A method, equipment, medium, and product for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels.

Abstract

This application discloses a method, equipment, medium, and product for scheduling cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport vessels, relating to the field of intelligent transportation. First, it collects basic information on roads leading to the port and real-time traffic data based on an open-source map API, using these as open-source map data. Then, it calculates the total number of vehicles waiting to cross the port during a predicted time period based on this open-source map data. Next, it calculates the average waiting time for each vehicle based on this total number of vehicles. Finally, it determines whether to trigger a decision to add more vessels based on the average waiting time. When this decision is triggered, it calculates the required number of additional vessels based on the total number of vehicles waiting to cross the port during the predicted time period and the port's vessel capacity. Based on the number of additional vessels, it optimizes the vessel scheduling scheme and manages and schedules the vessels. This application, using open-source map data to assist in the scheduling of cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport vessels, can improve the scientific nature and response speed of transportation scheduling.

Description

Technical Field

[0001] This application relates to the field of intelligent transportation technology, and in particular to a method, equipment, medium and product for scheduling cross-sea passenger and roll-on / roll-off transport vessels. Background Technology

[0002] Cross-sea passenger and vehicle ferry services are a vital mode of transportation connecting islands and the mainland, undertaking the tasks of passenger and vehicle distribution and cross-sea transfer. During peak holiday periods or in situations of concentrated travel due to weather or capacity fluctuations, problems such as prolonged vehicle congestion and severe road congestion leading to ports often occur. Current methods for counting waiting vehicles and scheduling ships mainly rely on the following types of approaches.

[0003] 1) Manual Statistics and Reporting: Currently, most ports use manual methods to count the number of vehicles waiting to cross the river, summarizing data through on-site inspections, manual counting, and regular reporting. While this method is simple, it suffers from poor data timeliness, inconsistent statistical standards, and the tendency to omit or miscount during peak periods, making it difficult to meet the needs of real-time monitoring and timely dispatch assistance.

[0004] 2) Unmanned Aerial Vehicle (UAV) Monitoring and Image Recognition: Some ports are experimenting with using UAVs or fixed monitoring systems to collect images and combine them with image recognition algorithms to automatically count vehicles waiting to cross the river. This method improves the level of automation, but it is greatly affected by weather, has a limited monitoring range, and requires high computing resources for image processing, resulting in high operation and maintenance costs, making it difficult to promote as a large-scale, all-weather, routine monitoring method.

[0005] 3) Port Scheduling and Ticketing Reservation Systems: The design of cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) ports generally includes existing ship scheduling and ticketing reservation systems, capable of collecting data on ship schedules, capacity allocation, ticket sales, and reservations. While these systems are highly effective in ship operation and ticketing management, they lack integration with external road traffic, making it impossible to monitor real-time congestion and vehicle density on roads outside the port area. Furthermore, discrepancies often exist between reservation data and actual arrivals, making them unreliable as the sole basis for scheduling.

[0006] 4) Traffic Flow Prediction and Simulation Research: Academic research has already developed methods based on traffic flow theory, simulation, or prediction models for estimating road traffic volume and queue length, mainly relying on monitoring facilities such as induction loops, ETC, or video checkpoints. These methods are widely used in general highway traffic management, but they are difficult to directly adapt to the special scenario of cross-sea passenger and vehicle ferry transportation, and a complete solution for estimating waiting vehicles and optimizing ship scheduling has not yet been formed.

[0007] It is evident that existing methods for counting waiting vehicles in cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport mainly rely on manual inspection and reporting. While this method is low-cost and simple to operate, it has significant limitations. Manual statistics cannot meet real-time requirements, and data lag is prone to occur during peak holiday periods or emergencies, affecting the timeliness and scientific accuracy of ship scheduling. While methods combining drones and video surveillance with image recognition improve automation, they are limited by weather conditions, coverage, and recognition costs, making large-scale, 24 / 7 continuous monitoring difficult. This method also requires additional manpower and financial investment in operation and maintenance, hindering its widespread application. Port scheduling and ticketing reservation systems are relatively comprehensive in managing ship schedules, capacity, and ticketing information, but lack the ability to link with external road traffic, failing to perceive real-time congestion and vehicle accumulation on roads leading to the port. Furthermore, discrepancies often exist between ticketing reservation data and actual arriving vehicles, resulting in inaccurate scheduling data. In addition, existing research methods based on traffic flow theory or simulation prediction are mostly applied to urban road or highway traffic management and are difficult to directly apply to cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport scenarios. These methods often rely on fixed traffic detection facilities, which are costly to deploy and maintain, and cannot flexibly meet the comprehensive scheduling needs of vehicle flow, ships and port capacity in cross-sea transportation.

[0008] In summary, existing technologies generally suffer from problems such as scattered data sources, insufficient real-time performance, inadequate utilization of real-time traffic data from open-source maps, and a disconnect between the estimation of waiting vehicles and ship scheduling. Scheduling methods still rely on manual experience and lack a data-driven, scientific decision-making mechanism. These shortcomings make cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport difficult to handle efficiently during peak periods and abnormal situations, urgently requiring new technological solutions. Summary of the Invention

[0009] The purpose of this application is to provide a method, equipment, medium, and product for scheduling cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport vessels, which is based on open-source map data to assist in the scheduling of cross-sea passenger and Ro-Ro transport vessels, so as to improve the scientific nature and response speed of transportation scheduling.

[0010] To achieve the above objectives, this application provides the following technical solution.

[0011] Firstly, this application provides a method for scheduling cross-sea passenger / roll-off (Ro-Ro) transport vessels, including: Basic information and real-time traffic data of roads leading to the port are collected based on the open-source map API and used as open-source map data; "port" here refers to passenger and roll-on / roll-off transport port; the basic information of the roads leading to the port includes the road name, location and number of lanes of each road; the real-time traffic data includes congested sections, congestion status and proportion of different types of vehicles on each road. The total number of vehicles waiting to cross the port during the predicted period is calculated based on open-source map data. The average waiting time for vehicles is calculated based on the total number of vehicles waiting to cross the port during the predicted period. The decision to add more ships is determined based on the average waiting time of vehicles. When the decision to add more vessels is triggered, the required number of new vessels is calculated based on the total number of vehicles waiting to cross at the port and the port's vessel capacity during the forecast period. Based on the increase in the number of ships, the ship scheduling plan is optimized, and the ships are managed and scheduled.

[0012] Optionally, the calculation of the total number of vehicles waiting to cross the port within the predicted time period based on open-source map data specifically includes: The average vehicle length is calculated based on the proportion of different vehicle types; different vehicle types include small passenger cars and large vehicles. Determine vehicle spacing based on congestion levels; The average length occupied by each vehicle on the road is calculated based on the average vehicle length and vehicle spacing. The total number of vehicles that can be accommodated in a congested section is calculated based on the length of the congested section and the number of lanes of each access road, as well as the average length occupied by each vehicle on the road. Predicted time period The total capacity of all congested sections of all access roads to the port is summed to obtain the predicted time period. Total number of vehicles waiting to cross the port .

[0013] Optionally, the step of calculating the average vehicle length based on the proportion of different vehicle types specifically includes: Using formula Calculate the average vehicle length ;in and The ratios of small passenger cars and large vehicles are respectively. ; and These are the average lengths of small passenger cars and large vehicles, respectively.

[0014] Optionally, the step of calculating the average length occupied by each vehicle on the road based on the average vehicle length and vehicle spacing specifically includes: Using formula Calculate the average length of road space occupied by each vehicle. ;in For vehicle spacing.

[0015] Optionally, the calculation of the total number of vehicles that a congested road segment can accommodate, based on the length of the congested section and the number of lanes of each access road, as well as the average length occupied by each vehicle on the road, specifically includes: Using formula Calculate the first The first on the road into the port Total number of vehicles that can be accommodated in each congested road section ;in Indicates the first The first on the road into the port The length of each congested road segment; Indicates the first The number of lanes on the access roads to the port.

[0016] Optionally, the step of calculating the average waiting time for vehicles based on the total number of vehicles waiting to cross the port during the predicted time period specifically includes: Using formula Calculate the average waiting time for vehicles ;in The rated vehicle carrying capacity of each vessel; It represents the average loading capacity of a ship per unit of time.

[0017] Optionally, the step of calculating the required number of new vessels based on the total number of vehicles waiting to cross the port and the port's vessel capacity during the predicted period specifically includes: Using formula Calculate the forecast period Port shipping capacity ;in For each ship Rated vehicle carrying capacity; For the prediction period All ships inside The planned number of departures; when When using the formula Calculate the forecast period Number of vehicles in short supply ; Combined with average single-ship capacity Using formula Calculate the required number of new ships .

[0018] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the cross-sea passenger roll-on / roll-off transport vessel scheduling method.

[0019] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the cross-sea passenger and roll-on / roll-off transport vessel scheduling method.

[0020] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the cross-sea passenger and roll-on / roll-off transport vessel scheduling method.

[0021] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method, equipment, medium, and product for scheduling cross-sea passenger / roll-on / roll-off (Ro-Ro) transport vessels. Based on open-source map data, it assists in the scheduling of Ro-Ro passenger / roll-off vessels by comprehensively integrating and deeply mining the basic information on port access roads and real-time road condition data provided by open-source maps. Combined with port vessel capacity and scheduling optimization decisions, it achieves scientific, accurate, and efficient scheduling of cross-sea passenger / roll-off (Ro-Ro) transport vessels. This application not only optimizes the scheduling process and improves the utilization efficiency of vessel capacity, but also significantly enhances the scientific nature, real-time performance, and reliability of the scheduling scheme, providing strong support for the safety and smooth operation of cross-sea passenger / roll-off transport. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating a method for scheduling cross-sea passenger and vehicle roll-on / roll-off transport vessels according to this application; Figure 2 This is a schematic diagram of the overall framework of a cross-sea passenger roll-on / roll-off transport vessel scheduling method proposed in this application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] This application proposes a method, equipment, medium, and product for scheduling cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport vessels. Belonging to the field of passenger and vehicle roll-on / roll-off transport management and traffic big data applications, this method combines real-time traffic information provided by open-source map data with port vessel scheduling data to assist in vessel scheduling decisions in cross-sea passenger and vehicle roll-on / roll-off transport scenarios. By integrating real-time traffic information from open-source maps with port vessel capacity data, it enables dynamic estimation of the number of vehicles awaiting ferries and provides optimized suggestions for vessel departure timing, improving the scientific nature and response speed of transport organization. This ensures the safe and efficient operation of cross-sea passenger and vehicle roll-on / roll-off transport and provides new technical means for intelligent port scheduling.

[0026] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] In one exemplary embodiment, such as Figure 1 As shown, a method for scheduling cross-sea passenger roll-on / roll-off (Ro-Ro) transport vessels is provided, including the following steps 1 to 6.

[0028] Step 1: Collect basic information on roads leading to the port and real-time traffic data based on the open-source map API, and use them together as open-source map data.

[0029] This application utilizes open-source map data to assist in the scheduling of cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transport vessels. Its overall framework is as follows: Figure 2 As shown. To achieve efficient perception of cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) vessel scheduling, it is first necessary to collect open-source map data. On the one hand, it is necessary to collect basic information of the access roads to the port based on the open-source map API (Application Programming Interface). The collected basic information of the access roads includes the road name, location, and number of lanes of each access road (main road). On the other hand, based on the collected basic information of the access roads to the port, real-time traffic data is collected from the open-source map API. Specifically, based on the open-source map API, an automated data acquisition program is built using the Python programming language to request and obtain real-time traffic information of the access roads to the port. Based on the collected real-time traffic information, JSON format data is parsed to extract key fields such as congestion status (e.g., congested road sections, congestion status, and congestion trends), the number of different types of vehicles, and vehicle speed. Further processing or calculation is performed to obtain data such as congested road sections, congestion status, and the proportion of different types of vehicles for each access road, which serves as the required real-time traffic data. Based on the above open-source map data, a data caching mechanism is constructed for the establishment of the dynamic analysis model of waiting vehicles in step 2.

[0030] Step 2: Calculate the total number of vehicles waiting to cross the port during the predicted time period based on open-source map data.

[0031] Based on the open-source map data of the port access road collected and preprocessed in step 1, a dynamic analysis model for waiting vehicles is established. This dynamic analysis model for waiting vehicles calculates the total number of waiting vehicles in the port during the predicted period based on the open-source map data, specifically including the following steps 2.1 to 2.5.

[0032] Step 2.1: Calculate the average vehicle length based on the proportion of different vehicle types.

[0033] This application classifies different types of vehicles into small passenger cars and large vehicles, based on the ratio of small passenger cars to large vehicles. and The average vehicle length is calculated using the following formula. : (1); in, and These are the average lengths of small passenger cars and large vehicles, for example, 4.5 meters and 12 meters respectively. .

[0034] Step 2.2: Determine vehicle spacing based on congestion conditions.

[0035] For each congested section of the access road to the port, vehicle spacing is defined for different congestion levels based on the congestion level returned by the open-source map API. .

[0036] Step 2.3: Calculate the average length occupied by each vehicle on the road based on the average vehicle length and vehicle spacing.

[0037] Based on average vehicle length and the defined vehicle spacing in congestion conditions The average length occupied by each vehicle on the road is calculated using the following formula. : (2).

[0038] Step 2.4: Calculate the total number of vehicles that the congested road section can accommodate based on the length of the congested section and the number of lanes of each access road, as well as the average length occupied by each vehicle on the road.

[0039] When calculating the vehicle capacity of a road segment, for each road Congested road sections (also known as the first) The first on the road into the port (Congested road sections), based on the length of the congested road sections. and number of road lanes Calculate the total number of vehicles that this congested road section can accommodate: (3); in, Indicates the first The first on the road into the port The length of each congested road segment; Indicates the first The number of lanes on the access roads to the port. Indicates the first The first on the road into the port The total number of vehicles that can be accommodated in each congested road section.

[0040] Furthermore, it's possible to differentiate between passenger cars and large vehicles. By allocating the total vehicle capacity of congested road sections according to the ratio of passenger cars to large vehicles, the number of different vehicle types (passenger cars and large vehicles) can be estimated: (4); in, Indicates the first The first on the road into the port The total number of small passenger vehicles that can be accommodated on each congested road section. Indicates the first The first on the road into the port The total number of large vehicles that each congested road section can accommodate.

[0041] Step 2.5: Predict the time period The total capacity of all congested sections of all access roads to the port is summed to obtain the predicted time period. Total number of vehicles waiting to cross the port .

[0042] Predicted time period The predicted time period can be obtained by summing up the number of vehicles on all congested sections of all roads leading into the port. Total number of vehicles waiting to cross the port : (5); in, and These represent the forecast periods. The number of small passenger cars and large vehicles waiting to be ferryed at the port.

[0043] The dynamic analysis model for waiting vehicles in this application (step 2) achieves accurate estimation of waiting vehicles at the port by considering road congestion status, length of congested road sections, number of lanes, proportion of different types of vehicles, and vehicle spacing under different congestion conditions.

[0044] Step 3: Calculate the average waiting time for vehicles based on the total number of vehicles waiting to cross the port during the predicted period.

[0045] Forecast period The estimated total number of vehicles waiting to cross the river at the port is: The average waiting time for vehicles It can be approximated as: (6); in The denominator represents the rated vehicle carrying capacity of each vessel; It represents the average loading capacity of a ship per unit of time.

[0046] Step 4: Determine whether to trigger the decision to add more ships based on the average vehicle waiting time.

[0047] After estimating the number of vehicles waiting to cross, the ship schedules are dynamically scheduled based on ship capacity and vehicle waiting time thresholds. The core objective of step 4 in this application is to determine whether vehicles waiting to cross can be loaded onto the planned ships in a timely manner within a predicted future period. If waiting times exceed the threshold, the process is as follows: The risk of a short period of time triggers the decision to add more ships.

[0048] Specifically, if the average waiting time of vehicles This indicates that the vehicle can be delivered within an acceptable timeframe ( If loading is completed within (hours), in this case, it is not necessary to trigger a decision to add another vessel. This indicates that some vehicles will have to wait for a long time, and the number of vehicles waiting to be ferryed at the port exceeds the waiting time. The risk is high, and in such cases, a decision to add more vessels needs to be made.

[0049] Step 5: When the decision to add more ships is triggered, calculate the required number of new ships based on the total number of vehicles waiting to cross the port during the forecast period and the port's shipping capacity.

[0050] During the forecast period First, calculate the total carrying capacity available from the planned vessels: (7); in For each ship Rated vehicle carrying capacity; For the prediction period All ships inside The planned number of flights. That is, the prediction period Port shipping capacity within the country.

[0051] Then Compared with the predicted total number of vehicles waiting to cross the port If a comparison is made, This indicates that the existing schedule can meet transportation demand, and no new ships are needed; if This indicates a capacity shortage, and the number of vehicles needed to fill the gap is calculated using the following formula: (8); in, For the prediction period The number of vehicles in short supply.

[0052] Based on the number of vehicles in short supply Combined with average single-ship capacity The required number of new ships is calculated using the following formula. : (9).

[0053] This application establishes a matching mechanism between port waiting vehicles and vessel capacity based on the estimated total number of vehicles waiting to cross the port output from step 2. The predicted total number of port waiting vehicles will be used for this purpose. Matching with the capacity parameters of passenger and roll-on / roll-off vessels currently in port or about to arrive (including maximum number of vehicles, cabin structure, loading and unloading efficiency, etc.), specifically with the total planned vessel capacity. A comparison is made to determine if there is a capacity shortage. When a capacity gap exists, the number of vehicles needed and the number of additional vessels required are calculated promptly. .

[0054] Step 6: Optimize the ship scheduling plan based on the number of newly added ships, and manage and schedule the ships.

[0055] The purpose of this application is to address the problems in the current cross-sea passenger and vehicle ferry scheduling, such as poor real-time statistics of waiting vehicles, scattered data sources, insufficient linkage with external road traffic, and reliance on human experience for scheduling decisions. This application collects real-time traffic data (such as information on congested sections and congestion status) of roads leading to the port provided by open-source map APIs, and combines it with port vessel scheduling data (such as vessel capacity and schedules) to achieve dynamic estimation of the number of waiting vehicles and optimization suggestions for vessel departure times. This improves the responsiveness, scientific nature, and efficiency of transportation organization, reduces vehicle congestion and road congestion, enhances the passenger travel experience, and provides reliable technical support for intelligent port management and water-land coordinated transportation.

[0056] After optimizing the vessel scheduling plan based on the number of new vessels, the scheduling plan is released and coordinated: the optimized vessel scheduling plan, including the number of new vessels, is then implemented. Departure time and loading ratio ( and The data is output to the port dispatch system and linked with the ticketing reservation system to update schedule information in a timely manner, pushing the latest ship departure arrangements to passengers and drivers. It is important to note that the departure of new ships should not disrupt the normal schedule; instead, they should be flexibly integrated into reasonable time slots to avoid impacting the existing timetable. The port dispatch system can provide the optimal departure time for new ships based on the port's available vessel pool and berth conditions, thereby achieving capacity balance and reducing vehicle waiting times.

[0057] Furthermore, operational effectiveness can be evaluated and feedback can be provided: after ships execute the scheduling plan, the port scheduling system tracks the arrival and boarding of vehicles in real time, evaluates vehicle waiting time, changes in port road congestion and transportation efficiency, and uses the evaluation results as feedback input for subsequent scheduling optimization to achieve closed-loop management.

[0058] Furthermore, it also includes the visualization of scheduling results. After completing the dynamic analysis of waiting vehicles and the optimization of ship scheduling, the results can be visualized and output for decision support, including the following: based on the real-time traffic conditions and prediction results of the roads leading to the port, outputting the curve of the number of waiting vehicles, the vehicle queuing trend, and the distribution of different types of vehicles, and dynamically marking the road congestion status and the port entry pressure index on the map interface.

[0059] This application proposes a method for scheduling cross-sea passenger / roll-on / roll-off (Ro-Ro) transport vessels. Based on open-source map data, it assists in the scheduling of these vessels by comprehensively integrating and deeply mining real-time traffic big data provided by open-source maps. Combined with vessel capacity parameters and scheduling optimization decisions, it achieves scientific, accurate, and efficient scheduling of cross-sea passenger / roll-on / roll-off (Ro-Ro) transport vessels. This method not only optimizes the scheduling process and improves the utilization efficiency of vessel capacity, but also significantly enhances the real-time performance and reliability of the scheduling scheme, providing strong support for the safety and smooth operation of cross-sea passenger / roll-on / roll-off transport.

[0060] This application significantly improves the comprehensiveness and scientific rigor of monitoring vehicles waiting to cross the border. By accessing multi-dimensional traffic data provided by open-source map APIs, including road congestion status, traffic flow, and the proportion of different vehicle types, it can perceive the congestion situation on roads surrounding the port area and the number of vehicles entering the port in real time. Compared to traditional methods that rely on ticketing data or manual statistics, this application provides broader data coverage and a higher update frequency, enabling timely reflection of vehicle aggregation during peak holiday periods and emergencies, thus providing scientific data support for dispatching.

[0061] This application improves the accuracy and rationality of scheduling by integrating traffic data with shipping capacity. By comparing the number of vehicles waiting to board with the total shipping capacity over a future period, this application can predict the average waiting time for vehicles and determine if there is a risk of insufficient capacity. When the prediction shows that the waiting time exceeds a set threshold, it automatically calculates the additional capacity demand, determines the number of additional ships needed and the appropriate timing for adding extra services, thereby avoiding large-scale vehicle congestion. This method overcomes the shortcomings of traditional scheduling methods that rely on experience and static rules, significantly improving the scientific rigor and rationality of scheduling.

[0062] This application optimizes scheduling by fully considering the dual objectives of capacity balance and operational stability. When adding new vessels, this application not only determines the number based on capacity gaps but also ensures that the existing flight schedules are not disrupted, thus achieving a balance between scheduling flexibility and stability. The scheduling scheme can quickly respond to sudden congestion while maintaining the orderliness and operability of route operations, ensuring efficient and stable transportation organization.

[0063] This application also establishes a data-driven closed-loop scheduling mechanism. Through visualization of scheduling results and the release and execution feedback of vessel capacity scheduling plans, scheduling strategies can be continuously optimized, achieving closed-loop management throughout the entire process of data acquisition, analysis and prediction, decision optimization, and execution evaluation. This mechanism promotes cross-sea passenger and vehicle roll-on / roll-off (Ro-Ro) transportation from the traditional "experience-based scheduling" to a new model of "real-time perception and intelligent decision-making," significantly improving the intelligence level of transportation organization.

[0064] The method presented in this application has broad applicability and scalability. Because it is based on open-source map data, it avoids reliance on high-cost monitoring equipment. This method is low-cost, quick to deploy, and highly scalable, making it particularly suitable for typical scenarios with high pressure on cross-sea passenger and vehicle ferry transportation, such as the Qiongzhou Strait. It can also be extended to the scheduling and management of passenger and vehicle ferry transportation in other cross-sea channels or ports, thus possessing significant practical significance and application value.

[0065] In summary, the cross-sea passenger / roll-on / roll-off (Ro-Ro) vessel scheduling method proposed in this application, based on open-source map data, fully leverages the real-time and wide-area perception advantages of open-source map big data. Combined with vessel capacity estimation and scheduling optimization strategies, it achieves a scientific, real-time, and efficient scheduling process. This method not only improves the accuracy, rationality, and reliability of waiting vehicle monitoring and capacity matching but also provides a solid technical guarantee for the safety and smooth operation of cross-sea Ro-Ro passenger / roll-off transportation, demonstrating outstanding innovation and broad application prospects.

[0066] In one exemplary embodiment, this application also provides a computer device, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface, and a communication interface. The processor, memory, and input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the aforementioned cross-sea passenger / roll-off transport vessel scheduling method.

[0067] In one exemplary embodiment, this application also provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the aforementioned cross-sea passenger roll-on / roll-off transport vessel scheduling method.

[0068] In one exemplary embodiment, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned cross-sea passenger and roll-on / roll-off transport vessel scheduling method.

[0069] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by hardware related to computer program instructions. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any reference to memory or other media in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0070] It should be noted that the information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0071] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0072] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels, characterized in that, include: Basic information and real-time traffic data of access roads to the port are collected based on open-source map APIs and used as open-source map data. The basic information of access roads to the port includes the road name, location and number of lanes of each access road. The real-time traffic data includes congested sections, congestion status and the proportion of different types of vehicles on each access road. The total number of vehicles waiting to cross the port during the predicted period is calculated based on open-source map data. The average waiting time for vehicles is calculated based on the total number of vehicles waiting to cross the port during the predicted period. The decision to add more ships is determined based on the average waiting time of vehicles. When the decision to add more vessels is triggered, the required number of new vessels is calculated based on the total number of vehicles waiting to cross at the port and the port's vessel capacity during the forecast period. Based on the increase in the number of ships, the ship scheduling plan is optimized, and the ships are managed and scheduled.

2. The method for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels according to claim 1, characterized in that, The calculation of the total number of vehicles waiting to cross the port within a predicted time period based on open-source map data specifically includes: The average vehicle length is calculated based on the proportion of different vehicle types; different vehicle types include small passenger cars and large vehicles. Determine vehicle spacing based on congestion levels; The average length occupied by each vehicle on the road is calculated based on the average vehicle length and vehicle spacing. The total number of vehicles that can be accommodated in a congested section is calculated based on the length of the congested section and the number of lanes of each access road, as well as the average length occupied by each vehicle on the road. Predicted time period The total capacity of all congested sections of all access roads to the port is summed to obtain the predicted time period. Total number of vehicles waiting to cross the port .

3. The method for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels according to claim 2, characterized in that, The calculation of average vehicle length based on the proportion of different vehicle types specifically includes: Using formula Calculate the average vehicle length ;in and The ratios of small passenger cars and large vehicles are respectively. ; and These are the average lengths of small passenger cars and large vehicles, respectively.

4. The method for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels according to claim 3, characterized in that, The calculation of the average length occupied by each vehicle on the road based on the average vehicle length and vehicle spacing specifically includes: Using formula Calculate the average length of road space occupied by each vehicle. ;in For vehicle spacing.

5. The method for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels according to claim 4, characterized in that, The calculation of the total number of vehicles that a congested road segment can accommodate is based on the length of the congested section and the number of lanes on each access road, as well as the average length occupied by each vehicle on the road. Specifically, this includes: Using formula Calculate the first The first on the road into the port Total number of vehicles that can be accommodated in each congested road section ;in Indicates the first The first on the road into the port The length of each congested road segment; Indicates the first The number of lanes on the access roads to the port.

6. The method for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels according to claim 2, characterized in that, The calculation of the average waiting time for vehicles based on the total number of vehicles waiting to cross the port during the predicted period specifically includes: Using formula Calculate the average waiting time for vehicles ;in The rated vehicle carrying capacity of each vessel; It represents the average loading capacity of a ship per unit of time.

7. The method for scheduling cross-sea passenger and roll-on / roll-off (Ro-Ro) transport vessels according to claim 2, characterized in that, The calculation of the required number of new vessels based on the total number of vehicles waiting to cross the port and the port's vessel capacity during the predicted period specifically includes: Using formula Calculate the forecast period Port shipping capacity ;in For each ship Rated vehicle carrying capacity; For the prediction period All ships inside The planned number of departures; when When using the formula Calculate the forecast period Number of vehicles in short supply ; Combined with average single-ship capacity Using formula Calculate the required number of new ships .

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the cross-sea passenger roll-on / roll-off transport vessel scheduling method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the cross-sea passenger and roll-on / roll-off transport vessel scheduling method as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the cross-sea passenger and roll-on / roll-off transport vessel scheduling method as described in any one of claims 1 to 7.

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