JP2023166082A - Used vehicle information processing apparatus, used vehicle information processing method, and program - Google Patents

Abstract

To provide a used vehicle information processing apparatus, a used vehicle information processing method, and a program for allowing a deteriorated state of a used vehicle to be appropriately recognized.SOLUTION: The used vehicle information processing apparatus comprises: an acquisition unit which acquires used vehicle information including specification information being information about specifications of a used vehicle and use information being information about the use of the used vehicle; a deterioration degree estimation unit which estimates a deterioration degree of the used vehicle using the used vehicle information as an explanatory variable; and a presentation unit which presents the estimated deterioration degree to a purchaser of the used vehicle.SELECTED DRAWING: Figure 23

Description

The present disclosure relates to a used vehicle information processing device, a used vehicle information processing method, and a program.

Patent Document 1 describes the following automatic vehicle assessment system. In the automatic vehicle appraisal system described in Patent Document 1, first, a plurality of pieces of auction contract result information that match basic vehicle information such as the vehicle type are selected from the vehicle information of the vehicle to be appraised. Next, the average value is calculated from the contract prices included in the auction contract result information. Next, each contract price is compared with the average value, and if the contract price that deviates farthest from the average value is outside the range of allowable values, that contract price is removed. Next, new auction closing result information is supplemented and the average value is recalculated, and if the difference between each closing price and the average value is within the allowable value range, the average value is value.

In Patent Document 1, vehicle information includes vehicle model name, grade, engine type name, model year, shift (type), door (type), mileage, color, vehicle inspection (day), evaluation (points), air conditioner, Options include a sunroof, leather, and multi-purpose trim. Here, the evaluation score is a numerical value indicating a comprehensive evaluation of the vehicle's exterior appearance, the degree of dirt on the interior, and the like. In Patent Document 1, evaluation points are given in 0.5 increments, for example, from 1 to 10. Furthermore, in Patent Document 1, the evaluation points are usually evaluated relatively according to the condition of the exterior and interior of the vehicle, but they are evaluated on a scale of 1 to 10 in 0.5 increments. The most common evaluation score is 4.5. Therefore, it is set to 4.5 by default, and if it is difficult for an amateur user to make a judgment, the default value is left as is.

Patent No. 3738160

Generally, in the case of used private passenger cars, it is often possible to roughly predict the parts that need maintenance if the vehicle type, model, year of manufacture, and cumulative mileage can be confirmed. On the other hand, for example, commercial vehicles are used in a wide variety of ways, and each vehicle has a different state of deterioration, making it difficult to identify parts that need maintenance.

However, in the automatic vehicle appraisal system described in Patent Document 1, the information that represents how it is used is exclusively the mileage, so there is a problem that, for example, it may be difficult for the buyer to properly understand the deterioration state of the vehicle. there were.

The present disclosure has been made in order to solve the above problems, and aims to provide a used vehicle information processing device, a used vehicle information processing method, and a program that can appropriately grasp the deterioration state of a used vehicle. shall be.

In order to solve the above problems, a used vehicle information processing device according to the present disclosure acquires used vehicle information including specification information that is information about the specifications of a used vehicle and usage information that is information about the use of the used vehicle. a deterioration degree estimation part that estimates the deterioration degree of the used vehicle using the used vehicle information as an explanatory variable; and a presentation part that presents the estimated deterioration degree to the buyer of the used vehicle. .

A used vehicle information processing method according to the present disclosure includes a step of acquiring used vehicle information including specification information that is information about specifications of a used vehicle and usage information that is information about the use of the used vehicle; The method includes the steps of estimating the degree of deterioration of the used vehicle using as an explanatory variable, and presenting the estimated degree of deterioration to the buyer of the used vehicle.

A program according to the present disclosure includes a step of acquiring used vehicle information including specification information that is information about the specifications of a used vehicle and usage information that is information about the use of the used vehicle, and using the used vehicle information as an explanatory variable. A computer is caused to execute the steps of estimating the degree of deterioration of the used vehicle and presenting the estimated degree of deterioration to the buyer of the used vehicle.

According to the used vehicle information processing device, used vehicle information processing method, and program of the present disclosure, it is possible to appropriately grasp the deterioration state of a used vehicle.

FIG. 1 is a block diagram illustrating a configuration example of a used vehicle information processing device according to a first embodiment of the present disclosure. FIG. 2 is a schematic diagram showing an example of used vehicle label information according to an embodiment of the present disclosure. FIG. 1 is a schematic diagram showing a configuration example of a used vehicle information DB according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram showing a configuration example of a purchase/sales record DB according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram showing a configuration example of a maintenance record DB according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram showing a configuration example of a maintenance cost record DB according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram illustrating an example of usedness according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram illustrating an example of usedness according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram showing a display example of a maintenance menu according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram showing a display example of a maintenance menu according to an embodiment of the present disclosure. 1 is a flowchart illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 1 is a diagram illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. It is a flowchart which shows another example of operation of the used vehicle information processing device concerning a 1st embodiment of this indication. FIG. 2 is a block diagram illustrating a configuration example of a used vehicle information processing device according to a second embodiment of the present disclosure. It is a flow chart which shows an example of operation of a used vehicle information processing device concerning a 2nd embodiment of this indication. FIG. 7 is a schematic diagram for explaining an operation example of a used vehicle information processing device according to a second embodiment of the present disclosure. 1 is a block diagram illustrating a basic configuration example of a used vehicle information processing device according to an embodiment of the present disclosure. FIG. 1 is a schematic block diagram showing the configuration of a computer according to at least one embodiment.

Hereinafter, a used vehicle information processing device, a used vehicle information processing method, and a program according to an embodiment of the present disclosure will be described with reference to the drawings. In addition, in each figure, the same reference numerals are used for the same or corresponding components, and the description thereof will be omitted as appropriate.

<First embodiment>
Hereinafter, a used vehicle information processing device, a used vehicle information processing method, and a program according to a first embodiment of the present disclosure will be described with reference to FIGS. 1 to 19. FIG. 1 is a block diagram illustrating a configuration example of a used vehicle information processing device according to a first embodiment of the present disclosure. FIG. 2 is a schematic diagram illustrating an example of used vehicle label information according to an embodiment of the present disclosure. FIG. 3 is a schematic diagram showing a configuration example of a used vehicle information DB (database) according to an embodiment of the present disclosure. FIG. 4 is a schematic diagram showing a configuration example of a purchase/sales record DB according to an embodiment of the present disclosure. FIG. 5 is a schematic diagram illustrating a configuration example of a maintenance record DB according to an embodiment of the present disclosure. FIG. 6 is a schematic diagram illustrating a configuration example of a maintenance cost record DB according to an embodiment of the present disclosure. FIGS. 7 and 8 are schematic diagrams illustrating examples of second-handness according to the embodiment of the present disclosure. 9 and 10 are schematic diagrams showing display examples of maintenance menus according to the embodiment of the present disclosure. FIG. 11 is a flowchart illustrating an example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure. 12 to 18 are diagrams illustrating operational examples of the used vehicle information processing device according to the first embodiment of the present disclosure. FIG. 19 is a flowchart illustrating another example of the operation of the used vehicle information processing device according to the first embodiment of the present disclosure.

Note that in the description of the first embodiment and the second embodiment described later, an intermediary such as an operator mediates the buying and selling of used vehicles, for example, by selling a used vehicle purchased from a seller to a buyer. An example is given in which the used vehicle information processing device according to the embodiment is applied to the system. It also cites forklifts as an example of used vehicles. However, the used vehicle information processing device according to the embodiment of the present disclosure is not limited to this example, and may include, for example, cargo transportation vehicles such as trucks and trailers, construction machines such as mixer trucks, tank trucks, dump trucks, bulldozers, and power shovels. It can be applied to used vehicles and new and old vehicles. Alternatively, the used vehicle information processing device according to the embodiment of the present disclosure may be used for all types of commercial or private use, such as construction vehicles such as pile driving vehicles, agricultural vehicles such as tractors, and passenger transportation vehicles such as buses. It can be applied to used vehicles and new and old vehicles. Furthermore, the form of buying and selling is not limited to the above example. For example, the present invention may be applied to a type of transaction in which a seller mediates a transaction between a buyer and receives a brokerage fee from one or both parties.

(Configuration of used vehicle information processing device)
The used vehicle information processing device 1 shown in FIG. 1 can be configured using, for example, one or more computers such as a server and a personal computer. Furthermore, part or all of one or more computers may be configured on a cloud, for example. The used vehicle information processing device 1 includes the following parts as a functional configuration composed of a combination of hardware such as one or more computers and software such as programs executed by the one or more computers. That is, the used vehicle information processing device 1 shown in FIG. A maintenance cost record DB 16 is provided. The used vehicle information processing unit 10 also includes a price estimation module 101, a used degree estimation module 102, and a maintenance module 103.

The used vehicle purchase system 11 is, for example, a Web server, and transmits and receives predetermined information to and from the user terminal 2 operated by the seller of the used vehicle via a communication line. The user terminal 2 is, for example, a computer such as a personal computer, a smartphone, or a tablet terminal, and is a terminal operated by a seller. The used vehicle purchase system 11 uses, for example, a used vehicle label that includes specification information, which is information related to the specifications of the used vehicle to be purchased from the seller, which is input on the user terminal 2, and usage information, which is information related to the use of the used vehicle. Get information. Note that, hereinafter, "seller" will also be referred to as "seller" and "buyer" will also be referred to as "buyer".

FIG. 2 shows an example of used vehicle label information 201. Used vehicle label information 201 shown in FIG. 2 includes specification information 202 and usage information 203. Specification information 202 is information regarding the specifications of the used vehicle. Usage information 203 is information regarding the usage of the used vehicle. Further, the specification information 202 shown in FIG. 2 includes information representing the manufacturer, fuel, engine type, displacement, transmission, maximum load, year of manufacture, warranty, attachment, and special specifications. Manufacturer is the manufacturer's name, Fuel is the type of fuel, Transmission is the type of transmission, Warranty is the remaining warranty period and warranty details, Attachment is the type of attachment (fork type, etc.), and Special Specification is the existence and content of special specifications. This is information representing the following. Further, usage information 203 shown in FIG. 2 includes information representing an hour meter (hours of use), industry of use, main cargo, failure/repair history, maintenance history, dirt and scratches, and country of use. Note that the configuration of the used vehicle label information 201 is not limited to the configuration example shown in FIG. 2.

The method of confirming each information is based on the seller's declaration. However, each information numbered 1 to 6 is model information, and can be confirmed by inputting the model number, etc. This information is relatively reliable. Additionally, the information numbered 7 can be confirmed on the vehicle body plate, etc. This information is also relatively reliable. On the other hand, information numbered 8 to 18 is information that is relatively likely to contain errors. However, regarding the information numbered 8 to 18, the reliability of the information can be improved by requesting input (transmission) of additional information, etc. For example, the reliability of the information numbered 8 can be improved by checking the warranty. The reliability of information numbered 9 and 10 can be improved by obtaining sales records from used vehicle sellers or by confirming with photographs. The reliability of the information numbered 11 can be improved by checking photos or obtaining telematics information depending on the vehicle. The reliability of the information numbered 12 can be improved by checking the sales information of the store, etc., or obtaining telematics information. The reliability of the information numbered 13 can be improved by checking the sales information of the store or the like. The reliability of the information numbered 14 can be improved by checking the sales information of the store, etc., or obtaining telematics information. The reliability of the information in numbers 15 and 16 can be improved by obtaining records of inspections, repairs, maintenance, etc., if available, or by adding or modifying them based on information inspected after purchase. You can improve your performance. The reliability of the information numbered 17 can be improved by adding or modifying the information based on photo confirmation or information inspected after purchase. The reliability of the information numbered 18 can be improved by checking the sales information of the store or the like.

Note that, for example, information numbered 12 and 14 is information that affects deterioration of the prime mover, cargo handling system, and drive unit. Further, for example, information numbered 13 and 18 is information that affects deterioration and rust of the prime mover, cargo handling system, and drive system.

The used vehicle purchase system 11 acquires used vehicle label information 201 from the user terminal 2, presents the degree of used vehicle (to be described later) to the user terminal 2, and informs the user of the purchase price (hereinafter also referred to as purchase price) of the used vehicle. It is presented to the terminal 2, and exchanges regarding the purchase are made.

Here, examples of information managed by the used vehicle information DB 13, purchase/sales record DB 14, maintenance work record DB 15, and maintenance cost record DB 16 will be described with reference to FIGS. 3 to 6. Note that in this embodiment, the database (DB) is a system that includes files containing data or a collection thereof and software that processes them. FIGS. 3 to 6 show examples of the configuration of each record that constitutes a table managed by each DB.

Each record of the used vehicle information DB 13 includes, for example, as shown in FIG. ), second-handness information, date and time of sale (purchase), and date and time of sale (sale) are stored. Note that when the same vehicle is bought and sold multiple times, for example, each item other than the vehicle identification information is added to the same record.

For example, as shown in FIG. 4, each record in the purchase/sales record DB 14 includes seller identification information, buyer identification information, used vehicle label information (specification information), used vehicle label information (used vehicle Information), second-handness information, date and time of sale (purchase), purchase price, date and time of sale (sale), and sale price are stored. Note that when the same vehicle is bought and sold multiple times, for example, each item other than the vehicle identification information is added to the same record.

In each record of the maintenance work record DB 15, as shown in FIG. 5, for example, information such as failure/repair history information, maintenance history information, and maintenance menu selection information is stored in association with vehicle identification information. The failure/repair history information is information representing the details and dates of zero or more failures or repairs. The maintenance history information is information representing the details and dates of zero or more maintenance. The maintenance menu selection information is information representing the maintenance content and estimated cost selected by the buyer as described later. The information managed by the maintenance work record DB 15 is, for example, registered based on a seller's declaration, or is registered based on, for example, information representing failure, repair, and maintenance records obtained from another system or the like.

For example, as shown in FIG. 6, each record in the maintenance cost performance DB 16 includes 0 or more pieces of repair cost information, 0 or more pieces of maintenance cost information, and each piece of maintenance menu selection information, linked to vehicle identification information. Information is stored. Repair cost information is information representing the cost of repair. The maintenance cost information is information representing the cost of maintenance. The maintenance menu selection information is the same as the maintenance work record DB 15. The information managed by the maintenance cost record DB1 is, for example, registered based on a seller's declaration, or is registered based on, for example, information representing failure, repair, and maintenance records obtained from another system.

Next, the price estimation module 101 shown in FIG. 1 estimates an appropriate purchase price from the seller and an appropriate sale price for the buyer for the target vehicle. Here, the appropriate purchase price or appropriate sale price means, for example, that the used vehicle label information 201 is close to the actual purchase price or sale price of other used vehicles similar to the target used vehicle (within a predetermined range). It means that there is). The price estimation module 101 uses, for example, a trained machine learning model that has been machine learned using a data set that includes past purchases and sales of used vehicles and used vehicle label information 201 at that time as training data. Estimate the purchase price and sale price. In this case, each value obtained by digitizing each item of the used vehicle label information 201 of the used vehicle to be estimated is input as an explanatory variable to the trained machine learning model. Then, an appropriate purchase price and sale price are output from the trained machine learning model.

Alternatively, the price estimation module 101 may be a machine learned machine using, for example, past sales results of used vehicles (including sales prices and used vehicle label information 201) and a data set of second-handness, which will be described later, as training data. Estimate the appropriate selling price using a learning model. In this case, the used vehicle label information 201 (values obtained by quantifying each item) of the used vehicle to be estimated and the degree of used vehicle are input as explanatory variables to the trained machine learning model. Then, an appropriate selling price is output from the trained machine learning model. Furthermore, the price estimation module 101 calculates a purchase price based on empirical rules or the like based on the estimated sale price.

The used degree estimating module 102 estimates the used degree, which is a value representing the degree of deterioration, of the target vehicle using the used car label information 201 as an explanatory variable. In this embodiment, the evaluation score of the secondhand degree of the entire used vehicle is set from 0 to 100, with 100 representing the least deteriorated state and 0 representing the most deteriorated state. FIG. 7 and FIG. 8 show examples of estimating second-handness. FIG. 7 shows major classifications and minor classifications of vehicle components (or component parts), and main confirmation items in association with each other. Figure 8 shows weighted points, ranges of item evaluation points, estimation examples of item evaluation points, estimation examples of major classification evaluation points, and overall evaluation points in association with the same major categories and minor categories as shown in FIG. Here is an example. In this embodiment, the used degree (deterioration degree) includes an item evaluation score, a major classification evaluation score, and an overall evaluation score.

In the examples shown in FIGS. 7 and 8, the degree of second-hand goods is classified and evaluated for each major classification and each minor classification. The main categories are prime movers, traveling equipment, cargo handling equipment, driver's seats, etc. The subclassifications for the prime mover are general (number: 1), engine body (number: 2), lubrication system (number: 3), and fan belt (number: 4). The subcategories of running equipment are general (number: 5), wheels (number: 6), suspension (number: 7), steering system (number: 8), clutch (number: 9), and power steering (number: 10). , tires (number: 11) and brakes (number: 12). The subcategories of cargo handling equipment are general (number: 13), fork (number: 14), mast (number: 15), lift cylinder (number: 16), lift chain (number: 17), and lift bracket (number: 18), backrest (number: 19) and tilt cylinder (number: 20). The subcategories for the driver's seat and others are general (number: 21), driving equipment (number: 22), head guard (number: 23), seat (number: 24), lighting (number: 25), mirror (number: 26), and an alarm device (number: 27).

In this embodiment, the second-hand degree estimation module 102 uses, for example, the result of an operator (inspector) actually checking a used vehicle and evaluating the second-hand degree, and used car label information input by the seller of the used vehicle. The degree of usedness is estimated using a trained machine learning model that is machine learned using a data set containing 201 as training data. In this case, the used degree estimation module 102 inputs the used car label information 201 of the target vehicle as an explanatory variable to the trained machine learning model, and calculates each item evaluation score for each subclass as an output of the machine learning model. Then, the used degree estimation module 102 calculates the evaluation score for each major classification using the weighted points for each major classification, and also calculates the overall evaluation score.

The main items to be checked by the operator for each subcategory can be as follows, as shown in FIG. 7, for example. The subcategory numbered 1 is an hour meter. Subcategory number 2 is abnormal noise and exhaust color. Regarding the subcategory number 3, it is the amount of oil.
The subcategory with number 4 is belt tension. The subcategory numbered 5 is an hour meter. Regarding the subcategory No. 6, it is bearing play. Regarding subclassification No. 7, it is the presence or absence of cracks. Regarding the subcategory number 8, it is chain tension. Regarding the subcategory number 9, it is the looseness at the time of switching. Regarding the subcategory No. 10, it is an oil leak. The subcategory No. 11 is shoe wear and oil amount. The subcategory numbered 12 is wear and tear. The subcategory numbered 13 is an hour meter. Subcategory number 14 is bending, cracking and abrasion. The subcategory No. 15 is tilt and crack. Regarding the subcategory No. 16, it is oil leakage. Regarding the subcategory No. 17, it is chain tension. The subcategory numbered 18 is bending and cracking. The subcategory numbered 19 is bending and cracking. Regarding sub-category No. 20, it is an oil leak. The subcategory numbered 21 is an hour meter. As for the subcategory with number 22, there is a malfunction. The subcategory numbered 23 is bending and cracking. The subcategory numbered 24 is scratches and tears. Regarding the subcategory number 25, it is lit. Regarding the subcategory No. 26, it is cracked. The subcategory numbered 27 is sound.

Moreover, the weighted points shown in FIG. 8 show the points allocated for each major classification when the total is 100 points. In the example shown in FIG. 8, weighting points are set at 20 points for the prime mover, 25 points for the traveling device, 35 points for the cargo handling device, and 20 points for the driver's seat and the like. In this case, the maximum classification evaluation score for the prime mover is 20. Further, the maximum classification evaluation score for the traveling device is 25. Further, the maximum classification evaluation score for cargo handling equipment is 35. Further, the maximum classification evaluation score for the driver's seat and the like is 20. The weighting points can be set based on, for example, the priority of maintenance for each major classification, the importance of performance for each major classification from the perspective of the entire vehicle, and the like.

The item evaluation score is an evaluation point for each subcategory. The item evaluation score is a value within the evaluation point range. For example, the degree of deterioration of the engine body in subclass No. 2 is evaluated using item evaluation points in the range of 0 to 5. When an operator performs an inspection, for example, an item evaluation score of 0 is when the confirmed results are a clear abnormal noise and an exhaust color ranging from gray to black. Item evaluation score 1 is when the confirmed results are that there is abnormal noise and the exhaust color is slightly white. Item evaluation score 2 is when the confirmed results are that there is abnormal noise and the exhaust color is transparent. Item evaluation score 3 is when the confirmed results are a slight abnormal noise and the exhaust color is slightly white. Item evaluation score 4 is when the confirmed results are a slight abnormal noise and a transparent exhaust color. Item evaluation score 5 is when the confirmed results are that there is no abnormal noise and the exhaust color is transparent. For example, an item evaluation score of 0 corresponds to a state in which maintenance is recommended before use. For example, an item evaluation score of 5 corresponds to a state in which no maintenance is required before use.

The major category evaluation score is calculated by dividing the weighted score for each major category by the total value of the maximum value of each evaluation point range for each item evaluation score as a coefficient. It is the value multiplied by the coefficient. For example, for the prime mover, the total value of the maximum values of each evaluation score range is 20, and the weighting point is 20, so the coefficient is 1, and the total value of each item evaluation score becomes the major classification evaluation score. Regarding the traveling device, the total value of the maximum value of each evaluation point range is 36, and the weighting point is 25, so the coefficient is 25/36 (= approximately 0.69), and the total value of each item evaluation point is 20. Approximately 13.9 multiplied by the coefficient 25/36 becomes the major classification evaluation score.

Moreover, the overall evaluation score is the total value of the evaluation points of each major classification. In the example shown in FIG. 8, the score is 34.2 out of 100 points.

The maintenance module 103 shown in FIG. 1 estimates maintenance candidates suitable for the used vehicle and the cost required for the maintenance based on the degree of used vehicle. In this embodiment, the list of multiple maintenance candidates estimated by the maintenance module 103 is referred to as a maintenance menu. FIG. 9 shows an example of a maintenance menu displayed on the user terminal 3. The user terminal 3 is, for example, a computer such as a personal computer, a smartphone, or a tablet terminal, and is a terminal operated by a buyer. In the example shown in FIG. 9, three maintenance courses (A course, B course, and C course) that are maintenance candidates are displayed. In this example, course A is a maintenance candidate that increases each item evaluation score shown in FIG. 8 to about 70% to 80% of each maximum value. In the example shown in FIG. 9, the estimated result that the overall evaluation score of second-hand goods will increase from 34.2 to 79.2 in the case of course A and the expected cost are displayed. In the B course, the major classification shown in Figure 8 increases the score of each item for cargo handling equipment to about 70% to 80% of the maximum value, and increases the score for each item for which the score is 0 for items other than cargo handling equipment. This is a candidate for maintenance to raise the value to 1. In the example shown in FIG. 9, the estimated result that the overall evaluation score of second-hand goods will increase from 34.2 to 56.7 in the case of course B and the expected cost are displayed. FIG. 10 shows an example of the display when course B is selected on the display screen shown in FIG. In the display example shown in FIG. 10, the estimated results of each evaluation point before maintenance and each evaluation point after maintenance for course B are shown in comparison. Further, the C course is a maintenance candidate that raises each item evaluation score from 0 to 1. In the example shown in FIG. 9, the estimated result that the overall evaluation score of second-hand goods will increase from 34.2 to 41.7 in the case of C course and the expected cost are displayed.

The maintenance module 103 inputs, for example, information (numerical values) representing the combination of maintenance items and contents and evaluation points for each item of usedness before maintenance as explanatory variables, and outputs evaluation points for each item after maintenance. Determine the combination of maintenance items and contents using a machine learning model. Using the trained machine learning model, the maintenance module 103 inputs the evaluation score for each item of usedness before maintenance, tries to input multiple combinations of maintenance items and contents, and selects each maintenance candidate. A combination of maintenance items and contents is determined to obtain an output as close as possible to the set target value of each item evaluation score after maintenance (within a predetermined threshold). In this case, the machine learning model performs machine learning using a data set that includes combinations of maintenance items and contents that have a track record in the past, and evaluation scores for each item of usedness before and after maintenance as training data.

The maintenance module 103 estimates the expected cost when performing the determined combination of maintenance items and contents. The maintenance module 103 refers to, for example, the maintenance work record DB 15 and the maintenance cost record DB 16, extracts costs similar to the combination of maintenance items and contents, and determines the determined maintenance items and contents based on the extracted costs. Estimate the cost depending on the combination.

Further, the used vehicle sales system 12 is, for example, a web server, and transmits and receives predetermined information to and from the user terminal 3 operated by the buyer of the used vehicle via a communication line. For example, the used vehicle sales system 12 presents to the user terminal 3 the sale price estimated by the price estimation module 101 for the used vehicle specified by the seller. Additionally, the used vehicle sales system 12 presents the user terminal 3 with the sales price estimated by the used degree estimation module 102. Further, the used vehicle sales system 12 presents the used degree estimated by the used degree estimation module 102 to the user terminal 3. Furthermore, the used vehicle sales system 12 presents the user terminal 3 with the maintenance menu and estimated cost estimated by the maintenance module 103. The used vehicle sales system 12 also exchanges information regarding the sale with the user terminal 3.

(Example of operation of used vehicle information processing device)
An example of the operation of the used vehicle information processing device 1 shown in FIG. 1 will be described with reference to FIG. 11. In the process shown in FIG. 11, the process from step S101 to S110 is the process between the user terminal 2 on the seller side and the used vehicle information processing device 1, and the process from step S111 to S118 is the process between the user terminal 3 on the buyer side. This is a process between the used vehicle information processing device 1 and the used vehicle information processing device 1.

In the process shown in FIG. 11, the used vehicle purchase system 11 performs a predetermined authentication process, and then inputs vehicle-related information such as used vehicle label information 201 from the user terminal 3 (step S101). The vehicle related information includes, for example, used vehicle label information 201 and information for improving its reliability.

Next, the used vehicle purchase system 11 assigns a predetermined identification number to the vehicle (step S102). Next, the used degree estimation module 102 estimates the used degree of the vehicle (step S103). Next, the used vehicle purchase system 11 presents the estimated used degree of the vehicle to the user terminal 2 (step S104). Next, the price estimation module 101 estimates the purchase price (step S105). Next, the used vehicle purchase system 11 presents the estimated purchase price to the user terminal 2 (step S106). Next, the used vehicle purchase system 11 determines whether or not the purchase at the purchase price presented at the user terminal 2 has been agreed upon (step S107).

If no agreement has been reached (step S107: No), the used vehicle purchase system 11 determines whether the number of disagreements has exceeded a predetermined number (step S108). If the number of disagreements is not greater than or equal to the predetermined number (step S108: No), the price estimation module 101 estimates the purchase price again, for example after changing the estimation method (step S105). Next, the used vehicle purchase system 11 presents the estimated purchase price to the user terminal 2 (step S106). If the number of disagreements is equal to or greater than the predetermined number (step S108: Yes), the used vehicle purchase system 11 ends the process shown in FIG. 11.

On the other hand, if an agreement is reached (step S107: Yes), the used vehicle information DB 13 and purchase/sales record DB 14 record that a sales contract has been concluded and store purchase information (step S109). The purchase information includes, for example, vehicle identification information shown in FIGS. 3 and 4, buyer identification information, used vehicle label information (specification information), used vehicle label information (usage information), used degree information, sale completion date and time (purchase), Contains purchase price information.

After that, in the used vehicle sales system 12, when there is an inquiry about the vehicle after executing a predetermined authentication process etc. from the user terminal 3 on the buyer side, the maintenance module 103 sends information about the maintenance menu, cost, and used condition after maintenance. is calculated (step S111). Next, the used vehicle sales system 12 presents the maintenance menu, cost, and degree of used vehicle after maintenance to the user terminal 3 (step S112). Next, the price estimation module 101 estimates the sale price (step S113). Next, the used vehicle sales system 12 presents the used condition of the vehicle before maintenance and the sale price to the user terminal 3 (step S114).

Next, the used vehicle sales system 12 determines whether or not the sale at the sale price presented at the user terminal 3 has been agreed upon (step S115).

If no agreement has been reached (step S115: No), the used vehicle sales system 12 determines whether the number of disagreements has exceeded a predetermined number (step S116). If the number of disagreements is not equal to or greater than the predetermined number (step S116: No), the price estimation module 101 estimates the selling price again, for example after changing the estimation method (step S113). Next, the used vehicle sales system 12 presents the estimated sales price to the user terminal 3 (step S114). If the number of disagreements is equal to or greater than the predetermined number (step S116: Yes), the used vehicle sales system 12 ends the process shown in FIG. 11.

On the other hand, if an agreement is reached (step S115: Yes), the used vehicle information DB 13 and the purchase/sales record DB 14 record that the sales contract has been concluded and store the sales information (step S117). The sale information includes, for example, seller identification information, sale completion date and time (sale), and sale price information shown in FIGS. 3 and 4. Here, the process shown in FIG. 11 ends.

Next, an example of the flow of each information in the used vehicle information processing device 1, the user terminal 2, and the user terminal 3 will be described with reference to FIGS. 12 to 18. FIG. 12 shows the flow of each information corresponding to steps S101 to S105 shown in FIG. 11. FIG. 13 shows the flow of each information corresponding to step S106, step S107: Yes to step S110 shown in FIG.
FIG. 14 shows the flow of each information corresponding to step S106 and step S107: No to step S108: Yes shown in FIG. FIG. 15 shows the flow of each information corresponding to steps S111 to S112 shown in FIG. 11. FIG. 16 shows the flow of each information corresponding to steps S113 to S114 shown in FIG. 11. FIG. 17 shows the flow of each information corresponding to step S114, step S115: Yes to step S118 shown in FIG. FIG. 18 shows the flow of each information corresponding to step S114 and step S115: No to step S115: Yes shown in FIG.

In the example shown in FIG. 12, when used vehicle label information 201 is input at user terminal 2 (S201), used vehicle label information 201 is sent from user terminal 2 to used vehicle purchasing system 11 (S202). The used vehicle purchase system 11 assigns a number (S203), and the used vehicle label information 201 is sent to the used vehicle information DB 13 and registered (S204). The used degree estimation module 102 acquires the used vehicle label information 201 from the used vehicle information DB 13 (S205), for example, according to the number assigned by the used vehicle purchase system 11 (S203). Further, the price estimation module 101 acquires the used vehicle label information 201 from the used vehicle information DB 13 (S206) according to the number assigned by the used vehicle purchase system 11 (S203), and also acquires the used vehicle label information 201 from the purchase/sales record information DB 14. Acquire performance information (S207).

When the used degree estimation module 102 estimates the used degree (S208), the used degree information indicating the estimated used degree is sent to the used vehicle purchase system 11 (S209) and is registered in the used vehicle information DB 13 (S210). . The used vehicle purchasing system 11 sends the used degree information to the user terminal 2 (S211), and the used degree is presented on the user terminal 2 (S212).

On the other hand, the price estimation module 101 estimates the purchase price (S213 (FIGS. 12 and 13)), and purchase price information indicating the estimated purchase price is sent to the used vehicle purchase system 11 (S214). The used vehicle purchase system 11 sends the purchase price information to the user terminal 2 (S215), and the purchase price is presented at the user terminal 2 (S216). Here, when an input to the effect of agreement is made on the user terminal 2 (S217), sale consent information is sent from the user terminal 2 to the used vehicle purchase system 11 (S218).

The sale agreement information is sent from the used vehicle purchase system 11 to the used vehicle information DB 13 (S219), and further sent from the used vehicle information DB 13 to the purchase/sales record information DB 14 (S220). Next, the purchase/sales record information DB 14 sends the sale information to the used vehicle information DB 13 (S221), and the used vehicle information DB 13 sends the sale information to the used vehicle purchase system 11 (S222). The used vehicle purchase system 11 sends the sale information to the user terminal 2 (S223), and the sale information is presented on the user terminal 2 (S224).

On the other hand, as shown in FIG. 14, when an input indicating disagreement is made on the user terminal 2 in response to the presentation of the purchase price (S216) (S225), the sale refusal information is transmitted from the user terminal 2 to the used vehicle purchasing system. 11 (S226).

The sale refusal information is sent from the used vehicle purchase system 11 to the used vehicle information DB 13 (S227), and further sent from the used vehicle information DB 13 to the purchase/sales record information DB 14 (S228). Next, the purchase/sales record information DB 14 deletes the information related to the relevant number, and then sends the failed sale information to the used vehicle information DB 13 (S229), and the used vehicle information DB 13 deletes the information related to the relevant number. After that, the transaction failure information is sent to the used vehicle purchase system 11 (S230). The used vehicle purchase system 11 sends the unsuccessful sale information to the user terminal 2 (S231), and the unsuccessful sale information is presented on the user terminal 2 (S232).

Further, in the example shown in FIG. 15, when information for identifying a vehicle (vehicle identification information) is input at the user terminal 3 (S301), the vehicle identification information is sent from the user terminal 3 to the used vehicle sales system 12 (S302). ). Here, the used vehicle sales system 12 identifies the target vehicle (S303). Next, in response to vehicle identification (S303), the maintenance module 103 acquires used degree information from the used vehicle information DB 13 (S304), and the price estimation module 101 acquires used degree information from the used vehicle information DB 13 (S305). ).

The maintenance module 103 further acquires maintenance work performance information from the maintenance work performance DB 16 (S306) and acquires maintenance cost performance information from the maintenance cost performance DB 15 (S307). Next, the maintenance module 103 generates a maintenance menu (S308), and maintenance menu information indicating the maintenance menu is sent to the used vehicle sales system 12 (S309). The used vehicle sales system 12 sends maintenance menu information to the user terminal 3 (S310), and the maintenance menu is presented on the user terminal 3 (S311).

Further, as shown in FIG. 16, the price estimation module 101 acquires sales performance information from the purchase/sales performance DB 14 (S312), and estimates the sale price (S313). Sale price information indicating the estimated sale price is sent to the used vehicle sales system 12 (S314). The used vehicle sales system 12 sends the sale price information to the user terminal 3 (S315), and the sale price is presented at the user terminal 3 (S316).

Further, as shown in FIG. 17, on the user terminal 3, an input to the effect of agreement is made in response to the presentation of the sale price (S316) (S317), and a candidate is selected in response to the presentation of the maintenance menu (S311). When this input is made (S318), purchase approval information is sent to the used vehicle sales system 12 (S319), and maintenance menu selection information is sent to the used vehicle sales system 12 (S320). The used vehicle sales system 12 registers the maintenance menu selection information in the maintenance work record DB 16 (S321) and also in the maintenance cost record DB 15 (S322). Further, the used vehicle sales system 12 sends purchase approval information to the purchase/sales record DB 14 (S323).

Next, the purchase/sales record DB 14 sends the sales completion information to the used vehicle sales system 12 (S324), and the used vehicle sales system 12 sends the sales completion information to the user terminal 3 (S325). is presented (S326). The purchase/sales record DB 14 sends sales completion information to the used vehicle information DB 13 (S327).

Further, as shown in FIG. 18, when an input is made on the user terminal 3 to the effect that the sales price is not agreed to (S316) (S328), purchase refusal information is sent to the used vehicle sales system 12. (S329). The used vehicle sales system 12 sends the purchase refusal information to the purchase/sales record DB 14 (S330). The purchase/sales record DB 14 sends information on failed sales to the used vehicle sales system 12 (S331), the used vehicle sales system 12 sends information on failed sales to the user terminal 3 (S332), and the user terminal 3 presents the information on failed sales. (S333).

Next, with reference to FIG. 19, a modification of the operation example of the used vehicle information processing device 1 described with reference to FIG. 11 will be described. In the process shown in FIG. 11, the timing of the establishment of the purchase contract and the establishment of the sale contract are different. In contrast, in the process shown in FIG. 19, the purchase contract and the sale contract are established at the same time. In the process shown in FIG. 19, the process in step S109 shown in FIG. 11 is deleted, and the process in step S117 and the process in step S118 are changed (shown as step S117a and step S118a). Other processing is the same in FIG. 11 and FIG. 19. In step S117a, processing associated with the establishment of a purchase and sale contract is performed, and in step S118a, purchase and sale information is stored.

(Actions/effects and modified examples of the first embodiment)
As described above, according to this embodiment, both the buyer side and the seller side can appropriately understand the deterioration state of a used vehicle.

According to this embodiment, when a sales contract is concluded between a seller, an intermediary, and a buyer, information on the used vehicle is linked to purchase/sales information, and vehicle usedness information and added to the database. It can be used as data for subsequent price estimation and used condition estimation.

Note that for the data held in each database, an arbitrary time period can be set, for example. For example, data from before a certain period may not be used for price estimation, second-handness estimation, maintenance menu selection and cost estimation.

In addition, among the data held in each database, cases were sold extremely cheaply or sold extremely high due to special circumstances, cases where maintenance was not normally performed, cases where maintenance was performed extremely cheaply due to special circumstances, and cases where maintenance was performed extremely cheaply or extremely A function may be added to flag unique data such as cases in which high maintenance costs are received. For example, it is possible to exclude these data when estimating the price, estimating the used condition, selecting a maintenance menu, and estimating its cost.

In initial setting of price estimation, deterioration level estimation, maintenance menu selection and cost estimation algorithm, statistical methods (multiple regression analysis) are used to etc.) or various AI (artificial intelligence), and perform trial calculations on the remaining 20% to select an algorithm with a high accuracy rate.

Note that the process shown in Figure 11 presents the purchase price, which is calculated by adding a certain profit to the estimation result calculated by the price estimation algorithm, and the used degree calculated by the used degree estimation algorithm to the seller, and if an agreement is reached, the buyer This is a case where a purchase contract is reached without a decision being made. Furthermore, in addition to the current used condition of the vehicle, it is also possible to present to the purchaser the various maintenance menus and their prices, and changes in the used condition when maintenance is performed.

In addition, in the process shown in FIG. 19, first, the purchase price, which is the estimation result calculated by the price estimation algorithm plus a certain profit, and the second-hand degree calculated by the second-hand degree estimation algorithm are presented to the seller, and an agreement is reached. If the purchase is temporarily held. Next, we present the sales price, second-hand condition, selected maintenance menu, maintenance cost with a certain profit added to the estimated price, and when an agreement is obtained, we enter into a purchase contract with the seller and a sales contract with the buyer. be. In addition to the current used condition of the vehicle, it is possible to present to the purchaser the various maintenance menus and their prices, and changes in the used condition when maintenance is performed.

Appropriate price estimation for commercial vehicles is difficult because there is little data on private vehicles and there are many factors that affect price estimation. Furthermore, for sellers, there is no objective data on the degree of deterioration of the used vehicle being sold, making it difficult to judge the validity of the sales price. Furthermore, buyers do not have quantitative data on how much maintenance will improve vehicle performance or how much it will cost. According to this embodiment, the accuracy of price estimation is improved, and it is also possible to present the degree of used condition (degree of deterioration), the degree of recovery of the degree of used condition when various maintenance is performed, and the cost thereof. As a result, it is expected that appropriate used car sales and transactions will become possible and the volume will increase.

In addition, when a sales contract is concluded between a seller, an intermediary, and a buyer, information on the used vehicle, purchase/sale information, vehicle usedness information, and maintenance menus and their costs are linked and added to the database. However, it is easy to use this data as data for the next price estimation (price assessment), pre-owned condition estimation, maintenance menu selection, and cost estimation. and the accuracy of estimating its costs will be improved.

In addition, by eliminating old data that no longer matches the actual situation, the accuracy of price estimation, second-handness estimation, maintenance menu selection, and cost estimation will be improved.

In addition, by eliminating singularity data, the accuracy of price estimation, second-handness estimation, maintenance menu selection, and cost estimation will be improved.

Further, after a certain amount of new data has been accumulated, the estimation accuracy can be further improved by updating the algorithm using this data in a similar manner.

Furthermore, according to the process shown in FIG. 11, it becomes possible to purchase a vehicle from a seller in a relatively short time, and the seller feels secure because he/she makes a buying/selling decision while referring to the objective degree of used vehicle of the vehicle being put up for sale. As a result, transaction intermediaries will be able to secure used vehicles more stably. On the other hand, if a buyer cannot be found, the item will be in stock and there is a risk of a decline in profits, but the buyer is shown the degree of used condition and is also shown the maintenance menu and its price, giving the buyer a sense of security and freedom of choice. This increases the risk of unsold items and reduces the risk of unsold items. The higher the accuracy of price estimation, the higher the accuracy of second-handness estimation, the smaller the accuracy risk of maintenance menu selection and cost estimation, so the amount of information accumulated in each database is enriched, and the price estimation and second-handness It is desirable to use it when the estimation accuracy increases.

Further, according to the process shown in FIG. 19, since the item is purchased from the seller after securing a buyer, there is no risk of the item becoming inventory. However, there is a risk that it will be difficult to secure used vehicles because there is no guarantee that the seller will continue the temporary contract until a buyer is found. An intermediary can present the used condition of a vehicle to both the seller and the buyer, allowing both the seller and the buyer to judge the buying and selling price based on the common index of used condition, and provide the buyer with a maintenance menu and its Since prices are presented, the buyer's sense of security and freedom of choice increases, which increases the success rate of contracts. It is desirable to use this method when the amount of information stored in the database is small and the price estimation accuracy and mid-altitude estimation are low.

<Second embodiment>
Next, a used vehicle information processing device, a used vehicle information processing method, and a program according to a second embodiment of the present disclosure will be described with reference to FIGS. 20 to 22. FIG. 20 is a block diagram illustrating a configuration example of a used vehicle information processing device according to a second embodiment of the present disclosure. FIG. 21 is a flowchart illustrating an example of the operation of the used vehicle information processing device according to the second embodiment of the present disclosure. FIG. 22 is a schematic diagram for explaining an example of the operation of the used vehicle information processing device according to the second embodiment of the present disclosure.

The used vehicle information processing device 1a according to the second embodiment shown in FIG. 20 has a used vehicle information processing unit 10 shown in FIG. The difference is that the corresponding used vehicle information processing section 10a is newly equipped with a used vehicle information conversion module 104. Other configurations are the same in the first embodiment and the second embodiment. The used vehicle information conversion module 104 is a functional configuration that estimates missing information when a part of the usage information 203 included in the used vehicle label information 201 described with reference to FIG. 2 is missing.

In the used vehicle information processing device 1a of the second embodiment, for example, in the process of step S103 shown in FIGS. 11 and 19, as shown in FIG. 21, if there is a omission in the usage information 203 (step S401: Yes) The used vehicle information conversion module 104 estimates and replenishes the missing information (step S402), and the used degree estimation module 102 estimates the used degree (step S403).

For example, in the case of a used vehicle for which the operator cannot obtain repair or maintenance records, the usage information 203 depends on information from the seller of the used vehicle. The information to be excluded may contain errors or omissions. Furthermore, even if data such as maintenance records can be obtained, it is assumed that the inspection items may differ from general maintenance items. Therefore, a situation may arise in which it is difficult to directly input data into the used degree estimation module 102. Furthermore, if usedness estimation is performed with missing data, there is a concern that the accuracy will decrease. Therefore, when the usage information 203 is missing, the used vehicle information conversion module 104 estimates the missing information from other usage information 203 using a learned machine learning model. An example of the operation by the used vehicle information conversion module 104 will be explained.

(1) Formation process of missing data estimation logic (1-1) Classification of used vehicles to be bought and sold First, the usage information 203 is classified by the type of motor and the size and type of the vehicle. For example, forklifts are classified into a total of 10 categories: 3 types of engine forks (small, medium, large) and 7 types of battery forks (counterbalance, reach, picking, rack fork, walkie, explosion-proof type, frozen/refrigerated type). . The aim is to improve the accuracy of estimation by using the usage information 203 of similar vehicles.

(1-2) Collection of usage information 203 for each category Used vehicle label information (usage information) stored in the used vehicle information DB 13 is aggregated for each category in (1-1) and used as source data for machine learning data. shall be. Further, the usage information 203 linked to each vehicle is set as one data set. Note that it is assumed that the hour meter information always exists.

(1-3) Creation of training data Select any number of sets from the data set aggregated in (1-2) and use them as candidates for creating training data (the larger the number of sets, the higher the accuracy rate, but it is important to create logic ). Furthermore, a data set is created by intentionally erasing one piece of usage information 203 (labeled as label information A) from the data set for each selected category, and is used as training data. Furthermore, in addition to label information A, a data set is also created in which usage information 203 (one or more) other than label information A is randomly deleted, and used as training data. The data set before the level information A is deleted is used as the correct data.

(1-4) Building machine learning/estimation logic using training data Perform learning using the dataset prepared in (1-3) above, and if label information A is missing, estimate its value from other data Form logic within machine learning models.

(1-5) Establishment of lineup of missing data estimation logic Implement (1-3) and (1-4) for all usage information 203 other than hour meter information, and make estimation possible even if any data is missing. Create a lineup to match. Note that if there is an item in the usage information 203 for which the estimated accuracy rate of the trained machine learning model is less than a predetermined value (for example, 90%) due to a small number of datasets, the data will not be accumulated. As a temporary measure until the situation is resolved, the following simple estimation will be used for evaluation. If each coefficient information is unknown, it is calculated as 1.0.

Simple estimated evaluation score = maximum value of evaluation point range × (hour meter evaluation score / 10) × industry coefficient × environmental coefficient × baggage coefficient × failure history coefficient × country of use coefficient

An example of the coefficients is shown in FIG.

(2) Missing data estimation process (2-1) Classification of target used vehicle A seller of a used vehicle obtains used vehicle label information 201 via the used car purchasing system 11, Confirm whether it falls into the category.

(2-2) Display of Usage Information 202 of Applicable Category On the user terminal 2, a sheet of usage information 203 of the applicable category is displayed.

(2-3) Importing usage information 203 Usage information 203 is imported into the sheet from the used car purchasing system 11. Note that areas where there is no relevant data will be left blank.

(2-4) Complementing missing data manually Regarding missing data (blank areas), we conduct interviews with sellers of used vehicles, and if we have already acquired a used vehicle, conduct a simple inspection, etc., and supplement the obtained data. input.

(2-5) Estimating missing data using a trained machine learning model When the sheet of usage information 203 whose data has been supplemented in (2-4) above is input to the trained machine learning model of the used car information conversion module 104, (1 Estimation is performed using the missing data estimation logic developed in -5). The estimation result is entered in the blank space of the usage information 203 sheet and is output as output.

According to this embodiment, even if there is a missing item in the usage information 203, the missing blind content can be estimated and complemented.

<Basic configuration example of embodiment>
FIG. 23 is a block diagram showing a basic configuration example of the used vehicle information processing device 1 according to the first embodiment and the used vehicle information processing device 1a according to the second embodiment. A used vehicle information processing device 300 shown in FIG. 23 has a configuration corresponding to the used vehicle information processing device 1 according to the first embodiment and the used vehicle information processing device 1a according to the second embodiment. The used vehicle information processing device 300 shown in FIG. 23 includes an acquisition section 301, a deterioration degree estimation section 302, a presentation section 303, a maintenance estimation section 304, and a used vehicle information estimation section 305.

The acquisition unit 301 acquires used vehicle information including specification information that is information about the specifications of the used vehicle and usage information that is information about the use of the used vehicle. The acquisition unit 301 corresponds to the used vehicle purchase system 11. The used vehicle information corresponds to the used vehicle label information 201.

The degree of deterioration estimating unit 302 estimates the degree of deterioration of the used vehicle using the used vehicle information as an explanatory variable. The deterioration degree estimating unit 302 corresponds to the used degree estimating module 102.

The presenting unit 303 presents the estimated degree of deterioration to the buyer of the used vehicle. The presentation unit 303 corresponds to the used vehicle sales system 12.

The maintenance estimating unit 304 estimates maintenance candidates suitable for the used vehicle and the cost required for the maintenance based on the degree of deterioration. Further, the presenting unit 303 presents the estimated degree of deterioration, candidates, and costs to the buyer side. The maintenance estimation unit 304 corresponds to the maintenance module 103.

Note that the presenting unit 303 may also present the estimated degree of deterioration to the seller of the used vehicle. In this case, the presentation unit 303 also corresponds to the used vehicle purchase system 11.

Further, when there is a missing content in the usage information 203, the used vehicle information estimation unit 305 estimates the missing content using other content in the usage information 203 that is not missing as an explanatory variable. The used vehicle information estimation unit 305 corresponds to the used vehicle information conversion module 104.

Note that the used vehicle is equipped with a prime mover, a traveling device, and a working device, and the deterioration degree estimating unit 302 estimates each predetermined component of the prime mover, each predetermined component of the traveling device, and the predetermined configuration of the working device. The degree of deterioration may be estimated for each element. Here, the working device corresponds to a cargo handling device.

Furthermore, the degree of deterioration estimating unit 302 can estimate the degree of deterioration by setting different weights for the prime mover, the traveling device, and the working device.

According to the used vehicle information processing device 300, it is possible to appropriately grasp the deterioration state of a used vehicle.

<Effect>
In the used vehicle information processing device, used vehicle information processing method, and program configured as described above, used vehicle information (used The present invention includes an acquisition unit 301 that acquires vehicle label information 201), and a deterioration degree estimating unit 302 that estimates the deterioration degree of the used vehicle using the used vehicle information as an explanatory variable. Therefore, according to the used vehicle information processing device, used vehicle information processing method, and program of the embodiment, it is possible to appropriately grasp the deterioration state of a used vehicle.

<Other embodiments>
Although the embodiment of the present disclosure has been described above in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and includes design changes within the scope of the gist of the present disclosure. .

<Computer configuration>
FIG. 24 is a schematic block diagram showing the configuration of a computer according to at least one embodiment.
Computer 90 includes a processor 91, main memory 92, storage 93, and interface 94.
The used vehicle information processing devices 1, 1a, and 300 described above are implemented in a computer 90. The operations of each processing section described above are stored in the storage 93 in the form of a program. The processor 91 reads the program from the storage 93, expands it into the main memory 92, and executes the above processing according to the program. Further, the processor 91 reserves storage areas corresponding to each of the above-mentioned storage units in the main memory 92 according to the program.

The program may be for realizing a part of the functions to be performed by the computer 90. For example, the program may function in combination with other programs already stored in storage or in combination with other programs installed in other devices. Note that in other embodiments, the computer may include a custom LSI (Large Scale Integrated Circuit) such as a PLD (Programmable Logic Device) in addition to or in place of the above configuration. Examples of PLDs include PAL (Programmable Array Logic), GAL (Generic Array Logic), CPLD (Complex Programmable Logic Device), and FPGA (Field Programmable Gate Array). In this case, some or all of the functions implemented by the processor may be implemented by the integrated circuit.

Examples of the storage 93 include HDD (Hard Disk Drive), SSD (Solid State Drive), magnetic disk, magneto-optical disk, CD-ROM (Compact Disc Read Only Memory), and DVD-ROM (Digital Versatile Disc Read Only Memory). , semiconductor memory, etc. Storage 93 may be an internal medium connected directly to the bus of computer 90, or may be an external medium connected to computer 90 via an interface 94 or a communication line. Furthermore, when this program is distributed to the computer 90 via a communication line, the computer 90 that received the distribution may develop the program in the main memory 92 and execute the above processing. In at least one embodiment, storage 93 is a non-transitory, tangible storage medium.

<Additional notes>
The used vehicle information processing device described in each embodiment is understood as follows, for example.

(1) Used vehicle information processing devices 1, 1a, and 300 according to the first aspect provide used vehicle information including specification information that is information about the specifications of a used vehicle and usage information that is information about the use of the used vehicle. an acquisition unit 301 that acquires the used vehicle information, a deterioration degree estimation unit 302 that estimates the degree of deterioration of the used vehicle using the used vehicle information as an explanatory variable, and a presentation unit that presents the estimated degree of deterioration to the buyer of the used vehicle. 303. According to this aspect and each of the following aspects, it is possible to appropriately grasp the deterioration state of a used vehicle.

(2) The used vehicle information processing devices 1, 1a and 300 according to the second aspect are the used vehicle information processing devices 1, 1a and 300 of (1), and are suitable for the used vehicle based on the degree of deterioration. The present invention further includes a maintenance estimating unit 304 that estimates maintenance candidates and costs required for the maintenance, and the presenting unit 303 presents the estimated deterioration degree, the candidates, and the costs to the buyer side.

(3) The used vehicle information processing devices 1, 1a, and 300 according to the third aspect are the used vehicle information processing devices 1, 1a, and 300 of (1) or (2), and the presenting unit 303 is The determined degree of deterioration is also presented to the seller of the used vehicle.

(4) The used vehicle information processing devices 1, 1a, and 300 according to the fourth aspect are the used vehicle information processing devices 1, 1a, and 300 of (1) to (3), and the content of the usage information is missing. If there is, the used vehicle information estimating unit 305 is further provided to estimate the missing content using other content of the usage information that is not missing as an explanatory variable.

(5) The used vehicle information processing devices 1, 1a and 300 according to the fifth aspect are the used vehicle information processing devices 1, 1a and 300 of (1) to (4), in which the used vehicle is driven by a prime mover and and a working device, and the deterioration degree estimating unit calculates the degree of deterioration for each predetermined component of the prime mover, for each predetermined component of the traveling device, and for each predetermined component of the work device. Estimate the degree of deterioration.

(6) The used vehicle information processing devices 1, 1a, and 300 according to the sixth aspect are the used vehicle information processing devices 1, 1a, and 300 of (1) to (4), and the deterioration degree estimating unit 302 is , the degree of deterioration is estimated by setting different weights for the prime mover, the traveling device, and the working device.

1, 1a, 300...Used vehicle information processing device 10, 10a...Used vehicle information processing unit 11...Used vehicle purchase system 12...Used vehicle sales system 101...Price estimation module 102...Used degree estimation module 103...Maintenance module 104...Used Vehicle information conversion module 301...acquisition section 302...degradation degree estimation section 303...degradation degree presentation section 304...maintenance estimation section 305...used vehicle information estimation section

Claims (8)

an acquisition unit that acquires used vehicle information including specification information that is information about the specifications of the used vehicle and usage information that is information about the use of the used vehicle;
a deterioration degree estimation unit that estimates the deterioration degree of the used vehicle using the used vehicle information as an explanatory variable;
a presentation unit that presents the estimated degree of deterioration to a buyer of the used vehicle;
A used vehicle information processing device comprising: further comprising a maintenance estimation unit that estimates maintenance candidates suitable for the used vehicle and costs required for the maintenance based on the degree of deterioration,
The used vehicle information processing device according to claim 1, wherein the presentation unit presents the estimated degree of deterioration, the candidate, and the cost to the buyer. The used vehicle information processing device according to claim 2, wherein the presentation unit also presents the estimated degree of deterioration to a seller of the used vehicle. If there is a missing content in the usage information, a used vehicle information estimation unit that estimates the missing content using other content that is not missing in the usage information as an explanatory variable;
The used vehicle information processing device according to any one of claims 1 to 3, further comprising: The used vehicle is equipped with a prime mover, a traveling device, and a working device,
The degree of deterioration estimating unit estimates the degree of deterioration for each predetermined component of the prime mover, for each predetermined component of the traveling device, and for each predetermined component of the working device. used vehicle information processing equipment. The used vehicle information processing device according to claim 5, wherein the deterioration degree estimating unit estimates the deterioration degree by setting different weights for the prime mover, the traveling device, and the working device. obtaining used vehicle information including specification information that is information about the specifications of the used vehicle and usage information that is information about the use of the used vehicle;
estimating the degree of deterioration of the used vehicle using the used vehicle information as an explanatory variable;
presenting the estimated degree of deterioration to a buyer of the used vehicle;
Used vehicle information processing method including. obtaining used vehicle information including specification information that is information about the specifications of the used vehicle and usage information that is information about the use of the used vehicle;
estimating the degree of deterioration of the used vehicle using the used vehicle information as an explanatory variable;
presenting the estimated degree of deterioration to a buyer of the used vehicle;
A program that causes a computer to execute.

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