Automatic wharf bridge crane heavy-in and heavy-out operation scheduling method and system, terminal and medium

Abstract

The invention relates to an automatic wharf bridge crane heavy-in and heavy-out scheduling method and system, a terminal and a medium, and belongs to the field of automatic container wharf loading and unloading operation, and the method comprises the steps: S1, obtaining operation data, and judging whether an operation point activates a bridge crane heavy-in and heavy-out operation mode or not; s2, calculating the predicted operation time of the operation queue in the state of activating the bridge crane heavy-in and heavy-out operation mode; s3, according to the predicted operation time in the step S2, adjusting the scheduling number and the distribution opportunity of the automated guided vehicle; s4, after the automatic guide transport vehicle arrives at the bridge crane operation area, whether the transport vehicle needs to be locked or not is judged according to whether the current operation point is in a heavy-in and heavy-out state or not, and a ship unloading task continues to be distributed or not; and S5, after the operation is completed, the automatic guide transport vehicle completes the ship unloading task according to the distribution instruction, and returns to the scheduling system to wait for new task distribution. The method effectively breaks through the limitation that the bridge crane can only execute a single-direction task in traditional wharf operation, and the waiting time of the bridge crane in the loading and unloading conversion process is shortened.

Description

Automated Terminal Crane Re-entry and Re-exit Operation Scheduling Methods, Systems, Terminals, and Media Technical Field

[0001] This invention belongs to the field of automated container terminal loading and unloading operations, specifically involving automated terminal quay crane re-entry and re-exit operation scheduling methods, systems, terminals and media. Background Technology

[0002] With the rapid growth of global container shipping, port automation technology is increasingly becoming an important development direction for improving terminal loading and unloading efficiency and reducing operating costs. In the operation system of automated terminals, quay cranes, as key loading and unloading equipment, directly affect the overall operation cycle through their operational scheduling efficiency. At the same time, automated guided vehicles (AGVs), as the main equipment for short-haul container transportation within the terminal, also play a crucial role in the efficient coordination between AGVs and quay cranes, becoming a key factor affecting port throughput.

[0003] In existing automated terminal scheduling systems, quay cranes typically perform tasks in a traditional "one-way operation" mode, i.e., unloading before loading or vice versa. The order of operations depends on fixed queues divided by ship compartments, and automated guided vehicles (AGVs) perform transport tasks in one direction based on the status of the quay cranes. Existing systems mainly focus on optimizing loading and unloading sequences and minimizing equipment paths, but they lack a unified scheduling strategy for repeated operations of quay cranes within the same compartment (i.e., re-entry and re-exit).

[0004] Current scheduling systems lack a targeted scheduling mechanism when faced with the need for gantry cranes to continuously perform bidirectional operations at the same location (such as immediately performing an unloading operation after completing a loading task). The main problems are as follows: First, the operating system cannot determine in real time whether the "re-entry and re-exit" conditions between tasks meet, resulting in prolonged waiting times for gantry cranes; second, the estimated operation time lacks dynamic modeling of compartment status, equipment performance, and environmental factors, leading to low prediction accuracy and impacting scheduling efficiency; third, the scheduling of transport vehicle resources relies on static rules, resulting in low resource utilization. Summary of the Invention

[0005] This invention addresses the problems in the prior art by providing an automated method, system, terminal, and medium for scheduling the re-entry and re-exit operations of quay cranes at wharves. It solves the problems caused by the traditional "one-way operation" mode used in the prior art, which results in long vessel stay times in port and low utilization time of quay cranes and other equipment during loading and unloading operations.

[0006] The technical solution adopted by this invention is as follows: Firstly, this application provides an automated terminal quay crane re-entry and re-exit operation scheduling method, comprising the following steps: Step S1: Obtain operation data, and determine whether the operation point has activated the quay crane re-entry and re-exit operation mode based on the operation data. When the operation sequence numbers of adjacent operation tasks in the operation queue are consecutive and belong to the same ship compartment, the quay crane re-entry and re-exit operation mode is activated; Step S2: Calculate the estimated operation time for the operation queue under the activated quay crane re-entry and re-exit operation mode: For unloading tasks, only instructions where the container position is already within the quay crane's range are retained for time calculation; for loading tasks, all instructions are retained for time calculation. Step S3: Based on the estimated operation time in Step S2, adjust the number of automated guided vehicles (AGVs) and the dispatching timing. Step S4: After the AGV arrives at the gantry crane operation area, determine whether the vehicle needs to be locked and the unloading task needs to be dispatched based on whether the current operation point is in a re-entry / re-exit state. If locking is required, after the current loading task is completed, the AGV will be directly switched to perform the unloading task. If not locked, a task to be dispatched to another gantry crane will be requested to perform a double-cycle task. Step S5: After the operation is completed, the AGV completes the unloading task according to the dispatching instruction and returns to the dispatching system to wait for a new task to be dispatched.

[0007] Furthermore, in step S1, the determination of the continuity of the job sequence number is based on the system-generated number of each task in the job queue, and the job queue is updated in real time according to the ship loading and unloading plan and the task completion status.

[0008] Furthermore, the compartment identification process is based on the spatial identification coding rules of the gantry crane operation area. The spatial identification includes the compartment number, deck / in-cabin markings, and operation category labels. The terminal operating system determines the consistency of the compartments according to these rules.

[0009] Furthermore, in step S2, during the calculation of the estimated operation time for the unloading / loading task, the estimated operation time will be calculated by weighting the data on historical equipment response efficiency, operation bottleneck location, and ship departure time to generate an estimated operation time model.

[0010] Furthermore, the estimated operation time model is calculated by the scheduling system based on a unified operation time. The estimated operation time model includes three parts: baseline operation time, weight correction factor, and additional adjustment time. The baseline operation time is generated based on the terminal's historical operation database and is statistically generated according to the classification of gantry crane equipment, operation type, and location. The weight correction factor is calculated based on cabin congestion, vessel priority, equipment health score, and on-site environmental factors. The additional adjustment time is assessed based on the current operation queue length, the probability of operation interruption, night operation parameters, and equipment handover waiting time.

[0011] Furthermore, before the scheduling system dispatches automated guided vehicles (AGVs) tasks, a set of AGV scheduling priority lists is generated based on the time data output by the expected operation time model. The dynamic adjustment of the number of AGVs to be dispatched is based on the loading and unloading concurrency in the ship operation plan, the current availability rate of the vehicles, and the expected resource bottleneck location, and a fuzzy logic control algorithm is used to determine the dispatch parameters.

[0012] Furthermore, in step S4, the triggering criteria for the dual-loop logic must meet at least one of the following conditions: the current crane task completion rate reaches a preset threshold, the adjacent crane operation load is lower than the scheduling saturation, the transport vehicle has sufficient remaining task capacity, and its task transfer path meets the shortest operation response time requirement.

[0013] Secondly, this application provides an automated terminal quay crane re-entry and re-exit operation scheduling system, including: a terminal operating system, used to manage the status of the operation queue, determine whether the re-entry and re-exit mode activation conditions are met, and complete the scheduling of automated guided vehicles and the dispatch of task instructions; a quay crane management system, used to receive the scheduling results of the terminal operating system, manage the quay crane operation process, and lock or reassign automated guided vehicles according to whether they are in the re-entry and re-exit state; an automated guided vehicle management module, used to respond to operation scheduling instructions and execute loading and unloading tasks, including loading, unloading, or scheduling conversion tasks; the status confirmation between the quay crane management system and the terminal operating system adopts a dual-channel redundancy mechanism for information exchange, including control interface communication and data bus broadcasting.

[0014] Thirdly, this application provides a terminal, comprising: a memory for storing an automated terminal crane re-entry and re-exit operation scheduling program; and a processor for executing the steps of the automated terminal crane re-entry and re-exit operation scheduling method as described in the first aspect when the automated terminal crane re-entry and re-exit operation scheduling system is used.

[0015] Fourthly, this application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the automated terminal crane re-entry and re-exit operation scheduling method as described in the first aspect.

[0016] As can be seen from the above technical solutions, this invention has the following advantages: 1. By constructing an automated terminal gantry crane re-entry and re-exit operation scheduling method, this invention achieves seamless connection between loading and unloading tasks of gantry cranes at the same work point by identifying the continuity of adjacent work tasks and the consistency of cargo compartments in the work queue. This method effectively breaks the limitation of traditional terminal operations where gantry cranes can only perform tasks in one direction, significantly reducing the waiting time of gantry cranes during loading and unloading transitions. At the same time, through intelligent judgment and task transfer mechanisms, automated guided vehicles do not need to travel empty between different work points and can continuously complete bidirectional operations within the same work area, greatly optimizing equipment utilization and work cycle. The system as a whole improves the coordination and response efficiency of automated terminal operations, providing technical support for the evolution of terminal operation systems towards high intelligence.

[0017] 2. By introducing system-generated task numbers as the basis for logical judgment, combined with a real-time update mechanism for the task queue, the system ensures accurate identification of the sequence and physical continuity between tasks in complex and ever-changing port operation scenarios. This guarantees the validity of the basis for determining the crane re-entry and re-exit mode. This mechanism improves the system's ability to perceive dynamic operation states, facilitating scheduling adjustments or priority reconfiguration in emergencies, and enhancing the flexibility and real-time performance of the entire terminal scheduling system. The system automatically maintains the continuity of the task queue based on loading and unloading plans and task progress, eliminating reliance on manual judgment for crane scheduling, reducing human intervention errors, and improving the level of intelligent operation management.

[0018] 3. By introducing a compartment identification scheme based on spatial identifier coding rules, the system can quickly and accurately determine the spatial matching location of the gantry crane operation, covering multi-dimensional elements such as compartment number, deck and compartment operation type identifiers. This method ensures the accuracy of task identification and helps the system accurately identify whether they are the same operation point, thus supporting the logical basis for the continuous operation of the gantry crane in a specific area. Furthermore, this spatial identifier mechanism also provides a spatial hierarchy reference for the operation scheduling algorithm, which can be extended to scenarios such as global operation optimization and gantry crane area balancing configuration, enhancing the system's deployment adaptability and data matching efficiency in complex ship loading and unloading scenarios.

[0019] 4. By employing multi-dimensional weighted modeling of crane operation time, including historical response efficiency, bottleneck identification, and vessel departure countdown factors, the estimated operation time no longer relies on static parameters but can be dynamically adjusted based on actual operating conditions, improving the accuracy of the scheduling system's prediction model. This method fully reflects the impact of the current operating environment on time costs, effectively enhancing the scientific judgment of the timing and quantity of transport equipment dispatch, thereby achieving reasonable control of the operation rhythm and maximizing resource allocation.

[0020] 5. A unified operation time prediction model integrates the scheduling time calculation logic of gantry crane loading and unloading operations. It introduces a three-layer structure of baseline operation time, weight correction factor, and additional adjustment time, effectively overcoming the shortcomings of traditional methods such as fragmented prediction models and poor adaptability. This model can take into account factors such as inherent equipment performance, changes in the site environment, and dynamic changes in queues, providing highly robust prediction capabilities in complex operation scenarios. The scheduling system can use this model to achieve efficient coordination between the scheduling rhythm of transport vehicles and the gantry crane cycle time, thereby improving the flexibility and responsiveness of the entire terminal operation system during operation.

[0021] 6. This method dynamically optimizes the task assignment of automated guided vehicles (AGVs) by introducing a scheduling priority list and fuzzy logic control algorithm. It no longer relies on static paths or fixed priority rules, significantly improving scheduling flexibility and resource response speed. Based on the predicted operation time output, the system ranks the response capabilities of currently available vehicles in real time, combining vehicle status, path complexity, and expected energy consumption to achieve optimal scheduling path matching. This scheduling mechanism not only reduces the idle time of transportation equipment but also avoids congestion in the work area caused by excessive concentrated vehicle dispatch, thereby improving the overall operational efficiency and intelligent resource scheduling of the terminal.

[0022] 7. This invention establishes a multi-dimensional condition triggering mechanism to determine whether to initiate a dual-cycle operation mode. This allows the scheduling system to make logical judgments based on real-time workload, crane resource saturation, and transport vehicle status, effectively enhancing the flexibility and intelligence of the system's scheduling path. In particular, after a transport vehicle completes its task, it can directly switch to a new task without leaving the current work area, significantly reducing equipment idle time and waiting time. Furthermore, this mechanism can automatically switch to inter-crane task coordination based on changes in the operational scenario, achieving a rebalancing of regional load scheduling and improving the operational stability of automated terminals during peak periods or under abnormal conditions.

[0023] 8. The system described in this invention integrates a terminal operating system, a gantry crane management system, and a transport vehicle management module to construct an intelligent scheduling closed-loop structure covering the entire process of task judgment, status confirmation, task distribution, and operation execution. The system employs a dual-channel redundant communication mechanism to ensure high reliability and low latency in status synchronization between the gantry cranes and transport equipment. Even in cases of network instability or data channel anomalies, it ensures uninterrupted operation, enhancing the industrial-grade stability of the scheduling system. This system architecture is suitable for deployment in highly automated port environments, possessing high scalability and adaptability, and is a crucial component of a smart terminal infrastructure platform. Attached Figure Description

[0024] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 is a flowchart illustrating the method in a specific embodiment of the present invention. Detailed Implementation

[0026] Various embodiments of this disclosure will be described more fully in the following detailed description. This disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of this disclosure to the specific embodiments disclosed herein, but rather this disclosure should be understood to cover all adjustments, equivalents, and / or alternatives falling within the spirit and scope of the various embodiments of this disclosure.

[0027] The following are explanations of some terms used in this plan to facilitate better understanding: 1. Quay Crane: A quay crane (also known as a port quay crane or container quay crane) is a piece of equipment specifically designed for port ship loading and unloading operations. It is typically located on the dock and used for loading and unloading containers or other cargo between ships and the dock. Quay cranes use their booms, cranes, and other components to lift containers from the ship and transport them to the quay, or to transfer cargo from the quay to the ship. The height and span of quay cranes are usually sufficient to cover the decks of modern large container ships, and they are widely used in large-scale cargo transshipment operations.

[0028] 2. Automated Guided Vehicles (AGVs): AGVs are unmanned transport devices that rely on a computer control system and various guidance methods such as ground navigation, visual recognition, lidar, magnetic stripes, and electromagnetic fields to achieve autonomous driving. They are widely used in intelligent manufacturing, warehousing and logistics, and automated terminals. In automated terminals, AGVs mainly undertake short-distance container transport tasks between ships and shore or between container yards, and are one of the key pieces of equipment for ports to achieve efficient, flexible, and unmanned operation processes.

[0029] AGVs offer significant advantages such as driverless operation, automatic path navigation, automatic obstacle avoidance, and rapid task scheduling response. Their navigation systems are typically based on LiDAR, inertial navigation, visual navigation, or multi-sensor fusion navigation technology. Combined with a back-end scheduling system, they can achieve functions such as path planning, queue scheduling, collaborative obstacle avoidance, and dynamic scheduling. Most dockside AGVs are heavy-duty designs, capable of carrying one or two standard containers. Their body structure typically employs a low-flatbed design, facilitating seamless docking with quay cranes, rail-mounted gantry cranes, and other loading and unloading equipment.

[0030] In modern port automation systems, AGV operation is coordinated and scheduled by the Terminal Operating System (TOS) and linked with the Quay Crane Management System (QCMS) and Yard Control System (YMS) to achieve an automated closed-loop container handling workflow. Through real-time linkage with information such as work tasks, equipment status, work priorities, and energy consumption management, AGVs not only improve terminal transportation efficiency but also effectively reduce labor costs and transportation risks, making them an indispensable core piece of equipment for building smart and green ports.

[0031] Example 1: This invention addresses the problems in the prior art by providing an automated terminal crane re-entry and re-exit operation scheduling method, as shown in Figure 1. The method includes the following steps: Step S1: Obtain operation data. Based on the operation data, determine whether the operation point is in the crane re-entry and re-exit operation mode. When adjacent operation tasks in the operation queue have consecutive operation numbers and belong to the same vessel compartment, the crane re-entry and re-exit operation mode is activated. In this example, the terminal operating system obtains the operation queue information for the current operation point from the database. The operation data includes the operation number, the vessel to which it belongs, the compartment number, the operation type (loading or unloading), and the operation priority. The system first sorts the operation numbers of adjacent operation tasks, determines whether the numbers are in a continuous increasing relationship, and simultaneously extracts the vessel number and compartment identifier corresponding to the task. If all the above tasks point to the same vessel and the compartment numbers are consistent, the system confirms that the current operation point meets the crane re-entry and re-exit activation conditions. Subsequently, the "Whether to enable re-entry and re-exit mode" field of the work point status is set to the enabled state, and the "Re-entry and re-exit is possible" indicator is displayed synchronously on the system front end or the gantry crane operation interface. The gantry crane management system (QCMS) receives the synchronization status and realizes the equipment logic switching preparation. Step S2: Calculate the estimated operation time for the work queue under the activated gantry crane re-entry and re-exit operation mode: For unloading tasks, only the instructions where the container position is already within the range of the gantry crane are retained for time calculation; for loading tasks, all instructions are retained for calculation. In the specific implementation process, the system first determines the type of each task in the current work queue. For unloading tasks, the system filters the operation instructions from the task list that the container has been lifted to the gantry crane gantry or platform area, including but not limited to container information at key nodes such as the gantry trolley, sea-side platform, land-side platform, and main trolley. Only this type of task is retained for time estimation to avoid considering the impact of containers that have not yet entered the operation area on scheduling. For loading tasks, since all instructions are theoretically operable, the system directly incorporates the entire work queue into the estimated time model for total duration evaluation. The estimated operation time will be used to control the frequency and number of subsequent transport vehicle dispatches, ensuring that resource allocation matches the operational rhythm. Step S3: Based on the estimated operation time from step S2, adjust the number of AGVs and their dispatch timing. The system dynamically adjusts the number of AGVs and their task start times based on the estimated operation time calculated in step S2, combined with the ship's planned completion time and the dock's operational progress control strategy. The system uses a fuzzy control algorithm to comprehensively consider factors such as the current AGV availability rate, equipment response speed, and work area congestion index to generate the optimal scheduling strategy. Simultaneously, a task priority list is generated based on the current location and status of each transport vehicle (empty / loaded, battery level, task completion time). Transport vehicles with high responsiveness are prioritized for task allocation to reduce path waiting time and system latency.All dispatched tasks are scheduled with the shortest possible response time as the constraint to improve resource utilization efficiency. In step S4, after the automated guided vehicle (AGV) arrives at the gantry crane operating area, the system determines whether to lock the vehicle and continue dispatching unloading tasks based on whether the current operating point is in a re-entry / re-exit state. If locking is required, after the current loading task is completed, the AGV will directly switch to unloading tasks. If not locked, it requests tasks from other gantry cranes to execute a double-loop task. When the vehicle arrives at the gantry crane interaction area, the system immediately triggers a status verification logic to read whether the current operating point is in an active re-entry / re-exit mode. If yes, the system sets the vehicle to a locked state and marks it as "task waiting," preventing it from automatically leaving the operating area. After the current loading task is completed, the vehicle automatically receives an unloading task matching its location and continues operation, achieving seamless connection of gantry crane operations. If the re-entry / re-exit mode is not activated at the work site, the system includes the transport vehicle in the dual-cycle scheduling logic and requests from adjacent gantry cranes if there are any unfinished unloading tasks. If the dual-cycle trigger conditions are met, the system immediately reassigns the task, realizing the lateral redistribution of the workload and preventing the equipment from returning to the yard empty. Step S5: After the operation is completed, the automated guided transport vehicle completes the unloading task according to the dispatch instruction and returns to the scheduling system to wait for new task assignment. In this step, after the transport vehicle completes the current gantry crane operation, it synchronizes the unloading completion status to the terminal operating system through the scheduling system. The system confirms the completion of the operation and clears the locked status or dual-cycle status flag. The transport vehicle enters the "idle" state and automatically navigates to the designated standby area to wait for subsequent task assignment. During this process, the system reorders the transport vehicle based on parameters such as the current remaining power, running time, and real-time path load of the work area to optimize the next round of task assignment order and ensure smooth system operation.

[0032] In this embodiment, in step S1, the determination of the continuous operation sequence number is based on the system-generated number of each task in the operation queue. The operation queue is updated in real time according to the ship loading and unloading plan and the task completion status. During system implementation, the TOS system generates an initial operation queue according to the ship loading and unloading plan and assigns a unique task number to each operation task. The task completion status is fed back in real time by QCMS or YMS. The system sorts the queue in ascending order of the number, identifies logically continuous task combinations, and removes completed tasks in real time according to the task completion mark, maintaining the real-time performance and integrity of the operation queue and ensuring that the judgment basis for the crane re-entry and re-exit mode is always valid.

[0033] In this embodiment, the compartment identification process is based on the spatial identification coding rules of the gantry crane operation area. The spatial identification includes the compartment number, deck / in-cabin markings, and operation category labels. The terminal operating system determines the compartment consistency according to these rules. The system presets spatial identification coding rules, for example, each operation point is configured with a unique "ship number-compartment number-level label" triplet identifier. When the scheduling system determines whether the gantry crane has entered a re-entry / re-exit state, it verifies the compartment consistency based on this code. Only when the spatial identifiers of the operation tasks are completely consistent does the system confirm that they belong to the same operation area and allow the re-entry / re-exit logic to be entered, ensuring the spatial accuracy of the scheduling decision.

[0034] In this embodiment, during step S2, the estimated operation time for unloading / loading tasks is calculated by weighting historical equipment response efficiency, bottleneck location, and ship departure time data to generate an estimated operation time model. The estimated operation time calculation adopts a three-stage modeling method. The first stage extracts the historical average single-box time of the gantry crane under the same type of operation from the database. The second stage collects the bottleneck nodes at the current operation site (such as AGV waiting time and gantry crane lifting frequency drop points). The third stage combines the ship's planned departure time and other time windows to generate an operation time window pressure coefficient. The three stages of data are weighted and summarized as the estimated time output, improving the dynamic adaptability of the time model.

[0035] In this embodiment, the estimated operation time model is calculated by the scheduling system based on a unified operation time. The estimated operation time model includes three parts: baseline operation time, weight correction factor, and additional adjustment time. The baseline operation time is generated based on the terminal's historical operation database and is classified and statistically generated according to the crane equipment, operation type, and location. The weight correction factor is calculated based on the cabin congestion, vessel priority, equipment health score, and on-site environmental factors. The additional adjustment time is assessed based on the current operation queue length, the probability of operation interruption, night operation parameters, and equipment handover waiting time.

[0036] The model is executed by a rule engine embedded in the scheduling system. The baseline operation time can be automatically generated by cleaning historical operation data through a sliding time window, and the weight correction factor is dynamically extracted by the AI ​​learning module from the decision rule parameters. The additional adjustment time module interfaces with the meteorological system, task monitoring module, and crane equipment health module to form a real-time correction logic, realizing the replicability and accuracy of the model's predictive capabilities at different terminal sites.

[0037] In this embodiment, before the scheduling system dispatches automated guided vehicles (AGVs) tasks, a priority list for AGV scheduling is generated based on the time data output by the estimated operation time model. The dynamic adjustment of the number of AGVs to be dispatched is based on the loading / unloading concurrency in the ship's operation plan, the current availability rate of the AGVs, and the expected resource bottleneck location, using a fuzzy logic control algorithm to determine the dispatch parameters. The system generates a priority factor matrix containing current location, running time, reachability score, remaining battery power, and equipment health score based on the status data of each AGV, and sorts them according to a decision function. The availability rate of the AGVs is determined by accessing the entire site's equipment perception system, combined with the ship's concurrent loading / unloading plan, yard equipment scheduling status, and path congestion level obtained from the current TOS system, forming a fuzzy logic input, and outputting the corresponding optimal dispatch quantity and dispatch rhythm. This method enables adaptive optimization of transportation equipment resources, improving the stability and efficiency of the scheduling system in high-concurrency scenarios.

[0038] In this embodiment, in step S4, the triggering criteria for the dual-loop logic include at least one of the following conditions: the current crane task completion rate reaches a preset threshold, the adjacent crane's operating load is below the scheduling saturation, the transport vehicle has sufficient remaining task capacity, and its task transfer path meets the shortest operation response time requirement. The system collects the task completion rate of each crane in real time. When the remaining task of a crane is less than 20% of the total task, the system enters a dual-loop pre-judgment state. Simultaneously, it analyzes the current scheduling resource utilization rate of adjacent cranes. If the load is less than 70% of the maximum schedulable ratio, task transfer is acceptable. Furthermore, if the transport vehicle's status score is not lower than the threshold set by the scheduling system (e.g., above 85 points), and its path transfer can be completed within 30 seconds, then the dual-loop conditions are met, triggering the dispatch of tasks to adjacent cranes, thus improving the system's resource adaptability.

[0039] Example 2: This application provides an automated terminal quay crane re-entry and re-exit operation scheduling system, including: a terminal operating system, used to manage the status of the operation queue, determine whether the re-entry and re-exit mode activation conditions are met, and complete the scheduling of automated guided vehicles and the dispatch of task instructions; in this embodiment, the terminal operating system is deployed on the port area operation main control server, and continuously obtains the current operation status of ships, quay cranes, yards, and transportation equipment by connecting to the ship planning management module and the operation real-time data acquisition module. The system first identifies the status of the operation queue of each quay crane operation point, extracts key fields such as operation number, compartment code, and task type, and makes rule judgments based on whether the operation number is consecutive, whether the ship to which it belongs is consistent, and whether the compartment is uniform. If the quay crane re-entry and re-exit mode trigger conditions are met, the status of the operation point is set to the active state. In this state, the system calls the scheduling engine module to dispatch tasks to AGVs, comprehensively using the estimated operation time model, task priority scoring mechanism, and path conflict avoidance algorithm to perform fine-grained scheduling control of transport vehicles, ensuring that the resource scheduling rhythm is accurately matched with the work load. The gantry crane management system is used to receive the scheduling results of the terminal operating system, manage the gantry crane operation process, and lock or reassign the automated guided vehicles based on whether they are in a re-entry / re-exit state. The gantry crane management system is deployed on each gantry crane operation terminal or edge control node. The system has functions such as gantry crane status perception, task execution instruction reception, operation process control, and interactive scheduling with transport vehicles. When the terminal operating system issues a scheduling instruction, the gantry crane management system parses the instruction content and identifies whether the current gantry crane operation point is in a re-entry / re-exit active state. If "yes", the system locks the transport vehicle currently in the operation area, meaning that the transport vehicle will not return to the yard after completing the current task, but will remain in the operation area to wait for the next instruction (unloading or loading task). If not inactive, the system will report to the terminal operating system that the gantry crane is in normal scheduling mode. After completing its task, the transport vehicle will enter the scheduling standby queue or execute a double-cycle dispatch. The automated guided vehicle (AGV) management module is used to respond to work scheduling instructions and execute loading and unloading tasks, including loading onto ships, unloading from ships, or scheduling conversion tasks. The AGV management module is connected to the core platform of the scheduling system or deployed inside the transport vehicle control host, mainly realizing functions such as receiving scheduling tasks, path planning, task execution, and status feedback. After receiving the work scheduling instruction, the module uses the specified gantry crane number, task type (loading / unloading), target yard or container number, etc., to call the autonomous navigation algorithm to calculate the optimal driving path and control the transport vehicle to the designated work area. When the transport vehicle arrives at the gantry crane interaction area, the management module automatically establishes a communication link with the gantry crane management system and determines the subsequent task flow path based on the work mode confirmation result.During task execution, the system records vehicle trajectory, loading / unloading status, and time data in real time and reports them to the dispatching system to support subsequent dispatching strategy optimization. The status confirmation between the crane management system and the terminal operating system employs a dual-channel redundancy mechanism for information exchange, including control interface communication and data bus broadcasting. To improve system stability and communication reliability, the information exchange between the crane management system and the terminal operating system uses a dual-channel redundancy mechanism. The first channel is a standard industrial control communication interface (such as Ethernet TCP / IP or Industrial Ethernet Profinet) for point-to-point interaction of structured data commands, such as operation activation status, lock control signals, and dispatch response confirmation. The second channel is a field data broadcasting channel (such as based on CAN bus, RS485, or industrial wireless broadcasting protocols) for low-latency, multi-device synchronous information broadcasting, such as operation status updates, emergency stop, and dispatch switching signals. The two channels are redundant backups of each other, ensuring that if one channel fails, the other can automatically take over the task, guaranteeing the security of task control and uninterrupted operation under high load and complex network environments.

[0040] Example 3: This application provides a terminal, including: a memory for storing an automated terminal crane re-entry and re-exit operation scheduling program; and a processor for executing the steps of the automated terminal crane re-entry and re-exit operation scheduling method as described in Example 1 when the automated terminal crane re-entry and re-exit operation scheduling system is used.

[0041] Example 4: This application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the automated terminal crane re-entry and re-exit operation scheduling method as described in Example 1.

[0042] It is understood that the systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer, which can be a personal computer, a laptop computer, a personal digital assistant, a tablet computer, a wearable device, or any combination of these devices.

[0043] In a typical configuration, a computer includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0044] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0045] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage, quantum memory, graphene-based storage media or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0046] It should be noted that the user 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. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0047] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0048] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0049] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of one or more embodiments of this specification. The singular forms “a,” “described,” and “the” used in one or more embodiments of this specification and in the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0050] It should be understood that although the terms first, second, third, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first information may also be referred to as second information without departing from the scope of one or more embodiments of this specification, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "in response to a determination," or "when," or "in the event of a determination."

[0051] The above description is merely a preferred embodiment of one or more embodiments of this specification and is not intended to limit the scope of one or more embodiments of this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of one or more embodiments of this specification should be included within the protection scope of one or more embodiments of this specification.

Claims

1. A method for scheduling the re-entry and re-exit operations of quay cranes at an automated terminal, characterized in that: Includes the following steps: Step S1: Obtain operation data and determine whether the work point is in the gantry crane re-entry / re-exit operation mode based on the operation data. When the operation sequence numbers of adjacent tasks in the operation queue are consecutive and belong to the same ship compartment, the gantry crane re-entry / re-exit operation mode is activated. Step S2: Calculate the estimated operation time for the operation queue in the gantry crane re-entry / re-exit operation mode: For unloading tasks, only the instructions that the container position is within the range of the gantry crane are retained for time calculation; for loading tasks, all instructions are retained for calculation. Step S3: Adjust the scheduling quantity and dispatch timing of the automated guided vehicles (AGVs) based on the estimated operation time in Step S2. Step S4: After the AGV arrives at the gantry crane operation area, determine whether the vehicle needs to be locked and the unloading task should continue to be dispatched based on whether the current work point is in the re-entry / re-exit state. If locking is required, the automated guided vehicle will be directly switched to unloading after the current loading task is completed; if not locked, it will request to be assigned to other gantry cranes and perform a double cycle task; Step S5: After the operation is completed, the automated guided vehicle will complete the unloading task according to the assignment instruction and return to the dispatch system to wait for a new task assignment.

2. The automated terminal crane re-entry and re-exit operation scheduling method according to claim 1, characterized in that, In step S1, the determination of the continuity of the job sequence number is based on the system-generated number of each task in the job queue, and the job queue is updated in real time according to the ship loading and unloading plan and the task completion status.

3. The automated terminal crane re-entry and re-exit operation scheduling method according to claim 2, characterized in that, The compartment identification process is based on the spatial identification coding rules of the gantry crane operation area. The spatial identification includes the compartment number, deck / inside markings and operation category labels. The terminal operating system determines the consistency of the compartments according to these rules.

4. The automated terminal crane re-entry and re-exit operation scheduling method according to claim 1, characterized in that, In step S2, during the calculation of the estimated operation time for the unloading / loading task, the estimated operation time will be calculated by weighting the data on historical equipment response efficiency, operation bottleneck location, and ship departure time to generate an estimated operation time model.

5. The automated terminal crane re-entry and re-exit operation scheduling method according to claim 4, characterized in that, The estimated operation time model is calculated by the scheduling system based on a unified operation time. The estimated operation time model includes three parts: baseline operation time, weight correction factor, and additional adjustment time. The baseline operation time is generated based on the terminal's historical operation database and is classified and statistically generated according to the gantry crane equipment, operation type, and location. The weighting adjustment factor is calculated based on compartment congestion, vessel priority, equipment health score, and on-site environmental factors; the additional adjustment time is assessed based on the current work queue length, the probability of work interruption, nighttime work parameters, and equipment handover waiting time.

6. The automated terminal crane re-entry and re-exit operation scheduling method according to claim 5, characterized in that, Before the scheduling system dispatches automated guided vehicles (AGVs) tasks, a priority list of AGVs is generated based on the time data output by the expected operation time model. The dynamic adjustment of the number of AGVs dispatched is based on the loading and unloading concurrency in the ship operation plan, the current availability rate of the vehicles, and the expected resource bottleneck location. The dispatch parameters are determined by a fuzzy logic control algorithm.

7. The automated terminal crane re-entry and re-exit operation scheduling method according to claim 1, characterized in that, In step S4, the triggering criteria for the dual-loop logic must meet at least one of the following conditions: the current crane task completion rate reaches a preset threshold, the adjacent crane operation load is lower than the scheduling saturation, the transport vehicle has sufficient remaining task capacity, and its task transfer path meets the shortest operation response time requirement.

8. An automated terminal crane re-entry and re-exit operation scheduling system, characterized in that, include: The dock operating system is used to manage the status of the work queue, determine whether the conditions for activating the re-entry and re-exit mode are met, and complete the scheduling of automated guided vehicles and the dispatch of task instructions. The gantry crane management system receives scheduling results from the terminal operating system, manages the gantry crane operation process, and locks or reassigns automated guided vehicles (AGVs) based on whether they are in a re-entry / re-exit state. The AGV management module responds to operation scheduling instructions and executes loading and unloading tasks, including loading onto ships, unloading from ships, or scheduling conversion tasks. The status confirmation between the gantry crane management system and the terminal operating system adopts a dual-channel redundancy mechanism for information exchange, including control interface communication and data bus broadcasting.

9. A terminal, characterized in that, include: The memory is used to store the scheduling program for the re-entry and re-exit operations of the automated terminal cranes; A processor is used to implement the steps of the automated terminal crane re-entry and re-exit operation scheduling method as described in any one of claims 1-7 when executing the automated terminal crane re-entry and re-exit operation scheduling system.

10. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions. When the computer reads the computer instructions in the storage medium, the computer executes the automated terminal crane re-entry and re-exit operation scheduling method as described in any one of claims 1 to 7.

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