OA20516A

OA20516A - Personality analyzing method, personality analyzing device, data processing method employing personality data, and data processing device employing personality data

Info

Publication number: OA20516A
Application number: OA1202100450
Authority: OA
Inventors: Keisuke Morishima; Kensaku Isobe; Hiroshi Nakao; Yusuke Umezawa; Hiroaki Kimura
Original assignee: Yamaha Hatsudoki Kabushiki Kaisha
Priority date: 2019-04-01
Filing date: 2020-04-01
Publication date: 2022-09-30

Abstract

Provided is a personality analyzing method capable of acquiring personality data with enhanced design flexibility of hardware resources. The personality analyzing method includes: acquiring personality conversion data generated by associating personality data with leaningvehicle-traveling data, based on data-conversionleaning-vehicle-traveling data related to traveling data of data-conversion-leaning vehicles obtained when a plurality of drivers drives the dataconversion-leaning vehicles; acquiring analysisleaning-vehicle-traveling data related to traveling data of an analysis leaning vehicle obtained when an analysis target drives the analysis leaning vehicle; converting the analysis-leaning-vehicletraveling data to converted personality data related to personality of the analysis target by using the personality conversion data; and generating and outputting personality data to be output by using the converted personality data after conversion.

Description

MORISHIMA, Keisuke (JP);

ISOBE, Kensaku (JP);

NAKAO, Hiroshi (JP);

UMEZAWA, Yusuke (JP);

KIMURA, Hiroaki (JP)

Mandataire : Cabinet BONNY & Associés, LAW FIRM, B.P. 869, YAOUNDE (CM).

Titre : Personality analyzing method, personality analyzing device, data processing method employing personality data, and data processing device employing personality data.

Abrégé :

Provided is a personality analyzing method capable of acquiring personality data with enhanced design flexibility of hardware resources. The personality analyzing method includes: acquiring personality conversion data generated by associating personality data with leaning-vehicle-traveling data, based on data-conversion-leaning-vehicle-traveling data related to traveling data of data-conversion-leaning vehicles obtained when a plurality of drivers drives the dataconversion-leaning vehicles; acquiring analysisleaning-vehicle-traveling data related to traveling data of an analysis leaning vehicle obtained when an analysis target drives the analysis leaning vehicle; converting the analysis-leaning-vehicle-traveling data to converted personality data related to personality of the analysis target by using the personality conversion data; and generating and outputting personality data to be output by using the converted personality data after conversion.

Fig. 1

O.A.P.I. - B.P. 887, YAOUNDE (Cameroun) - Tel. (237) 222 20 57 00-Site web: http:/www.oapi.int- Email: [email protected]

PERSONALITY ANALYZING METHOD, PERSONALITY ANALYZING DEVICE, DATA PROCESSING METHOD EMPLOYING PERSONALITY DATA, AND DATA PROCESSING DEVICE EMPLOYING PERSONALITY DATA

TECHNICAL FIELD

[0001] The present teaching relates to a personality analyzing method and a personality analyzing device for analyzing personality of an analysis target, a data processing method employing personality data, and a data processing device employing personality data.

BACKGROUND ART

[0002] A known data processing device perforais data processing using personality of a customer. As a configuration for performing data processing by using personality of a customer, configurations disclosed in Patent Documents 1-4, for example, are known.

[0003] Patent Document 1 discloses a gift advising method that détermines a level of jnterest of a user based on a product content selected by the user and recommends a gift to the user in accordance with the level of interest.

[0004] Patent Document 2 discloses an online matchmaking system. Specifically, in this matchmaking System, the number of a participant profile is determined for each participant, and the participant attends an online meeting corresponding to the number. In this online meeting, a feedback related to other participants is received from the participant so that détermination is made whether or not there is a two-way match between participants to frie online meeting.

[0005] Patent Document 3 discloses a System for determining a risk level of an individual. Specifically, the system processes Personal information such as eye related information to generate cognitive information associated with an individual, and détermines a risk level of the individual by usina the cognitive information. The cognitive information is compared to baseline cognitive information of an individual in order to détermine a risk level of the individual.

[0006] Patent Document 4 discloses a system for selecting and customizing advertisements to be provided to a user. Specifically, this system monitors user interactions within a Virtual gaming environment, and indirectiy détermines user characteristics based on the contents of the interactions. The system customizes, for a user, advertisements selected based on a user profile generated from user characteristics, and dispiays the advertisements to the user in a Virtual gaming environ mentI

[0007] In a data processing system for performing data processing by employing user personaiity, a configuration for acquiring the personaiity data in the form of questions and answers to the user is aîso known. As the configuration for acquiring personaiity data in the form of questions and answers to the user described above, configurations disclosed in Patent Documents 5 and 6, for example, are known.

[0008] Patent Document 5 discloses a method for evaluating financial personaiity. Specifically, in this method, a questionnaire for evaluating financial personaiity is provided to a user. In this method, user's investment-related attitudes are evaluated based on questionnaire results, and multi-dimensional financial personal information is generated. In the method, a risk profile of a user is constructed from the multi-dimensional financial Personal information.

[0009] Patent Document 6 disciôsês a method for measuring and managing risk in considération of a human behavior. This method measures and manages an operational risk in an organization, a crédit risk, and/or a market risk by using objective and subjective data. Specifically, in this method, psychometric and/or other personaiity assessment tools are applied to a selected group of people involved, and the results are stored as subjective data in a measuring and management System along with objective data.

CITATION LIST

PATENT DOCUMENT

[0010] Patent Document 1: U.S. Patent Application Publication No. 2018/0130115

Patent Document 2: International Patent Application Publication No. 2016/000069

Patent Documents: U.S. Patent Application Publication No. 2015/0025917

Patent Document 4: U.S, Patent No. 9152984

Patent Document 5: U.S. Patent Application Publication No. 2011/0251978

Patent Documente: U.S. Patent Application Publication No. 2005/0278245

SUMMARY OF INVENTION

TECHNICAL PROBLEM

[0011] In the case of performing data processing by using user personaiity as described above, to perform data processing more precisely, inhérent personaiity data with small user arbitrariness is demander!

[0012] In the case of obtaining user personaiity from results obtained in the form of questions and answers as described above in Paient Documents 4 and 5, to obtain inhérent personality with small user arbitrariness, it is necessary to increase the number of questions in different expressions and/or add questions related to a false discovery scale (lie scale) to questions. Accordingly, the number of questions to the user increases, and consequently, the number of types of data to be processed in the System signîficantly increases.

[0013] When the number of types of data to be processed in the System considerably increases as described above, a load on hardware of the system increases. Accordingly, hardware resources required for the System increase, which restricts design of hardware resources of the system. As a resuit, design flexibility of hardware resources of the system decreases.

[0014] It is therefore an object of the présent teaching to provide a personality analyzing method for acquiring personality data with enhanced design fiexibility of hardware resources.

SOLUTION TO PROBLEM

[0015] Through an analysis of traveling data of a leaning vehicle, the inventors of the présent teaching found that the traveling data of the leaning vehicle is signîficantly different from traveling data of a non-leaning vehicle. The leaning vehicle is a vehicle that leans rightward when tuming to the right and leans leftward when tuming to the left.

[0016] A leaning vehicle is smaller in vehicle size than a non-leaning vehicle. That is, the size of the leaning vehicle in the front-rear direction and/or in the left-right direction is smaller than that of the non-leaning vehicle. A rotationai operation amount of steering of the leaning vehicle is smaller than 360 degrees, and thus, the rotationai operation amount of steering of the leaning vehicle is smaller than that of the non-leaning vehicle. In addition, unlike the non-leaning vehicle, the leaning vehicle is a rider-active vehicle actively opérais b le by a rider. Thus, an operation ofthe leaning vehicle is different from an operation of the non-leaning vehicle. Traveling data of such a leaning vehicle whose operation is different from that of a non-leaning vehicle is signîficantly different from traveling data ofthe non-leaning vehicle, such as a four-wheeled vehicle.

[0017] The inventors of the présent teaching further intensively investigated traveling situations of a leaning vehicle to find that the leaning vehicle has a very high degree of flexibility in traveling by an intension of a rider, as compared to that of a non-leaning vehicle.

[0018] Thus, while a driver drives a leaning vehicle, the number of déterminations by the driver and the number of options in each détermination tend to be larger than those in a case where the driver drives a non-leaning vehicle.

[0019] In addition, while the driver drives the leaning vehicle, the driver is more likely to be subjected to stress from the outside than in the case where the driver drives the nonleaning vehicle. Furthermore, a wide variety of stress is appiied from the outside to the driver of the leaning vehicle.

[0020] As described above, since the number of déterminations by the driver and the number of options in each détermination are large and the driver is likely to be subjected to stress from the outside while the driver drives the leaning vehicle, personality of the driver tends to appear strongly in traveling data of the leaning vehicle. in addition, since the leaning vehicle has higher degrees of mobility and convenience than the non-leaning vehicle, the leaning vehicle can be used for various applications, and tends to be frequently used. Accordingly, personality of the driver tends to appear strongly in traveling data ofthe leaning vehicle. That is, the inventors ofthe présent teaching found that traveling data of the leaning venicié driven by ihe driver shows iess arbitrariness of the driver and more strongly reflects inherent personality ofthe driver.

[0021] In view of the above findings, the inventors of the présent teaching conceived a technique of analyzing inherent personality with small arbitrariness by using traveling data of the leaning vehicle, The use of traveling data of the leaning vehicle for personality analysis can reduce the number of types of data processed by a system and can reduce a load on system hardware for analyzing personality. Since hardware resources necessary for the System can be reduced, design flexibility of hardware resources of a System for personality analysis can be enhanced. The inventors devised a personality analyzing method capable of acquiring personality data with enhanced design flexibility of hardware resources.

[0022] There is a known technique of estimating characteristic tendency of a driver of a four-wheeled vehicle (see, for example, Japanese Patent Application Publication No. 2014-46820). Japanese Patent Application Publication No. 2014-46820 (hereinafter referred to as Reference 1) discloses a driver-characteristic-estimation device that estimâtes a scene in which a four-wheeled vehicle traveîs based on information indjçating a surrounding situation, detects a driving behavior of a driver based on vehicle information ofthe four-wheeled vehicle, and based on the driving behavior of the driver in the estimated scene, estimâtes characteristics ofthe driver based on a corrélation with a characteristic tendency label.

[0023] Reference 1, howevër, only provides description concerning a characteristic tendency label and an emotional réaction as driving behavior characteristics of the driver, and neither discloses nor suggests that personality of the driver is anaîyzed by using traveling data of a leaning vehicle, unlike the présent teaching. The personality as used in the présent teaching is determined based on, for example, psychological state, character, or tempérament of an individual. Such personality is neither disciosed nor suggested by Reference 1.

[0024] That is, in the four-wheeied vehicle disclosed in Reference 1, there are a small number of options of a driver in driving the vehicle, and thus, flexibility in driving by a driver¹ s intension is low. Thus, in the four-wheeled vehicle, personality of the driver is less likely to appear in traveling data of the vehicle. Accordingly, in the configuration of Reference 1 directed to four-wheeled vehicles, the limitation is to obtain not personality of the driver but three items conceming tendency (driving tendency) of the driver in driving the vehicle (i.e., other-minded type, self-oriented type, and non-empathetic type) and emotîonal reaction such as émotions.

[0025] On the other hand, as described above, in a leaning vehicle as described in the présent teaching, while a driver drives the leaning vehicle, the driver has many opiions, and thus, flexibility in driving by an intension of the driver is high, and the driver is likely to be subjected to stress from the outside. Accordingly, inhérent personality of the driver of the leaning vehicle tends to appear strongly in traveling data of the leaning vehicle. Thus, personality of the driver can be analyzed by using traveling data of the leaning vehicle, as described in the présent teaching.

[0026] As described above, limitation is to estimate driving tendency and emotîonal reaction such as émotions of the driver from vehicle information such as traveling data of a non-leaning vehicle such as a four-wheeled vehicle, as disciosed in Reference 1. it is clear that personality, which is determined by, for example, psychological state, character, or tempérament of an individual as described in the présent teaching, cannot be analyzed from the traveling data ofthe non-leaning vehicle.

[0027] The emotîonal reaction such as émotions of the driver constantly changes dépending on situations, and is significantly different from personality as used in the présent teaching. As an émotion estimating device for estimating émotions of a driver of a leaning vehicle, a device described in International Patent Application Publication No. 2018/092436 (hereinafter referred to as Reference 2) is known, for example. However, émotions as disclosed in Reference 2 are totally different from personality used in the présent teaching in terms of concept. Thus, the émotion estimating device of Reference 2 is significantly different in configuration from the personality analyzing device of the présent teaching. Therefore, even if Reference 1 and the Reference 2 were combined, this combination would not readily reach the configuration of the présent teaching.

[0028] A personality analyzing method according to one embodiment of the présent teaching includes: a personality-conversion-data-acquiring step of acquiring personality conversion data generated by assoçiating personality data with leaning-vehicle-traveiing data, the personality data showing personality determined based on, for example, psychological siate, character, or tempérament, the leaning-vehicie-traveling data being traveling data of a leaning vehicie configured tô lean rightward when turning to the right and lean leftward when turning to the left; an analysis-leaning-vehicle-traveling-dataacquiring step of acquiring ieaning-vehicle-traveling data for analysis (analysis-leaningvehicle-traveling data) related to traveling data of a leaning vehicle for analysis {analysis leaning vehicle) configured to lean rightward when turning to the right and lean leftward when turning to the left; a personality-data-conversion step of converting the acquired analysis-leaning-vehicle-traveling data to converted personality data related to personality of an analysis target, by using the acquired personality conversion data; a personality data-to-be-output-generation step of generating personality data to be output for output by using the converted personality data after conversion; and a personality-data-output step of outputting the generated personality data to be output. In the personalityconversion-data-acquiring step, the personality conversion data is generated by associating the personality data showing personality with the leaning-vehicie-traveling data that is traveling data of the leaning vehicle, based on leaning-vehicie-traveling data for data conversion (data-conversion-leaning-vehicle-traveling data) related to traveling data obtained when each of a plurality of drivers drives a leaning vehicle for data conversion (data-conversion-leaning vehicle). In the analysis-leaning-vehicle-travelingdata-acquiring step, as the analysis-ieaning-vehicie-traveüng data, data related to traveling data of the analysis leaning vehicle obtained when the analysis target drives the analysis leaning vehicle is acquired. The personality analyzing method anaiyzes personality of the analysis target driving the analysis leaning vehicle that leans rightward when turning to the right and leans leftward when turning to the left.

[0029] While driving a leaning vehicle, a driver makes a large number of déterminations from many options and is likely to be subjected to stress from the outside. Thus, leaning-vehicie-traveling data that is traveling data of the leaning vehicie driven by the driver is likely to strongiy show inhérent personality of the driver with small arbitrariness.

[0030] In view of this, the driver of the leaning vehicle is defined as an analysis target whose personality is to be analyzed so that personality of the analysis target can be thereby acquired. The use of the traveling data of the leaning vehicie for personality analysis can reduce the number of types of data to be processed by a device for analyzing personality and can reduce a load on hardware of the device. In addition, hardware resources necessary for the device can be reduced so that design flexibility of hardware resources of the device can be thereby enhanced.

[0031] As a resuit, personaiity data can be acquired with enhanced design flexibility of hardware resources.

[0032] In another aspect, the personaiity analyzing method of the présent teaching preferably has a configuration as follows: The data-conversion-leaning-vehicle-traveling data includes data related to traveling data obtained when each ofthe plurality of drivers drives the data-conversion-leaning vehicle in a lean State. The analysis-leaningvehicîe-traveîing data includes data related to traveling data obtained when the analysis target drives the analysis leaning vehicle in a lean State.

[0033] Accordingly, personaiity of the analysis target can be analyzed by using traveling data in the lean State of the leaning vehicle in which personaiity of the driver is more noticeable. Thus, personaiity of the analysis target as a driver can be more preciseiy analyzed.

[0034] In another aspect, the personaiity analyzing method according to the présent teaching preferably includes the following configurations. The data-conversion-ieaningvehicle-traveling data includes a larger amount of data reflecting a change in driving of the data-conversion-leaning vehicle by the driver than data not reflecting a change in driving of the data-conversion-leaning vehicle by the driver. The analysis-leaningvehicle-traveling data includes a larger amount of data reflecting a change in driving of the analysis leaning vehicle by the analysis target than data not reflecting a change in driving of the analysis leaning vehicle by the analysis target.

[0035] With this configuration, the leanîng-vehicle-traveling data as traveling data of the leaning vehicle driven by the driver reflects a change in driving of the leaning vehicle after détermination of the driver. Thus, ieaning-vehicîe-traveîing data that is traveling data of the leaning vehicle driven by the driver is likely to more strongly show inhérent personaiity of the driver with small arbitrariness.

[0036] Thus, personaiity of the analysis target as a driver can be more preciseiy analyzed, The use of the leanîng-vehicle-traveling data in which the types of data are specified can reduce the number of types of data to be processed by a device for analyzing personaiity and can further neduce a load on hardware of the device. In addition, hardware resources necessary for the device can be reduced so that design flexibility of hardware resources of the device can be thereby further enhanced.

[0037] As a resuît, personaiity data can be acquired more preciseiy with further enhanced design flexibility of hardware resources.

[0038] In another aspect, the personaiity analyzing method according to the présent teaching preferably includes the following configurations. The data-conversion-leaningvehicle-traveling data includes at least one of leaning-vehicle-driving-input data for data conversion (data-conversion-leaning-vehicle-driving-input data) related to a driving input to the data-conversion-leaning vehicie by the driver, leaning-vehicle-behavior data for data conversion (data-conversion-leaning-vehicle-behavior data) reîated to a behavior of the data-conversion-leaning vehicle, or leaning-vehicle-location data for data conversion (data-conversion-leaning-vehicie-location data) related to a location of the dataconversion-leaning vehicle. The analysis-leaning-vehicle-traveîing data includes at least one of leaning-vehicle-driving-input data for analysis (analysis-leaning-vehiciedriving-input data) related to a driving input to the analysis leaning vehicle by the analysis target, leaning-vehicle-behavior data for analysis (analysis-leaning-vehiciebehavior data) reîated to a behavior of the analysis leaning vehicle, or leaning-vehiclelocation data for analysis (analysis-leaning-vehicle-location data) related to a location of the analysis leaning vehicle.

[0039] Accordingly, leaning-vehicle-traveling data for use in conversion to personality data related to personality of an analysis target includes data more strongly reflecting personality of the analysis target as a driver.

[0040] That is, the leaning-vehicle-driving-input data conceming a driving input to the leaning vehicle by the driver and the leaning-vehicle-behavior data conceming a behavior of the leaning vehicle are related to, for example, sensitivity to environmental stimuli and stress, and intensities of anxiety and tension, of the driver. The leaning-vehicle-location data conceming a location of the leaning vehicle is related to personality such as psychological State and a character of the driver.

[0041] With this configuration, personality of the analysis target as a driver can be more precisely anaiyzed by using the leaning-vehicle-traveling data. The use of the leaning-vehicle-traveling data in which the types of data are specified can reduce the number of types of data to be processed by a device for analyzing personality and can further reduce a load on hardware of the device. In addition, hardware resources necessary for the device can be reduced so that design flexibility of hardware resources of the device can be thereby further enhanced.

[0042] As a resuit, personality data can be acquired more precisely with further enhanced design flexibility of hardware resources.

[0043] In another aspect, the personality analyzing method according to the présent teaching preferably includes the following configurations. The data-conversion-leaningvehicle-traveling data further includes leaning-vehicle-traveling-environment data for data conversion (data-conversion-leaning-vehicle-traveling-environment data) related to a traveling environment in which the data-conversion-leaning vehicle travels. The analysis-leaning-vehiçle-travelîng data further includes leaning-vehicle-traveling environment data for anaiysis (analysis-leaning-vehicle-traveling-environment data) related to a traveiing environment in which the analysis leaning vehicie travels.

[0044] Accordingiy, Îeaning-vehicie-traveîing data for use in conversion to personality data related to personality of an analysis target includes data more strongly reflecting personality of the analysis target as a driver.

[0045] The leaning-vehicle-traveling-environment data includes map data, for exampie. The map data may be associated with, for example, information on road situations, information on road traffic environments such as signais and facilities, and régulation information on traveiing on roads. The leaning-vehicle-traveling-environment data may be used for analyzing personality such as a charader of an analysis target, together with the leaning-vehicle-driving-input data, the leaning-vehide-behavior data, and the leaningvehicie-location data.

[0046] With this configuration, personality of the analysis target as a driver can be more précisély analyzed by using the leaning-vehicle-traveling data. The use of the leaning-vehicle-traveling data in which the types of data are specified can reduce the number of types of data to be processed by a device for analyzing personality and can further reduce a load on hardware of the device. In addition, hardware resources necessary for the device can be reduced so that design flexibility of hardware resources of the device can be thereby further enhanced.

[0047] As a resuit, personality data can be acquired more precisely with further enhanced design flexibility of hardware resources.

[0048] In another aspect, the personality analyzing method according to the présent teachîng preferabïy includes the foliowing configurations. The data-conversion-leaningvehicle-traveling data includes a larger amount of data in traveiing of the dataconversion-leaning vehicie on a public road than data in traveiing of the data-conversionleaning vehicie on a place except for a public road. The analysis-leaning-vehicletraveling data includes a larger amount of data in traveiing ofthe analysis leaning vehicie on a public road than data in traveiing of the analysis leaning vehicie on a place except for a public road.

[0049] Since the number of déterminations by the driver and the number of options in each détermination are large and the driver is likely to be subjected to stress from the outside while the driver drives the leaning vehicie on a public road, personality of the driver tends to appear strongly in traveiing data of the leaning vehicie, in addition, since the leaning vehicie has higher degrees of mobility and convenience than a non-leaning vehicie, the leaning vehicie can be used for various applications, and tends to be frequently used. Accordingiy, personality of the driver tends to appear more strongly in traveling data of the leaning vehicle traveling on a public road. That is, the traveling data of the leaning vehicle traveling on a public road more strongiy reflects inhérent personality of the driver with small arbiirariness of the driver.

[0050] With this configuration, personality of the analysis target as a driver can be 5 more precisely analyzed by using the leaning-vehicle-traveling data. The use of the teaning-vehicle-traveling data in winich the types of data are specified can reduce the number of types of data to be processed by a device for analyzing personality and can further reduce a load on hardware of the device. In addition, hardware resources necessary for the device can be reduced so that design flexibility of hardware resources 10 of the device can be thereby further enhanced.

[0051] As a resuit, personality data can be acquired more precisely with further enhanced design flexibility of hardware resources.

[0052] In another aspect, the personality analyzing method according to the present teaching preferably includes the following configurations. The dataconversion-leaning15 vehicle-traveling data includes data in a State where options of détermination by the driver are limited by a vehicle a round the data-conversion-îeaning vehicle but some options are left. The analysis-leaning-vehicle-traveling data includes data in a State where options of détermination by the analysis target are limited by a vehicle around the analysis leaning vehicle but some options are left.

[0053] With this configuration, the leaning-vehicle-traveling data in the State where options of détermination by the driver are limited but some options are left more clearly reflects personality of the driver than leaning-vehicle-traveling data in a State where no options of détermination by the driver are left. Thus, personality of the analysis target as the driver can be more precisely analyzed by using the leaning-vehicle-traveling data in 25 the State where options of détermination by the driver are limited but some options are left. The use of the leaning-vehicle-traveling data in which the types of data are specified can reduce the number of types of data to be processed by a device for analyzing personality and can further reduce a load on hardware of the device. In addition, hardware resources necessary for the device can be reduced so that design 30 flexibility of hardware resources of the device can be thereby further enhanced.

[0054] As a resuit, personality data can be acquired more precisely with further enhanced design flexibility of hardware resources.

[0055] In another aspect, the personality analyzing method according to the present teaching preferably includes the following configurations. The data-conversion-leaning35 vehicle-traveling data includes data in a State where at least one of a passenger or an object is mounted, The analysjs-leaning-vehicle-traveling data includes data in a State where at least one of a passenger or an object is mounted.

[0056] In the îeaning vehicle in the state where at least cne of a passenger or an object is mounted, options of détermination of the driver are more Rkeïy to be limited than in a state where at least one of a passenger or an object is not mounted. Th us, personality of the analysis target as a driver can be more precisely analyzed by using the leaning-vehicle-traveling data including the data in the state where at least one of a passenger or an object is mounted- The use of the leaning-vehicle-traveling data in which the types of data are specified can reduce the number of types of data to be processed by a device for analyzing personality and can further reduce a load on hardware of the device. In addition, hardware resources necessary for the device can be reduced so that design flexibility of hardware resources of the device can be thereby further enhanced.

[0057] As a resuit, personality data can be acquired more precisely with further enhanced design flexibility of hardware resources.

[0058] In another aspect, the personality analyzing method according to the présent teaching preferably includes the following configurations, The converted personality data after conversion is stored. The personality data to be output is generated by using a plurality of sets of the converted personality data that hâve been stored.

[0059] The use of a plurality of sets of converted personality data enables personality of the analysis target who is the driver of the Ieaning vehicle to be more precisely analyzed.

[0060] As a resuit, personality data can be acquired more precisely with further enhanced design flexibility of hardware resources.

[0061] In another aspect, the personality analyzing method according to the présent teaching preferably includes the following configurations. The personality data to be output is generated as personality data for data processing that is used for further data processing.

[0062] Accordingly, personality data obtained by the personality analyzing method by using the leaning-vehicle-traveling data of the ieaning vehicle driven by the analysis target can be used for another data processing device.

[0063] As a resuit, personality data capable of being used for further data processing can be acquired with enhanced design fiexibiliîy of hardware resources.

[0064] A personality analyzing device according to one embodiment of the présent teaching includes; a personaîity-conversion-data acquirer configured to acquire personality conversion data generated by associating personality data with leaningvehicle-traveling data, the personality data showing personality determined based on, for example, psychological state, character, or tempérament, the leaning-vehicle-traveling data being traveling data of a ieaning vehicle configured to lean rightward when tuming to the right and îean ieftward when tuming îo the ieft; an analysîs-leaning-vehicietraveiing-data acquirer configured to acquire analysis-leaning-vehicle-traveling data 5 related to traveling data of an analysis Ieaning vehicle configured to lean rightward when tuming to the right and lean leftward when tuming to the ieft: a personalîty data converter configured to convert the acquired analysis-leaning-vehicle-traveling data to converted personalîty data related to personalîty of an analysis target, by using the acquired personalîty conversion data; a personaiity-data-to-be-output generator configured to 10 generate personalîty data to be output for output by using the converted personalîty data after conversion; and a data output section configured to output the generated personalîty data to be output. The personality-conversion-data acquirer associâtes the personalîty data showing personalîty with the teaning-vehide-traveling data that is traveling data of the Ieaning vehicle, based en data-conversion-leaning-vehicle-traveling Î5 data related to traveling data obtained when each of a plurality of drivers drives a dataconversion-leanîng vehicle. The anaiysis4eaning-vehicle-trave!ing-data acquirer acquires, as the analysis-ieaning-vehicle-traveling data, data related to traveling data of the analysis Ieaning vehicle obtained when the analysis target drives the analysis Ieaning vehicle. The personalîty anaiyzing device analyses personalîty of the analysis 20 target driving the analysis Ieaning vehicle configured to lean rightward when tuming to the right and lean leftward when tuming to the Ieft.

[0065] In another aspect, the personalîty anaiyzing device according to frie présent teaching preferably indudes the foilowing configurations. The data-conversion-leaningvehicle-traveling data includes data related to traveling data obtained when each of the 25 plurality of drivers drives the data convers!on-Ieaning vehicle in a lean state. The analysis-ieaning-vehicle-traveling data includes data related to traveling data obtained when the analysis target drives the analysis Ieaning vehicle in a lean state.

[0066] In another aspect, the personalîty anaiyzing device according to the présent teaching preferably indudes the following configurations. The data-conversion-leaning30 vehicle-traveiing data indudes a iarger amount of data reflecting a change in driving of the data-conversion-ieaning vehide by the driver than data not reflecting a change in driving of the data-conversîon-ieaning vehicle by the driver. The analysis-leaningvehicle-traveling data indudes a Iarger amount of data reflecting a change in driving of the analysis Ieaning vehicle by the analysis target than data not reflecting a change in 35 driving of the analysis Ieaning vehicle by the analysis target.

[0067] In another aspect, the personality anaiyzing device according to the présent teaching preferably includes the following configurations, The data-conversion-leaningvehicle-traveling data includes at least one of data-conversion-leaning-vehicle-drivinginpui data related to a dhving input to the data-conversion-leaning vehicle by the driver, data-conversion-leaning-vehicle-behavior data related to a behavior of the dataconversion-leaning vehicle, or datc-cûnversion-lecnÎng vehicie lacctian data related to a location of the data-conversion-leaning vehicle. The anaiysis-leaning-vehicle-traveüng data includes at least one of analysis-leaning-vehicle-driving-input data related to a driving input to the analysis îeaning vehicle by the analysis target, analysis-leaningvehicle-behavior data related to a behavior of the analysis Ieaning vehicle, or analysisleaning-vehicle-location data related to a location ofthe analysis Ieaning vehicle.

[0068] In another aspect, the personaiity analyzing device according to the présent teaching preferabiy includes the following configurations. The daia-conversion-iêaningvehicle-traveling data further includes data-conversion-leaning-vehicle-travelingenvironment data related to a traveling environment in which the data-conversionleaning vehicle travels. The anaiysis-leaning-vehicle-traveiing data further includes analysis-leaning-vehicle-traveiing-envînonment data related to a traveling environment in which the analysis Ieaning vehicle travels.

[0069] In another aspect, the personaiity analyzing device according to the présent teaching preferably includes the following configurations. The personaiity data to be output is generated as personaiity data for data processing that is used for further data processing.

[0070] A data processing method according to one embodiment of the présent teaching is a data processing method ëmpioying the personaiity data to be output generated as the personaiity data for data processing in the personaiity analyzing method described above. The data processing method acquires the personaiity data to be output. The data processing method acquires first data different from the personaiity data to be output. The data processing method generates second data by using the personaiity data to be output and the first data, the second data being different from the personaiity data to be output and the first data. The data processing method outputs the second data.

[0071] The data processing method using personaiity data includes data processing methods as described in Patent Documents mentioned in Background Art. The présent teaching, however, is not limited to data processing methods as described in Patent Documents listed in the Background Art. The method according to the présent teaching only needs to be a data processing method employing personaiity data. For example, the first data and the second data may be data related to finance, Insurance, markets, products, services, envîronments, or customers used in the businesses of finance, insurance, sales, advertising, and so forth.

[0072] Accordingly, the personality data output by using the leaning-vehicie-traveling data including inhérent personality of the driver with small arbitrariness and the first data different from the output personality data are used to generate and output the second data different from the acquired personality data and the acquired first data, in this manner, the second data can be generated more precisely and output,

[0073] As a resuit, the second data can be generated more precisely and output by using personality data with enhanced design flexibility of hardware resources for executing the data processing method employing the personality data.

[0074] A data processing device according to one embodiment of the présent teaching is a data processing device employing the personality data to be output generated as the personality data for data processing in the personality analyzing method described above. The data processing device includes: a personality-data-to-be-output acquirer configured to acquire the personality data to be output; a first data acquirer configured to acquire first data, the first data being different from the personality data to be output; a second data generator configured to generate second data by using the personality data to be output and the first data, the second data being different from the personality data to be output and the first data; and a second-data-output section configured to output the second data.

[0075] The temninology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of frie invention.

[0076] As used herein, the terni “and/or” includes any and ail combinations of one or more ofthe associated listed items.

[0077] It will be further understood that the terms “including, “comprising or “having” and variations thereof when used in this spécification, specify the presence of stated features, steps, éléments, components, and/or their équivalents but do not preciude the presence or addition of one or more steps, operations, éléments, components, and/or groups thereof.

[0078] It will be further understood that the terms “mounted,” connected, coupled,” and/or their équivalents are used broadly and encompass both direct and indirect mounting, connecting and coupling. Further, “connected and coupled are not restricted to physical or mechanical connections or couplings, and can include connections or couplings, whether direct or indirect.

[0079] Unless otherwise defined, ail terms (including technical and scientific terms) used herein hâve the same meaning as commonly understood by one having ordinary skill in the art to which this invention belongs.

[0080] It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disciosure and will not be interpreted in an idealized oroverty formai sense unless expressly so defined herein.

[0081] In describing the invention, it will be understood that a number of techniques and steps are disclosed. Each of these has individual benefit and each can also be used in conjunction with one or more, or in some cases ali, of the other disclosed techniques.

[0082] Accordingly, for the sake of clarity, this description will refrain from repeating every possible combination of the individual steps in an unnecessary fashion. Neveriheless, the spécification and daims should be read with the understanding that such combinations are entirely within the scope of the invention and the daims.

[0083] In this spécification, embodiments of a personality analyzing method, a personality analyzing device, a data processing method employing personality data, and a data processing device employing personality data according to the present teaching will be described.

[0084] In the following description, numerous spécifie details are set forth in order to provide a thorough understanding of the présent invention. It will be évident, however, to one skilled in the art that the present invention may be practiced without these spécifie details.

[0085] The present disclosure is to be considered as an exemplification of the invention, and is not intended to limit the invention to the spécifie embodiments illustrated by the figures or description below.

[0086] [Leaning Vehicle]

A leaning vehicle herein is a vehicle that tums in a leaning posture. Specifically, the leaning vehicle is a vehicle that leans leftward when turning to the left and leans rightward when turning to the right, in the left-right direction of the vehicle. The leaning vehicle may be a single-passenger vehicle or a vehicle on which a plurality of passengers can ride. The leaning vehicle includes ail the types of vehicles that turn in leaning postures, such as three-wheeled vehicles and four-wheeled vehicles as well as two-wheeled vehicles.

[0087] [Personality]

Personality herein refers to indivîduality determined based on, for example, psychological state, character, or tempérament of an individual. Specifically, the personality may include five éléments of neuroticism, extroversion, openness to expenence, cooperativeness, and iniegrity. The personality may also include six character types such as dereism, conformity, stickiness, demonstrativeness, hypersensitivity, and overconfidence. The personality may also include tempéraments of novelty desire, reward dependence, damage avoidance, and persistence, and characters of self-orientation, cooperativeness, and self-transcendence.

[0088] The personality may include any parameters concerning individuality of an individual in addition to the parameters listed above, [0089] [Leaning-Vehicle-Traveling Data]

Leaning-vehicle-traveiing data herein refers to data related to traveling of a leaning vehicle. Specifically, the leaning-vehicle-traveiing data includes at least one of leaning-vehicle-driving-input data related to a driving input to a leaning vehicle by a driver, ieaning-vehicie-behavior data related to a bêhavior of the leaning vehicie, ieaningvehicie-location data related to a traveling location of the leaning vehicle, or leaningvehicle-traveling-environment data related to a traveling environment of traveling of the leaning vehicle, for examie. The leaning-vehicle-traveiing data may include processed data obtained by processing, for example, the leaning-vehicle-driving-input data, the leaning-vehicle-behavior data, the leaning-vehicle-location data, and the leaning-vehicletraveling-environment data. The leaning-vehicle-traveiing data may include processed data obtained by processing, for example, the leaning-vehicle-driving-input data, the leaning-vehicle-behavior data, the leaning-vehicle-location data, and the leaning-vehicletraveling-environment data with other data.

[0090] [Leaning-Vehicle-Driving-Input Data]

The leaning-vehicle-driving-input data herein is data related to an operation input of a driver that is performed when the driver drives a leaning vehicle. Specifically, the leaning-vehicle-driving-input data may include data related to, for example, an accelerator operation, a brake operation, steering, or a positional change of the center of gravity caused by a change in posture of the driver. Specifically, the leaning-vehicledriving-input data may include data related to, for example, operations of various switches such as a hom switch, a winker switch, and a lighting switch. The leaningvehicle-driving-input data is data related to a driving input by the driver, and thus, more strongly reflects a resuit of détermination by the driver. In the leaning vehicle, there are a large number of types of operation by the driver and flexibility in options by the driver during driving is high. Thus, personality of the driver tends to be strongly reflected. The leaning-vehicle-driving-input data may include processed data obtained by processing data acquired from, for example, a sensor. The leaning-vehicle-driving-input data may include processed data obtained by processing data acquired from, for exampîe, the sensor with other data.

[0091] [Leaning-Vehicle-Behavior Data]

The ïeaning-vehicle-behavior data herein is data related to a behavior of a leaning vehicle caused by a driving input by a driver while the îeaning vehicle is driven by the driver. Specifically, the ïeaning-vehicle-behavior data includes, for example, an accélération, a velocity, and an angle that vary when the driver as an analysis target drives the leaning vehicle. That is, the ïeaning-vehicle-behavior data is data showing a behavior of the leaning vehicle occurring, for example, in a case where the driver as an analysis target performs an accelerator operation or a brake operation to accelerate or decelerate the leaning vehicle, or in a case where steering of the leaning vehicle or a posture change including a positional change of the center of gravity is performed.

[0092] As described above, the ieaning-vehicie-bêhavior data may include not only the data concerning an accélération, a velocity, and an angle of the leaning vehicle but also an operation occurring in the leaning vehicle due to, for example, a switch operation performed on the leaning vehicle by the driver, That is, the Ïeaning-vehicle-behavior data includes data related to operations occurring in the leaning vehicle due to operations of various switches such as a horn switch, a winker switch, and a lighting switch. The ïeaning-vehicle-behavior data strongly reftects a resuit of a driving input by the driver. Thus, the ïeaning-vehicle-behavior data also tends to strongly reflect personality of the driver. The ïeaning-vehicle-behavior data may include processed data obtained by processing data acquired from, for example, a sensor. The ïeaning-vehicle-behavior data may include processed data obtained by processing data acquired from, for exemple, the sensor with other data.

[0093] [Leaning-Vehicle-Location Data]

The leaning-vehicle-location data herein is data related to a traveling location of a leaning vehicle. For example, the leaning-vehicle-location data can be detected based on information from a GPS, or a communication base station of a communication portable terminal. The leaning-vehicle-location data can be calculated by various positioning techniques, a SLAM, or the like. The leaning-vehicle-location data strongly reflects a resuit of a driving input of a driver in which personality of the driver is strongly reflected. Thus, the leaning-vehicle-location data also tends to strongly reflect personality of the driver. The leaning-vehicle-location data may include processed data obtained by Processing data acquired from, for example, a sensor. The leaning-vehicle-location data may include processed data obtained by processing data acquired from, for example, the sensor with other data.

[0094] [Leaning-Vehicle-Traveling-Environment Data]

The leaning-vehicle-traveiing-environment data herein includes map data, for example. The map data may be associated with, for example, information on road situations, information on road trafnc environments such as signais and faciiities, and régulation information on traveling on roads. The map data may be associated with environmental data such as weather, température, and humidity. The leaning-vehicletraveling-environment data can be used for analyzing personality such as a character of an analysis target, together with the leaning-vehicle-driving-input data, the ieaningvehicle-behavior data, and the leaning-vehicle-location data.

[0095] The information on road situations includes information on roads (areas) under crowded conditions, such as a condition in which traffic congestion frequently occurs and a condition in which many vehicles are parked on streets. Précision of the information increases when being combined with time frames. The information on road situations includes information on roads that easiiy flood upon squaüs.

[0096] The leaningwehicleHravelingrenvironment data is considered to be an exemple of stress on the driver from the outside. The leaning-vehicie-traveling-environment data affects détermination of the driver. The leaning-vehicle-traveling-environment data affects driving of the driver. Thus, the use of the leaning-vehicie-traveling-environment data causes personality of the driver to more strongly appear in traveling data of the leaning vehicle. The use of the leaning-vehicle-traveling-environment data affects the purpose of use and frequency of use of the leaning vehicle, and thus, personality of the driver tends to strongly appear in traveling data ofthe leaning vehicle.

[0097] The leaning-vehicle-traveling-environment data can be acquired by various configurations. The configuration for acquiring the leaning-vehicle-traveling-environment data is not limited to a spécifie configuration. For example, the configuration for acquiring the leaning-vehicleTraveling-environmeni data is an extemal-environmentrecognition device mounted on the leaning vehicle. More specifically, the configuration for acquiring the leaning-vehicle-traveling-environment data is, for example, a caméra or a radar. Altematively, the configuration for acquiring the leaning-vehicle-travelingenvironment data is a communication device. More specifically, the configuration for acquiring the leaning-vehicle-traveling-environment data is a vehicle-to-vehicle communication device or a road-to-vehicte communication device. The leaning-vehicletraveling-environmenî data can also be obtained through the Internet, forexampie.

[0098] [Public Road]

A public road herein is not a roadway in a simulation and a circuit, but a road for public on which general vehicles can travel. The public road includes a private road on which general vehicles can travel,

[0099] [Including Larger Amount of B Than A]

The expression “including a larger amount of B than A herein may include a case where no A is included. The expression “including a larger amount of B than A” may include a case where A is partialîy included.

[0100] For example, the expression “including a larger amount of data reflecting a change in driving of a leaning vehicle for data conversion (data-conversion-leaning vehicle) by a driver than data not reflecting a change in driving of the data-conversionleaning vehicle by the driver may include a case where data not reflecting a change in driving of the data-conversion-leaning vehicle by the driver is not included at ail. For example, the expression “including a larger amount of data reflecting a change in driving of a data-conversion-leaning vehicle by a driver than data not reflecting a change in driving of the data-conversion-leaning vehicle by the driver” may include a case where data not reflecting a change in driving of the data-conversion-leaning vehicle by the driver is partialîy included.

[0101] For example, the expression “a larger amount of data reflecting a change in driving of a leaning vehicle for analysis (analysis leaning vehicle) by an analysis target than data not reflecting a change in driving of the analysis leaning vehicle by the analysis target may include a case where data not reflecting a change in driving of the analysis leaning vehicle by the analysis target is not included at ail. For example, the expression “a larger amount of data reflecting a change in driving of an analysis leaning vehicle by an analysis target than data not reflecting a change in driving of the analysis leaning vehicle by the analysis target” may include a case where data not reflecting a change in driving of the analysis leaning vehicle by thê analysis targei is partis liy included.

[0102] For exampîe, the expression “including a larger amount of data in traveling of a data-conversion-leaning vehicle on a public road than data in traveling of the dataconversion-leaning vehicle on a place except for a public road” may include a case where data in traveling of the data-conversion-leaning vehicle on a place except for a public road is not included at ail. For example, the expression inciuding a larger amount of data in traveling of a data-conversion-leaning vehicle on a public road than data in traveling ofthe daia-conversion-leaning vehicle on a place except for a public road” may include a case where data in traveling of the data-conversion-leaning vehicle on a place except for a public road is padiaiiy included.

[0103] For example, the expression “including a larger amount of data in traveling of an analysis leaning vehicle on a public road than data in traveling of the analysis leaning vehicle on a place except for a public road may include a case where data in traveling of the analysis leaning vehicle on a place except for a public road is not included at ail. For example, the expression including a larger amount of data in traveling of an analysis leaning vehicle on a public road than data in traveling of the analysis leaning vehicle on a place excepi for a public road” may include a case where data in traveling of the analysis leaning vehicle on a place except for a public road is partîally included.

ADVANTAGEOUS EFFECTS OF INVENTION

[0104] According to one embodiment of the présent teaching, it is possible to provide a personaiity analyzing method capable of acquiring personaiity data with enhanced design flexibility of hardware resources.

BRIEF DESCRIPTION OF DRAWINGS

[0105] [FIG. 1] FIG. 1 is a view illustrating a schematic configuration of a personaiity analyzing device according to a first embodiment of the présent teaching.

[FIG. 2] FIG. 2 is a flowchart depicting an exemple of an operation of a ncire'Drt'⁵1 ifw O rt<5 hf7irJûV’Oû UC7r oui rcaHiy ctc icijr£ii ry

[FIG. 3] FIG. 3 is a view illustrating a schematic configuration of a personaiity analyzing system according to a second embodiment

[FIG. 4] FIG. 4 is a flowchart depicting an example of an operation of a data processing device.

DESCRIPTION OF EMBODIMENT

[0106] Embodiments will be described hereinafter with reference to the drawings. The dimensions of components in the drawings do not strictly represent actual dimensions ofthe components and dimensional proportions ofthe components.

[0107] <First Embodiment>

(Personaiity Analyzing Device)

FIG. 1 illustrâtes a schematic configuration of a personaiity analyzing device 1 according to an embodiment of the présent teaching. The personaiity analyzing device 1 is a device for analyzing personaiity of an analysis target. The personaiity analyzing device 1 according to this embodiment anaiyzes personaiity of an analysis target by using leanîng-vehicle-traveling data (analysis-leaning-vehicle-traveling data) of a leaning vehicle X (analysis leaning vehicle) obtained when the analysis target drives the leaning vehicieX, and outputs a resuîtofthe analysis.

[0108] The personaiity analysis in this embodiment refers to analysis of individuality determined based on, for example, psychological State, character, or tempérament of an analysis target. The personaiity is included in converted personaiity data obtained by converting leaning-vehicle-traveling data of the leaning vehicle X obtained when the analysis target dnves the leaning vehicle X as a driver, with a personality data converter 30 described later. That is, the converted personality data includes data related to personality of the analysis target.

[0109] The leaning-vehicie-traveling data in this embodiment is data related to traveling of a leaning vehicle. The leaning-vehide-traveling data refers to data in which personality of the driver appears in data related to traveling of the leaning vehicle obtained when the driver drives the leaning vehicle.

[0110] Specifically, the leaning-vehicie-traveling data includes, for example, leaningvehicle-driving-input data related to a driving input to a leaning vehicle by a driver, leaning-vehicle-behavior data related to a behavior of the leaning vehicle, leaningvehicle-location data related to a traveling location of the leaning vehicle, and a leaningvehicle-iraveling-environmeni data related to a traveling environment of traveling of the leaning vehicle. The leaning-vehicie-traveling data may include data other than the leaning-vehicle-driving-input data, the leaning vehicle behavior data, the leaning-vehicle» location data, and the leaning-vehicle-traveling-environment data. The leaning-vehicietraveling data may only include one or more of the leaning-vehicle-drivîng-input data, the leaning-vehicle-behavior data, the leaning-vehicle-locatîon data, or the leaning-vehicletraveling-environment data.

[0111] For example, in a case where the leaning vehicle is the leaning vehicle X that is an analysis leaning vehicle, the leaning-vehicie-traveling data is leaning-vehicie-traveling data for analysis (analysis-ieaning-vehicle-traveling data), the leaning-vehicie-drivinginput data is leaning-vehicle-driving-input data for analysis (analysis-ieaning-vehicledriving-input data), the leaning-vehicle-behavior data is leaning-vehicle-behavior data for analysis (analysis-ieaning-vehicle-behavior data), the leaning-vehicle-location data is leaning-vehicie-location data for analysis (analysis-leaning-vehicle-location data), and the leaning-vehicle-traveling-environment data is leaning-vehicle-traveling-environment data for analysis (anaiysis-leaning-vehicle-traveling-environment data).

[0112] For example, in a case where the leaning vehicle is a leaning vehicle that îs a data-conversion-leaning vehicle, the leaning-vehicie-traveling data is leaning-vehicietraveling data for data conversion (data-conversion-leaning-vehicle-traveling data), the leaning-vehicle-driving-input data is leaning-vehicie-driving-input data for data conversion (data-conversion-leaning-vehicle-driving-input data), the leaning-vehicle-behavior data is leaning-vehicie-behavior data for data conversion (data-conversion-leaning-vehiclebehavior data), the leaning-vehicle-location data is leaning-vehicle-location data for data conversion (data-conversion-leaning-vehicle-location data), and the leaning-vehicletraveling-environment data is ieaning-vehicle-traveiing-envirQnment data for data

I conversion (data-conversion-leaning-vehicie-traveling-environment data).

[0113] The leaning-vehicle-traveling data may inciude processed data obtained by processing, for example, the ieaning-vehicie-driving-input data, the leaning-vehiclebehavior data, the leaning-vehicle-location data, and the leaning-vehicle-traveling5 environment data. The leaning-vehicle-traveling data may include processed data obtained by processing the leaning-vehicle-driving-input data, the leaning-vehiclebehavior data, the leaning-vehide-location data, and the leaning-vehicie-travelingenvironment data with other data.

[0114] The leaning-vehide-driving-input data is data related to an operation input of a 10 driver that is performed when the driver drives a leaning vehicle, Specificalfy, the leaning-vehicle-driving-input data may include data related to, for example, an acceferator operation, a brake operation, steering, or à positional change of the center of gravity caused by a change in posture of the driver, Specifically, the leaning-vehide-drivinginput data may include data related to, for example, operations of various switches such 15 as a horn switch, a winker switch, and a lighting switch. The leaning-vehicle-drivinginput data is data related to a driving input by the driver, and thus, more strongly refîects a resuit of détermination by the driver, in the leaning vehicle, there are a large number of types of operation by the driver and flexibility in options by the driver during driving is high. Thus, personality of the driver tends to be strongly reflected, The leaning20 vehicle-driving-input data may include processed data obtained by processing data acquired from, for example, a sensor. The leaning-vehicle-driving-input data may include processed data obtained by processing data acquired from, for example, the sensor with other data,

[0115] The leaning-vehicle-behavior data is data related to a behavior of a leaning 25 vehicle caused by an operation input by a driver whüe the leaning vehicle is driven by the driver. Specifically, the leaning-vehicle-behavior data includes, for example, an accélération, a velocîty, and an angle that vary when the driver drives the leaning vehicle. That is, the leaning-vehicle-behavior data is data showing a behavior of the leaning vehicle occurring, for example, in a case where the driver performs an accelerator 30 operation or a brake operation to accelerate or decelerate the leaning vehicle, or in a case where steering of the leaning vehicle or a posture change including a positional change of the center of gravity is performed.

[0116] The leaning-vehicle-behavior data may include not only the data conceming an accélération, a velocîty, and an angle of the leaning vehicle, as described above, but 35 also an operation occurring in the leaning vehicle due to, for example, a switch operation performed on the leaning vehicle by the driver. That is. the leaning-vehicle-behavior data includes data related to operations occurring in the leaning vehicle due to operations of various switches such as a hom switch, a winker switch, and a lighting switch. The iêaning-vehicle-behavior data strongly refleds a resuit of a driving input by the driver. Th u s, the leaning-vehicle-behavior data also tends to strongly refie et personality of the 5 driver. The leaning-vehicle-behavior data may include processed data obtained by processing data acquired from, for example, a sensor. The leaning-vehicle-behavior data may include processed data obtained by processing data acquired from, for example, the sensor with other data.

[0117] The leaning-vehicle-location data is data related to a traveling location of a 10 leaning vehicie. For example, the leaning-vehicle-location data can be detected based on, for example, information from a GPS, or a communication base station of a communication portable terminai. The leaning-vehicle-location data can be calcuiated by various positioning techniques, a SLAM, or the like. The leaning-vehicle-location data strongly reflects a resuit of a driving input of a driver in which personality of the 15 driver is strongly reflected. Thus, the leaning-vehicle-location data also tends to strongly reflect personality of the driver. The leaning-vehicle-location data may include processed data obtained by processing data acquired from, for example, a sensor. The leaning-vehicle-location data may include processed data obtained by processing data acquired from, for example, the sensor with other data.

[0118] The ieaning-vehicle-traveling-environment data includes map data, for example.

The map data may be associated with, for example, information on road situations, information on road traffic environments such as signais and facilities, and régulation information on traveling on roads. The map data may be associated with environmental data such as weather, température, and humidity. The leaning-vehicle-traveling25 environment data can be used for analyzing personality such as a character of an analysis target, together with the leaning-vehicle-driving-input data, the leaning-vehiclebehavior data, and the leaning-vehicle-location data.

[0119] The information on road situations includes information on roads (régions) under crowded conditions, such as a condition in which traffic congestion frequentiy 30 occurs and a condition in which many vehicles are parked on streeis. Précision of this information increases when being combined with time frames. The information on road situations includes information on roads that easiïy fîood upon squalls.

[0120] The leaning-vehicle-traveling-environment data is considered to be an exampie of stress on the driver from the outside. The leaning-vehide-traveling-environment data 35 affects détermination of the driver. The leaning-vehicle-traveling-environment data affects driving of the driver. Thus, the use of the lean ing-vehicle-traveiing-environ ment

I data causes personality of the driver to more strongly appear in traveiing data of the leaning vehicie, The use of the leaning-vehicle-traveling-environment data affects the purpose of use and frequency of use of the leaning vehicie, and thus, personality of the driver tends to strongly appear in traveiing data ofthe leaning vehicie.

[0121] The personality analyzing device 1 includes a personality-conversion-data acquirer 10, an analysis-leaning-vehicle-traveling-data acquirer 20, the personality data converter30, a personality-data-to-be-output generator 40. a data, output section 50, and a data memory 60. In this embodiment, the personality analyzing device 1 is, for example, a portable terminal heid by an analysis target. The personality analyzing device 1 may be an arithmetic processing unit that acquires data through communication and performs a computation process.

[0122] The analysis-leaning-vêhicie-traveiing-data acquirer 20 acquires leaningvehicle-traveling data (analysis-leaning-vehicle-traveling data) when a driver as an analysis target drives the leaning vehicie X.

[0123] The analysis-leaning-vehicle-traveling-data acquirer 20 acquires data included in leaning-vehicle-traveling data of the leaning vehicie X when the analysis target drives the leaning vehicie X, that is, anaiysis-leaning-vehicle-driving-input data, analysis-leaningvehicle-behavior data, analysis-leaning-vehicle-location data, analysis-leaning-vehicletraveling-environment data, and so forth.

[0124] The analysis-leaning-vehicle-traveling-data acquirer 20 may acquire, for example, driving of the leaning vehicie X by the analysis target as an operation signal to thereby acquire the analysis-leaning-vehicle-driving-input data. Specifically, the anaÎysis-leaning-vehicle-trâveiing-data acquirer 20 may acquire data related to a driving input by the driver in the leaning vehicie X, that is, data related to, for example, an accelerator operation, a brake operation, steering, or a positional change of the center cf gravity caused by a change in posture of the driver, and data related to, for example, operations of various switches such as a hom switch, a winker switch, and a lighting switch. These sets of data are transmitted from the leaning vehicie X,

[0125] The analysis-leaning-vehicle-traveling-data acquirer 20 may acquire, for example, data including an accélération, a velocity, and an angle ofthe leaning vehicie X that change when the driver as an analysis target drives the leaning vehicie X as analysis-leaning-vehicle-behavior data. The analysis-leaning-vehicle-traveling-data acquirer 20 acquires the analysis-leaning-vehicle-behavior data by, for exampie, a gyro sensor. The analysis-leaning-vehicle-behavior data is data showing a behavior of ths leaning vehicie X occurring in a case where tire driver as an analysis target performs an accelerator operation or a brake operation to accelerate or deçelerate the leaning vehicie

X or in a case where steering of the leaning vehicle X or a posture change including a positionai change of the center of gravity is performed, for example.

[0126] The analysis-leaning-vehicie-traveling-data acquirer 20 may acquire an operation occurring in the leaning vehicle X by, for example, a switch operation performed by the driver as an analysis target on the leaning vehicle X, as the ieaningvehicle-behavior data, That is, the analysis-leaning-vehicle-traveling-data acquirer 20 may acquire data related to an operation occurring in the leaning vehicle X by, for example, operations of various switches such as a hom switch, a winker switch, and a iighting switch, as the analysis-leaning-vehicle-behavior data. These sets of data are transmitted from the leaning vehicle X to the personality analyzing device 1.

[0127] The analysis-leaning-vehicle-traveling-data acquirer 20 may acquire analysisleaning-vehicle-location data related to a traveling location of the leaning vehicle X, based on information from a GPS or a communication base station of a communication portable terminal, for example. The ana!ysis4eaning=vehîcle=location data can be calculated by various positioning techniques, a SLAM, or the like.

[0128] The analysis-leaning-vehicle-iraveling-data acquirer 20 may acquire the analysis-leaning-vehicle-traveling-environment data from, for example, map data. The map data may be associated with, for example, information on road situations, information on road traffic environments such as signais and facilities, and régulation information on traveling on road s. The map data may be associated with environmental data such as weather, température, and humidity. The map data may include information in which road information and information on road traffic environments (accompanying information to a road such as a signal) are associated with rule information on traveling on a road.

[0129] The analysis-leaning-vehicle-traveling-dats acquirer 20 may acquire the analysis-leaning-vehicle-traveling-environment data by, for example, an externalenvironment-recognition device mounted on the leaning vehicle X. More specifically, the anaiysis-leaning-vehicle-traveling-data acquirer 20 may acquire the analysis-leaningvehicle-traveling-environment data from a caméra or a radar, for example. The analysisleaning-vehicle-traveîing-data acquirer 20 may also acquire the analysis-leaning-vehicletraveling-environment data by, for example, a communication device. More specifically, the analysis-leaning-vehicie-traveling-data acquirer 20 may acquire the anaiysis-leaningvehicle-traveling-environment data by a vehicle-to-vehicle communication device or a road-to-vehic!e communication device. The analysis-leaning-vehicle-traveling-data acquirer 20 may acquire the analysis-leaning-vehicle-traveling-environment data through, for example, the Internet. As described above, the anaiysis-leaning-vehicle-traveling environment data can be acquired by various configurations. The configuration for acquiring the analysis-leaning-vehicle-traveling-environment data is not limited to a spécifie configuration.

[0130] The personality-conversion-data acquirer 10 acquires personality conversion data for converting leaning-vehicle-traveling data of the analysis target described above to personality data.

[0131] The personality conversion data are data in which leaning-vehicle-traveling data obtained when a plurality of drivers drives Ieaning vehicles are associated with personality data of these drivers. That is, the personality conversion data is data in which leaning-vehicle-traveling data and personality data are associated with each other in order to obtain, from the leaning-vehicle-traveling data, personality data suitable for the leaning-vehicle-traveling data.

[0132] The personality conversion data are generated based on data-conversionleaning-vehicls-traveling data obtained when a plurality of drivers drives Ieaning vehicles (data-conversion-teaning vehicles) by using an idea based on, for example, characterization or typology used in personality analysis. In this embodiment, the dataconversion-teaning-vehicle-travelin g data is similar to the analysis-leaning-vehicleiraveiing data described above except that the data-conversion-teanîng-vehicle-traveling data is data for use in generating the personality conversion data. The data-conversionleaning-vehicte-traveling data may include a different type of data from the analysisleaning-vehicîe-traveling data described above.

[0133] In this embodiment, the personality conversion data is generated by using Big Five Theory that is a characterization of personality. în this Big Five Theory, various characters of people are expressed by using a combination of five éléments. The Big Five Theory is a theory having universality across a cultural différence and an ethnie différence.

[01341 Specifically, the personality conversion data is data combinîng five éléments of neuroticism, extroversion, openness to expérience, cooperativeness, and integrity in the Big Five Theory with leaning-vehicle-traveling data.

[0135] The neuroticism refers to intensifies of sensitivity, anxiety and tension to environmental stimuli and stressors . The neuroticism has relevance to the degree of variation in traveling among traveling environments of the Ieaning vehicië X, for exampie. A driver not showing a significant différence in traveling of the Ieaning vehicle X among different traveling environments of the Ieaning vehicle X has weak neuroticism, whereas a driver showing a significant différence in traveling of the Ieaning vehicle X among different traveling environments of the Ieaning vehicle X has strong neuroticism.

[0136] For exampie, in a case where a vehicle behavior of the Ieaning vehicle X does not significantîy change between a traveling location where traffic congestion frequently occurs and a traveling location where traffic congestion does not frequently occur, the driver is not significantly affected by environments, that is, the driver has weak neuroticism. On the other hand, in a case where the vehicle behavior of the Ieaning vehicle X significantly changes, the driver is affected by environments, that is, the driver has strong neuroticism.

[0137] That is, the degree of neuroticism of the driver can be determined based on a différence or a variation (e.g., standard déviation) in parameter of the vehicle behavior among different traveling environments by specifying traveling environments of the Ieaning vehicle X,

[0138] The traveling environment includes, for exampie, urban and rural (area),” general road and expressway (road type),” “day and night (time),” “sunny and rainy (weather),” “dry and wet (road surface). The traveling environments are specîfied by using traveling location data, time data, weather data, road surface détection data, and so forth.

[0139] The neuroticism can be obtained by using, for example, leaning-vehicle-drivinginput data, Ieaning-vehicie-traveling-environment data, leaning-vehicle-location data, and leaning-vehicle-behavior data of the Ieaning vehicle X among the leaning-vehicletraveling data.

[0140] The extroversion refers to diplomacy, activeness, and aggressiveness. The extroversion has relevance to a traveling distance of the Ieaning vehicle X in a given period, for example. For exemple, it is determined that as the traveling distance of the Ieaning vehicle X increases, extroversion of a driver increases, whereas as the traveling distance of the Ieaning vehicle X decreases, extroversion of the driver decreases. Thus, the extroversion can be obtained by using leaning-vehicle-location data of the Ieaning vehicle X in the leaning-vehicle-traveling data.

[0141] The openness to expérience refers to strength of intellectuel curiosity, imagination, and affinity for novelty. The openness to expérience has relevance to the number of new points visited by the Ieaning vehicle X in a given period, for example. For example, as the number of new points visited by the Ieaning vehicle X in the given period increases, openness to expérience of the driver is determined to be larger, whereas the number of new points visited decreases, openness to expérience of the driver is determined to be lower. Points to be visited may be classified depending on the type so that the more times a point of a new type is visited by the Ieaning vehicle X in a given period, the more the driver is determined to be open to expérience. Even if the ΐ

number of new points visited by the leaning vehicle X in the given period is the same, it may be determined that the more types of points the leaning vehicle X visits, the more the driver is open to expérience.

[0142] The openness to expérience can be obtained by using leaning-vehicle-location data and leaning-vehicle-traveling-environment data including map data of the leaning vehicle X in the leaning-vehicle-travelîng data.

[0143] The cooperativeness refers to altruism, empathy, kindness, and so forth. The cooperativeness has relevance to the degree of cooperativeness with surroundings in a dense state, for exampîe. Thus, the cooperativeness can be obtained by using, for example, leaning-vehicle-location data in the leaning-vehicle-traveling data.

[0144] In particular, the cooperativeness has stronger relevance to the degree of déviation from an average behavior in a group in a dense state. Thus, the cooperativeness can be more precisely obtained by also using traveling location data of other leaning vehicles in the group in the dense state.

[0145] In a case where the leaning vehicle X is in a dense state with other leaning vehicles, not only leaning-vehicle-location data related to the traveling location of the leaning vehicle X but aîso leaning-vehicie-iocation data related to traveling locations of the other leaning vehicles in the dense state may be obtained to calculate the degree of déviation of the traveling location of the leaning vehicle X in the leaning vehicîe group in the dense state. In the case of calculating the degree of déviation of the traveling location of the leaning vehicle X as described above, cooperativeness of the driver is determined to be lower as the degree of déviation of the traveling location increases, whereas cooperativeness of the driver is determined to be higher as the degree of déviation decreases.

[0146] The integrity refers to self-controî, wiîl to achieve, earnestness, and strong sense of responsibility. The integrity has relevance to, for example, the degree of compliance with traffic rules and a smali variation in traveling of the leaning vehicle X. The degree of compliance with traffic rules is determined based on régulation information in accordance with the traveling location stored in map data and a behavior of the leaning vehicle X. Traveling without compliance with traffic rules inciudes a case where the vehicle traveîs at 60 km/h on a road where the velocity is restricted to 40 km/h, and a case where the vehicîe does not temporanly stop at a point where the vehicle is obliged to stop temporanly, for example.

[0147] As the frequency of traveling without compliance with traveling rules as described above increases, integrity of the driver is determined to be lower, whereas the frequency of traveling without compliance with traveling rules decreases, integrity of the < / driver is determined to be higher.

[0148] In the case of a variation in traveling as described above, traveling environments of the leaning vehicle X is classified and specified, and integrity of the driver is determined based on the différence or a variation (e.g., standard déviation) in parameter of a vehicle behavior of the leaning vehicle X in the traveling environments. A rider with high integrity has a high self-control and is se nous, and thus, is consi dered to drive in compliance with law and perform no sudden behavior.

[0149] The integrity can be obtained by using leaning-vehicle-location data, ieaningvehicle-traveiing-environment data including map data, and leaning-vehicle-behavior data, of the leaning vehicle X, in the leaning-vehicle-traveling data, for example.

[0150] The personality conversion data may be generated by using, for example, Cioninger's seven-dimensionai model of tempérament and character (Kijima et al. Quarteriy Psychiatrie Diagnosis (Nihon Hyoronsha), Vol. 7, No. 3, reprint, pp. 379-399), Driver behavior and character data (Taketoshi Takuma, IATSS review Vol. 2 No. 3, September 1976, pp. 183-190), Evaluation index of individual driver characteristics (Ishibashi et al, Mazda Technical Report, No, 22 (2004), pp, 155-180), and so forth. The “Cioninger's seven-dimensionai model of tempérament and character” is described in, for example, a site (https://www.institute-of-mental-health.jp/thesis/pdf/thesis06/thesis-06-04.pdf) of a mental health related research instîtute.

[0151] For example, in the Cioninger's seven-dimensionai model of tempérament and character, tempérament is expressed based on novelty desire, reward dependence, damage avoidance, and persistence, and character is expressed based on selforientation, coopérât!veness, and self-transcendence. în Driver behavior and character data, character is classified into six types: dereism, conformity, stickiness, demonstrativeness, hypersensitivity, and overconfidence. In Evaluation index of individual driver characteristics, a driving style is expressed based on confidence in driving skills, réluctance to driving, impatient driving tendency, careful driving tendency, preparatory driving to traffic lights, vehicle as status symbol, driving in unstable psychological State, and anxious tendency.

[0152] The personality conversion data may be data previously generated and stored in the data memory 60 or data generated by the personality-conversjon-data acquirer 10. The personality-conversion-data acquirer 10 may update the personality conversion data by using acquired leaning-vehicle-traveling data and personality.

[0153] The personality data converter 30 couverts analysis-leaningwehicle-traveling data acquired by the analysis-leaning-vehicle-traveîing-data acquirer 20 to converted personality data by using the personality conversion data described above. At this time, the personaîity data converter 30 ranks a driver as an analysis target with respect to the five éléments of neuroticism, extroversion, openness to expérience, coopérât! veness, and integrity described above. This ranking with each of these éléments described above may be expressed by using continuous values or a plurality of stages divided by thresholds. The personaîity data converter 30 may classify the driver into a plurality of types by using results of the ranking with each of the éléments described above, and use results ofthe classification as converted personaîity data,

[0154] The personality-data-to-be-output generator 40 generates personaîity data to be output, by using converted personaîity data converted by the personaîity data converter 30. The personaîity data to be output is data to be output from the personaîity analyzing device 1. The personaîity data to be output may be the same as the converted personaîity data, or data converted to data required as output data of the personaîity analyzing device 1 by using the converted personaîity data.

[0155] The personality-data-to-be=output generator 40 may perform data processing on the converted personaîity data to generate personaîity data to be output. For example, the personality-data-to-be-output generator 40 may generate personaîity data to be output by storing the converted personaîity data in the data memory 60 and using converted personaîity data extracted from the converted personaîity data stored in the data memory 60. Specifically, for exampîe, the personality-data-to-be-output generator 40 may generate personaîity data to be output from converted personaîity data in a given period stored in the data memory 60.

[0156] The data output section 50 outputs personaîity data to be output generated by the personality-data-to-be-output generator 40 to the ouîside of the personaîity anaiyzing device 1.

[0157] With the foregoîng configuration, the personaîity analyzing device 1 can analyze personaîity of an analysis target by using îeaning-vehicle-traveîing data of the leaning vehicle X driven by the analysis target. and output a resuît of the analysis as personaîity data to be output.

[0158] (Personaîity Analyzing Method)

Next, with reference to FIG. 2, a personaîity analyzing method conducted by the personaîity analyzing device 1 having the foregoîng configuration wil! be described. FIG. 2 is a flowchart depicting an exampîe cf operation of the personaîity anaiyzing device 1, that is, an exampîe of the personaîity analyzing method.

[0159] First, the analysis-leaning-vehicle-traveling-data acquirer 20 acquires analysis» leaning-vehicle-traveling data of a îeaning vehicie X (step SA1). The anaiysis-leaningvehicle-traveling data includes. for exampîe, anaîysis-leaning-vehicie-driving-input data, analysis-leamng-vehicle-behavior data, analysis-teaning-vehide-location data, analysis’eaning-vehicle-traveling-envi’Onment data, or the like.

[0160] The analysis-ieaning-vehictertrav^^ data may indude data other than the analysis-îeaning-vehîde-dnvfng-input data, the analysfs-ieanîng-vehide-behavior data, the analysis-lean;ng vehide-iocat:on data, and the analysis-leaning-vehicle-travelingenvironment data, The analysisTeaning-vehtde-travelîng data may only include one or more of the analysis-leaning-vehfcfe-driving-input data, the analysis-leaning-vehidebehavior data, the analysis-leaning-vehide-location data, or frie analysis-leaning-vehicletraveling-environment data,

[0161] Next, the personality data converter 30 convertsthe acquired analysis-leaningvehide-traveling data of frie leaning vehicle X to converted personality data by using personality conversion data (step SA2). The personality conversion data are data in which leaning-vehide-traveiing data obtained when a plurality of drivers drives leaning vehicles are associated with personality data. In this embodiment, the personality conversion data are data generated based on data-œnversion-leaning-vehicle-traveling data obtained when a plurality of drivera drives leaning vehicles by using the Big Five Theory,

[0162] The perso nalfty-data-to-be-output généra for 40 generates personality data to be output by using the converted personality data after the conversion (step SA3).

[0163] The data output section 50 outputs the generated personality data (step SA4). Thereafter, this flow is finished (end).

[0164] With the foregoing configuration, personality data of an analysis target as a driver can be acquired not by a conventionai question-and-answer format but by using leaning-vehicle-traveiing data more strongly reftecting inhérent personality of the driver with small arbitrariness of the driver. As described above, the use of the leaning-vehicletraveiing data can reduce frie amount of data processed by the personality analyzing system, as compared to a personality analyzing method using a conventionai questionand-answer format that requires a considerably large number of questions to the analysis target.

[0165] That is, the use of traveling data of a leaning vehicle for personality analysis can reduce the number of types of data processed by the system and can reduce a load on hardware of the personality analyzing device 1. Since hardware resources necessary for the personality analyzing device 1 can be reduced, design flexibility of hardware resources of the personality analyzing device 1 can be enhanced,

[0166] As a resuit, personality data can be acquired with enhanced design flexibility of hardware resources,

[0167] This embodiment is an example of a personalîty anaiyzing method for anaiyzing personalîty of an analysis target. The personalîty anaiyzing method according to this embodiment includes the following steps.

[0168] In the personalîty anaiyzing method of this embodiment, personalîty conversion 5 data, in which personalîty data showing personalîty is associated with leaning-vehicletraveling data that is traveling data of a Ieaning vehicle, is acquired. The personalîty conversion data are generated based on data-conversion-leaning-vehicle-traveling data related to traveling data of Ieaning vehicles obtained when a plurality of drivers drives the Ieaning vehicles.

[0169] The data-conversion-leaning-vehicle-traveling data mean leaning-vehicletraveling data by a plurality of drivers. The Ieaning vehicle is a vehicle that leans rightward when tuming to the right and leans leftward when tuming to the ieft. The dataconversion-leaning vehicles mean Ieaning vehicles that are driven by a plurality of drivers and serve as targets of the data-conversiomleaning-vehicle-traveling data.

[0170] For example, the data-conversion-leaning-vehicle-traveling data may be acquired by various sensors mounted on the data-conversion-leaning vehicle. The dataconversion-leaning-vehicle-traveling data may be acquired by various sensors mounted on the data-conversion-leaning vehicle such that the sensors can be easily attached or detached. The data-conversion-leaning-vehide-traveîing data may be acquired by 20 various sensors temporarily mounted on the data-conversion-leaning vehicle in order to collect data.

[0171] In the personalîty anaiyzing method, analysis-leaning-vehicle-traveling data related to traveling data of the Ieaning vehicle X obtained when an analysis target drives the Ieaning vehicle X, is acquired.

[0172] The analysis-leaning-vehicle-traveling data means leaning-vehicle-traveling data of the Ieaning vehicle X driven by the analysis target. The analysis Ieaning vehicle means a Ieaning vehicle X which is driven by the analysis target and serves as a target from which analysis-leaning-vehicle-traveling data is acquired.

[0173] The analysis target may be included in the plurality of drivers. The analysis 30 target may not be included in the plurality of drivers. The analysis Ieaning vehicle may be included in the data-conversion-leaning vehicles. The analysis Ieaning vehicle may not be included in the data-conversion-leaning vehicles. The analysis-leaning-vehicletraveling data may be included in the data-conversion-leaning-vehicle-traveling data. The analysis-leaning-vehicle-traveling data may not be included in the data-conversion35 leaning-vehicle-traveling data.

[0174] For exampie. the analysis-feaning-vehicle-traveling data may be acquired by vanous sensors mounted on the analysis Ieaning vehicle. The analysis-feaning-vehicletraveling data may be acquired by various sensors mounted on the analysis Ieaning vehicle such that the sensors can be easily aiîached or detached. The analysts-leaningvehicle-traveling data may be acquired by various sensors temporarily mounted on the analysis Ieaning vehicle in order to colîect data.

[0175] The various sensors for collecting the analysis-leaning-vehicle-traveling data may hâve lower détection acwraoy than various sensors for collecting the dataconversion-leaning-vehicle-traveling data.

[0176] The various sensors for collecting the analysis-leaning-vehicle-traveling data may be the same as the various sensors for collecting the data-conversion-leaningvehicle-traveling data.

[0177] The number of types of data included in the analysis-leaning-vehicle-traveling data may be smailer than the number of types of data included in the data-conversionleaning-vehicle-traveling data. The types of data included in the analysis-leaningvehicle-traveling data may be the same as the types of data included in the dataconversion-leaning-vehicle-traveling data.

[0178] The personaiity analyzing device 1 converts the acquired analysis-leaningvehicle-traveling data to converted personaiity data related to personaiity of the analysis target by using the acquired personaiity conversion data.

[0179] The personaiity analyzing device 1 generates personaiity data to be output for output by using the converted personaiity data after conversion.

[0180] The personaiity analyzing device 1 outputs the generated personaiity data to be output.

[0181] In another aspect, the personaiity analyzing method preferably includes the following configuration. The data-conversion-leaning-vehicle-traveling data includes a larger amount of data refleciing a change in driving of the data-conversion-leaning vehicle by a driver than data not reflecting a change in driving of the data-çonversion-leaning vehicle by the driver. The analysis-leaning-vehicle-traveling data includes a larger amount of data reflecting a change in driving of the analysis Ieaning vehicle by an analysis target than data not reflecting a change in driving ofthe analysis Ieaning vehicle by the analysis target.

[0182] A driver of a ieaning vehicle recognizes a situation and drives the Ieaning vehicle with détermination. At this time, there is a case where the driver changes driving and a case where the driver does not change driving before and after the détermination. In a Ieaning vehicle, driving has a large variation, and the driver has a large number of options in détermination, Thus, a scene where the driver changes driving has a

J considerably large number of variations. In view of this, when attention is given on the scene where the driver of the leaning vehicle changes driving, inhérent personality of the driver with small arbitrariness more greatly appears in leaning-vehicle-traveling data including a large amount of data reflecting a change in driving of the leaning vehicle by the driver,

[0183] A method for dividing leaning-vehicle-traveling data into data not reflecting a change in driving of a leaning vehicle by a driver and data reflecting a change in driving of the leaning vehicle by the driver includes the following methods,

[0184] For example, the leaning-vehicle-traveling data can be divided by directiy observing a change in driving ofthe leaning vehicle by the driver.

[0185] For example, the leaning-vehicle-traveling data can be divided by directiy observing a behavior of the leaning vehicle in which a resuit of change in driving of the leaning vehicle by the driver appears.

[0186] For example, the leaning-vehicle-traveling data can be divided by observing a position of the leaning vehicle in which a resuit of change in driving of the leaning vehicle by the driver appears,

[0187] For example, the leaning-vehicle-traveling data can be divided by observing a location of the leaning vehicle showing that the leaning vehicle travels in a place where the driver frequentiy changes driving of the leaning vehicle.

[0188] Specifically, the leaning-vehicle-traveling data can be divided by using location data ofthe leaning vehicle and traveting environment data (e.g., map data) ofthe leaning vehicle. More specifically, the leaning-vehicle-traveling data may be divided into rural traveling data and urban traveling data. The rural traveling data may be defined as data not reflecting a change in driving of frie leaning vehicle by the driver, and the urban traveling data may be used as data reflecting a change in driving of the leaning vehicle by the driver.

[0189] In another aspect, the personality analyzing method preferably includes the following configurations. The data-conversion-leaning-vehicle-traveling data includes at least one of data-conversion-leaning-vehicle-driving-input data related to a driving input to the data-conversion-leaning vehicle by the driver, data-conversion-leaning-vehiclebehavior data related to a behavior of the data-conversion-leaning vehicle, or dataconversion-ieaning-vehicie-focation data related to a location of the data-conversionleaning vehicle. The analysis-leaning-vehicle-traveling data includes at least one of anafysisHeaning-vehicle-driving-input data related to a driving input to the analysis leaning vehicle by an analysis target, analysis-leaning-vehicle-behavior data related to a behavior of the analysis leaning vehicle. or anaiysis-leaning-vehicle-location data related to a location of the analysis leaning vehicle,

[0190] The leaning-vehicle-driving-rnput data is data related to a driving input by the driver, and thus, more strongly refiects a resuît of détermination by the driver. In the leaning vehicle, there are a large number of types of operation by the driver and flexibility in options by the driver during driving is high. Thus, personaiity of the driver tends to be strongly reflected,

[0191] The leaning-vehicie-behavior data strongly refiects a resuit of a driving input by the driver in which personaiity of the driver is strongly reflected. Thus, leaning-vehiciebehavior data also tends to strongly refiect personaiity ofthe driver.

[0192] The leaning-vehicie-iocation data strongly refiects a resuit of a driving input by the driver in which personaiity of the driver is strongly reflected. Thus, the leaningvehicie-iocation data aïso tends to strongly refiect personaiity of the driver.

[0193] Accordingly, leanîng-vehicle-traveling data for use in conversion to personaiity data related to personaiity of an analysis target includes data strongly reflecting personaiity of the analysis target as a driver.

[0194] In another aspect, the personaiity analyzing method preferably includes the following configurations. The data-conversion-leaning-vehicle-traveling data further includes data-conversion-leaning-vehicie-traveting-environment data related to traveiing environments in which the data-conversion-leaning vehicle travels. The analysisleaning-vehicle-traveling data further includes analysis-ieaning-vehicle-traveiingenvironment data related to traveling environments in which the analysis leaning vehicle travels.

[0195] The traveiing environment data is considered to be an exampîe of stress on a driver from the outside. The traveiing environment data affects détermination of the driver. The traveiing environment data affects driving of the driver. Thus, the use of the traveling environment data causes personaiity of the driver to more strongly appear in traveling data of the leaning vehicle. The use of the traveiing environment data affects the purpose of use and frequency of use of the leaning vehicle, and thus, personaiity of the driver tends to strongly appear in traveling data of the leaning vehicle.

[0196] Accordingly, leaning-vehicle-traveling data for use in conversion to personaiity data related to personaiity of the analysis target includes data strongly reflecting personaiity of the analysis target as the driver,

[0197] The leaning-vehicle-traveiing-environment data includes map data, for example. The map data may be associated with, for exemple, information on road situations, information on road traffic environments such as signais and faciiities, and régulation information on traveling on roads, The leaning-vehicîe-traveling-environment data can be used for analyzing personality such as a character of an analysis target, together with the îeaning-vehicle-driving-input data, the îeaning-vehicle-behavior data, and the leaningvehicle-location data.

[0198] In another aspect, the personality analyzing method preferably includes the following configurations. The data-conversion-leaning-vehiGle-traveîing data includes a targer amount of data in traveling of the data-conversion-leaning vehicle on a public road than data in traveling of the data-conversion-leaning vehicle on a place except for a public road. The analysis-leaning-vehicle-traveling data includes a larger amount of data in traveling of the analysis leaning vehicle on a public road than data in traveling of the analysis leaning vehicle on a place except for a public road.

[0199] While a driver traveling on a public road drives a leaning vehicle, the driver makes détermination more frequently, has a wide variation of options in détermination, and is likely to be subjected to stress from the outside. Accord in gly, personality of the driver tends to appear more strongly in traveling data of the leaning vehicle. In addition, since the leaning vehicle has higher degrees of mobility and convenience than a nonleaning vehicle, the leaning vehicle can be used for various applications, and tends to be frequently used. Accordîngly, personality of the driver tends to appear more strongly in traveling data of the leaning vehicle traveling on a public road. That is, the traveling data of the leaning vehicle traveling on a public road more strongly reflects inherent personality of the driver with small arbitrariness of the driver. For example, it may be determined from leaning-vehicle-location data and leaning-vehicle-traveling-environment data whether the traveling data is data of traveling on a public road or not.

[0200] In another aspect, the personality analyzing method preferably includes the following configurations. The data-conversion-leaning-vehicle-traveling data includes data in a state where options of détermination by a driver are limited by vehicles around the data-conversion-leaning vehicle but some options are left. The analysis-leaningvehicle-traveling data includes data in a state where options of détermination by an analysis target are limited by vehicles around the analysis leaning vehicle, but some options are left.

[0201] For example, the state where options of détermination by a driver are limited by vehicles around a leaning vehicle but some options are left may be determined from leaning-vehicle-locaiion data and leaning-vehicle-traveling-environment data. More specifically, the state may be estimated based on date, time, and location where the leaning vehicle travels. Leaning-vehicle-traveling data for a leaning vehicle traveling in an urban distinct includes data in the state where options of détermination by the driver are limited by vehicles around the leaning vehicle but some options are left. The state may be estimated by acquiring data on an actual situation around the leaning vehicle. A plurality of methods for estimating a state may be combined.

[0202] The state where options of détermination by a driver are limited by vehicles around a leaning vehicle but some options are left refers to a traveiing state of the leaning vehicle where options are limited but some options are left when a driver of the leaning vehicle détermines driving among a group of vehicles including the leaning vehicle.

[0203] In another aspect, the personality analyzing method preferably includes the following configuration. The data-conversion-ieaning-vehicle-traveling data includes data in a state where at least one of a passenger or an object is mounted. The analysisleaning-vehicle-traveling data includes data in a state where at least one of a passenger or an object is mounted.

[0204] For exampîe, it may be determined from various sensors whether at least one of a passenger or an object is mounted or not. The détermination may be made based on a déclaration by a driver.

[0205] In another aspect, the personality analyzing method preferably includes the following configurations. In the personality analyzing method, the converted personality data after conversion is stored. In the personality analyzing method, the personality data to be output is generated by using the stored plurality of sets of converted personality data. The term “storing includes not only storing for a storage but also temporarily storing of results. For example, converted personality data stored in a storage and converted personality data stored in a temporary memory may be used. These sets of data may be used to update converted personality data stored in a storage. These sets of data may be used to generate new converted personality data. These sets of data may be used to perform statistical processing. These sets of data may be used to update converted personality data stored in a storage.

[0206] The use of a plurality of sets of converted personality data described above enables, for example, statistical processing and more précisé analysis of personality of an analysis target who is a driver of a leaning vehicle. More specifically, old converted personality data and new converted personality data are used to more precisely analyze personality of the analysis target who is a driver of the leaning vehicle X.

[0207] This embodiment is an example of a personality analyzing device that analyzes personaiity of an analysis target. The personality analyzing device of this embodiment includes the following configurations.

[0208] The personality analyzing device according to this embodiment includes: a personality-conversion-data acquirer configured to acquire personality conversion data generated by assoçiating personality data with leaning-vehicle-traveling data, the personality data showing personality determined based on, for example, psychological State, character, or tempérament, the leaning-vehicle-traveling data being traveling data of a leaning vehicle, the leaning vehicle being configured to lean rightward when tu min g to the right and lean leftward when tuming to the left; an analysis-leaning-vehicletraveling-data acquirer configured to acquire analysis-leaning»vehicfe-traveling data related to traveling data of an analysis leaning vehicle, the analysis leaning vehicle being configured to lean rightward when tuming to the right and lean leftward when tuming to the left; a personality data converter configured to couvert the acquired analysis-leaningvehicle-traveling data to converted personality data related to personality of the analysis target by using the acquired personality conversion data; a personaiity-data-to-be-output generator configured to generale personality data to be output for output by using the converted personality data after conversion; and a data output section configured to output the generated personality data to be output.

[0209] The personality-conversion-data acquirer generates the personality conversion data by associating the personality data showing personality with leaning-vehicletraveling data that is traveling data of the leaning vehicle, based on data-conversionleaning-vehicle-traveîing data related to traveling data obtained when a plurality of drivers drives data-conversion-leaning vehicles.

[0210] The analysis-leaning-vehicle-traveling-data acquirer acquires, as the analysisleaning-vehicie-traveling data, data related to traveling data of the analysis leaning vehicle obtained when an analysis target drives the analysis leaning vehicle.

[0211] The personality analyzing device analyzes personality of an analysis target driving the analysis leaning vehicle configured to lean rightward when tuming to the right and lean leftward when tuming to the left.

[0212] In another aspect, the personality analyzing device preferably includes the following configurations. The data-conversion-leaning-vehicle-traveling data include data related to traveling data obtained when a plurality of drivers drives the dataconversion-leaning vehicles in a lean State. The analysis-leaning-vehrde-traveling data includes data related to traveling data obtained when the analysis target drives the analysis leaning vehicle in a lean State.

[0213] Accordingly, personality of the analysis target can be analyzed by using traveling data in the lean state of the leaning vehicle in which personality ôf the driver is more noticeable. Thus, personality of the analysis target as a driver can be more precisely analyzed.

[0214] In another aspect, the personality analyzing device preferably includes the following configurations, The data-conversion-leaning-vehicle-traveling data includes a larger amount of data reflecting a change in driving of the data-conversion-leaning vehicie by a driver than data not reflecting a change in driving of the data-conversion-leaning vehicle by the driver. The anaiysis-leaning-vehicle-traveiing data includes a larger amount of data reflecting a change in driving of the analysis leaning vehicle by an analysis target than data not reflecting a change in driving of the analysis leaning vehicle by the analysis target.

[0215] In another aspect, the personality analyzing device preferably includes the following configurations. The data-conversion-leaning-vehicle-traveling data includes at least one of data-conversion-leaning-vehrcle-driving-input data related to a driving input to the data-conversion-leaning vehicle by the driver, data-conversion-leaning-vehiclebehavior data related to a behavior of the data-conversion-leaning vehicle, or dataconversion-leaning-vehictê-Îocation data related to a location of the data-conversionleaning vehicie. The analysis-leaning-vehicle-traveling data includes at least one of analysis-leaning-vehicle-driving-input data related to a driving input to the analysis leaning vehicle by the analysis target, analysis-leaning-vehicle-behavior data related to a behavior of the analysis leaning vehicle, or analysîs-leaning-vehicle-location data related to a location of the analysis leaning vehicle.

[0216] !n another aspect, the personality analyzing device preferably includes the following configurations. The data-conversion-leaning-vehicle-traveiing data further includes data-conversion-leaning-vehicle-traveling-environment data related to traveling environments in which the data-conversion-leaning vehicie traveis, The anaiysisleaning-vehicie-traveling data further includes analysis-leaning-vehicle-travelingenvironment data related to traveling environments in which the analysis leaning vehicle traveis.

[0217] In another aspect, the personality analyzing device preferably includes the following configurations. The data-conversion-leaning-vehicie-traveling data includes a larger amount of data in traveling of the data-conversion-leaning vehicle on a public road than data in traveling of the data-conversion-leaning vehicle on a place except for a public road. The analysis-leaning-vehicle-traveling data includes a larger amount of data in traveling of the analysis leaning vehicle on a public road than data in traveling of the analysis leaning vehicle on a place except for a public road.

[021 S] In another aspect, the personality analyzing device preferably includes the following configurations. The data-conversion-leaning-vehicle-traveling data includes data in a state where options of détermination by a driver are limited by vehicles around the data-conversion-leaning vehicle but some options are left. The analysis-leaningvehicle-traveling data includes data in a state where options of détermination by an analysis target are limited by vehicles around the analysis leaning vehicie but some options are left.

[0219] In another aspect, the personality analyzing device preferably includes the following configurations. The data-conversion-leaning-vehicle-traveling data includes data in a state where at least one of a passenger or an object is mounted. The analysis» ieaning-vehicle-traveiing data includes data in a state where at least one of a passenger or an object is mounted,

[0220] <Second Embodiment>

FIG. 3 illustrâtes an exampie of a personality analyzing System 100 including the personality analyzing device 1 according to the first embodiment. in the following description, components similar to those of the first embodiment are denoted by the same reference characters and wiii not be described again, and oniy components different from those of the first embodiment will be described.

[0221] The personality analyzing system 100 includes the personality analyzing device 1, and a personality-conversion-data-generating device 101 that generates personality conversion data,

[0222] The personality-conversion-data-generating device 101 is, for example, a dataprocessîng-computation device capable of communicating with the personality analyzing device 1 and including a processor. In a case where the personality analyzing device 1 is a data-processing-computation device including a processor, the personalityconversion-data-generating device 101 may be the same data-processing-computation device as the personality analyzing device 1.

[0223] The Personaliiy-convêrsion-data-gerièraîing device 101 acquires leaningvehicle-traveling data and personality data, and generates personality conversion data in which the leaning-vehicle-traveling data is associated with the personality data.

[0224] Specifically, the personal ity-conversion-data-generating device 101 includes a data memory 111 and a personality-conversion-data generator 112. Although not specifically shown, the personality-conversion-data-generating device 101 includes an acquirer that acquires leaning-vehicle-traveling data and personality data. Although not specifically shown, the personality-conversion-data-generating device 101 includes an output section that outputs generated personality conversion data.

[0225] The data memory 111 stores leaning-vehiciê-traveling data, personality data, and personality conversion data. Specifically, the data memory 111 stores dataconversionMeaning-vehicle-traveling data obtained when a plurality of drivers drives leaning vehicles Y (data-conversion-leaning vehicles). The data memory 111 also stores personality conversion data generated by the personality-conversion-data generator 112 described later.

[0226] The data memory 111 may store personality data by input, or may store personality data beforehand.

[0227] The data-conversion-leaning-vehicie-traveling data inciudes, for example, dataconversion-leaning-vehicle-’drivÎng-input data, data-conversiomleaning-vehicle-behavior data, data-conversion-leaning-vehicle-location data, data-conversion-leaning-vehicletraveling-environment data, and so forth,

[0228] The Personal ity-conversion-data generator 112 generates personality conversion data in which leaning-vehicie-traveling data is associated with personality data, based on data-conversion-leaning-vehicie-traveling data stored in the data memory 111. The personality conversion data generated by the personality-con version-data generator 112 is stored in the data memory 111.

[0229] The personality conversion data stored in the data memory 111 is used by the personality analyzing device 1 in converting leaning-vehicie-traveling data (analysisleaning-vehicle-traveling data) of a leaning vehicle X (analysis leaning vehicle) to converted personality data. In the personality analyzing device 1, a method for converting the leaning-vehicie-traveling data to the converted personality data is similar to that in the first embodiment, and thus, will not be specifically described.

[0230] The personality analyzing device 1 generates personality data to be output by using the converted personality data, and outputs the personality data to be output. The configuration of the personality analyzing device 1 is similar to that of the first embodiment, and thus, the personality analyzing device 1 will not be described specifically.

[0231] The personality data to be output that has been output from the personality analyzing device 1 may be input to, for example, a data processing device 102. In this case, the personality data to be output is generated by the personality analyzing device 1 as personality data for data processing to be used for data processing in the data processing device 102.

[0232] The data processing device 102 may be a device that perforons processing of, for exampie, data related to finance, Insurance, markets, products, services, environments, or customers used in the businesses of finance, Insurance, sales, advertising, and so forth. in a case where the personality analyzing device 1 is a dataprocessing-computation device, the data processing device 102 may be the same device as the personality analyzing device 1. The data processing device 102 may be the same data-processing-computation device as the personality-conversion-data-generatîng device 101.

[0233] The data processing device 102 includes, for example, a personality-data-tobe-output acquirer 121, a first data acquirer 122, a second data generator 123, a seconddata-output section 124, and a data memory 125.

[0234] The personality-data-to-be-output acquirer 121 acquires the personality data to be output that is output from the personality analyzing device 1.

[0235] The first data acquirer 122 acquires first data different from the personality data to be output. The first data is data as a data processing target in the data processing device 102. The first data is, for example, data related to finance, Insurance, markets, Products, services, environments, or customers used in the businesses of finance, insurance, sales, advertising, and so forth. The first data is stored in the data memory 125.

[0236] The second data generator 123 générales second data different from the personality data to be output and the first data, by using the personality data to be output and the first data. In a manner similar to the first data, the second data is also, for example, data related to finance, insurance, markets, products, services, environments, or customers used in the businesses of finance, Insurance, sales, advertising, and so forth.

[0237] The second-data-output section 124 outputs the second data generated by the second data generator 123.

[0238] (Information Processing Method Using Personality Data)

Next, a data processing method that performs data processing by using personality data to be output with the data processing device 102 having the configuration described above wili be described with reference to the flowchart shown in FIG. 4. FIG. 4 is a flowchart depicting an operation of data processing by the data Processing device 102.

[0239] As shown in FIG. 4, first, the personality-data-to-be-output acquirer 121 of the data processing device 102 acquires personality data to be output that was output from the personality analyzing device 1 (step SB1).

[0240] Next, the first data acquirer 122 ofthe data processing device 102 acquires first data stored in the data memory 125 (step SB2). The first data is data different from the personality data to be output.

[0241] Thereafter, the second data generator 123 of the data processing device 102 generates second data by using the acquired personality data to be output and the acquired first data (step SB3). The second data is data different from the personality data to be output and the first data.

[0242] Subsequently, the second-data-output section 124 of the data processing device 102 outputs the generated second data (step SB4).

[0243] As described above, the personaîity data to be output that was output from the personaîity anaiyzing device 1 can be used in computing a crédit risk or a crédit score by the data processing device in the field of, for example, finance or Insurance. That is, the 5 personaîity data obtained by using the leaningwehicîertraveling data can be used for computation by the data processing device in the field of, for exampîe, finance, Insurance, sales, and advertising,

[0244] Specificalîy, in the field such as finance or insurance, the data processing device acquires personaîity data to be output that was output, and by using the acquired 10 personaîity data to be output, outputs a crédit risk or a crédit score by computation.

[0245] In the fieîd such as finance or insurance, the data processing method may include the steps of: acquiring personaîity data io be output that was output from the personaîity analyzing device 1; and outputting crédit risk data related to a crédit risk or crédit score data related to a crédit score by using the acquired personaîity data to be 15 output.

[0246] în the fieîd such as finance or Insurance, the data processing device may inciude; a personaîity data acquirer configured to acquire personaîity data to be output that was output from the personaîity analyzing device 1; and either a credit-risk-output section configured to output crédit risk data related to a crédit risk or a credit-score-output 20 section configured to output crédit score data related to a crédit score.

[0247] In the data processing method and the data processing device described above, in a case where the output crédit risk is low or a case where the output crédit score is high, it may be configured such that an analysis target easiîy obtains a ïoan, or if the analysis target obtains a loan, an interest rate rs preferentially treated, or an analysis 25 target receives a preferentia! insurance rate, for example.

[0248] In addition, personaîity data to be output that was output from the personaîity analyzing device 1 as described above can be used as a parameter to be taken into considération for recommendation to an analysis target when a data processing device perforais computation in the field of sales or advertising, for example. In the field such 30 as sales or advertising, products or services may be recommended to an analysis target depending on personaîity data of the analysis target by performing computation with the data processing device.

[0249] Specificalîy, in the fieîd such as sales or advertising, the data processing device can acquire personaîity data to be output that was output from the personaîity analyzing 35 device 1, and by using the acquired personaîity data to be output, output a product or a service to be recommended to the analysis target by computation.

[0250] In the field such as sales or advertising, the data processing device may include: a personality data acquirer configured to acquire personality data to be output that was output from the personality analyzing device 1 ; and either a product-relateddata-output section configured to output product-related data concerning a product to be recommended to an analysis target or a ser/ice-related-data-output section configured to output service-related data concerning a service to be recommended to the analysis target, by using the acquired personality data to be output,

[0251] In the field such as sales or advertising, the data processing method may include the steps of: acquiring personality data output from the personality analyzing device 1; and outputting either product-related data concerning a product to be recommended to an analysis target or service-reiated data concerning a service to be recommended to the anaiysis target, by using the acquired personality data,

[0252] The personality analyzing method according to each of the embodiments described above is an example of a personality analyzing method for analyzing personality of an analysis target.

[0253] The personality analyzing method according to the présent teaching preferabiy includes the following configurations. Personality data to be output is generated as personality data for data processing that is used for further data processing.

[0254] For example, the further data processing may be processing of data related to finance, insurance, markets, products, services, environments, or customers used in the businesses of finance, insurance, sales, advertising, and so forth.

[0255] In another aspect, personality data output in the personality analyzing method according to the présent teaching is preferabiy used for a data processing method using the following personality data. In this data processing method, the personality data to be output that was output is acquired. in the data processing method, first data different from the personality data to be output is acquired. In the data processing method, the personality data to be output and the acquired first data are used to generate second data different from the personality data to be output and the acquired first data. In the data processing method, the generated second data is output,

[0256] The data processing method employing personality data includes data processing methods as described in Patent Documents mentioned in Background Art. The présent teaching, however, is not limited to the data processing methods as described in Patent Documents listed in the Background Art. The data processing method may be any data processing method as long as the data processing method employs personality data. For example, the first data and the second data may be data related to finance, insurance, markets, products, services, environments, or customers used in the businesses of finance, insurance, sales, advertising, and so forth.

[0257] With the configuration of this embodiment, the personality analyzing device 1 and the personality anaiyzing method employing the device can acquire personality data usable in the data processing device 102. As described in the first embodiment, the use of traveling data of a leaning vehicle for personality analysis can reduce the number of types of data processed by the system and can reduce a load on hardware of the personality analyzing device 1.

[0258] As a resuit, personality data usable in a data processing device can be acquired with enhanced design flexibility of hardware resources.

[0259] The personality analyzing device according to the present teaching preferably includes the following configurations. The personality data to be output is generated as personality data for data processing that is used for further data processing.

[0260] In another aspect, personality data output in the personality analyzing device according to the present teaching is preferably used for a data processing device using the following personality data. The data processing device includes: a personality-datato-be-output acquirer configured to acquire the personality data to be output; a first data acquirer configured to acquire first data different from the personality data to be output; a second data generator configured to generate second data different from the personality data to be output and the first data by using the personality data to be output and the first data; and a second-data-output section configured to output the second data.

[0261] In each of the embodiments described above, personality conversion data is generated by using leaning-vehicle-traveling data. Aiternatively, personality conversion data may be generated by using mot only leaning-vehicle-traveling data but also data except for the leaning-vehicle-traveling data.

[0262] In the embodiments, leaning-vehicle-traveling data is acquired as analysisleaning-vehicle-traveling data, and by using personality conversion data, the analysisleaning-vehicle-traveling data is converted to converted personality data related to personality of an analysis target. Aiternatively, data other than the leaning-vehicletraveling data may be acquired for analysis such that the data and leaning-vehicletraveling data are converted to converted personality data by using personality conversion data.

[0263] The personality data to be output may be combined with data other than the leaning-vehicle-traveling data and used.

[0264] As described above, various types of data described in the embodiments may be combined with data other than the leaning-vehicle-traveling data.

INDUSTRIAL APPLICAB1LITY

[0265] The présent teaching is usabie for a personality analyzing method and a personality analyzing device for analyzing personality of an analysis target, and a data processing method and a data processing device that use personality data obtained by the personality analyzing method and the personality analyzing device.

REFERENCE SIGNS LIST

[0266] 1 personality analyzing device personality-conversion-data acquirer analysis-leaning-vehicle-traveling-data acquirer personality data converter personality-daia-io-be-output generator data output section

60,111,125 data memory

100 personaiity analyzing system

101 personaiity-conversion-data-generating device

112 personality-conversion-data generator

102 data processing device

121 personality-data-to-be-output acquirer

122 first data acquirer

123 second data generator

124 second-data-output section

X leaning vehicle (analysis leaning vehicle)

Y leaning vehicle (data-conversion-leaning vehicle)

Claims

1. A personalîty anaiyzing method, comprising:

a Personality-conversion-data-acquiring step of acquiring personalîty conversion data generated by associating personalîty data with leaning-vehicle-traveling data, the personalîty data showing personalîty determined based on, for example, psychological state, character, or tempérament, the leaning-vehicle-traveling data being traveling data of a Ieaning vehicle configured to lean rightward when tuming to the right and lean leftward when tuming to the Ieft;

an anaîysis-leaning-vehicle-traveling-data-acquiring step of acquiring analysis-leantngvehicle-traveiing data reiated to traveling data of an analysis Ieaning vehicle configured to lean rightward when turning to the right and lean leftward when tuming to the Ieft;

a personality-data-conversion step of converting the acquired analysis-ieanîng-vehicletraveling data to converted personalîty data related to personalîty of an analysis target, by using the acquired personalîty conversion data;

a personality-data-to-be-outpuFgenerafion step of generating personalîty data to be output for output by using the converted personalîty data after conversion; and a personality-data-output step of outputting the generated personalîty data to be output, wherein in the personality-conversion-data-acquiring step, the personalîty conversion data is generated by assocîating the personalîty data showing personalîty with the leaning-vehicle-traveling data that is traveling data of the Ieaning vehicle, based on dataconversion-leaning-vehicle-traveling data related to traveling data obtained when each of a plurality of drivers drives a data-conversion-leaning vehicle, in the analysis-îeaningvehicle-traveling-data-acquiring step, as the analysis-leaning-vehicle-traveling data, data related to traveling data ofthe analysis Ieaning vehicle obtained when the analysis target drives the analysis Ieaning vehicle is acquired, and personalîty of the analysis target driving the analysis Ieaning vehicle îs analyzed,

2. The personalîty anâîyzing method according to claim 1, wherein the dataconversion-îeaning-vehicie-traveling data includes data related to traveling data obtained when each of the plurality of drivers drives the data-conversion-leaning vehicle in a lean state, and the analysis-leaning-vehicle-iraveling data includes data related to traveling data obtained when the analysis target drives the analysis leaning vehicle in a lean state.

3. The personality analyzing method according to claim 1 or 2, wherein the dataconversion-leaning-vehicle-traveling data includes a iarger amount of data reflecting a change în driving of the data-conversion-leaning vehicle by the driver than data not reflecting a change in driving of the data-conversion-leaning vehicle by the driver, and the analysis-leaning-vehide-traveüng data includes § Iarger amount of data reflecting a change in driving of the analysis leaning vehicle by the analysis target than data not reflecting a change in driving of the analysis leaning vehicle by the analysis target.

4. The personality analyzing method according to any one of daims 1 to 3, wherein the data-conversion-leaning-vehicle-traveling data includes at least one of data-conversionleaning-vehicle-driving-input data related to a driving input to the data-conversionleaning vehicle by the driver, data-conversion-leaning-vehicle-behavior data related to a behavior of the data-conversion-leaning vehicle, or data-conversion-leaning-vehiclelocation data related to a location of the data-conversion-leaning vehicle, and the analysis-leaning-vehicle-traveling data includes at least one of analysis-leaning-vehicledriving-input data related to a driving input to the analysis leaning vehicle by the analysis target, analysis-leaning-vehicle-behavior data related to a behavior of the analysis leaning vehicle, or anaîysis-leaning-vehicle-location data reîated to a location of the analysis leaning vehicle.

5. The personality analyzing method according to any one of daims 1 to 4, wherein the data-conversion-leaning-vehide-traveling data further includes data-conversion-leaningvehide-iraveling-environment data related to a traveling environment in which the dataconversion-leaning vehicle travels, and the analysis-leaning-vehicle-traveling data further includes analysis-leaning-vehicle-traveling-environment data related to a traveling environment in which the analysis leaning vehicle travels.

6. The personality analyzing method according to any one of daims 1 to 5, wherein the data-conversion-leaning-vehide-traveiing data includes a Iarger amount of data in traveling of the data-conversion-leaning vehicle on a public road than data in traveling of the data-conversion-leaning vehicle on a place except for a public road, and the analysis-leaning-vehicle-traveling data includes a Iarger amount of data in traveiing of the analysis leaning vehicle on a public road than data in traveiing of the analysis

J.

leaning vehicle on a place except for a public road.

7. The personality analyzing method according to any one of claims 1 to 6, wherein the data-conversion-leaning-vehicle-traveling data includes data in a state where options of détermination by the driver are limited by a vehicle around the data-conversion-leaning vehicle but some options are left, and the analysis-leaning-vehicle-traveling data includes data in a state where options of détermination by the analysis target are limited by a vehicle around the analysis leaning vehicle but some options are left.

8. The personality analyzing method according to any one of claims 1 to 7, wherein the data-conversion-leaning-vehicle-traveling data includes data in a state where at least one of a passenger or an object is mounted, and the anaiysis-leaning-vehicie-traveling data includes data in a state where at least one of a passenger or an object is mounted.

9. The personality analyzing method according to any one of claims 1 to 8, wherein the converted personality data after conversion is stored, and the personality data to be output is generated by using a plurality of sets of the converted personality data that hâve been stored.

10. The personality analyzing method according to any one of claims 1 to 9, wherein the personality data to be output is generated as personality data for data processing that is used for further data processing.

11. A personality analyzing device, comprising:

a person ality-conversion-data acquirer configured to acquire personality conversion data generated by associating personality data with leaning-vehicle-traveling data, the personality data showing personality determined based on, for example, psychologicaî state, character, or tempérament, the leaning-vehicle-traveling data being traveling data of a leaning vehicle configured to lean rightward when turning to the right and lean leftward when turning to the left;

an anaiysis-leaning-vehicle-traveling-data acquirer configured to acquire analysisieaning-vehicle-traveîing data related to traveling data of an analysis leaning vehicle configured to lean rightward when turning to the right and lean leftward when turning îo the left;

a personaiity data converter configured to convert the acquired analysis-ieaning-vehicletraveling data to converted personaiity data related to personaiity of an analysis target, by using the acquired personaiity conversion data;

a perso nality-data-to-be-ouiput generator configured to generate personaiity data to be output for output by using the converted personaiity data after conversion; and a data output section configured to output the generated personaiity data to be output, wherein the Personal ity-conversion-data acquirer generates the personaiity conversion data by associating the personaiity data showing personaiity with the leanîng-vehicletraveling data that is traveling data of the leaning vehicle, based on data-conversionieaning-vehicie-traveüng data related to traveling data obtained when each of a plurality of drivers drives a data-conversion-leaning vehicle, the analysis-leaning-vehicletraveling-data acquirer acquires, as the analysis-leaning-vehicle-traveling data, data related to traveling data of the analysis leaning vehicle obtained when the analysis target drives the analysis leaning vehicle, and personaiity of the analysis target driving the analysis leaning vehicle is analyzed.

12. The personaiity analyzing device according to claim 11, wherein the dataconversion-leaning-vehicle-traveling data includes data related to traveling data obtained when each of the plurality of drivers drives the data-conversion-leaning vehicle in a lean State, and the anaîysis-ieaning-vehicle-travefing data includes data related to traveling data obtained when the analysis target drives the analysis leaning vehicle in a lean State.

13. The personaiity analyzing device according to claim 11 or 12, wherein the dataconversion-leaning-vehicle-traveling data includes a larger amount of data reflecting a change in driving of the data-conversion-leaning vehicle by the driver than data not reflecting a change in driving of the data-conversion-leaning vehicle by the driver, and the analysis-leaning-vehicle-traveling data includes a larger amount of data reflecting a change in driving of the analysis leaning vehicle by the analysis target than data not reflecting a change in driving of the analysis leaning vehicle by the analysis target.

14. The personaiity analyzing device according to any one of daims 11 to 13, wherein the data-conversion-leaning-vehicle-traveling data includes at least one of dataconversion-ieaning-vehicie-driving-input data related to a driving input to the dataconversion-leaning vehicle by the driver, data-conversîon-leaning-vehicle-behavior data i

related to a behavior of the data-conversion-leaning vehicle, or data-conversion-leaningvehicle-location data related to a location of the data-conversion-leaning vehicle, and the analysfs-îeaning-vehicie-travëîing data includes at least one of anaîysis-feaning-vehicfedriving-input data related to a driving input to the analysis leaning vehicîe by the analysis target, analysisMeaning-vehicle-behavior data related to a behavior of the analysis leaning vehicle, or analysis-leaning-vehicie-location data related to a location of the analysis leaning vehicle.

15. The personality analyzing device according to any one of claims 11 to 14, wherein the data-conversion-îeaning-vehicle-traveling data further includes data-conversionieaning-vehicle-traveling-environment data related to a traveling environment in which the data-conversion-leaning vehîcie travels, and the analysis-leaning-vehicle-traveling data further includes analysis-leaning-vehicle-traveüng-environment data related to a traveling environment in which the analysis leaning vehicle travels.

16. The personality analyzing device according to any one of claims 11 to 15, wherein the personality data to be output is generated as personality data for data processing that is used for further data processing.

17. A data processing method employing the personality data to be output generated as the personality data for data processing in the personality analyzing method as claimed in claim 10, the data processing method comprising:

acquiring thê personaiity data to be ôuîput;

acquiring first data different from the personality data to be output;

generating second data by using the personality data to be output and the first data, the second data being different from the personality data to be output and the first data; and outputting the second data.

18. A data processing device employing the personality data to be output generated as the personality data for data processing in the personality analyzing device as claimed in claim 16, the data processing device comprising:

a personality-data-to-be-output acquirer configured to acquire the personality data to be output;

a first data acquirer configured to acquire first data, the first data being different from the personality data to be output;

a second data generator configured to generate second data by using the personaiity data to be output and the first data, the second data being different from the personaiity data to be output and the first data; and a second-data-output section configured to output the second data.