Port automatic transfer vehicle scheduling method and system

Abstract

The invention relates to the technical field of software systems, and particularly discloses a port automatic transfer vehicle scheduling method and a port automatic transfer vehicle scheduling system. And selecting to issue an instruction to the optimal unmanned container truck dragging head according to the operation time and the energy consumption, so that the unmanned container truck dragging head travels to the target area where the container with the corresponding container number in the storage yard is located according to the planned path to transfer the container in the harbor area. The method has the beneficial effects that a global optimal target can be obtained by calculating a time optimal target and an energy consumption optimal target and comprehensively calculating when an unmanned container truck head dragging task in a port is issued, and a scheduling instruction is preferentially issued for scheduling, so that the waiting time in the operation process is shortened, and the full load rate of the unmanned container truck head dragging during round trip is improved; and the scheduling efficiency of the unmanned container truck towing head is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of software systems, and in particular to a method and system for dispatching automated port transfer vehicles. Background Art

[0002] Port automation is an important part of the modern logistics system, aiming to improve port operation efficiency, reduce labor costs and enhance safety through advanced information technology and automation equipment. In the port automation system, vertical scheduling and horizontal transport scheduling are two core links. In port automation, horizontal transport scheduling mainly focuses on efficient management and path planning of internally used container trucks to ensure fast and accurate transfer of goods between the terminal front and the yard, as well as within the yard. However, when it comes to external container trucks entering the port, the existing system often has certain limitations. External container trucks bring additional challenges to port scheduling due to factors such as their diverse sources, uncertain arrival times, and inconsistent models of installed vehicle-side equipment.

[0003] The Chinese patent with application number: CN202311673798.1 provides a method and system for optimal path planning of vehicles in a smart port based on the Internet of Vehicles, including collecting data information contained in the smart port of the Internet of Vehicles, and using the data information as the input of the scheduling model; according to the scheduling model, it is divided into a multi-layer architecture, and each layer of the architecture is processed to create a scheduling model function; according to the scheduling model function, the number of layers of the navigation path of the vehicle container truck contained in the architecture is optimized by minimizing the path nodes to obtain the optimal path. The scheduling in the above patent adopts the minimization path optimization, which is only suitable for planning routes to minimize the vehicle's travel distance, but it is necessary to consider factors such as the operation process and waiting time. The shortest route does not mean the shortest operation. By introducing advanced prediction models and optimization algorithms, this application can further improve the port's processing capabilities for external container trucks, reduce waiting time, improve customer satisfaction, and enhance the overall operational efficiency of the port. Summary of the invention

[0004] The present invention proposes a port automated transfer vehicle dispatching method and system in order to solve the above-mentioned problems.

[0005] The technical solution of the present invention is achieved in this way:

[0006] The port automated transfer vehicle dispatching method comprises the following steps:

[0007] Step 1: Before the external container truck enters the port area, it makes an appointment through the appointment system. The TCS cloud control dispatching system generates a dispatching instruction based on the dispatching information. The dispatching instruction includes the operation type, container number, and destination;

[0008] Step 2: The TCS cloud-controlled dispatching system calculates the unmanned container trucks in the managed port area according to the dispatching instructions, and sends instructions to the optimal unmanned container truck based on the operation time and energy consumption, so that it drives to the target area where the container with the corresponding container number is located in the yard according to the planned path;

[0009] Step 3: The TCS cloud control dispatching system dispatches the gantry crane to load the containers in the target area of ​​the yard and transfer the containers with the corresponding container numbers to the empty trailers;

[0010] Step 4: The unmanned container truck arrives at the target area of ​​the yard according to the planned path, sends an arrival signal to the TCS cloud control dispatching system, and waits for the next instruction;

[0011] Step 5: According to the operation status of the gantry crane, the time it takes to complete the operation is simulated and calculated, and the waiting time T of the unmanned container tractor is determined to be greater than the set threshold value T0;

[0012] Step 6: If T>T0, the container truck resources are released, and the unmanned container truck tractor enters the queue to wait for the task to be issued again, and waits for the new task instruction to be issued again. At the same time, the TCS cloud control dispatching system issues an instruction to dispatch the unmanned container truck tractor to the nearest waiting area to wait for the next dispatch; if T<T0, the unmanned container truck tractor waits for the trailer to be loaded, and then automatically completes the connection with the trailer. After the connection is completed, a signal is sent to the TCS cloud control dispatching system to obtain the dispatch instruction to go to the destination where the external container truck is connected;

[0013] Step 7: The TCS cloud control dispatching system sends the planned path for the unmanned container tractor to reach the destination to the unmanned container tractor, and the unmanned container tractor drives to the destination at the transfer station according to the planned path;

[0014] Step 8: The unmanned container truck tractor arrives at the destination of the transfer station according to the planned route, and performs the automatic detachment action to realize the automatic separation of the unmanned container truck tractor and the trailer. The fully loaded trailer waits for the arrival of the external container truck for loading at the transfer station. The unmanned container truck tractor sends an arrival signal to the TCS cloud control dispatching system and waits for the next instruction;

[0015] Step 9: The TCS cloud control dispatching system calculates the waiting time T2 of the unmanned container tractor waiting for the towing task at the transfer station and the set threshold T1 according to the scheduled task;

[0016] Step 10: If T2>T1, the container truck resources are released, and the unmanned container truck tractor enters the queue to wait for the task to be issued again, and waits for the new task instruction to be issued again. At the same time, the TCS cloud control dispatching system issues an instruction to dispatch the unmanned container truck tractor to the nearest waiting area to wait for the next dispatch; if T2<T1, the unmanned container truck tractor waits at the transfer station to receive the towing instruction. If there are multiple tractors waiting, they will automatically queue up and wait according to the time when the signal is sent to the TCS cloud control dispatching system;

[0017] Step 11: After the container transported to the port by an external container truck at the transshipment terminal is transferred to the empty tractor through the gantry crane, the TCS cloud control dispatching system issues a towing task and selects the highest priority unmanned container truck tractor in the queue list to issue a dispatching instruction. After receiving the dispatching instruction, the unmanned container truck tractor at the transshipment terminal automatically connects with the target trailer. After the connection is completed, it sends a connection completion signal to the TCS cloud control dispatching system and waits for the next instruction;

[0018] Step 12: The TCS cloud control dispatching system sends the planned path for the unmanned container tractor to reach the destination to the unmanned container tractor, and the unmanned container tractor drives to the destination at the yard according to the planned path;

[0019] Step 13: After the unmanned container tractor arrives at the corresponding destination, it automatically performs the detachment task and detaches from the fully loaded trailer. The fully loaded trailer waits in the yard for the TCS cloud control dispatching system to dispatch the gantry crane to unload the container. At the same time, the unmanned container tractor sends a job completion instruction to the TCS cloud control dispatching system to release the container truck resources. The unmanned container tractor enters the queue waiting for the task to be issued again, and waits for the issuance of new task instructions again. At the same time, the TCS cloud control dispatching system sends an instruction to dispatch the unmanned container tractor to the nearest waiting area and wait for the next dispatch.

[0020] Furthermore, the calculation of the optimal unmanned container truck tractor in step 2 includes the following steps:

[0021] Step 2.1: The TCS cloud-controlled dispatching system obtains the status of all unmanned container truck tractors, the target trailer location, and the transfer location of the transfer station in the port area according to the dispatching instruction information, and obtains the unmanned container truck tractor queue list-a;

[0022] Step 2.2: Filter all unmanned container truck tractors in list-a. If they exist in the priority exclusion queue, remove the tractor from list-a to obtain the unmanned container truck tractor queue list-b;

[0023] Step 2.3: Scan the area within a radius of s meters where the container is to be loaded or unloaded to determine whether there is a parking area. If so, dispatch the first vehicle in the parking queue and output the corresponding unmanned container tractor number to facilitate the dispatch instruction to the tractor;

[0024] Step 2.4: Filter all unmanned container truck tractors in list-b, remove the unmanned container truck tractors whose distance from the target trailer is more than s meters, and obtain the unmanned container truck tractor queue list-c;

[0025] Step 2.5: Filter all unmanned container truck tractors in list-c, remove those with two instructions, and only keep those with zero or one instruction, to obtain the unmanned container truck tractor queue list-d;

[0026] Step 2.6: Filter all unmanned container truck tractors in list-d and calculate the power difference. If the value after deducting the power required for the operation from the remaining power is less than the set threshold value n%, remove the unmanned container truck tractor and obtain the unmanned container truck tractor queue list-e;

[0027] Step 2.7: Filter all unmanned container trucks in list-e, calculate the comprehensive dispatching time and energy consumption, and then calculate the dispatching parameters J of each unmanned container truck to determine the optimal dispatching target.

[0028]

[0029] Where Ti is the time required for the i-th tractor to reach the target position from the current time; Ei is the energy consumed by the i-th tractor to reach the target trailer position from the current position; a is the time conversion coefficient, the unit is 1 / second; b is the energy consumption conversion coefficient, the unit is 1 / (kW*h);

[0030] Step 2.8: Compare the dispatching parameters of all unmanned container truck tractors in the queue list-e, obtain the unmanned container truck tractor with the smallest J value as the optimal dispatching target and output its number to facilitate issuing dispatching instructions to the tractor.

[0031] Furthermore, the state of the unmanned container truck tractor obtained in step 2.1 includes the location, power level, and mileage information of the container truck tractor.

[0032] Furthermore, in step 2.7, the calculation of the optimal scheduling target includes two calculation steps: single operation optimality and global operation optimality.

[0033] 2.71. Optimal calculation for a single operation: Calculate Ji = min (a*Ti + b*Ti) of each unmanned container tractor within a radius of s meters in turn. First calculate the time and energy consumption required from the start of the dispatch to the estimated completion of the operation, and take the minimum value of (a*Ti + b*Ei). The calculation formula is as follows:

[0034] ∑ Ti =△Tr+△Te+△Ts;

[0035] ∑ Ei=△Er+△Ee+△Es;

[0036] in,

[0037] ∑ Ti is the comprehensive dispatching time; △Tr is the driving time required for the unmanned container tractor to reach the operation point and execute the operation command. If the tractor has no operation command, △Tr is 0; △Te is the sum of the operation time of the gantry crane transferring the container to the trailer and the unmanned container tractor and the trailer automatically connecting; △Ts is the estimated driving time for the unmanned container tractor to drive to the destination according to the planned route;

[0038] ∑ Ei is the comprehensive dispatching energy consumption; △Er is the driving energy consumption required for the unmanned container tractor to arrive at the operation point and execute the operation command. If the tractor has no operation command, △Er is 0; △Ee is the sum of the energy consumption of the gantry crane transferring the container to the trailer and the unmanned container tractor and the trailer automatically hooking up; △Es is the estimated driving energy consumption of the unmanned container tractor to the destination according to the planned route;

[0039] 2.72. Global operation optimal calculation: sum up the optimal objectives of all operation processes, obtain the global optimal scheduling and the minimum sum of all single operations,

[0040]

[0041] Furthermore, in step 2.8, if the J values ​​of two unmanned container truck tractors are equal, the unmanned container truck tractor located at the first calculation order is selected as the optimal scheduling target.

[0042] The present invention also discloses a port automated transport vehicle dispatching system, comprising a data acquisition module, a monitoring module, a dispatching engine module, an instruction interaction module, and a basic data resource library.

[0043] The data acquisition module continuously maintains communication with the unmanned container tractor at a predetermined frequency, collecting vehicle operation status, task progress, and related environmental parameters in real time;

[0044] The monitoring module is used to monitor the status of all trucks and tractors in the field and maintain the updates of various queues;

[0045] The dispatch engine module dispatches the best transport vehicle and plans the best driving route based on high-precision maps, vehicle operation tasks, and vehicle status;

[0046] The command interaction module is used to connect to the TCS cloud control dispatch system and unmanned container truck tractors for command interaction;

[0047] The basic data resource library includes high-precision map resources, equipment library, operation rule library, and warning rule library, providing data support for the simulation operation of the business.

[0048] By adopting the above technical scheme, the beneficial effects of the present invention are as follows: when issuing unmanned container truck tractor tasks in the port, the global optimal target can be obtained by calculating the optimal time target and the optimal energy consumption target and performing comprehensive calculations to give priority to issuing scheduling instructions for scheduling, thereby reducing the waiting time during the operation and increasing the full load rate of the unmanned container truck tractor during the round trip, thereby improving the scheduling efficiency of the unmanned container truck tractor. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 This is a flow chart of the operation completed by the unmanned container truck tractor of the present invention;

[0051] Figure 2 This is a schematic diagram of the segmented operation of the unmanned container truck tractor of the present invention;

[0052] Figure 3 Schematic diagram of the position of the unmanned container truck tractor in an embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram of the route simulation planning of the unmanned container truck tractor of the present invention;

[0054] Figure 5 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] like Figure 1 As shown, when an external container truck reserves the task of delivering a container to a port and taking away the container through a reservation system, the port automated transfer vehicle scheduling method includes the following steps:

[0057] Step 1: Before the external container truck enters the port area, it makes an appointment through the appointment system. The TCS cloud control dispatching system generates a dispatching instruction based on the dispatching information to transfer the trailer [TC001] at the target location Q1 to the transfer station [Z01], and then returns from the transfer station [Z01] to [B01];

[0058] Step 2: The TCS cloud-controlled dispatching system calculates the unmanned container trucks in the managed port area according to the dispatching instructions, and sends instructions to the optimal unmanned container truck based on the operation time and energy consumption, so that it drives to the target area Q1 point where the container with the corresponding container number in the yard is located according to the planned path;

[0059] like Figure 2 As shown in the figure, when the unmanned container tractor T1003 is operating, taking the yard as the starting point, the operation can be divided into:

[0060] The first section: the distance between the unmanned container truck tractor and the operating point D1 (there is no such section when there is no operating instruction);

[0061] The second section: Truck collection operation D2 (no such section when there is no operation instruction);

[0062] The third section: collect cards and go to the target area D3;

[0063] The fourth section: The container truck starts from the target area and drives to the transfer area D4;

[0064] The fifth section: The container truck returns to the yard area D5 from the transfer area as the starting point;

[0065] Since D4 and D5 are the same for any dispatched truck path, it is only necessary to require the minimum value of J among D1, D2, and D3.

[0066] Step 2.1: The TCS cloud-controlled dispatching system obtains the status of all unmanned container truck tractors, the target trailer location, and the transfer location of the transfer station in the port area according to the dispatching instruction information, and obtains the unmanned container truck tractor queue list-a. The obtained unmanned container truck tractor status includes the location, power, and mileage information of the container truck tractor;

[0067] The distribution locations of unmanned container tractors in the port area are as follows: Figure 3 As shown:

[0068] T1001 tractor position P1, tractor is not connected, operation instruction is being executed;

[0069] T1002 tractor position P2, tractor connected, operation instruction in progress;

[0070] T1003 tractor position P3, tractor connected, operation instruction in progress;

[0071] T1004 tractor position P4, tractor is not connected and not operating;

[0072] T1005 tractor position P5, tractor is not connected and not operating;

[0073] T1006 Tractor position P6, tractor connected, operation instruction in progress.

[0074] Step 2.2: Filter all unmanned container truck tractors in list-a. If they exist in the priority exclusion queue, remove the tractor from list-a to obtain the unmanned container truck tractor queue list-b. In this embodiment, there is no container truck tractor that is prioritized for exclusion.

[0075] Step 2.3: Scan the radius of the container position to be loaded and unloaded within s (s = 300) meters to determine whether there is a parking area. If so, dispatch the first vehicle in the parking queue and output the corresponding unmanned container truck tractor number to facilitate the dispatch instruction to the tractor. In this embodiment, the parking area is not included within 300 meters;

[0076] Step 2.4: Filter all unmanned container trucks in list-b and obtain them through distance measurement calculation:

[0077] S1(P1,O1)=450m(meter);

[0078] S2(P2,O1)=297m(meter);

[0079] S3(P3,O1)=171m(meter);

[0080] S4(P4,O1)=243m(meters);

[0081] S5(P5,O1)=299m(meters);

[0082] S6(P6,O1)=312m(meters);

[0083] Remove the unmanned container tractors T1001 and T1006 whose distance from the target trailer is more than 300 meters, and obtain the unmanned container tractor queue list-c. In the queue list-c, position P2 T1002, position P3 T1003, position P4 T1004, and position P5 T1005 are reserved for scheduling;

[0084] Step 2.5: Filter all unmanned container truck tractors in list-c, remove the unmanned container truck tractors with two instructions, and only keep the unmanned container truck tractors with zero or one instruction, to obtain the unmanned container truck tractor queue list-d. In this embodiment, no unmanned container truck tractors with two instructions are included within 300 meters;

[0085] Step 2.6: Filter all unmanned container truck tractors in list-d and calculate the power difference. If the value after deducting the power required for the operation from the remaining power is less than the set threshold of 20%, remove the unmanned container truck tractor T1004 and obtain the unmanned container truck tractor queue list-e. In the queue list-e, P2 position T1002, P3 position T1003, and P5 position T1005 are reserved for scheduling;

[0086] Step 2.7: Filter all unmanned container trucks in list-e, calculate the comprehensive dispatching time and energy consumption, and then calculate the dispatching parameters J of each unmanned container truck to determine the optimal dispatching target.

[0087]

[0088] Among them, Ti is the time required for the i-th tractor to reach the target position from the current time; Ei is the energy consumed by the i-th tractor to reach the target trailer position from the current position; a is the time conversion coefficient, the unit is 1 / second; b is the energy consumption conversion coefficient, the unit is 1 / (kW*h). The path of the tractor to reach the target position is as follows Figure 4 As shown;

[0089] The calculation of the optimal scheduling target includes two calculation steps: single operation optimization and global operation optimization.

[0090] 2.71. Optimal calculation for a single operation:

[0091] Calculate Ji = min (a*Ti + b*Ti) of each unmanned container tractor within the radius of s meters in turn. First calculate the time and energy consumption required from the scheduling initiation time to the estimated completion of the operation, and take the minimum value of (a*Ti + b*Ei). The calculation formula is as follows:

[0092] ∑ Ti =△Tr+△Te+△Ts;

[0093] Among them, ∑Ti is the comprehensive dispatching time; △Tr is the driving time required for the unmanned container tractor to reach the operation point and execute the operation command. If the tractor has no operation command, △Tr is 0; △Te is the sum of the operation time of the gantry crane transferring the container to the trailer and the unmanned container tractor and the trailer automatically connecting; △Ts is the estimated driving time for the unmanned container tractor to drive to the destination according to the planned route;

[0094] ∑ Ei =△Er+△Ee+△Es;

[0095] Among them, ∑Ei is the comprehensive dispatching energy consumption; △Er is the driving energy consumption required for the unmanned container tractor to arrive at the operation point and execute the operation command. If the tractor has no operation command, △Er is 0; △Ee is the sum of the operating energy consumption of the gantry crane transferring the container to the trailer and the unmanned container tractor and the trailer automatically hooking up; △Es is the estimated driving energy consumption of the unmanned container tractor to drive to the destination according to the planned route;

[0096] 2.72. Global operation optimal calculation: sum up the optimal objectives of all operation processes, obtain the global optimal scheduling and the minimum sum of all single operations,

[0097]

[0098] The calculation results of each unmanned container tractor are as follows:

[0099]

[0100] Step 2.8: Compare the dispatch parameters of all unmanned container truck tractors in queue list-e, obtain the unmanned container truck tractor T1002 with the smallest J value as the optimal dispatch target and output its number, so as to facilitate the dispatch instruction to the tractor;

[0101] Step 3: The TCS cloud control dispatching system dispatches the gantry crane to load the containers in the target area Q1 of the yard and transfer the containers with the corresponding container numbers to the empty trailer TC001;

[0102] Step 4: The unmanned container truck tractor T1002 arrives at the target area Q1 of the yard according to the planned path, and sends an arrival signal to the TCS cloud control dispatching system, waiting for the next instruction;

[0103] Step 5: According to the operation status of the gantry crane, the time for the gantry crane to complete the operation is simulated and calculated, and the waiting time T of the unmanned container tractor T1002 is determined to be greater than the set threshold value T0;

[0104] Step 6: In this embodiment, T<T0 is set, the unmanned container tractor T1002 waits for the trailer TC001 to complete loading, and then automatically completes the connection with the trailer TC001. After the connection is completed, a signal is sent to the TCS cloud control dispatching system to obtain the dispatching instruction to the destination Z01 to connect with the external container truck;

[0105] Step 7: The TCS cloud control dispatching system sends the planned path for the unmanned container tractor T1002 to reach the destination to the unmanned container tractor T1002, and the unmanned container tractor T1002 drives to the destination Z01 located at the transfer station according to the planned path;

[0106] Step 8: The unmanned container tractor T1002 arrives at the destination Z01 of the transfer station according to the planned route, and performs the automatic detachment action to realize the automatic separation of the unmanned container tractor T1002 and the trailer TC001. The fully loaded trailer TC001 waits for the arrival of the external container truck at the transfer station. The unmanned container tractor T1002 sends an arrival signal to the TCS cloud control dispatching system and waits for the next instruction;

[0107] Step 9: The TCS cloud control dispatching system calculates the waiting time T2 of the unmanned container tractor T1002 waiting for the towing task at the transfer station and the set threshold T1 according to the scheduled task;

[0108] Step 10: If T2>T1, the container truck resources are released, and the unmanned container truck tractor enters the queue to wait for the task to be issued again, and waits for the new task instruction to be issued again. At the same time, the TCS cloud control scheduling system issues an instruction to dispatch the unmanned container truck tractor to the nearest waiting area and wait for the next scheduling; if T2<T1, the unmanned container truck tractor waits at the transfer station to receive the towing instruction. If there are multiple tractors waiting, they will automatically queue up and wait according to the time when the signal is sent to the TCS cloud control scheduling system. In this embodiment, T2>T1, the container truck resources are released and wait for the next scheduling.

[0109] like Figure 5 As shown, the present invention also discloses a port automated transfer vehicle dispatching system, including a data acquisition module, a monitoring module, a dispatching engine module, an instruction interaction module, and a basic data resource library.

[0110] The data acquisition module continuously maintains communication with the unmanned container tractor at a predetermined frequency, collecting vehicle operation status, task progress, and related environmental parameters in real time;

[0111] The monitoring module is used to monitor the status of all truck tractors in the field and maintain the updates of various queues, such as facilitating the discovery of queues with faults during operation;

[0112] The scheduling engine module schedules the best transport vehicle and plans the best driving route based on high-precision maps, vehicle operation tasks, and vehicle status. The vehicle status includes the vehicle's location, whether there is a task, the estimated completion time of the current task, and the estimated energy consumption required to complete the next task.

[0113] The command interaction module is used to connect to the TCS cloud control dispatch system and unmanned container truck tractors for command interaction;

[0114] The basic data resource library includes high-precision map resources, equipment library, operation rule library, and warning rule library, providing data support for the simulation operation of the business.

[0115] The unmanned container truck tractor used in the present application is an electric-driven container truck tractor equipped with a GPS positioning module, and has a traction head capable of automatically towing and hooking. The container truck tractor is prior art and will not be described in detail.

[0116] The port area is divided into a container yard, a transshipment station for exchanging containers between internal and external container trucks, and a parking area for unmanned container truck tractors. There are multiple parking areas, each close to the yard and the transshipment station.

[0117] Components not described in detail herein are prior art.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for dispatching automated port transfer vehicles, characterized in that: The following steps are involved: Step 1: Before the external container truck enters the port area, it makes an appointment through the appointment system. The TCS cloud control dispatching system generates a dispatching instruction based on the dispatching information. The dispatching instruction includes the operation type, container number, and destination; Step 2: The TCS cloud-controlled dispatching system calculates the unmanned container trucks in the managed port area according to the dispatching instructions, and sends instructions to the optimal unmanned container truck based on the operation time and energy consumption, so that it drives to the target area where the container with the corresponding container number is located in the yard according to the planned path; Step 3: The TCS cloud control dispatching system dispatches the gantry crane to load the containers in the target area of ​​the yard and transfer the containers with the corresponding container numbers to the empty trailers; Step 4: The unmanned container truck arrives at the target area of ​​the yard according to the planned path, sends an arrival signal to the TCS cloud control dispatching system, and waits for the next instruction; Step 5: According to the operation status of the gantry crane, the time it takes to complete the operation is simulated and calculated, and the waiting time T of the unmanned container tractor is determined to be greater than the set threshold value T0; Step 6: If T>T0, the container truck resources are released, and the unmanned container truck tractor enters the queue to wait for the task to be issued again, waiting for the new task instruction to be issued again. At the same time, the TCS cloud control dispatching system sends instructions to dispatch the unmanned container truck tractor to the nearest waiting area to wait for the next dispatch; If T<T0, the unmanned container truck tractor waits for the trailer to be loaded, and then automatically connects with the trailer. After the connection is completed, it sends a signal to the TCS cloud control dispatching system to obtain the dispatching instruction to the destination where the external container truck is connected; Step 7: The TCS cloud control dispatching system sends the planned path for the unmanned container tractor to reach the destination to the unmanned container tractor, and the unmanned container tractor drives to the destination at the transfer station according to the planned path; Step 8: The unmanned container truck tractor arrives at the destination of the transfer station according to the planned route, and performs the automatic detachment action to realize the automatic separation of the unmanned container truck tractor and the trailer. The fully loaded trailer waits for the arrival of the external container truck for loading at the transfer station. The unmanned container truck tractor sends an arrival signal to the TCS cloud control dispatching system and waits for the next instruction; Step 9: The TCS cloud control dispatching system calculates the waiting time T2 of the unmanned container tractor waiting for the towing task at the transfer station and the set threshold T1 according to the scheduled task; Step 10: If T2>T1, the container truck resources are released, and the unmanned container truck tractor enters the queue to wait for the task to be issued again, and waits for the new task instruction to be issued again. At the same time, the TCS cloud control dispatching system issues an instruction to dispatch the unmanned container truck tractor to the nearest waiting area to wait for the next dispatch; if T2<T1, the unmanned container truck tractor waits at the transfer station to receive the towing instruction. If there are multiple tractors waiting, they will automatically queue up and wait according to the time when the signal is sent to the TCS cloud control dispatching system; Step 11: After the container transported to the port by an external container truck at the transshipment terminal is transferred to the empty tractor through the gantry crane, the TCS cloud control dispatching system issues a towing task and selects the highest priority unmanned container truck tractor in the queue list to issue a dispatching instruction. After receiving the dispatching instruction, the unmanned container truck tractor at the transshipment terminal automatically connects with the target trailer. After the connection is completed, it sends a connection completion signal to the TCS cloud control dispatching system and waits for the next instruction; Step 12: The TCS cloud control dispatching system sends the planned path for the unmanned container tractor to reach the destination to the unmanned container tractor, and the unmanned container tractor drives to the destination at the yard according to the planned path; Step 13: After the unmanned container tractor arrives at the corresponding destination, it automatically performs the detachment task and detaches from the fully loaded trailer. The fully loaded trailer waits in the yard for the TCS cloud control dispatching system to dispatch the gantry crane to unload the container. At the same time, the unmanned container tractor sends a job completion instruction to the TCS cloud control dispatching system to release the container truck resources. The unmanned container tractor enters the queue waiting for the task to be issued again, and waits for the issuance of new task instructions again. At the same time, the TCS cloud control dispatching system sends an instruction to dispatch the unmanned container tractor to the nearest waiting area and wait for the next dispatch.

2. The port automated transfer vehicle dispatching method according to claim 1, characterized in that: The calculation of the optimal unmanned container truck tractor in step 2 comprises the following steps: Step 2.1: The TCS cloud control dispatching system obtains the status of all unmanned container truck tractors, the target trailer location, and the transfer location of the transfer station in the port area according to the dispatching instruction information, and obtains the unmanned container truck tractor queue list-a; Step 2.2: Filter all unmanned container truck tractors in list-a. If they exist in the priority exclusion queue, remove the tractor from list-a to obtain the unmanned container truck tractor queue list-b; Step 2.3: Scan the area within a radius of s meters where the container is to be loaded or unloaded to determine whether there is a parking area. If so, dispatch the first vehicle in the parking queue and output the corresponding unmanned container tractor number to facilitate the dispatch instruction to the tractor; Step 2.4: Filter all unmanned container truck tractors in list-b, remove the unmanned container truck tractors whose distance from the target trailer is more than s meters, and obtain the unmanned container truck tractor queue list-c; Step 2.5: Filter all unmanned container truck tractors in list-c, remove those with two instructions, and only keep those with zero or one instruction, to obtain the unmanned container truck tractor queue list-d; Step 2.6: Filter all unmanned container truck tractors in list-d and calculate the power difference. If the value after deducting the power required for the operation from the remaining power is less than the set threshold value n%, remove the unmanned container truck tractor and obtain the unmanned container truck tractor queue list-e; Step 2.7: Filter all unmanned container trucks in list-e, calculate the comprehensive dispatching time and energy consumption, and then calculate the dispatching parameters J of each unmanned container truck to determine the optimal dispatching target. Where Ti is the time required for the i-th tractor to reach the target position from the current time; Ei is the energy consumed by the i-th tractor to reach the target trailer position from the current position; a is the time conversion coefficient, the unit is 1 / second; b is the energy consumption conversion coefficient, the unit is 1 / (kW*h); Step 2.8: Compare the dispatching parameters of all unmanned container truck tractors in the queue list-e, obtain the unmanned container truck tractor with the smallest J value as the optimal dispatching target and output its number to facilitate issuing dispatching instructions to the tractor.

3. The port automated transfer vehicle dispatching method according to claim 2, characterized in that: The state of the unmanned container truck tractor obtained in step 2.1 includes the location, power level, and mileage information of the container truck tractor.

4. The port automated transfer vehicle dispatching method according to claim 2, characterized in that: In step 2.7, the calculation of the optimal scheduling target includes two calculation steps: single operation optimality and global operation optimality. 2.

71. Optimal calculation for a single operation: Calculate Ji = min (a*Ti + b*Ti) of each unmanned container tractor within the radius of s meters in turn. First calculate the time and energy consumption required from the scheduling initiation time to the estimated completion of the operation, and take the minimum value of (a*Ti + b*Ei). The calculation formula is as follows: ∑ Ti =△Tr+△Te+△Ts; ∑ Ei =△Er+△Ee+△Es; Among them, ∑Ti is the comprehensive dispatching time; △Tr is the driving time required for the unmanned container tractor to arrive at the operation point to execute the operation command. If the tractor has no operation command, △Tr is 0; △Te is the sum of the operation time when the gantry crane transfers the container to the trailer and the unmanned container tractor and the trailer are automatically connected; △Ts is the estimated driving time for the unmanned container tractor to travel to the destination according to the planned path; ∑Ei is the comprehensive dispatching energy consumption; △Er is the driving energy consumption required for the unmanned container tractor to arrive at the operation point to execute the operation command. If the tractor has no operation command, △Er is 0; △Ee is the sum of the operation energy consumption when the gantry crane transfers the container to the trailer and the unmanned container tractor and the trailer are automatically connected; △Es is the estimated driving energy consumption of the unmanned container tractor to travel to the destination according to the planned path; 2.

72. Global operation optimal calculation: sum up the optimal objectives of all operation processes, obtain the global optimal scheduling and the minimum sum of all single operations, 5. The port automated transfer vehicle dispatching method according to claim 2, characterized in that: In step 2.8, if there are two unmanned container truck tractors with the same J value, the unmanned container truck tractor at the first calculation order is selected as the optimal scheduling target.

6. A port automated transshipment vehicle dispatching system, based on the port automated transshipment vehicle dispatching method according to any one of claims 1 to 6, characterized in that: Including data acquisition module, monitoring module, scheduling engine module, instruction interaction module, basic data resource library, The data acquisition module continuously maintains communication with the unmanned container tractor at a predetermined frequency, collecting vehicle operation status, task progress, and related environmental parameters in real time; The monitoring module is used to monitor the status of all trucks and tractors in the field and maintain the updates of various queues; The dispatch engine module dispatches the best transport vehicle and plans the best driving route based on high-precision maps, vehicle operation tasks, and vehicle status; The command interaction module is used to connect to the TCS cloud control dispatch system and unmanned container truck tractors for command interaction; The basic data resource library includes high-precision map resources, equipment library, operation rule library, and warning rule library, providing data support for the simulation operation of the business.

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