WO2024011886A1

WO2024011886A1 - Carrier moving path optimization method and apparatus, and electronic device

Info

Publication number: WO2024011886A1
Application number: PCT/CN2023/073059
Authority: WO
Inventors: 翁端文; 褚如昶; 吕新
Original assignee: 浙江衣拿智能科技股份有限公司
Priority date: 2022-07-12
Filing date: 2023-01-19
Publication date: 2024-01-18
Also published as: CN115293675A

Abstract

Disclosed in the present invention are a carrier moving path optimization method and apparatus, and an electronic device. The method comprises: determining a target conveying place of a target carrier, and calculating a target carrier moving path of the target carrier on the basis of the current position of the target carrier and the target conveying place; determining a node road section corresponding to each key node in the target carrier moving path; and, when the target carrier moves to a node road section, recalculating the target carrier moving path on the basis of the current position and the target conveying place, and controlling the target carrier to move on the basis of the recalculated target carrier moving path. After calculating a target carrier moving path having the optimal conveying efficiency by means of the current position of and a target conveying place of a target carrier, the present application recalculates the optimal path every time the target carrier passes through a key node.

Description

Optimization method, device and electronic equipment for vehicle movement path

Technical field

This application relates to the field of automatic control technology, specifically, to an optimization method, device and electronic equipment for a vehicle movement path.

Background technique

In existing clothing production lines, hanging vehicles are controlled by a single line, that is, each production line is independently produced and controlled. With the development of the industry, factories are getting larger and larger, and the production efficiency of a single production line can no longer meet production needs. There are as many as dozens of hanging lines for clothing in the factory area, and the production lines need to coordinate production. This requires carriers to be transported on various production lines. However, the current carrier transportation control method is relatively single and fixed. The carrier transmission efficiency between multiple production lines is not high, and the transportation time during the transmission process is long.

Contents of the invention

In order to solve the above problems, embodiments of the present application provide a method, device and electronic device for optimizing a vehicle movement path.

In a first aspect, embodiments of the present application provide a method for optimizing a vehicle movement path. The method includes:
Determine the target transportation location of the target vehicle, and calculate the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location;
Determine the node sections corresponding to each key node in the movement path of the target vehicle, where the key node is a transition transportation node between two adjacent production lines;
When the target vehicle moves to the node section, the target vehicle moving path is recalculated based on the current position and the target transportation location, and the target vehicle moving path is controlled based on the recalculated target vehicle moving path. The target vehicle moves.

Preferably, calculating the target vehicle movement path of the target vehicle based on the current position of the target vehicle and the target transportation location includes:
Determine all candidate vehicle movement paths based on the current location of the target vehicle and the target transportation location, where the candidate vehicle movement paths include at least one production line;
Calculate the total weight score of each candidate vehicle movement path based on the weight score corresponding to each preset weight parameter;
The candidate vehicle movement path with the highest total weight score is determined as the target vehicle movement path.

Preferably, all candidate vehicle movement paths are determined based on the current location of the target vehicle and the target transportation location, and the candidate vehicle movement paths include at least one production line, including:
Determine each production line between the current location of the target vehicle and the target transportation location and the bridging station between each of the production lines;
Combining each of the production lines and bridging stations in order of distance corresponding to the current position of the target vehicle to generate a candidate vehicle movement path;
Repeat the step of combining the production lines and bridging stations in order of distance corresponding to the current position of the target vehicle until all candidate vehicle movement paths covering all combinations are generated.

Preferably, the preset weight parameters include the current congestion situation of the production line, the number of production lines and the theoretical passage time of the path;
Calculating the total weight score of each candidate vehicle movement path based on the weight score corresponding to each preset weight parameter includes:
Determine the upper limit number of vehicles and the actual number of vehicles for each production line in the candidate vehicle movement path, and determine the first weight score based on the ratio of the actual number of vehicles to the upper limit number of vehicles, and the ratio is used to Characterize the current congestion situation of the production line;
Determine a second weight score based on the number of production lines in the candidate vehicle movement path;
Determine the theoretical transit time of each production line and bridge station in the candidate vehicle movement path, accumulate the theoretical transit time of each unit, obtain the theoretical transit time of the path, and correspond to the theoretical transit time based on the path theory The duration range determines the third weight score;
Calculate the sum of the first weight score, the second weight score and the third weight score to obtain the total weight score of the candidate vehicle movement path.

Preferably, when the target vehicle moves to the node section, the target vehicle moving path is recalculated based on the current position and the target transportation location, and the target vehicle movement path is recalculated based on the recalculated target vehicle. The movement path controls the movement of the target vehicle, including:
When the target vehicle moves to the node section, continue to repeatedly calculate the target vehicle movement path based on the current position and the target transportation location until the target vehicle leaves the node section;
Control the movement of the target vehicle based on the last calculated movement path of the target vehicle.

Preferably, the step of continuously and repeatedly calculating the movement path of the target vehicle based on the current location and the target transportation location until the target vehicle leaves the node section further includes:
Compare the moving paths of each target vehicle, determine repeated paths, and increase the credibility score of the production line corresponding to the repeated paths;
When there are multiple target vehicle movement paths with the same total weight score during the subsequent calculation of the target vehicle movement path, the target vehicle movement path with the highest total credibility score is selected.

In a second aspect, embodiments of the present application provide a device for optimizing a carrier movement path, which device includes:
A calculation module configured to determine the target transportation location of the target vehicle and calculate the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location;
A determination module used to determine the node sections corresponding to each key node in the target vehicle movement path, where the key node is a transition transportation node between two adjacent production lines;
A control module configured to recalculate the movement path of the target vehicle based on the current position and the target transportation location when the target vehicle moves to the node section, and based on the recalculated target vehicle The movement path controls the movement of the target vehicle.

In a third aspect, embodiments of the present application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the first Method steps provided by any possible implementation manner of the aspect or the first aspect.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program implements the first aspect or any possible implementation of the first aspect. method provided.

The beneficial effects of the present invention are: after calculating the moving path of the target vehicle with optimal transportation efficiency through the current position of the target vehicle and the target transportation location, the optimal path will be recalculated every time it passes through a key node, so as to ensure the smooth operation of the transportation process. During the process, the transportation route is continuously optimized to ensure that the transmission efficiency of the vehicle can continue to be maintained at the highest level during the dynamic changes of the suspension system.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. Those of ordinary skill in the art can also obtain other drawings based on these drawings without exerting creative efforts.

Figure 1 is a schematic flowchart of a method for optimizing a vehicle movement path provided by an embodiment of the present application;
Figure 2 is a schematic structural diagram of a vehicle movement path optimization device provided by an embodiment of the present application;
FIG. 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

Implementation

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application.

In the following introduction, the terms “first” and “second” are used for descriptive purposes only and shall not be understood as indicating or implying relative importance. The following description provides multiple embodiments of the present application. Different embodiments can be replaced or combined. Therefore, the present application can also be considered to include all possible combinations of the same and/or different embodiments described. Thus, if one embodiment contains features A, B, C, and another embodiment contains features B, D, then the application should also be considered to include all other possible combinations containing one or more of A, B, C, D embodiment, although this embodiment may not be explicitly documented in the following content.

The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of the elements described without departing from the scope of the disclosure. Various procedures or components may be omitted, substituted, or added as appropriate from each example. For example, the described methods may be performed in a different order than that described, and various steps may be added, omitted, or combined. Additionally, features described with respect to some examples may be combined into other examples.

Referring to Figure 1, Figure 1 is a schematic flowchart of a method for optimizing a vehicle movement path provided by an embodiment of the present application. In the embodiment of this application, the method includes:
S101. Determine the target transportation location of the target vehicle, and calculate the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location.

The execution subject of this application can be a cloud server.

In the embodiment of this application, for the target vehicle that needs to be transported in the suspension system, the cloud server will first determine the target transportation location to which it is to be transported. Based on the current location of the target vehicle and the target transportation location, it can then The distribution of production lines between the two locations, current working conditions and other factors are used to calculate the vehicle movement path of the target vehicle, and then determine the target vehicle movement path with optimal transportation efficiency.

In an implementation manner, calculating the target vehicle movement path of the target vehicle based on the current position of the target vehicle and the target transportation location includes:
Determine all candidate vehicle movement paths based on the current location of the target vehicle and the target transportation location, where the candidate vehicle movement paths include at least one production line;
Calculate the total weight score of each candidate vehicle movement path based on the weight score corresponding to each preset weight parameter;
The candidate vehicle movement path with the highest total weight score is determined as the target vehicle movement path.

In this embodiment of the present application, a candidate vehicle movement path that can be used to transport the target vehicle will be determined based on the current location of the target vehicle and the target transportation location it needs to go to. The target vehicle will be transported through the production line track of the suspension system, so it is determined that the candidate vehicle movement path will include at least one production line. If there are more than two production lines, it will also need to be transported through the bridge station set up between the production lines. After all candidate vehicle movement paths are determined, in order to determine the transportation efficiency of each candidate vehicle movement path, preset weight parameters will be set in advance, and the cloud server will pass each preset weight parameter of the candidate vehicle movement path. The corresponding weight scores are calculated, and then the total weight scores of each candidate vehicle movement path are determined. Finally, the candidate vehicle movement path with the highest total weight score will be determined as the target vehicle movement path with the optimal transportation efficiency.

In an implementation, all candidate vehicle movement paths are determined based on the current location of the target vehicle and the target transportation location, and the candidate vehicle movement paths include at least one production line, including:
Determine each production line between the current location of the target vehicle and the target transportation location and the bridging station between each of the production lines;
Combining each of the production lines and bridging stations in order of distance corresponding to the current position of the target vehicle to generate a candidate vehicle movement path;
Repeat the step of combining the production lines and bridging stations in order of distance corresponding to the current position of the target vehicle until all candidate vehicle movement paths covering all combinations are generated.

In the embodiment of this application, the structure of the entire hanging system is generally relatively complex and consists of many production lines and bridge stations used to connect each production line. The cloud server first needs to determine which production lines and bridge stations exist between the current location and the target transportation location, and then combines each production line and bridge station in order of distance from the current location to generate a candidate vehicle movement path. On a certain path node, there may be multiple production lines to choose from, that is, there are many combinations of paths. In order to determine the optimal path, the cloud server will traverse all combinations and determine all candidate vehicle movements. path.

In one implementation, the preset weight parameters include the current congestion situation of the production line, the number of production lines, and the theoretical passage time of the path;
Calculating the total weight score of each candidate vehicle movement path based on the weight score corresponding to each preset weight parameter includes:
Determine the upper limit number of vehicles and the actual number of vehicles for each production line in the candidate vehicle movement path, and determine the first weight score based on the ratio of the actual number of vehicles to the upper limit number of vehicles, and the ratio is used to Characterize the current congestion situation of the production line;
Determine a second weight score based on the number of production lines in the candidate vehicle movement path;
Determine the theoretical transit time of each production line and bridge station in the candidate vehicle movement path, accumulate the theoretical transit time of each unit, obtain the theoretical transit time of the path, and correspond to the theoretical transit time based on the path theory The duration range determines the third weight score;
Calculate the sum of the first weight score, the second weight score and the third weight score to obtain the total weight score of the candidate vehicle movement path.

In the embodiment of this application, taking the current congestion situation of the production line, the number of production lines, and the theoretical passage time of the path as an example, the preset weight parameters are set. Each production line will be designed according to the production line structure during design. The maximum capacity that the production line can theoretically accommodate The upper limit of the number of carriers can also be determined through the chip data identification device to determine the actual number of carriers currently on the production line, and the ratio between the two can be calculated. Different weight scores can be set in advance according to different ratios, so after the ratio is calculated, the first weight score can be determined. Although the moving speed of each production line track may be different, that is, the more production lines pass through, the slower the transportation speed is not necessarily, but the more production lines pass through, the more times the production line track needs to be switched, and the easier it is for vehicles to appear Accidents such as drops, etc., therefore, different weight scores are also set in advance according to the number of production lines, so as to determine the second weight score based on the actual number of production lines. According to the different track running speed and length of each production line and bridge station, the theoretical unit transit time required for transportation is also different. Since the unit theoretical passing time can be determined at the production line design stage, the cloud server directly obtains the theoretical passing time of each unit and accumulates it to obtain the path theoretical passing time. The third party can be determined based on the duration range corresponding to the path theoretical passing time. Weight score. By accumulating the first weight score, the second weight score and the third weight score, the total weight score of the candidate vehicle movement path can be obtained.

S102. Determine the node sections corresponding to each key node in the movement path of the target vehicle. The key node is a transition transportation node between two adjacent production lines.

In the embodiment of this application, after calculating and determining the moving path of the target vehicle, the cloud server will determine each node section in the moving path of the target vehicle. Generally speaking, the bridge station connected between the two production lines will be regarded as the key node. Considering that the hanging system is relatively large, the real-time status of each production line in the entire system is constantly changing dynamically. Therefore, during the transportation process, the calculated movement path of the target vehicle may gradually become less than optimal. path. Therefore, the cloud server will identify each key node so that after the target vehicle is transported to a certain key node, it can update and adjust the movement path of the target vehicle to ensure that the movement path of the target vehicle used during the movement is always the optimal transportation efficiency. of.

S103. When the target vehicle moves to the node section, recalculate the target vehicle movement path based on the current position and the target transportation location, and control the target vehicle movement path based on the recalculation. The target vehicle moves.

In the embodiment of this application, after the target vehicle moves to the node section, the cloud server will recalculate the target vehicle's moving path based on the current location of the target vehicle at this time combined with the target transportation location, and will calculate the target vehicle's movement path during the subsequent movement process. , control the movement of the target vehicle based on the recalculated movement path of the target vehicle, in order to achieve recalculation and update of the movement path of the target vehicle in the node section as a transitional transportation, through continuous updating and adjustment of the movement path of the target vehicle To continuously ensure that the transportation efficiency during transportation is the highest.

In an implementation manner, step S103 includes:
When the target vehicle moves to the node section, continue to repeatedly calculate the target vehicle movement path based on the current position and the target transportation location until the target vehicle leaves the node section;
Control the movement of the target vehicle based on the last calculated movement path of the target vehicle.

In the embodiment of this application, considering that the bridge station as a key node also has a certain length, the moving path of the target vehicle calculated when the target vehicle first enters the bridge station, when it moves to about to leave the bridge station, Due to the dynamic changes of the entire suspension system, the calculated movement path of the target vehicle may no longer be the optimal path. Therefore, when the target vehicle moves on the node section, the calculation of the target vehicle's movement path will be continuously repeated until the target vehicle leaves the node section. Then, the last calculated moving path of the target vehicle will be used as the optimal path to control the movement of the target vehicle, further ensuring the transportation efficiency of the target vehicle.

In one possible implementation, the step of continuously and repeatedly calculating the movement path of the target vehicle based on the current location and the target transportation location until the target vehicle leaves the node section further includes:
Compare the moving paths of each target vehicle, determine repeated paths, and increase the credibility score of the production line corresponding to the repeated paths;
When there are multiple target vehicle movement paths with the same total weight score during the subsequent calculation of the target vehicle movement path, the target vehicle movement path with the highest total credibility score is selected.

In the embodiment of this application, the cloud server will also compare the moving paths of each target vehicle calculated during the movement of the node section, and determine the same repeated parts, that is, repeated paths. The area corresponding to the repeated path can be considered as an area that has not changed significantly during the continuous repeated calculation process. The cloud server will consider this area to be relatively stable and will not fluctuate significantly over time. In the actual transportation process, in order to ensure the reliability of the transportation efficiency of the target vehicle, it is hoped that the stability of the transportation path will be better. Therefore, for repeated paths, the credibility score of the corresponding production line will be increased, so that in the subsequent calculation process of the moving path of the target vehicle, if the total weight score is the same and both are the highest score, The moving path of the target vehicle with the highest total credibility score will be prioritized for transportation to ensure the stability of the transportation process and thereby ensure the reliability of the transportation efficiency determined by calculation.

The optimization device for the vehicle movement path provided by the embodiment of the present application will be introduced in detail below with reference to Figure 2. It should be noted that the optimization device of the carrier movement path shown in Figure 2 is used to execute the method of the embodiment shown in Figure 1 of the present application. For convenience of explanation, only the parts related to the embodiment of the present application are shown. If specific technical details are not disclosed, please refer to the embodiment shown in Figure 1 of this application.

Please refer to Figure 2. Figure 2 is a schematic structural diagram of a device for optimizing a carrier movement path provided by an embodiment of the present application. As shown in Figure 2, the device includes:
The calculation module 201 is used to determine the target transportation location of the target vehicle, and calculate the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location;
The determination module 202 is used to determine the node sections corresponding to each key node in the target vehicle movement path, where the key node is a transition transportation node between two adjacent production lines;
The control module 203 is configured to recalculate the movement path of the target vehicle based on the current position and the target transportation location when the target vehicle moves to the node section, and based on the recalculated target vehicle The movement path of the vehicle controls the movement of the target vehicle.

In an implementation manner, the computing module 201 includes:
A first determination unit configured to determine all candidate vehicle movement paths based on the current location of the target vehicle and the target transportation location, where the candidate vehicle movement paths include at least one production line;
A first calculation unit configured to calculate the total weight score of each candidate vehicle movement path based on the weight score corresponding to each preset weight parameter;
The second determination unit is configured to determine the candidate vehicle movement path with the highest total weight score as the target vehicle movement path.

In an implementation manner, the first determining unit includes:
A first determination element used to determine each production line between the current position of the target carrier and the target transportation location and the bridging station between each of the production lines;
A combination component for sequentially combining each of the production lines and bridging stations in order of distance corresponding to the current position of the target vehicle to generate a candidate vehicle movement path;
The first repeating element is used to repeat the step of combining the production lines and bridging stations in order of distance corresponding to the current position of the target carrier until all candidate carrier movement paths covering all combinations are generated.

In an implementation manner, the first computing unit includes:
The second determination element is used to determine the upper limit number of vehicles and the actual number of vehicles for each production line in the candidate vehicle movement path, and determine the first weight score based on the ratio of the actual number of vehicles to the upper limit number of vehicles. value, the ratio is used to characterize the current congestion situation of the production line;
a third determination component configured to determine a second weight score based on the number of production lines of the production lines in the candidate carrier movement path;
The fourth determination element is used to determine the theoretical transit time per unit of each of the production lines and bridge stations in the candidate vehicle movement path, accumulate the theoretical transit time of each unit, and obtain the theoretical transit time of the path, and based on the The above-mentioned path theory determines the third weight score through the corresponding time range;
A calculation element is used to calculate the sum of the first weight score, the second weight score and the third weight score to obtain the total weight score of the candidate vehicle movement path.

In an implementation manner, the control module 203 includes:
A repeating unit configured to continuously and repeatedly calculate the moving path of the target vehicle based on the current position and the target transportation location when the target vehicle moves to the node section until the target vehicle leaves the node. road section;
A control unit configured to control the movement of the target vehicle based on the last calculated movement path of the target vehicle.

In an implementation manner, the control module 203 also includes:
A comparison unit, used to compare the moving paths of each target carrier, determine repeated paths, and improve the credibility score of the production line corresponding to the repeated paths;
A selection unit configured to select the target vehicle with the highest total credibility score when multiple target vehicle movement paths with the same total weight score appear during subsequent calculation of the target vehicle movement path. With movement path.

Those skilled in the art can clearly understand that the technical solutions of the embodiments of the present application can be implemented with the help of software and/or hardware. The "units" and "modules" in this specification refer to software and/or hardware that can complete specific functions independently or in cooperation with other components. The hardware can be, for example, a field-programmable gate array (Field-Programmable Gate Array, FPGA). , Integrated Circuit (IC), etc.

Each processing unit and/or module in the embodiments of this application can be implemented by an analog circuit that implements the functions described in the embodiments of this application, or by software that performs the functions described in the embodiments of this application.

Referring to Figure 3, which shows a schematic structural diagram of an electronic device involved in the embodiment of the present application. The electronic device can be used to implement the method in the embodiment shown in Figure 1. As shown in FIG. 3 , the electronic device 300 may include: at least one central processing unit 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

Among them, the communication bus 302 is used to realize connection communication between these components.

Among them, the user interface 303 may include a display screen (Display) and a camera (Camera), and the optional user interface 303 may also include a standard wired interface and a wireless interface.

Among them, the network interface 304 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

Among them, the central processing unit 301 may include one or more processing cores. The central processing unit 301 uses various interfaces and lines to connect various parts of the entire electronic device 300, and by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305, Execute various functions of the terminal 300 and process data. Optionally, the central processor 301 may use at least one of digital signal processing (DSP), field-programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). A form of hardware implementation. The central processing unit 301 may integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics central processing unit (Graphics Processing Unit, GPU), a modem, etc. Among them, the CPU mainly handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content that needs to be displayed on the display; and the modem is used to handle wireless communications. It can be understood that the above-mentioned modem may not be integrated into the central processor 301 and may be implemented by a separate chip.

Among them, the memory 305 may include random access memory (RAM) or read-only memory (Read-Only Memory). Optionally, the memory 305 includes non-transitory computer-readable storage medium. Memory 305 may be used to store instructions, programs, codes, sets of codes, or sets of instructions. The memory 305 may include a program storage area and a data storage area, where the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), Instructions, etc., used to implement each of the above method embodiments; the storage data area can store data, etc. involved in each of the above method embodiments. The memory 305 may optionally be at least one storage device located away from the aforementioned central processor 301 . As shown in Figure 3, memory 305, which is a computer storage medium, may include an operating system, a network communication module, a user interface module and program instructions.

In the electronic device 300 shown in Figure 3, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the central processor 301 can be used to call the optimization of the vehicle movement path stored in the memory 305. application and specifically do the following:
Determine the target transportation location of the target vehicle, and calculate the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location;
Determine the node sections corresponding to each key node in the movement path of the target vehicle, where the key node is a transition transportation node between two adjacent production lines;
When the target vehicle moves to the node section, the target vehicle moving path is recalculated based on the current position and the target transportation location, and the target vehicle moving path is controlled based on the recalculated target vehicle moving path. The target vehicle moves.

This application also provides a computer-readable storage medium on which a computer program is stored, which implements the steps of the above method when executed by a processor. Among them, the computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives and magneto-optical disks, ROM, RAM, EPROM, EEPROM, DRAM, VRAM, flash memory devices , magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.

It should be noted that for the sake of simple description, the foregoing method embodiments are expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence. Because in accordance with this application, certain steps may be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily necessary for this application.

In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or may be Integrated into another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some service interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical or other forms.

The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software functional units.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, It includes several instructions to cause a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (Random Access Memory, RAM), mobile hard disk, magnetic disk or optical disk and other media that can store program code.

Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable memory. The memory can include: flash memory. disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is to say, all equivalent changes and modifications made based on the teachings of this disclosure are still within the scope of this disclosure. Embodiments of the present disclosure will be readily apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure that follow the general principles of the disclosure and include common knowledge or customary technical means in the technical field that are not described in the disclosure. . It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being defined by the following claims.

Claims

A method for optimizing a vehicle movement path, characterized in that the method includes:

Determine the target transportation location of the target vehicle, and calculate the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location;

Determine the node sections corresponding to each key node in the movement path of the target vehicle, where the key node is a transition transportation node between two adjacent production lines;

When the target vehicle moves to the node section, the target vehicle moving path is recalculated based on the current position and the target transportation location, and the target vehicle moving path is controlled based on the recalculated target vehicle moving path. The target vehicle moves.
The method of claim 1, wherein calculating the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location includes:

Determine all candidate vehicle movement paths based on the current location of the target vehicle and the target transportation location, where the candidate vehicle movement paths include at least one production line;

Calculate the total weight score of each candidate vehicle movement path based on the weight score corresponding to each preset weight parameter;

The candidate vehicle movement path with the highest total weight score is determined as the target vehicle movement path.
The method of claim 2, wherein all candidate vehicle movement paths are determined based on the current location of the target vehicle and the target transportation location, and the candidate vehicle movement paths include at least one production line ,include:

Determine each production line between the current location of the target vehicle and the target transportation location and the bridging station between each of the production lines;

Combining each of the production lines and bridging stations in order of distance corresponding to the current position of the target vehicle to generate a candidate vehicle movement path;

Repeat the step of combining the production lines and bridging stations in order of distance corresponding to the current position of the target vehicle until all candidate vehicle movement paths covering all combinations are generated.
The method according to claim 2, characterized in that the preset weight parameters include the current congestion situation of the production line, the number of production lines and the theoretical passage time of the path;

Calculating the total weight score of each candidate vehicle movement path based on the weight score corresponding to each preset weight parameter includes:

Determine the upper limit number of vehicles and the actual number of vehicles for each production line in the candidate vehicle movement path, and determine the first weight score based on the ratio of the actual number of vehicles to the upper limit number of vehicles, and the ratio is used to Characterize the current congestion situation of the production line;

Determine a second weight score based on the number of production lines in the candidate vehicle movement path;

Determine the theoretical transit time of each production line and bridge station in the candidate vehicle movement path, accumulate the theoretical transit time of each unit, obtain the theoretical transit time of the path, and correspond to the theoretical transit time based on the path theory The duration range determines the third weight score;

Calculate the sum of the first weight score, the second weight score and the third weight score to obtain the total weight score of the candidate vehicle movement path.
The method of claim 2, wherein when the target vehicle moves to the node section, the target vehicle moving path is recalculated based on the current position and the target transportation location, and controlling the movement of the target vehicle based on the recalculated movement path of the target vehicle, including:

When the target vehicle moves to the node section, continue to repeatedly calculate the target vehicle movement path based on the current position and the target transportation location until the target vehicle leaves the node section;

Control the movement of the target vehicle based on the last calculated movement path of the target vehicle.
The method of claim 5, wherein the target vehicle moving path is continuously and repeatedly calculated based on the current location and the target transportation location until the target vehicle leaves the node section, and further include:

Compare the moving paths of each target vehicle, determine repeated paths, and increase the credibility score of the production line corresponding to the repeated paths;

When there are multiple target vehicle movement paths with the same total weight score during the subsequent calculation of the target vehicle movement path, the target vehicle movement path with the highest total credibility score is selected.
A device for optimizing the movement path of a carrier, characterized in that the device includes:

A calculation module configured to determine the target transportation location of the target vehicle and calculate the target vehicle movement path of the target vehicle based on the current location of the target vehicle and the target transportation location;

A determination module used to determine the node sections corresponding to each key node in the target vehicle movement path, where the key node is a transition transportation node between two adjacent production lines;

A control module configured to recalculate the movement path of the target vehicle based on the current position and the target transportation location when the target vehicle moves to the node section, and based on the recalculated target vehicle The movement path controls the movement of the target vehicle.
An electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, it implements any one of claims 1-6 The steps of the method.
A computer-readable storage medium with a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method described in any one of claims 1-6 are implemented.