Unmanned ship parallel driving system and method based on 5G remote driving cabin and unmanned ship

Abstract

The application discloses a 5G remote cabin-based unmanned ship parallel driving system and method and an unmanned ship, and relates to the technical field of automatic driving communication and control. The system comprises a ship-end data quantization module, a ship-end data transmission timeliness regulation module and a cabin-end data reception real-time regulation module. The application obtains a ship-end data transmission delay index by collecting ship-end data and judges whether to perform ship-end data transmission timeliness regulation, obtains a cabin-end data reception delay parameter to obtain a cabin-end data reception delay gradient index and judges whether to perform cabin-end data reception real-time regulation, thereby improving the real-time performance of the unmanned ship parallel driving, and solving the problem of low real-time performance of the unmanned ship parallel driving caused by communication link delay accumulation in the prior art.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving communication and control technology, and in particular to a parallel driving system, method and unmanned vessel based on a 5G remote cockpit. Background Technology

[0002] Before startup, the unmanned surface vessel (USV) undergoes a comprehensive self-check, and only after passing the self-check is it officially launched. Once launched, the USV uses its 5G network communication module to quickly and stably transmit its current spatiotemporal data (including position, speed, and heading) to the shore-based ground station command system. Simultaneously, on the shore-based ground station command system side, operators set target nodes and return points for the USV and select the control decision mode through the control decision module, then transmit this setting information to the USV via the 5G network communication module. After receiving the data from the shore-based ground station command system, the USV's intelligent navigation module acquires the next moment's spatiotemporal data and combines it with offline electronic nautical chart data to fuse the data collected by the sensor modules, thereby constructing and updating the aquatic environment model.

[0003] After obtaining the optimal navigation route calculated by the intelligent navigation module, the motion of the unmanned surface vessel (USV) is controlled using a PID (Proportional-Integral-Derivative) control method based on an improved Line of Sight (LOS) system. This optimizes heading and speed control, enabling precise tracking of the USV's path and achieving autonomous navigation control. During navigation, the USV calculates its safe distance based on real-time LiDAR scanning information. If other vessels maintain a safe distance or the water conditions are passable, the USV continues along its original navigation path. If the distance between the USV and other vessels is less than the safe distance or the water conditions are impassable, the intelligent navigation module quickly formulates an obstacle avoidance route and instructs the motion control module to execute it immediately. If an obstacle avoidance route cannot be formulated in time, the USV will trigger an emergency obstacle avoidance function, immediately braking or reversing its movement to perform an emergency avoidance maneuver. Furthermore, in emergency situations, the shore-based ground station command system can take over control of the USV, allowing manual operation to complete the obstacle avoidance maneuver.

[0004] For example, the integrated autonomous driving system for unmanned ships announced in patent application CN110673600B includes: a perception module for sensing the ship's navigation environment and acquiring real-time information on waterways, hydrology, the ship's own status, and traffic environment dynamics; a communication system for transmitting data and commands between the ship and the shore, and between system modules; a data processing module for processing the information acquired by the perception module; a decision-making module for identifying the ship's current operating status and environment based on the data output by the data processing module, selecting the next action to be taken, and generating corresponding operation commands; and an execution module for receiving operation commands from the decision-making module and using a PID controller to control the ship's propellers and rudder to change the ship's motion state.

[0005] For example, patent application CN112947413B discloses an unmanned intelligent debris-collecting vessel, which includes a collection compartment, a power compartment, an engine compartment, a bridge, and a ballast compartment. A water inlet pipe in the ballast compartment controls water from outside the hull to enter the ballast compartment, causing the hull to tilt forward with the water level higher than the bottom of the collection compartment, enabling the vessel to collect debris. The hull is equipped with a dual-system navigation and positioning system, a monitoring device, and a dynamic lidar. A dynamic obstacle avoidance algorithm embedded in the control system senses and fuses the signals transmitted from these three systems to identify and locate obstacles, replan the navigation route, and achieve obstacle avoidance. When the debris-collecting vessel malfunctions, a remote control station manipulates the vessel to return.

[0006] The above-mentioned technology has at least the following technical problems:

[0007] Existing unmanned surface vessel (USV) remote control technologies, especially in medium- to long-range and complex environments, face systemic bottlenecks across five dimensions: communication, decision-making, functionality, data, and scenario adaptability. Firstly, at the communication level, the mainstream 2.4G Wi-Fi solution suffers from inherent limitations due to its extremely short communication range (typically less than 1 kilometer without obstructions), poor resistance to obstructions (susceptible to interference from islands, bridges, etc.), and limited bandwidth (unable to handle high-definition video and multi-sensor data). This not only fails to meet the remote coverage requirements of vast waterways such as large lakes and rivers but also causes severe delays in human-machine interaction due to high latency, rendering remote control "high-risk blind control" and fundamentally negating its feasibility as a reliable remote control solution.

[0008] Secondly, at the decision-making level, existing unmanned surface vessels (USVs) rely excessively on autonomous decision-making. However, their perception systems, often employing single sensors, are prone to missing or misjudging obstacles in complex waters. Furthermore, their decision-making algorithms have poor fault tolerance and cannot handle sudden multi-target scenarios. More importantly, they lack a low-latency, highly reliable remote takeover mechanism. If the autonomous system fails, the vessel will become uncontrollable, resulting in extremely low safety. Thirdly, at the functional and data level, existing remote control systems are limited to basic navigation control and lack standardized control interfaces and command formats for specialized machinery such as cleanup vessels (e.g., bow opening / closing, conveyor belts). Simultaneously, data from various modules on the vessel is transmitted in a decentralized manner without a unified domain controller for integration and low-latency feedback. This prevents operators from grasping the overall status in real time, leading to biased and delayed decision-making. The accumulated latency in communication links also contributes to low real-time performance of parallel driving of the USV. Summary of the Invention

[0009] This application provides a parallel driving system, method, and unmanned vessel based on a 5G remote cockpit, which solves the problem of low real-time performance of parallel driving of unmanned vessels due to the accumulation of delays in communication links in the prior art, and improves the real-time performance of parallel driving of unmanned vessels.

[0010] On one hand, a parallel driving system for unmanned vessels based on a 5G remote cockpit is provided, including: a ship-side data quantification module, a ship-side data transmission timeliness control module, and a cockpit-side data reception real-time control module. The ship-side data quantification module collects ship-side data to obtain a ship-side data transmission latency index, which quantifies the timeliness from when a data packet is sent from the ship-side domain controller to when the data packet is successfully received by the 5G cloud. The ship-side data transmission timeliness control module determines whether to perform ship-side data transmission timeliness control based on the ship-side data transmission latency index. If so, it sends a ship-side optimization status synchronization command to the 5G cloud after the ship-side data transmission timeliness control is performed; otherwise, it directly sends a ship-side data transmission timeliness control command. The ship-side optimization status synchronization command is sent to the 5G cloud. The ship-side data transmission timeliness control includes generation time window control and modulation / demodulation rate control. The cabin-side data reception real-time control module is used to obtain cabin-side data reception delay parameters to obtain cabin-side data reception delay gradient index, which is used to quantify the real-time performance of cabin-side data reception from ship-side control commands. Based on the cabin-side data reception delay gradient index, it determines whether to perform cabin-side data reception real-time control. If so, a cabin-side control result notification command is sent after cabin-side data reception real-time control. If not, a cabin-side control result notification command is sent directly. Cabin-side data reception real-time control includes reception frequency control and maximum task number threshold control.

[0011] On the other hand, a parallel driving method for unmanned ships based on a 5G remote cockpit is provided, including: collecting ship-side data to obtain a ship-side data transmission latency index, used to quantify the timeliness from sending a data packet from the ship-side domain controller to the successful reception of the data packet by the 5G cloud; determining whether to perform ship-side data transmission timeliness control based on the ship-side data transmission latency index; if yes, sending a ship-side optimized state synchronization command to the 5G cloud after ship-side data transmission timeliness control; otherwise, directly sending a ship-side optimized state synchronization command to the 5G cloud. Ship-side data transmission timeliness control includes generation time window control and modulation / demodulation rate control; obtaining cockpit-side data reception latency parameters to obtain a cockpit-side data reception latency gradient index, used to quantify the real-time reception of cockpit data from ship-side control commands; determining whether to perform cockpit-side data reception real-time control based on the cockpit-side data reception latency gradient index; if yes, sending a cockpit-side control result notification command after cockpit-side data reception real-time control; otherwise, directly sending a cockpit-side control result notification command. Cockpit-side data reception real-time control includes reception frequency control and maximum task number threshold control.

[0012] On the other hand, it provides a parallel driving unmanned ship based on a 5G remote cockpit, including: a ship end and a cabin end. The ship end includes a positioning module, a perception module, a vision module, a battery management module, a propulsion system, a transmission mechanism, a domain controller, and a 5G shipborne terminal; the cabin end includes a remote cockpit, a display platform, and a cabin end server.

[0013] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0014] 1. By collecting ship-side data, a ship-side data transmission latency index is obtained. This index quantifies the timeliness from when a data packet is sent from the ship-side domain controller to when the packet is successfully received by the 5G cloud. Based on the ship-side data transmission latency index, it is determined whether to implement ship-side data transmission timeliness adjustment to appropriately reduce transmission frequency or latency, thereby optimizing network resource utilization, avoiding unnecessary data redundancy, and maintaining the overall system operating efficiency and stability. 2. Obtaining cabin-side data reception latency parameters yields a cabin-side data reception latency gradient index. This index quantifies the real-time performance of cabin-side data reception from ship-side control commands. Based on the cabin-side data reception latency gradient index, it is determined whether to implement cabin-side data reception real-time performance adjustment to appropriately reduce reception frequency or introduce a reception buffer mechanism, thereby reducing network load, avoiding data congestion, and ensuring the stability and processing efficiency of data reception, thus improving the real-time performance of unmanned surface vessel parallel driving.

[0015] 2. Determine whether to implement ship-side data transmission timeliness control based on the ship-side data transmission delay index to appropriately reduce transmission frequency or delay; determine whether to implement generation time window control based on ship-side data acquisition delay, indicating that the data acquisition frequency is too fast or the system load is too light. In this case, generation time window control should be implemented to appropriately extend the time window interval, thereby reducing the acquisition frequency, reducing redundant data processing, and optimizing system resource utilization efficiency; determine whether to implement modulation and demodulation rate control based on 5G signal receiving power, indicating that the signal quality is insufficient to support the current high-speed modulation and demodulation. In this case, modulation and demodulation rate control should be implemented to reduce the transmission rate, enhance the signal anti-interference capability, thereby ensuring the stability of the communication link and the reliability of data transmission, and thus improving the real-time performance of unmanned ship parallel driving.

[0016] 3. Determine whether to perform real-time control of cabin data reception based on the cabin data reception delay gradient exponent to ensure the stability and processing efficiency of data reception; determine whether to perform reception frequency control based on the 5G cloud reception time interval, indicating that the cabin data transmission rate is too fast and exceeds the cloud processing capacity or network carrying capacity. In this case, reception frequency control should be performed to reduce the cabin data transmission frequency, thereby restoring the stability of data reception and system processing efficiency; determine whether to perform maximum task number threshold control based on the domain controller task scheduling latency, indicating that the system task load is too heavy and exceeds the real-time processing capacity. In this case, maximum task number threshold control should be performed to reduce the number of concurrent tasks, thereby ensuring the real-time performance of task scheduling and system stability, and thus improving the real-time performance of unmanned vessel parallel driving. Attached Figure Description

[0017] Figure 1 A schematic diagram of the structure of the unmanned ship parallel driving system based on a 5G remote cockpit provided in an embodiment of this application;

[0018] Figure 2 A flowchart of a parallel driving method for an unmanned vessel based on a 5G remote cockpit, provided for an embodiment of this application;

[0019] Figure 3 A schematic diagram of the ship end structure of the unmanned ship parallel driving system based on a 5G remote cockpit provided in an embodiment of this application;

[0020] Figure 4 A schematic diagram of the cabin end structure of the unmanned ship parallel driving system based on a 5G remote cockpit provided in an embodiment of this application;

[0021] Figure 5 A schematic diagram of the architecture of an unmanned ship parallel driving system based on a 5G remote cockpit provided in an embodiment of this application;

[0022] Reference numerals: 100, ship's end; 110, propeller; 120, BMS; 130, positioning module; 140, sensing module; 150, transmission mechanism; 151, bow opening and closing mechanism; 151, conveyor belt; 160, vision module; 170, domain controller; 180, 5G shipborne terminal; 200, cabin end; 210, remote cockpit; 211, steering wheel; 212, gear shift; 213, pedal; 220, display platform; 230, cabin end server. Detailed Implementation

[0023] This application provides a parallel driving system, method, and unmanned vessel based on a 5G remote cockpit, which solves the problem of low real-time performance of parallel driving of unmanned vessels due to the accumulation of communication link delays in the prior art. By collecting ship-end data to obtain the ship-end data transmission delay index and determining whether to perform ship-end data transmission timeliness control, and obtaining cabin-end data reception delay parameters to obtain the cabin-end data reception delay gradient index and determining whether to perform cabin-end data reception real-time control, the real-time performance of parallel driving of unmanned vessels is improved.

[0024] The technical solution in this application is to solve the problem of low real-time performance of unmanned surface vessel parallel driving caused by the accumulation of delays in communication links. The overall approach is as follows:

[0025] By collecting ship-side data, a ship-side data transmission latency index is obtained, which is used to quantify the timeliness from when a data packet is sent from the ship-side domain controller to when the data packet is successfully received by the 5G cloud. Based on the ship-side data transmission latency index, it is determined whether to perform ship-side data transmission timeliness adjustment. If so, a ship-side optimization status synchronization command is sent to the 5G cloud after ship-side data transmission timeliness adjustment. If not, a ship-side optimization status synchronization command is sent directly to the 5G cloud. The cabin-side data reception latency parameter is obtained to obtain a cabin-side data reception latency gradient index, which is used to quantify the real-time performance of cabin-side data reception from ship-side control commands. Based on the cabin-side data reception latency gradient index, it is determined whether to perform cabin-side data reception real-time performance adjustment. If so, a cabin-side adjustment result notification command is sent after cabin-side data reception real-time performance adjustment. If not, a cabin-side adjustment result notification command is sent directly, thereby improving the real-time performance of unmanned ship parallel driving.

[0026] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0027] like Figure 1The diagram shows the structure of an unmanned vessel parallel driving system based on a 5G remote cockpit provided in this application embodiment. The system includes: a ship-side data quantization module, a ship-side data transmission timeliness control module, and a cockpit-side data reception real-time control module. The ship-side data quantization module collects ship-side data to obtain a ship-side data transmission latency index, which quantifies the timeliness from when a data packet is sent from the ship-side domain controller to when the packet is successfully received by the 5G cloud. The ship-side data transmission latency control module determines whether to perform ship-side data transmission latency control based on the latency index. If so, it sends the ship-side optimized status after the latency control. If the command is not sent to the 5G cloud, the ship-side optimization status synchronization command is sent directly to the 5G cloud. The ship-side data transmission timeliness control includes generation time window control and modulation / demodulation rate control. The cabin-side data reception real-time control module is used to obtain cabin-side data reception delay parameters to obtain cabin-side data reception delay gradient index, which is used to quantify the real-time performance of cabin-side data reception from ship-side control commands. Based on the cabin-side data reception delay gradient index, it is determined whether to perform cabin-side data reception real-time control. If yes, a cabin-side control result notification command is sent after cabin-side data reception real-time control. If no, a cabin-side control result notification command is sent directly. Cabin-side data reception real-time control includes reception frequency control and maximum task number threshold control.

[0028] It needs to be explained that the specific steps to obtain the ship-side data transmission latency index are as follows:

[0029] S1, the transmission frequency impact value is obtained by interactively processing the results of the analysis of the transmission frequency threshold and the proportion of data transmission frequency at the ship end through the transmission frequency impact factor; where the proportion analysis refers to division operation and the interactive processing refers to multiplication operation.

[0030] S2, through the interaction of the thread number influence factor on the ratio of the relative deviation between the number of parallel processing threads for ship data and the set thread number, the thread number influence value is obtained; the relative deviation ratio refers to the ratio of the absolute value of the difference between the number of parallel processing threads for ship data and the set thread number to the set thread number.

[0031] S3 interactively processes the results of the analysis of the ratio of 5G cloud receiving latency to receiving latency threshold through the receiving latency impact factor to obtain the receiving latency impact value.

[0032] S4, the data transmission delay index at the ship end is obtained by coupling the impact values ​​of transmission frequency, number of threads, and reception delay.

[0033] It should be noted that the transmission frequency impact factor, thread count setting, thread count impact factor, transmission frequency threshold, reception latency impact factor, and reception latency threshold were all obtained from the parallel driving database. Specifically, the ship-side data transmission frequency refers to the number of times ship-side data is sent to the cloud server via the 5G network per unit time; the number of ship-side data parallel processing threads refers to the number of parallel threads processing ship-side data in the domain controller of the unmanned vessel; and the 5G cloud reception latency refers to the total time elapsed from the moment the data packet is prepared in the transmission buffer of the ship-side 5G module, ready to be sent (starting with the first bit), until the last bit of the data packet successfully arrives at the application reception buffer of the cloud server.

[0034] It needs to be explained that the specific steps to obtain the cabin-end data reception delay gradient exponent are as follows:

[0035] S11, the results of the analysis of the proportion of the data transmission delay index and the transmission delay threshold of the ship end to be corrected are interactively processed by the transmission delay impact factor to obtain the transmission delay impact value.

[0036] S22, the results of the analysis of the ratio of data reception delay to reception delay threshold by the reception delay impact factor are interactively processed to obtain the reception delay impact value.

[0037] S33, the results of the relative deviation ratio between the 5G cloud receiving time interval and the set value of the receiving time interval are interactively processed by the receiving time interval influence factor to obtain the receiving time interval influence value; where the relative deviation ratio refers to the ratio of the absolute value of the difference between the 5G cloud receiving time interval and the set value of the receiving time interval to the set value of the receiving time interval.

[0038] S44, the transmission delay impact value, the reception delay impact value, and the reception time interval impact value are coupled and processed to obtain the cabin data reception delay gradient exponent.

[0039] It should be noted that the transmission delay impact factor, transmission delay threshold, reception delay impact factor, reception delay threshold, reception time interval impact factor, and reception time interval setting value were all obtained from the parallel driving database. Specifically, the ship-side data transmission delay index to be corrected refers to the ship-side data transmission delay index that is re-acquired if ship-side data transmission timeliness control has been implemented; otherwise, the current ship-side data transmission delay index is recorded as the ship-side data transmission delay index to be corrected. Cabin-side data reception delay refers to the time it takes for the cabin to receive data from the 5G cloud. The 5G cloud reception time interval refers to the time interval between the ship-side uploading data to the 5G cloud.

[0040] In this embodiment, a closed-loop, adaptive data transmission and reception optimization mechanism is constructed through the synergistic effect of the ship-side data quantization module, the ship-side data transmission timeliness control module, and the cabin-side data reception real-time control module, thereby realizing real-time monitoring and dynamic control of the entire data link from the ship to the 5G cloud. The ship-side data quantification module accurately quantifies the timeliness of successful data packet reception from the ship-side domain controller to the cloud by collecting data transmission latency indices, providing a reliable basis for subsequent control. The ship-side data transmission timeliness control module uses this index to determine whether to perform generation time window control or modulation / demodulation rate control to optimize the ship-side data transmission rhythm and rate. Regardless of whether control is performed, a ship-side optimization status synchronization command is sent to the cloud to ensure real-time cloud awareness of the ship-side status. Simultaneously, the cabin-side data reception real-time control module quantifies the real-time reception of ship-side control commands by acquiring the cabin-side data reception latency gradient index, and determines whether to perform reception frequency control or maximum task threshold control to optimize the cabin-side data reception and processing capabilities. Regardless of whether control is performed, a cabin-side control result notification command is sent, forming a closed-loop information feedback system. Overall, this mechanism, through two-way control, status synchronization, and result feedback between the ship and cabin sides, significantly improves the real-time performance, stability, and reliability of data transmission, effectively avoiding data congestion, resource waste, or response delays, and ensuring the efficient collaborative operation and intelligent decision support capabilities of the ship-shore communication system.

[0041] Furthermore, if the ship-end data transmission delay index is lower than or equal to the transmission delay reference value, then no ship-end data transmission timeliness control will be performed; if the ship-end data transmission delay index is higher than the transmission delay reference value, then it will be determined whether to perform generation time window control based on the ship-end data acquisition delay. If so, then it will be determined whether to perform modulation and demodulation rate control after performing generation time window control; if not, then it will be determined directly whether to perform modulation and demodulation rate control.

[0042] As a further explanation, the process for determining whether to implement generation time window adjustment based on the ship's data acquisition latency is as follows:

[0043] If the ship-side data acquisition delay exceeds the set acquisition delay value, the transmission delay correction and acquisition delay correction are input into the time window mapping table for querying to obtain the generation time window width adjustment. Based on this adjustment, the ship-side data generation time window is coupled with the current ship-side data generation time window to obtain the adjusted window, thus dynamically expanding the generation time window width. This effectively alleviates data backlog and processing pressure caused by excessive acquisition delay or transmission delay fluctuations, improves the synchronization and stability of data acquisition and transmission, and ensures that the system maintains efficient and reliable data flow and real-time response capabilities under high load or abnormal operating conditions. The transmission delay correction represents the difference between the ship-side data transmission delay index and the transmission delay reference value, while the acquisition delay correction represents the difference between the ship-side data acquisition delay and the set acquisition delay value. The coupling process refers to an addition operation.

[0044] If the data acquisition delay at the ship's end is less than or equal to the set acquisition delay value, the generation time window adjustment will not be executed, and the current time window width will remain unchanged. This avoids unnecessary resource adjustments and system disturbances, ensures the stability and efficiency of the data acquisition and transmission process, reduces control overhead, and improves system operating efficiency and real-time response.

[0045] In this embodiment, the mechanism enables adaptive dynamic adjustment of the data generation time window, which can effectively alleviate pressure when the load is too high and maintain stable operation when the load is normal, thereby continuously optimizing the performance of the data link and the efficiency of resource utilization in complex and ever-changing real-world application scenarios.

[0046] As a further explanation, the specific procedure for determining whether to perform modulation / demodulation rate control is as follows:

[0047] If the 5G signal received power exceeds the set upper limit of received power, the transmission delay correction and received power correction are input into the demodulation rate mapping table to obtain the demodulation rate adjustment factor, thereby dynamically reducing the demodulation rate. This effectively suppresses signal distortion, interference, or bit error rate increases caused by excessively strong signals, ensuring the accuracy and reliability of data demodulation. At the same time, it optimizes the allocation of signal processing resources at the receiving end and improves the system's stable operation capability in strong signal environments. The received power correction represents the difference between the 5G signal received power and the set upper limit of received power.

[0048] The system determines whether the demodulation rate adjustment factor is greater than its set value. If so, it inputs the adjustment factor correction amount into the demodulation rate mapping table to obtain the modulation / demodulation rate reduction amount. Based on the current 5G shipborne terminal modulation / demodulation rate and the reduction amount, a difference is processed to obtain the adjusted 5G shipborne terminal modulation / demodulation rate. This dynamically reduces the modulation / demodulation rate, effectively suppressing signal distortion, increased bit error rate, or excessive receiver processing pressure caused by excessively high demodulation rates. This ensures data transmission accuracy and link stability, while optimizing terminal power consumption and system resource utilization efficiency. It also improves the shipborne terminal's adaptive control capability and communication reliability in complex signal environments. The adjustment factor correction amount represents the difference between the demodulation rate adjustment factor and its set value. The difference processing refers to a subtraction operation.

[0049] If not, the adjustment factor is input into the demodulation rate mapping table to obtain the modulation / demodulation rate increase. Based on the current 5G shipborne terminal modulation / demodulation rate and the increased modulation / demodulation rate, a coupling process is performed to obtain the adjusted 5G shipborne terminal modulation / demodulation rate. This dynamically increases the modulation / demodulation rate, effectively enhancing data transmission efficiency and throughput. Simultaneously, it fully utilizes current signal resources, avoiding waste of communication resources or increased transmission latency due to excessively low rates. This ensures that the shipborne terminal maintains efficient and fast data transmission capabilities even with good signal quality or light load, improving the overall communication system's response speed and resource utilization. The adjustment factor represents the difference between the demodulation rate adjustment factor and its set value. The coupling process refers to an addition operation.

[0050] If the 5G signal received power is within the received power setting range, modulation and demodulation rate adjustment will not be performed. The received power setting range refers to the closed interval formed by the lower limit of the received power setting and the upper limit of the received power setting. This maintains the stable operation of the current modulation and demodulation rate to avoid additional processing overhead or communication jitter caused by frequent adjustments, and ensures the continuity and stability of data transmission.

[0051] As a further specific explanation, determining whether to perform modulation / demodulation rate control also includes:

[0052] If the 5G signal received power is less than the set lower limit of received power, the transmission delay correction amount and the received power comparison amount are input into the demodulation rate mapping table to obtain the demodulation rate control factor, thereby dynamically reducing the modulation and demodulation rate to enhance the signal anti-interference capability and bit error tolerance, effectively cope with the link quality degradation caused by signal weakening, ensure the reliability and stability of data transmission, and optimize the receiver signal processing strategy to improve the robustness and communication continuity of the shipborne terminal in low signal-to-noise ratio environments. The received power comparison amount represents the difference between the set lower limit of received power and the 5G signal received power.

[0053] The system determines whether the demodulation rate control factor is greater than its set value. If so, it inputs the adjustment amount of the control factor into the demodulation rate mapping table to obtain the modulation and demodulation rate increase. Based on the current 5G shipborne terminal modulation and demodulation rate and the increased modulation and demodulation rate, the system performs superposition processing to obtain the adjusted 5G shipborne terminal modulation and demodulation rate. This dynamically increases the modulation and demodulation rate to fully utilize channel resources when signal quality recovers or improves, thereby increasing data transmission rate and system throughput. Simultaneously, it avoids low communication efficiency caused by prolonged low-rate operation, enhances the shipborne terminal's adaptive response capability and resource utilization efficiency in signal fluctuation environments, and ensures efficient and reliable operation of the communication link. The adjustment amount of the control factor represents the difference between the demodulation rate control factor and its set value. Superposition processing refers to addition.

[0054] If not, the adjustment factor compensation amount is input into the demodulation rate mapping table to obtain the modulation and demodulation rate reduction amount. Based on the current 5G shipborne terminal modulation and demodulation rate and the modulation and demodulation rate reduction amount, the difference is processed to obtain the adjusted 5G shipborne terminal modulation and demodulation rate, thereby dynamically reducing the modulation and demodulation rate to further optimize signal reception quality, reduce bit error rate, and improve link stability. It is especially suitable for communication environments with continuously weak signals or large interference, ensuring that the shipborne terminal can still maintain reliable data transmission under complex wireless conditions. At the same time, it effectively reduces system power consumption, extends equipment lifespan, and improves the robustness and continuous operation capability of the overall communication system. The adjustment factor compensation amount represents the difference between the demodulation rate adjustment factor and the demodulation rate adjustment factor set value.

[0055] In this embodiment, by real-time monitoring of 5G signal reception power, combined with a multi-level control mechanism and dynamic mapping table lookup, refined and adaptive control of the modulation and demodulation rate of the shipborne terminal is achieved. This overall mechanism not only significantly improves the adaptability and robustness of the shipborne terminal in complex and dynamic signal environments, but also optimizes the efficiency of communication resource utilization and extends the service life of the equipment, providing comprehensive protection for the efficient and reliable operation of the 5G shipborne communication system.

[0056] Furthermore, if the cabin-end data reception delay gradient index is lower than or equal to the delay gradient reference value, then the cabin-end data reception real-time control will not be performed; if the cabin-end data reception delay gradient index is greater than the delay gradient reference value, then it will be determined whether to perform reception frequency control based on the 5G cloud reception time interval. If so, then it will be determined whether to perform maximum task number threshold control after reception frequency control; if not, then it will be determined directly whether to perform maximum task number threshold control.

[0057] As further explained, the process for determining whether to perform reception frequency adjustment based on the 5G cloud reception time interval is as follows:

[0058] If the 5G cloud reception interval is lower than the set lower limit of the reception interval, the delay gradient correction amount and the reception interval correction amount are input into the reception frequency mapping table to obtain the reception frequency reduction amount. Based on the current cabin data reception frequency and the reception frequency reduction amount, the difference is processed to obtain the adjusted cabin data reception frequency, thereby dynamically reducing the cabin data reception frequency. This effectively alleviates the risk of cloud processing overload, network congestion, or data loss caused by excessively high reception frequency, ensuring the stability and reliability of data reception. At the same time, it optimizes the efficiency of cloud resource utilization and system response performance, and improves the overall stable operation capability and anti-interference resilience of the communication link. The delay gradient correction amount represents the difference between the cabin data reception delay gradient exponent and the delay gradient reference value, and the reception interval correction amount represents the difference between the 5G cloud reception interval and the set lower limit of the reception interval.

[0059] If the 5G cloud receiving time interval is within the receiving time interval setting range, no receiving frequency adjustment will be performed. This indicates that the current data receiving frequency has reached a dynamic balance with the cloud processing capacity, network carrying capacity, and transmission requirements. This avoids the waste of system resources and additional computing overhead caused by frequent adjustments, while ensuring the real-time performance and stability of data transmission. This allows the communication link to maintain efficient and stable operation without manual intervention. The receiving time interval setting range is used to represent the closed interval formed by the lower limit and upper limit of the receiving time interval setting.

[0060] If the 5G cloud receiving time interval is higher than the set upper limit of the receiving time interval, the delay gradient correction amount and the receiving time interval comparison amount are input into the receiving frequency mapping table to obtain the receiving frequency adjustment amount. Based on the current cabin data receiving frequency and the receiving frequency adjustment amount, the adjusted cabin data receiving frequency is obtained, thereby dynamically increasing the cabin data receiving frequency. This effectively addresses the problems of data transmission lag, insufficient communication link utilization, or reduced real-time performance caused by excessively low receiving frequency, ensuring the timeliness and efficiency of data transmission. At the same time, it optimizes the cloud data receiving rhythm and system resource scheduling capabilities, improving the overall communication link response speed and data throughput performance. The receiving time interval comparison amount represents the difference between the 5G cloud receiving time interval and the set upper limit of the receiving time interval.

[0061] In this embodiment, this complete closed-loop control strategy not only realizes the adaptive dynamic adjustment of the data reception frequency at the cabin end, but also significantly enhances the system's anti-interference capability, robustness and operating efficiency in complex network environments, ensuring the efficient and reliable operation of the shipborne communication system under changing operating conditions.

[0062] As a further explanation, the specific steps for determining whether to implement the maximum task count threshold adjustment are as follows:

[0063] If the domain controller task scheduling latency is lower than or equal to the scheduling latency setting, the maximum task number threshold adjustment will not be executed. This indicates that the current task scheduling mechanism and the system load capacity have reached an optimal matching state. This avoids system jitter and additional computational overhead caused by frequent threshold adjustments, while ensuring the real-time performance and efficiency of task scheduling. This allows the domain controller to maintain stable operation without additional intervention, improving the overall system resource utilization efficiency and task execution reliability.

[0064] If the domain controller task scheduling latency is higher than the scheduling latency setting, the result of the harmonic averaging of the latency gradient correction and the scheduling latency reference value is input into the maximum task number mapping table to obtain the maximum task number threshold reduction amount. The difference between the current domain controller maximum task number threshold and the maximum task number threshold reduction amount is processed to obtain the adjusted domain controller maximum task number threshold. This dynamically reduces the maximum number of concurrent tasks allowed by the system, effectively alleviating the scheduling latency deterioration, resource contention, and response delay problems caused by task overload, ensuring the real-time performance of task scheduling and system stability, while improving the rationality of resource allocation and overall operating efficiency, and enhancing the robustness and adaptability of the domain controller under high load or sudden task scenarios. The scheduling latency reference value represents the difference between the domain controller task scheduling latency and the scheduling latency setting value.

[0065] In this embodiment, through this dual judgment and dynamic control mechanism, the system can maintain efficient and stable operation when the load is normal, and make timely self-adjustment when the load is too heavy, thereby continuously optimizing task scheduling performance and resource utilization efficiency in complex and ever-changing task environments, and ensuring long-term reliable operation of the system.

[0066] like Figure 2The diagram shows a flowchart of a parallel driving method for unmanned vessels based on a 5G remote cockpit, provided in an embodiment of this application. The method includes: collecting ship-side data to obtain a ship-side data transmission latency index, used to quantify the timeliness from when a data packet is sent from the ship-side domain controller to when the data packet is successfully received by the 5G cloud; determining whether to perform ship-side data transmission timeliness adjustment based on the ship-side data transmission latency index; if so, sending a ship-side optimization status synchronization command to the 5G cloud after ship-side data transmission timeliness adjustment; otherwise, directly sending a ship-side optimization status synchronization command to the 5G cloud. In the G cloud, the timeliness control of ship-side data transmission includes generation time window control and modulation / demodulation rate control; the cabin-side data reception delay parameter is obtained to obtain the cabin-side data reception delay gradient index, which is used to quantify the real-time performance of cabin-side data reception from ship-side control commands. Based on the cabin-side data reception delay gradient index, it is determined whether to perform cabin-side data reception real-time control. If so, a cabin-side control result notification command is sent after cabin-side data reception real-time control is performed; otherwise, a cabin-side control result notification command is sent directly. Cabin-side data reception real-time control includes reception frequency control and maximum task number threshold control.

[0067] The unmanned ship based on the 5G remote cockpit is a parallel driving unmanned ship, including: the ship end and the cabin end. The ship end includes a positioning module, a perception module, a vision module, a battery management module, a propulsion system, a transmission mechanism, a domain controller, and a 5G shipborne terminal; the cabin end includes a remote cockpit, a display platform, and a cabin end server.

[0068] It is necessary to understand that, such as Figure 3 The diagram shown is a schematic representation of the ship-end structure of the unmanned vessel parallel driving system based on a 5G remote cockpit provided in this application embodiment. Specifically, the ship-end includes a positioning module, a perception module, a vision module, a battery management module, a thruster, a transmission mechanism, a domain controller, and a 5G shipborne terminal. Figure 4 As shown in the figure, the cabin-end structure of the unmanned ship parallel driving system based on the 5G remote cockpit provided in this application embodiment is as follows. Specifically, the cabin-end includes a remote cockpit, a display platform, and a cabin-end server.

[0069] It should be added that the domain controller communicates with the 5G shipborne terminal; the 5G shipborne terminal communicates with the cabin-side server via the 5G cloud; the cabin-side server communicates with the display platform; the remote cockpit receives and executes actions and sends control commands to the cabin-side server; the cabin-side server sends control commands to the 5G shipborne terminal via the 5G cloud; the 5G shipborne terminal sends control commands to the domain controller, which then issues control commands to the propellers; the domain controller issues control commands to the transmission mechanism; the positioning module sends positioning attitude data to the domain controller; the perception module sends perception data to the domain controller; the vision module sends video stream data to the domain controller; the battery management module sends battery status data to the domain controller; and the propellers send status information to the domain controller. The remote cockpit includes a steering wheel, accelerator, brake pedal, and gearshift; the steering wheel includes paddle shifters and buttons; the perception module includes a LiDAR module and a vision recognition module; the transmission module includes a bow opening / closing mechanism and a conveyor belt; the vision module uses WebRTC streaming media; and the control commands include throttle commands, braking commands, gear shift commands, steering commands, driving mode commands, bow opening / closing commands, and conveyor belt operation commands.

[0070] It is necessary to understand that, such as Figure 5 The diagram shows the architecture of a parallel driving system for unmanned vessels based on a 5G remote cockpit provided in this application embodiment. Specifically, the vessel end 100 includes a positioning module 130, a perception module 140, a vision module 160, a BMS 120, a thruster 110, a transmission mechanism 150, a domain controller 170, and a 5G shipborne terminal 180; the cockpit end 200 includes a remote cockpit 210, a display platform 220, and a cockpit server 230. The remote cockpit 210 mainly comprises three parts: a steering wheel 211, a gear shift 212, and pedals 213. The steering wheel 211 has paddle shifters and multiple buttons, which can be used to issue corresponding commands to control the vessel end 100 to perform different functions as needed. According to different business requirements, the data from the remote cockpit 210 is converted into a corresponding ROS custom message format and published to the 5G cloud using MQTT message middleware. For example, for unmanned clean-up vessels, the following custom message format is defined:

[0071] G29RemoteCtrl.msg:int16 steerAngle (steering wheel angle -180-180); uint8 power (throttle command 0-127); uint8 brake (brake command 0 / 1); uint8 gear (gear position 0 / 1); uint8driveMode (driving mode 0-remote driving 1-autonomous driving); uint8 headOnOff (bow opening / closing 0-1); uint8transporter (conveyor belt operation command 0-1); The display platform 220 is used to display the unmanned vessel video stream, the current status of the remote cockpit 210, and the status of the unmanned vessel's sensors in real time, such as positioning, attitude, BMS, thruster speed, power, alarms, etc. Monitoring personnel can view the data on the display platform 220 in real time and operate the unmanned vessel using the remote cockpit 210.

[0072] The functions of the thruster 110 include: reporting the status of the thruster 110, including speed, temperature, stall status, voltage, current, etc., and receiving remote control commands through the 5G shipborne terminal 180, converting steering, throttle, and gear into motor control commands to control the direction and duty cycle of the motor.

[0073] In this embodiment, an unmanned cleanup vessel is used as an example. This vessel has a twin-propeller propulsion system. Forward and backward movement are achieved through the forward / reverse rotation of the propellers, and steering is achieved through the differential speed of the propellers. The formula for converting gear position, throttle power, and steering angle into left and right propeller commands is as follows:

[0074] A gear is 1-forward gear;

[0075] A-1 steering angle is greater than 0: ;

[0076] A-2 steering angle is less than 0: ;

[0077] B gear is 0-reverse;

[0078] A-1 steering angle is greater than 0: ;

[0079] A-2 steering angle is less than 0: ;

[0080] Here, represents the left motor throttle and represents the right motor throttle. The BMS module 120 at the ship's end 100 parses the battery's CAN protocol and uses the 5G shipborne terminal 180 to send the battery status via MQTT message middleware. When the cabin end 200 monitors for battery malfunction or insufficient power, it can execute relevant actions. The perception module 140 mainly uploads the data collected by the visual recognition and lidar recognition modules to the cabin end 200, which displays the outline information of obstacles in real time for reference during decision-making. Taking the unmanned cleanup vessel as an example, the transmission mechanism 150 includes two parts: the bow opening and closing mechanism 151 and the conveyor belt 152. The ship's end 100 receives the bow opening and closing commands and conveyor belt commands sent by the remote cockpit 210, converts them into control signals, and controls the opening and closing of the bow and the start and stop of the conveyor belt. The ship's 100-degree vision module 160 primarily employs WebRTC streaming media technology, utilizing a 5G shipborne terminal 180 to push video streams to the cloud; simultaneously, the cabin-side 200 pulls the stream and displays it in real-time on its display platform 220. Employing 5G communication and WebRTC streaming media technologies, it can achieve a latency of less than 300ms for 1080P video streams.

[0081] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0082] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0083] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0084] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0085] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0086] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A parallel driving system for unmanned vessels based on a 5G remote cockpit, characterized in that, include: Ship-side data quantification module, ship-side data transmission timeliness control module, and cabin-side data reception real-time control module; The ship-side data quantification module is used to collect ship-side data to obtain the ship-side data transmission delay index, which is used to quantify the timeliness from when the data packet is sent from the ship-side domain controller to when the data packet is successfully received by the 5G cloud. The ship-end data transmission timeliness control module is used to determine whether to perform ship-end data transmission timeliness control based on the ship-end data transmission delay index. If yes, the ship-end data transmission timeliness control module sends a ship-end optimization status synchronization command to the 5G cloud after the ship-end data transmission timeliness control. If no, the ship-end optimization status synchronization command is sent directly to the 5G cloud. The ship-end data transmission timeliness control includes generation time window control and modulation / demodulation rate control. The real-time control module for cabin data reception is used to obtain cabin data reception delay parameters to obtain cabin data reception delay gradient index, which is used to quantify the real-time performance of cabin data reception from ship-side control commands. Based on the cabin data reception delay gradient index, it determines whether to perform cabin data reception real-time control. If yes, a cabin control result notification command is sent after cabin data reception real-time control is performed. If no, a cabin control result notification command is sent directly. The cabin data reception real-time control includes reception frequency control and maximum task number threshold control. The ship-side data includes the ship-side data transmission frequency, the number of parallel processing threads for ship-side data, and the 5G cloud reception latency. If the ship-end data transmission delay index is lower than or equal to the transmission delay reference value, then the ship-end data transmission timeliness control will not be implemented. If the ship-end data transmission delay index is higher than the transmission delay reference value, then determine whether to perform generation time window adjustment based on the ship-end data acquisition delay. If yes, then determine whether to perform modulation and demodulation rate adjustment after performing generation time window adjustment. If no, then directly determine whether to perform modulation and demodulation rate adjustment. The cabin data reception delay parameters include the ship-side data transmission delay index to be corrected, the cabin data reception delay, and the 5G cloud reception time interval. If the delay gradient exponent of the cabin data reception is lower than or equal to the delay gradient reference value, then the real-time control of cabin data reception will not be performed. If the data reception delay gradient exponent at the cabin end is greater than the delay gradient reference value, then it is determined whether to perform reception frequency adjustment based on the 5G cloud reception time interval. If so, then it is determined whether to perform maximum task number threshold adjustment after reception frequency adjustment. If not, then it is determined whether to perform maximum task number threshold adjustment directly.

2. The unmanned vessel parallel driving system based on a 5G remote cockpit according to claim 1, characterized in that, The specific process for determining whether to perform time window adjustment based on the ship's data acquisition delay is as follows: If the ship-end data acquisition delay is greater than the acquisition delay set value, the transmission delay correction amount and the acquisition delay correction amount are input into the time window mapping table for querying to obtain the generation time window width adjustment amount. Based on the generation time window width adjustment amount and the current ship-end data generation time window, the adjusted ship-end data generation time window is obtained. The transmission delay correction amount is used to represent the degree of deviation between the ship-end data transmission delay index and the transmission delay reference value, and the acquisition delay correction amount is used to represent the degree of deviation between the ship-end data acquisition delay and the acquisition delay set value. If the data acquisition delay at the ship's end is less than or equal to the set acquisition delay value, the generation time window adjustment will not be executed.

3. The unmanned vessel parallel driving system based on a 5G remote cockpit according to claim 1, characterized in that, The specific process for determining whether to perform modulation / demodulation rate control is as follows: If the 5G signal received power is greater than the set upper limit of received power, the transmission delay correction amount and the received power correction amount are input into the demodulation rate mapping table to obtain the demodulation rate adjustment factor. The received power correction amount is used to represent the degree of deviation between the 5G signal received power and the set upper limit of received power. Determine whether the demodulation rate adjustment factor is greater than the demodulation rate adjustment factor set value. If so, input the adjustment factor correction amount into the demodulation rate mapping table to obtain the modulation and demodulation rate reduction amount. Perform difference processing based on the current 5G shipborne terminal modulation and demodulation rate and the modulation and demodulation rate reduction amount to obtain the adjusted 5G shipborne terminal modulation and demodulation rate. The adjustment factor correction amount is used to represent the degree of positive deviation between the demodulation rate adjustment factor and the demodulation rate adjustment factor set value. If not, the adjustment factor reference value is input into the demodulation rate mapping table to obtain the modulation and demodulation rate increase. Based on the current 5G shipborne terminal modulation and demodulation rate and the modulation and demodulation rate increase, the 5G shipborne terminal modulation and demodulation rate is coupled to obtain the adjusted 5G shipborne terminal modulation and demodulation rate. The adjustment factor reference value is used to indicate the degree of negative deviation between the demodulation rate adjustment factor and the demodulation rate adjustment factor set value. If the 5G signal receiving power is within the receiving power setting range, modulation and demodulation rate control will not be performed. The receiving power setting range refers to the closed interval formed by the lower limit of the receiving power setting and the upper limit of the receiving power setting.

4. The unmanned vessel parallel driving system based on a 5G remote cockpit according to claim 3, characterized in that, The determination of whether to perform modulation / demodulation rate control also includes: If the 5G signal received power is less than the set lower limit of received power, the transmission delay correction amount and the received power comparison amount are input into the demodulation rate mapping table to obtain the demodulation rate control factor. The received power comparison amount is used to reflect the degree of deviation between the set lower limit of received power and the 5G signal received power. Determine whether the demodulation rate control factor is greater than the demodulation rate control factor set value. If so, input the control factor correction amount into the demodulation rate mapping table to obtain the modulation and demodulation rate increase amount. Based on the current 5G shipborne terminal modulation and demodulation rate and the modulation and demodulation rate increase amount, perform superposition processing to obtain the adjusted 5G shipborne terminal modulation and demodulation rate. The control factor correction amount is used to represent the positive deviation of the demodulation rate control factor from the demodulation rate control factor set value. If not, the adjustment factor compensation amount is input into the demodulation rate mapping table to obtain the modulation and demodulation rate reduction amount. Based on the current 5G shipborne terminal modulation and demodulation rate and the modulation and demodulation rate reduction amount, the difference is processed to obtain the adjusted 5G shipborne terminal modulation and demodulation rate. The adjustment factor compensation amount is used to represent the degree of negative deviation between the demodulation rate adjustment factor and the set value of the demodulation rate adjustment factor.

5. The unmanned vessel parallel driving system based on a 5G remote cockpit according to claim 1, characterized in that, The specific process for determining whether to perform reception frequency adjustment based on the 5G cloud reception time interval is as follows: If the 5G cloud receiving time interval is lower than the set lower limit of the receiving time interval, the delay gradient correction amount and the receiving time interval correction amount are input into the receiving frequency mapping table to obtain the receiving frequency reduction amount. Based on the current cabin data receiving frequency and the receiving frequency reduction amount, the difference is processed to obtain the adjusted cabin data receiving frequency. The delay gradient correction amount is used to represent the degree of deviation between the cabin data receiving delay gradient exponent and the delay gradient reference value. The receiving time interval correction amount is used to represent the degree of negative deviation between the 5G cloud receiving time interval and the set lower limit of the receiving time interval. If the 5G cloud receiving time interval is within the receiving time interval setting range, then receiving frequency control will not be performed. The receiving time interval setting range is used to represent the closed interval formed by the lower limit of the receiving time interval setting and the upper limit of the receiving time interval setting. If the 5G cloud receiving time interval is higher than the upper limit of the receiving time interval, the delay gradient correction amount and the receiving time interval comparison amount are input into the receiving frequency mapping table to obtain the receiving frequency adjustment amount. Based on the current cabin data receiving frequency and the receiving frequency adjustment amount, the cabin data receiving frequency is coupled and processed to obtain the adjusted cabin data receiving frequency. The receiving time interval comparison amount is used to indicate the degree of positive deviation between the 5G cloud receiving time interval and the upper limit of the receiving time interval.

6. The unmanned vessel parallel driving system based on a 5G remote cockpit according to claim 1, characterized in that, The specific steps for determining whether to perform maximum task number threshold adjustment are as follows: If the domain controller task scheduling delay is lower than or equal to the scheduling delay setting, the maximum number of tasks threshold adjustment will not be executed. If the domain controller task scheduling delay is higher than the scheduling delay set value, the result of the harmonic averaging of the delay gradient correction and the scheduling delay reference value is input into the maximum task number mapping table for querying to obtain the maximum task number threshold reduction amount. The difference between the current domain controller maximum task number threshold and the maximum task number threshold reduction amount is processed to obtain the adjusted domain controller maximum task number threshold. The scheduling delay reference value is used to indicate the degree of deviation between the domain controller task scheduling delay and the scheduling delay set value.

7. A parallel driving method for unmanned vessels based on a 5G remote cockpit, wherein the parallel driving method for unmanned vessels based on a 5G remote cockpit applies the parallel driving system for unmanned vessels based on a 5G remote cockpit as described in any one of claims 1-6, characterized in that, include; The ship-side data transmission latency index is obtained by collecting ship-side data, which is used to quantify the timeliness from when the data packet is sent from the ship-side domain controller to when the data packet is successfully received by the 5G cloud. The ship-end data transmission delay index determines whether to perform ship-end data transmission timeliness control. If yes, a ship-end optimization status synchronization command is sent to the 5G cloud after ship-end data transmission timeliness control. If no, a ship-end optimization status synchronization command is sent directly to the 5G cloud. The ship-end data transmission timeliness control includes generation time window control and modulation / demodulation rate control. The cabin data reception delay parameter is obtained to obtain the cabin data reception delay gradient index, which is used to quantify the real-time performance of cabin data reception from ship-side control commands. Based on the cabin data reception delay gradient index, it is determined whether to perform cabin data reception real-time performance adjustment. If so, a cabin control result notification command is sent after cabin data reception real-time performance adjustment. If not, a cabin control result notification command is sent directly. The cabin data reception real-time performance adjustment includes reception frequency adjustment and maximum task number threshold adjustment.

8. An unmanned surface vessel (USV) for parallel driving based on a 5G remote cockpit, wherein the USV for parallel driving based on a 5G remote cockpit utilizes the parallel driving system for USVs as described in any one of claims 1-6, characterized in that... include: The ship end and the cabin end are defined as follows: the ship end includes a positioning module, a sensing module, a vision module, a battery management module, a propulsion system, a transmission mechanism, a domain controller, and a 5G shipborne terminal; the cabin end includes a remote cockpit, a display platform, and a cabin end server.

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