Unmanned ship narrow channel dynamic passage control system and control method thereof

Abstract

The invention discloses an unmanned ship narrow channel dynamic passage control system and a control method thereof. The system comprises an unmanned ship module, an Internet of Things communication module and an Internet of Things scheduling platform module. According to the invention, centralized cooperative scheduling of multiple unmanned ships is realized through an Internet of Things platform, virtual management is carried out on narrow channel resources in combination with a virtual electronic fence, and through accurate trajectory prediction and a scientific right-of-way decision-making mechanism, the narrow channel resources are optimized. The problems of collision risk and low efficiency caused by the lack of cooperation of the unmanned ship in a narrow channel in the prior art are solved. A conflict solution strategy of space exclusive occupation and first arrival and first obtaining is adopted, and fine control instructions such as authorized passing, waiting and speed regulation are matched, so that safe and orderly passing of multiple ships in a narrow channel is ensured; all modules of the system are clear in division of labor, communication is efficient, and the system is suitable for various multi-unmanned-ship collaborative operation scenes and has high practicability and popularization value.

Description

Technical Field

[0001] This invention relates to the field of dynamic passage control technology for unmanned vessels in narrow waterways, and in particular to a dynamic passage control system and control method for unmanned vessels in narrow waterways. Background Technology

[0002] With the widespread application of unmanned vessels in environmental monitoring, water conservancy inspection, logistics transportation, and water rescue, the scenarios of multiple unmanned vessels working together are increasing. In the operating area, there are often bottleneck areas such as bridges, sluices, and narrow waterways, which can usually only accommodate a single vessel or a limited number of vessels to pass through. Currently, most unmanned surface vessels (USVs) rely on onboard sensors for obstacle avoidance and navigation control. However, in narrow waterways, this obstacle avoidance method based on single-vehicle perception has significant drawbacks: 1. Perception limitations: Due to limited field of view, GPS signal drift, or multipath effects, onboard sensors may not be able to accurately predict whether there are other vessels in the waterway and their intentions before entering a narrow waterway; 2. Lack of coordination: Each vessel acts independently, lacking a global perspective for scheduling, which can easily lead to multiple vessels attempting to enter a narrow waterway simultaneously, creating a "deadlock" or collision risk; 3. Decision conflicts: Even if both vessels comply with international collision avoidance rules, in the absence of communication, they may misjudge the situation and take conflicting avoidance actions. In response to the above problems, this application proposes a dynamic passage control system and control method for unmanned vessels in narrow waterways. Summary of the Invention

[0003] Based on the technical problems existing in the background technology, the present invention proposes a dynamic passage control system and control method for unmanned vessels in narrow waterways.

[0004] The present invention proposes a dynamic passage control system for unmanned vessels in narrow waterways, comprising an unmanned vessel module, an Internet of Things (IoT) communication module, and an IoT scheduling platform module; The unmanned vessel module consists of multiple unmanned vessels with a unified standard motion control model. The unmanned vessel module includes a state perception unit, a first communication unit, and a control execution unit. The IoT communication module includes a communication network that uses 4G / 5G / radio / LoRa / satellite communication methods. It is responsible for transmitting the real-time status of the unmanned vessel back to the IoT scheduling platform module, and can also send decision control commands from the IoT platform to the unmanned vessel. The IoT scheduling platform module is responsible for storing maps of the unmanned vessel's navigation area and electronic fences for narrow channels, receiving status information from unmanned vessels, maintaining a global real-time unmanned vessel status list, and issuing scheduling navigation instructions to unmanned vessels globally based on the adjudication results of the right-of-way decision engine. It includes a data aggregation and processing unit, a map and narrow channel management unit, a right-of-way decision engine, and a motion instruction generation unit.

[0005] Preferably, the state perception unit includes GPS / BeiDou and IMU, used to collect its own position, speed and heading status data in real time, and the control execution unit includes a motion controller and a thruster, used to execute navigation control commands issued by the platform.

[0006] Preferably, the map and the narrow waterway management unit mark the boundary line of the narrow waterway on the high-precision electronic map in the form of polygons or line segments connected by key vertices, forming a virtual electronic fence, setting the initial state of the narrow waterway to "idle", and updating the waterway status in real time.

[0007] Preferably, the state sensing unit collects state data at a fixed period T_repor, and the data packet includes ship ID, timestamp, latitude and longitude (P_x, P_y), ground speed SOG, and ground heading COG.

[0008] Preferably, the right-of-way decision engine predicts the ship's position within a future timeframe T_predict based on the ship's current motion state using a trajectory prediction model. T_predict is 1.2-1.5 times the time required for the ship to enter the channel. The predicted position is calculated using the following formula: P_predicted_x=P_current_x+SOG*sin(COG)*T_predict; P_predicted_y=P_current_y+SOG*cos(COG)*T_predict; Where P_current_x and P_current_y are the current coordinates of the ship, and P_predicted_x and P_predicted_y are the predicted coordinates.

[0009] Preferably, the passage right decision engine follows the principles of "exclusive space" and "first come, first served". When it detects that the predicted path of a ship intersects with the electronic fence of a narrow channel, if the channel status is "idle", the channel is set to "occupied" and the ship is granted passage right; if the channel status is "occupied", the ship is added to the channel reservation queue.

[0010] Preferably, the control commands generated by the motion command generation unit include "authorized passage" commands, "waiting" commands, and "speed adjustment" commands. The "authorized passage" command includes the command type, channel ID, suggested speed, and maximum speed limit; the "waiting" command includes the command type, target waiting point (W_x, W_y), and stop / low-speed loitering requirements; and the "speed adjustment" command includes the command type and target speed.

[0011] This invention proposes a dynamic passage control method for unmanned vessels in narrow waterways, comprising the following steps: S1: System Initialization and Map Marking: Start the IoT scheduling platform module, load the high-precision electronic map, digitally mark the virtual electronic fence of the narrow waterway, initialize the waterway status to "idle", and create a global vessel status table and waterway reservation queue; S2: The unmanned vessel collects its own status data at fixed intervals through the status perception unit and uploads it to the IoT scheduling platform module in real time through the IoT communication module. S3: The platform data aggregation and processing unit updates the ship status table, and the right-of-way decision engine calculates the ship's future predicted position based on the trajectory prediction model, and uses the ray method to determine whether the predicted position or path intersects with the electronic fence of the narrow channel. S4: If the predicted path of a vessel intersects with the electronic fence, the vessel is considered to have the intention to enter, triggering a right-of-way request. The decision engine allocates the right-of-way based on the current state of the channel. S5: Channel occupancy conflicts are handled through a conflict resolution mechanism. The motion command generation unit generates corresponding control commands based on the decision results. The corresponding control commands include "authorization to pass", "wait" and "speed adjustment" commands. S6: The unmanned vessel receives and parses control commands, drives the thrusters to execute commands through the control execution unit, and sends confirmation information to the platform; S7: When the vessel has completely left the narrow channel electronic fence, the platform updates the channel status to "idle", retrieves the first vessel from the reservation queue and grants it the right of passage, updates the queue and issues instructions.

[0012] Preferably, in step S4, when allocating passage rights, if the channel status is "idle", the engine immediately sets the channel status to "occupied", records the occupant as the requesting vessel, and sends an "authorized passage" command to the requesting vessel. If the channel status is "occupied", it is determined whether the occupant is the requesting vessel itself. If so, the authorization is maintained; otherwise, the conflict resolution mechanism is triggered.

[0013] Preferably, in step S7, it is determined whether the vessel has completely left the narrow channel based on its current position data. The determination condition is IsPointInPolygon(Current_Position,Geofence)==False, where Geofence is the virtual electronic fence of the narrow channel.

[0014] Compared with existing technologies, the beneficial effects of this invention are: This invention enables centralized collaborative scheduling of multiple unmanned vessels through an IoT platform, and combines virtual electronic fences for virtualized management of narrow waterway resources. Through precise trajectory prediction and a scientific right-of-way decision-making mechanism, it solves the collision risks and inefficiencies caused by the lack of coordination among unmanned vessels in narrow waterways in existing technologies. It employs a conflict resolution strategy of "exclusive space allocation" and "first-come, first-served," coupled with refined control commands such as "authorized passage," "waiting," and "speed adjustment," ensuring the safe and orderly passage of multiple vessels in narrow waterways. The system's modules have clear division of labor and efficient communication, making it suitable for various multi-unmanned vessel collaborative operation scenarios, and possessing strong practicality and promotional value. Attached Figure Description

[0015] Figure 1 This is a block diagram of a dynamic passage control system for unmanned vessels in narrow waterways proposed in this invention; Figure 2 This is a timing diagram of a dynamic passage control method for unmanned vessels in narrow waterways proposed in this invention. Figure 3 This is a flowchart of a dynamic passage control method for unmanned vessels in narrow waterways proposed in this invention. Detailed Implementation

[0016] The present invention will be further explained below with reference to specific embodiments. Example

[0017] Reference Figure 1 This embodiment proposes a dynamic passage control system for unmanned vessels in narrow waterways, including an unmanned vessel module, an Internet of Things (IoT) communication module, and an IoT scheduling platform module. The unmanned vessel module consists of multiple unmanned vessels with a unified standard motion control model. The unmanned vessel module includes a state perception unit, a first communication unit, and a control execution unit. The state perception unit includes GPS / BeiDou and IMU, which are used to collect its own position, speed and heading status data in real time. The control execution unit includes motion controller and thruster, which are used to execute navigation control commands issued by the platform. The state awareness unit collects state data at a fixed period of T_repor. The data packet contains ship ID, timestamp, latitude and longitude (P_x, P_y), ground speed SOG, and ground heading COG. The IoT communication module includes a communication network that uses 4G / 5G / radio / LoRa / satellite communication methods. It is responsible for transmitting the real-time status of the unmanned vessel back to the IoT scheduling platform module, and can also send decision control commands from the IoT platform to the unmanned vessel. The IoT scheduling platform module is responsible for storing maps of the unmanned vessel navigation area and electronic fences for narrow channels, receiving status information of unmanned vessels, maintaining a global real-time unmanned vessel status list, and issuing scheduling navigation instructions to unmanned vessels globally based on the adjudication results of the right-of-way decision engine. It includes a data aggregation and processing unit, a map and narrow channel management unit, a right-of-way decision engine, and a motion instruction generation unit. The data aggregation and processing unit stores high-precision electronic maps of the operating waters and virtual electronic fence information for narrow channels; the map and narrow track management unit receives and processes all status data uploaded by unmanned vessels and maintains a global real-time vessel status table; the right-of-way decision engine manages the channel reservation queue and realizes the reasonable allocation of right-of-way through the right-of-way decision engine; the motion command generation unit generates control commands such as "authorized passage", "wait", and "speed adjustment" based on the decision results and issues them to the corresponding unmanned vessels; The map and narrow waterway management unit mark the boundary line of the narrow waterway on the high-precision electronic map in the form of polygons or line segments connected by key vertices, forming a virtual electronic fence, setting the initial state of the narrow waterway to "idle", and updating the waterway status in real time; The right-of-way decision engine predicts the ship's position within a future timeframe T_predict based on the ship's current motion state and using a trajectory prediction model. T_predict is 1.2-1.5 times the time required for the ship to enter the channel. The predicted position is calculated using the following formula: P_predicted_x=P_current_x+SOG*sin(COG)*T_predict; P_predicted_y=P_current_y+SOG*cos(COG)*T_predict; Where P_current_x and P_current_y are the current coordinates of the vessel, and P_predicted_x and P_predicted_y are the predicted coordinates; the right-of-way decision engine follows the principles of "exclusive space" and "first-come, first-served". When it detects that the predicted path of a vessel intersects with the electronic fence of a narrow channel, if the channel status is "idle", the channel will be set to "occupied" and the vessel will be granted the right of way; if the channel status is "occupied", the vessel will be added to the channel reservation queue. The control commands generated by the motion command generation unit include "authorized passage" commands, "waiting" commands, and "speed adjustment" commands. The "authorized passage" command includes the command type, channel ID, suggested speed, and maximum speed limit; the "waiting" command includes the command type, target waiting point (W_x, W_y), and stop / low-speed loitering requirements; and the "speed adjustment" command includes the command type and target speed.

[0018] Reference Figure 2-3 This embodiment also proposes a dynamic passage control method for unmanned vessels in narrow waterways, including the following steps: S1: System Initialization and Map Marking: Start the IoT scheduling platform module, load the high-precision electronic map, digitally mark the virtual electronic fence of the narrow waterway, initialize the waterway status to "idle", and create a global vessel status table and waterway reservation queue; S2: The unmanned vessel collects its own status data at fixed intervals through the status perception unit and uploads it to the IoT scheduling platform module in real time through the IoT communication module. S3: The platform data aggregation and processing unit updates the ship status table, and the right-of-way decision engine calculates the ship's future predicted position based on the trajectory prediction model, and uses the ray method to determine whether the predicted position or path intersects with the electronic fence of the narrow channel. S4: If the predicted path of a vessel intersects with the electronic fence, the vessel is considered to have the intention to enter and triggers a right-of-way request. The decision engine allocates the right-of-way based on the current status of the channel. When allocating the right-of-way, if the channel status is "idle", the engine immediately sets the channel status to "occupied" and records the occupant as the requesting vessel, and sends an "authorized passage" instruction to the requesting vessel. If the channel status is "occupied", it determines whether the occupant is the requesting vessel itself. If so, the authorization is maintained; otherwise, the conflict resolution mechanism is triggered. S5: Channel occupancy conflicts are handled through a conflict resolution mechanism. The motion command generation unit generates corresponding control commands based on the decision results. The corresponding control commands include "authorization to pass", "wait" and "speed adjustment" commands. S6: The unmanned vessel receives and parses control commands, drives the thrusters to execute commands through the control execution unit, and sends confirmation information to the platform; S7: When a vessel has completely left the narrow channel electronic fence, the platform updates the channel status to "idle", retrieves the first vessel from the reservation queue and grants it the right of passage, updates the queue and issues instructions. The determination of whether the vessel has completely left the narrow channel is based on the vessel's current position data. The determination condition is IsPointInPolygon(Current_Position,Geofence)==False, where Geofence is the virtual electronic fence of the narrow channel. The specific logical steps are as follows: S701: When the hull of a ship (release ship) completely leaves the virtual geofence of the target channel, the platform determines that it has left based on its location data; S702: The platform updates the channel status from "occupied" to "idle"; S703: Check the reservation queue for this channel. If the queue is not empty, take the vessel at the head of the queue, grant it the right of passage, set the channel status to "occupied", and send an "authorized passage" instruction to the vessel. S704: Both the released vessel and the newly authorized vessel have received the corresponding instructions, and the system enters the next control cycle.

[0019] This embodiment achieves centralized collaborative scheduling of multiple unmanned vessels through an IoT platform, and combines virtual electronic fences to virtualize the management of narrow waterway resources. Through accurate trajectory prediction and a scientific right-of-way decision-making mechanism, it solves the problems of collision risk and low efficiency caused by the lack of coordination among unmanned vessels in narrow waterways in existing technologies. It adopts a conflict resolution strategy of "space exclusive" and "first come, first served" and is equipped with refined control commands such as "authorized passage", "waiting", and "speed adjustment" to ensure the safe and orderly passage of multiple vessels in narrow waterways. The system has clear division of labor among its modules and efficient communication, and is suitable for various multi-unmanned vessel collaborative operation scenarios, with strong practicality and promotional value.

[0020] Additionally, it should be noted that a data structure needs to be defined before updating the ship's status, and the logical algorithm used is as follows: Python classShip: def__init__(self,id,position,heading,speed,radar_data): self.id=id#ship number self.position = position # Current position (x, y) self.heading=heading # Heading: 'outbound' (departure) or 'return' (return) self.speed=speed#current speed self.radar_data=radar_data#Millimeter-wave radar data: distance to the preceding ship self.status="moving" # Ship status: 'moving' or 'stopped' ``` Python classCloudPlatform: def__init__(self,narrow_area): self.ships={} # Stores all ship information {ship_id:Ship} self.narrow_area=narrow_area # Coordinates of the narrow area where ships can pass each other self.traffic_mode="normal" # Current traffic mode: 'normal' or 'emergency' self.waiting_ships=[] # Queues of ships waiting in a narrow area; The logical algorithm used when updating the ship's status is as follows: Python def update_ship_status(ship): """ Update ship status, including speed adjustments and status updates.

[0021] """ #Adjust speed based on radar data ifship.radar_data<5: ship.speed=max(0,ship.speed-0.1) #Slow down else: ship.speed=min(1.0,ship.speed+0.1)#Accelerate #Update ship position (simplified to linear motion) ifship.heading=='outbound': ship.position += ship.speed elifship.heading=='return': ship.position -= ship.speed returnship.

[0022] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A dynamic passage control system for unmanned vessels in narrow waterways, characterized in that, This includes unmanned vessel modules, IoT communication modules, and IoT scheduling platform modules; The unmanned vessel module consists of multiple unmanned vessels with a unified standard motion control model. The unmanned vessel module includes a state perception unit, a first communication unit, and a control execution unit. The IoT communication module includes a communication network that uses 4G / 5G / radio / LoRa / satellite communication methods. It is responsible for transmitting the real-time status of the unmanned vessel back to the IoT scheduling platform module, and can also send decision control commands from the IoT platform to the unmanned vessel. The IoT scheduling platform module is responsible for storing maps of the unmanned vessel's navigation area and electronic fences for narrow channels, receiving status information from unmanned vessels, maintaining a global real-time unmanned vessel status list, and issuing scheduling navigation instructions to unmanned vessels globally based on the adjudication results of the right-of-way decision engine. It includes a data aggregation and processing unit, a map and narrow channel management unit, a right-of-way decision engine, and a motion instruction generation unit.

2. The unmanned vessel dynamic passage control system for narrow waterways according to claim 1, characterized in that, The state perception unit includes GPS / BeiDou and IMU, which are used to collect its own position, speed and heading status data in real time. The control execution unit includes a motion controller and a thruster, which are used to execute navigation control commands issued by the platform.

3. The unmanned vessel dynamic passage control system for narrow waterways according to claim 1, characterized in that, The map and the narrow waterway management unit mark the boundary line of the narrow waterway on the high-precision electronic map through polygons or line segments connected by key vertices, forming a virtual electronic fence. The initial state of the narrow waterway is set to "idle", and the waterway status is updated in real time.

4. The unmanned vessel dynamic passage control system for narrow waterways according to claim 1, characterized in that, The state sensing unit collects state data at a fixed period of T_repor. The data packet includes ship ID, timestamp, latitude and longitude (P_x, P_y), ground speed SOG, and ground heading COG.

5. The unmanned vessel dynamic passage control system for narrow waterways according to claim 1, characterized in that, The right-of-way decision engine predicts the ship's position within a future timeframe T_predict based on the ship's current motion state and using a trajectory prediction model. T_predict is 1.2-1.5 times the time required for the ship to enter the channel. The predicted position is calculated using the following formula: P_predicted_x=P_current_x+SOG*sin(COG)*T_predict; P_predicted_y=P_current_y+SOG*cos(COG)*T_predict; Where P_current_x and P_current_y are the current coordinates of the ship, and P_predicted_x and P_predicted_y are the predicted coordinates.

6. The unmanned vessel dynamic passage control system for narrow waterways according to claim 1, characterized in that, The passage right decision engine follows the principles of "exclusive space" and "first come, first served". When it detects that the predicted path of a ship intersects with the electronic fence of a narrow channel, if the channel status is "idle", the channel is set to "occupied" and the ship is granted passage right; if the channel status is "occupied", the ship is added to the channel reservation queue.

7. The unmanned vessel dynamic passage control system for narrow waterways according to claim 1, characterized in that, The control commands generated by the motion command generation unit include "authorized passage" commands, "waiting" commands, and "speed adjustment" commands. The "authorized passage" command includes the command type, channel ID, suggested speed, and maximum speed limit; the "waiting" command includes the command type, target waiting point (W_x, W_y), and stop / low-speed loitering requirements; and the "speed adjustment" command includes the command type and target speed.

8. A method for dynamic passage control of unmanned vessels in narrow waterways, based on the system described in any one of claims 1-7, characterized in that, Includes the following steps: S1: System Initialization and Map Marking: Start the IoT scheduling platform module, load the high-precision electronic map, digitally mark the virtual electronic fence of the narrow waterway, initialize the waterway status to "idle", and create a global vessel status table and waterway reservation queue; S2: The unmanned vessel collects its own status data at fixed intervals through the status perception unit and uploads it to the IoT scheduling platform module in real time through the IoT communication module. S3: The platform data aggregation and processing unit updates the ship status table, and the right-of-way decision engine calculates the ship's future predicted position based on the trajectory prediction model, and uses the ray method to determine whether the predicted position or path intersects with the electronic fence of the narrow channel. S4: If the predicted path of a vessel intersects with the electronic fence, the vessel is considered to have the intention to enter, triggering a right-of-way request. The decision engine allocates the right-of-way based on the current state of the channel. S5: Channel occupancy conflicts are handled through a conflict resolution mechanism. The motion command generation unit generates corresponding control commands based on the decision results. The corresponding control commands include "authorization to pass", "wait" and "speed adjustment" commands. S6: The unmanned vessel receives and parses control commands, drives the thrusters to execute commands through the control execution unit, and sends confirmation information to the platform; S7: When the vessel has completely left the narrow channel electronic fence, the platform updates the channel status to "idle", retrieves the first vessel from the reservation queue and grants it the right of passage, updates the queue and issues instructions.

9. A method for dynamic passage control of unmanned vessels in narrow waterways according to claim 8, characterized in that, In S4, when allocating passage rights, if the channel status is "idle", the engine immediately sets the channel status to "occupied", records the occupant as the requesting vessel, and sends an "authorize passage" command to the requesting vessel. If the channel status is "occupied", it determines whether the occupant is the requesting vessel itself. If so, the authorization is maintained; otherwise, the conflict resolution mechanism is triggered.

10. A method for dynamic passage control of unmanned vessels in narrow waterways according to claim 8, characterized in that, In S7, it is determined whether the ship has completely left the narrow channel based on the ship's current position data. The determination condition is IsPointInPolygon(Current_Position,Geofence)==False, where Geofence is the virtual electronic fence of the narrow channel.

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