WO2020202450A1

WO2020202450A1 - Personality analysis method, personality analysis device, information processing method using personality data, and information processing device using personality data

Info

Publication number: WO2020202450A1
Application number: PCT/JP2019/014557
Authority: WO
Inventors: 圭祐森島; 謙作磯部; 中尾　浩; 佑輔梅澤; 裕章木邨
Original assignee: ヤマハ発動機株式会社
Priority date: 2019-04-01
Filing date: 2019-04-01
Publication date: 2020-10-08
Also published as: TWI807180B; JPWO2020204104A1; JP7280945B2; WO2020204104A1; TW202038175A

Abstract

Provided is a personality analysis method in which personality data can be acquired while a degree of freedom in designing hardware resources is increased. This personality analysis method involves: acquiring personality conversion data generated by associating personality data with leaning vehicle traveling data on the basis of data-conversion-use leaning vehicle traveling data which relates to traveling data of leaning vehicles for data conversion, acquired when a plurality of drivers drive and manipulate leaning vehicles for data conversion; acquiring analysis-use leaning vehicle traveling data relating to traveling data of a leaning vehicle for analysis, acquired when a driver to be analyzed drives the leaning vehicle for analysis; converting the analysis-use leaning vehicle traveling data into conversion personality data relating to the personality of the driver to be analyzed by using the personality conversion data; and generating and outputting output personality data by using the converted conversion personality data.

Description

Personality analysis method, personality analyzer, information processing method using personality data, and information processing device using personality data

The present invention relates to a personality analysis method for analyzing the personality of an analysis subject, a personality analyzer, an information processing method using personality data, and an information processing device using personality data.

Information processing devices that perform information processing using the customer's personality are known. As a configuration for performing information processing using the personality of the customer, for example, the configurations disclosed in Patent Documents 1 to 4 are known.

Patent Document 1 discloses a gift advice method that determines a user's interest level based on the product content selected by the user and recommends a gift to the user according to the interest level.

Patent Document 2 discloses an online matching system. Specifically, in this matching system, a participant profile number is determined for each participant, and the participant attends an online meeting according to the number. In this online conference, feedback on other participants is received from a participant to determine whether there is a two-way match between the participants in the online conference.

Patent Document 3 discloses a system for determining an individual's risk level. Specifically, this system processes personal information such as eyeball-related information to generate cognitive information about an individual, and uses the cognitive information to determine an individual's risk level. The cognitive information is compared to the individual's baseline cognitive information to determine the level of risk for the individual.

Patent Document 4 discloses a system for selecting and customizing an advertisement provided to a user. Specifically, this system monitors the user's dialogue in the virtual game environment and indirectly determines the user characteristics based on the dialogue content. The system customizes selected advertisements for users based on user profiles generated from user characteristics and displays them to users in a virtual game environment.

Further, in an information processing system that processes information using a user's personality, a configuration is also known in which the personality data is acquired in a question-and-answer format for the user. As described above, as a configuration for acquiring personality data in a question-and-answer format for a user, for example, a configuration disclosed in Patent Documents 5 and 6 is known.

Patent Document 5 discloses a method for evaluating an economic personality. Specifically, in this method, a questionnaire is given to the user to evaluate the financial personality. Then, in the above method, the investment-related attitude of the user is evaluated based on the result of the questionnaire, and multidimensional economic personal information is generated. In the method, a user's risk profile is constructed from the multidimensional economic personal information.

Patent Document 6 discloses a method of measuring and managing risk in consideration of human behavior. This method uses objective and subjective data to measure and manage operational risk, credit risk and / or market risk within an organization. Specifically, in this method, psychological measurement and / or other personality assessment tools are applied to the selected person, and the results are accumulated as subjective data in the measurement and management system, along with objective data. ..

U.S. Patent Publication No. 2018/0130115 International Publication 2016/000069 U.S. Patent Publication 2015/0025917 U.S. Pat. No. 9,152984 U.S. Patent Publication 2011/0251978 U.S. Patent Publication No. 2005/0278245

By the way, when information processing is performed using the user's personality as described above, in order to perform information processing with higher accuracy, data of the essential personality with less arbitrariness of the user is desired.

When seeking the personality of a user from the results obtained in the question-and-answer format as in Patent Documents 4 and 5 described above, in order to obtain an essential personality with less arbitrariness, the number of questions with different expressions may be increased or questions may be asked. It is necessary to add a question about the false discovery scale (Lyscale) in. Therefore, since the number of questions to the user increases, the types of data processed by the system become very large.

In this way, when the types of data processed by the system become extremely large, the load on the hardware of the system increases. Therefore, since the hardware resources required by the system increase, the design of the hardware resources of the system is restricted. Therefore, the degree of freedom in designing the hardware resources of the system is reduced.

An object of the present invention is to provide a personality analysis method capable of acquiring personality data while increasing the degree of freedom in designing hardware resources.

As a result of examining a personality analysis method that can acquire personality data while increasing the degree of freedom in designing hardware resources, the present inventors have come up with the following configuration.

The personality analysis method according to the embodiment of the present invention is a personality analysis method for analyzing the personality of the person to be analyzed. This personality analysis method is a method of analyzing a lean vehicle for data conversion obtained when a plurality of drivers operate a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left. Based on the lean vehicle driving data for data conversion related to the driving data, the personality conversion data generated by associating the personality data indicating the personality with the lean vehicle driving data which is the driving data of the lean vehicle is acquired. The personality analysis method is a traveling of the lean vehicle for analysis obtained when the person to be analyzed drives and operates a lean vehicle for analysis that tilts to the right when turning right and tilts to the left when turning left. Acquire lean vehicle driving data for analysis related to the data. Using the acquired personality conversion data, the acquired lean vehicle running data for analysis is converted into conversion personality data related to the personality of the analysis target person. The personality analysis method uses the converted converted personality data to generate output personality data for output. The personality data for the generated output is output.

When driving a lean vehicle, the driver makes many decisions from many options and is easily exposed to external stress. Therefore, the lean vehicle driving data, which is the driving data of the lean vehicle driven by the driver, is less arbitrariness and tends to strongly show the essential personality of the driver.

Therefore, by setting the driver who drives and operates the lean vehicle as the analysis target person who analyzes the personality, the personality of the analysis target person can be acquired. By using the running data of the lean vehicle for the personality analysis, it is possible to reduce the types of data processed by the personality analysis device and reduce the hardware load of the device. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be increased.

Therefore, personality data can be acquired while increasing the degree of freedom in designing hardware resources.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The lean vehicle driving data for data conversion is a change in driving operation for the lean vehicle for data conversion by the driver from data that does not reflect the change in driving operation for the lean vehicle for data conversion by the driver. Contains a lot of data that reflects. The lean vehicle driving data for analysis shows that the change in driving operation for the lean vehicle for analysis by the analysis target person is different from the data that does not reflect the change in driving operation for the lean vehicle for analysis by the analysis target person. Contains a lot of reflected data.

With this configuration, the lean vehicle driving data, which is the driving data of the lean vehicle driven by the driver, reflects the change in the driving operation of the lean vehicle after the driver judges. Therefore, the lean vehicle driving data, which is the driving data of the lean vehicle operated by the driver, is less arbitrariness and the essential personality of the driver is more likely to appear.

Therefore, it is possible to analyze the personality of the analysis target person who is the driver more accurately. Further, by using the lean vehicle traveling data in which the data type is specified, the type of data processed by the device for analyzing personality can be reduced, and the hardware load of the device can be further reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.

Therefore, it is possible to acquire more accurate personality data while increasing the degree of freedom in designing hardware resources.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The lean vehicle driving data for data conversion is the lean vehicle driving operation input data for data conversion related to the driving operation input to the lean vehicle for data conversion by the driver, and the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion related to and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion. The lean vehicle driving data for analysis is related to the lean vehicle driving operation input data for analysis related to the driving operation input to the lean vehicle for analysis by the analysis subject, and the behavior of the lean vehicle for analysis. It includes at least one of lean vehicle behavior data for analysis and lean vehicle position data for analysis related to the position of the lean vehicle for analysis.

As a result, the lean vehicle driving data used when converting to personality data related to the personality of the analysis target person includes data that more reflects the personality of the analysis target person who is the driver.

That is, the lean vehicle driving operation input data regarding the driving operation input to the lean vehicle by the driver and the lean vehicle behavior data regarding the behavior of the lean vehicle are, for example, the driver's sensitivity to environmental stimuli and stress, and the strength of anxiety and tension. And so on. In addition, the lean vehicle position data regarding the position of the lean vehicle is related to the personality such as the driver's mental state and personality.

With this configuration, the personality of the analysis target person who is the driver can be analyzed more accurately by using the lean vehicle driving data. Further, by using the lean vehicle traveling data in which the data type is specified, the type of data processed by the device for analyzing personality can be reduced, and the hardware load of the device can be further reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion further includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels. The lean vehicle travel data for analysis further includes lean vehicle travel environment data for analysis related to the travel environment in which the lean vehicle for analysis travels.

Lean vehicle driving environment data includes, for example, map data. The map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. The lean vehicle driving environment data can be used for analyzing personality such as the personality of the person to be analyzed, together with the lean vehicle driving operation input data, the lean vehicle behavior data, and the lean vehicle position data.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road. The lean vehicle traveling data for analysis includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for analysis travels on a road other than a public road.

When a driver traveling on a public road is operating a lean vehicle, the driver has more judgments, has more choices of judgment, and is easily exposed to external stress. The driver's personality is more likely to appear in the data. In addition, since lean vehicles have higher maneuverability and convenience than non-lean vehicles, lean vehicles tend to be used for various purposes and frequently used. Therefore, the driver's personality is more likely to appear in the driving data of a lean vehicle traveling on a public road. That is, the driving data of a lean vehicle traveling on a public road has less arbitrariness of the driver and more reflects the essential personality of the driver.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for data conversion, but a plurality of data are left. The lean vehicle traveling data for analysis includes data in a state where a plurality of judgment options of the analysis target person are limited by vehicles around the lean vehicle for analysis, but a plurality of data are left.

With this configuration, the lean vehicle driving data in the state where the driver's judgment options are limited but a plurality of judgment options are left is compared with the lean vehicle driving data in the state where the driver's judgment options are not left. , Reflects the driver's personality more clearly. Therefore, it is possible to more accurately analyze the personality of the analysis target person who is the driver by using the lean vehicle driving data in a state where the driver's judgment options are limited but a plurality of them are left. Further, by using the lean vehicle traveling data in which the data type is specified, the type of data processed by the device for analyzing personality can be reduced, and the hardware load of the device can be further reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion includes data in a state where at least one of a passenger and an object is mounted. The lean vehicle driving data for analysis includes data in a state where at least one of a passenger and an object is mounted.

A lean vehicle equipped with at least one of a passenger and an object is more likely to be restricted in the driver's judgment options than a vehicle not equipped with at least one of a passenger and an object. Therefore, it is possible to more accurately analyze the personality of the analysis target person who is the driver by using the lean vehicle driving data including the data in the state where at least one of the passenger and the object is mounted. Further, by using the lean vehicle traveling data in which the data type is specified, the type of data processed by the device for analyzing personality can be reduced, and the hardware load of the device can be further reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The converted conversion personality data is stored. Using the plurality of stored conversion personality data, the personality data for the output is generated.

By using a plurality of converted personality data, it is possible to analyze the personality of the analysis target person who is the driver of the lean vehicle more accurately.

From another point of view, the personality analysis method of the present invention preferably includes the following configurations. The personality data for output is generated as information processing personality data used for further information processing.

As a result, the personality data obtained by the personality analysis method using the lean vehicle driving data of the lean vehicle driven and operated by the analysis target person can be used in a further information processing device.

Therefore, it is possible to acquire personality data that can be used for further information processing while increasing the degree of freedom in designing hardware resources.

The personality analyzer according to the embodiment of the present invention is a personality analyzer that analyzes the personality of the person to be analyzed. This personality analyzer is a lean vehicle for data conversion obtained when a plurality of drivers operate a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left. Personality conversion that acquires personality conversion data generated by associating personality data indicating personality with lean vehicle driving data that is lean vehicle driving data based on lean vehicle driving data for data conversion related to the driving data of The data acquisition unit and the running data of the lean vehicle for analysis obtained when the analysis target person operates the lean vehicle for analysis that tilts to the right when turning right and tilts to the left when turning left. Using the lean vehicle driving data acquisition unit for analysis that acquires the lean vehicle driving data for analysis and the acquired personality conversion data, the acquired lean vehicle driving data for analysis is used as the personality of the person to be analyzed. A personality data conversion unit that converts to related conversion personality data, an output personality data generation unit that generates personality data for output to be output using the converted conversion personality data, and the generated output. It is provided with a data output unit that outputs personality data for the user.

From another point of view, the personality analyzer of the present invention preferably includes the following configurations. The lean vehicle driving data for data conversion is a change in driving operation for the lean vehicle for data conversion by the driver from data that does not reflect the change in driving operation for the lean vehicle for data conversion by the driver. Contains a lot of data that reflects. The lean vehicle driving data for analysis shows that the change in driving operation for the lean vehicle for analysis by the analysis target person is different from the data that does not reflect the change in driving operation for the lean vehicle for analysis by the analysis target person. Contains a lot of reflected data.

From another point of view, the personality analyzer of the present invention preferably includes the following configurations. The lean vehicle driving data for data conversion is the lean vehicle driving operation input data for data conversion related to the driving operation input to the lean vehicle for data conversion by the driver, and the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion related to and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion. The lean vehicle driving data for analysis is related to the lean vehicle driving operation input data for analysis related to the driving operation input to the lean vehicle for analysis by the analysis subject, and the behavior of the lean vehicle for analysis. It includes at least one of the lean vehicle behavior data for analysis and the lean vehicle position data for analysis related to the position of the lean vehicle for analysis.

From another point of view, the personality analyzer of the present invention preferably includes the following configurations. The lean vehicle traveling data for data conversion further includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels. The lean vehicle travel data for analysis further includes lean vehicle travel environment data for analysis related to the travel environment in which the lean vehicle for analysis travels.

From another point of view, the personality analyzer of the present invention preferably includes the following configurations. The personality data for output is generated as information processing personality data used for further information processing.

The information processing method according to the embodiment of the present invention is an information processing method using the output personality data generated as the information processing personality data by the above-mentioned personality analysis method. This information processing method acquires the output personality data. The information processing method acquires first data different from the output personality data. The information processing method uses the output personality data and the first data to generate the output personality data and second data different from the first data. The information processing method outputs the second data.

The information processing method using the personality data includes the information processing method as described in the patent document described in the background technology. However, it is not limited to the information processing method described in the patent document described in the background technology. Any information processing method that uses personality data may be used. For example, the first data and the second data may be data related to finance, insurance, market, goods, services, environment or customers used in businesses such as finance, insurance, sales and advertising.

As a result, the acquired personality data and acquisition using the personality data output using the lean vehicle driving data including the less arbitrariness and the essential driver's personality and the first data different from the output personality data. The second data different from the first data is generated and output. Therefore, it is possible to generate and output the second data with higher accuracy.

Therefore, it is possible to generate and output more accurate second data using the personality data while increasing the degree of freedom in designing the hardware resource that executes the information processing method using the personality data.

The information processing device according to the embodiment of the present invention is an information processing device that uses the personality data for output generated as the personality data for information processing by the personality analyzer described above. This information processing device includes an output personality data acquisition unit that acquires the output personality data, a first data acquisition unit that acquires first data different from the output personality data, and an output personality data unit. A second data generation unit that uses the personality data and the first data to generate the personality data for output and a second data different from the first data, and a second data output unit that outputs the second data. , Equipped with.

The technical terms used in the present specification are used for the purpose of defining only specific examples, and there is no intention of limiting the invention by the technical terms.

As used herein, "and / or" includes all combinations of one or more relatedly listed components.

As used herein, the use of "including, including," "comprising," or "having," and variations thereof, are described features, processes, elements, components, and / or. , Identifying the existence of their equivalents, but may include one or more of steps, actions, elements, components, and / or groups thereof.

In the present specification, "attached", "connected", "combined", and / or their equivalents are used in a broad sense and are "direct and indirect" attachments. Includes both connection and connection. Further, "connected" and "connected" are not limited to physical or mechanical connections or connections, but can include direct or indirect connections or connections.

Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

Terms defined in commonly used dictionaries should be construed to have meanings consistent with their meaning in the context of the relevant technology and disclosure, unless expressly defined herein. , Is not interpreted in an ideal or overly formal sense.

It is understood that a number of techniques and processes are disclosed in the description of the present invention. Each of these has its own interests and can be used with one or more of the other disclosed techniques, or in some cases all.

Therefore, for the sake of clarity, the description of the present invention refrains from unnecessarily repeating all possible combinations of individual steps. However, the specification and claims should be read with the understanding that all such combinations are within the scope of the present invention.

This specification describes an embodiment of a personality analysis method, a personality analysis device, an information processing method using personality data, and an information processing device using personality data according to the present invention.

In the following description, a number of specific examples will be given to provide a complete understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention can be practiced without these specific examples.

Therefore, the following disclosure should be considered as an example of the invention and is not intended to limit the invention to the particular embodiments set forth in the drawings or description below.

[Lean vehicle]
In the present specification, the lean vehicle is a vehicle that turns in an inclined posture. Specifically, a lean vehicle is a vehicle that inclines to the left when turning to the left and to the right when turning to the right in the left-right direction of the vehicle. The lean vehicle may be a single-seater vehicle or a vehicle that can accommodate a plurality of people. The lean vehicle includes not only a two-wheeled vehicle but also all vehicles that turn in an inclined posture, such as a three-wheeled vehicle or a four-wheeled vehicle.

[Personality]
In the present specification, personality means individuality determined by an individual's psychological state, personality, temperament, and the like. Specifically, the personality may include five elements: neuroticism, extroversion, openness to experience, coordination, and integrity. In addition, the personality may include six personality types such as internal closure, synchrony, stickiness, manifestation, hypersensitivity, and coherence. In addition, the personality may include a novelty desire, reward dependence, damage avoidance and persistence temperament and a self-oriented, cooperative and self-transcendent personality. In addition, as driving styles associated with the personality, confidence in driving skills, reluctance to drive, impatient driving tendency, careful driving tendency, preparatory driving for traffic lights, car as a status symbol, unstable spirit It may include driving in a state and anxious tendencies.

In addition to the above, the personality may include any parameter as long as it is a parameter related to an individual's individuality.

[Lean vehicle driving data]
In the present specification, the lean vehicle traveling data is data related to the traveling of the lean vehicle. Specifically, the lean vehicle driving data includes lean vehicle driving operation input data related to driving operation input to the lean vehicle by the driver, lean vehicle behavior data related to the behavior of the lean vehicle, and the traveling position of the lean vehicle. It includes at least one data such as related lean vehicle position data and lean vehicle driving environment data related to the driving environment in which the lean vehicle travels. Further, the lean vehicle traveling data may include processed data obtained by processing lean vehicle driving operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle traveling environment data, and the like. The lean vehicle driving data may include processing data processed by using lean vehicle driving operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle driving environment data, and other data. Good.

[Lean vehicle driving operation input data]
In the present specification, the lean vehicle driving operation input data is data related to the driver's operation input performed when the driver drives and operates the lean vehicle. Specifically, the lean vehicle driving operation input data may include data related to accelerator operation, braking operation, steering, or change of the center of gravity position due to a change in the driver's posture. Further, specifically, the lean vehicle driving operation input data may include data related to the operation of various switches such as a horn switch, a blinker switch, and a lighting switch. Since the lean vehicle driving operation input data is data related to the driving operation input by the driver, the result of the driver's judgment is more reflected. Lean vehicles tend to strongly reflect the driver's personality because there are many types of driver's driving operations and they are intricately related. Further, the lean vehicle driving operation input data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle driving operation input data may include processing data processed using data acquired from a sensor or the like and other data.

[Lean vehicle behavior data]
In the present specification, the lean vehicle behavior data is data related to the behavior of the lean vehicle generated by the operation input of the driver when the lean vehicle is driven and operated by the driver. Specifically, the lean vehicle behavior data includes, for example, the acceleration, speed, and angle of the lean vehicle that change when the driver who is the analysis target drives and operates the lean vehicle. That is, when the driver who is the analysis target operates the accelerator or the brake to accelerate or decelerate the lean vehicle, the lean vehicle behavior data changes the posture including steering of the lean vehicle or changing the position of the center of gravity. It is data showing the behavior of a lean vehicle that occurs in such a case.

Further, the lean vehicle behavior data may include not only data on the acceleration, speed, and angle of the lean vehicle as described above, but also operations generated in the lean vehicle by a switch operation or the like performed by the driver on the lean vehicle. .. That is, the lean vehicle behavior data includes data related to the operation generated in the lean vehicle by operating various switches such as a horn switch, a blinker switch, and a lighting switch. The lean vehicle behavior data strongly reflects the result of input of the driver's driving operation. Therefore, the driver's personality tends to be strongly reflected in the lean vehicle behavior data. Further, the lean vehicle behavior data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle behavior data may include processing data processed using data acquired from a sensor or the like and other data.

[Lean vehicle position data]
In the present specification, the lean vehicle position data is data related to the traveling position of the lean vehicle. For example, the lean vehicle position data can be detected based on GPS and communication base station information of a communication mobile terminal. The lean vehicle position data can be calculated by various positioning techniques, SLAM, and the like. The lean vehicle position data strongly reflects the result of input of the driver's driving operation, which strongly reflects the driver's personality. Therefore, the driver's personality tends to be strongly reflected in the lean vehicle position data. Further, the lean vehicle position data may include processed data obtained by processing data acquired from a sensor or the like. The lean vehicle position data may include processing data processed using data acquired from a sensor or the like and other data.

[Lean vehicle driving environment data]
In the present specification, the lean vehicle driving environment data includes, for example, map data. The map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. In addition, the map data may be associated with environmental data such as weather, temperature or humidity. The lean vehicle driving environment data can be used for personality analysis such as the personality of the person to be analyzed, together with the lean vehicle driving operation input data, the lean vehicle behavior data, and the lean vehicle position data.

The information on the road conditions includes information on roads (regions) in a congested environment such as frequent traffic jams and many vehicles parked on the street. By combining this information with the time zone, the accuracy of the information is further improved. In addition, the information on the road condition includes information on a road that is easily flooded when there is a squall.

The lean vehicle driving environment data is considered to be an example of external stress received by the driver. The lean vehicle driving environment data influences the judgment of the driver. The lean vehicle driving environment data affects the driving operation of the driver. Therefore, by using the lean vehicle driving environment data, the driver's personality is more likely to appear in the driving data of the lean vehicle. Further, since the purpose and frequency of use of the lean vehicle are affected by using the lean vehicle driving environment data, the driving data of the lean vehicle tends to strongly show the personality of the driver.

The lean vehicle driving environment data can be obtained from various means. The means for acquiring the lean vehicle driving environment data is not limited to a certain means. For example, the means for acquiring the lean vehicle traveling environment data is an external environment recognition device mounted on the lean vehicle. More specifically, the means for acquiring the lean vehicle driving environment data includes a camera, a radar, and the like. Further, for example, the means for acquiring the lean vehicle traveling environment data is a communication device. More specifically, the means for acquiring the lean vehicle traveling environment data is a vehicle-to-vehicle communication device and a road-to-vehicle communication device. The lean vehicle driving environment data can also be obtained, for example, via the Internet.

[Public road]
In the present specification, the public road is not a simulation and circuit track, but a public road through which general vehicles can pass. The public roads also include private roads that general vehicles can pass through.

[Contains more B than A]
In the present specification, "containing more B than A" does not have to contain A at all. "Contains more B than A" may include a part of A.

For example, driving includes more data that reflects changes in driving operations for lean vehicles for data conversion by drivers than data that does not reflect changes in driving operations for lean vehicles for data conversion by drivers. It is not necessary to include any data that does not reflect changes in driving operations for lean vehicles for data conversion by a person. For example, driving includes more data that reflects changes in driving operations for lean vehicles for data conversion by drivers than data that does not reflect changes in driving operations for lean vehicles for data conversion by drivers. It may include some data that does not reflect changes in driving operations for lean vehicles for data conversion by the person.

For example, it is analyzed that the data that does not reflect the change in driving operation for the lean vehicle for analysis by the analysis subject contains more data that reflects the change in driving operation for the lean vehicle for analysis by the analysis subject. It does not have to include any data that does not reflect changes in driving maneuvers for the lean vehicle for analysis by the subject. For example, it is analyzed that the data that does not reflect the change in driving operation for the lean vehicle for analysis by the analysis subject contains more data that reflects the change in driving operation for the lean vehicle for analysis by the analysis subject. It may include some data that does not reflect changes in driving operations on the lean vehicle for analysis by the subject.

For example, if a lean vehicle for data conversion contains more data when a lean vehicle for data conversion travels on a public road than a data when a lean vehicle for data conversion travels on a non-public road, the lean vehicle for data conversion travels on a non-public road. It does not have to contain any time data. For example, if a lean vehicle for data conversion contains more data when a lean vehicle for data conversion travels on a public road than a data when a lean vehicle for data conversion travels on a non-public road, the lean vehicle for data conversion travels on a non-public road. It may include some time data.

For example, the fact that the data when the lean vehicle for analysis travels on a public road is included more than the data when the lean vehicle for analysis travels on a non-public road is the data when the lean vehicle for analysis travels on a non-public road. It does not have to contain at all. For example, the fact that the data when the lean vehicle for analysis travels on a public road is included more than the data when the lean vehicle for analysis travels on a non-public road is the data when the lean vehicle for analysis travels on a non-public road. May be partially included.

According to one embodiment of the present invention, it is possible to provide a personality analysis method capable of acquiring personality data while increasing the degree of freedom in designing hardware resources.

FIG. 1 is a diagram showing a schematic configuration of a personality analyzer according to the first embodiment of the present invention. FIG. 2 is a flowchart showing an example of the operation of the personality analyzer. FIG. 3 is a diagram showing a schematic configuration of the personality analysis system according to the second embodiment. FIG. 4 is a flowchart showing an example of the operation of the information processing device.

While analyzing the running data of the lean vehicle, the present inventors noticed that the running data of the lean vehicle and the running data of the non-lean vehicle are significantly different. The lean vehicle is a vehicle that tilts to the right when turning right and tilts to the left when turning left.

Lean vehicles are smaller in size than non-lean vehicles. That is, the lean vehicle is smaller in the front-rear direction and / or the left-right direction of the vehicle body than the non-lean vehicle. In addition, the lean vehicle has a smaller amount of steering rotation operation than the non-lean vehicle. The amount of rotational operation of the steering of a lean vehicle is less than 360 degrees. Further, a lean vehicle is a rider-active vehicle that can be actively operated by the rider, unlike a non-lean vehicle. Therefore, the operation of a lean vehicle is different from the operation of a non-lean vehicle. The running data of a lean vehicle whose operation is different from that of a non-lean vehicle is significantly different from the running data of a non-lean vehicle.

When the present inventors examined the running condition of the lean vehicle in more detail, they noticed that the lean vehicle had a much higher degree of freedom of running by the rider's intention than the non-lean vehicle.

Therefore, when the driver is operating a lean vehicle, the number of judgments and judgment options of the driver tend to be larger than when the driver is operating a non-lean vehicle.

In addition, the driver is more likely to be exposed to external stress when operating a lean vehicle than when operating a non-lean vehicle. Moreover, the external stress exerted on the driver operating the lean vehicle is very diverse.

In this way, when the driver is operating the lean vehicle, the driver has many judgments and choices of judgment, and is easily exposed to stress from the outside. Therefore, the driving data of the lean vehicle is used for driving. The personality of the person is strong and easy to appear. Further, since the lean vehicle has higher mobility and convenience than the non-lean vehicle, the lean vehicle has various purposes of use and tends to be used more frequently. Therefore, the driver's personality tends to appear strongly in the driving data of the lean vehicle. That is, the present inventors have noticed that the driving data of the lean vehicle operated by the driver is less arbitrariness of the driver and more reflects the essential personality of the driver.

Therefore, the present inventors have come up with a method for analyzing an essential personality with less arbitrariness using the driving data of a lean vehicle. By using the driving data of a lean vehicle for personality analysis, it is possible to reduce the types of data processed by the system and reduce the hardware load of the system for analyzing personality. In addition, since the hardware resources required by the system can be reduced, the degree of freedom in designing the hardware resources of the system for analyzing personality can be increased. We have created a personality analysis method that can acquire personality data while increasing the degree of freedom in designing hardware resources.

Hereinafter, each embodiment will be described with reference to the drawings. The dimensions of the constituent members in each drawing do not faithfully represent the actual dimensions of the constituent members and the dimensional ratio of each constituent member.

<Embodiment 1>
(Personality analyzer)
FIG. 1 shows a schematic configuration of the personality analyzer 1 according to the embodiment of the present invention. The personality analyzer 1 is an apparatus that analyzes the personality of the person to be analyzed. The personality analyzer 1 of the present embodiment obtains lean vehicle running data (lean vehicle running data for analysis) of the lean vehicle X (lean vehicle for analysis) obtained when the person to be analyzed drives and operates the lean vehicle X. It is used to analyze the personality of the person to be analyzed and output the analysis result.

The analysis of personality in the present embodiment means the analysis of individuality determined by the psychological state, personality, temperament, etc. of the person to be analyzed. This personality is converted into conversion personality data obtained by converting the lean vehicle running data of the lean vehicle X obtained when the analysis target person drives and operates the lean vehicle X as a driver by the personality data conversion unit 30 described later. included. That is, the converted personality data includes data related to the personality of the person to be analyzed.

The lean vehicle running data in this embodiment is data related to the running of the lean vehicle. The lean vehicle driving data means data related to the driving of the lean vehicle obtained when the driver operates the lean vehicle so that the driver's personality appears.

Specifically, the lean vehicle driving data includes lean vehicle driving operation input data related to driving operation input to the lean vehicle by the driver, lean vehicle behavior data related to the behavior of the lean vehicle, and the traveling position of the lean vehicle. Includes relevant lean vehicle position data, lean vehicle driving environment data related to the driving environment in which the lean vehicle travels, and the like. The lean vehicle traveling data may include data other than the lean vehicle driving operation input data, the lean vehicle behavior data, the lean vehicle position data, and the lean vehicle traveling environment data. Further, the lean vehicle driving data may include only one or a plurality of data among the lean vehicle driving operation input data, the lean vehicle behavior data, the lean vehicle position data, and the lean vehicle driving environment data. ..

For example, in the case of a lean vehicle X in which the lean vehicle is a lean vehicle for analysis, the lean vehicle driving data is lean vehicle driving data for analysis, and the lean vehicle driving operation input data is a lean vehicle driving operation input for analysis. The lean vehicle behavior data is data, the lean vehicle behavior data is lean vehicle behavior data for analysis, the lean vehicle position data is lean vehicle position data for analysis, and the lean vehicle driving environment data is lean vehicle running for analysis. Environmental data.

For example, when the lean vehicle is a lean vehicle for data conversion, the lean vehicle running data is lean vehicle running data for data conversion, and the lean vehicle driving operation input data is lean vehicle driving for data conversion. The lean vehicle behavior data is operation input data, the lean vehicle behavior data is lean vehicle behavior data for data conversion, the lean vehicle position data is lean vehicle position data for data conversion, and the lean vehicle driving environment data is data conversion. Lean vehicle driving environment data for.

The lean vehicle driving data may include processed data obtained by processing lean vehicle driving operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle driving environment data, and the like. Further, the vehicle traveling data includes processing data processed by using lean vehicle driving operation input data, lean vehicle behavior data, lean vehicle position data, lean vehicle traveling environment data and other data and other data. May be good.

The lean vehicle driving operation input data is data related to the driver's operation input performed when the driver drives and operates the lean vehicle. Specifically, the lean vehicle driving operation input data may include data related to accelerator operation, braking operation, steering, or change of the center of gravity position due to a change in the driver's posture. Specifically, the lean vehicle driving operation input data may include operations of various switches such as a horn switch, a blinker switch, and a lighting switch. Since the lean vehicle driving operation input data is data related to the driving operation input by the driver, the result of the driver's judgment is more reflected. Lean vehicles tend to strongly reflect the driver's personality because there are many types of driver's driving operations and they are intricately related. Further, the lean vehicle driving operation input data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle driving operation input data may include processing data processed using data acquired from a sensor or the like and other data.

The lean vehicle behavior data is data related to the behavior of the lean vehicle generated by the driver's operation input when the lean vehicle is driven and operated by the driver. Specifically, the lean vehicle behavior data includes, for example, the acceleration, speed, and angle of the lean vehicle that change when the driver operates the vehicle. That is, the lean vehicle behavior data is generated when the driver accelerates or decelerates the lean vehicle by operating the accelerator or the brake, or changes the posture including steering of the lean vehicle or changing the position of the center of gravity. This is data showing the behavior of a lean vehicle.

As described above, the lean vehicle behavior data may include not only data on the acceleration, speed, and angle of the lean vehicle, but also movements that occur in the lean vehicle due to a switch operation or the like performed by the driver on the lean vehicle. That is, the lean vehicle behavior data includes data related to the operation generated in the lean vehicle by operating various switches such as a horn switch, a blinker switch, and a lighting switch. The lean vehicle behavior data strongly reflects the result of input of the driver's driving operation. Therefore, the driver's personality tends to be strongly reflected in the lean vehicle behavior data. Further, the lean vehicle behavior data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle behavior data may include processing data processed using data acquired from a sensor or the like and other data.

The lean vehicle position data is data related to the running position of the lean vehicle. For example, the lean vehicle position data can be detected based on GPS, information on a communication base station of a communication mobile terminal, or the like. The lean vehicle position data can be calculated by various positioning techniques, SLAM, and the like. The lean vehicle position data strongly reflects the result of input of the driver's driving operation, which strongly reflects the driver's personality. Therefore, the driver's personality tends to be strongly reflected in the lean vehicle position data. Further, the lean vehicle position data may include processed data obtained by processing data acquired from a sensor or the like. The lean vehicle position data may include processing data processed using data acquired from a sensor or the like and other data.

The lean vehicle driving environment data includes, for example, map data. This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. In addition, the map data may be associated with environmental data such as weather, temperature or humidity. The lean vehicle driving environment data can be used for personality analysis such as the personality of the person to be analyzed, together with the lean vehicle driving operation input data, the lean vehicle behavior data, and the lean vehicle position data.

The personality analyzer 1 includes a personality conversion data acquisition unit 10, a lean vehicle driving data acquisition unit 20 for analysis, a personality data conversion unit 30, an output personality data generation unit 40, a data output unit 50, and a data storage unit. 60 and. In the present embodiment, the personality analyzer 1 is, for example, a mobile terminal owned by the person to be analyzed. The personality analysis device 1 may be an arithmetic processing unit that acquires data via communication and performs arithmetic processing.

The lean vehicle driving data acquisition unit 20 for analysis acquires lean vehicle driving data (lean vehicle driving data for analysis) when the driver who is the analysis target drives the lean vehicle X.

When the analysis target person drives the lean vehicle X, the analysis lean vehicle driving data acquisition unit 20 includes data included in the lean vehicle driving data of the lean vehicle X, that is, lean vehicle driving operation input data for analysis, and analysis. Lean vehicle behavior data for analysis, lean vehicle position data for analysis, lean vehicle driving environment data for analysis, etc. are acquired.

The analysis lean vehicle driving data acquisition unit 20 may acquire the analysis lean vehicle driving operation input data by, for example, acquiring the driving operation of the analysis target person with respect to the lean vehicle X as an operation signal. Specifically, the analysis lean vehicle driving data acquisition unit 20 changes the position of the center of gravity due to data related to the driver's operation input in the lean vehicle X, that is, accelerator operation, brake operation, steering, or change in the driver's posture. Data related to the above, data related to the operation of various switches such as a horn switch, a blinker switch, and a lighting switch may be acquired. These data are transmitted from the lean vehicle X.

The lean vehicle driving data acquisition unit 20 for analysis obtains data including the acceleration, speed, and angle of the lean vehicle X, which changes when the driver who is the analysis target drives and operates the lean vehicle X, for analysis. It may be acquired as vehicle behavior data. The analysis lean vehicle travel data acquisition unit 20 acquires the analysis lean vehicle behavior data by, for example, a gyro sensor. The lean vehicle behavior data for analysis includes a posture including steering of the lean vehicle X or a change in the position of the center of gravity when the driver who is the analysis target operates the accelerator or the brake to accelerate or decelerate the lean vehicle X. This is data showing the behavior of the lean vehicle X that occurs when a change is made.

Further, even if the analysis lean vehicle driving data acquisition unit 20 acquires the operation generated in the lean vehicle X by the switch operation or the like performed on the lean vehicle X by the driver who is the analysis target, as the lean vehicle behavior data. Good. That is, the analysis lean vehicle travel data acquisition unit 20 acquires data related to the operation generated in the lean vehicle X by operating various switches such as the horn switch, the blinker switch, and the lighting switch as the analysis lean vehicle behavior data. You may. These data are transmitted from the lean vehicle X to the personality analyzer 1.

The analysis lean vehicle travel data acquisition unit 20 may acquire analysis lean vehicle position data related to the travel position of the lean vehicle X based on, for example, GPS and communication base station information of a communication mobile terminal. .. The lean vehicle position data for the analysis can be calculated by various positioning techniques, SLAM, and the like.

The analysis lean vehicle driving data acquisition unit 20 may acquire the analysis lean vehicle driving environment data from, for example, map data. This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel. In addition, the map data may be associated with environmental data such as weather, temperature or humidity. The map data may include information in which road information and information on the road traffic environment (information incidental to the road such as a signal) are associated with rule information related to road travel.

The analysis lean vehicle driving data acquisition unit 20 may acquire the analysis lean vehicle driving environment data by, for example, an external environment recognition device mounted on the lean vehicle X. More specifically, the analysis lean vehicle travel data acquisition unit 20 may acquire the analysis lean vehicle travel environment data from a camera, radar, or the like. Further, the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data by, for example, a communication device. More specifically, the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data by the vehicle-to-vehicle communication device and the road-to-vehicle communication device. The analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data via the Internet, for example. As described above, the lean vehicle traveling environment data for the analysis can be obtained from various means. The means for acquiring the lean vehicle driving environment data for analysis is not limited to a certain means.

The personality conversion data acquisition unit 10 acquires the personality conversion data that converts the lean vehicle driving data of the above-mentioned analysis target person into the personality data.

The personality conversion data is data in which lean vehicle driving data obtained when a plurality of drivers each drive a lean vehicle and personality data of those drivers are associated with each other. That is, the personality conversion data is data in which lean vehicle travel data and personality data are associated with each other in order to obtain personality data suitable for the lean vehicle travel data.

The personality conversion data is obtained when, for example, a plurality of drivers drive and operate a lean vehicle (lean vehicle for data conversion) by using a concept based on a characteristic theory or a typology used in personality analysis. Generated based on lean vehicle driving data for data conversion. In the present embodiment, the lean vehicle travel data for data conversion is the same data as the lean vehicle travel data for analysis described above, except that the data is used for generating the personality conversion data. The lean vehicle travel data for data conversion may include data of a different type from the lean vehicle travel data for analysis described above.

In the present embodiment, the personality conversion data is generated by using the Big Five theory, which is a characteristic theory of personality. In this Big Five theory, various personalities of human beings are expressed by a combination of five elements. The Big Five theory is a theory that has universality that transcends cultural and ethnic differences.

Specifically, the personality conversion data is a combination of lean vehicle driving data for the five elements of the Big Five theory: neurotic tendency, extroversion, openness to experience, cooperation, and integrity. It is data.

The neurotic tendency represents sensitivity to environmental stimuli and stressors, anxiety and tension. The neurotic tendency is related to, for example, the magnitude of the variation in travel of the lean vehicle X depending on the travel environment. The driver who does not see a big difference in the running of the lean vehicle X due to the difference in the running environment of the lean vehicle X has a weak tendency for neurosis, and the driving of the lean vehicle X shows a big difference due to the difference in the running environment of the lean vehicle X. Drivers are more prone to neurosis.

For example, if there is no significant change in the vehicle body behavior of the lean vehicle X between a driving position where congestion often occurs and a driving position where congestion does not occur much, the driver is not significantly affected by the environment, that is, the driver's The tendency to neurosis is judged to be weak. On the other hand, when there is a large change in the vehicle body behavior of the lean vehicle X, it is determined that the driver is affected by the environment, that is, the driver has a strong tendency toward neurosis.

That is, the driving environment of the lean vehicle X can be specified, and the driver's neurotic tendency can be determined based on the difference or variation (for example, standard deviation) of the parameters of the vehicle body behavior under different driving environments.

The driving environment is, for example, "urban area and suburbs (region)", "general road and highway (road type)", "day and night (time)", "sunny and rain (weather)", "dry and wet". (Road surface) ”etc. The traveling environment is specified by using traveling position data, time data, meteorological data, road surface detection data, and the like.

The neuropathy tendency can be grasped by using, for example, the lean vehicle driving operation input data of the lean vehicle X, the lean vehicle driving environment data, the lean vehicle position data, and the lean vehicle behavior data among the lean vehicle driving data. it can.

The extroversion represents diplomacy, activity, and aggressiveness. The extroversion is related to, for example, the mileage of the lean vehicle X within a certain period of time. For example, it is determined that the longer the mileage of the lean vehicle X, the higher the extroversion of the driver, and the shorter the mileage of the lean vehicle X, the lower the extroversion. Therefore, the extroversion can be grasped by using, for example, the lean vehicle position data of the lean vehicle X in the lean vehicle travel data.

Openness to experience represents the strength of intellectual curiosity, imagination, and affinity for new things. Openness to experience is related, for example, to the number of new points visited by lean vehicle X within a certain period of time. For example, it is judged that the greater the number of new points visited by the lean vehicle X within a certain period of time, the higher the openness to the driver's experience, and the smaller the number of new points, the greater the openness to the driver's experience. Judged as low. It should be noted that the points to be visited may be distinguished for each type, and it may be judged that the greater the number of times the lean vehicle X visits a new type of point within a certain period of time, the higher the openness to the driver's experience. Further, even if the number of new points visited by the lean vehicle X within a certain period is the same, it may be judged that the more types of points visited, the higher the openness to the driver's experience.

The openness to the experience can be grasped by using, for example, the lean vehicle driving environment data including the lean vehicle position data and the map data of the lean vehicle X among the lean vehicle traveling data.

The cooperativeness represents altruism, empathy, kindness, and the like. The cooperation is related to, for example, the degree of cooperation with the surroundings in a dense state. Therefore, the cooperation can be grasped by using, for example, the lean vehicle position data in the lean vehicle travel data.

In particular, the coordination has a stronger relationship with the degree of divergence from the average behavior in the dense group. Therefore, the cooperativeness can be grasped more accurately by using the traveling position data of other lean vehicles in the densely packed group.

When the lean vehicle X is in a dense state together with other lean vehicles, it is related not only to the lean vehicle position data related to the traveling position of the lean vehicle X but also to the traveling position of the other lean vehicles in the dense state. The lean vehicle position data may also be grasped to calculate the degree of deviation of the traveling position of the lean vehicle X in the group of lean vehicles in a dense state. When the degree of deviation of the traveling position of the lean vehicle X is calculated in this way, for example, it is determined that the greater the degree of deviation of the traveling position, the lower the driver's cooperation, and the smaller the degree of deviation, the more the driver's cooperation It is judged that the sex is high.

The above-mentioned integrity represents self-control, willingness to achieve, seriousness, and a strong sense of responsibility. The integrity is related to, for example, the degree of illegal driving or illegal activity, and the small variation in the traveling of the lean vehicle X. The degree of illegal traveling is determined based on the regulation information according to the traveling position recorded in the map data and the behavior of the lean vehicle X. The illegal traveling includes, for example, traveling at 60 km / h on a road whose speed is regulated at 40 km / h, or not suspending at a point where the vehicle is obliged to suspend.

It is judged that the more frequently the driver does not comply with the above-mentioned driving regulations, the lower the driver's integrity is, and the less frequently the driver does not comply with the driving regulations, the higher the driver's integrity is determined. Will be done.

Further, in the case of the variation in driving, the driving environment of the lean vehicle X is classified and specified, and based on the difference or variation (for example, standard deviation) of the parameters of the vehicle body behavior of the lean vehicle X in the driving environment. , The integrity of the driver is judged. Riders with high integrity have high self-control and are serious, so it is considered that they will comply with the law and will not take any sudden actions.

The integrity can be grasped by using, for example, the lean vehicle driving environment data including the lean vehicle position data and the map data of the lean vehicle X and the lean vehicle behavior data among the lean vehicle traveling data.

The personality conversion data is a 7-dimensional model of Cloninger's temperament and personality (Kijima et al., Quarterly Psychiatric Diagnosis (Nippon Critics), Vol. 7, No. 3, Reprint, p379-399), driver behavior and personality data. (Taketoshi Takuma, IATS review Vol.2 No.3, September 1976, p183-190), evaluation index of individual driver characteristics (Ishibashi et al., Mazda Technical Report, No.22 (2004), p155-160), etc. And may be generated.

For example, in the 7-dimensional model of Croninger's temperament and personality, the temperament is expressed by novelty desire, reward dependence, damage avoidance and persistence, and the personality is expressed by self-orientation, cooperation and self-transcendence. In the driver behavior and personality data, personality is classified into six types: internal closure, synchronism, stickiness, manifestation, hypersensitivity, and overconfidence. In addition, in the evaluation index of driver's personal characteristics, driving style, confidence in driving skill, negativeness to driving, impatient driving tendency, careful driving tendency, preparatory driving for traffic lights, car as status symbol, non-existence It is expressed by driving in a stable mental state and anxious sexual tendency.

The personality conversion data may be data that has been generated in advance and stored in the data storage unit 60, or may be data that is generated by the personality conversion data acquisition unit 10. The personality conversion data acquisition unit 10 may update the personality conversion data by using the acquired lean vehicle traveling data and personality.

The personality data conversion unit 30 uses the personality conversion data described above to convert the lean vehicle travel data for analysis acquired by the lean vehicle travel data acquisition unit 20 for analysis into conversion personality data. At this time, the personality data conversion unit 30 ranks the driver who is the analysis target for the above-mentioned five elements of neurotic tendency, extroversion, openness to experience, cooperation, and integrity. I do. This leveling may be expressed as a continuous value for each of the above-mentioned elements, or may be expressed in a plurality of stages divided by a threshold value. Further, the personality data conversion unit 30 may classify into a plurality of types by using the result of leveling by each of the above-mentioned elements, and the classification result may be used as the conversion personality data.

The output personality data generation unit 40 generates output personality data using the converted personality data converted by the personality data conversion unit 30. The personality data for this output is data output from the personality analyzer 1. The personality data for output may be the same data as the converted personality data, or is data converted into data required as output data of the personality analyzer 1 using the converted personality data. May be good.

Further, the output personality data generation unit 40 may process the converted personality data to generate output personality data. For example, the output personality data generation unit 40 stores the conversion personality data in the data storage unit 60, and outputs the conversion personality data using the conversion personality data extracted from the conversion personality data stored in the data storage unit 60. You may generate personality data for. Specifically, for example, the output personality data generation unit 40 may generate the output personality data from the conversion personality data stored in the data storage unit 60 within a certain period of time.

The data output unit 50 outputs the output personality data generated by the output personality data generation unit 40 to the outside of the personality analyzer 1.

With the above configuration, the personality analyzer 1 analyzes the personality of the analysis target person using the lean vehicle running data of the lean vehicle X driven and operated by the analysis target person, and outputs the analysis result as personality data for output. can do.

(Personality analysis method)
Next, the personality analysis method performed by the personality analyzer 1 having the above-described configuration will be described with reference to FIG. FIG. 2 is a flow showing an example of the operation of the personality analysis device 1, that is, an example of the personality analysis method.

First, the analysis lean vehicle travel data acquisition unit 20 acquires the lean vehicle travel data for analysis of the lean vehicle X (step SA1). The lean vehicle driving data for analysis includes, for example, lean vehicle driving operation input data for analysis, lean vehicle behavior data for analysis, lean vehicle position data for analysis, lean vehicle driving environment data for analysis, and the like. Is done.

The lean vehicle driving data for analysis includes data other than lean vehicle driving operation input data for analysis, lean vehicle behavior data for analysis, lean vehicle position data for analysis, and lean vehicle driving environment data for analysis. It may be included. The lean vehicle driving data for the analysis includes the lean vehicle driving operation input data for the analysis, the lean vehicle behavior data for the analysis, the lean vehicle position data for the analysis, and the lean vehicle driving environment data for the analysis. Of these, only one or more data may be included.

Next, the personality data conversion unit 30 converts the acquired lean vehicle running data for analysis of the lean vehicle X into conversion personality data by the personality conversion data (step SA2). This personality conversion data is data in which the lean vehicle driving data obtained when a plurality of drivers each drive and operate the lean vehicle and the personality data are associated with each other. In the present embodiment, the personality conversion data is data generated based on lean vehicle driving data for data conversion obtained when a plurality of drivers each drive a lean vehicle by using the big five theory. is there.

The output personality data generation unit 40 generates output personality data using the converted conversion personality data (step SA3).

The data output unit 50 outputs the generated personality data (step SA4). After that, this flow ends (end).

With the above configuration, the analysis target person who is the driver uses lean vehicle driving data that is less arbitrariness of the driver and more reflects the essential personality of the driver, instead of the conventional question-and-answer format. You can get personality data. By using lean vehicle driving data in this way, the amount of data processed by the personality analysis system is compared with the conventional personality analysis method that requires asking a large number of questions to the analysis target person. Can be reduced.

That is, by using the running data of the lean vehicle for the analysis of personality, the types of data processed by the system can be reduced, and the load on the hardware of the personality analyzer 1 can be reduced. Further, since the hardware resources required by the personality analyzer 1 can be reduced, the degree of freedom in designing the hardware resources of the personality analyzer 1 can be increased.

Therefore, it is possible to acquire personality data while increasing the degree of freedom in designing hardware resources.

This embodiment is an example of a personality analysis method for analyzing the personality of an analysis target person. The personality analysis method of the present embodiment includes the following steps.

In the personality analysis method of the present embodiment, personality conversion data that associates personality data indicating personality with lean vehicle driving data, which is lean vehicle driving data, is acquired. This personality conversion data is generated based on the lean vehicle driving data for data conversion related to the driving data of the lean vehicle obtained when a plurality of drivers drive and operate the lean vehicle.

The lean vehicle driving data for data conversion means lean vehicle driving data by a plurality of drivers. Further, the lean vehicle is a vehicle that tilts to the right when turning right and tilts to the left when turning left. The lean vehicle for data conversion means a lean vehicle operated by a plurality of drivers who are the targets of the lean vehicle driving data for data conversion.

For example, the lean vehicle running data for data conversion may be acquired by various sensors provided in the lean vehicle for data conversion. Further, the lean vehicle traveling data for data conversion may be acquired by various sensors provided so as to be easily attached to and detached from the lean vehicle for data conversion. The lean vehicle traveling data for data conversion may be acquired by various sensors temporarily provided in the lean vehicle for data conversion for data collection.

In the personality analysis method, the lean vehicle running data for analysis related to the running data of the lean vehicle X obtained when the analysis target person drives and operates the lean vehicle X is acquired.

The lean vehicle running data for analysis means the lean vehicle running data of the lean vehicle X driven and operated by the analysis target person. The lean vehicle for analysis means a lean vehicle X driven and operated by the analysis target person, which is a target for acquiring lean vehicle travel data for analysis.

The analysis target person may be included in the plurality of drivers. The person to be analyzed may not be included in the plurality of drivers. The lean vehicle for analysis may be included in the lean vehicle for data conversion. The lean vehicle for analysis may not be included in the lean vehicle for data conversion. The lean vehicle travel data for analysis may be included in the lean vehicle travel data for data conversion. The lean vehicle travel data for analysis may not be included in the lean vehicle travel data for data conversion.

For example, the lean vehicle travel data for analysis may be acquired by various sensors provided in the lean vehicle for analysis. Further, the lean vehicle travel data for analysis may be acquired by various sensors provided so as to be easily detachable from the lean vehicle for analysis. The lean vehicle travel data for analysis may be acquired by various sensors temporarily provided in the lean vehicle for analysis for data collection.

Note that the various sensors for collecting the lean vehicle running data for the analysis may have lower detection accuracy than the various sensors for collecting the lean vehicle running data for the data conversion.

The various sensors for collecting the lean vehicle running data for the analysis may be the same as the various sensors for collecting the lean vehicle running data for the data conversion.

The type of data included in the lean vehicle travel data for analysis may be less than the type of data included in the lean vehicle travel data for data conversion. The type of data included in the lean vehicle travel data for analysis may be the same as the type of data included in the lean vehicle travel data for data conversion.

The personality analyzer 1 converts the acquired lean vehicle driving data for analysis into conversion personality data related to the personality of the person to be analyzed by using the acquired personality conversion data.

The personality analyzer 1 uses the converted converted personality data to generate output personality data for output.

The personality analyzer 1 outputs the generated personality data for output.

From another point of view, the personality analysis method preferably includes the following configurations. The lean vehicle driving data for data conversion reflects the change in driving operation for the lean vehicle for data conversion by the driver rather than the data that does not reflect the change in driving operation for the lean vehicle for data conversion by the driver. Contains a lot of data. The lean vehicle driving data for analysis reflects the change in driving operation for the lean vehicle for analysis by the analysis subject from the data that does not reflect the change in driving operation for the lean vehicle for money analysis by the analysis subject. Contains a lot of data.

The driver of the lean vehicle recognizes the situation, makes a judgment, and performs the driving operation. At this time, there are cases where the driver changes the driving operation before and after the judgment and cases where the driving operation is not changed. In a lean vehicle, there are many variations in driving operation and there are many options for the driver's judgment, so there are many variations in the scene in which the driver changes the driving operation. Therefore, focusing on the scene in which the driver of this lean vehicle changes the driving operation, the lean vehicle driving data containing a lot of data reflecting the change in the driving operation of the lean vehicle by the driver is less arbitrariness and essential. Driver's personality is more likely to appear.

The method of separating the lean vehicle driving data into data that does not reflect the change in the driving operation of the lean vehicle by the driver and data that reflects the change in the driving operation of the lean vehicle by the driver is as follows. There is a method.

For example, it is possible to directly see and separate the change in the driving operation of the lean vehicle by the driver from the lean vehicle driving data.

For example, from the lean vehicle driving data, it is possible to directly see and separate the behavior of the lean vehicle in which the result due to the change in the driving operation of the lean vehicle by the driver appears.

For example, from the lean vehicle driving data, the position of the lean vehicle in which the result due to the change in the driving operation of the lean vehicle by the driver appears can be seen and separated.

For example, from the lean vehicle driving data, the position of the lean vehicle indicating that the driver is traveling in a place where the driving operation for the lean vehicle is frequently changed can be seen and separated.

Specifically, it can be separated by using the position data of the lean vehicle and the driving environment data (for example, map data) of the lean vehicle. More specifically, the driving data in the suburbs and the driving data in the city may be separated. The driving data in the suburbs may be data that does not reflect the change in driving operation for the lean vehicle by the driver, and the driving data in the city may be data that reflects the change in driving operation for the lean vehicle by the driver.

From another point of view, the personality analysis method preferably includes the following configurations. The lean vehicle driving data for data conversion is related to the lean vehicle driving operation input data for data conversion related to the driving operation input to the lean vehicle for data conversion by the driver, and the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion. The lean vehicle driving data for analysis is the lean vehicle driving operation input data for analysis related to the driving operation input to the lean vehicle for analysis by the analysis target person, and the analysis related to the behavior of the lean vehicle for analysis. The lean vehicle behavior data for analysis and the lean vehicle position data for analysis related to the position of the lean vehicle for analysis are included.

Lean vehicle driving operation input data is data related to driving operation input by the driver, so it more reflects the result of the driver's judgment. Lean vehicles tend to strongly reflect the driver's personality because there are many types of driver's driving operations and they are intricately related.

The lean vehicle behavior data strongly reflects the result of the driver's driving operation input, which strongly reflects the driver's personality. Therefore, the lean vehicle behavior data also tends to strongly reflect the personality of the driver.

The lean vehicle position data strongly reflects the result of the driver's driving operation input, which strongly reflects the driver's personality. Therefore, the lean vehicle position data tends to strongly reflect the personality of the driver.

From another point of view, the personality analysis method preferably includes the following configurations. The lean vehicle traveling data for data conversion further includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels. The lean vehicle travel data for analysis further includes lean vehicle travel environment data for analysis related to the travel environment in which the lean vehicle for analysis travels.

Driving environment data is considered to be an example of external stress that the driver receives. The driving environment data influences the judgment of the driver. The driving environment data affects the driving operation of the driver. Therefore, by using the driving environment data, the personality of the driver is more likely to appear in the driving data of the lean vehicle. In addition, since the purpose and frequency of use of the lean vehicle are affected by using the driving environment data, the personality of the driver tends to appear strongly in the driving data of the lean vehicle.

From another point of view, the personality analysis method preferably includes the following configurations. The lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road. The lean vehicle traveling data for analysis includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for analysis travels on a road other than a public road.

When a driver traveling on a public road is operating a lean vehicle, the driver makes more decisions, has more choices of decisions, and is more likely to be exposed to external stress. Therefore, the driver's personality tends to appear more strongly in the driving data of the lean vehicle. In addition, since lean vehicles have higher maneuverability and convenience than non-lean vehicles, lean vehicles tend to be used for various purposes and frequently used. Therefore, the driver's personality is more likely to appear in the driving data of a lean vehicle traveling on a public road. That is, the driving data of a lean vehicle traveling on a public road has less arbitrariness of the driver and more reflects the essential personality of the driver. For example, whether or not the data is traveling on a public road may be determined from the lean vehicle position data and the lean vehicle traveling environment data.

From another point of view, the personality analysis method preferably includes the following configurations. The lean vehicle traveling data for data conversion includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for data conversion, but a plurality of data are left. The lean vehicle traveling data for analysis includes data in a state where a plurality of judgment options of the analysis target person are limited by vehicles around the lean vehicle for analysis, but a plurality of data are left.

For example, the driver's judgment options are limited by the vehicles around the lean vehicle, but a plurality of remaining states may be determined from the lean vehicle position data and the lean vehicle driving environment data. More specifically, the state may be estimated based on the date, time, and place where the lean vehicle is traveling. Lean vehicle driving data when traveling in an urban area includes data in a state where a plurality of driver's judgment options are restricted by vehicles around the lean vehicle, but a plurality of them are left. In addition, data on the actual surrounding conditions of the lean vehicle may be acquired to estimate the state. A combination of methods for estimating a plurality of states may be used.

The driver's judgment options are limited by the vehicles around the lean vehicle, but a plurality of remaining options are defined as the driver of the lean vehicle driving in a group of a plurality of vehicles including the lean vehicle. It means the running state of the lean vehicle when a plurality of options are left although the options are limited when the operation is determined.

From another point of view, the personality analysis method preferably includes the following configurations. The lean vehicle traveling data for data conversion includes data in a state where at least one of a passenger and an object is mounted. The lean vehicle driving data for analysis includes data in a state where at least one of a passenger and an object is mounted.

For example, it may be determined from various sensors whether or not at least one of a passenger and an object is mounted. Further, the determination may be made based on the declaration by the driver.

From another point of view, the personality analysis method preferably includes the following configurations. In the personality analysis method, the converted conversion personality data is stored. In the personality analysis method, the stored personality data for output is generated by using the plurality of stored conversion personality data. Note that the memory includes not only the memory for storage but also the temporary memory of the result. For example, the conversion personality data stored in the storage and the conversion personality data stored in the temporary memory may be used. These may be used to update the conversion personality data stored in the storage. These may be used to generate new conversion personality data. Statistical processing may be performed using these. These may be used to update the conversion personality data stored in the storage.

By using a plurality of converted personality data as described above, for example, it can be statistically processed, and the personality of the analysis target person who is the driver of the lean vehicle can be analyzed more accurately. More specifically, the old conversion personality data and the new conversion personality data can be used to more accurately analyze the personality of the analysis target person who is the driver of the lean vehicle X.

This embodiment is an example of a personality analyzer that analyzes the personality of the person to be analyzed. The personality analyzer of the present embodiment includes the following configurations.

The personality analyzer according to the present embodiment is a personality analyzer that analyzes the personality of the person to be analyzed. This personality analyzer is a lean vehicle for data conversion obtained when a plurality of drivers operate a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left. Personality conversion that acquires personality conversion data generated by associating personality data indicating personality with lean vehicle driving data that is lean vehicle driving data based on lean vehicle driving data for data conversion related to the driving data of The data acquisition unit and the running data of the lean vehicle for analysis obtained when the analysis target person operates the lean vehicle for analysis that tilts to the right when turning right and tilts to the left when turning left. Using the lean vehicle driving data acquisition unit for analysis that acquires the lean vehicle driving data for analysis and the acquired personality conversion data, the acquired lean vehicle driving data for analysis is used as the personality of the person to be analyzed. A personality data conversion unit that converts to related conversion personality data, an output personality data generation unit that generates personality data for output to be output using the converted conversion personality data, and the generated output. It is provided with a data output unit that outputs personality data for the user.

From another point of view, the personality analyzer preferably includes the following configurations. The lean vehicle driving data for data conversion is a change in driving operation for the lean vehicle for data conversion by the driver from data that does not reflect the change in driving operation for the lean vehicle for data conversion by the driver. Contains a lot of data that reflects. The lean vehicle driving data for analysis shows that the change in driving operation for the lean vehicle for analysis by the analysis target person is different from the data that does not reflect the change in driving operation for the lean vehicle for analysis by the analysis target person. Contains a lot of reflected data.

From another point of view, the personality analyzer preferably includes the following configurations. The lean vehicle driving data for data conversion is the lean vehicle driving operation input data for data conversion related to the driving operation input to the lean vehicle for data conversion by the driver, and the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion related to and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion. The lean vehicle driving data for analysis is related to the lean vehicle driving operation input data for analysis related to the driving operation input to the lean vehicle for analysis by the analysis subject, and the behavior of the lean vehicle for analysis. It includes at least one of the lean vehicle behavior data for analysis and the lean vehicle position data for analysis related to the position of the lean vehicle for analysis.

From another point of view, the personality analyzer preferably includes the following configurations. The lean vehicle traveling data for data conversion further includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels. The lean vehicle travel data for analysis further includes lean vehicle travel environment data for analysis related to the travel environment in which the lean vehicle for analysis travels.

From another point of view, the personality analyzer preferably includes the following configurations. The lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road. The lean vehicle traveling data for analysis includes more data when the lean vehicle for analysis travels on a public road than data when the lean vehicle for analysis travels on a road other than a public road.

From another point of view, the personality analyzer preferably includes the following configurations. The lean vehicle traveling data for data conversion includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for data conversion, but a plurality of data are left. The lean vehicle traveling data for analysis includes data in a state where a plurality of judgment options of the analysis target person are limited by vehicles around the lean vehicle for analysis, but a plurality of data are left.

From another point of view, the personality analyzer preferably includes the following configurations. The lean vehicle traveling data for data conversion includes data in a state where at least one of a passenger and an object is mounted. The lean vehicle driving data for analysis includes data in a state where at least one of a passenger and an object is mounted.

<Embodiment 2>
FIG. 3 shows an example of the personality analysis system 100 including the personality analysis device 1 of the first embodiment. Hereinafter, the same components as those of the first embodiment are designated by the same reference numerals and the description thereof will be omitted, and only the configurations different from the first embodiment will be described.

The personality analysis system 100 includes a personality analysis device 1 and a personality conversion data generation device 101 that generates personality conversion data.

The personality conversion data generation device 101 is, for example, an information processing arithmetic unit capable of communicating with the personality analysis device 1 and having a processor. When the personality analysis device 1 is an information processing calculation device having a processor, the personality conversion data generation device 101 may be the same information processing calculation device as the personality analysis device 1.

The personality conversion data generation device 101 acquires lean vehicle traveling data and personality data, and generates personality conversion data in which the lean vehicle traveling data and the personality data are associated with each other.

Specifically, the personality conversion data generation device 101 has a data storage unit 111 and a personality conversion data generation unit 112. Although not particularly shown, the personality conversion data generation device 101 has an acquisition unit for acquiring lean vehicle traveling data and personality data. Further, although not particularly shown, the personality conversion data generation device 101 has an output unit that outputs the generated personality conversion data.

The data storage unit 111 stores lean vehicle driving data, personality data, and personality conversion data. Specifically, the data storage unit 111 stores lean vehicle running data for data conversion obtained when a plurality of drivers drive and operate the lean vehicle Y (lean vehicle for data conversion). Further, the data storage unit 111 stores the personality conversion data generated by the personality conversion data generation unit 112, which will be described later.

Note that personality data may be stored by input in the data storage unit 111, or personality data may be stored in advance.

The lean vehicle driving data for data conversion includes, for example, lean vehicle driving operation input data for data conversion, lean vehicle behavior data for data conversion, lean vehicle position data for data conversion, and lean vehicle driving environment for data conversion. Includes data etc.

The personality conversion data generation unit 112 generates personality conversion data in which the lean vehicle travel data and the personality data are associated with each other, based on the lean vehicle travel data for data conversion stored in the data storage unit 111. The personality conversion data generated by the personality conversion data generation unit 112 is stored in the data storage unit 111.

The personality conversion data stored in the data storage unit 111 is converted from the lean vehicle running data (lean vehicle running data for analysis) of the lean vehicle X (lean vehicle for analysis) into the converted personality data by the personality analyzer 1. It is used when doing. Since the method of converting the lean vehicle traveling data into the converted personality data in the personality analyzer 1 is the same as that of the first embodiment, detailed description thereof will be omitted.

The personality analyzer 1 generates personality data for output using the converted personality data, and outputs the personality data for the output. Since the configuration of the personality analyzer 1 is the same as that of the first embodiment, detailed description of the personality analyzer 1 will be omitted.

The output personality data output from the personality analyzer 1 may be input to, for example, the information processing device 102. In this case, the output personality data is generated in the personality analyzer 1 as information processing personality data used for information processing in the information processing device 102.

The information processing device 102 may be, for example, a device that processes data related to finance, insurance, market, goods, services, environment, or customers used in businesses such as finance, insurance, sales, and advertising. When the personality analysis device 1 is an information processing calculation device, the information processing device 102 may be the same device as the personality analysis device 1. The information processing device 102 may be the same information processing calculation device as the personality conversion data generation device 101.

The information processing device 102 includes, for example, an output personality data acquisition unit 121, a first data acquisition unit 122, a second data generation unit 123, a second data output unit 124, and a data storage unit 125.

The output personality data acquisition unit 121 acquires the output personality data output from the personality analyzer 1.

The first data acquisition unit 122 acquires the first data different from the personality data for the output. This first data is data to be processed by the information processing apparatus 102. The first data is data related to finance, insurance, market, goods, services, environment or customers used in business such as finance, insurance, sales and advertising. The first data is stored in the data storage unit 125.

The second data generation unit 123 uses the output personality data and the first data to generate the output personality data and second data different from the first data. Similar to the first data, this second data is also data related to finance, insurance, market, goods, services, environment or customers used in business such as finance, insurance, sales and advertising.

The second data output unit 124 outputs the second data generated by the second data generation unit 123.

(Information processing method using personality data)
Next, an information processing method for performing information processing using personality data for output by the information processing apparatus 102 having the above configuration will be described with reference to the flowchart shown in FIG. FIG. 4 is a flowchart showing the operation of information processing by the information processing device 102.

As shown in FIG. 4, first, the output personality data acquisition unit 121 of the information processing apparatus 102 acquires the output personality data output from the personality analyzer 1 (step SB1).

Next, the first data acquisition unit 122 of the information processing device 102 acquires the first data stored in the data storage unit 125 (step SB2). This first data is different from the personality data for output.

After that, the second data generation unit 123 of the information processing apparatus 102 generates the second data by using the acquired personality data for output and the acquired first data (step SB3). This second data is different from the personality data for output and the first data.

Subsequently, the second data output unit 124 of the information processing device 102 outputs the generated second data (step SB4).

The output personality data output from the personality analyzer 1 in this way can be used, for example, in the field of finance or insurance, when the information processing device calculates and processes credit risk or credit score. That is, the personality data obtained by using the lean vehicle driving data can be used for the arithmetic processing of the information processing device in the fields of finance, insurance, sales, advertising, and the like.

Specifically, in fields such as finance or insurance, an information processing device acquires the output personality data for output, and uses the acquired personality data for output to perform credit risk or credit by arithmetic processing. The score can be output.

In fields such as finance or insurance, the information processing method is a process of acquiring personality data for output output from the personality analyzer 1 and credit risk data related to credit risk using the acquired personality data for output. Alternatively, it may include a step of outputting credit score data regarding the credit score.

In fields such as finance or insurance, an information processing device uses a personality data acquisition unit that acquires personality data for output output from the personality analyzer 1 and the acquired personality data to provide credit regarding credit risk. It may include a credit risk output unit that outputs risk data or a credit score output unit that outputs credit score data related to credit scores.

In the above-mentioned information processing method and information processing device, when the output credit risk is low or the credit score is high, for example, when the analysis target person can easily obtain a loan or when the analysis target person receives a loan. May give preferential interest rates, or allow the person being analyzed to receive preferential treatment of insurance premiums.

Further, as described above, the personality data for output output from the personality analyzer 1 is taken into consideration when recommending to the analysis target person when the information processing apparatus performs arithmetic processing in the field of sales or advertising, for example. It can be used as a parameter. In fields such as sales or advertising, a product or service may be recommended to the analysis target person according to the personality data of the analysis target person by performing arithmetic processing on the information processing device.

Specifically, in fields such as sales or advertising, the information processing device acquires personality data for output output from the personality analyzer 1, and uses the acquired personality data for output for arithmetic processing. Can output the products or services recommended to the analysis target person.

In fields such as sales or advertising, an information processing device is an analysis target using a personality data acquisition unit that acquires personality data for output output from the personality analyzer 1 and the acquired personality data for output. It may include a product-related data output unit that outputs product-related data related to a product recommended to a person, or a service-related data output unit that outputs service-related data related to services.

In fields such as sales or advertising, the information processing method is a process of acquiring personality data output from the personality analyzer 1 and product-related data or services related to products recommended to the analysis target person using the acquired personality data. It may include a process of outputting service-related data related to the above.

The personality analysis method in each of the above-described embodiments is an example of a personality analysis method for analyzing the personality of the analysis target person.

The personality analysis method of the present invention preferably includes the following configurations. The output personality data is generated as information processing personality data used for further information processing.

For example, the further information processing may be the processing of data related to finance, insurance, markets, products, services, environment or customers used in businesses such as finance, insurance, sales and advertising.

From another point of view, it is preferable that the personality data output by the personality analysis method of the present invention is used in the information processing method using the following personality data. In this information processing method, the personality data for the output is acquired. In the information processing method, first data different from the personality data for output is acquired. In the information processing method, the personality data for output and the acquired first data are used to generate the personality data for output and the second data different from the acquired first data. In the information processing method, the generated second data is output.

The information processing method using the personality data includes the information processing method as described in the patent document described in the background technology. However, it is not limited to the information processing method described in the patent document described in the background technology. The information processing method may be any information processing method as long as it is an information processing method that uses personality data. For example, the first data and the second data may be data related to finance, insurance, market, goods, services, environment or customers used in businesses such as finance, insurance, sales and advertising.

According to the configuration of the present embodiment, the personality data available in the information processing device 102 can be acquired by the personality analysis device 1 and the personality analysis method using the personality analysis device 1. Further, as described in the first embodiment, by using the traveling data of the lean vehicle for the personality analysis, the types of data processed by the system can be reduced, and the hardware load of the personality analyzer 1 can be reduced.

Therefore, it is possible to acquire personality data that can be used in the information processing device while increasing the degree of freedom in designing hardware resources.

The personality analyzer of the present invention preferably includes the following configurations. The personality data for output is generated as information processing personality data used for further information processing.

From another viewpoint, it is preferable that the personality data output by the personality analyzer of the present invention is used in an information processing device that uses the following personality data. This information processing apparatus includes an output personality data acquisition unit that acquires the personality data for the output, a first data acquisition unit that acquires the first data different from the output personality data, and the personality for the output. A second data generation unit that uses the data and the first data to generate personality data for output and second data that is different from the first data, a second data output unit that outputs the second data, and a second data output unit. To be equipped with.

The present invention can be used for a personality analysis method and a personality analyzer for analyzing the personality of an analysis subject, and can also be used for an information processing method and an information processing device using personality data obtained by these methods and devices. Is.

1 Personality analyzer 10 Personality conversion data acquisition unit 20 Analy lean vehicle driving data acquisition unit 30 Personality data conversion unit 40 Output personality data generation unit 50

Data output unit

60, 111, 125 Data storage unit 100 Personality analysis system 101 Personality conversion Data generation device 112 Personality conversion Data generation unit 102 Information processing device 121 Output personality data acquisition unit 122 First data acquisition unit 123 Second data generation unit 124 Second data output unit X Lean vehicle (lean vehicle for analysis)
Y lean vehicle (lean vehicle for data conversion)

Claims

It is a personality analysis method that analyzes the personality of the person to be analyzed.
It is related to the running data of the lean vehicle for data conversion obtained when a plurality of drivers operate a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left. Based on the lean vehicle driving data for data conversion, the personality conversion data generated by associating the personality data indicating the personality with the lean vehicle driving data which is the driving data of the lean vehicle is acquired.
For analysis related to the running data of the lean vehicle for analysis obtained when the analysis subject operates a lean vehicle for analysis that tilts to the right when turning right and tilts to the left when turning left. Acquire lean vehicle driving data and
Using the acquired personality conversion data, the acquired lean vehicle driving data for analysis is converted into conversion personality data related to the personality of the person to be analyzed.
Using the converted conversion personality data, the personality data for output to be output is generated, and the personality data for output is generated.
Output the personality data for the generated output,
Personality analysis method.
In the personality analysis method according to claim 1,
The lean vehicle driving data for data conversion is a change in driving operation for the lean vehicle for data conversion by the driver from data that does not reflect the change in driving operation for the lean vehicle for data conversion by the driver. Contains a lot of data that reflects
The lean vehicle driving data for analysis shows that the change in driving operation for the lean vehicle for analysis by the analysis subject is different from the data that does not reflect the change in driving operation for the lean vehicle for analysis by the analysis target person. A personality analysis method that contains a lot of reflected data.
In the personality analysis method according to claim 1 or 2.
The lean vehicle driving data for data conversion is the lean vehicle driving operation input data for data conversion related to the driving operation input to the lean vehicle for data conversion by the driver, and the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion related to and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion.
The lean vehicle driving data for analysis is related to the lean vehicle driving operation input data for analysis related to the driving operation input to the lean vehicle for analysis by the analysis target person, and the behavior of the lean vehicle for analysis. A personality analysis method comprising at least one of lean vehicle behavior data for analysis and lean vehicle position data for analysis related to the position of the lean vehicle for analysis.
In the personality analysis method according to any one of claims 1 to 3,
The lean vehicle traveling data for data conversion further includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels.
The lean vehicle running data for analysis is a personality analysis method including further lean vehicle running environment data for analysis related to the running environment in which the lean vehicle for analysis is running.
In the personality analysis method according to any one of claims 1 to 4.
The lean vehicle traveling data for data conversion includes more data when the lean vehicle for data conversion travels on a public road than data when the lean vehicle for data conversion travels on a road other than a public road.
The lean vehicle traveling data for analysis is a personality analysis method including more data when the lean vehicle for analysis travels on a public road than data when the lean vehicle for analysis travels on a road other than a public road.
In the personality analysis method according to any one of claims 1 to 5,
The lean vehicle driving data for data conversion includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle for data conversion, but a plurality of data are left.
The lean vehicle traveling data for analysis is a personality analysis method including data in a state where a plurality of judgment options of an analysis target person are limited by vehicles around the lean vehicle for analysis, but a plurality of data are left.
In the personality analysis method according to any one of claims 1 to 6.
The lean vehicle driving data for data conversion includes data in a state where at least one of a passenger and an object is mounted.
The lean vehicle driving data for analysis is a personality analysis method including data in a state where at least one of a passenger and an object is mounted.
In the personality analysis method according to any one of claims 1 to 7.
The converted conversion personality data is stored, and the converted personality data is stored.
A personality analysis method for generating personality data for the output using the plurality of stored conversion personality data.
In the personality analysis method according to any one of claims 1 to 8.
The personality data for output is a personality analysis method generated as information processing personality data used for further information processing.
It is a personality analyzer that analyzes the personality of the person to be analyzed.
It is related to the running data of the lean vehicle for data conversion obtained when a plurality of drivers operate a lean vehicle for data conversion that tilts to the right when turning right and tilts to the left when turning left. A personality conversion data acquisition unit that acquires personality conversion data generated by associating personality data indicating personality with lean vehicle driving data, which is driving data of a lean vehicle, based on lean vehicle driving data for data conversion.
For analysis related to the running data of the lean vehicle for analysis obtained when the analysis subject operates a lean vehicle for analysis that tilts to the right when turning right and tilts to the left when turning left. Lean vehicle driving data acquisition unit for analysis that acquires lean vehicle driving data,
Using the acquired personality conversion data, a personality data conversion unit that converts the acquired lean vehicle driving data for analysis into conversion personality data related to the personality of the person to be analyzed, and a personality data conversion unit.
An output personality data generator that generates output personality data for output using the converted conversion personality data.
A data output unit that outputs the generated personality data for output, and
A personality analyzer equipped with.
In the personality analyzer according to claim 10,
The lean vehicle driving data for data conversion is a change in driving operation for the lean vehicle for data conversion by the driver from data that does not reflect the change in driving operation for the lean vehicle for data conversion by the driver. Contains a lot of data that reflects
The lean vehicle driving data for analysis shows that the change in driving operation for the lean vehicle for analysis by the analysis target person is different from the data that does not reflect the change in driving operation for the lean vehicle for analysis by the analysis target person. A personality analyzer that contains a lot of reflected data.
In the personality analyzer according to claim 10 or 11.
The lean vehicle driving data for data conversion is the lean vehicle driving operation input data for data conversion related to the driving operation input to the lean vehicle for data conversion by the driver, and the behavior of the lean vehicle for data conversion. Includes at least one of lean vehicle behavior data for data conversion related to and lean vehicle position data for data conversion related to the position of the lean vehicle for data conversion.
The lean vehicle driving data for analysis is related to the lean vehicle driving operation input data for analysis related to the driving operation input to the lean vehicle for analysis by the analysis subject, and the behavior of the lean vehicle for analysis. A personality analyzer comprising at least one of lean vehicle behavior data for analysis and lean vehicle position data for analysis related to the position of the lean vehicle for analysis.
In the personality analyzer according to any one of claims 10 to 12,
The lean vehicle traveling data for data conversion further includes lean vehicle traveling environment data for data conversion related to the traveling environment in which the lean vehicle for data conversion travels.
The lean vehicle running data for analysis is a personality analyzer further including lean vehicle running environment data for analysis related to the running environment in which the lean vehicle for analysis is running.
In the personality analyzer according to any one of claims 10 to 13.
The personality data for output is a personality analyzer that is generated as personality data for information processing used for further information processing.
An information processing method using the output personality data generated as the information processing personality data by the personality analysis method according to claim 9.
Acquire the personality data for the output and
Acquire the first data different from the personality data for the output,
Using the personality data for output and the first data, the personality data for output and the second data different from the first data are generated.
An information processing method using personality data that outputs the second data.
An information processing apparatus that uses the output personality data generated as the information processing personality data by the personality analyzer according to claim 14.
An output personality data acquisition unit that acquires the output personality data,
A first data acquisition unit that acquires first data different from the personality data for output, and
A second data generation unit that uses the output personality data and the first data to generate the output personality data and second data different from the first data.
A second data output unit that outputs the second data, and
An information processing device that uses personality data.