Driver virtual identity assessment method, system and device based on digital management

Abstract

The invention discloses a driver virtual identity assessment method, system and device based on digital management. The method comprises the following steps: acquiring freight order information and transportation route information of a target object within a set time; carrying out clustering analysis on cargo characteristics and transportation requirements in the freight order information to obtain transportation proportions of different cargo types; determining a cargo type of which the transportation proportion is not less than a set proportion, and generating a special transportation cargo set of the target object and a score of each special transportation cargo; clustering analysis is carried out on the transportation route information, a plurality of transportation areas and the active frequency of each transportation area are obtained, and the active frequency is the number of times that the target object passes through the transportation areas; and determining a transportation area with an active frequency not less than a set frequency, and generating an active area set of the target object and a score of each active area. According to the invention, through the freight order information and the transportation route information, the special transportation goods and the active area of the target object are generated, and visual data support is provided for a goods owner to select a driver.

Description

Technical Field

[0001] The present invention relates to the field of logistics and transportation technology, and in particular to a driver virtual identity assessment method, system and device based on digital management. Background Art

[0002] Freight logistics refers to the physical flow of goods from suppliers to consumers. Modern freight logistics increasingly relies on information technology and automated systems to improve efficiency and reduce costs. The application of technologies such as the Internet of Things, big data, and artificial intelligence makes the logistics process more transparent and traceable.

[0003] Currently, freight transportation platforms lack the means to accurately locate drivers. Shippers usually choose drivers for long-term cooperation and rarely consider delegating freight tasks to unfamiliar drivers. There is a lack of effective communication and understanding between drivers and shippers, which makes it easy for drivers to find it difficult to accept orders and for shippers to find suitable drivers. Summary of the invention

[0004] In order to solve the technical problems existing in the background technology, the present invention proposes a driver virtual identity evaluation method, system and device based on digital management, which solves the problem that the current cargo owners cannot effectively understand the driver's transportation advantages and the driver's transportation advantages have no way to be displayed to the cargo owners.

[0005] The present invention proposes a driver virtual identity evaluation method based on digital management, comprising:

[0006] Obtain the target object's freight order information and transportation route information within a set time;

[0007] Performing cluster analysis on the cargo characteristics and transportation requirements in the freight order information to obtain the transportation ratio of different cargo types, where the transportation ratio is the ratio of the number of transportations of each type of cargo to the total number of transportations of all cargo types;

[0008] Determine the cargo types whose transportation proportion is not less than the set proportion, generate a set of special transportation cargoes for the target object and a score for each special transportation cargo;

[0009] Performing cluster analysis on the transportation route information to obtain multiple transportation areas and the activity frequency of each transportation area, where the activity frequency is the number of times the target object passes through the transportation area;

[0010] The transport areas whose active frequency is not less than the set frequency are determined, and an active area set of the target object and a score for each active area are generated.

[0011] As a further improvement of the present invention, cluster analysis of the transportation route information specifically includes:

[0012] Get the origin, destination and transfer nodes in the transportation routes of all freight orders;

[0013] Pre-plan the set area range of different transportation areas in the electronic map;

[0014] Record the total number of markings of the starting point, destination, and transfer nodes within different set areas;

[0015] The activity frequency of each transport region is determined based on the total number of markings.

[0016] As a further improvement of the present invention, cluster analysis of the transportation route information specifically includes:

[0017] Performing cluster analysis on the transport sections in the transport route information, where the transport sections include sections consisting of a starting point and a transfer node, adjacent transfer nodes, or a transfer node and a destination;

[0018] Pre-plan the set area range of different transportation areas in the electronic map;

[0019] Record the cumulative number of transport sections in different set areas;

[0020] The activity frequency of each transportation area is determined based on the accumulated number of times.

[0021] As a further improvement of the present invention, it also includes:

[0022] Obtain cargo damage data of different cargo types for analysis to obtain the damage extent of all cargo types;

[0023] Generate incidental cargo damage information for the special transport cargo score.

[0024] As a further improvement of the present invention, it also includes:

[0025] If the transportation proportion of all cargo types is less than the set proportion, all cargo types are sorted from high to low according to the transportation proportion, and the first ranking of each cargo type is obtained;

[0026] Determine the cargo types whose first ranking is greater than the set ranking as the special transport cargo set of the target object, and determine the special transport cargo score according to the level interval of the transportation proportion.

[0027] As a further improvement of the present invention, it also includes:

[0028] If the active frequency of all transport areas is less than the set frequency, all transport areas are sorted from highest to lowest according to the active frequency, and the second ranking of each transport area is obtained;

[0029] The transport areas whose second ranking is greater than the set ranking are determined as the active area set of the target object, and the active area score is determined according to the level interval of the active frequency of the transport area.

[0030] As a further improvement of the present invention, it also includes:

[0031] Obtaining basic personal information and driving mileage data of the target object, wherein the basic personal information includes height, weight, age and physical examination data;

[0032] Analyze and determine the target object’s potential driving risk and driving maturity index.

[0033] The present invention also proposes a driver virtual identity evaluation system based on digital management, comprising:

[0034] The acquisition module is used to obtain the freight order information and transportation route information of the target object within a set time;

[0035] The first analysis module is used to perform cluster analysis on the cargo characteristics and transportation requirements in the freight order information to obtain the transportation ratio of different cargo types, where the transportation ratio is the ratio of the number of transportation times of each type of cargo to the total number of transportation times of all cargo types;

[0036] The first evaluation module is used to determine the types of goods whose transportation proportion is not less than the set proportion, and generate a set of special transportation goods of the target object and a score for each special transportation goods;

[0037] The second analysis module is used to perform cluster analysis on the transportation route information to obtain multiple transportation areas and the activity frequency of each transportation area, where the activity frequency is the number of times the target object passes through the transportation area;

[0038] The second evaluation module is used to determine the transportation area whose active frequency is not less than the set frequency, and generate an active area set of the target object and a score for each active area.

[0039] The present invention also proposes a driver virtual identity assessment device based on digital management, comprising: a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the above-mentioned driver virtual identity assessment method based on digital management is implemented.

[0040] Beneficial effects:

[0041] The present invention obtains the freight order information and transportation route information of the target object within the set time; performs cluster analysis on the cargo characteristics and transportation requirements in the freight order information to obtain the transportation proportion of different cargo types; determines the cargo type whose transportation proportion is not less than the set proportion, generates a special transportation cargo set of the target object and a score for each special transportation cargo; performs cluster analysis on the transportation route information to obtain multiple transportation areas and the active frequency of each transportation area, where the active frequency is the number of times the target object passes through the transportation area; determines the transportation area whose active frequency is not less than the set frequency, generates the active area set of the target object and the score for each active area. Thus, by analyzing the freight order information and transportation route information, the special transportation cargo and active area of ​​the target object are generated, that is, the transportation advantages of the driver are displayed to the cargo owner, the cargo owner can effectively understand the transportation advantages of the driver, and provide visual data support for the cargo owner to select the driver. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 The present invention is a flowchart of a driver virtual identity assessment method based on digital management. DETAILED DESCRIPTION

[0043] like Figure 1 As shown, Figure 1 This is a flow chart of a driver virtual identity evaluation method based on digital management according to an embodiment of the present invention;

[0044] Reference Figure 1 , a driver virtual identity assessment method based on digital management proposed in an embodiment of the present invention includes:

[0045] S10: Obtaining the freight order information and transportation route information of the target object within a set time;

[0046] S20: performing cluster analysis on the cargo characteristics and transportation requirements in the freight order information to obtain the transportation ratio of different cargo types, where the transportation ratio is the ratio of the number of transportations of each type of cargo to the total number of transportations of all cargo types;

[0047] In some implementations, further comprising:

[0048] Obtain cargo damage data of different cargo types for analysis to obtain the damage extent of all cargo types;

[0049] Generate incidental cargo damage information for the special transport cargo score.

[0050] S30: Determine the cargo types whose transportation proportion is not less than the set proportion, generate a set of special transportation cargoes of the target object and a score for each special transportation cargo;

[0051] In some implementations, further comprising:

[0052] If the transportation proportion of all cargo types is less than the set proportion, all cargo types are sorted from high to low according to the transportation proportion, and the first ranking of each cargo type is obtained;

[0053] Determine the cargo types whose first ranking is greater than the set ranking as the special transport cargo set of the target object, and determine the special transport cargo score according to the level interval of the transportation proportion.

[0054] S40: performing cluster analysis on the transport route information to obtain a plurality of transport areas and an active frequency of each transport area, wherein the active frequency is the number of times the target object passes through the transport area;

[0055] In some implementations, cluster analysis of the transportation route information specifically includes:

[0056] Get the origin, destination and transfer nodes in the transportation routes of all freight orders;

[0057] Pre-plan the set area range of different transportation areas in the electronic map;

[0058] Record the total number of markings of the starting point, destination, and transfer nodes within different set areas;

[0059] The activity frequency of each transport region is determined based on the total number of markings.

[0060] In some implementations, cluster analysis of the transportation route information specifically includes:

[0061] Performing cluster analysis on the transport sections in the transport route information, where the transport sections include sections consisting of a starting point and a transfer node, adjacent transfer nodes, or a transfer node and a destination;

[0062] Pre-plan the set area range of different transportation areas in the electronic map;

[0063] Record the cumulative number of transport sections in different set areas;

[0064] The activity frequency of each transportation area is determined based on the accumulated number of times.

[0065] S50: Determine the transport areas whose active frequency is not less than the set frequency, and generate an active area set of the target object and a score for each active area.

[0066] In some implementations, further comprising:

[0067] If the active frequency of all transport areas is less than the set frequency, all transport areas are sorted from highest to lowest according to the active frequency, and the second ranking of each transport area is obtained;

[0068] The transport areas whose second ranking is greater than the set ranking are determined as the active area set of the target object, and the active area score is determined according to the level interval of the active frequency of the transport area.

[0069] In some implementations, further comprising:

[0070] Obtaining basic personal information and driving mileage data of the target object, wherein the basic personal information includes height, weight, age and physical examination data;

[0071] Analyze and determine the target object’s potential driving risk and driving maturity index.

[0072] The present invention also proposes a driver virtual identity evaluation system based on digital management, comprising:

[0073] The acquisition module is used to obtain the freight order information and transportation route information of the target object within a set time;

[0074] The first analysis module is used to perform cluster analysis on the cargo characteristics and transportation requirements in the freight order information to obtain the transportation ratio of different cargo types, where the transportation ratio is the ratio of the number of transportation times of each type of cargo to the total number of transportation times of all cargo types;

[0075] The first evaluation module is used to determine the types of goods whose transportation proportion is not less than the set proportion, and generate a set of special transportation goods of the target object and a score for each special transportation goods;

[0076] The second analysis module is used to perform cluster analysis on the transportation route information to obtain multiple transportation areas and the activity frequency of each transportation area, where the activity frequency is the number of times the target object passes through the transportation area;

[0077] The second evaluation module is used to determine the transportation area whose active frequency is not less than the set frequency, and generate an active area set of the target object and a score for each active area.

[0078] The present invention also proposes a driver virtual identity assessment device based on digital management, comprising: a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the above-mentioned driver virtual identity assessment method based on digital management is implemented.

[0079] It should be noted that the program in the above embodiment can be any combination of one or more programming languages ​​to write program codes for executing the operation of the embodiment of the present application, and the programming language includes object-oriented programming languages, such as Java, C++, etc., and also includes conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed completely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on the remote computing device, or completely on the remote computing device or server.

[0080] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0081] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A driver virtual identity assessment method based on digital management, characterized in that: include: Obtain the target object's freight order information and transportation route information within a set time; Performing cluster analysis on the cargo characteristics and transportation requirements in the freight order information to obtain the transportation ratio of different cargo types, where the transportation ratio is the ratio of the number of transportations of each type of cargo to the total number of transportations of all cargo types; Determine the cargo types whose transportation proportion is not less than the set proportion, generate a set of special transportation cargoes for the target object and a score for each special transportation cargo; Performing cluster analysis on the transportation route information to obtain multiple transportation areas and the activity frequency of each transportation area, where the activity frequency is the number of times the target object passes through the transportation area; The transport areas whose active frequency is not less than the set frequency are determined, and an active area set of the target object and a score for each active area are generated.

2. A driver virtual identity assessment method based on digital management according to claim 1, characterized in that: The cluster analysis of the transportation route information specifically includes: Get the origin, destination and transfer nodes in the transportation routes of all freight orders; Pre-plan the set area range of different transportation areas in the electronic map; Record the total number of markings of the starting point, destination, and transfer nodes within different set areas; The activity frequency of each transport region is determined based on the total number of markings.

3. A driver virtual identity assessment method based on digital management according to claim 1, characterized in that: The cluster analysis of the transportation route information specifically includes: Performing cluster analysis on the transport sections in the transport route information, where the transport sections include sections consisting of a starting point and a transfer node, adjacent transfer nodes, or a transfer node and a destination; Pre-plan the set area range of different transportation areas in the electronic map; Record the cumulative number of transport sections in different set areas; The activity frequency of each transportation area is determined based on the accumulated number of times.

4. A driver virtual identity assessment method based on digital management according to claim 1, characterized in that: Also includes: Obtain cargo damage data of different cargo types for analysis to obtain the damage extent of all cargo types; Generate incidental cargo damage information for the special transport cargo score.

5. A driver virtual identity assessment method based on digital management according to claim 1, characterized in that: Also includes: If the transportation proportion of all cargo types is less than the set proportion, all cargo types are sorted from high to low according to the transportation proportion, and the first ranking of each cargo type is obtained; Determine the cargo types whose first ranking is greater than the set ranking as the special transport cargo set of the target object, and determine the special transport cargo score according to the level interval of the transportation proportion.

6. A driver virtual identity assessment method based on digital management according to claim 1, characterized in that: Also includes: If the active frequency of all transport areas is less than the set frequency, all transport areas are sorted from largest to smallest according to the active frequency, and the second ranking of each transport area is obtained; The transport areas whose second ranking is greater than the set ranking are determined as the active area set of the target object, and the active area score is determined according to the level interval of the active frequency of the transport area.

7. A driver virtual identity assessment method based on digital management according to claim 1, characterized in that: Also includes: Obtaining basic personal information and driving mileage data of the target object, wherein the basic personal information includes height, weight, age and physical examination data; Analyze and determine the target object’s potential driving risk and driving maturity index.

8. A driver virtual identity assessment system based on digital management, characterized in that: include: The acquisition module is used to obtain the freight order information and transportation route information of the target object within a set time; The first analysis module is used to perform cluster analysis on the cargo characteristics and transportation requirements in the freight order information to obtain the transportation ratio of different cargo types, where the transportation ratio is the ratio of the number of transportation times of each type of cargo to the total number of transportation times of all cargo types; The first evaluation module is used to determine the types of goods whose transportation proportion is not less than the set proportion, and generate a set of special transportation goods of the target object and a score for each special transportation goods; A second analysis module is used to perform cluster analysis on the transportation route information to obtain multiple transportation areas and the activity frequency of each transportation area, where the activity frequency is the number of times the target object passes through the transportation area; The second evaluation module is used to determine the transportation area whose active frequency is not less than the set frequency, and generate an active area set of the target object and a score for each active area.

9. A driver virtual identity assessment device based on digital management, characterized in that: include: A memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions, characterized in that: when the program instructions are loaded and executed by the processor, a driver virtual identity assessment method based on digital management as described in any one of claims 1 to 7 is implemented.

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