JP2018038750A - Driver state estimation method and driver state estimation device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To accurately estimate whether a driver is in a state suitable for driving.SOLUTION: A driver state estimation method includes: measuring a brain wave of a driver (S101); and estimating whether the driver is in a state suitable for driving depending on the brain wave when detecting a drive operation of the driver (S105 to S107).SELECTED DRAWING: Figure 2

Description

  The present invention relates to a driver state estimation method and a driver state estimation device.

  In Patent Document 1, the driver himself reports that the degree of arousal has decreased, and the brain wave power amount at the time of the report is stored, and thereafter the stored brain wave power amount and the current brain wave power are stored. It is proposed to determine the state of arousal by comparing the amount.

JP-A-4-122241

Since the amount of electroencephalogram power depends on individual characteristics, stress, fatigue, and the like, as described above, it is difficult to accurately estimate the state of the driver only by observing the amount of electroencephalogram power.
An object of the present invention is to accurately estimate whether or not a driver is in a state suitable for driving.

  The driver state estimation method and the driver state estimation device according to one aspect of the present invention measure the driver's brain activity, detect the driver's driving operation, and according to the brain activity when the driving operation is detected It is estimated whether the driver is in a state suitable for driving.

  According to the present invention, it is possible to accurately estimate whether or not the driver is in a state suitable for driving by focusing on the brain activity when the driving operation is detected.

It is a block diagram which shows a driving assistance device. It is a flowchart which shows the driving assistance process of 1st Embodiment. It is a time chart which shows an electroencephalogram. It is a flowchart which shows the modification of a driving assistance process. It is a flowchart which shows the driving assistance process of 2nd Embodiment. It is a figure which shows an example of an electroencephalogram measurement. It is a figure which shows an example of the feature vector in an electroencephalogram signal. It is a figure explaining the detection of action preparation potential. It is a flowchart which shows the driving assistance process of 3rd Embodiment. It is a flowchart which shows the driving assistance process of 4th Embodiment.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. Each drawing is schematic and may be different from the actual one. Further, the following embodiments exemplify apparatuses and methods for embodying the technical idea of the present invention, and the configuration is not specified as follows. That is, the technical idea of the present invention can be variously modified within the technical scope described in the claims.

<< First Embodiment >>
"Constitution"
In the first embodiment, the driver drives the driver himself, estimates whether or not the driver is in a state suitable for driving, and estimates that the driver is not in a state suitable for driving. It provides driving assistance by intervening in the driver's driving.
FIG. 1 is a block diagram illustrating a driving support device.
The driving support device 11 includes a driver state estimation device 12, a traveling environment sensor 13, a steering actuator 14, an accelerator opening actuator 15, and a brake control actuator 16.

The driver state estimation device 12 includes an electroencephalogram sensor 21 (first sensor), a sensor group 22 (second sensor), and a controller 23. The sensor group 22 includes a vehicle speed sensor 31, an acceleration sensor 32, a yaw rate sensor 33, an accelerator opening sensor 34, a brake switch 35, a steering operation amount sensor 36, and a winker switch 37.
The electroencephalogram sensor 21 measures a driver's brain waveform. In the electroencephalogram sensor 21, for example, a plurality of electrodes are provided on the headrest, and electric activity generated in the brain, that is, action potentials generated in nerve cells (neurons) and synaptic potentials when signals are transmitted between nerve cells, This is input to the controller 23 as a potential difference signal generated between the electrodes. The controller 23 measures the brain wave of the driver by analyzing the frequency of the inputted potential difference signal.

The vehicle speed sensor 31 detects the vehicle speed. The vehicle speed sensor 31 is provided, for example, in a driven gear on the output side of the transmission, detects the magnetic field lines of the sensor rotor by a detection circuit, converts the magnetic field change accompanying the rotation of the sensor rotor into a pulse signal, and outputs the pulse signal to the controller 23. . The controller 23 determines the vehicle speed from the input pulse signal.
The acceleration sensor 32 detects acceleration / deceleration in the vehicle longitudinal direction. The acceleration sensor 32 detects, for example, the displacement of the movable electrode relative to the fixed electrode as a change in capacitance, and converts it into a voltage signal proportional to the acceleration / deceleration and outputs it to the controller 23. The controller 23 determines the acceleration / deceleration from the input voltage signal.

The yaw rate sensor 33 detects the yaw angle change speed (yaw rate) of the vehicle body. The yaw rate sensor 33 is provided on a vehicle body that is on a spring, for example, a vibrator made of a crystal tuning fork is vibrated by an alternating voltage, and a distortion amount of the vibrator caused by Coriolis force at the time of angular velocity input is converted into an electrical signal. To 23. The controller 23 determines the yaw rate of the vehicle from the input electric signal.
The accelerator opening sensor 34 detects a pedal opening (operation position) corresponding to the depression amount of the accelerator pedal. The accelerator opening sensor 34 is, for example, a potentiometer, and converts the pedal opening of the accelerator pedal into a voltage signal and outputs the voltage signal to the controller 23. The controller 23 determines the pedal opening of the accelerator pedal from the input voltage signal.

The brake switch 35 detects ON / OFF of the brake. The brake switch 35 outputs a voltage signal corresponding to ON / OFF of the brake to the controller 23 via, for example, a detection circuit of a normally closed contact. The controller 23 determines ON / OFF of the brake from the input voltage signal.
The steering operation amount sensor 36 includes a rotary encoder and detects the steering angle of the steering shaft. The steering operation amount sensor 36 detects light transmitted through the slit of the scale with two phototransistors when the disk-shaped scale rotates together with the steering shaft, and outputs a pulse signal accompanying the rotation of the steering shaft to the controller 23. To do. The controller 23 determines the steering angle of the steering shaft from the input pulse signal.

The blinker switch 37 detects the operating state of the direction indicator (winker). The blinker switch 37 outputs a voltage signal corresponding to ON / OFF of the left switch and ON / OFF of the right switch to the controller 23 via, for example, a detection circuit of a normally open contact. The controller 23 determines the operating state of the blinker switch, that is, ON / OFF of the left direction switch and ON / OFF of the right direction switch from the input voltage signal.
The controller 23 is composed of a microcomputer, for example, and executes driving support processing described later. That is, it is estimated whether or not the driver is in a state suitable for driving, and when it is estimated that the driver is not in a state suitable for driving, driving assistance is performed through control intervention in the driving of the driver. For driving assistance, the steering actuator 14, the accelerator opening actuator 15, and the brake control actuator 16 are driven and controlled while observing the detection values of the sensor group 22 and the travel environment sensor 13.

The travel environment sensor 13 includes a camera 41, a radar 42, a map database 43, and a GPS receiver 44.
The camera 41 images the front of the vehicle body. The camera 41 is, for example, a CCD wide-angle camera provided at the upper part of the front window in the vehicle interior, and outputs imaged image data in front of the vehicle body to the controller 23.
The radar 42 detects the distance to the front object existing in front of the host vehicle, the relative velocity, and the direction. The radar 42 is composed of, for example, a millimeter wave radar provided in the front grill, and outputs various detected data to the controller 23. As for the distance and the relative speed, for example, an FM-CW (Frequency Modulation-Continuous Wave) method is used, and the distance and the relative speed are detected according to the frequency difference due to the Doppler effect. As for the azimuth, for example, a DBF (Digital Beam Forming) method is used, and the azimuth is detected according to the phase difference of reflected waves received by a plurality of channels.

  The map database 43 is composed of a DVD-ROM drive, a hard disk drive, a flash memory drive, etc., and road map information including road type, road alignment, lane width, vehicle traffic direction, etc., on a nonvolatile electronic storage medium I remember it. Alternatively, the road map information database may be managed by a server, and only the updated road map information difference data may be acquired through, for example, a telematics service, and the road map information stored in the map database 43 may be updated.

The GPS receiver 44 acquires current position information of the host vehicle. The GPS receiver 44 receives radio waves from four or more GPS receiver satellites, and determines the current position (longitude, latitude, altitude) of the vehicle according to the distance from each GPS receiver satellite determined from the time difference between transmission and reception. ) And determine the direction of travel. The controller 23 sets the travel route to the destination input by the user while matching the current position information with the road map information, and performs route guidance to the user according to the travel route.
The steering actuator 14 is composed of a motor capable of transmitting torque to the steering shaft. The controller 23 sets a required target steering angle when driving along a curve, changing lanes, or turning right or left at an intersection, and drives the steering actuator 14 according to the target steering angle. Control.

The accelerator opening actuator 15 is composed of, for example, an electronically controlled throttle valve that controls the opening of the throttle valve. The controller 23 sets a required target driving force when starting or accelerating the host vehicle, and drives and controls the accelerator opening actuator 15 according to the target driving force.
The brake control actuator 16 includes a hydraulic circuit used for anti-skid control (ABS), traction control (TCS), stability control (VDC: Vehicle Dynamics Control), and the like. The controller 23 sets a required target braking force when the host vehicle is decelerated or stopped, and drives and controls the brake control actuator 16 according to the target braking force.

Next, an example of the driving support process executed by the controller 23 will be described.
FIG. 2 is a flowchart showing the driving support process of the first embodiment.
In step S101, the brain wave sensor 21 measures the driver's brain wave (brain activity). In addition, it is not limited to an electroencephalogram, For example, you may measure brain activity by cerebral blood flow. Moreover, you may measure brain activity from the heart rate, the respiratory rate, the amount of perspiration, and the driver | operator's face image imaged with the camera.
In subsequent step S102, it is determined whether or not the driver group has detected a driving operation by the sensor group 22. The driving operation is, for example, an event such as a lane change operation, a right / left turn operation, an acceleration operation, or a deceleration operation. Here, when the driving operation is not detected, the process returns to the predetermined main program as it is. On the other hand, when the driving operation is detected, the process proceeds to step S103.

In step S103, the normal brain wave of the driver is read. The normal brain wave is a brain wave stored in advance when the driver performs a driving operation in a normal state. The normal brain wave is stored as a brain wave for each driving operation such as a lane change operation, a right / left turn operation, an acceleration operation, a deceleration operation, and the like, and the normal brain wave corresponding to the detected driving operation is read. Of course, instead of every driving operation, one representative brain wave may be stored in advance and read.
FIG. 3A is a time chart showing an example of a normal brain wave.
In normal times, the potential waveform rises slightly when it tries to cause a driving operation, then decreases, then rises again (recovers) from the point when the driving operation starts, and tries to cause the driving operation. There is a tendency to rise more than the previous state. The period before the operation start is Tb, and the period after the operation start is Ta, which is about 1 to 2 seconds, respectively.

In subsequent step S104, the coincidence rate α (correlation coefficient) between the brain wave when the driving operation is detected and the brain wave in the normal time is calculated.
In a succeeding step S105, it is determined whether or not the coincidence rate α is equal to or higher than a predetermined threshold α1. Here, when the coincidence rate α is equal to or higher than the threshold α1 and the correlation is high, the process proceeds to step S106. On the other hand, when the coincidence rate α is less than the threshold value and the correlation is low, the process proceeds to step S107.
FIG. 3B is a time chart showing an example of an electroencephalogram having a coincidence rate α with the normal electroencephalogram being a threshold value α1 or more.
Here, the waveform of the electric potential is the same pattern as the brain wave in normal times, and when it first tries to cause a driving operation, it gradually rises and then decreases, then rises again from the time when the driving operation is started, It is higher than the state before the driving operation was attempted.

FIG. 3C is a time chart showing an example of an electroencephalogram in which the coincidence rate α with the normal electroencephalogram is less than the threshold α1.
Here, unlike the normal brain wave, the waveform of the electric potential is almost constant when attempting to drive, decreases slightly before starting the driving operation, and slightly increases immediately after starting the driving operation. And overall there are few undulations.
In step S106, the driver returns to a predetermined main program after estimating that the driver is in a state suitable for driving (appropriate state). The state suitable for driving is a state where the driver's arousal level is high and the driver can concentrate on driving.

In step S107, it is estimated that the driver is not in a state suitable for driving (appropriate state), that is, in a state unsuitable for driving (inappropriate state), and then the process proceeds to step S108. The state unsuitable for driving is a state where the driver's arousal level is low and the driver cannot concentrate on driving.
In the subsequent step S108, the driving support device 11 is operated to intervene in the driving of the driver, thereby returning to a predetermined main program after driving support is executed. That is, by observing the detection values of the sensor group 22 and the travel environment sensor 13, the steering actuator 14, the accelerator opening actuator 15, and the brake control actuator 16 are drive-controlled to realize appropriate travel. In addition, it is good also as a structure which outputs a warning as driving assistance.
The above is the driving support process.

<Action>
First, the brain wave of the driver is measured by the brain wave sensor 21 (S101). For example, when a driving operation such as a lane change operation is detected by the sensor group 22 (the determination in S102 is “Yes”), the normal brain wave is read (S103), and the measured brain wave is compared with the normal brain wave. To do. Then, the coincidence rate α between the measured electroencephalogram and the normal brain wave is calculated (S104). When the coincidence rate α is equal to or greater than the threshold α1 (the determination in S105 is “Yes”), the driver is in a state suitable for driving. (S106). On the other hand, when the coincidence rate α is less than the threshold α1 (determination in S105 is “No”), it is estimated that the driver is not in a state suitable for driving (S107), and driving assistance is executed (S108).

  Thus, by paying attention to the electroencephalogram change pattern when the driving operation is detected, it is possible to accurately estimate whether or not the driver is in a state suitable for driving. In addition, the normal brain wave when the driver performs driving in normal time is stored in advance, and the state of the driver is easily estimated by determining the degree of similarity between the measured brain wave and the normal brain wave. be able to. In addition, when it is estimated that the driver is not in a state suitable for driving, driving assistance such as control intervention in the driver's driving or output of an alarm is executed, so the driver's confidence in the driving system of the vehicle Can be improved. In particular, when it is estimated that the driver is in a state suitable for driving, the driving assistance is not executed, so that the driver does not feel uncomfortable. Furthermore, since the brain wave is measured by detecting the driver's brain wave with the brain wave sensor 21, it can be accurately measured.

<Modification>
In the first embodiment, when the measured electroencephalogram and the normal electroencephalogram are substantially coincident (or similar), it is estimated that the driver is in a state suitable for driving. However, the present invention is not limited to this. is not. For example, after measuring the electroencephalogram when the driving operation is detected a plurality of times, the ratio β in which the electroencephalogram when the driving operation is detected and the normal electroencephalogram substantially coincide (or similar) may be considered. .
FIG. 4 is a flowchart illustrating a modified example of the driving support process.
Here, except that Steps S111 to S113 are added during the transition from Step S105 to S106, the process is the same as the above-described driving support process, and thus the description of common parts is omitted.

In step S111, it is determined whether or not the electroencephalogram when the driving operation is detected is measured a plurality of times (a predetermined number of times or more). When the electroencephalogram when the driving operation is detected is measured a plurality of times, the process proceeds to step S112. On the other hand, if the electroencephalogram when the driving operation is detected is not measured a plurality of times, the process directly returns to the main program.
In step S112, the ratio β of the number of times that the brain wave when the driving operation is detected and the brain wave when the driving operation is detected is calculated out of the number of times when the brain wave is measured when the driving operation is detected.
In subsequent step S113, when the ratio β is equal to or larger than a predetermined brain wave threshold value β1, the process proceeds to step S106. On the other hand, when it is less than the electroencephalogram threshold β1, the process directly returns to the predetermined main program.
As a result, it can be estimated more accurately whether or not the driver is in a state suitable for driving.

"effect"
Next, the main effects of the first embodiment will be described.
(1) In the driver state estimation method, the driver's brain waves are measured, and the driving operation of the driver is detected. Then, it is estimated whether or not the driver is in a state suitable for driving according to the electroencephalogram when the driving operation is detected.
Thus, by paying attention to the electroencephalogram when the driving operation is detected, it can be accurately estimated whether or not the driver is in a state suitable for driving.

(2) In the driver state estimation method, an electroencephalogram when the driver performs a driving operation in a normal state is stored in advance as a normal electroencephalogram. When the coincidence rate α between the measured electroencephalogram and the normal brain wave is equal to or higher than the threshold value α1, it is estimated that the driver is in a state suitable for driving. When the coincidence rate α is less than the threshold value α1, the driver drives the vehicle. It is estimated that the condition is not suitable for
Thus, by determining the coincidence rate α between the measured brain wave and the normal brain wave, it can be easily estimated whether or not the driver is in a state suitable for driving.

(3) In the driver state estimation method, when the electroencephalogram is measured a plurality of times and the measured electroencephalogram and the normal electroencephalogram coincide, the detected electroencephalogram and the normal electroencephalogram coincide with each other. Consider the ratio β. That is, it is estimated that the driver is in a state suitable for driving when the ratio β is equal to or greater than a predetermined brain wave threshold value β1.
Thus, by considering the ratio β of the number of times of coincidence, it can be estimated with higher accuracy whether or not the driver is in a state suitable for driving.

(4) In the driver state estimation method, the electroencephalogram activity is measured from at least one of the driver's brain wave, cerebral blood flow, heart rate, respiratory rate, sweat rate, and driver's face image.
Thus, by detecting the brain wave, cerebral blood flow, heart rate, respiration rate, sweating amount, and face image, the driver's brain activity can be measured easily and accurately.

(5) In the driver state estimation method, when it is estimated that the driver is not in a state suitable for driving, control intervention is performed in the driving of the driver.
As described above, the driving assistance is executed only when the driver is not suitable for driving, thereby improving the driver's reliability with respect to the vehicle driving system.

(6) The driver state estimation device includes an electroencephalogram sensor 21 that measures a driver's brain wave, and a sensor group 22 that detects a driver's driving operation. And the controller 23 which estimates whether a driver | operator is in the state suitable for a driving | operation according to the brain wave when driving operation is detected is provided.
Thus, by paying attention to the electroencephalogram when the driving operation is detected, it can be accurately estimated whether or not the driver is in a state suitable for driving.

<< Second Embodiment >>
"Constitution"
In the second embodiment, the presence / absence of the action preparation state is determined from the electroencephalogram before the driving operation is detected, and it is estimated whether the driver is suitable for driving according to the determination result.
FIG. 5 is a flowchart showing the driving support process of the second embodiment.
Here, since the processing in steps S103 to S105 described above is the same as that in the first embodiment except that the processing is changed to a new step S201, description of common portions will be omitted.

In step S201, it is determined whether or not an action preparation potential (action preparation state) is detected from an electroencephalogram before detecting a driving operation.
Here, the action preparation potential will be described.
FIG. 6 is a diagram illustrating an example of electroencephalogram measurement.
The plurality of electrodes of the electroencephalogram sensor 21 are arranged on the tops Fz, Fz, Cz, and CPz of the driver who are involved in the cognitive function according to the International 10-20 Law.
FIG. 7 is a diagram illustrating an example of a feature vector in an electroencephalogram signal.
Here, N feature values are extracted from the electroencephalogram before the driving operation, and an electroencephalogram feature vector P = (p1, p2,..., PN) is generated. As the feature amount, for example, a value sampled at regular intervals is used.

FIG. 8 is a diagram illustrating detection of action preparation potentials.
A feature amount of past action preparation potential is stored in a database in advance, and a region D when it is arranged in the feature space is determined. For example, if there are a plurality of samples, the region D is determined as a region D having a center of the center of gravity of the vector set {P} and a radius of the standard deviation σ. Then, it is determined whether or not the feature vector P of the action preparation potential measured in real time from the driver is in the region D. Here, when the feature vector P is in the region D, it is determined that the driver's action preparation potential is generated. When the feature vector P is not in the region D, the driver's action preparation potential is generated. Judge that it is not.
In this way, it is determined whether or not the action preparation potential is detected. When the action preparation potential is detected, the process proceeds to step S106. On the other hand, when the action preparation potential is not detected, the process proceeds to step S107. In the second embodiment, the action preparation potential is detected from the electroencephalogram, but may be detected from other than the action preparation potential as long as the driver's action preparation state can be detected.
The above is the driving support process.

<Action>
For example, when a driving operation such as a lane change operation is detected by the sensor group 22 (determination in S102 is “Yes”), it is determined whether or not an action preparation potential is detected from an electroencephalogram before the driving operation is detected. The action preparation potential is the potential that appears in the brain waves prior to body movement when the driver tries to take some action. The driver's arousal level is high and the driver concentrates on driving. Sometimes it appears prominently. Therefore, when the action preparation potential is detected ("Yes" in S201), it is estimated that the driver is in a state suitable for driving (S106). On the other hand, when the action preparation potential is not detected (determination in S201 is “No”), it is estimated that the driver is not in a state suitable for driving (S107), and driving assistance is executed (S108). Thus, by paying attention to the presence or absence of the action preparation potential before detecting the driving operation, it is possible to accurately estimate whether or not the driver is in a state suitable for driving.
In the second embodiment, the same effects as those in the first embodiment described above can be obtained, and detailed description thereof will be omitted.

<Modification>
In the second embodiment, when the action preparation potential is detected, it is estimated that the driver is in a state suitable for driving. However, the present invention is not limited to this. For example, when the expression time of the action preparation potential is greater than or equal to a predetermined threshold, it is estimated that the driver is in a state suitable for driving, and when the expression time of the action preparation potential is less than the threshold, the driver It may be estimated that it is not in a suitable state.
Thus, by paying attention to the expression time of the action preparation potential, it is possible to accurately estimate whether or not the driver is in a state suitable for driving.

"effect"
Next, main effects of the second embodiment will be described.
(1) In the driver state estimation method, when an action preparation potential is detected from an electroencephalogram before detecting a driving operation, it is estimated that the driver is in a state suitable for driving. On the other hand, when the action preparation potential is not detected, it is estimated that the driver is not in a state suitable for driving.
Thus, by paying attention to the presence or absence of the action preparation potential before detecting the driving operation, it is possible to accurately estimate whether or not the driver is in a state suitable for driving.

<< Third Embodiment >>
"Constitution"
In the third embodiment, the brain wave when a driving operation is detected is measured a plurality of times, and the ratio γ in which the action preparation potential is detected is taken into consideration.
FIG. 9 is a flowchart showing the driving support process of the third embodiment.
Here, it is the same as the second embodiment described above except that steps S301 to S303 are added during the transition from step S201 to S106, and therefore, description of common parts is omitted.

In step S301, it is determined whether or not the electroencephalogram when the driving operation is detected is measured a plurality of times (a predetermined number of times or more). When the electroencephalogram when the driving operation is detected is measured a plurality of times, the process proceeds to step S302. On the other hand, if the electroencephalogram when the driving operation is detected is not measured a plurality of times, the process directly returns to the main program.
In step S302, the ratio γ of the number of times that the action preparation potential is detected is calculated from the number of times that the electroencephalogram is measured when the driving operation is detected.
In subsequent step S303, when the ratio γ is equal to or greater than a predetermined threshold γ1, the process proceeds to step S106. On the other hand, when it is less than the threshold value γ1, the process returns to the predetermined main program as it is.
The above is the driving support process.

<Action>
When the driving operation is detected, the electroencephalogram is measured a plurality of times (the determination in S301 is “Yes”), and the action preparation potential is detected (the determination in S201 is “Yes”), the electroencephalogram when the driving operation is detected is Of the measured number of times, the ratio γ of the number of times the action preparation potential is detected is calculated (S302). When the ratio γ is equal to or greater than the threshold value γ1 (Yes in S303), it is estimated that the driver is in a state suitable for driving (S106). Thus, by considering the ratio γ of the number of times of detection, it can be estimated more accurately whether or not the driver is in a state suitable for driving.
In the third embodiment, the same effects as those of the second embodiment described above can be obtained, and detailed description thereof is omitted.

"effect"
Next, the main effects of the third embodiment will be described.
(1) In the driver state estimation method, when the driving operation is detected, the electroencephalogram is measured a plurality of times, and when the action preparation potential is detected, out of the number of times the electroencephalogram is measured when the driving operation is detected, the action preparation Consider the ratio γ of the number of times the potential is detected. That is, when the ratio γ is equal to or greater than a predetermined threshold γ1, it is estimated that the driver is in a state suitable for driving.
Thus, by considering the ratio γ of the number of times of detection, it can be estimated more accurately whether or not the driver is in a state suitable for driving.

<< 4th Embodiment >>
"Constitution"
In the fourth embodiment, it is determined whether or not the electroencephalogram after detecting the driving operation returns to the state before detecting the action preparation state, and whether the driver is suitable for driving according to the determination result. It is to estimate whether or not.
FIG. 10 is a flowchart showing the driving support process of the fourth embodiment.
Here, except that step S401 is added during the transition from step S201 to step S106, the process is the same as that of the second embodiment described above, and therefore, description of common parts is omitted.
In step S401, it is determined whether or not the electroencephalogram after detecting the driving operation has returned to the state before detecting the action preparation potential (action preparation state). Here, when the state before the action preparation potential is detected is returned to, the process proceeds to step S106. On the other hand, when not returning to the state before detecting the action preparation potential, the process proceeds to step S107.
The above is the driving support process.

<Action>
When the action preparation potential is detected (determination in S201 is “Yes”), it is determined whether the electroencephalogram after detecting the driving operation has returned to the state before the action preparation potential is detected. Here, when the state before the action preparation potential is detected is returned (the determination in S401 is “Yes”), it is estimated that the driver is in a state suitable for driving (S106). On the other hand, when the state does not return to the state before the action preparation potential is detected (determination in S401 is “No”), it is estimated that the driver is not in a state suitable for driving (S107).
In the fourth embodiment, the same effect as that of the second embodiment described above can be obtained, and detailed description thereof is omitted.

"effect"
Next, the main effects of the fourth embodiment will be described.
(1) In the driver state estimation method, when the action preparation potential is detected from the electroencephalogram before detecting the driving operation, the electroencephalogram after detecting the driving operation returns to the state before detecting the action preparation potential. Sometimes it is estimated that the driver is in a state suitable for driving. On the other hand, when the state does not return to the state before detecting the action preparation potential, it is estimated that the driver is not in a state suitable for driving.
Thus, by considering the brain wave after detecting the driving operation, it can be estimated with higher accuracy whether or not the driver is in a state suitable for driving.

  Although the present invention has been described with reference to a limited number of embodiments, the scope of rights is not limited thereto, and modifications of the embodiments based on the above disclosure are obvious to those skilled in the art.

DESCRIPTION OF SYMBOLS 11 Driver assistance apparatus 12 Driver state estimation apparatus 21 Electroencephalogram sensor (1st sensor)
22 Sensor group (second sensor)
23 Controller

Claims (8)

Measure driver's brain activity,
Detecting the driving operation of the driver,
A driver state estimation method for estimating whether or not the driver is in a state suitable for driving according to the brain activity when the driving operation is detected. Pre-store brain activity when the driver is driving in normal time as normal brain activity,
When the measured brain activity and the normal brain activity match, it is estimated that the driver is in a state suitable for driving, and when the measured brain activity does not match, it is estimated that the driver is not in a state suitable for driving. The driver state estimation method according to claim 1, wherein the driver state is estimated. When the brain activity is measured a plurality of times and the measured brain activity and the normal brain activity match,
It is estimated that the driver is in a state suitable for driving when the ratio of the number of times the detected brain activity coincides with the normal brain activity among the plurality of times is equal to or greater than a predetermined ratio. The driver state estimation method according to claim 2, wherein:   From the brain activity before detecting the driving operation, it is estimated that the driver is in a state suitable for driving when the behavior preparing state is detected, and a state suitable for driving when the behavior preparing state is not detected. The method of estimating a driver state according to any one of claims 1 to 3, wherein the driver state is estimated to be absent. From the brain activity before detecting the driving operation, when detecting an action ready state,
When the brain activity after detecting the driving operation returns to the state before detecting the action preparation state, it is estimated that the driver is in a state suitable for driving, and before the action preparation state is detected. The driver state estimation method according to any one of claims 1 to 3, wherein when the state does not return to the state, it is estimated that the driver is not in a state suitable for driving.   The brain activity is measured from at least one of the driver's brain wave, cerebral blood flow, heart rate, respiratory rate, sweat rate, and driver's face image. The driver state estimation method according to claim 1.   The driver state estimation method according to any one of claims 1 to 6, wherein when the driver estimates that the driver is not in a state suitable for driving, the driving support device is operated. A first sensor that measures the driver's brain activity;
A second sensor for detecting the driving operation of the driver;
And a controller that estimates whether or not the driver is in a state suitable for driving according to brain activity when the driving operation is detected.

Images