An intelligent route recommendation method and system based on the S-100 standard

Abstract

The present invention relates to the field of marine surveying and mapping technology, and specifically discloses a method and system for intelligent route recommendation based on the S-100 standard. The method comprises: collecting real-time information data, historical track data, environmental protection data, and cargo data; processing to obtain a route safety assessment index, and processing the environmental protection data to obtain a route environmental protection assessment index; comprehensively analyzing the cargo data and real-time information data to obtain a route timeliness assessment index; comprehensively analyzing to obtain an intelligent route recommendation coefficient, and using the intelligent route recommendation coefficient to recommend the best intelligent route. 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, and reduce carbon emissions, providing users with safer, more efficient, and more environmentally friendly route options, while supporting the goal of sustainable development.

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] Currently, 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 publication number CN111536962B is a route planning method and device, storage medium, and computer equipment for intelligent ships. The method includes: if a target ship determines that it is within a preset range of a narrow waterway based on current electronic nautical chart information, a first set of routes for the target ship to pass through the narrow waterway is planned, and the risk value of each route in the set is calculated to ensure that the target ship follows the navigation path with the lowest risk value; the target ship obtains its own ship information and surrounding obstruction information in real time to calculate the collision risk between the target ship and the surrounding obstructions. If the collision risk exceeds a preset safety threshold, a second set of routes for the target ship to pass through the narrow waterway is planned, and the risk value of each route in the set is calculated to ensure that the target ship follows the navigation path with the lowest risk value. This method can provide a safe and feasible route 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 route end point, and performing route planning based on the improved genetic algorithm according to the route network, route starting point and route end point to obtain the initial optimal route; 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, the present application discovered 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 ocean 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 shortcomings of the existing technology, 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] Based on historical track data, the initial route is constructed 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 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 required for each batch of cargo, and real-time information data includes the average wave height of each route 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. 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 were extracted from the S-100 standard database, and a comprehensive analysis was conducted to obtain the route safety assessment index.

[0013] As a further method, the environmental protection data is processed to obtain an environmental protection assessment index of the route. The specific analysis process is: 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 conducted 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 smart 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 evaluation index, the smart 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 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, 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 the qualified routes are arranged in descending order, 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 assessment 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 Indicates the number of ships on the route of the i-th segment, S0 indicates the maximum number of ships allowed in the segment, L i Indicates the number of obstacles on the route of the i-th segment, L0 indicates the maximum number of obstacles allowed in the 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 of 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 route timeliness evaluation index is specifically expressed as follows:

[0024]

[0025] Among them, B represents the route timeliness evaluation index, e represents the natural constant, T j T represents the actual delivery time of the jth batch of goods, j0 It represents the time required for the critical goods to be delivered, P irepresents the average wave height of the i-th segment, P0 represents the set critical segment average wave height, 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, Indicates the impact factor of the route timeliness assessment corresponding to the set average wave height, It represents the route timeliness assessment impact 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 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, 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, 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 based on comprehensive analysis of cargo data and real-time information data.

[0029] The smart route recommendation module is used to evaluate each smart route based on 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 routes meet 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 trends on the route.

[0034] (3) By evaluating the timeliness of shipping routes, the present invention can understand the transportation needs and characteristics of different shipping routes and different goods, thereby rationally allocating port resources and ensuring 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 with reference to the accompanying drawings. However, 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 effort.

[0036] Figure 1 Schematic diagram of the method of the present invention.

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

[0038] Figure 3 Schematic diagram of the functional relationship between the route safety assessment index and the smart route recommendation coefficient involved in an embodiment of the present invention.

[0039] Figure 4 Flowchart of route data signal transmission of the present invention. DETAILED DESCRIPTION

[0040] 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.

[0041] Reference Figure 1 and Figure 4 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.

[0042] Based on historical track data, the initial route is constructed 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 data is processed to obtain the route environmental assessment index.

[0043] 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 route segment, combined with the route safety assessment index, a comprehensive analysis is conducted to obtain the route timeliness assessment index.

[0044] 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.

[0045] Specifically, an initial route is constructed based on historical track data and key nodes are obtained. The entire route is then divided into several segments based on the key nodes. The specific process is as follows: the historical track data is the GPS track record of passing ships, usually provided by an automatic identification system. 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.

[0046] Specifically, the real-time information data of each section is processed to obtain a route safety assessment 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.

[0047] 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.

[0048] 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.

[0049] It should be understood that the said section obstacles include fixed obstacles in each section such as shoals, shipwrecks, rocks, lighthouses, etc., as well as mobile obstacles such as buoys and drifting objects.

[0050] In one specific embodiment, an automatic identification system (AIS) is used to track and count the number of ships in each section. The latest electronic nautical chart data and a real-time monitoring system are used to determine the number of obstacles in each section. Furthermore, data from offshore weather stations is used to determine the average wind speed for each section. By monitoring the number of ships in each section, high-density areas can be identified promptly, helping ships avoid busy waterways and choose more accessible alternative routes, thereby reducing the risk of collisions between ships. By monitoring the number of obstacles in each section, obstacles can be marked and removed promptly, reducing the risk of collisions between ships and obstacles. The location and type of obstacles can also be used to adjust the channel design and improve navigation efficiency. By monitoring the average wind speed in each section, captains and crew can plan the optimal route based on current and expected wind conditions, thereby avoiding strong wind areas and reducing navigation risks. It can also predict possible high winds in advance and take appropriate preventative measures.

[0051] Specifically, the route safety assessment index has the following numerical expression:

[0052]

[0053] Among them, A represents the route safety assessment index, e represents the natural constant, S i Indicates the number of ships on the route of the i-th segment, S0 indicates the maximum number of ships allowed in the segment, L i Indicates the number of obstacles on the route of the i-th segment, L0 indicates the maximum number of obstacles allowed in the 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 of the segment, i represents the number of segments, i = 1, 2, 3, ..., m, and m represents the total number of segments.

[0054] The algorithm in this embodiment combines the number of ships, the number of obstacles, and the average wind speed in each section to comprehensively analyze and obtain a route safety assessment index. In this formula, the greater the number of ships in each section, the more likely it is that the channel will be congested, making it difficult for ships to avoid obstacles and increasing navigation risks. In addition, 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 be stranded on the channel for longer periods of time. The formation of certain obstacles (such as driftwood and icebergs) is related to wind speed. Strong winds may cause more obstacles to appear on the channel. Comprehensive analysis can produce a more comprehensive route safety assessment index.

[0055] Table 1 Example of route safety assessment index data

[0056]

[0057] As shown in Table 1, the route safety assessment index is determined by the number of ships in a segment, the number of obstacles in the segment, and the average wind speed. In one specific embodiment, m = 1, the maximum number of ships allowed in a segment is 20, the maximum number of obstacles allowed in a segment is 5, and the maximum average wind speed allowed is 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. It can identify high-risk areas and take corresponding measures to reduce the probability of collision, such as speed restrictions or diversion measures. Taking into account the average wind speed, routes with smaller tailwinds or headwinds can be selected to reduce sailing time and save fuel. In segments with higher wind speeds, alternative routes may need to be selected to avoid adverse wind effects. By standardizing the number of ships, obstacles, and average wind speeds across different routes, ensuring they are compared at the same level, the assessment is fairer and more comparable. This also helps identify which routes are safer, enabling more efficient resource allocation. By weighting the impact of the number of ships, obstacles, and average wind speed on a route, the relative importance of these factors in the assessment index can be reflected. The weights of these factors can be adjusted to suit specific needs, making the model highly adaptable. It can be seen that the lower the number of ships, obstacles, or average wind speed on a route, the higher the route safety assessment index. By assessing the route safety index, safer routes can be planned for ships, avoiding hazardous areas and reducing the risk of collisions and groundings. It can also identify congested and windy routes, enabling measures to reduce travel time and improve overall transport efficiency. Long-term safety assessment data can also be used in scientific research to understand risk trends along 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 by using 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 protection data is processed to obtain an environmental protection assessment 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.

[0062] The route environmental impact factors corresponding to the preset greenhouse gas emissions of the entire route and the route environmental impact factors corresponding to the number of obstacles on the route 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 one specific embodiment, sensors and monitoring equipment are installed to directly measure greenhouse gas emissions from ship engines, and the number of protected area crossings along the route is monitored using the Automatic Identification System (AIS). Monitoring greenhouse gas emissions along the route can help identify emission hotspots and reduction opportunities, enabling them to reduce greenhouse gas emissions by adjusting operating procedures or adopting more efficient fuels and technologies. Monitoring the number of protected area crossings along the route can also help ensure that route planning avoids important ecological areas, reducing impacts on local ecosystems and thus maintaining biodiversity and ecosystem health.

[0065] Specifically, the route environmental performance evaluation index is expressed as follows:

[0066]

[0067] Among them, C represents the environmental performance evaluation 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 environmental performance evaluation impact factor corresponding to the greenhouse gas emissions of the entire route, and θ2 represents the environmental performance evaluation impact factor corresponding to the number of times the route crosses the protected area.

[0068] The algorithm in this embodiment combines the greenhouse gas emissions of the entire route and the number of protected area crossings to comprehensively analyze and obtain a route environmental assessment index. Avoiding crossing protected areas as much as possible can reduce the impact on the environment, but it may also lead to changes in route length. Longer routes may lead to higher greenhouse gas emissions because ships need to consume more fuel to complete the journey. There is a certain trade-off between greenhouse gas emissions of the entire route and the number of protected area crossings. Comprehensive analysis can minimize the impact on the environment and obtain a more comprehensive route environmental assessment index.

[0069] It should be noted that this example considers two key factors: greenhouse gas emissions along the entire route and the number of protected area crossings. This can reduce disruption to ecosystems and wildlife, contributing to mitigating global warming and climate change. Transparent reporting of greenhouse gas emissions and protected area crossings can enhance public trust, bring social benefits, and contribute to the achievement of sustainable development goals. By standardizing greenhouse gas emissions along the entire route and the number of protected area crossings, ensuring they are compared at the same level, the fairness and comparability of the assessment are improved. Furthermore, the settings of U0 and V0 provide a reference for shipping companies and regulators to understand when acceptable environmental performance levels are met or exceeded. By weighting the impact of greenhouse gas emissions along the entire route and the number of protected area crossings, reflecting their relative importance in the assessment index, the weights of different factors can be adjusted according to different needs, making the model highly adaptable. It is not difficult to see that the lower the greenhouse gas emissions along the entire route or the number of protected area crossings, the higher the route's environmental performance assessment index.

[0070] In a specific embodiment, the value range of the route environmental assessment impact 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 impact factor of each route can be obtained from the S-100 standard database. By adjusting the value of the impact factor, the degree of influence of different factors on the final route environmental assessment index can be flexibly adjusted.

[0071] It should be understood that in this embodiment, the relationship between the greenhouse gas emissions of the entire route and the number of times the protected area is crossed and the environmental impact assessment index of the route is constructed to construct a mapping set of route environmental impact assessment factors corresponding to the greenhouse gas emissions of the entire route and the number of times the protected area is crossed. The real-time greenhouse gas emissions of the entire route and the number of times the protected area is crossed are input, and the corresponding route environmental impact 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 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 cargo, 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 and thus reducing additional costs. By monitoring the average wave height of each section, safer and more efficient routes can be planned, which helps 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, and corrective measures can be taken to avoid accidents.

[0077] Specifically, the route timeliness evaluation index has the following numerical expression:

[0078]

[0079] Among them, B represents the route timeliness evaluation index, e represents the natural constant, T j T represents the actual delivery time of the jth batch of goods, j0 It represents the time required for the critical goods to be delivered, P i represents the average wave height of the i-th segment, P0 represents the set critical segment average wave height, 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, Indicates the impact factor of the route timeliness assessment corresponding to the set average wave height, It represents the route timeliness assessment impact 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 in this embodiment combines the actual delivery time required for cargo, average wave height, and route safety assessment index to comprehensively analyze and obtain the route timeliness assessment index. Higher waves may cause the ship to slow down, extending the voyage time, thereby affecting the actual delivery time of cargo. Higher waves may also increase navigation risks, further affecting route safety. Safe routes often provide more stable and predictable sailing times, reduce the occurrence of accidents, and thus ensure on-time delivery of cargo. Comprehensive analysis can maximize the efficiency and safety of the route and obtain a more comprehensive route timeliness assessment index.

[0081] It should be noted that this embodiment considers three key factors: actual delivery time, average wave height, and route safety assessment index. This can predict and reduce delays caused by inclement weather, thereby increasing the probability of on-time delivery of goods. It also allows for more efficient route planning, avoids high-risk areas, and reduces additional costs caused by unexpected events, thereby enhancing customer satisfaction and promoting the healthy development of the entire industry. By standardizing the actual delivery time, average wave height, and route safety assessment index to ensure they are compared at the same level, the fairness and comparability of the assessment are improved. It is also possible to identify which factors have the greatest impact on route timeliness, allowing for targeted improvements. It is not difficult to see that the shorter the actual delivery time, the lower the average wave height, or the higher the route safety assessment index, the higher the route timeliness assessment index. By assessing route timeliness, we can understand the transportation needs and characteristics of different routes and different goods, thereby rationally allocating port resources such as berths, storage yards, and equipment, ensuring the efficient use of port resources. It can also optimize port operation processes, improve port operational efficiency, reduce vessel waiting time, and thus reduce overall operating costs.

[0082] In a specific embodiment, the route timeliness assessment influencing factors corresponding to the actual delivery time of the cargo, the average wave height, and the route safety assessment index have values ranging from 0 to 1. Each route timeliness assessment influencing factor can be obtained from the S-100 standard database. By adjusting the values of the influencing factors, the degree of 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, average wave height and route safety assessment index is constructed through the relationship between the actual delivery time of goods, average wave height and route safety assessment index in historical data, and the route timeliness assessment index. The real-time actual delivery time of goods, average wave height and 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. 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 follows:

[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 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 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 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, and ρ3 = 0.2. When B = C = 0.1, the functional relationship between the intelligent route recommendation coefficient and the route safety assessment index is shown as curve a; when B = C = 0.5, the functional relationship between the intelligent route recommendation coefficient and the route safety assessment index is shown as curve b; when B = C = 1, the functional relationship between the intelligent route recommendation coefficient and the route safety assessment index is shown as curve c.

[0092] It should be explained that in this embodiment, three key factors are comprehensively considered, namely the route safety assessment index, the route timeliness assessment index and the route environmental assessment index, which can achieve safer, more efficient and more environmentally friendly route operations, which are crucial for 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 assessment index, their relative importance in the assessment index is reflected, and the weights of different factors can be adjusted according to different needs, so that the model has good adaptability. It is not difficult to see that the larger the route safety assessment index or the route timeliness assessment index or the route environmental 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 factors 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. The influencing factors of each smart route recommendation coefficient can be obtained from the S-100 standard database. By adjusting the values of the influencing factors, the degree of influence of different factors on the final smart route recommendation coefficient can be flexibly adjusted.

[0094] 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. The real-time route safety assessment index, route timeliness assessment index and route environmental protection assessment index are input, and the corresponding intelligent route recommendation coefficient influencing factors are obtained from the mapping set.

[0095] 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.

[0096] 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 from 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.

[0097] The smart route recommendation coefficients of the qualified routes are arranged in descending order, and the route with the largest smart route recommendation coefficient is marked as the best smart route.

[0098] 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 for collecting real-time information data, historical track data, environmental protection data, and cargo data, including 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, the number of batches of cargo, and the actual delivery time required for each batch of cargo.

[0099] 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, 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.

[0100] The intelligent route timeliness evaluation module is used to obtain the route timeliness evaluation index based on comprehensive analysis of cargo data and real-time information data.

[0101] The smart route recommendation module is used to evaluate each smart route based on 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.

[0102] 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.

[0103] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments 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 scope of protection 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; Based on historical flight data, the initial route is constructed 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 route segment, combined with the route safety assessment index, a comprehensive analysis is conducted to obtain the route timeliness assessment index; The best smart route is recommended based on the smart route recommendation coefficient obtained through comprehensive analysis of the route safety assessment index, route timeliness assessment index, and route environmental assessment index. The real-time information data of each flight segment is processed to obtain the route safety assessment index. 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 a comprehensive analysis is performed to obtain the route safety assessment index. The environmental protection data is processed to obtain the route environmental protection evaluation index. 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 critical protection zone crossings were extracted from the S-100 standard database, and a comprehensive analysis was conducted to obtain the environmental performance evaluation index of the route. The route timeliness evaluation index is a quantitative indicator obtained by analyzing the actual delivery time required for each batch of cargo, the average wave height of each section, and the route safety evaluation index, and is used to quantify the timeliness performance of the route; 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, represents the actual delivery time of the jth batch of goods, Indicates the time required for the set critical goods to be delivered. represents the average wave height of the i-th segment, Indicates the average wave height of the set critical section, represents the route safety assessment index, Indicates 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, Indicates the impact factor of the route timeliness assessment corresponding to the set average wave height, It represents the route timeliness assessment impact 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.

2. The intelligent route recommendation method based on the S-100 standard according to claim 1, characterized in that: The comprehensive analysis results in the smart route recommendation coefficient. 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.

3. The intelligent route recommendation method based on the S-100 standard according to claim 1, characterized in that: 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.

4. The intelligent route recommendation method based on the S-100 standard according to claim 1, characterized in that: The optimal smart route is recommended 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 a route is less than the smart route recommendation coefficient threshold, the route is evaluated as an unqualified route; The smart route recommendation coefficients of the qualified routes are arranged in descending order, and the route with the largest smart route recommendation coefficient is marked as the best smart route.

5. The intelligent route recommendation method based on the S-100 standard according to claim 1, characterized in that: The specific numerical expression of the route safety assessment index is: ; in, represents the route safety assessment index, represents a natural constant, represents the number of ships on the route of the i-th segment, Indicates the maximum number of ships allowed in the voyage. represents the number of obstacles on the route of the i-th segment, Indicates the maximum number of obstacles allowed in the flight segment. represents the average wind speed of the i-th segment, Indicates the maximum allowable average wind speed for the flight segment. Indicates the impact factor of route safety assessment corresponding to the number of ships in the set section, Indicates the route safety assessment impact factor corresponding to the set number of obstacles in the flight segment, It represents the route safety assessment impact factor corresponding to the set average wind speed of the flight segment. i represents the number of flight segments, i=1,2,3,...,m, and m represents the total number of flight segments.

6. A system using the intelligent route recommendation method based on the S-100 standard according to any one of claims 1 to 5, characterized in that: include: The intelligent route data collection module is 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 protected areas crossed, the number of cargo batches, and the actual delivery time required for each batch of cargo; The intelligent route safety and environmental protection assessment module is used to construct an initial route based on historical track data and obtain key nodes. The entire route is then divided into several small routes based on the key nodes. The real-time information data of each small route is processed to obtain a route safety assessment index, and the environmental protection data is processed to obtain a route environmental protection assessment index. The intelligent route timeliness evaluation module is used to comprehensively analyze cargo data and real-time information data to obtain a route timeliness evaluation index; The smart route recommendation module is used to evaluate each smart route based on 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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