calculate the collision risk between its own ship and the surrounding obstacles. If the collision risk exceeds the preset safety threshold, it plans the second route set for the target ship to pass through the narrow waterway, and calculates the risk value of each route in the set, so that the target ship executes the navigation path with the minimum risk value. It can provide a safe and feasible path for intelligent ships passing through narrow waterways.

[0004] For example, the invention patent with the announcement number CN117346796B is an intelligent route planning method, device and electronic equipment based on the route network, including: obtaining ship trajectory data, generating a route network according to the ship trajectory data; selecting the route starting point and the route end point, and performing route planning based on the route network, the route starting point and the route end point to obtain the initial optimal route based on the improved genetic algorithm; determining the segment to be optimized based on the initial optimal route, and performing local optimization on the segment to be optimized based on the multi-strategy improved RRT* algorithm to obtain the optimized route.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it was found that the above technology has at least the following technical problems: the current intelligent route recommendation method pays more attention to historical track data and initial real-time information, but the marine environment is unpredictable, and in some special cases, the recommendation method may still be inaccurate, and the safety of the route cannot be fully guaranteed. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides an intelligent route recommendation method and system based on the S-100 standard, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides an intelligent route recommendation method based on the S-100 standard, including: collecting real-time information data, historical track data, environmental protection data, and cargo data.

[0008] The initial route is constructed based on the historical track data and the key nodes are obtained. The entire route is then divided into several segments based on the key nodes. The real-time information data of each segment is processed to obtain the route safety assessment index, and the environmental data is processed to obtain the route environmental assessment index.

[0009] Based on cargo data and real-time information data, where cargo data includes the number of cargo batches and the actual delivery time of each batch of cargo, and real-time information data includes the average wave height of each segment, combined with the route safety assessment index, a comprehensive analysis is conducted to obtain the route timeliness assessment index.

[0010] The smart route recommendation coefficient is obtained based on a comprehensive analysis of the route safety assessment index, route timeliness assessment index and route environmental assessment index, and the best smart route is recommended using the smart route recommendation coefficient.

[0011] As a further method, the real-time information data of each section is processed to obtain a route safety assessment index, and the specific processing process is: the real-time information data specifically includes the number of ships in the section, the number of obstacles in the section, the average wind speed and the average wave height.

[0012] The critical number of ships, critical number of obstacles and critical average wind speed are extracted from the S-100 standard database, and the route safety assessment index is obtained through comprehensive analysis.

[0013] As a further method, the environmental protection data is processed to obtain an environmental protection evaluation index of the route. The specific analysis process is as follows: the environmental protection data includes greenhouse gas emissions throughout the route and the number of times the protected area is crossed.

[0014] The critical greenhouse gas emissions and the number of critical protection zone crossings were extracted from the S-100 standard database, and a comprehensive analysis was performed to obtain the route environmental performance evaluation index.

[0015] As a further method, the route timeliness evaluation index is a quantitative indicator obtained by analyzing the actual delivery time required for each batch of goods, the average wave height of each section and the route safety evaluation index, which is used to quantify the timeliness performance of the route.

[0016] As a further method, the comprehensive analysis obtains the intelligent route recommendation coefficient, and the specific analysis process is: according to the route safety evaluation index, the route timeliness evaluation index and the route environmental protection evaluation index, the intelligent route recommendation coefficient is obtained through comprehensive analysis.

[0017] As a further method, the route safety assessment index is a quantitative indicator obtained by analyzing the number of ships, the number of obstacles and the average wind speed in each section, and is used to quantify the safety performance of the route.

[0018] As a further method, the best smart route is recommended using the smart route recommendation coefficient. The specific recommendation process is: extracting the smart route recommendation coefficient threshold in the S-100 standard database, comparing the smart route recommendation coefficient of each route with the smart route recommendation coefficient threshold, if the smart route recommendation coefficient of a route is greater than or equal to the smart route recommendation coefficient threshold, then the route is evaluated as a qualified route, if the smart route recommendation coefficient of the route is less than the smart route recommendation coefficient threshold, then the route is evaluated as an unqualified route.

[0019] The smart route recommendation coefficients of qualified routes are arranged in order from large to small, and the route with the largest smart route recommendation coefficient is marked as the best smart route.

[0020] As a further method, the route safety evaluation index has a specific numerical expression as follows:

[0021]

[0022] Among them, A represents the route safety assessment index, e represents the natural constant, S i represents the number of ships on the route of the ith segment, S0 represents the maximum number of ships allowed in the segment, and L i represents the number of obstacles on the route of the ith flight segment, L0 represents the maximum number of obstacles allowed in the flight segment, and F i represents the average wind speed of the i-th segment, F0 represents the maximum allowable average wind speed of the segment, ω1 represents the route safety assessment impact factor corresponding to the set number of ships in the segment, ω2 represents the route safety assessment impact factor corresponding to the set number of obstacles in the segment, ω3 represents the route safety assessment impact factor corresponding to the set average wind speed in the segment, i represents the number of segments, i=1,2,3,...,m, and m represents the total number of segments.

[0023] As a further method, the specific numerical expression of the route timeliness evaluation index is:

[0024]

[0025] Among them, B represents the route timeliness evaluation index, e represents the natural constant, T j represents the actual delivery time of the jth batch of goods, T j0 It represents the time required for the delivery of the set critical goods, P irepresents the average wave height of the ith segment, P0 represents the average wave height of the set critical segment, A represents the route safety assessment index, A0 represents the set critical route safety assessment index, Indicates the impact factor of the route timeliness assessment corresponding to the set time deviation required for cargo delivery, It represents the impact factor of the route timeliness assessment corresponding to the set average wave height, It represents the route timeliness assessment influencing factor corresponding to the set route safety assessment index, i represents the number of flight segments, i=1,2,3,...,m, m represents the total number of flight segments, j represents the number of cargo batches, j=1,2,3,...,n, n represents the total number of cargo batches.

[0026] The second aspect of the present invention provides an intelligent route recommendation system based on the S-100 standard, including: an intelligent route data acquisition module for collecting real-time information data, historical track data, environmental protection data, and cargo data, including the number of ships in the segment, the number of obstacles in the segment, the average wind speed, the average wave height, and the greenhouse gas emissions of the entire route, the number of times the protected area is crossed, the number of batches of cargo, and the actual delivery time required for each batch of cargo.

[0027] The intelligent route safety and environmental protection assessment module is used to construct the initial route and obtain key nodes based on historical track data, and then divide the entire route into several small routes based on the key nodes, process the real-time information data of each small route to obtain the route safety assessment index, and process the environmental protection data to obtain the route environmental protection assessment index.

[0028] The intelligent route timeliness evaluation module is used to obtain the route timeliness evaluation index through comprehensive analysis based on cargo data and real-time information data.

[0029] The smart route recommendation module is used to evaluate each smart route according to the smart route recommendation coefficient. If the evaluation result is qualified, the recommendation coefficients of each qualified smart route are then compared. The route with the highest recommendation coefficient is recommended as the best smart route. If the evaluation result is unqualified, the smart route is discarded.

[0030] The S-100 standard database is used to store data related to smart routes, including route safety assessment influencing factors corresponding to the number of ships in the section, route safety assessment influencing factors corresponding to the number of obstacles in the section, route safety assessment influencing factors corresponding to the average wind speed, critical cargo delivery time, critical average wave height, critical route safety assessment index, route environmental assessment influencing factors corresponding to the greenhouse gas emissions of the entire route, route environmental assessment influencing factors corresponding to the number of protected area crossings, and smart route recommendation coefficient thresholds.

[0031] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0032] (1) By evaluating the intelligent route recommendation coefficient, the present invention can ensure that the recommended route meets safety standards, reduce the possibility of accidents, help route transportation arrive on time, reduce delays, reduce environmental impact, reduce carbon emissions, and provide users with safer, more efficient, and more environmentally friendly route options, while supporting the goal of sustainable development.

[0033] (2) By evaluating the route safety index, the present invention can plan safer routes for ships, avoid dangerous areas, and reduce the occurrence of incidents such as collisions or groundings. At the same time, it can identify congested and windy sections, so as to take measures to reduce sailing time and improve overall transportation efficiency. Long-term safety assessment data can also be used for scientific research to help understand the risk change trend on the route.

[0034] (3) By evaluating the timeliness of routes, the present invention can understand the transportation needs and characteristics of different routes and different goods, so as to reasonably allocate port resources and ensure the effective use of port resources. At the same time, it helps to optimize port operation processes, improve port operation efficiency, reduce ship waiting time and thus reduce overall operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0036] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0037] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0038] Figure 3 Schematic diagram of the functional relationship between the route safety assessment index and the intelligent route recommendation coefficient involved in an embodiment of the present invention. Figure 4 Flow chart of route data signal transmission of the present invention. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0040] Reference Figure 1 As shown, the first aspect of the present invention provides an intelligent route recommendation method based on the S-100 standard, including: collecting real-time information data, historical track data, environmental protection data, and cargo data.

[0041] The initial route is constructed based on the historical track data and the key nodes are obtained. The entire route is then divided into several segments based on the key nodes. The real-time information data of each segment is processed to obtain the route safety assessment index, and the environmental data is processed to obtain the route environmental assessment index.

[0042] Based on cargo data and real-time information data, where cargo data includes the number of cargo batches and the actual delivery time of each batch of cargo, and real-time information data includes the average wave height of each segment, combined with the route safety assessment index, a comprehensive analysis is conducted to obtain the route timeliness assessment index.

[0043] The smart route recommendation coefficient is obtained based on a comprehensive analysis of the route safety assessment index, route timeliness assessment index and route environmental assessment index, and the best smart route is recommended using the smart route recommendation coefficient.

[0044] Specifically, an initial route is constructed based on historical track data and key nodes are obtained, and then the entire route is divided into several segments based on the key nodes. The specific process is: the historical track data is the GPS track record of past ships, usually provided by the automatic identification system, and the key nodes are important locations such as ports, strait entrances, channel intersections, turning points, etc. The extracted key nodes are connected in sequence to form a complete route, and the starting point and end point of each segment are adjacent key nodes respectively.

[0045] Specifically, the real-time information data of each section is processed to obtain the route safety assessment index, and the specific processing process is: the real-time information data specifically includes the number of ships in the section, the number of obstacles in the section, the average wind speed and the average wave height.

[0046] The route safety assessment influencing factors corresponding to the number of ships in the preset section, the route safety assessment influencing factors corresponding to the number of obstacles in the section, and the route safety assessment influencing factors corresponding to the average wind speed are extracted from the S-100 standard database.

[0047] Based on the number of ships, number of obstacles and average wind speed in each section, a comprehensive analysis is conducted to obtain the route safety assessment index.

[0048] It should be understood that the section obstacles include fixed obstacles in each section such as shoals, sunken ships, rocks, lighthouses, etc., as well as mobile obstacles such as buoys and drifting objects.

[0049] In a specific embodiment, the number of ships in each section is tracked and counted using the automatic identification system of ships, the number of obstacles in each section is obtained using the latest electronic chart data and real-time monitoring system, and the average wind speed of each section is obtained using the data of the marine meteorological station. By monitoring the number of ships in each section, high-density areas can be identified in a timely manner, which helps ships avoid busy waterways and choose smoother alternative routes, thereby reducing the risk of collision between ships; by monitoring the number of obstacles in each section, obstacles can be marked and removed in a timely manner, reducing the risk of collision between ships and obstacles, and the design of the waterway can be adjusted according to the location and type of obstacles to improve navigation efficiency; by monitoring the average wind speed of each section, it helps the captain and crew to plan the best route according to the current and expected wind conditions, thereby avoiding strong wind areas and reducing navigation risks, and can also predict the strong wind weather that may be encountered in advance and take corresponding preventive measures.

[0050] Specifically, the route safety assessment index has a specific numerical expression as follows:

[0051]

[0052] Among them, A represents the route safety assessment index, e represents the natural constant, S i represents the number of ships on the route of the ith segment, S0 represents the maximum number of ships allowed in the segment, and L i represents the number of obstacles on the route of the ith flight segment, L0 represents the maximum number of obstacles allowed in the flight segment, and F i represents the average wind speed of the i-th segment, F0 represents the maximum allowable average wind speed of the segment, ω1 represents the route safety assessment impact factor corresponding to the set number of ships in the segment, ω2 represents the route safety assessment impact factor corresponding to the set number of obstacles in the segment, ω3 represents the route safety assessment impact factor corresponding to the set average wind speed in the segment, i represents the number of segments, i=1,2,3,...,m, and m represents the total number of segments.

[0053] The algorithm of this embodiment combines the number of ships, the number of obstacles and the average wind speed in each section, and comprehensively analyzes to obtain the route safety assessment index. The more ships there are in each section in this formula, the more likely it is that the channel will be congested, making it difficult for ships to avoid obstacles, increasing the risk of navigation; and under high wind speed conditions, ships may need to choose safer routes, resulting in an increase in the number of ships in certain sections. At the same time, the work of removing obstacles may be affected, causing obstacles to remain on the channel for a longer time; the formation of certain obstacles (such as driftwood, icebergs, etc.) is related to wind speed, and strong winds may cause more obstacles to appear on the channel. Comprehensive analysis can obtain a more comprehensive route safety assessment index.

[0054] Table 1 Example of route safety assessment index data

[0055]

[0056]

[0057] As shown in Table 1, the route safety assessment index is jointly determined by the number of ships in the segment, the number of obstacles in the segment and the average wind speed. In a specific embodiment, m=1, the maximum number of ships in the segment is allowed to be 20, the maximum number of obstacles in the segment is allowed to be 5, the maximum average wind speed is allowed to be 14 knots, the route safety assessment impact factor corresponding to the set number of ships in the segment is 0.3, the route safety assessment impact factor corresponding to the set number of obstacles in the segment is 0.4, and the route safety assessment impact factor corresponding to the set average wind speed is 0.3. This formula takes into account the number of ships, the number of obstacles and the average wind speed in each segment, and can identify high-risk areas and take corresponding measures to reduce the probability of collision, such as taking speed limit or diversion measures. Considering the average wind speed, a route with a smaller tailwind or headwind can be selected to reduce the sailing time and save fuel. In the segment with higher wind speed, it may be necessary to select an alternative route to avoid adverse wind effects. By standardizing the number of ships, obstacles and average wind speed in different sections, ensuring that they are compared at the same level, the fairness and comparability of the evaluation are improved. At the same time, it is possible to understand which sections are safer, so as to reasonably arrange resource allocation. By weighting the impact of the number of ships in the section, the number of obstacles in the section and the average wind speed, it reflects their relative importance in the evaluation index. The weights of different factors can be adjusted according to different needs, making the model very adaptable. It can be seen that the smaller the number of ships in the section, the number of obstacles in the section or the average wind speed, the larger the route safety evaluation index. By evaluating the route safety index, safer routes can be planned for ships, avoiding dangerous areas, reducing the occurrence of collisions or reefing, and at the same time, congested and windy sections can be identified, so as to take measures to reduce sailing time and improve overall transportation efficiency. Long-term safety evaluation data can also be used for scientific research to help understand the risk trend on the route.

[0058] In a specific embodiment, the route safety assessment influencing factors corresponding to the number of ships, the number of obstacles and the average wind speed in each section have a value range between 0 and 1. Each route safety assessment influencing factor can be obtained from the S-100 standard database. By adjusting the value of the influencing factor, the degree of influence of different factors on the final route safety assessment index can be flexibly adjusted.

[0059] It should be understood that in this embodiment, a mapping set of the number of ships in a segment, the number of obstacles in a segment, the average wind speed and the corresponding route safety assessment influencing factors is constructed through the relationship between the number of ships in a segment, the number of obstacles in a segment and the average wind speed in the historical data and the route safety assessment index. The real-time number of ships in a segment, the number of obstacles in a segment and the average wind speed are input, and the corresponding route safety assessment influencing factors are obtained from the mapping set.

[0060] In a specific embodiment, the route safety assessment index is a quantitative indicator obtained by analyzing the number of ships, the number of obstacles and the average wind speed in each section, and is used to quantify the safety performance of the route.

[0061] Furthermore, the environmental data is processed to obtain an environmental assessment index of the route, and the specific analysis process is as follows: the environmental data includes greenhouse gas emissions throughout the route and the number of times the protected area is crossed.

[0062] The route environmental assessment influencing factors corresponding to the preset greenhouse gas emissions of the entire route and the route environmental assessment influencing factors corresponding to the number of route obstacles are extracted from the S-100 standard database.

[0063] Based on the greenhouse gas emissions of the entire route and the number of times the protected area is crossed, a comprehensive analysis is conducted to obtain the route environmental assessment index.

[0064] In a specific embodiment, sensors and monitoring equipment are installed to directly measure greenhouse gas emissions from ship engines, and the number of times a route crosses protected areas is monitored using a ship automatic identification system. By monitoring greenhouse gas emissions throughout the route, it can help identify emission hotspots and emission reduction opportunities, and then reduce greenhouse gas emissions by adjusting operating procedures or adopting more efficient fuels and technologies. By monitoring the number of times a route crosses protected areas, it can help ensure that route planning avoids important ecological areas and reduces the impact on local ecosystems, thereby maintaining biodiversity and ecosystem health.

[0065] Specifically, the route environmental performance evaluation index has the following numerical expression:

[0066]

[0067] Among them, C represents the environmental assessment index of the route, U represents the greenhouse gas emissions of the entire route, U0 represents the greenhouse gas emissions of the entire critical route, V represents the number of times the route crosses the protected area, V0 represents the number of times the critical route crosses the protected area, θ1 represents the route environmental assessment influencing factor corresponding to the greenhouse gas emissions of the entire route, and θ2 represents the route environmental assessment influencing factor corresponding to the number of times the route crosses the protected area.

[0068] The algorithm of this embodiment combines the greenhouse gas emissions of the entire route and the number of times the protected area is crossed, and a comprehensive analysis is performed to obtain the route environmental assessment index. Avoiding crossing the protected area as much as possible can reduce the impact on the environment, but it may also bring about changes in the length of the route. A longer route may lead to higher greenhouse gas emissions because the ship needs to consume more fuel to complete the journey. There is a certain trade-off relationship between the greenhouse gas emissions of the entire route and the number of times the protected area is crossed. A comprehensive analysis can minimize the impact on the environment and obtain a more comprehensive route environmental assessment index.

[0069] It should be explained that two key factors, namely, greenhouse gas emissions throughout the route and the number of protected area crossings, are considered in this embodiment, which can reduce interference with ecosystems and wildlife, help mitigate global warming and climate change, and transparent reporting of greenhouse gas emissions and the number of protected area crossings can enhance public trust, bring social benefits, and contribute to the realization of sustainable development goals. By standardizing the greenhouse gas emissions throughout the route and the number of protected area crossings, ensuring that they are compared at the same level, the fairness and comparability of the evaluation are improved. At the same time, the setting of U0 and V0 can provide a reference standard for shipping companies and regulators so that they can understand when an acceptable environmental protection level is reached or exceeded. By weighting the impact of greenhouse gas emissions throughout the route and the number of protected area crossings, it reflects their relative importance in the evaluation index. The weights of different factors can be adjusted according to different needs, making the model very adaptable. It is not difficult to see that the smaller the greenhouse gas emissions throughout the route or the number of protected area crossings, the greater the environmental protection evaluation index of the route.

[0070] In a specific embodiment, the value range of the route environmental assessment influencing factor corresponding to the greenhouse gas emissions of the entire route and the number of times the protected area is crossed is between 0 and 1. The environmental assessment influencing factor of each route can be obtained from the S-100 standard database. By adjusting the value of the influencing factor, the influence of different factors on the final route environmental assessment index can be flexibly adjusted.

[0071] It should be understood that in this embodiment, a mapping set of route environmental assessment influencing factors corresponding to the route’s total greenhouse gas emissions and the number of protected area crossings is constructed through the relationship between the route’s total greenhouse gas emissions and the number of protected area crossings in historical data and the route’s environmental assessment index. The real-time route’s total greenhouse gas emissions and the number of protected area crossings are input, and the corresponding route environmental assessment influencing factors are obtained from the mapping set.

[0072] In a specific embodiment, the route environmental performance evaluation index is a quantitative indicator obtained by analyzing the greenhouse gas emissions of the entire route and the number of times the protected area is crossed, and is used to quantify the environmental performance of the route.

[0073] Specifically, based on the cargo data and real-time information data, a comprehensive analysis is performed to obtain a route timeliness evaluation index. The specific analysis process is as follows: the cargo data includes the number of cargo batches and the actual delivery time required for each batch of cargo.

[0074] The environmental impact factors of the route corresponding to the preset actual delivery time of the goods and the environmental impact factors of the route corresponding to the number of obstacles on the route are extracted from the S-100 standard database.

[0075] Based on the actual delivery time of each batch of goods, the average wave height of each section and the route safety assessment index, a comprehensive analysis is conducted to obtain the route timeliness assessment index.

[0076] It should be explained that in this embodiment, professional supply chain management software is used to monitor the actual delivery time of each batch of goods, and the wave measurement system installed on the ship is used to monitor the wave conditions encountered by the ship in real time. By monitoring the actual delivery time of each batch of goods, the visibility of the entire supply chain can be improved, so that all parties can understand the status and location of the goods in a timely manner, while reducing delays, thereby reducing additional costs. By monitoring the average wave height of each section, safer and more efficient routes can be planned, helping to take preventive measures and reduce casualties and property losses. By monitoring the route safety assessment index, safety hazards in the route can be discovered in a timely manner, corrective measures can be taken, and accidents can be avoided.

[0077] Specifically, the route timeliness evaluation index has a specific numerical expression as follows:

[0078]

[0079] Among them, B represents the route timeliness evaluation index, e represents the natural constant, T j represents the actual delivery time of the jth batch of goods, T j0 It represents the time required for the delivery of the set critical goods, P i represents the average wave height of the ith segment, P0 represents the average wave height of the set critical segment, A represents the route safety assessment index, A0 represents the set critical route safety assessment index, Indicates the impact factor of the route timeliness assessment corresponding to the set time deviation required for cargo delivery, It represents the impact factor of the route timeliness assessment corresponding to the set average wave height, It represents the route timeliness assessment influencing factor corresponding to the set route safety assessment index, i represents the number of flight segments, i=1,2,3,...,m, m represents the total number of flight segments, j represents the number of cargo batches, j=1,2,3,...,n, n represents the total number of cargo batches.

[0080] The algorithm of this embodiment combines the time required for actual delivery of goods, the average wave height and the route safety assessment index, and comprehensively analyzes to obtain the route timeliness assessment index. Higher waves may cause the ship to slow down and extend the sailing time, thereby affecting the actual delivery time of the goods. Higher waves may increase the navigation risk and further affect the safety of the route. Safe routes can often provide more stable and predictable sailing times, reduce the occurrence of accidents, and thus ensure that the goods are delivered on time. Comprehensive analysis can maximize the efficiency and safety of the route and obtain a more comprehensive route timeliness assessment index.

[0081] It should be explained that three key factors are considered in this embodiment, namely, the time required for the actual delivery of goods, the average wave height and the route safety assessment index, which can predict and reduce delays caused by bad weather, thereby increasing the probability of on-time delivery of goods, and more effectively planning routes, avoiding high-risk areas, and reducing additional costs caused by unexpected events, thereby enhancing customer satisfaction and promoting the healthy development of the entire industry. By standardizing the time required for the actual delivery of goods, the average wave height and the route safety assessment index, ensuring that they are compared at the same magnitude, the fairness and comparability of the assessment are improved, and which factors have the greatest impact on the timeliness of the route can be identified, so as to improve them in a targeted manner. It is not difficult to see that the smaller the time required for the actual delivery of goods, the smaller the average wave height, or the larger the route safety assessment index, the larger the route timeliness assessment index. By evaluating the timeliness of the route, the transportation needs and characteristics of different routes and different goods can be understood, so as to reasonably allocate port resources, such as berths, yards, equipment, etc., to ensure the effective use of port resources, and to optimize the port operation process, improve port operation efficiency, reduce ship waiting time, and thus reduce overall operating costs.

[0082] In a specific embodiment, the value range of the route timeliness assessment influencing factor corresponding to the actual delivery time of the goods, the average wave height and the route safety assessment index is between 0 and 1. Each route timeliness assessment influencing factor can be obtained from the S-100 standard database. By adjusting the value of the influencing factor, the influence of different factors on the final route timeliness assessment index can be flexibly adjusted.

[0083] It should be understood that in this embodiment, a mapping set of route ring timeliness assessment influencing factors corresponding to the actual delivery time of goods, the average wave height and the route safety assessment index is constructed through the relationship between the actual delivery time of goods, the average wave height and the route safety assessment index in the historical data, and the route timeliness assessment index. The real-time actual delivery time of goods, the average wave height and the route safety assessment index are input, and the corresponding route timeliness assessment influencing factors are obtained from the mapping set.

[0084] In a specific embodiment, the route timeliness evaluation index is a quantitative indicator obtained by analyzing the actual delivery time of goods, the average wave height and the route safety evaluation index, and is used to quantify the timeliness performance of the route.

[0085] Specifically, a comprehensive analysis is performed to obtain the intelligent route recommendation coefficient, and the specific analysis process is as follows: extracting the intelligent route recommendation coefficient influencing factors corresponding to the preset route safety assessment index, route timeliness assessment index and route environmental assessment index from the S-100 standard database.

[0086] Based on the route safety assessment index, route timeliness assessment index and route environmental protection assessment index, a comprehensive analysis is conducted to obtain the smart route recommendation coefficient.

[0087] Specifically, the smart route recommendation coefficient is expressed as:

[0088] D=tanh(ρ1*A+ρ2*B+ρ3*C);

[0089] Among them, D represents the smart route recommendation coefficient, A represents the route safety assessment index, B represents the route timeliness assessment index, C represents the route environmental protection assessment index, ρ1 represents the smart route recommendation influencing factor corresponding to the set route safety assessment index, ρ2 represents the smart route recommendation influencing factor corresponding to the set route timeliness assessment index, and ρ3 represents the smart route recommendation influencing factor corresponding to the set route environmental protection assessment index.

[0090] In a specific embodiment, the algorithm of this embodiment combines the route safety evaluation index, the route timeliness evaluation index and the route environmental protection evaluation index, and comprehensively analyzes to obtain the intelligent route recommendation coefficient. Generally, safe routes can usually provide more stable and predictable sailing times, reduce the occurrence of accidents, and thus help improve timeliness. At the same time, it can reduce the possibility of accidents, thereby reducing potential environmental pollution, and reducing delays helps to reduce additional fuel consumption and carbon emissions. Comprehensive analysis can improve the overall performance of the route and obtain a more accurate intelligent route recommendation coefficient.

[0091] like Figure 3 As shown, in a specific embodiment, ρ1 = 0.5, ρ2 = 0.3, ρ3 = 0.2. When B = C = 0.1, the functional relationship between the intelligent route recommendation coefficient and the route safety evaluation index is shown as curve a; when B = C = 0.5, the functional relationship between the intelligent route recommendation coefficient and the route safety evaluation index is shown as curve b; when B = C = 1, the functional relationship between the intelligent route recommendation coefficient and the route safety evaluation index is shown as curve c.

[0092] It should be explained that in this embodiment, three key factors, namely, the route safety assessment index, the route timeliness assessment index, and the route environmental protection assessment index, are comprehensively considered to achieve safer, more efficient, and more environmentally friendly route operations, which are crucial to improving the competitiveness of enterprises, meeting customer needs, and supporting sustainable development goals. By weighting the impact of the route safety assessment index, the route timeliness assessment index, and the route environmental protection assessment index, it reflects their relative importance in the assessment index. The weights of different factors can be adjusted according to different needs, making the model very adaptable. It is not difficult to see that the larger the route safety assessment index, the route timeliness assessment index, or the route environmental protection assessment index, the larger the smart route recommendation coefficient. By evaluating the smart route recommendation coefficient, it can be ensured that the recommended route meets safety standards, reduces the possibility of accidents, is most likely to arrive on time, reduces delays, has less impact on the environment, and reduces carbon emissions. In short, it can provide users with safer, more efficient, and more environmentally friendly route options while supporting the goal of sustainable development.

[0093] In a specific embodiment, the value range of the smart route recommendation coefficient influencing factor corresponding to the route safety evaluation index, route timeliness evaluation index and route environmental evaluation index at the historical time node is between 0 and 1. Each smart route recommendation coefficient influencing factor can be obtained from the S-100 standard database. By adjusting the value of the influencing factor, the influence of different factors on the final smart route recommendation coefficient can be flexibly adjusted.

[0094] like Figure 4 As shown, it is a flow chart of route data signal transmission of the present invention, wherein the route data includes the number of ships in the route segment, the number of obstacles in the route segment, the average wind speed, the average wave height and the greenhouse gas emissions of the entire route, the number of times the protected area is crossed and the number of batches of goods, the actual delivery time required for each batch of goods, and they are pre-processed and the transmission and receiving operations are analyzed to obtain the route safety evaluation index, route timeliness evaluation index and route environmental protection evaluation index as well as the intelligent route recommendation coefficient.

[0095] It should be understood that in this embodiment, a mapping set of route safety assessment index, route timeliness assessment index and route environmental protection assessment index and corresponding intelligent route recommendation coefficient influencing factors is constructed through the relationship between the route safety assessment index, route timeliness assessment index and route environmental protection assessment index in historical data and the intelligent route recommendation coefficient, and the real-time route safety assessment index, route timeliness assessment index and route environmental protection assessment index are input to obtain the corresponding intelligent route recommendation coefficient influencing factors from the mapping set.

[0096] Specifically, the smart route recommendation coefficient is a quantitative indicator obtained by analyzing the route safety assessment index, route timeliness assessment index and route environmental assessment index, and is used to quantify the degree of recommendation of the smart route.

[0097] Specifically, the best smart route is recommended using the smart route recommendation coefficient. The specific recommendation process is: extract the smart route recommendation coefficient threshold in the S-100 standard database, compare the smart route recommendation coefficient of each route with the smart route recommendation coefficient threshold, if the smart route recommendation coefficient of a route is greater than or equal to the smart route recommendation coefficient threshold, then the route is evaluated as a qualified route, if the smart route recommendation coefficient of the route is less than the smart route recommendation coefficient threshold, then the route is evaluated as an unqualified route.

[0098] The smart route recommendation coefficients of qualified routes are arranged in order from large to small, and the route with the largest smart route recommendation coefficient is marked as the best smart route.

[0099] Reference Figure 2 As shown, the second aspect of the present invention provides an intelligent route recommendation system based on the S-100 standard, including: an intelligent route data acquisition module, used to collect real-time information data, historical track data, environmental protection data, and cargo data, including the number of ships in the segment, the number of obstacles in the segment, the average wind speed, the average wave height and the greenhouse gas emissions of the entire route, the number of times the protected area is crossed and the number of batches of cargo, and the actual delivery time required for each batch of cargo.

[0100] The intelligent route safety and environmental protection assessment module is used to construct the initial route and obtain key nodes based on historical track data, and then divide the entire route into several small routes based on the key nodes, process the real-time information data of each small route to obtain the route safety assessment index, and process the environmental protection data to obtain the route environmental protection assessment index.

[0101] The intelligent route timeliness evaluation module is used to obtain the route timeliness evaluation index through comprehensive analysis based on cargo data and real-time information data.

[0102] The smart route recommendation module is used to evaluate each smart route according to the smart route recommendation coefficient. If the evaluation result is qualified, the recommendation coefficients of each qualified smart route are then compared. The route with the highest recommendation coefficient is recommended as the best smart route. If the evaluation result is unqualified, the smart route is discarded.

[0103] The S-100 standard database is used to store data related to smart routes, including route safety assessment influencing factors corresponding to the number of ships in the section, route safety assessment influencing factors corresponding to the number of obstacles in the section, route safety assessment influencing factors corresponding to the average wind speed, critical cargo delivery time, critical average wave height, critical route safety assessment index, route environmental assessment influencing factors corresponding to the greenhouse gas emissions of the entire route, route environmental assessment influencing factors corresponding to the number of protected area crossings, and smart route recommendation coefficient thresholds.

[0104] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent route recommendation method based on the S-100 standard, characterized in that: include: Collect real-time information data, historical track data, environmental data, and cargo data; The initial route is constructed based on the historical track data and key nodes are obtained. The entire route is then divided into several segments based on the key nodes. The real-time information data of each segment is processed to obtain the route safety assessment index, and the environmental protection data is processed to obtain the route environmental protection assessment index; Based on cargo data and real-time information data, where cargo data includes the number of cargo batches and the actual delivery time required for each batch of cargo, and real-time information data includes the average wave height of each section, combined with the route safety assessment index, a comprehensive analysis is conducted to obtain the route timeliness assessment index; The smart route recommendation coefficient is obtained based on a comprehensive analysis of the route safety assessment index, route timeliness assessment index and route environmental assessment index, and the best smart route is recommended using the smart route recommendation coefficient.

2. The intelligent route recommendation method based on the S-100 standard according to claim 1 is characterized by: The real-time information data of each flight segment is processed to obtain the route safety evaluation index, and the specific processing process is as follows: The real-time information data specifically includes the number of ships in the section, the number of obstacles in the section, the average wind speed and the average wave height; The critical number of ships, critical number of obstacles and critical average wind speed are extracted from the S-100 standard database, and the route safety assessment index is obtained through comprehensive analysis.

3. The intelligent route recommendation method based on the S-100 standard according to claim 1 is characterized by: The environmental protection data is processed to obtain the route environmental protection evaluation index, and the specific analysis process is as follows: The environmental data include greenhouse gas emissions throughout the route and the number of times the protected area is crossed; The critical greenhouse gas emissions and the number of crossings of the critical protection zone were extracted from the S-100 standard database, and a comprehensive analysis was performed to obtain the route environmental assessment index.

4. The intelligent route recommendation method based on the S-100 standard according to claim 2 is characterized in that: The route timeliness evaluation index is a quantitative indicator obtained by analyzing the actual delivery time of each batch of goods, the average wave height of each section and the route safety evaluation index, and is used to quantify the timeliness performance of the route.

5. The intelligent route recommendation method based on the S-100 standard according to claim 2 is characterized by: The comprehensive analysis obtains the intelligent route recommendation coefficient, and the specific analysis process is as follows: Based on the route safety assessment index, route timeliness assessment index and route environmental protection assessment index, a comprehensive analysis is conducted to obtain the smart route recommendation coefficient.

6. The intelligent route recommendation method based on the S-100 standard according to claim 2 is characterized by: The route safety assessment index is a quantitative indicator obtained by analyzing the number of ships, the number of obstacles and the average wind speed in each section, and is used to quantify the safety performance of the route.

7. The intelligent route recommendation method based on the S-100 standard according to claim 1 is characterized by: The best smart route is recommended by using the smart route recommendation coefficient. The specific recommendation process is as follows: Extracting the smart route recommendation coefficient threshold from the S-100 standard database, comparing the smart route recommendation coefficient of each route with the smart route recommendation coefficient threshold, if the smart route recommendation coefficient of a route is greater than or equal to the smart route recommendation coefficient threshold, the route is evaluated as a qualified route, if the smart route recommendation coefficient of the route is less than the smart route recommendation coefficient threshold, the route is evaluated as an unqualified route; The smart route recommendation coefficients of qualified routes are arranged in order from large to small, and the route with the largest smart route recommendation coefficient is marked as the best smart route.

8. The intelligent route recommendation method based on the S-100 standard according to claim 2 is characterized by: The specific numerical expression of the route safety evaluation index is: Among them, A represents the route safety assessment index, e represents the natural constant, S i represents the number of ships on the route of the ith segment, S0 represents the maximum number of ships allowed in the segment, and L i represents the number of obstacles on the route of the ith flight segment, L0 represents the maximum number of obstacles allowed in the flight segment, and F i represents the average wind speed of the i-th segment, F0 represents the maximum allowable average wind speed of the segment, ω1 represents the route safety assessment impact factor corresponding to the set number of ships in the segment, ω2 represents the route safety assessment impact factor corresponding to the set number of obstacles in the segment, ω3 represents the route safety assessment impact factor corresponding to the set average wind speed in the segment, i represents the number of segments, i=1,2,3,...,m, and m represents the total number of segments.

9. The intelligent route recommendation method based on the S-100 standard according to claim 4 is characterized by: The specific numerical expression of the route timeliness evaluation index is: Among them, B represents the route timeliness evaluation index, e represents the natural constant, T j represents the actual delivery time of the jth batch of goods, T j0 It represents the time required for the delivery of the set critical goods, P i represents the average wave height of the ith segment, P0 represents the average wave height of the set critical segment, A represents the route safety assessment index, A0 represents the set critical route safety assessment index, Indicates the impact factor of the route timeliness assessment corresponding to the set time deviation required for cargo delivery, It represents the impact factor of the route timeliness assessment corresponding to the set average wave height, It represents the route timeliness assessment influencing factor corresponding to the set route safety assessment index, i represents the number of flight segments, i=1,2,3,...,m, m represents the total number of flight segments, j represents the number of cargo batches, j=1,2,3,...,n, n represents the total number of cargo batches.

10. A system using the intelligent route recommendation method based on the S-100 standard according to any one of claims 1 to 9, characterized in that: include: Intelligent route data collection module, used to collect real-time information data, historical track data, environmental data, and cargo data, including the number of ships in the route, the number of obstacles in the route, the average wind speed, the average wave height, the greenhouse gas emissions of the entire route, the number of times the protected area is crossed, the number of cargo batches, and the actual delivery time required for each batch of cargo; The intelligent route safety and environmental protection evaluation module is used to construct the initial route and obtain key nodes based on historical track data, and then divide the entire route into several small routes based on the key nodes, process the real-time information data of each small route to obtain the route safety evaluation index, and process the environmental protection data to obtain the route environmental protection evaluation index; Intelligent route timeliness evaluation module, which is used to obtain the route timeliness evaluation index through comprehensive analysis based on cargo data and real-time information data; The smart route recommendation module is used to evaluate each smart route according to the smart route recommendation coefficient. If the evaluation result is qualified, the recommendation coefficients of each qualified smart route are then compared. The route with the highest recommendation coefficient is recommended as the best smart route. If the evaluation result is unqualified, the smart route is discarded. The S-100 standard database is used to store data related to smart routes, including route safety assessment influencing factors corresponding to the number of ships in the section, route safety assessment influencing factors corresponding to the number of obstacles in the section, route safety assessment influencing factors corresponding to the average wind speed, critical cargo delivery time, critical average wave height, critical route safety assessment index, route environmental assessment influencing factors corresponding to the greenhouse gas emissions of the entire route, route environmental assessment influencing factors corresponding to the number of protected area crossings, and smart route recommendation coefficient thresholds.

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