OA20518A - Customer-sense-of-value-analysis method, customer-sense-of-value-analysis device, data processing method using sense of-value data, and data processing device using sense-of-value data - Google Patents

Abstract

Provided is a customer-sense-of-value-anaiysis method capable of acquiring sense-of-value data, while ensuring design flexibility of hardware resources of a data processing device. The customer-sense-of-value-analysis method includes: a sense-of-value-conversion-dataacquiring step of acquiring sense-of-valueconversion-data which associates leaning-vehicletraveling data, evaluation data of a customer and sense-of-value data of the customer; a step of acquiring analysis-leaning-vehicle-traveling data and analysis evaluation data, and a step of converting the acquired analysis-leaning-vehicletraveling data and the acquired analysis evaluation data to sense-of-value data of a customer. Leaning-vehicle-traveling data for sense-of-value-conversion data and evaluation data of a customer are used to acquire, as the sense-of-value-conversion data, data in which the leaning-vehicle-traveling data, the evaluation data of the customer and sense-of-value data of the customer are associated. The acquired analysisleaning-vehicle-traveling data and the acquired analysis evaluation data are converted to the sense-of-value data by using the acquired senseof-value-conversion data.

Description

CUSTOMER-SENSE-OF-VALUE-ANALYSIS METHOD, CUSTOMER-SENSE-OFVALUE-ANALYS1S DEVICE, DATA PROCESSING METHOD USING SENSE-OFVALUE DATA, AND DATA PROCESSING DEVICE USING SENSE-OF-VALUE DATA

TECHNICAL FIELD

[0001] The present teaching relates to a customer-sense-of-value-analysis method and a customer-sense-of-value-analysis device for analyzing a customer s sense of value, a data processing method using sense-of-value data, and a data processing device using sense-of-value data,

BACKGROUND ART

[0002] A known data processing system performs data processing using a customer’s preference. As a configuration for performing data processing by using a customer’s preference, configurations disclosed in Patent Documents 1 to 6, for example, are known. [0003] Patent Document 1 disdoses a System for presenting to a user supplementary information related to an advertisement that the user appears to hâve found interesting.

[0004] Patent Document 2 discloses a System for presenting a set of d ri vers to a user and allowing the user to select a driver among the set of drivers,

[0005] Patent Document 3 discloses an electronic commerce System that introduces to a user a merchant who can sel! merchandise by using a users preference and transmits a purchase request to the merchant.

[0006] Patent Document 4 disctoses a system for proposing a recipe based on a useris preference and available foods stored in a storage unit such as a refrigerator.

[0007] Patent Document 5 disctoses a system for hôtel services analysis based on a useris preference.

[0008] Patent Document 6 discloses a system for analyzing a customer’s preference based on a merchandise purchasing history of the customer,

CITATION LIST

PATENT DOCUMENT

[0009] Patent Document 1: U,S. Patent Application Publication No. 2019/0005549 Patent Document 2: U.S. Patent Application Publication No. 2015/0206267 Patent Document 3: U.S. Patent No. 10134078

Patent Document 4: U.S. Patent No. 9821344

Patent Document 5: U.S. Patent Application Publication No. 2019026793

Patent Documente: U.S. Patent Application Publication No, 2017/0140403

SUMMARY OF INVENTION

TECHNICAL PROBLEM

[0010] There are as many sets of users preference data as the number of types of user actions. The préférence data is data indicating a superficial préférence.

[0011] If there exists highly versatile data indicating a users latent preference, what is called data indicating a sense of value, combination of the data indicating a sense of value and the data indicating a superficial preference will further facrirtate utîlization of the data indicating a preference

[0012] To obtain the higNy versaifle data indicating a latent preference, what is called the data indicating a sense of value, one approach may be to use data indicating préférences involved with numeroes types of user actions. If the data indicating préférences involved with such numerous types of user actions are used, however, the number of types of data to be processed in the System increases.

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

[0014] The présent teaching has an object to provide a customer-sense-of-valueanalysis method capable of acquiring highly versatile data indicating a customer’s latent preference, what is caited data indicating a sense of vaiue, while ensuring design fiexibility of hardware resources of a data processing device.

SOLUTION TO PROBLEM

[0015] Through an analysis of traveling data of a Ieaning vehicle, the inventors of the présent teaching feund that tire traveling data of the ieaning vehicle is significantly different from traveling data of a non-leaning vehicle. The Ieaning vehicle is a vehicle that leans rightward when tuming ta the nght and leans leftward when tuming to the left.

[0016] A Ieaning vehicle is smalîer in vehicle size than a non-leaning vehicle. That is, the size of the Ieaning vehicle in the front-rear direction and/or in the left-right direction is smalîer than that of the non-leaning vehicle. A rotational operation amount of steering of the Ieaning vehicle is smalîer than 360 degrees, and thus, the rotational operation amount of steering of the Ieaning vehicle is smalîer than that of the non-leaning vehicle. In addition, unlike the non-leaning vehicle, the Ieaning vehicle is a rider-active vehicle actively operatable by a driver (rider). Thus, an operation of the ieaning vehicle is ?

different from an operation of the non-leaning vehicle. Traveiing data of such a leaning vehicle who se operation is different from that of a non-leaning vehicle is significantly different from traveling data ofthe non-îeaning vehicle, such as a four-wheeled vehicle.

[0017] The inventors of the présent teaching further intensively investigated traveiing situations of a leaning vehicle to find that the leaning vehicle has a very high degree of flexibility in traveling by an intention of a driver, 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 Iarger 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 applied from the outside to the driver of the leaning vehicle.

[0020] Thus, it was found that there are many variations of traveling data of the leaning vehicle due to différences in devers who drive the leaning vehicle, différences in leaning vehicles, différences in traveling environments and so forth, as compared to traveling data of a non-leaning vehicle.

[0021] In addition, when the leaning vehicle is used as a business vehicle carrying a customer, évaluation data of the customer regarding the ride may in some cases be collected.

[0022] Then. the inventors of the présent teaching intensively investigated a relationshîp between traveling data of the leaning vehicle and évaluation data of a customer to find that the évaluation data of the customer is data reflecting the customeris preference with respect to the traveling data ofthe leaning vehicle.

[0023] There are many variations of traveling data of the leaning vehicle, and therefore, there are many variations of stimuli received by a customer who rides on the leaning vehicle. Furthermore, the customer riding on the leaning vehicle is passive to the stimuli.

[0024] Thus, a quite severe évaluation is made unconsciously by the customer regarding the ride on the leaning vehicle, and tends to more strongly refiect his/her preference. In view of this, the inventors of the présent teaching found that data indicating the customeris sense of value can be acquired based on a relationship between traveling data of the leaning vehicle and évaluation data of the customer.

[0025] In view of the above findings, the inventors of the présent teaching conceived a technique of analyzing a customeris sense of value by acquiring data indicating the customers sense of value, using traveling data of the leaning vehicle and évaluation data ofthe customer.

[0026] A customer-sense-of-value-analysis method according to one embodiment of the présent teaching includes: a sense-of-vaiue-conversion-data-acquiring step of acquiring sense-oTvalue-conversiomdata which associâtes leaning-vehicle-traveling data, évaluation data and sense-of-value data of a customer, the leaning-vehicle-traveling data being traveling data of a leaning vehicle configured to lean rightward when tuming to the right and lean leftward when tuming to the left, the évaluation data showing évaluation by the customer; an analysis-data-acquiring step of acquiring leaning-vehicletraveling data for analysis (analysis-leaning-vehicle-traveling data) that is traveling data of a leaning vehicle for analysis (analysis leaning vehicle), and évaluation data for analysis (analysis évaluation data) of a customer as an analysis target riding on the anaiysis leaning vehicle; a sense-of-value-data-conversion step of converting the acquired analysis-leaning-vehicle-traveling data and the acquired analysis évaluation data to sense-of-value data related to a sense of value of the customer; an output-sense-ofvaîue-data-generating step of generating output-sense-of-value data for output by using the converted sense-of-value data; and an output-sense-of-value-data-outputting step of outputting the generated output-sense-of-value data to be output. The sense-of-va lueconversion-data-acquiring step uses leaning-vehicle-traveling data for sense-of-valueconversion data related to traveling data obtained when each of a plurality of drivers drives a leaning vehicle for sense-of-value-conversion data, and évaluation data obtained from each of a plurality of customers riding on the leaning vehicle for sense-of-va luecon version data when the Ira vélin g data is obtained, to thereby acquire, as the sense-ofvalue-conversion data, data in which the leaning-vehicle-traveling data, the évaluation data showing évaluation by the customer and sense-of-value data of the customer are associated. The sense-of-value-data-conversion step converts the acquired analysisleaning-vehicle-traveiing data and the acquired analysis évaluation data to the sense-ofvalue data by using the acquired sense-of-value-conversion data.

[0027] Evaluation data of a customer is data reflecting a preference of the customer with respect to traveling data of a leaning vehicle, Therefore, sense-of-valueconversion data that associâtes the leaning-vehicle-traveling data, the évaluation data and sense-of-value data, can be generated based on the leaning-vehicle-traveling data and the évaluation data. Leaning-vehicle-traveling data and évaluation data can be converted to sense-of-value data of a customer as an analysis target by using the sense-of-value-conversion data. Thus, the customer-sense-of-value analysis method according to one embodiment of the présent teaching can acquire highly versatile data indicating a customer’s latent preference, that is, sense-of-value data, based on a relationship between the traveling data of the leaning vehicle and the évaluation data of the customer, and thereby analyze a sense of value of the customer.

[0028] The sense-of-value data can be acquired based on the leaning-vehicletraveling data and the évaluation data, as well as the sense cf vaÏue -conversion data. Accordingly, the customer-sense-of-value-analysis method can reduce a data amount to be processed, as compared to a case of using data indicating preferences involved with numerous types of user actions. Therefore, the customer-sense-of-value-analysis method according to one embodiment of the présent teaching can acquire highiy versatile data indicating a useras latent preference, what is called data indicating a sense of value, whiie ensuring design ftexibiiity of hardware resources of a data processing device.

[0029] In another aspect, the customer-sense-of-va!ue-analysis method according to the présent teaching preferably includes the following configurations. The sense-ofvalue-conversion data is data in which the sense-of-value data of the customer is associated with a preference of the customer, the preference of the customer being estimated from the leaning-vehicle-traveling data for sense-of-value-conversion data and the évaluation data of the customer.

[0030] A driving characteristic of the driver can be analyzed based on leaning-vehicletraveling data. The driving characteristic includes, for example, a degree of trust, comfort and cost effectiveness.

[0031] A customer’s preference can be estimated by analyzing a relationship between évaluation data of the customer and a driving characteristic of a driver of a vehicle with the customer aboard. For example, when a customer rides on a vehicle of a driver whose driving characteristic is rated high in a degree of trust, and the customer highiy évaluâtes the driver, it can be estimated that the customer has a strong preference for the degree of trust. Likewise, when a customer rides on a vehicle of a driver whose driving characteristic is rated high in comfort, and the customer highiy évaluâtes the driver, it can be estimated that the customer has a strong preference for the comfort. When a customer rides on a vehicle of a driver whose driving characteristic is rated high in cost effectiveness, and the customer highiy évaluâtes the driver, it can be estimated that the customer has a strong preference for the cost effectiveness.

[0032] A preference of a customer can be associated with a sense of value that Controls a desire type of the customer. Accordingly, the sense-of-value data is associated with the customer’s preference estimated from the leaning-vehicle-traveling data for sense-of-value-conversion data and the évaluation data of the customer, in the sense-of-value-conversion data,,

[0033] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicie-traveling data for sense-of-value-conversion data includes data related to traveling data obtained when the leaning vehicle for sense-of-value-conversion data with each of the plurality of customers aboard traveis in a lean State, and the anaiysisleaning-vehicle-traveling data includes traveling data obtained when the analysis leaning vehicie with the customer as the analysis target aboard traveis in a lean State.

[0034] The leaning-vehicie-traveling data of the leaning vehicle which is in a lean state is largely affected by a driving characteristic of the driver. Thus, the use of the traveling data obtained when the leaning vehicle is in a lean State allows for more accurate analysis of a sense of value of the customer.

[0035] In another aspect, the customer-sense-of-value-analy sis method according to the présent teaching preferably includes the following configurations. The leaningvehicie-traveling data for sense-of-va iue-con version data includes a larger amount of data reflecting a change in driving of the leaning vehicle for sense-of-value-conversion data by the driver than data not reflecting a change in driving of the leaning vehicle for sense-of-value-conversion data 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 a driver than data not reflecting a change in driving of the analysis leaning vehicle by the driver.

[0036] With this configuration, the leaning-vehicie-traveling data strongly reflects a change in operation of the lêaning vehicle after détermination of the driver. In other words, the leaning-vehicie-traveling data includes many stimuli felt by a customer riding on the leaning vehicle. The stimuli felt by the customer affects évaluation by the customer. Furthermore, in the case of the leaning vehicle, the stimuli felt by the customer riding on the leaning vehicle hâve a large number of variations, By using such leaning-vehicie-traveling data, the customer-sense-of-value-analysis method according to the présent teaching can acquire more accurate data indicating a sense of value, whîle ensuring design flexibility of hardware resources of the data processing device.

[0037] The stimuli include not only a physical stimulus such as vibration received from the vehicle, but also a psychologie stimulus rëceivëd during a sequence of riding actions, such as a sense of discomfort stemming from a location of getting on or off the vehicle and a sense of discomfort stemming from waiting time.

[0038] in another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaning vehicle-traveling data for sense-of-value-conversion data includes at least one of leaningvehicle-operation-input data for sense-of-value-conversion data, leaning-vehicle-behavior data for sense-of-value-conversion data, or leaning-vehicie-iocation data for sense-ofvalue-conversion data, the leaning-vehicle-operation-input data for sense-of-valuecon version data being related to an operation input to the leaning vehicle for sense-ofvalue-conversion data, the leaning-vehicle-behavior data for sense-of-value-conversion data being related to a behavior of the leaning vehicle for sense-of-value-conversion data, the leaning-vehicie-iocation data for sense-of-value-conversion data being related to a location of the leaning vehicle for sense-of-value-conversion data. The analysisleaning-vehicle-traveling data includes at least one of leaning-vehicle-operation-input data for analysis (analysis-leaning-vehicle-operation-input data) related to an operation input to the analysis leaning vehicle, leaning-vehicle-behavior data for analysis (analysisleaning-vehicle-behavior data) related to a behavior of the analysis leaning vehicle, or leaning-vehicie-iocation data for analysis (ana!ysis4eaning-vehide4ocation data) related to a location of frie analysis leaning vehicle.

[0039] The leaning-vehicle-operation-input data is data related to an operation input by the driver, and thus, more strongly refiects 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, there is a large number of variations of operation.

The leaning-vehicle-behavior data and the leaning-vehicie-iocation data strongly refiect a resuit of an operation input by the driver. With this configuration, the leaning-vehicletraveling data strongly refiects a change in operation of the leaning vehicle after détermination of the driver, in other words, the leaning-vehicle-traveling data includes more stimuli feît by a customer riding on the leaning vehicle. Furthermcre, in the case of the leaning vehicle, the stimuli felt by the customer riding on the leaning vehicle hâve a larger number of variations, By using such leaning-vehicle-traveling data, the customersense-of-value-analysis method according to the présent teaching can acquire more accurate data indicating a sense of value, while ensuring design flexibility of hardware resources of the data processing device.

[0040] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably indudes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data indudes leaning-vehicletraveling-environment data for sense-of-value-conversion data, the leaning-vehicletraveling-environment data for sense-of-value-conversion data being related to a traveling environment in which the leaning vehicle for sense-of-value-conversion data travels. The analysis-leaning-vehicle-traveling data includes leaning-vehicle-travelingenvironment data for analysis (analysis-îeaning-vehicle-traveling-environment data) related to a traveling environment in which the analysis Ieaning vehicie travels.

[0041] The traveling environment data is considered to be an exampie of stress on a driver and a customer from the outside. The traveling environment data affects détermination of évaluation by the customer regarding his/her ride. Thus, the use of the traveling environment data makes it easier to analyse the stimuli received by the customer from the leaning-vehicle-traveling data. By using such leaning-vehicletraveling data, the customer-sense-of~value-analysis method according to the présent teaching can acquire more accurate data indîcating a sense of value of the customer, while ensuring design flexibility of hardware resources of the data processing device. Accordingly, the customer-sense-of-value-analysis method according to one embodiment of the présent teaching can analyze more accu rate ly the customeris sense of value.

[0042] In another aspect, the customer sense cf value analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-vaiue-conversion data includes a langer amount of data in traveling of the Ieaning vehicle for sense-of-value-conversion data on a public road than data in traveling of the ieaning vehicle for sense-of-value-conversion data on a place except for a public road. The analysis-leaning-vehicle-traveling data includes a iarger amount of data in traveling of the anaiysis ieaning vehicle on a public road than data rn traveling of the analysis ieaning vehicle on a place except for a public road.

[0043] While a driver traveling on a public road drives a Ieaning vehicle, the driver makes détermination more frequentiy, has a wide variation of options in détermination, and is iikely to be subjected to stress from the outside. Accordingly, traveling data of the Ieaning vehicle includes a Iarger number of variations. In traveling on a public road, a customer is also Iikely to be subjected to stress from the outside, wtrich affects his/her évaluation regarding the ride. Thus, the use of the leaning-vehicle-traveling data including a large amount of data in traveling on a public road makes it easier to analyze the stimuli received by the customer from the leaning-vehicle-traveling data. By using such leaning-vehicle-traveling data, the customer-sense-of-value-analysis method according to the présent teaching can acquire more précisé data indîcating a sense of value, while ensuring design flexibility of hardware resources of the data processing device.

[0044] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes data in a state where options of détermination by a driver are limited by vehicles around the leaning vehicie for se nse-of-value-con version data but some options are left. The anaîysis-îeaning-vehicletraveling data includes data in a state where options of détermination by a driver are limited by vehicles around the analysis leaning vehicie, but some options are left.

[0045] By using the leaning-vehicle-traveling data in a state where options of détermination by a driver are limited but some options are left, it is possible to more easily analyze the stimuli received by a customer from the leaning-vehicle-traveling data. By using such leaning-vehicle-traveling data, more accurate data indicating a sense of value can be acquired, while en surin g design flexibility of hardware resources of the customersense-of-value-analysis device.

[0046] In another aspect, the customer-sense-of-value-analysis method according to the présent ieaching preferabiy includes the fôiîowing configurations. The leaningvehicle-traveling data for sense-of-va lu e-con version data includes data in a state where no customer is aboard the leaning vehicie for sense-of-value-conversion data. The analysis-leaning-vehicle-traveling data includes data in a state where no customer is aboard the analysis leaning vehicie.

[0047] By using the leaning-vehicle-traveling data in a state where no customer is aboard the leaning vehicie, for example, the leaning-vehicle-traveling data before the customer gets on the leaning vehicie or after the customer gets off the leaning vehicie, it is possible to more easily analyze the physical or psychological stimuli received by the customer from the leaning-vehicle-traveling data. By using such leaning-vehicletraveling data, the customer-sense-of-value-analysis method according to the présent teaching can acquire more accurate data indicating a sense of value, while ensuring design flexibility of hardware resources of the data processing device.

[0048] in another aspect, the eustomer-sense cf-value analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes vehicle-type-related data related to a type of the leaning vehicie. The analysis-leaning-vehicle-traveling data includes vehicle-type-related data related to a type of the leaning vehicie.

[0049] The vehicle-type-related data includes data related to a manufacturer and a type of the leaning vehicie. A manufadurer of, and/or a type of, the leaning vehicie to a customer’s liking affect the customer’s preference. For exampie, a customer who prefers to luxury vehicles has a great demand for status, and his/her preference is highly status oriented. Thus, it is possible to acquire the customer’s sense-of-value data which is associated with the customer’s évaluation as to status.

[0050] In another aspect, the çusfomer-sense-of-value-analysis method according to i

the présent teaching preferabiy includes the following configurations. The customersense-of-value-analysis method according to the présent teaching stores the converted sense-of-value data. The customer-sense-of-value-analysis method according to the présent teaching generates the output-sense-of-value data by using a plurality of sets of the sense-of-valus data that has been stored.

[0051] By using the plurality of sets of sense-of-value data, more accurate data indicating a sense of value can be acquired, while ensuring design flexibility of hardware resources of the data processing device

[0052] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferabiy includes the following configurations. The output-senseof-value data is generated as sense-of-value data for data processing that is used for further data processing.

[0053] Accordingly, the sense-of-value data acquired by the customer-sense-of-valueanalysis method by using the analysis-leaning-vehicle-traveling data of the analysis leaning vehicle driven by an analysis target can be used for another data processing device,

[0054] As a resuit, data indicating a sense of value capable of being used for further data processing can be acquired, while ensuring design flexibility of hardware resources of the data processing device.

[0055] A customer-sense-of-value-analysis device according to the présent teaching includes: a sense-of-value-conversion-data acquirer configured to acquire sense-ofvalue-conversion-data which associâtes leaning-vehicle-traveling data, évaluation data and sense-of-value data of a customer, the ïeaning-vehicle-traveiîng data being traveling data of a leaning vehicle configured to lean rightward when tuming to the right and lean leftward when turning to the feft, the évaluation data showing évaluation by the customer; an analysrs-leaning-vehicle-traveüng-data acquirer configured to acquire analysis-leaningvehicle-traveling data that is traveling data of an analysis leaning vehicle; an analysisevaluation-data acquirer configured to acquire analysis évaluation data of a customer as an analysis target riding on the analysis leaning vehicle; a sense-of-value-data conventer configured to convert the acquired analysis-leaning-vehicle-traveling data and the acquired analysis évaluation data to sense-of-value data related to a sense of value of the customer; an output-sense-of-value-data generator configured to generate outputsense-of-value data for output by using the converted sense-of-value data; and an output-sense-of-value-dataoutput section configured to output the generated outpub sense-of-value data to be output. The sense-of-value-conversion-data acquirer uses leaning-vehicle-traveling data for sense-of-value-conversion data related to traveling data obtained when each of a plurality of drivers drives a leaning vehicle for sense-of-va lueconversion data, and évaluation data obtained from each of a plurality of customers riding on the leaning vehicle for sense-of-value-con version data when the traveling data is obtained, to thereby acquire, as the sense-of-value-conversion data, data in which the leaning-vehicle-traveling data, the évaluation data showing évaluation by the customer and sense-of-value data of the customer are associated. The sense-of-value-data converter converts the acquired analysis-leaning-vehicle-traveling data and the acquired analysis évaluation data to the sense-of-value data by using the acquired sense-of-va lueconversion data.

[0056] In another aspect, the customer-sense-of-value-analysis device according to the présent teaching preferably includes the following configurations. The sense-ofvalue-conversion data is data in which the sense-of-value data of the customer is associated with a preference of the customer, the preference of the customer being estimated from the leaning-vehicle-traveling data and the évaluation data of the customer.

[0057] In another aspect, the customer-sense-ôf-value-analysis device according to the présent teaching preferably includes the following configurations, The leaningvehicle-traveling data for sense-of-value-conversion data includes data related to traveling data obtained when the leaning vehicle for sense-of-value-conversion data with each of the plurality of customers aboard travels in a lean state, and the analysisleaning-vehicle-traveling data includes traveling data obtained when the analysis leaning vehicle with the customer as the analysis target aboard travels in a lean state.

[0058] In another aspect, the customer-sense-of-value-analysis device according to one embodiment of the présent teaching preferably includes the following configurations. The leaning-vehicle-traveling data for sense-of-value-conversion data includes a larger amount of data reflecting a change in driving of the leaning vehicle for sense-of-valueconversion data by the driver than data not reflecting a change in driving of the leaning vehicle for sense-of-value-conversion data by the driver, and the anaiysis-leaningvehicle-traveiing data includes a larger amount of data reflecting a change in driving of the analysis leaning vehicle by a driver than data not reflecting a change in driving ofthe analysis leaning vehicle by the driver.

[0059] In another aspect, the customer-sense-of-vaiuê-anaiysis device according to one embodiment of the présent teaching preferably includes the following configurations. The leaning-vehicle-traveling data for sense-of-value-conversion data includes at least one of leaning-vehicle-operation-inpui data for sense-of-value-conversion data, leaningvehicle-behavior data for sense-of-value-conversion data, or leaning-vehicle-iocation data for sense-of-value-conversion data, the !eaning-vehicle-ope ration-in put data for sense-of-value-conversion data being related to an operation input to the leaning vehicle for sense-of-value-conversion data, the ieaning-vëhiclë-bêhavior data for sense-ofvaiue-conversion data being related to a behavior of the leaning vehicle for sense-ofvaiue-conversion data, the leaning-vehicle-location data for sense-of-value-conversion data being related to a location of the leaning vehicle for sense-of-value-conversion data, The analysis-leaning-vehicle-traveling data includes at ieast one of analysisleaning-vehicle-operation-input data related to an operation input to the analysis leaning vehicle, analysis-leaning-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.

[0060] in another aspect, the customer-sense-of-vaîue-anaiysis device according to one embodiment of the présent teaching preferably includes the following configurations. The leaning-vehicle-traveling data for sense-of-value-conversion data further includes leaning-vehicle-traveling-environment data for sense-of-value-conversion data, the leaning-vehicle-traveling-environment data for sense-of-value-conversion data being related to a traveling environment in which the leaning vehicle for sense-of-valueconversion data travels. The analysis-ieaning-vehicîe-traveling data further includes analysis-leaning-vehicle-traveling-environment data related to a traveling environment in which the analysis leaning vehicle travels.

[0061] in another aspect, the customer-sense-of-value-analysis device according to one embodiment of the présent teaching preferably includes the following configurations. The output-sense-of-value data is generated as sense-of-vaiue data for data processing that is used for further data processing.

[0062] A data processing method using the sense-of-vaiue data according to one embodiment of the présent teaching is a data processing method using the output-senseof-value data generated as the sense-of-va|ue data for data processing in the customersense-of-value-analysis method described above. The data processing method acquires the output-sense-of-value data. The data processing method acquires first data different from the output-sense-of-value data. The data processing method according to the présent teaching generates second data by using the output-sense-ofvalue data and the first data, the second data being different from the output-sense-ofvalue data and the first data. The data processing method outputs the second data.

[0063] The sense-of-value data indicating a sense of value is highly versatile data indicating a use rts latent preference. The data processing method using the sense-ofvalue data includes data processing methods using preference data as described in

Patent Documents mentioned in Sackground 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 using preference 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.

[0064] Accordingly, the data processing method according to the présent teaching uses the acquired output-sense-of-value data that is highly versatile data indicating a useris latent preference and the First data different from the output-sense-of-value data to generate and output the second data different from the acquired output-sense-of-value data and the acquired first data. In this manner, the second data can be generated more accurately and output.

[0065] A data processing device according to one embodiment of the présent teaching is a data processing device using the output-sense-of-value data generated as the sense-of-value data for data processing in the customer-sense-of-value-analysis device described above. The data processing device includes: an output-sense-of-value-data acquirer configured to acquire the output-sense-of-value data; a first data acquirer configured to acquire first data, the first data being different from the output-sense-ofvalue data; a second data generator configured to generate second data by using the output-sense-of-value data and the first data, the second data being different from the output-sense-of-value data and the first data; and a second-data-output section configured to output the second data.

[0066] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0067] As used herein, the term and/or includes any and ail combinations of one or more ofthe associated listed items.

[0068] 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 preclude the presence or addition of one or more steps, operations, éléments, components, and/or groups thereof.

[0069] 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.

[0070] Unless otherwise defined, ail terms (including technical and scientific terms) used herein hâve the same meaning as commonly understood by one having ordinary ski II in the art to which this invention belongs.

[0071] It will be further understood that terms, such as those defined rn 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 disclosure and will not be interpreted in an idealized or overly formai sense unless expressly so defined herein.

[0072] In describîng 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 conjunotion with one or more, or in some cases ail, of the other disclosed techniques.

[0073] Accordingiy, for the sake of clarity, this description will refrain from repeating every possible combination of the individual steps in an unnecessary fashion. Nevertheless, the spécification and claims should be read with the understanding that such combinations are entirely within the scope of the invention and the claims, [0074] In this spécification, a customer-sense-of-value-analysis method, a customersense-of-value-analysis device, a data processing method using sense-of-value data, and a data processing device using sense-of-value data according to the present teaching will be described.

[0075] In the following description, numerous spécifie details are set forth in order to provide a thorough understanding ofthe present invention. It will be évident, however, to one skilled in the art that the présent invention may be practiced without these spécifie details.

[0076] 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.

[0077] [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 vehicie 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-wrieeled vehicles and four-wheeled vehicles as well as two-wheeled vehicles.

[0078] [Sense-of-Vaiue Data]

Sense-of-value data herein refers to data indicating a customer’s évaluation criteria determined by the customers preference and desire. In other words, the senseof-value data is highly versatile data indicating the customer’s latent preference. Specifically, the sense-of-va lue data includes data related to the customer’s évaluation crilerion indicating a degree of satisfaction of a preference, data related to the customer’s évaluation criterion indicating a degree of desire for health, data related to the customer’s évaluation criterion indicating a degree of energy-saving desire, and data related to the customer’s évaluation criterion indicating a degree of social-life-related desire. Basically, the customer refers to an individuel; however, it may refer to a group of a plurality of customers.

[0079] [Evaluation Data]

Evaluation data herein refera to data related to évaluation for a driver and a vehicle when a customer rides on the vehicle. The évaluation data is, for example, évaluation related to the driver and/or the vehicle when the customer rides on the vehicle, and overall évaluation felt by the customer is given on a five-point scale. Five (5) is the highest, and the évaluation dégradés as the number decreases. The évaluation data may further include a degree of trust, comfort, and cost effectiveness including speed. An évaluation axis in the évaluation data is not limited to one. The évaluation data may include évaluation axes corresponding to a plurality of évaluation items.

[0080] [Vehicle Traveling Data]

Vehicle traveling data herein refers to data related to traveling of a Ieaning vehicle. Specifically, the vehicle traveling data includes at least one of îeaning-vehicleoperation-input data related to a driving input to a Ieaning vehicle by a driver, leaningvehicle-behavior data related to a behavior of the ieaning vehicle, leaning-vehicle-location data related to a traveling location of the Ieaning vehicle, leaning-vehicle-travelingenvironment data related to a traveling environment of traveling of the Ieaning vehicle, or vehicle-type-information data of the Ieaning vehicle, for example. The leaning-vehicletraveling data may include processed data obtained by processing, for example, the leaning-vehicle-operation-input data, the leaning-vehicle-behavior data, the leaningvehicle-location data, the leaning-vehicle-traveling-environment data, and the vehicletype-information data of the Ieaning vehicle. The leaning-vehicle-traveling data may include processed data obtained by processing, for example, the leaning-vehicle-drivinginput data, the leaning-vehicle-behavior data, the leaning-vehicle-location data, the leanjngwehicie-traveiing-snvircnment data, and the vehicle-type-information data of the Ieaning vehicle with other data.

[0081] [Leaning-Vehicie-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 iighting switch. The leaningvehicle-driving-input data is data related to a driving input by the driver, and thus, more strongly reflects a result of détermination by the driver. In the leaning vehicle, there are a large number of types of driving by the driver and flexibility in options by the driver during driving is high. Thus, the leaning-vehicle-driving-input data tends to hâve numerous variations. The ieanirig-vehicie-driving-input data may include processed data obtained by processing data acquired from, for example, a sensor. The leaning-vehicledriving-input data may include processed data obtained by processing data acquired from, for example, the sensor with other data.

[0082] [Leaning-Vehicle-Behavior Data]

The leaning-vehicie-behavior data herein is data related to a behavior of a leaning vehicle caused by an operation input by a driver while the leaning vehicle is driven by the driver. Specifically, the leaning-vehicie-behavior data includes, for exampie, an accélération, a velocity, and an angle that vary when the driver drives the leaning vehicle with a customer as an analysis target aboard the leaning vehicle. That is, the leaning-vehicie-behavior data is data showing a behavior of the leaning vehicle occurring, for exampie, in a case where the driver 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.

[0083] As described above, the leaning-vehicie-behavior 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 leaning-vehicie-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 Iighting switch. The leaning-vehicie-behavior data strongly reflects a resuit of an operation input by the driver. Thus, the leaning-vehicie-behavior data also tends to hâve numerous variations. The leaning-vehicie-behavior data may include processed data obtained by processing data acquired from, for example, a sensor, The leaning-vehide-behavior data may include processed dala obtained by processing data acquired from, for example, the sensor with other data.

[0084] [Leaning-Vehicle-Location Data]

The leaning-vehicfe-location data herein is data related to a location of a leaning vehicle. For exampie, 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-iocation data strongly reflects a resuit of an operation input of a driver. Thus, the leaning-vehicle-location data also tends to hâve numerous variations, The leaning-vehicle-location data may include processed data obtained by processing data acquired from, for exampie, a sensor. The leaning-vehicie-location data may include processed data obtained by processing data acquired from, for example, the sensor with other data.

[0085] [Leaning-Vehide-Traveling-Environ ment Data]

The leaning-vehicle-traveling-environment data herein 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-vehicietraveling-environment data can be used for analyzing a customer’s sense of value, together with the leaning-vehicie-driving-înput data, the leaning-vehicle-behavior data, and the leaning-vehicle-location data.

[0036] The information on road situations indu des 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 parksd on Street s. Précision of the information increases when being combined with time frames. The information on road situations includes information on roads that easily flood upon squalis.

[0087] The leaning-vehicle-traveling-environment data is considered to be an example of stress on the driver and the customer from the outside. The traveling environment data affects détermination of the driver. The leaning-vehicle-traveling-environment data affects driving of the driver. Thus, the use of the traveling environment data increases variations of traveling data of the ieaning vehicle.

[0088] The leaning-vehicie-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-vehicle-traveling-environment data is an external-environment17 récognition device mounted on the leaning vehicle. More specificalîy, the configuration for acquiring the leaning-vehicle-traveling-environment data is, for example, a caméra or a radar, Altemativeiy, the configuration for acquiring the leaning-vehicie-travelingenvironment data is a communication device. More specificalîy, the configuration for 5 acquiring the leaning-vehicle-traveling-environment data is a vehicle-to-vehicle communication device or a road-to-vehicle communication device. The leaning-vehicietraveling-environment data can also be obtained through the Internet, for example.

[0089] [Vehicle-Type-Related Data]

The vehicle-type-related data herein includes data related to a manufacturer 10 and a type of a leaning vehicle. The vehicle-type-related data is used to distinguish traveling ieaning vehicles from each other. A manufacturer of, and/or a type of, a leaning vehicle to a customer’s iiking affect the customer’s preference. For example, a customer who préféra to luxury vehicles has a great demand for status, and his/her preference is highiy status oriented.

[0090] [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.

[0091] [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 partially included.

[0092] For exampîe, the expression “including a larger amount of data reflecting a change in operation of a leaning vehicle for sense-of-value-conversion data by a driver 25 than data not reflecting a change in operation cf the leaning vehicle for sense-of-valueconversion data” may include a case where data not reflecting a change in operation of the leaning vehicle for sense-of-value-çonversion data is not included at al). For example, the expression “including a larger amount of data reflecting a change in operation of a leaning vehicle for sense-of-value-conversion data by a driver than data 30 not reflecting a change in operation of the leaning vehicle for sense-of-value-conversion data” may include a case where data not reflecting a change în operation of the leaning vehicle for sense-of-value-conversion data is partiaHy included.

[0093] For example, the expression “a larger amount of data reflecting a change in operation of a leaning vehicle for analysis (analysis leaning vehicie) by a driver than data 35 not reflecting a change in operation of the analysis leaning vehicle” may include a case where data not reflecting a change in operation of the analysis leaning vehicle is not included at ail. For example, the expression “a larger amount of data reflecting a change in operation of an analysis Ieaning vehicle by a driver than data not reflecting a change in operation of the analysis ieaning vehicle” may include a case where data not reflecting a change in operation ofthe analysis Ieaning vehicle is partially included.

[0094] For exampie, the expression “including a larger amount of data in traveling of a Ieaning vehicle for sense-of-value-conversion data on a public road than data in traveling of the Ieaning vehicle for sense-of-value-conversion data on a place except for a public road may include a case where data in traveling of the Ieaning vehicle for sense-ofvalue-conversion data on a place except for a public road is not included at ail. For exampie, the expression including a larger amount of data in traveling of a Ieaning vehicle for sense-of-value-conversion data on a public road than data in traveling of the Ieaning vehicïe for sense-of-value-conversion data on a place except for a public road” may include a case where data in traveling of the Ieaning vehicle for sense-of-valueconversion data on a place except for a public road is partially included.

ADVANTAGEOUS EFFECTS OF INVENTION

[0095] According to the cusiomer-sense-of-vaîue-analysis method of one embodiment of the présent teaching, it is possible to provide a customer-sense-of-value-analysis method capable of acquiring highly versatile data indicating a useris latent preference, what is called sense-of-value data, while ensuring design fiexibility of hardware resources of a data processing device.

BRI EF DESCRIPTION OF DRAWiNGS

[0096] [FIG. 1] FIG. 1 is a view illustrating a schematic configuration of a customersense-of-value-analysis device according to a first embodiment ofthe présentteaching.

[FIG. 2] FIG. 2 is a flowchart depicting a customer-sense-of-value-analysis method according to the first embodiment ofthe présent teaching.

[FIG. 3] FIG. 3 is a view illustrating a schematic configuration of a customersense-of-value-analysis system according to a second embodiment.

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

[FIG. 5] FIG. 5 is a flowchart depicting an example of a method of acquiring sense-of-value-conversion data according to the first embodiment of the présent teaching.

DESCRIPTION OF EMBODIMENT

[0097] Embodiments will be described hereînafter with reference to the drawings. The dimensions of components in the drawings do not strictly represent actual dimensions of the components and dimensions! proportions of the components, for example.

[0098] < First Embodiment^ (Customer-Sense-of-Vaiue-Analysis Device)

Fig. 1 illustrâtes a schematic configuration of a customer-sense-of-valueanalysis device 1 according to a first embodiment of the présent teaching. The customer-sense-of-value-analysis device 1 is a device for anaiyzing sense-of-value data of a customer as an analysis target. The customer-sense-of-value-analysis device 1 of this embodiment acquires leaning-vehicle-traveling data for analysis (analysisrteaningvehicle-traveiing data), including traveling data while the customer as an analysis target rides on a Ieaning vehicle X, and évaluation data for anaiysis (analysis évaluation data) of the customer regarding his/her ride. The customer-sense-of-vaiue-analysis device 1 then converts the acquired anaiysis-leaning-vehicle-traveiing data and the acquired analysis évaluation data to sense-of-value data related to a sense of value of the customer as an analysis target, by using sense-of-value-conversion data. The customer-sense-of-value-analysis device 1 generates output-sense-of-value data from the sense-of-value data, and outputs the generated output-sense-of-value data. There are a case where the customer-sense-of-value-anatysis device 1 of this embodiment outputs, as the output-sense-of-value data, the sense-of-value data as it is, and a case where it converts the sense-of-value data to, for example, data that is easy to process as data to be provided, and ouîputs the converted data.

[0099] Analysis of a sense of value in this embodiment refers to anaiyzing a customer¹s évaluation criteria for satisfaction of a preference, desire for health, energysaving désiré, social-life-related desire, and so forth. The sense-of-value data refers to data indîcating a customer’s évaluation criteria for his/her preference.

[0100] This sense-of-value data is included in sense-of-value data obtained by converting leaning-vehicle-traveling data of the Ieaning vehicle X obtained when a customer as an analysis target rides on the Ieaning vehicle X as a passenger and analysis évaluation data of the customer regarding his/her ride by a sense-of-va!ue-data converter 40 described îater. The sense-of-vaîue data includes sense-of-value data related to a preference of the customer as an analysis target.

[0101] The leaning-vehicle-traveling data in this embodiment is data related to traveling of a Ieaning vehicie. The Ieaning-vehide-traveling data refers to data in which a latent preference of the customer appears in data related to traveling of the Ieaning vehicle obtained when a driver drives the leaning vehicle.

[0102] Specifically, the !eaning-vehide-traveiing data includes, for example, leaningvêhide-drîving-input data reiated to a driving input to a îeaning vehicie by a driver, leaning-vehicle-behavior data related to a behavior of the leaning vehicle, leaningvehicie-iocation data related to a traveling location of the leaning vehicle, vehicle-related data of the leaning-vehide, and a leaning-vehide-traveiing-enviFonment data related to a traveling environment of traveling of the leaning vehicle, The leaning-vehicie-traveling data may include data other than the ieaning-vehicle-driving-input data, the leaningvehide-behavior data, the leaning-vehide-focation data, and the leaning-vehidetravelîng-environment data. The leaning-vehide-traveling data may only include one or more of the ieaning-vehicle-driving-input data, the leaning-vehicle-behavior data, the leaning-vehicie-location data, or the îeaning-vehicie-iraveiing-environment data.

[0103] For example, in a case where the leaning vehide is a leaning vehicle for senseof-value-conversion data, the leaning vehicle-traveling data is leaning-vehicie-traveling data for sense-of-value-conversion data, the acquired leaning-vehide-driving-input data is leaning-vehicle-driving-fnput data for sense-of-value-conversion data, the acquired leaning-vehide-behavior data is leaning-vehicle-behavior data for sense-of-valueconversion data, the acquired leaning-vehide-location data is leaning-vehicle-location data for sense-of-value-conversion data, the acquired vehicle-related data of the leaning vehicle is vehicle-related data for sense-of-value-conversion data, and the acquired leaning-vehicle-traveling-environment data is leaning-vehicle-traveling-environment data for sense-of-value-conversion data.

[0104] For example, in a case where the leaning vehide is the analysis îeaning vehicle X, the leaning-vehide-traveling data is ieaning-vehide-traveling data for analysis (analysis-leaning-vehicfe-travelfog data), the ieaning-vehide-driving-input data is teaningvehide-driving-input data for analysis (anafysis-leanîng-vehide-driving-input data), the leaning-vehicle-behavior data is leaning-vehicle-behavior data for analysis (analysisleaning-vehicle-behavior data), the leaning-vehide-location data is leaning-vehidelocation data for analysis (analysis-leaning-vehicle-location data), the vehide-related data of the leaning vehide is vehicle-related data for anaîysis (analysis-vehicle-related data), and the leaning-vehide-traveîing-environment data is lean ing-vehide-trave lin genvironment data for analysis (analysis-leaning-vehicle-traveling-environment data).

[0105] The leaning-vehicie-traveling data may include processed data obtained by processing, for example, the leaning-vehide-driving-input data, the leaning-vehiclebehavior data, the îeaning-vehicle-tocation data, and the ieaning-vehicle-travelingenvironment data, The leaning-vehide-traveling data may include processed data obtained by processing, for example, the leaning-vehide-driving-input data, the leaningvehicle-behavior data, the leaning-vehide-location data, and the leaning-vehîcletraveling-environment data with other data.

[0106] The leaning-vehicle-driving-input data 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 indude data related to, for example, an accélérator 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-vehicle-drivinginput data may indude data related to, for example, operations of various switches such as a hom switch, a winker switch, and a lighting switch.

[0107] The leaning-vehide-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-vehide-driving-input data also reflects personality of the driver,

[0108] The personality herein refers to individuality determined based on, for example, psychoîogical state, character, or tempérament of an individual, Specifically, the personality may include five éléments of neuroticism, extroversion, openness to expérience, cooperativeness, and integrity. The personality may also indude six character types such as dereism, conformity, stickiness, demonstrativeness, hypersensitivity, and overconfidence. The personality may also indude tempéraments of novelty désiré, reward dependence, damage avoidance, and persistence, and characters of self-orientation, cooperativeness, and self-transcendence.

[0109] The lean ing-vehicle-driving-in put data may include processed data obtained by processing data acquired from, for example, a sensor, The leaning-vehicle-driving-input data may indude processed data obtained by processing data acquired from, for example, the sensor with other data,

[0110] The leaning-vehicle-behavior data is data related to a behavior of a leaning vehicle caused by an operation input by a driver while the leaning vehicle is driven by the driver, Spedfically, the leaning-vehicle-behavior data includes, for example, an accélération, a velociiy, 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 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.

The leaning-vehicle-behavior data may include not only the data concerning an accélération, a velocity, and an angle of the leaning vehicle as described above, but also an operation occurring in the leaning vehicle due to, for example, a switch operation 5 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 leaning-vehicle-behavior data strongly refiects a resuit of a driving input by the driver. Thus, the leaning-vehicle-behavior data also tends to strongly refiect stimuli to a 10 customer riding on the leaning vehicle as a passenger. 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 inciude processed data obtained by processing data acquired from, for example, frie sensor with other data. [0111] The leaning-vehicîe-îocation data is data related to a traveling location of a 15 leaning vehicle. For example, the leaning-vehicie-iocation data can be detected based on, for example, information from a GPS, or a communication base station of a communication portable terminal. The leaning-vehicie-iocation data can be calculated by various positioning techniques, a SLAM, or the like. The leaning-vehicie-iocation data strongly refiects a resuit of a driving input of a driver. Thus, the leaning-vehicle20 location data also tends to strongly refiect stimuli to a customer. The leaning-vehicieiocation data may include processed data obtained by processing data acquired from, for example, a sensor. The leaning-vehicie-iocation data may inciude processed data obtained by processing data acquired frorn, for example, the sensor with other data. [0112] The leaning-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-traveïingenvironment data can be used for analyzing a sense of value of a customer as an 30 analysis target, together with the leaning-vehicle-driving-input data, the leaning-vehiclebehavior data, and the leaning-vehicie-iocation data.

[0113] The information on road situations includes information on roads (régions) 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 this 35 information increases when being combined with time frames. The information on road situations includes information on roads that easily flood upon squalls.

[0114] The vehicie-related data includes, for exampie, information data associated with a manufacturer and a type of a leaning vehicle, The vehicle-related data is used to distinguish travelling leaning vehicles from each other. A manufacturer of, and/or a type of, a vehicle to a customer’s lîking affect the customer’s preference.

[0115] The leaning-vehicle-traveling-environment data is considered to be an example of stress on a driver and a customer from the outside. The leaning-vehicle-travelingenvironment data affects détermination of the driver. Thus, the use of the leaningvehicle-traveling-environment data causes traveling data of a leaning vehicle to more sirongly refiect stimuli that the customer receives from the outside, such as stress. A traveling environment of the leaning vehicle affects the purpose of use and frequency of use of the leaning vehicle. The use of the leaning-vehide-traveting-environment data causes the traveling data of the leaning vehicle to refîect stimuli that are given to the customer and hâve relevance to the purpose of use and frequency of use of the leaning vehicle.

[0116] The leaning-vehicle-traveling data for sense-of-value data includes a larger amount of data reflecting a change in operation ofthe leaning vehicle for sense-of-valueconversion data by a driver than data not reflecting a change in operation of the leaning vehicle for sense-of-value-conversion data. The analysis-leaning-vehicle-traveling data preferabiy includes a larger amount of data reflecting a change in operation of the analysis leaning vehicle by a driver than data not reflecting a change in operation of the analysis leaning vehicle,

[0117] The leaning-vehicle-traveling data strongly refiects a change in operation ofthe leaning vehicle after détermination of the driver. In other words, the leaning-vehicletraveling data includes many stimuli felt by a customer riding on the leaning vehicle. Furthermore, in the case of the leaning vehicle, the stimuli felt by the customer riding on the leaning vehicle hâve a large number of variations. By using such leaning-vehicletraveling data, in this embodiment, more accu rate data indicating a sense of value can be acquired, while ensuring design flexibility of hardware resources of the customer-senseof-value-analysis device 1.

[0118] The stimuli includes not only a physical stimulus such as vibration received from the vehicle as described above, but also a psychologie stimulus received during a sequence of riding actions, such as a sense of discomfort stemming from a location of getting on or off the vehicle and a sense of discomfort stemming from waiting time.

[0119] The customer-sense-of-value-ana!ysis device 1 includes a sense-of-valueconversion-data acquirer 10, an analysis-leaning-vehicle-traveling-data acquirer 20, an analysis-evaluation-data acquirer 30, the sense-of-value-data converter 40, an output sense-of-value-data generator 50, a data output section 60 and a data memory 70. The customer-sense-of-value-analysis device 1 of this embodiment is, for example, a portable terminal held by an analysis target. The customer-sense-of-vaiue-analysis device 1 may be an arithmetic processing unit that acquires data through communication and performs a computation process.

[0120] The analysis-leaning-vehicle-traveling-data acquirer 20 acquires leaningvehicle-traveling data (analysis-leaning-vehicle-traveling data) when a driver drives the leaning vehicle X with a customer as an analysis target aboard.

[0121] The analysis-leaning-vehicle-traveling-data acquirer 20 acquires data included in leaning-vehicle-traveling data of the leaning vehicle X when the driver drives the leaning vehicle X with the customer aboard, that is, analysis-leaning-vehicle-driving-input data, analysis-ieaning-vehicle-behavior data, analysis-leaning-vehicle-location data, analysis-leaning-vehicle-traveling-environment data, and so forth.

[0122] The analysis-leaning-vehicls-traveling-data acquirer 20 may acquire, for example, driving by the driver of the leaning vehicle X with the customer aboard as an operation signal to thereby acquire the analysis-leaning-vehicle-driving-input data. Specifically, the analysis-leaning-vehicie-traveling-data acquirer 20 may acquire data related to an operation input by the driver in the leaning vehicle X, that is, 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, 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 vehicle X.

[0123] The analysis-leaning-vehiciê-traveling-data acquirer 20 may acquire, for example, data including an accélération, a velocity, and an angle of the leaning vehicîe X that change when the driver of the leaning vehicle X with the customer aboard drives the leaning vehicle X, as analysis-leaning-vehicle-behavior data. The anaîysis4eaningvehicle-traveling-data acquirer 20 acquires the analysis-leaning-vehicle-behavior data by, for example, a gyro sensor. The analysis-leaning-vehicle-behavior data is data showing a behavior of the leaning vehicle X occurring in a case where the driver of the leaning vehicle X perforons an accelerator operation or a brake operation to accelerate or decelerate the leaning vehicle X, or in a case where steering of the leaning vehicle X or a posture change including a positional change of the center of gravity is performed, for example.

[0124] The analysisrieaning-vehicle-traveling-data acquirer 20 may acquire an operation occurring in the leaning vehicîe X by, for example, a switch operation performed on the leaning vehicle X by the driver of the leaning vehicle X, as the leaning vehicle-behavior data. That is, the analysis-leaning-vehicle-traveling-data acquirer 20 may acquîre data reiated to an operation occurring in the leaning vehicle X by, for example, operations of various switches such as a horn switch, a wlnker switch, and a lighting switch, as the analysis-leaning-vehicle-behavior data. These sets of data are transmitted from the leaning vehicle X to the customer-senseof valueanaiysis device 1. [0125] The analysis-ieaning-vehicle-traveling-data acquirer 20 may acquire anatysisleaning-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 an alysïs-leaning-vehicle-location data can be calculated by various positioning techniques, a SLAM, or the like.

[0126] The analysis-leaning-vehicle-traveling-data acquirer 20 may acquire the analysis-leaning-vehicie-iraveling-environmenÎ data from, for exampie, map data. The map data may be associated with, for exampie, 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 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 ruie information on traveling on a road.

[0127] The analysis-leaning-vehicle-traveling-data acquirer 20 may acquîre the analysis-leaning-vehicle-traveüng-environment data by, for example, an externaienvironment-recognition device mounted on the ieaning vehicle X. More specifically, the analysis-ieaning-vëhiciê-trâveling-dâta acquirer 20 may acquire the anaîysis-leaningvehicle-traveling-environment data from a caméra or a radar, for exampie. The analysisleaning-vehicfe-traveling-data acquirer 20 may also acquire the analysis-ieaning-vehicletraveling-environment data by, for example, a communication device. More specifically, the anaiysis-leaning-vehicle-traveling-data acquirer 20 may acquire the analysis-leaningve h icle-traveling-environment data by a vehicle-to-vehicle communication device or a road-to-vehicle 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 analysis-leaning-vehîcle-travelingenvîronment 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.

[0128] The analysis-evaluation-data acquirer 30 receives évaluation data that represents the évaluation by the customer from a portable terminal such as a smartphone held by the customer. The évaluation data is évaluation related to the driver and the vehicle when the customer rides on the vehicle, and for example, overall évaluation felt by the customer is given on a five-point scaie, for exampie. Five (5) is the highest, and évaluation dégradés as the number decreases. The évaluation data may further include a degree of trust, comfort, and cost effectiveness including speed, that is, the shortness of time to reach a destination.

[0129] The sense-of-value-conversion-data acquirer 10 acquires sense-of-valueconversion data for converting leaning-vehicle-traveling data of the leaning vehicle X that the customer as an analysis target described above rides on and analysis évaluation data to sense-of-value data.

[0130] The sense-of-value-con version data are data in which sense-of-value data of customers indicating the customers’ senses of value, leaning-vehicle-traveling data and évaluation data of the customers are assocîated, based on the leaning-vehicle-traveling data obtained when the plurality of customers rides on a plurality of leaning vehicles, and the évaluation data of the customers regarding their rides.

[0131] The sense-of-value-conversion data is generated, for example, by the steps as described below. For example, a userts preference is analyzed from a driveris driving characteristic analyzed from leaning-vehicle-traveling data and from évaluation regarding the ride. By analyzing a relevance between the analyzed preference and the driving characteristic, the sense-of-value-conversion data is then generated as data assocîating the leaning-vehicle-traveling data, the évaluation data and sense-of-value data indicating a sense of value.

[0132] With reference to Fig. 5, an example of a method of acquiring sense-of-valuecon version data, conducted by the sense-of-value-conversion-data acquirer 10, will be described. Fig. 5 is a flowchart depicting an example of the method of acquiring the sense-of-value-conversion data.

[0133] First, the sense-of-value-conversion-data acquirer 10 acquires leaning-vehicletraveling data for sense-of-value-conversion data. The leaning-vehicle-traveling data for sense-of-value-conversion data are data obtained when a plurality of drivers drives leaning vehicles for sense-of-value-conversion data with customers aboard and stored in the data memory 70 (Step SC1).

[0134] Next, the sense-of-value-conversion-data acquirer 10 analyzes driving characteristics by using the acquired leaning-vehicle-traveling data (Step SC2). The driving characteristics are, for example, a degree of trust, comfort and cost effectiveness.

[0135] Subsequently, the sense-of-value-conversion-data acquirer 10 acquires évaluation data for sense-of-value-conversion data of a plurality of customers regarding their rides on the leaning vehicles for sense-of-value-conversion data, by using the acquired leaning-vehicle-traveling data, where the leaning vehicles for sense-of-valuecon version data are leaning vehicles used to analyze the driving characteristics (Step SC3).

[0136] Nest, the sense-of-value-conversion-data acquirer 10 analyzes préférences of the customers from the analyzed driving characteristics and the évaluation data (Step SC4).

[0137] Subsequently, the sense-of-value-conversion-data acquirer 10 associâtes the préférences of the customers with sense-of-value data that control desire types of the customers. Wîth this processing, the sense-of-value-conversion-data acquirer 10 generates sense-of-value-conversion data which associate the leaning-vehicle-traveling data, the évaluation data and the sense-of-value data of the customers (Step SC5). The sense-of-value-conversion-data acquirer 10 acquires the generated sense-of-valueconversion data (Step SCS). Thereafter, this flow is fmished (end).

[0138] The driving characteristic includes a degree of trust, comfort and cost effectiveness. For example, the degree of trust is obtained by performing an analysis from a driveris skill and the frequency of driving in compliance with law, based on leaningvehicle-traveling data of the driver. Specifically, the degree of trust can be determined, for example, by using leaning-vehicle-location data, leaning-vehicle-traveling-environment data including map data, and leaning-vehicle-behavior data, of the leaning vehicle X, in the leaning-vehicle-traveling data. A criierion for the degree of trust in a driver is calculated based on degrees of trust in a plurality of drivers.

[0139] The comfort is obtained, for example, by calcuîating a swinging level of a body and a vibration level from leaning-vehicle-traveling data of a plurality of drivers. Leftand-jright movement, up-and-down movement and back-and-forth movement are calculated from the leaning-vehicle-traveling data, and based on these calculation results, the swinging level of a body is then calculated. The vibration level is calculated by obtaining, for example, an accélération in an up-down direction from the leaning-vehicletraveling data. A criterion for the comfort is calculated based on the swinging level of a body and the vibration level.

[0140] The cost effectiveness is calculated by, for example, the shortness of time to reach a destination and speed, obtained from iêaning-vehicle-traveling data of a plurality of drivers.

[0141] The présent embodiment ailows a customer’s preference to be estimated by analyzing a relationship between évaluation data of the customer and a driving characteristic of a driver of a vehicle with the customer aboard. For example, when a customer rides on a vehicie of a driver whose driving characteristic is rated high in a degree of trust, and the customer highly évaluâtes the driver, it can be estimated that the customer has a strong preference for the degree of trust. Likewise, when a customer rides on a vehicie of a driver whose driving characteristic is rated high in comfort, and the customer highly évaluâtes the driver, it can be estimated that the customer has a strong preference for the comfort. When a customer rides on a vehicie of a driver whose driving characteristic is rated high in cost effectiveness, and the customer highly évaluâtes the driver, it can be estimated that the customer has a strong preference for the cost effectiveness.

[0142] Thus, a customer's preference can be estimated from a relationship between évaluation ofthe customer and a driving characteristic based on leaning-vehicle-traveling data. By obtaining évaluation from a plurality of cusiomers and leaning-vehicle-traveling data from a plurality of drivers, it is possible to achieve a nonarbitrary, versatile relevance. [0143] A customer’s preference can be associated with a sense of value controlling the customer’s desire type. For example, in a case of a customer who has a strong preference for the degree of trust, a relationship with a strong desire for health can be obtained as his/her sense of value. In a case of a customer who has a strong preference for the cost effectiveness, a relationship with a strong desire for energy saving can be obtained as his/her sense of value. In a case of a customer who is highly oriented to status and the comfort, a relationship with a strong social-life-retated desire can be obtained as his/her sense of value. Sense-of-value-conversion data to analyze a sense of value are obtained based on these relationships.

[0144] Status orientation affects a customer’s preference. The status orientation is determined, for exampie, based on a manufacturer of, and/or a type of, a vehicie to a customer’s liking. Specifically, it can be estimated that a customer who prefers to luxury vehicles has a great demand for status. Information on a type of a leaning vehicie can be associated with évaluation as to status by a customer.

[0145] The sense-of-value-conversion data may be data previously generated and stored in the data memory 70, or data generated by the sense-of-value-conversion-data acquirer 10. To generate the sense-of-value-con version data in the sense-of-va lue conversion-data acquirer 10, the data memory 70 stores leaning-vehicle-traveling data for sense-of-value-conversion data obtained when a plurality of drivers drives leaning vehicles for sense-of-value-con version data with customers aboard, évaluation data for sense-of-value-con version data of the plurality of customers regarding their rides, and data which associate the driving characteristics of the drivers of the leaning vehicles with senses of value of the customers.

[0146] The sense-of-value-conversion-data acquirer 10 reads out leaning-vehicletraveling data for sense-of-value-conversion data, and évaluation data for sense-of-valueconversion data regarding the ride from the data memory 70. The sense-of-valueconversion-data acquirer 10 perforons an analysis of a driving characteristîc and an analysis of a customer’s preference to thereby generate sense-of-value-conversion data that associâtes the leaning-vehicle-traveling data, the customer’s évaluation data and sense-of-value data indicating the customer’s sense of value.

[0147] The sense-of-vaiue-conversion-data acquirer 10 may update the sense-ofvalue-conversion data with acquired leaning-vehicle-traveling data and sense-of-value data,

[0148] The sense-of-value-data converter 40 converts analysis-Seaning-vehîcletraveling data acquired by the analysis-leaning-vehicle-traveling-data acquirer 20 and analysis évaluation data acquired by the analysis-evaluation-data acquirer 30 to senseof-value data by using the sense-of-value-conversion data described above. At this time, the sense-of-value-data converter 40 ranks a customer as an analysis target with regard to respective éléments of a degree of trust, comfort cost effectiveness and status orientation 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 sense-of-value-data converter 40 may classify the customer into a plurality of types by using results of the ranking with each of the éléments described above, and use results of the classification as the sense-of-value data,

[0149] The output-sense-of-value-data generator 50 generates output-sense-of-value data, by using sense-of-value data converted by the sense-ôf-vâlue-dâtâ converter 40. The output-sense-of-value data is data to be output from the customer-sense-of~valueanalysis device 1. The output-sense-of-value data may bs the same as the sense-ofvalue data, or data converted to data required as output data of the customer-sense-ofvalue-analysis device 1 by using the sense-of-value data.

[0150] The output-sense-of-value-data generator 50 may perform data processing on the sense-of-value data to generate output-sense-of-value data. For example, the output-sense-of-value-data generator 50 may generate output-sense-of-value data by storing the sense-of-value data in the data memory 70 and using sense-of-value data extracted from the sense-of-value data stored in the data memory 70. Specifically, for example, the output-sense-of-value-data generator 50 may generate output-sense-ofvalue data from sense-of-value data in a given period stored in the data memory 70.

[0151] The data output section 60 outputs output-sense-of-value data generated by the output-sense-of-value-data generator 50 to the outside of the customer-sense-of30 value-analysis device 1.

[0152] With the foregoing configuration, the eu stomer-sense-of-value-analysis device 1 can analyse a customer’s sense of value by using ieaning-ve'nicïe-traveîing data of the Ieaning vehicle X with the customer as an analysis target aboard and évaluation data at that time, and output a resuit of the analysis as output-sense-of-value data. This outputsense-of-value data can be recognized as one data item indicating the customer’s sense of value.

[0153] (Customer-Sense-of-Value-Anaiysis Method)

Next, with reference to Fig. 2, a customer-sense-of-va lue analysis method conducted by the customer-sense-of-value-analysis device 1 having the foregoing configuration will be described. Fig. 2 is a flowchart depicting an analysis of a customer’s sense of value.

[0154] First, the analysîs-leaning-vehicle-traveüng-data acquirer20 acquires leaning-vehicle-traveling data of a Ieaning vehicle X at an analysis-data-acquiring step (step SA1). The analysis-leaning-vehicle-traveling data includes, for example, analysisleaning-vehicle-driving-input data, analysis-leaning-vehicle-behavror data, analysisieaning-vehicle-location data, analysis-leanîng-vehicie-traveling-environment data, and so forth.

[0155] The analysis-leaning-vehicle-traveling data may include data other than the analysis-leaning-vehicle-driving-input data, the analysis-leaning-vehicle-behavior data, the analysis-leaning-vehicle-iocation data, and the analysis-leaning-vehicle-travelingenvironment data. The analysis-ieaning-vehicle-traveling data may only include one or more of the analysis-îeaning-vehicle-driving-input data, the analysis-leaning-vehiclebehavior data, the analysis-leaning-vehicle-location data, or the analysis-leaning-vehicletraveling-environment data.

[0156] Next, the analysis-evaluation-data acquirer 30 acquires évaluation data of a customer at the analysis-data-acquiring step (step SA2). The évaluation data is évaluation data related to a driver and a vehicle when the customer rides on the vehicle, and is, for example, data that provides overall évaluation felt by the customer on a fivepoint scale, for example.

[0157] Subsequently, the sense-of-value-data converter 40 converts the acquired leaning-vehicle-traveling data and the acquired évaluation data to sense-of-vaiue data by using sense-of-value-conversion data at a sense-of-vaiue-data-conversion step (step SA3). The sense-of-value-conversion data are data generated by associating leaningvehicle-traveling data, évaluation data and sense-of-value data indicating a sense of value, based on leaning-vehicle-traveling data including traveling data of a plurality of riders who opérâtes leaning vehicles with customers aboard, and évaluation data of the plurality of customers regarding their rides. For example, the sense-of-value data is data indicating a sense of value of a customer as an analysis target with regard to each of the éléments of a degree of trust, comfort, cost effectiveness and status orientation.

[0158] Next, the output-sense cf value-data generator 50 generates output-sense-ofvaîue data by using the sense-of-value data after the conversion at an outputting step (step SA4).

[0159] The data output section 60 outputs the generated output-sense-of-va!ue data (step SA5). Thereafter, this flow is finished (end).

[0160] The output-sense-of-value data thus output is related to a customer’s preference, and may be used as preference data that is a parameter to be taken into considération for recommendation to the customer as an analysis target when a data processing device performs computation in the field of finance or insurance, for example. Specificalîy, in the field such as finance or insurance, the data processing device acquires, as preference data, output-sense-of-value data that was output, and by using the acquired preference data, outputs data related to a suitable service for a customer by computation.

[0161] In the field such as finance or insurance, a data processing method may include the steps of: acquiring, as preference data, output-sense-of-value data that was output; and outputting data related to a suitable service for a customer by computation by using the acquired preference data. In the field such as finance or insurance, the data processing device may include; an acquirer configured to acquire, as preference data, output-sense-of-value data that was output; and an output section configured to output data related to a suitable service for a customer by computation by using the acquired preference data. A service that matches the customer’s sense of value can be proposed by using the output data related to a service.

[0162] In addition, sense-of-value data that was output as described above can be used as a parameter to be taken into considération for recommendation to a customer as an analysis target when the data processing device performs computation in the field of sales or advertising, for example.

[0163] Specificalîy, in the field such as sales or advertising, the data processing method acquires, as preference data, output-sense-of-varue data that was output; and outputs data related to a suitable service for a customer by computation by using the acquired preference data. In the fieîd such as sales or advertising, the data processing method may include the steps of: acquiring, as preference data, output-sense-of-value data that was output: and outputting data related to a suitable service for a customer by computation by using the acquired preference data. In the field such as sales or advertising, the data processing device may include an acquirer configured to acquire, as preference data, output-sense-of-value data that was output; and an output section configured to output data related to a suitable service for a customer by computation by using the acquired preference data. A service that matches the customer’s sense of value can be proposed by using the output data related to a service. Products or services may be recommended to an analysis target depending on sense-of-value data of the analysis target.

[0164] The sense-of-value-data obtained by using the leaning-vehicle-traveling data and the évaluation data can be used for computation using the customer’s preference data by the data processing device, in the field of, for example, finance, insurance, sales, and advertising.

[0165] As a resuit, sense-of-value data usable by the data processing device can be acquired with enhanced design flexibility of hardware resources.

[0166] The customer-sense-of-value-analysis method of this embodiment is an example of a method of analyzing a customer’s sense of value. A leaning vehicle is a vehicle that leans rightward when tuming to the right and leans leftward when tuming to the left. Leaning vehicles for sense-of-value-conversion data mean leaning vehicles that are operated by a plurality of drivers and serve as targets of leaning-vehicle-traveling data for sense-of-value-conversion data. For example, the leaning-vehicle-traveling data for sense-of-value-conversion data may be acquired by various sensors mounted on the leaning vehicles for sense-of-value-conversion data. The leaning-vehicle-traveling data for sense-of-value-conversion data may be acquired by various sensors mounted on the leaning vehicles for sense-of-value-conversion data such that the sensors can be easily attached or detached. The leaning-vehicle-traveling data for sense-of-valueconversion data may be acquired by various sensors temporarily mounted on the leaning vehicles for sense-of-value-conversion data in order to collect data.

[0167] The customer-sense-of-value-analysis method of this embodiment acquires analysis-ieaning-vehicle-traveling data, including traveling data when a customer as an analysis target rides on an analysis leaning vehicle that leans rightward when tuming to the right and leans leftward when tuming to the left, and analysis évaluation data of the customer regarding his/her ride. The analysis-leaning-vëhicïe-traveiing data means leaning-vehicle-traveling data of the leaning vehicle on which the customer as an analysis target rides. The analysis leaning vehicle means a leaning vehicle on which the customer as an analysis target rides.

[0168] The analysis-leaning-vehicle-traveling data may be included in the lean in g vehicie-traveling data for sense-of-value-conversion data. The analysis-leaning-vehicletraveling data may not be included in the leaning-vehicle-traveling data for sense-ofvalue-conversion data. For exampie, the analysis-leaning-vehicle-traveling data may be acquired by various sensors mounted on the analysis Ieaning vehicle. The analysisleaning-vehicle-traveling data may be acquired by various sensors mounted on the analysis Ieaning vehicle such that the sensors can be easily attached or detached.

[0169] The analysis-leaning-vehicle-fraveîing data may be acquired by various sensors temporarily mounted on the analysis Ieaning vehicle in order to collect data. The various sensors for collecting the analysis-leanîng-vehicîe-traveling data may hâve lower détection accuracy than various sensors for collecting the leaning-vehicle-traveling data for sense-of-value-conversion data.

[0170] The various sensors for collecting the analysis-îêàning-vehicle-traveling data may be the same as the various sensors for collecting the leaning-vehicle-traveling data for sense-of-value-conversion data. 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 leaning-vehicle-traveling data for sense-of-value-conversion data. The types of data included in the analysis-leaning-vehicle-traveling data may be the same as the types of data included in the leaning-vehicle-traveling data for sense-of-valueconversion data.

[0171] in another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes data related to traveling data obtained when the îeaning vehide with a customer aboard fraveis in a lean State. The anaiysis-leaning-vehîcle-traveling data includes traveling data obtained when the Îeaning vehide with a customer as an analysis target aboard travels in a lean State.

[0172] The leaning-vehicle-traveiing data of the Ieaning vehicle which is in a lean State is largely affected by a driving characteristic of the driver. Thus, the use of the traveling data obtained when the Ieaning vehide is in a lean State allows for more accurate analysis of a sense of value of the customer.

[0173] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes a larger amount of data reflecting a change in driving of the Ieaning vehicle for sense-of-vaîue-conversion data by a driver than data not reflecting a change in driving of the Ieaning vehicle for sense-of-value-conversion data by the driver. The analysis-leaning-vehicle-traveling data includes a larger amount of data reflecting a change in driving of the analysis leaning vehicle by a driver than data not reflecting a change in driving of the analysis leaning vehicle by the driver,

[0174] A driver of a leaning vehicle recognizes a situation and drives the leaning 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 leaning 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 considerably large number of variations. In other words, leaning-vehicle-traveiing data includes a large number of variations of stîmuli felt by a customer riding on the leaning vehicle. Furthermore, in the case of the leaning vehicle, the stimuli felt by the customer riding on the leaning vehicle hâve a large number of variations. By using such leaningvehicle-traveiing data, more accurate data indicating a sense of value can be acquired, while ensuring design flexibility of hardware resources of the customer-sense-of-valueanalysis device.

[0175] A method for dividing leaning-vehicle-traveiing 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.

[0176] For example, the leaning-vehicle-traveiing data can be divided by directly observing a change in driving of the leaning vehicle by the driver. For example, the leaning-vehicle-traveiing data can be divided by directly observing a behavior of the leaning vehicle in which a resuit of change in driving of the leaning vehicle by the driver appears. For example, the leaning-vehicle-traveiing 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. For exampie, the leaning-vehicle-traveiing data can be divided by observing a location of the leaning vehicle showing that the leaning vehicle travels in a place where frie driver frequently changes driving of the leaning vehicle. Specifically, the leaning-vehicle-traveiing data can be divided by using location data of the leaning vehicle and traveling environment data (e.g., map data) of the leaning vehicle. More specifically, the leaning-vehicle-traveiing 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 the 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.

[0177] In another aspect, the customer-sense-of-value-analysis method according to the present teaching preferably includes the following configurations. The leaningvehicle-traveiing data for se nse-of-value-conversion data includes at least one of leaningvehicle-operation-input data for sense-of-value-conversion data, leaning-vehicle-behavior data for sense-of-value-conversion data, or leaning-vehicie-iocation data for sense-ofvalue-conversion data, where the teaning-vehicle-operation-input data for sense-of-valueconversion data is related to an operation input to the ïeaning vehicle for sense-of-valueconversion data, the leaning-vehicle-behavior data for sense-of-value-conversion data is related to a behavior of the leaning vehicle for sense-of-value-conversion data, and the leaning-vehicie-iocation data for sense-of-value-conversion data is related to a location of the leaning vehicle for sense-of-value-conversion data, The analysis-leaning-vehicletraveling data includes at least one of analysis-leaning-vehicle-operation-input data related to an operation input to the analysis leaning vehicle, analysis-leaning-vehidebehavior data related to a behavior of the analysis leaning vehicle, or analysrs-leaningvehicîe-location data related to a location of the analysis leaning vehicle.

[0178] The ieaning-vehicie-operaiiûn-input data is data related to an operation input by the driver, and thus, more strongly refiects a resuit of détermination by the driver. In the leaning vehicle, there are s large number of types of operation by the driver and flexibility in options by the driver during driving is high. Thus, there are a large number of variations of operation, The leaning-vehicle-behavior data and the leaning-vehicieiocation data strongly refîect a resuit of an operation input by the driver. With this configuration, the leaning-vehicle-traveling data strongly refiects a change in operation of the leaning vehicle after détermination of the driver. In other words, the leaning-vehicletraveling data includes more stimuü felt by a customer riding on the leaning vehicle. Furthermore, in the case of the leaning vehicle, the stimuli felt by the customer riding on the leaning vehicle hâve a larger number of variations. By using such leaning-vehicletraveling data, more accurate data indicating a sense of value can be acquired, while ensuring design flexibility of hardware resources of the customer-sense-of-value-analysis device.

[0179] ln another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations, The leaningvehicle-traveling data for sense-of-value-conversion data includes leaning-vehicletraveling-environment data for sense-of-value-conversion data, where the leaningvehicle-traveling-environment data for sense-of-value-conversion data is related to a traveiing environment in which the leaning vehicle for sense-of-value-conversion data travels, The analysis-leaning-vehide-traveling data indudes analysis-Îeaning-ve'nîcietraveling-environment data related to a traveling environment in which the analysis leaning vehicle travels,

[0180] The traveiing environment data is considered to be an example of stress on a driver and a customer from the outside. The traveling environment data affects détermination of the driver. The traveling environment data affects an operation of the driver. Thus, the use of the traveling environment data makes it easier to analyze the stimuli received by the customer from the leaning-vehicie-traveling data. By using such leaning-vehicie-traveling data, more accurate data indîcating a sense of value can be acquired, while ensuring design flexibility of hardware resources of the customer-senseof-value-analysis device.

[0181] The ieaning-vehicle-traveiing-environment data indudes map data, for example, The map data may be associated with, for exampîe, information on road situations, information on road traffic environments such as signais and facilities, and régulation information on traveling on roads. The leaning-vehicle-traveling-environment data can be used for anaiyzing a sense of value of a customer as an analysis target, together with the leaning-vehîcle-operation-input data, the ieaning-vehide-behavior data, and the leaning-vehicle-location data.

[0182] In another aspect, the customer-sense-ofwalue-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data indudes a larger amount of data in traveling of the Ieaning vehicle for sense-of-value-conversion data on a public road than data in traveling of the Ieaning vehicle for sense-of-value-conversion data on a place except for a public road. The analysis-leaning-vehide-traveling data indudes a larger amount of data in traveling of the analysis Ieaning vehicle on a public road than data in traveling of the analysis Ieaning vehicie on a place except for a public road.

[0183] While a driver traveling on a public road drives a Ieaning vehicle, the driver makes détermination more frequently, has a wide variation of options in détermination, and is Iikely to be subjected to stress from the outside. Accordingly, traveling data ofthe Ieaning vehicle includes a larger number of variations. Thus, the use of the leaningvehicle-traveling data including a large amount of data in traveling on a public road makes it easier to analyze the stimuli received by the customer from the leaning-vehicletraveling data. By using such leaning-vehicle-traveling data, more accurate data indîcating a sense of value can be acquired, while ensuring design flexibility of hardware resources of the customer-sense-of-vaiue-anaiysis device.

[0184] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes data in a state where options of détermination by a driver are limited by vehicles around the Ieaning vehicle for sense-of-value-conversion data but some options are Ieft. The analysis-leaning-vehicletraveling data includes data in a state where options of détermination by a driver are limited by vehicles around the analysis leaning vehicle, but some options are left.

[0185] By using the leaning-vehicle-traveling data in a state where options of détermination by a driver are limited but some options are left, it is possible to more easily analyze the stimuli received by a customer from the leaning-vehicle-traveling data. By using such leaning-vehicle-traveling data, more accurate data indîcating a sense of value can be acquired, while ensuring design flexibility of hardware resources of a data processing device.

[0186] 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-location data and leaning-vehicle-traveiing-environment data. More specifically, the state may be estimated based on date, time, and location where the leaning vehicle travels. Leaning-vehicié-traveiing 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.

[0187] in another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes data in a state where no customer is aboard the leaning vehicle far sense-of-value-conversion data, The analysis-leaning-vehicle-traveling data includes data in a state where no customer is aboard the analysis leaning vehicle. The leaning-vehicle-traveling data includes leaningvehicle-traveling data before a customer gets on the leaning vehicle or after the customer gets off the leaning vehicle.

[0188] By using the leaning-vehicle-traveling data in a state where no customer is aboard the leaning vehicle, for example, the leaning-vehicle-traveling data before the customer gets on the leaning vehicle or after the customer gets off the leaning vehicle, it is possible to more easily analyze the physical or psychological stimuli received by the customer from the leaning-vehicle-traveling data. By using such leaning-vehicletraveling data, more accurate data indîcating a sense of value can be acquired, while ensuring design flexibility of hardware resources of the customer-sense-of-value-analysis device.

[0189] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-vaîue-conversion data includes vehicle-type-related data related to a type of the leaning vehicle. The analysis-leaning-vehicle-traveling data includes vehicle-type-refated data related to a type of the leaning vehicle

[0190] In another aspect, tire customer-sense-of-vaiue-anaiysis method according to the présent teaching preferabiy includes the following configurations. The converted sense-of-value data is stored. The output-sense-of-value data is generated by using a plurality of sets of the sense-of-value data that has been stored. The term “storing includes not only storing for a storage but also temporarily storing of results. For example, sense-of-value data stored in a storage and sense-of-value data stored in a temporary memory may be used. These sets of data may be used to update sense-ofvalue data stored in a storage. These sets of data may be used to generate new senseof-value data. These sets of data may be used to perform statistical processing. These sets of data may be used to update sense-of-value data stored in a storage.

[0191] The use of the plurality of sets of sense-of-vaiue data enabies, for example, statistical processing and acquisition of more accurate data indicating a sense of value, while ensuring design flexibility of hardware resources of the data processing device. More specifically, old sense-of-value data and new sense-of-value data are used to more accurately analyze a customer’s sense of value,

[0192] In another aspect, the customer-sense-of-value-analysis method according to the présent teaching preferabiy includes the following configurations. The output-senseof-value data is generated as sense-of-value data for data processing that is used for further data processing.

[0193] As a resuit, data indicating a sense of value capable of being used for further data processing can be acquired, while ensuring design flexibility of hardware resources of the data processing device.

[0194] 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.

[0195] The customer-sense-of-value-analysis device according to the présent teaching includes: a sense-of-value-conversion-data acquirer configured to acquire sense-ofvalue-conversion-data which associâtes leaning-vehicle-traveling data, évaluation data and sense-of-value data of a customer, where the leaning-vehicle-traveling data is traveling data of a leaning vehicle configured to lean rightward when tuming to the right and lean leftward when turning to the ieft, and the évaluation data shows évaluation by the customer; an analysis-leaning-vehicle-traveling-data acquirer configured to acquire analysis-leaning-vehicie-traveling data that is traveling data cf an analysis leaning vehicle; an analysis-evaluation-data acquirer configured to acquire analysis évaluation data of a customer as an analysis target riding on the analysis leaning vehicle: a sense of-va lue-data converter configured to convert the acquired analysis-leaning-vehicletraveling data and the acquired analysis évaluation data to sense-of-value data related to a sense of value of the customer; an output-sense-of-value-daia generator configured to generate output-sense-of-value data for output by using the converted sense-of-value data; and an output-senseofivalue-data-output section configured to output the generated output-sense-of-value data to be output. The sense-of-value-conversion-data acquirer uses leaning-vehicie-traveiing data for sense-of-value-conversion data related to traveling data obtained when each of a plurality of drivers drives a leaning vehicle for sense-of-value-conversion data, and évaluation data obtained from each of a plurality of customers riding on the leaning vehicle for sense-of-value-conversion data when the traveling data is obtained, to thereby acquire, as the sense-of-value-conversion data, data in which the leaning-vehide-traveling data, the évaluation data showing évaluation by the customer and sense-of-value data of the customer are assocîated. The sense-ofvalue-data converter converts the acquired ûndysisÎcaning-vehicle-travchng data and the acquired analysis évaluation data to the sense-of-value data by using the acquired sense-of-value-conversion data.

[0196] In another aspect, the customer-sense-of-value-analysis device according to the present teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes a larger amount of data reflecting a change in operation of the leaning vehide for sense-of-value-conversion data by a driver than data not reflecting a change in operation of the leaning vehide for sense-of-value-conversion data. The analysis-leaning-vehicle-traveling data includes a larger amount of data reflecting a change in operation of the analysis leaning vehicle by a driver than data not reflecting a change in operation of the analysis leaning vehide.

[0197] in another aspect, the cuslomersense-of-value-analysis device according to the present teaching preferably includes the following configurations. The leaningvehide-traveling data for sense-of-value-conversion data indudes at least one of leaningvehicle-operation-input data for sense-of-value-conversion data, leaning-vehicie-behavior data for sense-of-value-conversion data, or leaning-vehide-location data for sense-ofvalue-conversion data, where the leaning-vehide-operation-input data for sense-of-valueconversion data is related to an operation input to the leaning vehide for sense-of-valueconversion data, the leaning-vehicie-behavior data for sense-of-value-conversion data is related to a behavior of the leaning vehide for sense-of-value-conversion data, and the leaning-vehide-location data for sense-of-vaiue-œnversicn data is related to a location of the leaning vehide for sense-of-value-œnversion data. The analysis-ieaning-vehicletraveling data includes at least one of analysis-leaning-vehicle-operation-input data related to an operation input to the analysis leaning vehicle, analysis-ieaning-vehiclebehavior data related to a behavior of the analysis leaning vehicle, or analysis-leaningvehicie-location data related to a location of the analysis leaning vehicle.

[0198] In another aspect, the customer-sense-of-va!ue-analysis device according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes leaning-vehidetraveîrng-environmenl data for sense-of-value-conversion data, where the îeaningvehicle-traveling-environment data for sense-of-value-conversion data is related to a traveling environment in which the leaning vehide for sense-of-value-conversion data travels. The analysis-leaning-vehide-traveiing data includes analysis-leaning-vehicletraveling-envîronment data related to a traveling environment in which the analysis leaning vehicle travels.

[0199] In another aspect, the customer-sense-of-value-anaiysis device according to the présent teaching preferably includes the following configurations. The output-sense= of-value data is generated as sense-of-value data for data processing that is used for further data processing,

[0200] In another aspect, the customer-sense-of-value-analysis device according to the présent teaching preferably indudes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data indudes a larger amount of data in traveling of the leaning vehicle for sense-of-value-conversion data on a public road than data in traveling of the leaning vehicle for sense-of-value-conversion data on a place except for a public road. The analysis-leaning-vehicle-traveling data indudes a larger amount of data in traveling of the analysis leaning vehicle on a public road than data in traveling of the analysis leaning vehide on a place except for a public road.

[0201] In another aspect, the customer-sense-of-vaîue-analysis device according to the présent teaching preferably indudes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data indudes data in a state where options of détermination by a driver are limited by vehicles around the leaning vehide for sense-of-value-conversion data but some options are left. The analysis-leaning-vehicletraveling data indudes data in a state where options of détermination by a driver are limited by vehicles around the analysis leaning vehicle but some options are left.

[0202] in another aspect, the customèf-sense-of-valuë-analysis device according to the présent teaching preferably indudes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data indudes data in a state where no customer is aboard the leaning vehide for sense-of-value-conversion data. The analysis-leaning-vehide-traveling data includes data in a state where no customer is aboard the anaiysis leaning vehicie,

[0203] In another aspect, the customer-sense-of-vaiue-analysis device according to the présent teaching preferably includes the following configurations. The leaningvehicle-traveling data for sense-of-value-conversion data includes vehicle-type-related data related to a type of a leaning vehicie. The an a lysis-leaning-vehicle-traveiing data includes vehicle-type-related data related to a type of a leaning vehicie.

[0204] In another aspect, the çustomer-sense-of-value-analysis device according to the présent teaching preferably includes the following configurations. The converted sense-of-value data is stored, and the output-sense-of-value data is generated by using a plurality of sets of the sense-of-value data that has been stored.

[0205] In another aspect, the customer-sense-of-vatue-anaiysis device according to the present teaching preferabiy includes the foiiowing configurations. The output-senseof-value data is generated as sense-of-value data for data processing that is used for further data processing.

[0206] <Second Embodiment>

FIG. 3 illustrâtes an example of a customer-sense-of-value-analysis system 100 including the customer-sense-of-value-analysis 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 wiil not be described again, and only components different from those of the first embodiment will be described.

[0207] The customer-sense-of-value-analysis system 100 includes the customersense-of-value-anaiysis device 1, and a sense-of-value-conversion-data-generating device 101 that generates sense-of-value conversion-data.

[0208] The sense-of-value-conversiomdata-generating device 101 is, for example, a data-processing-computation device capable of communicating with the customer-senseof-value-analysis device 1 and including a processor. in a case where the customersense-of-vatue-analysis device 1 is a data-processing-computation device including a processor, the sense-of-value-conversion-data-generating device 101 may be the same data-processing-computation device as the customer-sense-of-value-anaiysis device 1.

[0209] The sense-of-value-conversion-data-generating device 101 acquires leaningvehicle-traveling data, évaluation data and sense-of-value data, and generates sensë-ofvalue-conversion data in which the teaning-vehicte-traveiing data, the évaluation data and the sense-of-value data are associated.

[0210] Specifically, the se nse-of-value-con version-data-generating device 101 includes a data memory 111 and a sense-of-value-conversion-data generator 112,

Although not specificalîy shown, the sense-of-value-conversion-data-generating device 101 includes an acquirer that acquires leaning-vehicle-traveling data, évaluation data and sense-of-value data. Although not specificalîy shown, the sense-of-vaïue-conversiondata-generating device 101 includes an output section that outputs generated sense-ofvalue-conversion data.

[0211] The data memory 111 stores leaning-vehicle-traveling data, évaluation data, sense-of-value data, and sense-of-value-conversion data, Specificalîy, the data memory 111 stores leaning-vehicle-traveling data for sense-of-value-conversion data obtained when a plurality of drivers drives leaning vehicles Y (leaning vehicles for sense-of-va lueconversion-data) with customers aboard. The data memory 111 also stores évaluation data for sense-of-value-conversion data ofthe plurality of customers regarding their rides. Furthermore, the data memory 111 stores sense-ôf-vâiue-conversion data generated by the sense-of-va!ue-conversion-data generator 112 described later.

[0212] The data memory 111 may store sense-of-value data by input, or may store sense-of-value data beforehand. Evaluation data is stored by input in the data memory 111. As the înputting method, a variety of methods are used, such as communication from a portable terminai of a customer, or an input based on a questionnaire.

[0213] The leaning-vehicle-traveling data for acquiring sense-of-value-conversion data includes, for example, leaning-vehicle-driving-input data for sense-of-vaiue-conversion data, ieaning-vehicle-behavior data for sense-of-value-conversion data, leaning-vehiclelocation data for sense-of-value-conversion data, leaning-vehicle-traveling-environment data for sense-of-value-conversion data, and so forth.

[0214] The sense-of-vaîue-cônversion-data generator 112 generates sense-of-valueconversion data in which sense-of-value data, leaning-vehicle-traveling data for sense-ofvalue-conversiomdata and évaluation data for sense-cf-value-conversion-data are associated, where the sense-of-vaiue data, the leaning-vehicle-traveling data and the évaluation data hâve been stored in the data memory 111. The sense-of-valueconversion data generated by the sense-of-value-conversion-data generator 112 is stored in the data memory 111.

[0215] The sense-of-value-conversion data stored in the data memory 111 is used by the customer-sense-of-value-analy si s device 1 in converting leaning-vehicle-traveling data (analysis-leaning-vehicie-îraveling data) of a leaning vehicle X (analysis leaning vehicle) and évaluation data to sense-of-value data. In the customer-sense-of-valueanaiysis device 1, a method for converting the leaning-vehicle-traveling data and the évaluation data to the sense-of-value data is similar to that in the first embodiment, and thus, will not be specificalîy described,

[0216] The customer-sense-of-vaîue-analysis device 1 generates output-sense-ofvalue data by using the sense-of-value data, and outputs the output-sense-of-value data. The configuration of the customer-sense-of-vaîue-analysis device 1 is similar to that of the first embodiment, and thus, the customer-sense-of-value-analysis device 1 will not be described specificaliy.

[0217] The output-sense-of-value data that has been output from the customer-senseof-vaiue-analysis device 1 may be input to, for exampîe, a data processing device 102. In this case, the output-sense-of-value data is generated by the customer-sense-of-valueanaiysîs device 1 as sense-of-value data for data processing to be used for data processing in the data processing device 102.

[0218] The data processing device 102 may be a device used in, for example, the businesses of finance, insurance, saies, advertising, and sô forih. The data processing device 102 may be a device that perforons processing of data related to finance, Insurance, markets, products, services, environments, or customers. In a case where the customer-sense-of-value-analysis device 1 is a data-processing-computation device, the data processing device 102 may be the same device as the customer-sense-of-valueanalysis device 1. The data processing device 102 may be the same data-processingcomputation device as the sense-of-value-conversion-data-generating device 101.

[0219] The data processing device 102 includes, for example, an output-sense-ofvalue-data acquirer 121, a first data acquirer 122, a second data generator 123, a second-data-output section 124, and a data memory 125.

[0220] The output-sense-of-value-data acquirer 121 acquires the output-sense-ofvaiue data that is output from the customer-sense-of-value-anasysis device 1.

[0221] The first data acquirer 122 acquires first data different from the output-sense-ofvalue data. The first data is data as a data processing target in the data processing device 102. The first data is, for exampîe, data related to finance, insurance, markets, products, services, environments, or customers used in the businesses of finance, insurance, sales, advertising, and so forih. The first data is stored in the data memory 125.

[0222] The second data generator 123 generates second data different from the output-sense-of-value data and the first data, by using the output-sense-of-value data and the first data. In a manner similar to the first data, the second data is also, for exampîe, data related to finance, insurance, markets, products, services, environments, or customers used in the businesses of finance, insurance, sales, advertising, and so forth.

[0223] The second-data-output section 124 outputs the second data generated by the second data generator 123.

[0224] Next, a data processing method that performs data processing by using outputsense-of-value data with the data processing device 102 having the configuration described above will be described with reference to the flowchart shown in FIG. 4. FIG. 4 îs a flowchart depicting an operation of data processing by the data processing device 102.

[0225] As shown in FIG. 4, first, the output-sense-of-value-data acquirer 121 of the data processing device 102 acquires output-sense-of-value data that was output from the customer-sense-of-value-anaiysis device 1 (stepSBI).

[0226] Next, the first data acquirer 122 of the data processing device 102 acquires first data stored in the data memory 125 (step SB2). The first data is data different from the output-sense-of-vaiue data.

[0227] Thereafter, the second data generator 123 of the data processing device 102 generates second data by using the acquired output-sense-of-value data and the acquired first data (step SB3). The second data is data different from the output-senseof-value data and the first data.

[0228] Subsequently, the second-data-output section 124 of the data processing device 102 outputs the generated second data (step SB4).

[0229] As described above, the output-sense-of-value data that was output from the customer-sense-of-value-anaîysis device 1 can be used in computing data reîated to a suitable service for a customer by the data processing device in the fieîd of, for example, finance or Insurance. That is, the sense-of-value data obtained by using the leaningvehicle-traveîing data and the évaluation data can be used for computation by the data processing device in the field of, for example, finance, insurance, sales, and advertising.

[0230] Specifically, in the field such as finance or insurance, the data processing device acquires output-sense-of-value data that was output, acquires preference data by computation by using the acquired output-sense-of-value data, and outputs data related to a suitable service for a customer by computation by using the acquired preference data.

[0231] In the field such as finance or insurance, the data processing method may include the steps of: acquiring output-sense-of-value data that was output from the customer-sense-of-value-anaiysis device 1; and cuiputting data reîated to a suitable service for a customer by computation by using the acquired preference data.

[0232] In addition, output-sense-of-value data that was output from the customer sense-of-value-analysis 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 performs computation in the field of sales or advertising, for example. In the field such as saies or advertising, products or services may be recommended to an analysis target depending on sense-of-value data of the analysis target by performing computation with the data processing device.

[0233] Specifically, in the field such as sales or advertising, the data processing device can acquire output-sense-of-value data that was output from the customer-sense-ofvalue-analysis device 1, and by using the acquired output-sense-of-value data, output a product or a service to be recommended to the analysis target by computation.

[0234] In the field such as sales or advertising, the data processing device may include: a sense-of-value-data acquirer configured to acquire output-sense-of-value data that was output from the customer-sense-of-value-analysis device 1; and either a product-related-daia-output section configured to output product-related data conceming a product to be recommended to an analysis target or a service-related-data-output section configured to output service-related data conceming a service to be recommended to the analysis target, by using the acquired output-sense-of-value data.

[0235] In the field such as sales or advertising, the data processing method may include the steps of: acquiring sense-of-value data output from the customer-sense-ofvalue-analysis device 1; and outputting either product-related data conceming a product to be recommended to an analysis target or service-related data conceming a service to be recommended to the analysis target, by using the acquired sense-of-value data.

[0236] In another aspect, sense-of-value data output in the customer-sense-of-valueanalysis method according to the present teaching is preferably used for a data processing method using the following sense-of-value data. In this data processing method, the output-sense-of-value data that was output is acquired. In the data processing method, first data different from the output-sense-of-value data is acquired. In the data processing method, the output-sense-of-value data and the acquired first data are used to generate second data different from the output-sense-of-value data and the acquired first data. In the data processing method, the generated second data is output. [0237] The data processing method using sense-of-value data includes data Processing methods as described in Patent Documents mentioned in Background Art. The present teaching, however, is not limited to the data processing methods as described in Patent Documents iisted in the Background Art. The data processing method may be any data processing method as long as the data processing method uses sense-of-value data. For exampie, 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.

[0238] With the configuration of this embodiment, the eu stomer-sense-of-va lueanalysis device 1 and the customer-sense-of-value-analysis method using the device can acquire sense-of-value data usabîe in the data processing device 102. As described in the first embodiment, the use of traveling data of a leaning vehicle for analysis of a sense of value can reduce the number of types of data processed by the system and can reduce a load on hardware ofthe customer- se nse-of-vaiue-analy sis device 1.

[0239] As a resuit, sense-of-vaîue data usable in a data processing device can be acquired with enhanced design flexibility of hardware resources.

[0240] In each of the embodiments described above, sense-of-value-conversion data is generated by using leaning-vehicle-traveiing data. Altematively, sense-of-valueconversion data may be generated by using not only leaning-vehicle-traveiing data but also data except for the leaning-vehicle-traveiing data.

[0241] In the embodiments, leaning-vehicle-traveiing data is acquired as analysisleaning-vehicle-traveling data, and by using sense-of-value-conversion data, the anaîysisleaning-vehicfe-traveling data is converted to sense-of-va lue data related to a sense of value of a customer as an analysis target. Altematively, data other than the leaningvehicle-traveiing data may be acquired for analysis such that the data and leaningvehicle-traveiing data are converted to sense-of-va lue data by using sense-of-valueconversion data.

[0242] The output-sense-of-value data may be combined with data other than the leaning-vehicle-traveiing data and used.

[0243] As described above, various types of data described in the embodiments may be combined with data other than the leaning-vehicle-traveiing data.

INDUSTRIAL APPLICABILITE

[0244] The present teaching is usable for a customer-sen$e-of-value-ana!ysis method and a eu stomer-sense-of-va lue-analy sis system for analyzing a customer’s sense of value, and a data processing method and a data processing device that use sense-ofvalue data obtained by the customer-sense-of-value-analysis method and the customersense-of-value-analysis device.

REFERENCE SiGNS LIST

[0245] 1 eu stomer-sense-of-value-anaiy si s device sense-of-value-conversion-data acquirer analysis-leaning-vehicle-traveling-data acquirer analysis-evaluation-data acquirer sense-of-value-data converter output-sense-of-vaîue-data generator data output section

70, 111 data memory

100 customer-sense-of-value-analysis system

101 sense-of-value-conversion-data~generating device

102 data processing device

X leaning vehicie (analysis leaning vehicle)

Y leaning vehicie (leaning vehicle for sense-of-value-conversion data) 10

Claims (20)

1. A eustomër-sënse-of-vaiuë-anaiysis method of analyzing a sense of value of a customer as an analysis target, comprising:

a sense-of-value-conversion-data-acquiring step of acquiring sense-of-valueconversion-data which associâtes leaning-vehicle-traveling data, évaluation data and sense-of-value data of a customer, 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 left, the évaluation data showing évaluation by the customer;

an analysis-data-acquiring step of acquiring analysis-leaning-vehicle-traveling data that is traveling data of an analysis Ieaning vehicle, and analysis évaluation data of the customer riding on the analysis Ieaning vehicle;

a sense-of-value-data-conversion step of converting the acquired analysisleaningwehicle-traveling data and the acquired analysis évaluation data to sense-of=value data related to a sense of value ofthe customeras the analysistarget;

an output-sense-of-value-data-generating step of generating output-sense-ofvalue data for output by using the converted sense-of-va lue data; and an output-sense-of-value-data-outputting step of outputting the generated output-sense-of-value data to be output, wherein the sense-of-value-conversion-data-acquiring step uses leaning-vehicletraveling data for sense-of-value-coAversion data related to traveling data obtained when each of a plurality of drivers drives a Ieaning vehicle for sense-of-value-con version data, and évaluation data obtained from each of a plurality of customers riding on the Ieaning vehicle for sense-ofivalue-conversion data when the traveling data is obtained, to thereby acquire, as the sense-of-value-conversion data, data in which the leaning-vehicletraveling data, the évaluation data showing évaluation by the customer and sense-ofvalue data ofthe customerare associated, and the sense-of-vatue-data-conversîon step converts the acquired analysisleaning-vehicle-traveling data and the acquired analysis évaluation data to the sense-ofvalue data by using the acquired sense-of-value-conversîon data.

2. The customer-sense-of-value-analysis method according to claim 1, wherein the sense-of-va lue-conversion data is data in which the sense-of-value data of the customer is associated with a preference of the customer, the preference of the customer being estimated from the leaning-vehicle-traveling data and the évaluation data of the customer.

3. The customer-sense-of-value-analysis method according to claim 1 or 2, wherein the îeaning-vehicie-traveling data for sense-of-value-conversion data includes data related to traveling data obtained when the Ieaning vehicle for sense-of-valueconversion data with each of the plurality of customers aboard travels in a lean State, and the analysis-leaning-vehicle-traveüng data includes traveling data obtained when the analysis Ieaning vehicle with the customer as the analysis target aboard travels in a lean State.

4. The customer-sense-of-value-analysis method according to any one of claims 1 to 3, wherein the leaning-vehicle-traveling data for sense-of-value-conversion data includes a larger amount of data reflecting a change in driving of the Ieaning vehicle for sense-ofvalue-conversion data by the driver than data not reflecting a change in driving of the Ieaning vehicle for sense-of-value-conversion data by the driver, and the analysis-leaning-vehicle-traveling data includes a larger amount of data reflecting a change in driving of the analysis Ieaning vehicle by a driver than data not reflecting a change in driving ofthe analysis Ieaning vehicle by the driver.

5. The customer-sense-of~value-analysis method according to any one of claims 1 to 4, wherein the ieaning-vehicie-travëiing data for sense-of-vaiue-conversion data includes at least one of leaning-vehicle-operation-input data for sense-of-value-conversion data, Ieaning-vehicle-behavior data for sense-of-value-conversion data, or leaning-vehiclelocation data for sense-of-value-conversion data, the leaning-vehicle-operation-input data for sense-of-value-conversion data being related to an operation input to the Ieaning vehicle for sense-of-value-conversion data, the leaning-vehicle-behavior data for sense-of-value-conversion data being related to a behavior of the Ieaning vehicle for sense-of-value-conversion data, the leaning-vehicle-location data for sense-of-valueconversion data being related to a location of frie Ieaning vehicle for sense-of-valueconversion data, and the analysis-leaning-vehicle-traveling data includes at least one of analysis leaning-vehide-operation-input data related to an operation input to the analysis leaning vehicle, analysrs-ieaning-vehicle-behavior data related to a behavior of the analysis leaning vehicle, or analysis-ieaning-vehicle-location data related to a location of the analysis leaning vehicle.

6. The customer-sense-of-value-analysis method according to any one of daims 1 to 5, wherein the leaning-vehicle-traveling data for sense-of-value-conversion data includes leaning-vehicle-traveling-environment data for sense-of-value-conversion data, the leaning-vehicle-traveling-environment data for sense-of-value-conversion data being related to a traveling environment in which the leaning vehicle for sense-of-valueconversion data travels, and the analysis-leaning-vehicle-traveling data includes analysis-leaning-vehicletraveling-enviranment data related to a traveling environment in which the analysis leaning vehicle travels.

7. The customer-sense-of-value-analysis method according to any one of daims 1 to 6, wherein the leaning-vehide-traveling data for sense-of-value-conversion data includes a larger amount of data in traveling of the leaning vehicle for sense-of-value-conversion data on a public road than data in traveling of the leaning vehicle for sense-of-valueconversion data on a place except for a public road, and 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.

8. The customer-sense-of-value-analysis method according to any one of daims 1 to 7, wherein the iëaning-vëhicië-trâvëîing data for sense-of-value-conversion data includes data in a state where options of détermination by the driver are limited by a vehicle around the leaning vehicle for sense-of-value-conversion data but some options are left, and the analysis-leaning-vehicle-traveling data includes data in a state where options of détermination by the driver are limited by a vehicle around the analysis leaning vehicle but some options are left.

9. The customer-sense-of-value-analysis method according to any one of claims 1 to 8, wherein the leaning-vehicle-traveiing data for sense-of-value-conversion data includes data in a state where no customer is aboard the Ieaning vehicle for sense-of-valueconversion data, and the anaiysis-leaning-vehicle-travefing data includes data in a state where no customer is aboard the analysis Ieaning vehicle.

10. The customer-sense-of-vatue-analysis method according to any one of claims 1 to 9, wherein the leaning-vehicle-traveiing data for sense-of-value-conversion data includes vehicie-typé-reiatéd data related io a type of the ieaning vehicie, and the analysis-leaning-vehide-traveiing data inciudes vehicie-type-related data related to a type of the Ieaning vehicle.

11. The customer-sense-of-value-analysis method according to any one of claims 1 to 10, wherein the converted sense-of-value data is stored, and the output-sense-of-vaiue data is generated by using a plurality of sets of the sense-of-value data that has been stored.

12. The customer-sense-of-value-analysis method according to any one of claims 1 to 11, wherein the output-sense-of-value data is geriêfatëd as sense-ôf-vâlue data for data processing that is used for further data processing.

13. A customer-sense-of-value-analysis device for anaiyzing a sense of value of a customer as an analysis target, comprising:

a sense-of-value-conversion-data acquirer configured to acquire sense-ofvalue-conversion-data which associâtes leaning-vehicle-traveiing data, évaluation data and sense-of-value data of a customer, 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, the évaluation data showing évaluation by the customer;

an analysis-leaning-vehicte-traveiing-data acquirer configured to acquire analysis-leaning-vehicie-traveling data that is traveling data of an analysis ieaning vehicle;

an analysis-evaluation-data acquirer configured to acquire analysis évaluation data of the customer as the analysis tanget riding on the analysis leaning vehicle;

a sense-of-vaiue-data converter configured to convert the acquired analysisleaning-vehicle-traveling data and the acquired analysis évaluation data to sense-of-vaiue data related to a sense of value ofthe customer;

an output-sense-of-value-data generator configured to generate output-senseof-value data for output by using the converted sense-of-value data; and an output-sense-of-value-data-output section configured to output the generated output-sense-of-value data to be output, wherein the sense-of-value-conversion-data acquirer uses leaning-vehicle-traveling data for sense-of-value-conversion data related to traveling data obtained when each of a plurality of drivers drives a leaning vehicle for sense-of-value-conversion data, and évaluation data obtained from each of a plurality of customers riding on the leaning vehicle for sense-of-value-conversion data when the traveling data is obtained, to thereby acquire, as the sense-of-value-conversion data, data in which the leaning-vehicletraveling data, the évaluation data showing évaluation by the customer and sense-ofvalue data of the customer are associated, the sense-of-value-data converter couverts the acquired analysis-leaningvehicle-traveling data and the acquired analysis évaluation data to the sense-of-value data by using the acquired sense-of-value-conversion data,

14. The aistomer-sense-of-value-analysis device according to claim 13, wherein the sense-of-value-conversion data is data in which the sense-of-value data of the customer is associated with a preference of the customer, the preference of the customer being estimated from the leaning-vehicle-traveling data and the évaluation data ofthe customer.

15. The customer-sense-of-value-analysis device according to claim 13 or 14 wherein the leaning-vehicle-traveling data for sense-of-value-conversion data includes data related to traveling data obtained when the leaning vehicle for sense-of-valueconversion data with each of the plurality of customers aboard travels in a lean state, and the analysis-leaning-vehicle-traveling data includes traveling data obtained when the analysis leaning vehicle with the customer as the analysis target aboard traveis in a lean State.

16. The customer-sense-of-value-analysis device according to any one of daims 13 to 15, wherein the leaning-vehicie-traveling data for sense-of-value-conversion data includes a larger amount of data reflecting a change in driving of the leaning vehicle for sense-ofvaiue-conversion data by the driver than data not reflecting a change in driving of the leaning vehide for sense-of-value-conversion data 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 vehide by a driver than data not reflecting a change in driving of the analysis leaning vehide by the driver.

17. The customer-sense-of-value-analysis device according to any one of daims 13 to 16, wherein the leaning-vehicie-traveling data for sense-of-value-conversion data includes at least one of ieâning-vehide-opération-input data for sense-of-value-conversion data, leaning-vehicle-behavior data for sense-of-value-conversion data, or leaning-vehidelocation data for sense-of-value-conversion data, the leaning-vehicle-operation-input data for sense-of-value-conversion data being related to an operation input to the leaning vehicle for sense-of-value-conversion data, the leaning-vehide-behavior data for sense-of-value-conversion data being related to a behavior of the leaning vehicle for sense-of-value-conversion data, the leaning-vehide-location data for sense-of-valueconversion data being related to a location of the leaning vehide for sense-of-valueconversion data, and the analysis-leaning-vehiclë-traveling data indudes at least one of anaiysisleaning-vehicle-operation-input data related to an operation input to the analysis leaning vehide, analysis-leaning-vehide-behavior data related to a behavior of the analysis leaning vehide, or analysis-leaning-vehicle-location data related to a location of the analysis leaning vehicle.

18. The customer-sense-of-value-analysis device according to any one of daims 13to 17, wherein the leaning-vehicie-traveling data for sense-of-value-conversion data includes leaning-vehicle-traveling-environment data for sense-of-value-conversion data, the leaning-vehicle-traveling-environment data for sense-of-value-conversion data being reiated to a traveling environment in which the leaning vehicle for sense-of-valueconversion data travels, and the analysis-leaning-vehicle-traveling data includes analysis-leaning-vehicletraveling-environment data related to a traveling environment in which the analysis 5 leaning vehicle travels.

19, The customer-sense-of-value-analysis device according to any one of claims 13 to 18, wherein the output-sense-of-value data is generated as sense-of-value data for data 10 processing that is used for further data processing.

20. A data processing method using the output-sense-of-value data generated as the sense-of-value data for data processing in the customer-sense-ofvalue-analysis method as claimed in claim 12, the data processing method comprising:

15 acquiring the output-sense-of-value data;

acquiring first data different from the output-sense-of-value data;

generating second data by using the output-sense-of-value data and the first data, the second data being different from the output-sense-of-value data and the first data; and

20 outputting the second data.

21. A data processing device using the output-sense-of-value data generated as the sense-of-value data for data processing in the customer-sense-of-value-analysis device as clairned in claim 19, the data processing device comprising;

25 an output-sense-of-va!ue-data acquirer configured to acquire the output-senseoTvalue data;

a first data acquirer configured to acquire first data, the first data being different from the output-sense-of-value data;

a second data generator configured to generate second data by using the

30 output-sense-of-value data and the first data, the second data being different from the output-sense-of-value data and the first data; and a second-data-outpui section configured to output the second data.