Intelligent scheduling system applied to vehicle stowage of ro-ro passenger ship

Abstract

The invention discloses an intelligent scheduling system applied to passenger roll-on-roll-off ship vehicle stowage, and the system comprises a data collection module which is configured to collect the information of vehicles, passengers, ships and ports from different information sources in real time through a scheduling interface; the data preprocessing module is configured to preprocess the acquired information of the vehicles, the passengers, the ships and the ports; the portrait updating module is configured to construct a truck portrait and a passenger portrait, and update the truck portrait and the passenger portrait in real time based on the vehicle and passenger information collected in real time; the priority ranking module is configured to update and rank the vehicle priority in real time according to the real-time updating result of the truck portrait and the passenger portrait; the stowage decision module is configured to output a stowage scheme based on the ship digital twin model and the vehicle priority ranking result; and the visualization module is configured to provide visual display of the loading process of the ro-ro passenger ship.

Description

Technical Field

[0001] The present invention relates to the technical field of ro-ro passenger ship loading and dispatching, and in particular to an intelligent dispatching system applied to ro-ro passenger ship vehicle loading and dispatching. Background Art

[0002] With the rapid development of the global economy, the demand for cargo transportation industry has increased year by year, especially in the shipping field. As a multifunctional ship integrating passenger and cargo transportation, Ro-Ro passenger ship has high economic value and practicality. In order to improve the transportation efficiency and safety of Ro-Ro passenger ships, new technologies and methods are constantly being applied to the management and scheduling of Ro-Ro passenger ships. However, in terms of Ro-Ro passenger ship loading management, traditional methods have been unable to meet the high efficiency and high precision requirements of the modern shipping industry. How to effectively load Ro-Ro passenger ships has become the key to improving transportation efficiency and service quality.

[0003] At present, the optimization of ro-ro passenger ship loading mostly adopts optimization algorithms such as linear programming, integer programming, genetic algorithm, etc. Although these methods can achieve better solutions in theory, they have certain limitations in practical applications, such as high algorithm complexity, resulting in long calculation time, sensitivity to parameters, strict requirements, and lack of adaptability.

[0004] In addition, existing ro-ro passenger ship stowage scheduling methods generally lack visualization functions. Since the amount of information in the stowage process is large and involves the allocation of multiple resources, such as ships, cargo, and passengers, it is difficult for existing technologies to achieve intuitive and clear display in the ro-ro passenger ship stowage scheduling process, which makes it difficult for decision makers to quickly understand the overall situation, reducing scheduling efficiency and accuracy.

[0005] At the same time, the existing technology also has limitations in the realization of the query function in the process of ro-ro passenger ship loading and scheduling. The query function usually requires screening and processing of huge amounts of data, while the existing query method is relatively cumbersome and has low query efficiency, which is not conducive to improving the overall scheduling efficiency. Summary of the invention

[0006] In view of the above-mentioned prior art, the present invention provides an intelligent dispatching system for vehicle loading on ro-ro passenger ships, mainly to solve the technical problems existing in the above-mentioned background technology.

[0007] To achieve the above object, the technical solution of the embodiment of the present invention is implemented as follows:

[0008] An intelligent dispatching system for vehicle loading on a ro-ro passenger ship, the dispatching system comprising:

[0009] A data collection module, wherein the data collection module is configured to collect vehicle, passenger, ship and port information from different information sources in real time through a dispatch interface;

[0010] A data preprocessing module, wherein the data preprocessing module is configured to preprocess the acquired vehicle, passenger, ship and port information;

[0011] A portrait updating module, wherein the portrait updating module is configured to construct a truck portrait and a passenger portrait, and update the truck portrait and the passenger portrait in real time based on the vehicle and passenger information collected in real time;

[0012] A priority sorting module, wherein the priority sorting module is configured to update and sort vehicle priorities in real time according to the real-time update results of the truck portrait and the passenger portrait;

[0013] A loading decision module, wherein the loading decision module is configured to output a loading plan based on the ship digital twin model and the vehicle priority sorting results;

[0014] The visualization module is configured to provide a visualization display of the ro-ro passenger ship loading process.

[0015] Optionally, the truck portrait content includes cargo timeliness, cargo transportation progress and vehicle status, and the passenger portrait content includes personnel timeliness, arrival time and special needs.

[0016] Optionally, update and sort vehicle priorities in real time, including: setting, or calculating the cargo timeliness weight W m , cargo transportation progress weight W p , vehicle state weight W v , and, set, or, calculate the personnel timeliness weight W t , arrival time weight W a , Special demand weight W s , the comprehensive vehicle priority is calculated by the following formula based on the above-mentioned weights: Comprehensive priority = static weight × (1 + W m +W p +W v +W t +W a +W s ), sorting is performed based on the comprehensive priority calculation results, giving priority to vehicles with higher rankings, and recalculating the comprehensive priority and adjusting the sorting when new data is updated.

[0017] Optionally, based on the digital twin model of the ship and the vehicle priority ranking results, a loading plan is output, including:

[0018] Build a digital twin model of the ship and generate an empty stowage plan list;

[0019] Traverse all vehicles to be assigned and check whether the vehicles meet the ship's load and space requirements. If the vehicle's weight and size are within the ship's remaining capacity, add the vehicle to the loading sequence and update the ship's remaining load and space.

[0020] According to the vehicle priority sorting results and intelligent algorithms, the loading order and loading position of each vehicle are generated for all vehicles in the loading sequence;

[0021] The loading order and loading position of each vehicle are input into the digital twin model of the ship to simulate the placement of different vehicles in the cabin and generate multiple loading plans that maximize the use of cabin space;

[0022] Evaluate the stability, safety, timeliness and energy consumption of multiple loading schemes respectively;

[0023] According to the evaluation results, the optimal loading scheme is selected, included in the loading scheme list and output.

[0024] Optionally, the process of building a digital twin model of a ship includes: using basic data such as CAD drawings and structural drawings of the ship to build a virtual space model of the ship, converting the physical structure of the ship into a virtual structure of the virtual space model, and gridding the internal space of the virtual space model of the ship, where each grid represents a small part of the ship's space and annotates the availability and remaining load information of that part of the space.

[0025] Optionally, a loading simulation diagram based on the digital twin model of the ship is generated by using Canvas technology, and the loading conditions inside each ship at the berth and on the deck of the ship are viewed through the loading simulation diagram.

[0026] Optionally, the system further comprises a query module, which is used to query the loading conditions of different ships as well as vehicle information and personnel information.

[0027] The beneficial effects of the present invention are as follows: 1) By applying a knowledge-driven loading algorithm for trucks and passenger portraits, the present invention optimizes the loading process of ro-ro passenger ships, and automatically generates the optimal loading plan by combining real-time data of vehicles, ships and ports. Compared with the prior art, the present invention significantly reduces the impact of human factors, improves the accuracy and efficiency of loading, and ensures maximum space utilization and load balance.

[0028] 2) By establishing a digital twin model of the ship, the present invention can simulate the ship space in real time and accurately calculate the allocation position of each vehicle, thereby maximizing the utilization of ship space, improving loading efficiency, and ensuring load balance. Compared with the existing technology, the ship digital twin technology makes loading decisions more accurate and dynamic, and can be adjusted according to real-time changes.

[0029] 3) The present invention provides a visualization function for the loading process of ro-ro passenger ships, so that decision makers can intuitively understand the entire loading process and results, and improve scheduling efficiency and accuracy. Compared with the prior art, the present invention has made innovations in visualization, which helps staff to better determine the placement of vehicles, thereby achieving optimized loading. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 A block diagram of an intelligent dispatching system for vehicle loading on ro-ro passenger ships

[0031] Figure 2 This is a flowchart of Canvas front-end image enhancement in an embodiment of the present invention;

[0032] Figure 3 The PC terminal displays the ship loading situation in an embodiment of the present invention;

[0033] Figure 4 This is a general schematic diagram of the ship loading operation at the PAD end in an embodiment of the present invention;

[0034] Description of Figure Numbers:

[0035] 1. Data acquisition module; 2. Data preprocessing module; 3. Image update module; 4. Priority sorting module; 5. Loading decision module; 6. Visualization module; 7. Query module. DETAILED DESCRIPTION

[0036] The technical solution of the present invention is further elaborated in detail below in conjunction with the drawings and specific embodiments of the specification. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In the following description, the expression "some embodiments" is related to a subset of all possible embodiments, but it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0037] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0038] It should be understood that the present invention can be implemented in different forms and should not be interpreted as being limited to the embodiments proposed herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and the scope of the present invention will be fully conveyed to those skilled in the art. And the purpose of the terms used herein is only to describe specific embodiments and is not intended to be a limitation of the present invention. When used herein, the singular forms of "one", "one" and "said / the" are also intended to include plural forms, unless the context clearly indicates another way. It should also be understood that the terms "compose" and / or "include" when used in this specification determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0039] It should also be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "inside", "outside", "left", "right" and similar expressions used herein are for illustrative purposes only and are not intended to be the only implementation method.

[0040] In order to fully understand the present invention, a detailed structure will be proposed in the following description to illustrate the technical solution proposed by the present invention. The optional embodiments of the present invention are described in detail as follows, but in addition to these detailed descriptions, the present invention may also have other implementations.

[0041] Please refer to the attached Figures 1 to 4 The present application provides an intelligent dispatching system for vehicle loading on a ro-ro passenger ship, the dispatching system comprising:

[0042] Data collection module 1, the data collection module is configured to collect vehicle, passenger, ship and port information from different information sources in real time through the dispatch interface; wherein, through data collection, the information that can be collected includes but is not limited to (except for encrypted sensitive information):

[0043] 1) Vehicle information: vehicle type, vehicle size, vehicle weight, license plate number, vehicle model, etc.

[0044] 2) Passenger information: number of passengers paying full / half-price / free tickets, type of passengers accompanying the passenger, payment status, etc.

[0045] 3) Vessel information: sailing (departure) date / time, vessel number, rated passenger capacity / total cargo capacity / deadweight tonnage, total number of passengers / vehicles assigned, vehicle / passenger loading limit, etc.

[0046] 4) Port and shipping information: port name code, berth number, route code, voyage number, etc.

[0047] A data preprocessing module 2, wherein the data preprocessing module is configured to preprocess the acquired vehicle, passenger, ship and port information;

[0048] A portrait updating module 3, wherein the portrait updating module is configured to construct a truck portrait and a passenger portrait, and update the truck portrait and the passenger portrait in real time based on the vehicle and passenger information collected in real time;

[0049] A priority sorting module 4, wherein the priority sorting module is configured to update and sort vehicle priorities in real time according to the real-time update results of the truck portrait and the passenger portrait;

[0050] A loading decision module 5, wherein the loading decision module is configured to output a loading plan based on the ship digital twin model and the vehicle priority ranking results;

[0051] The visualization module 6 is configured to provide a visualization display of the loading process of the ro-ro passenger ship.

[0052] Specifically, the system integrates multi-source data to obtain data from different information sources in real time, including vehicle dispatch systems, port management systems, ship monitoring systems, and third-party logistics platforms. These data cover vehicle type, weight, size, arrival time, type of transported goods, passenger identity, number of luggage, special needs, ship cabin structure, maximum load, remaining space, equipment status, as well as port berth arrangements, weather conditions, and traffic flow. Through API interfaces, sensor networks, RFID tags, cameras and other technical means, the system can fully grasp all key factors in the passenger and vehicle ferry loading process, ensure that subsequent decisions are based on the most accurate and timely information, and can quickly respond to emergencies such as vehicle delays or weather changes, dynamically adjust the loading plan, and ensure the flexibility and adaptability of the loading process.

[0053] Next, the data preprocessing module 2 cleans, standardizes and formats the collected raw data to ensure data quality and consistency. It can identify and process abnormal data, such as incorrect vehicle weight or unreasonable number of passenger luggage, and complete or estimate missing data. The preprocessing module also classifies and aggregates the data to extract useful information features, providing a basis for subsequent portrait construction and priority sorting. The preprocessed data is more standardized and reliable, avoiding decision-making errors caused by data quality issues. At the same time, it can be used more efficiently for subsequent analysis and calculation, improving the overall performance of the system.

[0054] Based on the real-time collected vehicle and passenger information, the system constructs and dynamically updates truck portraits and passenger portraits in the portrait update module 3. The truck portrait is a comprehensive description of each truck, including vehicle type, weight, size, type of transported goods, timeliness requirements, etc. The passenger portrait is a comprehensive description of each passenger, including passenger identity, number of luggage, special needs, such as mobility impairment or emergency material transportation, etc. The system will dynamically adjust the truck portrait and passenger portrait based on the real-time updated vehicle and passenger information to ensure that they always reflect the latest status. By constructing and updating these portraits, the system can have a more comprehensive understanding of the needs and characteristics of each vehicle and each passenger, thereby providing a more personalized basis for subsequent priority sorting and loading decisions. In particular, for passengers with special needs and high-timeliness goods, the system can prioritize their loading and improve user experience and satisfaction.

[0055] Based on the real-time update results of the truck portrait and passenger portrait output by the portrait update module 3, the system uses the priority of the vehicle sorting module 4 to dynamically adjust and sort. The system will assign a comprehensive priority to each vehicle based on various factors, such as the timeliness requirements of the vehicle, the special needs of the passengers, the weight and size of the vehicle, the berth arrangement of the port, etc. For example, a truck transporting fresh food may be given a higher timeliness weight, while a truck carrying dangerous goods will be given priority in a safe area. The system will also consider the traffic flow and weather conditions of the port to ensure that the loading plan can be completed in the shortest time. By dynamically adjusting the priority of the vehicle, the system can ensure that high-priority vehicles and passengers can quickly get on and off the ship, reduce waiting time, and improve the overall loading and unloading efficiency. At the same time, it can also flexibly respond to emergencies such as vehicle delays or weather changes to ensure the flexibility and adaptability of the loading plan.

[0056] The loading decision module 5 generates the optimal loading plan based on the digital twin model of the ship and the vehicle priority sorting results. The digital twin model of the ship is a virtual model that is completely synchronized with the actual ship, which can reflect the space distribution, center of gravity position, equipment status and other information in the cabin in real time. The system combines the space utilization optimization algorithm, stability analysis, safety assessment and other functions of the digital twin model to ensure that the loading plan not only maximizes the use of the cabin space, but also ensures the stability and safety of the ship. In addition, the system will also consider the priority of the vehicle to ensure that high-priority vehicles can be loaded first. With the support of the digital twin model, the loading decision module can generate a more scientific and reasonable loading plan, which maximizes the use of the cabin space while ensuring the stability and safety of the ship, reducing unnecessary space waste and energy consumption, and reducing operating costs. At the same time, through safety assessment, it also ensures the isolation of dangerous goods, temperature control of cold chain transportation, and reservation of emergency channels, etc., to improve the safety of the transportation process.

[0057] Finally, the visualization module 6 provides an intuitive operation interface for dispatchers, showing the real-time status of the ro-ro passenger ship loading process. Dispatchers can use this interface to view the placement of vehicles and cargo in the cabin, the center of gravity distribution of the ship, the operating status of equipment and other information. The system supports dispatchers to make manual adjustments through the visualization interface, view the effects of the adjustments in real time, and optimize the loading plan according to the actual situation. The visualization module enables dispatchers to understand the loading process more intuitively, reduces the difficulty of operation, improves work efficiency, enhances teamwork ability, and can provide real-time feedback on problems in the loading process, allowing dispatchers to make dynamic adjustments to ensure the optimal execution of the loading plan.

[0058] In an optional implementation, the data in the present application mainly comes from the call of the ferry intelligent dispatch interface. Before the interface call is initiated, it is necessary to initiate authentication to the interface server and obtain a Token. The Token is the globally unique interface call credential, and the Token is required when calling each interface. The data interface authentication process is mainly completed through two software tools, Python and Postman. The default calling method is POST. The specific steps are as follows:

[0059] 1) Import the required modules: hashlib is used to generate hash values, time is used to get the current time, and random is used to generate random numbers.

[0060] 2) Generate timestamp (time_stamp): Convert the current timestamp to an integer and save it as a string.

[0061] 3) Generate a random number (nonce): Use the random() function of the random module to generate a random number and save it as a string.

[0062] 4) Set application key (app_secret): Save the application key as a string.

[0063] 5) Sort the parameters: Sort the application key, timestamp, and random number in ASCII code order and concatenate them into a string.

[0064] 6) Create a SHA-1 hash object: Use the sha1() function in the hashlib module to create a SHA-1 hash object.

[0065] 7) Update the hash object: Encode the sorted parameter string and add it to the hash object, and use the update() method of the sha1 object to update it.

[0066] 8) Get the encrypted signature: Use the hexdigest() method of the sha1 object to get the SHA-1 encrypted value of the sort parameter string and use it as the signature.

[0067] 9) Output results: Output timestamp, random number and signature, which are key information for data interface authentication.

[0068] After obtaining the timestamp (time_stamp), random number (nonce) and signature (signature), the steps to obtain the token in the Postman debugging tool are as follows:

[0069] 10) Open the Postman debugging tool and create a new request.

[0070] 11) In the Header section of the request, add a field called "Authorization".

[0071] 12) In the Authorization field, set the authentication method to "Token".

[0072] 13) Generate Token: Concatenate the timestamp, random number and signature according to the format required by the interface and use them as the value of the Token. For example, if the Token format required by the interface is "timestamp = {timestamp} & nonce = {random number} & signature = {signature}", the concatenated string is used as the value of the Token.

[0073] 14) Fill the generated Token value into the Authorization field.

[0074] 15) Send request: Fill in other request parameters, such as URL, request method, request body, etc., and send the request.

[0075] Postman will use the entered Token as authentication information and attach the Token to the request to authenticate the interface.

[0076] After obtaining the Token of the authentication interface, you can call the business interface, also using Python software. The specific steps are as follows:

[0077] 1) Import the required modules: pandas for data processing, requests for sending HTTP requests, csv for processing CSV files, and ast for converting strings to dictionaries.

[0078] 2) Define the interface URL: Save the URL of the business data interface to be called in the variable url.

[0079] 3) Define basic data: According to the interface requirements, create a dictionary base_data, which contains the various fields of business data and their corresponding values.

[0080] 4) Set the request header: Create a dictionary headers and set the content of the request header, including 'content-type' and 'Authorization'.

[0081] 5) Define the time range: set the start time start_time and end time end_time, as well as the time interval interval.

[0082] 6) Loop call interface: Use the while loop to gradually increase the time interval within the specified time range to generate the corresponding request parameter data, which includes basic data and current time information. Then use the requests.post() method to send a POST request, passing the request parameter data and request headers, and get the response response of the interface.

[0083] 7) Process the response data: Convert the JSON data of the interface response into a DataFrame object df, and then use the df.apply() function and the custom function remove_non_lists() to filter out the rows that meet the conditions. Write the rows that meet the conditions into the CSV file 'output.csv'.

[0084] 8) Process CSV files: Open the 'output.csv' file and the 'final.csv' file, read each line of data in 'output.csv', and try to convert the string into a dictionary. If the conversion is successful, write the values ​​in the dictionary to the 'final.csv' file line by line.

[0085] 9) Complete the call: After completing the loop call and data processing, the calling process of the business data interface ends.

[0086] After data collection is completed, the collected data needs to be preprocessed, including data cleaning, organization and formatting, to ensure the accuracy, consistency and standardization of the data, and provide basic data support for subsequent intelligent scheduling and multi-dimensional loading decisions.

[0087] Among them, ① data cleaning refers to the removal of duplicate, erroneous or incomplete data from the collected data to ensure the accuracy and completeness of the data. For example, the data can be deduplicated by comparing information such as license plate numbers and ship names, and the missing or erroneous information in the data can be deleted. ② Data sorting refers to the standardization of the cleaned data to facilitate subsequent data analysis and processing. For example, information such as vehicle type, vehicle size, and vehicle weight can be uniformly formatted, or information such as cargo weight, quantity, and size can be uniformly converted to ensure data consistency and standardization. ③ Data formatting refers to the standardization of the cleaned and sorted data to adapt to the processing requirements of the intelligent scheduling system. For example, data such as vehicle information, ship information, and port information can be stored in a preset data format, or the data can be converted into a standard data format to facilitate system processing. ④ In the process of data preprocessing, data verification and exception handling are also required to ensure the accuracy and completeness of the data. For example, data verification technology can be used to verify the data to check the correctness and completeness of the data; if data abnormalities are found, corresponding exception handling is required, such as deleting abnormal data or manually modifying the data.

[0088] The details of the relevant data preprocessing are shown in Table 1.

[0089] Table 1 Specific contents of relevant data preprocessing

[0090]

[0091]

[0092] In one embodiment, the truck portrait content includes cargo timeliness, cargo transportation progress and vehicle status, and the passenger portrait content includes personnel timeliness, arrival time and special needs.

[0093] Furthermore, the vehicle priority is updated and sorted in real time, specifically including: setting, or calculating the cargo timeliness weight W m , cargo transportation progress weight W p , vehicle state weight W v , and, set, or, calculate the personnel timeliness weight W t , arrival time weight W a , Special demand weight W s , the comprehensive vehicle priority is calculated by the following formula based on the above-mentioned weights: Comprehensive priority = static weight × (1 + W m +W p +W v +W t +W a +Ws ), sorting is performed based on the comprehensive priority calculation results, giving priority to vehicles with higher rankings, and recalculating the comprehensive priority and adjusting the sorting when new data is updated.

[0094] Among them, the timeliness of goods (W m ): Goods with high timeliness have higher priority. The system dynamically adjusts the weight according to the timeliness requirements of the goods (for example, perishable goods have a higher timeliness weight).

[0095] Transport Progress (W p ): The current transportation progress and estimated arrival time of the truck. When a truck is delayed, its priority will be increased to ensure that it is loaded as soon as possible.

[0096] Vehicle status (W v ): If the truck is broken or in poor condition, its priority will be lower.

[0097] Passenger profile related weight factors:

[0098] Timeliness requirements (W t ): Business passengers or passengers who need to arrive urgently have higher priority. The system will dynamically adjust the weight according to the passenger's timeliness requirements.

[0099] Arrival time (W a ): Estimated arrival time of the passenger. If the passenger has already arrived at the terminal or is about to arrive, his priority is higher.

[0100] Special needs (W s ): Passengers with special needs (such as those with limited mobility, pregnant women, etc.) will also affect their priority, ensuring that special passengers are loaded in a timely manner.

[0101] In addition, the static weight is determined by factors such as vehicle type, weight, and size. The dynamic weight factor adjusts the corresponding weight based on the real-time updated truck and passenger portraits to ensure the rationality and flexibility of the priority sorting.

[0102] When new data is updated (such as passenger arrival time, truck transportation progress, special needs of trucks or passengers, etc.), the system will recalculate the dynamic weight and adjust the sorting. According to the dynamic weight calculation results, the vehicles will be reordered, giving priority to trucks and passengers with higher weights. Finally, the effect of the dynamic adjustment will be evaluated, and the influence coefficient and adjustment strategy of the weight factor will be optimized to ensure the optimization of the loading and scheduling plan.

[0103] In the present invention, in order to achieve a reasonable loading plan, the digital twin technology of the cabin is used to make multi-dimensional loading decisions. Through the digital twin technology, the internal space, load distribution and available area of ​​the ship can be accurately simulated, so as to optimize the loading. Multi-dimensional loading decision means taking into account various information such as vehicles, ships, ports, etc., and dynamically adjusting the loading plan based on the digital twin model of the ship to ensure the optimal use of the ship space, improve transportation efficiency and minimize costs.

[0104] By establishing a virtual ship model, the ship digital twin technology provides real-time feedback and simulation support for loading decisions. It can accurately simulate the internal structure and loading space of the ship, and dynamically adjust according to the actual loading requirements. The following is the specific process of multi-dimensional loading decision-making based on the ship digital twin technology:

[0105] Build a digital twin model of the ship and generate an empty stowage plan list;

[0106] Traverse all vehicles to be assigned and check whether the vehicles meet the ship's load and space requirements. If the vehicle's weight and size are within the ship's remaining capacity, add the vehicle to the loading sequence and update the ship's remaining load and space.

[0107] According to the vehicle priority sorting results and intelligent algorithms, the loading order and loading position of each vehicle are generated for all vehicles in the loading sequence;

[0108] The loading order and loading position of each vehicle are input into the digital twin model of the ship. The digital twin model of the ship can simulate the spatial changes of the ship in real time. According to the actual changes in the loading process, such as the actual weight or size of some vehicles is different from the expected), the use of the ship space is dynamically adjusted. During the loading process, the digital twin model provides real-time spatial data feedback. If the loading position of some vehicles is inappropriate, the system will automatically prompt and readjust the loading plan to ensure the optimal use of the ship space. Multiple loading plans that maximize the use of the cabin space are generated. The configuration plan includes the ship and port information assigned to each vehicle, and lists in detail the specific location of each vehicle, the car number, the loading and unloading order and other information;

[0109] Evaluate the stability, safety, timeliness and energy consumption of multiple loading schemes respectively;

[0110] According to the evaluation results, the optimal loading scheme is selected, included in the loading scheme list and output.

[0111] The stability analysis is used to evaluate the impact of different loading schemes on the stability of the cabin, to ensure that the center of gravity of the cargo is reasonably distributed, and to avoid ship instability due to improper loading.

[0112] Based on the weight and position of the vehicle, the system automatically calculates the center of gravity of the cabin and evaluates its impact on the stability of the ship. The system simulates swaying, tilting, etc. under different sea conditions to ensure that the ship can remain stable under various conditions.

[0113] If a loading plan causes the center of gravity of the cabin to shift, the system will suggest adjusting the position of the vehicles to ensure a reasonable center of gravity distribution. For example, heavier vehicles can be placed at the bottom of the cabin, or light vehicles can be placed on the sides to balance the center of gravity of the cabin.

[0114] Safety assessment is used to evaluate the impact of different loading solutions on safety based on the vehicle's weight, type and special needs (such as flammable and explosive items, cold chain transportation, etc.).

[0115] For vehicles transporting dangerous goods, the system will automatically place them in a safe area away from other goods to ensure that there is a sufficient safety distance between the dangerous goods and other goods. The system will also select a suitable storage location (such as a well-ventilated area with suitable temperature) based on the type of dangerous goods.

[0116] For goods that require temperature control (such as food, medicine, etc.), the system will allocate a dedicated refrigerated area for them and ensure that the temperature, humidity and other conditions in the area meet the requirements. The system will also monitor the operating status of the refrigeration equipment to detect and deal with potential problems in a timely manner.

[0117] Timeliness guarantee is used to arrange high-priority vehicles (such as time-sensitive goods or passengers with special needs) in locations that are easy to load and unload, ensuring that they can get on and off the ship quickly and reduce waiting time.

[0118] According to the priority of the vehicle, the system will give priority to high-priority vehicles entering the cabin and place them close to the exit or loading and unloading area. This ensures that these vehicles can complete loading and unloading in the shortest time and reduce waiting time.

[0119] Energy consumption optimization is used to simulate the impact of different loading schemes on the energy consumption of air conditioning, lighting and other equipment in the cabin, select the loading scheme with the lowest energy consumption, and reduce operating costs.

[0120] The system will simulate the impact of different loading schemes on the energy consumption of air conditioning, lighting and other equipment based on the environmental conditions in the cabin (such as temperature, humidity, light, etc.) and the placement of the vehicles. The system will evaluate the energy consumption level of each scheme and select the one with the lowest energy consumption.

[0121] Furthermore, the process of building a digital twin model of a ship includes: using basic data such as the ship's CAD drawings and structural drawings to build a virtual space model of the ship, converting the ship's physical structure into a virtual structure of the virtual space model, and gridding the internal space of the ship's virtual space model, where each grid represents a small part of the ship's space and annotates the availability and remaining load information of that part of the space.

[0122] Furthermore, in order to enable decision makers to intuitively understand the entire loading process and results, the present invention is mainly based on the PC-side data module and the PAD-side operation module, combined with Canvas technology, to display the loading process and results in a visual form to dispatchers, helping them to achieve "one picture" type of efficient management function for the real-time loading situation of the ship.

[0123] The PC side is used for the setting of basic data, interface data acquisition, synchronization, and the final display of the visual loading module; the ferry production management system provides basic data support, mainly including ship data, vehicle data, etc., supports customers to customize related parameters, and flexibly configures. Basic data is an extensibility technology, and information system managers can customize some codes to meet extensibility requirements. In order to enable dispatchers to perceive and guide actual ship loading in a timely, efficient, simple and intuitive manner, in this invention, Canvas technology is used to make new attempts and interpretations of ship loading.

[0124] Technical principle: Canvas is a label element. When used, it is the same as other labels. You need to create it first. <canvas>< / canvas> Tag, and then get the drawing context through the getContext('2d') function, which is an interface required for real drawing. The two pixel-level operation functions getImageData() and putImageData() provide possibilities and ideas for online image enhancement. The getImageData() method can return the RGBA value of the image and encapsulate it into an imageData array for subsequent calls by the user, which makes it possible to obtain the pixel points of the image in the foreground for corresponding operations; the putImageData() method can redraw the processed pixel points on the canvas for the viewer to view.

[0125] Traditional technology uses the analysis center to perform background image enhancement, and then feeds back to the front-end browser for display, which requires a lot of processing time and transmission time. Canvas technology directly enhances and redraws the image in the foreground without changing the original image, and can show the enhanced image to the dispatcher in real time. When the ship has completed all the loading, the dispatcher can view the loading status of each ship at the berth on the visualization platform. Through the visualization platform, "one picture" management is realized, and the loading status of all ships and all decks can be clearly seen. The system pops up the ship information window by clicking on the ship, and selects the loading status button, and the system will display the ship's loading status.

[0126] The PAD side is for on-site visual real-time stowage. This module is the main operation module of the system. The on-site dispatcher uses this module on the tablet side to select the ship that needs to be loaded. Through the license plate recognition device, the license plate information of the vehicle to be loaded is obtained on the tablet, and the length, width, height, weight, cargo and other information of the vehicle are further obtained through the license plate number. Through comparison, it is confirmed whether the license plate number of the vehicle to be loaded is consistent with that in the system. If it is inconsistent, the on-site dispatcher is allowed to manually adjust and enter the correct license plate number. At the same time, the on-site dispatcher can select the corresponding model for the vehicle, and drag the icon to the lane where the vehicle is actually located and the approximate corresponding position in the deck loading area to complete the loading operation. During the loading process, the cabin guide is allowed to adjust the position of the vehicle that has been completed at any time.

[0127] In an optional embodiment, in order to improve the query efficiency and simplify the query process, the present invention designs a ship loading query module 7 based on the intelligent scheduling system, which relies on the Oracle database to realize data indexing, provide multi-dimensional query, real-time query, query result display and other functions. The specific design steps of the ship loading query module are as follows:

[0128] 1) Database design: Design the database structure according to the requirements of ro-ro passenger ship loading and data model. Determine the structure, fields and relationships of the table to ensure the consistency and integrity of the data. Design the index according to the query requirements. Indexes can improve query performance and speed up the query. Select the appropriate index type according to the query frequency and field.

[0129] 2) Data import: Import the ro-pax ferry loading data into the Oracle database. Use tools provided by Oracle (such as SQL Loader) or programming languages ​​(such as Python) to implement data import.

[0130] 3) Query optimization: Use Oracle's query optimizer to optimize the query plan. The query optimizer will select the best execution plan based on the table's statistical information and query conditions. Use the HINTS instruction to guide the query optimizer to select a specific execution plan.

[0131] 4) Index optimization: Optimize the index based on the query performance requirements and actual conditions. You can consider creating new indexes, deleting unnecessary indexes, or adjusting the index storage method.

[0132] 5) Query statement writing: Write SQL query statements according to actual query requirements. Use correct syntax and query statement structure, and add appropriate query conditions and sorting rules as needed.

[0133] 6) Query execution plan analysis: Before executing a query statement, you can use tools (such as SQLDeveloper) or commands (such as EXPLAIN PLAN) provided by Oracle to obtain the query execution plan and analyze the query execution plan to see whether it meets performance requirements, such as index usage, table connection method, etc.

[0134] 7) Performance monitoring and tuning: Monitor database performance indicators, such as response time, query throughput, etc. You can use the performance monitoring tools provided by Oracle (such as Enterprise Manager) to monitor database performance, and perform performance tuning based on the monitoring results, including index optimization, SQL statement rewriting, database parameter adjustment, etc.

[0135] In summary, the present invention provides an intelligent dispatching system for ro-ro passenger ship vehicle loading, which realizes the automation, intelligence and visualization of the ro-ro passenger ship loading process by introducing multi-dimensional loading decision-making, greatly improving the production efficiency and overall dispatching effect of the passenger and cargo ro-ro terminal. At the same time, the present invention provides a quick query function, simplifies the query process, improves the query efficiency, and further improves the overall dispatching efficiency.

[0136] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An intelligent dispatching system for vehicle loading on a ro-ro passenger ship, characterized in that: The dispatching system comprises: A data collection module, wherein the data collection module is configured to collect vehicle, passenger, ship and port information from different information sources in real time through a dispatch interface; A data preprocessing module, wherein the data preprocessing module is configured to preprocess the acquired vehicle, passenger, ship and port information; A portrait updating module, wherein the portrait updating module is configured to construct a truck portrait and a passenger portrait, and update the truck portrait and the passenger portrait in real time based on the vehicle and passenger information collected in real time; A priority sorting module, wherein the priority sorting module is configured to update and sort vehicle priorities in real time according to the real-time update results of the truck portrait and the passenger portrait; A loading decision module, wherein the loading decision module is configured to output a loading plan based on the ship digital twin model and the vehicle priority sorting results; The visualization module is configured to provide a visualization display of the ro-ro passenger ship loading process.

2. The intelligent dispatching system for vehicle loading on a ro-ro passenger ship according to claim 1 is characterized in that: The truck portrait content includes cargo timeliness, cargo transportation progress and vehicle status, and the passenger portrait content includes personnel timeliness, arrival time and special needs.

3. The intelligent dispatching system for vehicle loading on a ro-ro passenger ship according to claim 2 is characterized in that: Real-time update and sorting of vehicle priorities, including: setting, or calculating the cargo timeliness weight W m , cargo transportation progress weight W p , vehicle state weight W v , and, set, or, calculate the personnel timeliness weight W t , arrival time weight W a , Special demand weight W s , the comprehensive vehicle priority is calculated by the following formula based on the above-mentioned weights: Comprehensive priority = static weight × (1 + W m +W p +W v +W t +W a +W s ), sorting is performed based on the comprehensive priority calculation results, giving priority to vehicles with higher rankings, and recalculating the comprehensive priority and adjusting the sorting when new data is updated.

4. The intelligent dispatching system for vehicle loading on a ro-ro passenger ship according to claim 3 is characterized in that: Based on the digital twin model of the ship and the vehicle priority ranking results, the loading plan is output, including: Build a digital twin model of the ship and generate an empty stowage plan list; Traverse all vehicles to be assigned and check whether the vehicles meet the ship's load and space requirements. If the vehicle's weight and size are within the ship's remaining capacity, add the vehicle to the loading sequence and update the ship's remaining load and space. According to the vehicle priority sorting results and intelligent algorithms, the loading order and loading position of each vehicle are generated for all vehicles in the loading sequence; The loading order and loading position of each vehicle are input into the digital twin model of the ship to simulate the placement of different vehicles in the cabin and generate multiple loading plans that maximize the use of cabin space; Evaluate the stability, safety, timeliness and energy consumption of multiple loading schemes respectively; According to the evaluation results, the optimal loading scheme is selected, included in the loading scheme list and output.

5. The intelligent dispatching system for vehicle loading on a ro-ro passenger ship according to claim 4, characterized in that: The process of building a digital twin model of a ship includes: using the ship's CAD drawings, structural drawings and other basic data to build a virtual space model of the ship, converting the ship's physical structure into a virtual structure of the virtual space model, and gridding the internal space of the ship's virtual space model. Each grid represents a small part of the ship's space and marks the availability and remaining load information of that part of the space.

6. The intelligent dispatching system for vehicle loading on a ro-ro passenger ship according to claim 5, characterized in that: The Canvas technology is used to generate a loading simulation diagram based on the digital twin model of the ship, through which the loading conditions inside each ship at the berth and on the deck of the ship can be viewed.

7. The intelligent dispatching system for vehicle loading on a ro-ro passenger ship according to claim 6, characterized in that: The system also includes a query module, which is used to query the loading conditions of different ships as well as vehicle information and personnel information.

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