JP2010033549A - Information provision device, information provision method, program and information provision system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an information provision device for appropriately providing information in consideration of a plurality of workloads of a user who is driving a vehicle. <P>SOLUTION: The information provision device 1 is provided with a model DB2 in which a quantization model for calculating a workload value from contribution actions of the user driving the vehicle is stored in advance for each of a plurality of different workloads related to driving of the vehicle. The information provision device 1 acquires data regarding the contributing action from the user driving the vehicle for each of the plurality of workloads, and estimates the workload value of the user from data on the contributing operation of the user driving the vehicle using the quantization model. Then, the information to be provided to the user driving the vehicle is controlled according to the workload value estimated by each of the plurality of workloads. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an information providing apparatus having a function of controlling information provision according to a user's workload while driving a vehicle.

  2. Description of the Related Art Conventionally, a system for improving driver ability is known as a system for providing information to a user who is driving a vehicle (see, for example, Patent Document 1). In this conventional system, a vehicle driver (user) is monitored, driver state data relating to the state of the vehicle driver is acquired, and a driver's cognitive load is estimated. And prioritization of the vehicle information notified to a driver is performed based on the recognition load of the driver.

JP 2004-524203 A

  The user's cognitive load (workload) while driving a vehicle is classified into a plurality of different workloads according to the type of user's contributing behavior that contributes to the workload. For example, a driving workload resulting from a user's driving operation when driving a vehicle, a device operating workload resulting from a user's device operation when operating a device provided in the vehicle, and a user's operating time when driving a vehicle Auditory workload due to auditory movement, visual workload due to user's visual movement when driving the vehicle, intrinsic workload due to user's psychological state when driving the vehicle, etc. An example of multiple workloads.

  However, in the conventional system, the above-mentioned various workloads are collectively treated as “driver's cognitive load”, and the driver's cognitive load is estimated and vehicle information to be notified to the driver is prioritized. Yes. That is, in the conventional system, it is not assumed to provide information according to the workload of the user who is driving the vehicle for each of a plurality of different workloads, and appropriate information is not provided to the user. There was a problem that there was something.

  For example, if the user ’s driving workload while driving a vehicle is low (such as driving straight ahead) but the auditory workload is high (such as when listening to traffic information on the radio), When the entire workload (the sum of a plurality of different workloads) is low to some extent, the vehicle information is notified to the user. However, in this case, it is difficult for the user to listen to the notified vehicle information because the auditory workload is high. As described above, the conventional system does not take into account a plurality of workloads of the user who is driving the vehicle, and there is a problem in that appropriate information may not be provided to the user.

  The present invention has been made in view of the above problems, and an object thereof is to provide an information providing apparatus capable of providing appropriate information in consideration of a plurality of workloads of a user who is driving a vehicle.

  The information providing apparatus of the present invention is based on correct data in which a correlation between a user's contribution behavior and a workload value contributing to the workload is recorded for each of a plurality of different workloads related to driving of the vehicle, Model storage means for storing a quantification model for calculating the workload value from the user's contribution behavior while driving the vehicle, and data regarding the contribution behavior from the user who is driving the vehicle for each of the plurality of workloads Data acquisition means for acquiring, for each of the plurality of workloads, workload estimation means for estimating the user's workload value from data of the user's contribution behavior while driving the vehicle, using the quantification model; , Information to be performed on the user who is driving the vehicle according to the workload value estimated for each of the plurality of workloads Includes an information providing control means for controlling the test, the.

  Thereby, for each of a plurality of workloads, the workload value is estimated from the data acquired from the user who is driving the vehicle using the quantification model, and control of providing information to the user is performed according to the estimated workload value. Done. Therefore, appropriate information provision control is performed in consideration of the workload value for each of a plurality of workloads. Further, in this case, since the workload is estimated using a pre-stored quantification model, the load required for the workload estimation process can be reduced, and in real time for the user who is driving the vehicle. Information can be provided.

  Moreover, in the information provision apparatus of this invention, the said correct answer data may be produced | generated based on the recording of the biosignal at the time of the said user's contribution action.

  Thereby, highly accurate correct answer data can be obtained by using the user's biological signal (for example, pupil radius change rate), and therefore the estimation accuracy of the workload value using the quantification model based on the correct answer data is improved. improves.

  In the information providing apparatus of the present invention, the correct answer data may be generated based on a subjective evaluation record during the user's contribution action.

  As a result, highly accurate correct answer data can be obtained by using the user's subjective evaluation (for example, NASA-TLX), and therefore the accuracy of estimating the workload value using the quantification model based on the correct answer data is improved. To do.

  Further, in the information providing apparatus of the present invention, the quantification model includes a formulation model that formulates the user workload value for the user's contribution behavior while driving the vehicle for each of the plurality of workloads. The workload formulated by the formulation model includes a driving workload caused by a user's driving operation when driving the vehicle and a user's device operation when operating a device provided in the vehicle. Resulting equipment operation workload, an auditory workload resulting from a user's auditory movement when driving the vehicle, and a visual workload resulting from a user's visual action when driving the vehicle; Any of intrinsic workloads resulting from the psychological state of the user when driving the vehicle may be included.

  This allows users to contribute behavior while driving a vehicle using a formulation model for multiple workloads (driving workload, equipment operation workload, auditory workload, visual workload, intrinsic workload, etc.) The workload value can be easily calculated from the data.

  In the information providing apparatus of the present invention, weighting processing may be performed in the formulation model in consideration of the user's familiarity with respect to vehicle driving based on the user's travel history.

  Thereby, it becomes possible to calculate the workload value in consideration of the user's familiarity with driving the vehicle (for example, the workload value is low on the route the user always travels).

  The information providing apparatus according to the present invention includes a correct data recording unit that records the correct data during driving of the vehicle, and a model that performs learning processing of the quantification model using the correct data recorded during driving of the vehicle. Learning means.

  As a result, the quantification model is learned using the correct answer data recorded while the user is driving the vehicle, and the quantification model is adapted to the user. By using a user-adapted quantification model and estimating a workload value for the user, it is possible to provide information suitable for the user.

  In the information providing apparatus of the present invention, the quantification model includes a probability inference model for calculating the workload value of the user from data of the user's contribution behavior during driving the vehicle for each of the plurality of workloads. The plurality of workloads used in the probabilistic inference model include a driving workload caused by a user's driving operation when driving the vehicle, and a user's device when operating a device provided in the vehicle Equipment operation workload caused by operation, auditory workload caused by user's auditory movement when driving the vehicle, and visual workload caused by user's visual action when driving the vehicle And an intrinsic workload caused by the psychological state of the user when driving the vehicle.

  This allows users to contribute behavior while driving a vehicle using a probabilistic inference model for each of multiple workloads (driving workload, equipment operation workload, auditory workload, visual workload, intrinsic workload, etc.) The workload value can be easily calculated from the data.

  In the information providing apparatus of the present invention, a consumption workload value required for the user to receive the information is set for the plurality of workloads in the information provided to the user who is driving the vehicle. And the information provision control means is operating the vehicle so that a sum of the workload value estimated for each of the plurality of workloads and the consumed workload value is equal to or less than the upper limit workload value of the user. Information provision control for the user may be performed.

  As a result, the total of the workload value estimated for each of the plurality of workloads and the consumption workload value of the information provided to the user while driving the vehicle does not exceed the user's upper limit workload value. Providing information appropriately for. For example, if the user's driving workload while driving a vehicle is low (such as driving straight ahead) but the auditory workload is high (eg when listening to traffic information on the radio), the consumption of the auditory workload Information with a high workload value (such as polite route guidance) is not provided to the user. Also, if the auditory workload is high (for example, when listening to traffic information on the radio) but the visual workload is low, the information that the consumption workload value of the auditory workload is low (video with text information) Etc.) to the user. In this way, appropriate information is provided in consideration of the conflict of workload values for each of a plurality of workloads.

  In the information providing apparatus according to the present invention, display of the workload value estimated for each of the plurality of workloads may be included in providing information to the user who is driving the vehicle.

  Thereby, since the estimated workload value is displayed for each of the plurality of workloads, the user can check his / her own workload values.

  In the information providing apparatus of the present invention, providing information to the user who is driving the vehicle may include providing information for providing a service to the user who is driving the vehicle.

  Accordingly, it is possible to provide information (such as a confirmation message) for providing a service to a user who is driving the vehicle in consideration of the workload value estimated for each of a plurality of workloads.

  In the information providing apparatus of the present invention, the information provision control unit increases the workload when the workload value estimated for each of the plurality of workloads is equal to or less than the lower limit workload value of the user. Control of providing information to the user while driving the vehicle may be performed so as to provide stimulation content information to be performed.

  Thereby, when the workload value of the user who is driving the vehicle is equal to or lower than the lower limit workload value, the stimulation content information is provided to the user. When the workload value of the user while driving the vehicle is extremely low, the user's attention may be reduced. In such a case, the user's attention can be improved by providing stimulus content information.

  The information providing method of the present invention is a method for providing information to a user who is driving a vehicle, and for each of a plurality of different workloads related to driving of the vehicle, the user's contributing behavior that contributes to the workload A quantification model for calculating the workload value from a user's contribution behavior while driving a vehicle is stored on the basis of correct data in which a correlation with the workload value is recorded. For each of the workloads, obtaining data regarding the contributing behavior from the user driving the vehicle, and using the quantification model for each of the plurality of workloads, Estimating the user workload value from the data, and driving the vehicle according to the workload value estimated for each of the plurality of workloads And performing the control of the information providing made to the user, it includes a.

  According to this method, for each of a plurality of workloads, a workload value is estimated from data acquired from a user who is driving the vehicle using a quantification model, and information is provided to the user according to the estimated workload value. Is controlled. Therefore, appropriate information provision control is performed in consideration of the workload value for each of a plurality of workloads. Further, in this case, since the workload is estimated using a pre-stored quantification model, the load required for the workload estimation process can be reduced, and in real time for the user who is driving the vehicle. Information can be provided.

  The information providing program of the present invention is a program for providing information to a user who is driving a vehicle, and the memory contributes to the workload for each of a plurality of different workloads related to driving of the vehicle. A quantification model for calculating the workload value from the user's contribution behavior while driving the vehicle is stored based on the correct answer data in which the correlation between the user's contribution behavior and the workload value is recorded; The program uses the quantification model for each of the plurality of workloads, the processing for obtaining data regarding the contributing behavior from the user driving the vehicle, and the quantification model for each of the plurality of workloads. A process of estimating the workload value of the user from the data of the user's contribution behavior while driving the vehicle, and for each of the plurality of workloads Depending on the constant has been the workload value is intended to execute a processing for controlling the information providing made to the user in the vehicle operation.

  Even with this program, the workload value is estimated from the data acquired from the user who is driving the vehicle using a quantification model for each of a plurality of workloads, and information is provided to the user according to the estimated workload value. Control is performed. Therefore, appropriate information provision control is performed in consideration of the workload value for each of a plurality of workloads. Further, in this case, since the workload is estimated using a pre-stored quantification model, the load required for the workload estimation process can be reduced, and in real time for the user who is driving the vehicle. Information can be provided.

  The information providing system of the present invention is an information providing system including an in-vehicle device mounted on a vehicle and a center device communicable with the in-vehicle device, and the information providing system is related to driving of the vehicle. For each of a plurality of different workloads, the workload value is calculated from the user's contribution behavior while driving the vehicle based on the correct answer data in which the correlation between the contribution behavior of the user contributing to the workload and the workload value is recorded. Model storage means in which a quantification model is calculated, data acquisition means for acquiring data related to the contributing behavior from a user who is driving the vehicle for each of the plurality of workloads, and the plurality of workloads Every time, the workload value of the user is estimated from the data of the user's contribution behavior while driving the vehicle using the quantification model. And an information provision control means for controlling information provision performed for the user during driving of the vehicle according to the workload value estimated for each of the plurality of workloads. The data acquisition means is provided in the in-vehicle device, and the information provision control means is provided in the center device.

  Also with this system, the workload value is estimated from the data acquired from the user who is driving the vehicle using the quantification model for each of the plurality of workloads, and the estimated workload value is determined according to the estimated workload value. Control of information provision to the user is performed. In this case, in the center device, appropriate information provision control is performed in consideration of the workload value for each of a plurality of workloads. Also in this case, since the workload is estimated using a pre-stored quantification model, the load required for the workload estimation process can be reduced. It becomes possible to provide information in real time.

  In the information providing system of the present invention, the center device includes a workload prediction unit that predicts a future workload value when the vehicle travels on a planned travel route using the quantification model, The information provision control means may perform control of information provision to be performed for the user who is driving the vehicle when traveling on the planned travel route based on the future workload value.

  Thereby, the future workload value when the vehicle travels on the planned travel route can be predicted in advance. When the vehicle travels on the planned travel route, the vehicle is based on the predicted future workload value. Control of information provision to the user during driving is appropriately performed. Therefore, in order to estimate the workload value, the user who is driving the vehicle based on the future workload value predicted in advance without having to acquire the data on the contribution behavior from the user driving the vehicle in real time. It is possible to provide information in real time.

  According to the present invention, for each of a plurality of workloads, a workload value is estimated from data acquired from a user who is driving the vehicle using a quantification model, and information is provided to the user according to the estimated workload value. By performing this control, it is possible to provide appropriate information in consideration of a plurality of workloads of the user who is driving the vehicle.

It is a block diagram which shows the structure of the information provision apparatus in 1st Embodiment. It is explanatory drawing which shows an example (example which used the formulation model) of the estimation of a workload. It is explanatory drawing which shows the other example (example using a probabilistic reasoning model) of the estimation of a workload. It is a figure which shows an example (correction data of a biological signal parameter | index) of correct data. It is a figure which shows the other example (correction data of a subjective evaluation parameter | index) of correct answer data. It is a figure which shows the example of the information provided to a user. It is a figure which shows an example of the monitor display of a workload value. It is explanatory drawing of control of information provision in the information provision apparatus of 1st Embodiment. It is a block diagram which shows the structure of the information provision system in 2nd Embodiment. It is a sequence diagram which shows the flow of operation | movement of the information provision system in 2nd Embodiment. It is a block diagram which shows the structure of the information provision system in 3rd Embodiment. It is a sequence diagram which shows the flow of operation | movement of the information provision system in 3rd Embodiment. It is a block diagram which shows the structure of the information provision system in 4th Embodiment. It is explanatory drawing which shows an example of prediction of a workload value. It is explanatory drawing which shows an example of prediction of a workload value. It is explanatory drawing which shows an example of prediction of a workload value. It is explanatory drawing which shows an example of prediction of a workload value. It is a sequence diagram which shows the flow of operation | movement of the information provision system in 4th Embodiment. It is a block diagram which shows the structure of the information provision system in 5th Embodiment. It is a sequence diagram which shows the flow of operation | movement of the information provision system in 5th Embodiment.

<First Embodiment>
Hereinafter, an information providing apparatus according to a first embodiment of the present invention will be described with reference to the drawings. In the present embodiment, the case of an information providing device used for a vehicle navigation device or the like is illustrated. This information providing apparatus has a function of controlling information provision to the user, and this function is realized by a program stored in the HDD or memory of the apparatus.

  First, the overall configuration of the information providing apparatus according to the present embodiment will be described with reference to the drawings. FIG. 1 is a block diagram of an information providing apparatus. As shown in FIG. 1, the information providing apparatus includes a model DB 2 (database) in which a quantification model for calculating a workload value is calculated for each of a plurality of workloads related to vehicle driving. The quantification model is a model for calculating the workload value from the user's contribution behavior while driving the vehicle using correct data in which the correlation between the contribution behavior of the user contributing to the workload and the workload value is recorded. It is. The detailed contents of the quantification model and the correct answer data will be described later with reference to the drawings.

  In addition, the information providing apparatus includes a data acquisition unit 6 that acquires data related to the user's contributing behavior during driving of the vehicle from the vehicle sensor 3, the line-of-sight camera 4, and the biological sensor 5 mounted on the vehicle for each of a plurality of workloads. I have.

(Workload type)
Here, the types of workload of the user who is driving the vehicle and the contribution data of the workload will be described. The user's workload while driving the vehicle includes a driving workload caused by the user's driving operation when driving the vehicle. For example, the data acquisition unit 6 uses data relating to driving workload contribution behavior (for example, steering angle data, vehicle speed data, inter-vehicle distance data, accelerator opening rate data, brake signal data, etc. during vehicle driving) as vehicle sensor 3. Get from.

  Moreover, the user's workload during driving of the vehicle includes a device operation workload caused by the user's device operation when operating the device provided in the vehicle. The data acquisition unit 6 acquires from the vehicle sensor 3 data related to the contribution behavior of the device operation workload (for example, navigation operation data, audio operation data, air conditioner operation data, window opening / closing operation data, etc. while driving the vehicle).

  In addition, the user's workload while driving the vehicle includes an auditory workload caused by the user's auditory motion when driving the vehicle. The data acquisition unit 6 acquires data (for example, voice information data or music information data included in route guidance or audio reproduction while driving the vehicle) from the vehicle sensor 3 regarding the contribution behavior of the auditory workload.

  In addition, the user's workload during driving of the vehicle includes a visual workload resulting from the user's visual motion when driving the vehicle. The data acquisition unit 6 acquires from the line-of-sight camera 4 data related to the visual workload contribution behavior (for example, the viewpoint movement speed data and viewpoint coordinate data of the user who is driving the vehicle).

  Further, the workload of the user who is driving the vehicle includes an intrinsic workload caused by the psychological state of the user when driving the vehicle. The data acquisition unit 6 acquires from the biometric sensor 5 data related to intrinsic workload contribution behavior (for example, heart rate data, blood pressure data, and respiratory rate data of a user who is driving the vehicle).

  As shown in FIG. 1, the information providing apparatus 1 is a user who is driving a vehicle for each of a plurality of workloads (driving workload, equipment operation workload, auditory workload, visual workload, intrinsic workload). The workload estimation unit 7 for estimating the workload value is provided. The workload estimation unit 7 uses the quantification model stored in the model DB 2 to calculate the workload value for each of a plurality of workloads from the data of the user's contribution behavior during driving of the vehicle acquired by the data acquisition unit 6. Is estimated.

(Estimation of workload using quantification model)
Here, estimation of a workload, which is a feature of the present invention, will be described with reference to the drawings. FIG. 2 is an explanatory diagram showing an example of workload estimation in the present embodiment. Here, as illustrated in FIG. 2, a case where a workload value is estimated for each of a plurality of workloads using a formulation model as one of the quantification models will be described as an example. For this formulation, for example, statistical methods such as linear multiple regression analysis, principal component analysis, and factor analysis are used.

As shown in FIG. 2, data contributing to the driving workload (driving WL contribution data) includes a steering angle d1 (degrees), a vehicle speed d2 (km / h), an inter-vehicle distance d3 (m), an accelerator during driving the vehicle. Data of the opening rate d4 (%) and the brake signal d5 (ON: 1, OFF: 0) are included. By formulating the relationship between these data d1 to d5 and correct answer data (described later) by a statistical method or the like, the driving workload (DWL) is formulated as shown in the following formula 1.
DWL = α (n) × d1 / 360 + β (n) × d2 / 100 + γ (n) / d3
+ Δ (n) × d4 / 100 + ε × d5 (Formula 1)

  Here, α, β, γ, δ, and ε are weighting coefficients, and n is a familiarity coefficient that takes into account the user's familiarity with respect to vehicle driving. This familiarity coefficient is a coefficient determined based on the user's travel history. The weighting coefficient α will be described as an example. The weighting coefficient when the user travels for the first time (n = 1) is α (1), and the weighting when the user travels the vehicle for the second time (n = 2). The coefficient is α (2). In other words, it can be said that this formulation model is weighted in consideration of the user's familiarity with vehicle driving.

Further, data (device operation WL contribution data) contributing to the device operation workload includes navigation operation o1 (hardware button operation: A1, touch panel operation: A2, etc.) and audio operation o2 (skip button operation: A3, volume operation: A4, etc.), air conditioner operation o3 (with operation: 1, no operation: 0), and window opening / closing operation o4 (with operation: 1, no operation: 0) are included. By deriving the relationship between the data o1 to o4 and the correct answer data by a statistical method or the like, the equipment operation workload (OWL) is formulated as shown in the following Expression 2.
OWL = α (n) × o1 + β (n) × o2
+ Γ (n) × o3 + δ (n) × o4 (Formula 2)
A1 to A4 are respectively predetermined constants. In addition, α, β, γ, and δ are weighting coefficients, and n is a familiarity coefficient that takes into account the user's familiarity with respect to vehicle driving.

In addition, the audio information a1 (route guidance: B1, facility information guidance: B2, telephone: data included in route guidance and audio reproduction while driving the vehicle is included in the data contributing to the auditory workload (auditory WL contribution data). B3) and music information a2 (classic: B4, rock: B5, favorite song: B6, etc.). An auditory workload (AWL) is formulated as shown in Equation 3 below by deriving the relationship between the data a1 and a2 and the correct answer data by a statistical method or the like.
AWL = α (n) × a1 + β (n) × a2 (Formula 3)
B1 to B6 are predetermined constants. In addition, α and β are weighting coefficients, and n is a familiarity coefficient in consideration of the user's familiarity with respect to vehicle driving.

The data contributing to the visual workload (visual WL contribution data) includes the viewpoint movement speed v1 (mm / second) during driving and the viewpoint coordinates v2 (room mirror: C1, side mirror: C2, navigation: Data such as C3). The visual workload (VWL) is formulated as shown in Equation 4 below by deriving the relationship between the data v1 and v2 and the correct data using a statistical method or the like.
VWL = α (n) × v1 + β (n) × v2 (Formula 4)
C1 to C6 are predetermined constants. In addition, α and β are weighting coefficients, and n is a familiarity coefficient in consideration of the user's familiarity with respect to vehicle driving.

The data contributing to the intrinsic workload (endogenous WL contribution data) includes data on the heart rate i1 (times / min), blood pressure i2 (mmHg), and respiratory rate i3 (times / min) while driving the vehicle. included. By deriving the relationship between the data i1 to i3 and the correct answer data by a statistical method or the like, the intrinsic workload (IWL) is formulated as shown in the following equation (5).
IWL = α (n) × i1 + β (n) × i2 + γ (n) × i3 (Formula 5)
Α, β, and γ are weighting factors, and n is a familiarity factor that takes into account the user's familiarity with driving the vehicle.

  In the foregoing, an example of workload estimation using a formulation model has been described, but the scope of the present invention is not limited to this. For example, as shown in FIG. 3, a probabilistic inference model may be used for estimating the workload.

  As the probability inference model, for example, a Bayesian network or a neural network is used. For example, the driving workload will be specifically described. In this case, the steering angle d1 (degrees), the vehicle speed d2 (km / h), which is data contributing to the driving workload (driving WL contribution data), Establishing a Bayesian network or neural network probability model using the inter-vehicle distance d3 (m), accelerator opening rate d4 (%), and brake signal d5 (ON: 1, OFF: 0) as data The workload value of the driving workload (DWL) is estimated.

  Similarly, with respect to the device operation workload, the above-described device operation WL contribution data (o1 to o4) is input, and a probability model of a Bayesian network or a neural network is constructed, and the inference result of the device operation workload (OWL) Workload values are estimated.

  As for the auditory workload, the above-mentioned auditory WL contribution data (a1, a2) is used as an input to construct a probability model of a Bayesian network or a neural network, and the inference result of the auditory workload (AWL) work The load value is estimated.

  As for the visual workload, the above-described visual WL contribution data (v1, v2) is used as an input to construct a probability model of a Bayesian network or a neural network, and the inference result of the visual workload (VWL) work The load value is estimated.

  As for the intrinsic workload, the above-described intrinsic WL contribution data (i1 to i3) is used as an input to construct a probability model of a Bayesian network or a neural network, and the intrinsic workload (IWL) work as an inference result. The load value is estimated.

  In constructing a quantification model (formulation model or probabilistic reasoning model), correct data may be used and a user's profile (age, gender, driving calendar), etc. may be taken into consideration.

(Correct data)
Next, correct data used to construct a quantification model will be described with reference to the drawings. In the present embodiment, a quantification model is constructed using two types of correct answer data (biological signal index and subjective evaluation index). Note that the construction of a quantification model can also be referred to as modeling (quantification) of each workload.

  FIG. 4 is a diagram illustrating an example of correct data of the biological signal index. Here, a pupil reaction is described as an example of a biological signal index, but the scope of the present invention is not limited to this. The biological signal index of the present invention includes heart rate fluctuation, respiratory rate fluctuation, bioelectric potential fluctuation and the like in addition to pupil reaction.

  In general, when the pupil is mydriatic (the pupil radius increases), the sympathetic nerve is stimulated and the user is excited. Conversely, when the pupil is miotic (the pupil radius is small), the parasympathetic nerve is stimulated and the user is relaxed. The larger the pupil response (pupil radius change rate), the higher the workload applied to the user, and the lower the pupil response, the lower the workload applied to the user.

  In the present embodiment, time series data of the user's pupil reaction during driving of the vehicle when the user runs on a predetermined experimental course is acquired, and the correspondence with driving of the vehicle is analyzed. For example, in the correct answer data in FIG. 4, the pupil response is small at the time of departure, and the pupil response is large when performing a left turn, right turn, passing or overtaking, and the like. From this correct data of pupil response, the part that contributes to each workload is extracted, and each workload is formulated based on the magnitude and rate of change of the pupil response of that part. .

  Here, the formulation of the operation workload will be described as an example. For example, from the correct answer data of the pupil response in FIG. 4, a part that performs a driving workload contribution action (for example, a right turn part) is extracted, and driving WL contribution data at that time (steering angle signal, vehicle speed, inter-vehicle distance) The driving workload is formulated using statistical methods to determine the relationship between the accelerator opening rate and the brake signal data). That is, based on the correct answer data of the pupil reaction, a formulation model (the above formula 1) for calculating the workload value of the driving workload from the driving WL contribution data is obtained.

  In the above, the example which formulates driving | running | working workload from the correct data of the pupil reaction was demonstrated. Although explanation is omitted here, in the same way, the equipment operation workload, the auditory workload, the visual workload, and the intrinsic workload are formulated.

  FIG. 5 is a diagram illustrating an example of correct answer data of a subjective evaluation index. Here, the conventional NASA-TLX will be described as an example of the subjective evaluation index, but the scope of the present invention is not limited to this. For example, instead of the conventional NASA-TLX, a continuous NASA-TLX (time series NASA-TLX) in which subjective evaluation is performed on a PC while watching a video may be used. The subjective evaluation index of the present invention includes SWAT, MCH and the like in addition to NASA-TLX.

  NASA-TLX is an index by which a user subjectively quantifies a workload. Generally, the larger the value, the higher the user's workload, and the smaller the value, the lower the user's workload.

  In the present embodiment, time series data of the NASA-TLX of the user who is driving the vehicle when the user runs on a predetermined experimental course is acquired, and the correspondence with the driving of the vehicle is analyzed. For example, in the correct answer data of FIG. 5, the value of NASA-TLX is large at the time of departure, left turn, or right turn, and the value of NASA-TLX is small when going straight. From such NASA-TLX correct answer data, a portion that contributes to each workload is extracted, and based on the size, rate of change, etc. of the NASA-TLX of that portion, a formula for each workload is extracted. Is done.

  Here, the formulation of the operation workload will be described as an example. For example, from the correct answer data of NASA-TLX in FIG. 5, a part (for example, a right-turn part) performing a driving workload contribution action is extracted, and driving WL contribution data at that time (steering angle signal, vehicle speed, inter-vehicle distance) The relationship between the distance, the accelerator opening rate, and the brake signal data) is derived by a statistical method to formulate the driving workload. That is, based on the NASA-TLX correct answer data, a formulation model (the above formula 1) for calculating the workload value of the driving workload from the driving WL contribution data is obtained.

  In the above, the example which formulates a driving | working workload from the correct data of NASA-TLX was demonstrated. Although explanation is omitted here, in the same way, the equipment operation workload, the auditory workload, the visual workload, and the intrinsic workload are formulated.

  Returning to FIG. 1, the configuration of the information providing apparatus 1 will be described. The information providing apparatus 1 includes an information DB 8 that stores information (also referred to as content information) for providing information to a user. Here, the content information stored in the information DB 8 will be described in detail with reference to the drawings.

  FIG. 6 is a diagram showing an example of content information stored in the information DB 8. As shown in FIG. 6, the content information includes video types such as voice, music, and video, and is classified into a large classification (such as route guidance) and a small classification (such as polite guidance and simple guidance). . In each content information, a consumption workload value required for the user to receive the content information is set for each of a plurality of workloads.

  For example, in the example of FIG. 6, the consumed workload value of the polite guidance auditory workload is 40 and the consumed workload value of the visual workload is 0. Also, the consumption workload value of the simple guidance auditory workload is 20, and the consumption workload value of the visual workload is 0. As described above, in each piece of content information, a consumption workload value is set for each workload.

  In the example of FIG. 6, the consumption workload value of the auditory workload of the favorite song of Rock is 30. Such content information having a high consumption workload value of the auditory workload can be said to be stimulating content information that increases the auditory workload of the user.

  As shown in FIG. 1, the information providing apparatus 1 includes an information provision control unit 11 having a function of controlling a monitor 9 and a speaker 10 mounted on a vehicle. This information provision control part 11 selects the content information memorize | stored in information DB8 according to the workload value estimated for every some workload, and with respect to the user who is driving the vehicle from the monitor 9 or the speaker 10 The information provision is controlled so as to provide the information.

  For example, the information providing control unit 11 determines the vehicle so that the total of the workload value estimated for each of the plurality of workloads and the consumed workload value of the content information is equal to or less than a predetermined upper limit workload value (for example, 100). Controls the provision of information to the driving user. In addition, when the workload value estimated for each of a plurality of workloads is equal to or less than a predetermined lower limit workload value (for example, 10), the information provision control unit 11 provides stimulation content information for increasing the workload. In this manner, information provision control for the user who is driving the vehicle is performed. In addition, as shown in FIG. 7, the information provision control unit 11 also has a function of displaying a workload value estimated for each of a plurality of workloads on the monitor 9.

  In addition, although the example which estimates a workload using the quantification model previously memorize | stored in model DB2 was demonstrated above, in this information provision apparatus 1, user adaptation is performed by learning a quantification model. May be performed.

  As shown in FIG. 1, the information providing apparatus 1 includes a correct data recording unit 12, a correct data DB 13, and a model learning unit 14. The correct data recording unit 12 has a function of recording correct data while the user is driving the vehicle, and correct data recorded while the user is driving the vehicle is recorded in the correct data DB 13. The model learning unit 14 has a function of learning a quantification model using correct data recorded in the correct data DB 13.

  About the information provision apparatus 1 comprised as mentioned above, the operation | movement is demonstrated using drawing. Here, control of information provision and display of workload values, which are features of the present invention, will be described.

  FIG. 8 is an explanatory diagram of information provision control performed by the information provision apparatus 1 according to the present embodiment. In the example of FIG. 8, the vehicle driven by the user first goes straight along the route, waits for a right turn, then makes a right turn and a left turn, and goes straight ahead and waits for a signal.

  When such a vehicle is driven, the information providing apparatus 1 acquires contribution action data (such as driving WL contribution data) from the user for each of a plurality of workloads and stores the data in the model DB 2. The workload value is estimated using the quantification model. FIG. 8 shows driving workload, auditory workload, and visual workload as estimation results.

  And in the information provision apparatus 1, control of information provision is performed according to the workload value estimated for every some workload as mentioned above. For example, at time Ta in FIG. 8, the user's driving workload is low, but the auditory workload is high. Therefore, provision of audio and music content information having a high consumption workload value of the auditory workload is not performed. In this case, however, the user's visual workload is low. Therefore, information on video content information (still image without character information) with a low consumption workload value of an auditory workload and a high consumption workload value of a visual workload is provided.

  Further, at time Tb in FIG. 8, the auditory workload is low, but the user's visual workload is high. Accordingly, the provision of information of audio-video content information (simple route guidance) having a high consumption workload value for the auditory workload and a low consumption workload value for the visual workload is performed.

  In addition, at time Tc in FIG. 8, all of the driving workload, the auditory workload, and the visual workload are low. In such a case, information on stimulation content information (rock favorite music) that increases the user's workload is provided.

  According to such an information providing apparatus 1 of the present embodiment, for each of a plurality of workloads, a workload value is estimated from data acquired from a user who is driving the vehicle using a quantification model, and the estimated workpiece By controlling the provision of information to the user according to the load value, it is possible to provide appropriate information in consideration of a plurality of workloads of the user who is driving the vehicle.

  That is, in the present embodiment, for each of a plurality of workloads, a workload value is estimated from data acquired from a user who is driving the vehicle using a quantification model, and the user is notified according to the estimated workload value. Information provision is controlled. Therefore, appropriate information provision control is performed in consideration of the workload value for each of a plurality of workloads. In this case, since the workload estimation is performed using the quantification model stored in advance in the model DB 2, the load required for the workload estimation processing can be reduced, and the user who is driving the vehicle can be reduced. It is possible to provide information in real time.

  In this embodiment, reliable data with high reliability can be obtained by using a user's biological signal (for example, pupil radius change speed), and therefore, a workload using a quantification model based on the correct data. The accuracy of value estimation is improved.

  Further, in the present embodiment, highly accurate correct answer data can be obtained by using a user's subjective evaluation (for example, NASA-TLX), and therefore, a workload value using a quantification model based on the correct answer data. The estimation accuracy of is improved.

  Further, in the present embodiment, a formulation model is used for each of a plurality of workloads (driving workload, equipment operation workload, auditory workload, visual workload, intrinsic workload), and the vehicle is in operation. It becomes possible to easily calculate the workload value from the data of the user's contribution behavior.

  In the present embodiment, weighting processing is performed in consideration of the user's familiarity in the formulation model, so that the user's familiarity with vehicle driving (for example, the workload value is low on the route on which the user always travels). It becomes possible to calculate the workload value in consideration.

  Further, in the present embodiment, the quantification model is learned by using the correct data recorded while the user is driving the vehicle, and the quantification model is adapted to the user. By using a user-adapted quantification model and estimating a workload value for the user, it is possible to provide information suitable for the user.

  In the present embodiment, a probabilistic reasoning model is used for each of a plurality of workloads (driving workload, equipment operation workload, auditory workload, visual workload, intrinsic workload), and the vehicle is in operation. It becomes possible to easily calculate the workload value from the data of the user's contribution behavior.

  In the present embodiment, as shown in FIG. 7, the estimated workload value is displayed for each of a plurality of workloads, so that the user can check his / her own workload values. In this way, by visualizing the quantified workload value, the driver and passengers can grasp the state of the driver's workload.

  In this embodiment, the total of the workload value estimated for each of the plurality of workloads and the consumption workload value of the information provided to the user who is driving the vehicle exceeds the upper limit workload value of the user. Information is appropriately provided to the user so that there is no such problem. For example, as shown in FIG. 8, when the user's driving workload while driving the vehicle is low (such as driving straight ahead) but the auditory workload is high (such as when listening to traffic information on the radio) Information with a high consumption workload value (such as polite route guidance) of the auditory workload is not provided to the user. Also, if the auditory workload is high (for example, when listening to traffic information on the radio) but the visual workload is low, the information that the consumption workload value of the auditory workload is low (video with text information) Etc.) to the user. In this way, appropriate information is provided in consideration of the conflict of workload values for each of a plurality of workloads.

  In the present embodiment, when the user's workload value during vehicle driving is equal to or lower than the lower limit workload value, stimulation content information is provided to the user. When the workload value of the user while driving the vehicle is extremely low, the user's attention may be reduced. In such a case, the user's attention can be improved by providing stimulus content information.

  That is, in the present embodiment, not only the information provision control that prevents the workload from becoming too high, but also the control that prevents the workload from becoming too low for a long time is performed. As a result, it is possible to suppress the occurrence of drowsiness due to the workload becoming too low for a long time, and it is possible to add an appropriate workload so that a comfortable driving can be performed.

  The embodiments of the present invention have been described above by way of example, but the scope of the present invention is not limited to these embodiments, and can be changed or modified in accordance with the purpose within the scope of the claims. is there.

  For example, providing information to a user who is driving a vehicle may include providing information for providing a service to the user who is driving the vehicle. The services for the user who is driving the vehicle include, for example, an air conditioner temperature and air volume adjustment service, a power window opening and closing service, and an audio sound adjustment service. The provision of information for service provision includes notification of a confirmation message to the user when the service is provided.

  For example, when providing an air conditioner temperature and air volume adjustment service, a confirmation message such as “Would you like to lower the temperature? In the information providing apparatus of the present invention, such a confirmation message is controlled to flow when it is estimated that the user's driving workload during driving of the vehicle is low. In addition, the audio sound adjustment service is controlled so that a confirmation message such as “Would you like to reduce the volume of music?” Is played when the auditory workload of the user driving the vehicle is estimated to be high. May be.

  The services for the user who is driving the vehicle include, for example, a search keyword input service, a glob input service, a setting request service for an unset item, and the like. Information provision for service provision includes notification of a message (input request message) that causes the user to input information. Note that the input of information by the user includes input by operation of a remote controller or a touch panel, input by voice, and the like.

  For example, in the search keyword input service and the glob input service, when it is estimated that the user's driving workload while driving the vehicle is low, a message (input request message) that prompts the user's input is played. In the setting request service for unset items, when it is estimated that the user's driving workload during driving of the vehicle is low, the system makes an inquiry (notification of an input request message) for prompting setting for the unset items. Further, in the above service, when it is estimated that the user's driving workload while driving the vehicle is high, control may be performed so that the user cannot input.

  In this way, it is possible to provide information (such as a confirmation message or an input request message) for providing services to a user who is driving the vehicle in consideration of the workload value estimated for each of a plurality of workloads. Become.

<Second Embodiment>
Next, an information providing system according to a second embodiment of this invention will be described. Here, the information providing system according to the second embodiment will be described focusing on differences from the information providing apparatus according to the first embodiment. Therefore, unless otherwise specified herein, the configuration and operation of the present embodiment are the same as those of the first embodiment.

  FIG. 9 is a block diagram illustrating a configuration of the information providing system according to the present embodiment. As shown in FIG. 9, the information providing system includes an in-vehicle device 20 mounted on a vehicle and a center device 30 installed in an information center or the like. The in-vehicle device 20 and the center device 30 include communication units 21 and 31, respectively, and can communicate with each other via a network (not shown). And in this 2nd Embodiment, the vehicle-mounted apparatus 20 is provided with the data acquisition function, and the center apparatus 30 is provided with the workload estimation function and the information provision control function.

  The operation of the information providing system according to the second embodiment will be described below with reference to FIG.

  When providing information in the information providing system of the second embodiment, first, the data acquisition unit 6 of the in-vehicle device 20 receives contribution action data (such as driving WL contribution data) from the in-vehicle sensor (such as the vehicle sensor 3). Obtain (S1). And the vehicle-mounted apparatus 20 transmits the data of the contribution action to the center apparatus 30 via the network from the communication part 21 (S2).

  When the center device 30 receives the contribution behavior data from the in-vehicle device 20, the center device 30 estimates the workload value for each of a plurality of workloads using the quantification model stored in the model DB 2 (S3). Then, in the center apparatus 30, information provision control is performed according to the workload value estimated for each of the plurality of workloads (S4). For example, when the auditory workload is high and the visual workload is low, the content of audio or music that has a high audio workload consumption workload value is not provided, and the visual workload consumption workload Information provision control is performed so as to provide content information of a video having a high value.

  The center device 30 transmits the content information determined based on the control as described above from the communication unit 31 to the in-vehicle device 20 via the network (S5). Then, the in-vehicle device 20 provides the content information received from the center device 30 to the user (driver) who is driving the vehicle (S6). Thus, for example, when the auditory workload is high and the visual workload is low, the audio and music content information with a high audio workload consumption workload value is not provided, and the visual workload is consumed. Provision of video content information with a high workload value is performed.

  Such an information providing system according to the second embodiment of the present invention also provides the same operational effects as those of the first embodiment.

  That is, also by the information providing system of the present embodiment, the workload value is obtained from data acquired from the user who is driving the vehicle using a quantification model for each of a plurality of workloads, similarly to the apparatus of the first embodiment. And the provision of information to the user is controlled according to the estimated workload value. In this case, the center device 30 performs appropriate information provision control in consideration of the workload value for each of a plurality of workloads. Also in this case, since the workload is estimated using a pre-stored quantification model, the load required for the workload estimation process can be reduced. It becomes possible to provide information in real time.

<Third Embodiment>
Next, an information providing system according to a third embodiment of the present invention will be described. Here, the information providing system according to the third embodiment will be described focusing on differences from the information providing apparatus according to the second embodiment. Therefore, unless otherwise mentioned here, the configuration and operation of the present embodiment are the same as those of the second embodiment.

  FIG. 11 is a block diagram illustrating a configuration of the information providing system according to the present embodiment. As shown in FIG. 11, in the third embodiment, the in-vehicle device 20 includes a data acquisition function and a workload estimation function, and the center device 30 includes an information provision control function.

  Hereinafter, the operation of the information providing system according to the third embodiment will be described with reference to FIG.

  When providing information in the information providing system of the third embodiment, first, the data acquisition unit 6 of the in-vehicle device 20 receives contribution action data (such as driving WL contribution data) from the in-vehicle sensor (such as the vehicle sensor 3). Obtaining (S10), the workload value is estimated for each of a plurality of workloads using the quantification model stored in the model DB 2 (S11). And the vehicle-mounted apparatus 20 transmits the estimated workload value to the center apparatus 30 from the communication part 21 via a network (S12).

  When the center device 30 receives the workload value from the in-vehicle device 20, the center device 30 performs control of information provision according to each workload value (S13). And the center apparatus 30 transmits the content information determined based on the control of the information provision from the communication part 31 to the vehicle-mounted apparatus 20 via a network (S14). Then, the in-vehicle device 20 provides the content information received from the center device 30 to the user (driver) who is driving the vehicle (S15).

  Such an information providing system according to the third embodiment of the present invention also provides the same operational effects as those of the second embodiment.

  That is, also by the information providing system of the present embodiment, the workload value is obtained from data acquired from the user who is driving the vehicle using a quantification model for each of a plurality of workloads, as in the apparatus of the second embodiment. And the provision of information to the user is controlled according to the estimated workload value. In this case, the center device 30 performs appropriate information provision control in consideration of the workload value for each of a plurality of workloads. Also in this case, since the workload is estimated using a pre-stored quantification model, the load required for the workload estimation process can be reduced. It becomes possible to provide information in real time.

<Fourth embodiment>
Next, an information providing system according to a fourth embodiment of this invention will be described. Here, the information providing system according to the fourth embodiment will be described focusing on differences from the information providing apparatus according to the second embodiment. Therefore, unless otherwise mentioned here, the configuration and operation of the present embodiment are the same as those of the second embodiment.

  FIG. 13 is a block diagram illustrating a configuration of the information providing system according to the present embodiment. As shown in FIG. 13, in the fourth embodiment, the center device 30 uses a quantification model to predict a future workload value when the vehicle travels on the planned travel route. 32.

  Here, a method for predicting a future workload value using a quantification model will be described in detail with reference to the drawings.

  FIG. 14 is an explanatory diagram illustrating an example of workload value prediction. As shown in FIG. 14, in this example, the workload value calculated in advance by the equation of the quantification model is mapped on the map. And the workload estimation part 32 will predict a future workload value by reading the workload value mapped beforehand, if the information of the driving plan route of a vehicle is received. For example, as shown in FIG. 14, when the planned travel route of the vehicle is “section A (straight section)” “section B (intersection section)” “section C (curve section with poor visibility)”. The workload values “Section A: 30”, “Section B: 70”, and “Section C: 50” mapped in advance to the section are read out and predicted as future workload values.

  FIG. 15 is an explanatory diagram illustrating another example of workload value prediction. As shown in FIG. 15, in this example, contribution behavior data is acquired from another vehicle (a vehicle ahead) by inter-vehicle communication, and a future workload value is predicted. For example, as shown in FIG. 15, when another vehicle traveling in front of the host vehicle passes an intersection, the workload value “55” is calculated from the contribution behavior data of the preceding vehicle at that time. It is predicted as the workload value when the vehicle passes the intersection in the future.

  FIG. 16 is an explanatory diagram illustrating still another example of workload value prediction. In this example, in addition to the example of FIG. 15 (data obtained from the vehicle ahead), prediction of future workload values is performed using traffic light data obtained by infrastructure cooperation. For example, in the example of FIG. 16, if another vehicle traveling in front of the host vehicle passes through the intersection with a yellow signal, the workload value “55” is calculated from the contribution behavior data of the vehicle ahead. The When the host vehicle passes through the intersection with a green light, the workload value is corrected to, for example, “30” in consideration of the state of the signal. In this way, the workload value when the own vehicle passes through the intersection with a green light in the future is predicted.

  FIG. 17 is an explanatory diagram showing still another example of workload value prediction. As shown in FIG. 17, in this example, when the host vehicle has traveled in the past on the planned travel route of the vehicle (when there is a travel history of the host vehicle), the contribution behavior of the host vehicle at that time Predict future workload values from the data. For example, as shown in FIG. 17, when the host vehicle has previously traveled in “Section A” and “Section B”, the workload value “Section A: 40” is calculated from the contribution behavior data at that time. “Section B: 40” is calculated and predicted as a future workload value when traveling in the section from now on.

  The operation of the information providing system according to the fourth embodiment will be described below with reference to FIG.

  When providing information in the information providing system of the fourth embodiment, first, the data acquisition unit 6 of the in-vehicle device 20 receives contribution action data (such as driving WL contribution data) from the in-vehicle sensor (such as the vehicle sensor 3). Obtain (S1). And the vehicle-mounted apparatus 20 transmits the data of the contribution action to the center apparatus 30 via the network from the communication part 21 (S2). In this case, the in-vehicle device 20 also transmits information such as a planned travel route and the current position of the host vehicle to the center device 30 in order to predict a future workload value (S7).

  When the center device 30 receives the contribution behavior data from the in-vehicle device 20, the center device 30 estimates the workload value for each of a plurality of workloads using the quantification model stored in the model DB 2 (S3). Further, when the center device 30 receives information such as the planned travel route and the current position from the in-vehicle device 20, the center device 30 predicts a future workload value by various methods as shown in FIGS. 14 to 17 (S8).

  Then, the center device 30 controls information provision according to the workload value estimated for each of a plurality of workloads (S4), and the content information determined based on the information provision control is transmitted to the communication unit 31. To the in-vehicle device 20 via the network (S5). Then, the in-vehicle device 20 provides the content information received from the center device 30 to the user (driver) who is driving the vehicle (S6).

  Such an information providing system according to the fourth embodiment of the present invention also provides the same operational effects as those of the second embodiment.

  In addition, in the present embodiment, the future workload value when the vehicle travels on the planned travel route can be predicted in advance, and when the vehicle travels on the planned travel route, the predicted future work Control of providing information to the user who is driving the vehicle is appropriately performed based on the load value. Therefore, in order to estimate the workload value, the user who is driving the vehicle based on the future workload value predicted in advance without having to acquire the data on the contribution behavior from the user driving the vehicle in real time. It is possible to provide information in real time.

<Fifth embodiment>
Next, an information providing system according to a fifth embodiment of the present invention will be described. Here, the information providing system according to the fifth embodiment will be described focusing on differences from the information providing apparatus according to the third embodiment. Therefore, unless otherwise mentioned here, the configuration and operation of the present embodiment are the same as those of the third embodiment.

  FIG. 19 is a block diagram showing a configuration of the information providing system according to the present embodiment. As shown in FIG. 19, in the fifth embodiment, the center device 30 uses the quantification model to predict a future workload value when the vehicle travels on the planned travel route. 32. The method for predicting the future workload value is the same as in the fourth embodiment.

  The operation of the information providing system according to the fifth embodiment will be described below with reference to FIG.

  When providing information in the information providing system of the fifth embodiment, first, the data acquisition unit 6 of the in-vehicle device 20 receives contribution action data (such as driving WL contribution data) from the in-vehicle sensor (such as the vehicle sensor 3). Obtaining (S10), the workload value is estimated for each of a plurality of workloads using the quantification model stored in the model DB 2 (S11). And the vehicle-mounted apparatus 20 transmits the estimated workload value to the center apparatus 30 from the communication part 21 via a network (S12). In this case, the in-vehicle device 20 also transmits information such as the planned travel route and the current position of the host vehicle to the center device 30 in order to predict a future workload value (S16).

  When the center device 30 receives information such as the planned travel route and the current position from the in-vehicle device 20, the center device 30 predicts the future workload value by the same method as in the fourth embodiment (S17). When the center device 30 receives the workload value from the in-vehicle device 20, the center device 30 controls information provision according to each workload value (S13). And the center apparatus 30 transmits the content information determined based on the control of the information provision from the communication part 31 to the vehicle-mounted apparatus 20 via a network (S14). Then, the in-vehicle device 20 provides the content information received from the center device 30 to the user (driver) who is driving the vehicle (S15).

  Such an information providing system according to the fifth embodiment of the present invention also provides the same operational effects as those of the third embodiment.

  In addition, in the present embodiment, the future workload value when the vehicle travels on the planned travel route can be predicted in advance, and when the vehicle travels on the planned travel route, the predicted future work Control of providing information to the user who is driving the vehicle is appropriately performed based on the load value. Therefore, in order to estimate the workload value, the user who is driving the vehicle based on the future workload value predicted in advance without having to acquire the data on the contribution behavior from the user driving the vehicle in real time. It is possible to provide information in real time.

  The embodiments of the present invention have been described above by way of example, but the scope of the present invention is not limited to these embodiments, and can be changed or modified in accordance with the purpose within the scope of the claims. is there.

  For example, in the above description, the case where the future workload is predicted by the center device 30 is illustrated, but the future workload may be predicted by the in-vehicle device 20.

  As described above, the information providing apparatus according to the present invention has an effect of being able to provide appropriate information in consideration of a plurality of workloads of a user who is driving the vehicle, and is used as a navigation apparatus for a vehicle. Is useful.

1 Information provider 2 Model DB
DESCRIPTION OF SYMBOLS 3 Vehicle sensor 4 Eye-gaze camera 5 Biosensor 6 Data acquisition part 7 Workload estimation part 8 Information DB
9 Monitor 10 Speaker 11 Information Providing Control Unit 12 Correct Data Recording Unit 13 Correct Data DB
14 Model Learning Department

Claims (15)

For each of a plurality of different workloads related to the driving of the vehicle, the user's contributing behavior while driving the vehicle based on the correct data in which the correlation between the user's contributing behavior contributing to the workload and the workload value is recorded Model storage means for storing a quantification model for calculating the workload value from:
For each of the plurality of workloads, data acquisition means for acquiring data related to the contributing behavior from a user who is driving the vehicle;
For each of the plurality of workloads, using the quantification model, workload estimation means for estimating the user workload value from the data of the user's contribution behavior while driving the vehicle,
Information provision control means for controlling information provision performed to the user during driving of the vehicle according to the workload value estimated for each of the plurality of workloads;
An information providing apparatus comprising:   The information providing apparatus according to claim 1, wherein the correct answer data is generated based on recording of a biological signal at the time of the user's contribution action.   The information providing apparatus according to claim 1, wherein the correct answer data is generated based on a subjective evaluation record during the user's contribution action. The quantification model includes, for each of the plurality of workloads, a formulation model in which the workload value of the user with respect to the user's contribution behavior while driving the vehicle is formulated.
The workload formulated by the formulation model includes a driving workload caused by a user's driving operation when driving the vehicle and a user's device operation when operating a device provided in the vehicle. Resulting equipment operation workload, an auditory workload resulting from a user's auditory movement when driving the vehicle, and a visual workload resulting from a user's visual action when driving the vehicle; 4. The information providing apparatus according to claim 1, wherein any one of intrinsic workloads resulting from a user's psychological state when driving the vehicle is included. 5.   5. The information providing apparatus according to claim 4, wherein in the formulation model, weighting processing is performed in consideration of the user's familiarity with respect to vehicle driving based on the user's travel history. Correct data recording means for recording the correct data during vehicle operation;
Model learning means for performing learning processing of the quantification model using the correct data recorded during driving of the vehicle,
The information providing apparatus according to claim 1, further comprising: The quantification model includes, for each of the plurality of workloads, a probabilistic inference model that calculates the workload value of the user from data of the user's contribution behavior while driving the vehicle,
The plurality of workloads used in the stochastic inference model include a driving workload caused by a user's driving operation when driving the vehicle, and a user's device operation when operating a device provided in the vehicle. Equipment operation workload caused by the vehicle, an auditory workload caused by the user's auditory motion when driving the vehicle, and a visual workload caused by the user's visual motion when driving the vehicle The information providing apparatus according to claim 1, wherein any one of intrinsic workloads caused by a user's psychological state when driving the vehicle is included. In the information provided to the user who is driving the vehicle, a consumption workload value required for the user to receive the information is set for each of the plurality of workloads.
The information provision control unit is configured to prevent the user who is driving the vehicle so that a total of the workload value estimated for each of the plurality of workloads and the consumed workload value is equal to or less than the upper limit workload value of the user. The information provision apparatus according to claim 1, wherein information provision control is performed.   9. The information according to claim 1, wherein the provision of information to the user who is driving the vehicle includes display of the workload value estimated for each of the plurality of workloads. Providing device.   The information provision apparatus according to any one of claims 1 to 9, wherein the provision of information to the user who is driving the vehicle includes provision of information for providing a service to the user who is driving the vehicle. .   The information provision control means provides the stimulation content information for increasing the workload when the workload value estimated for each of the plurality of workloads is equal to or lower than the lower limit workload value of the user. The information providing apparatus according to claim 1, wherein the information providing control is performed for a user who is driving the vehicle. A method for providing information to a user who is driving a vehicle,
For each of a plurality of different workloads related to the driving of the vehicle, the user's contributing behavior while driving the vehicle based on the correct data in which the correlation between the user's contributing behavior contributing to the workload and the workload value is recorded Stores a quantification model for calculating the workload value from
The method
For each of the plurality of workloads, obtaining data regarding the contributing behavior from a user driving the vehicle;
For each of the plurality of workloads, using the quantification model, estimating the workload value of the user from data of the user's contribution behavior while driving the vehicle;
According to the workload value estimated for each of the plurality of workloads, performing control of information provision performed for the user during driving of the vehicle;
An information providing method comprising: A program for providing information to a user who is driving a vehicle,
For each of a plurality of different workloads related to the driving of the vehicle, the memory is based on the correct answer data in which the correlation between the user's contributing behavior contributing to the workload and the workload value is recorded. A quantification model for calculating the workload value from the user's contribution behavior is stored,
The program is stored in a computer.
For each of the plurality of workloads, processing for obtaining data related to the contributing behavior from the user who is driving the vehicle;
For each of the plurality of workloads, using the quantification model, a process of estimating the user workload value from data of the user's contribution behavior during driving the vehicle;
A process of controlling information provision performed for a user who is driving the vehicle according to the workload value estimated for each of the plurality of workloads;
An information providing program characterized by causing An information providing system comprising an in-vehicle device mounted on a vehicle and a center device communicable with the in-vehicle device,
The information providing system includes:
For each of a plurality of different workloads related to the driving of the vehicle, the contribution of the user during the driving of the vehicle based on the correct answer data in which the correlation between the contribution behavior of the user contributing to the workload and the workload value is recorded. Model storage means for storing a quantification model for calculating the workload value from an action;
For each of the plurality of workloads, data acquisition means for acquiring data related to the contributing behavior from a user who is driving the vehicle;
For each of the plurality of workloads, using the quantification model, workload estimation means for estimating the user workload value from the data of the user's contribution behavior while driving the vehicle,
Information provision control means for controlling information provision performed to the user during driving of the vehicle according to the workload value estimated for each of the plurality of workloads;
With
The data providing system is provided in the in-vehicle device, and the information providing control unit is provided in the center device. The center device includes a workload prediction unit that predicts a future workload value when the vehicle travels on a planned travel route using the quantification model,
The information provision control unit performs control of information provision to be performed for a user who is driving the vehicle when traveling on the planned traveling route based on the future workload value. Information providing system described.