JP2007265377A - Driver state determining device and driving support device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To discriminate the state of a driver in more detail. <P>SOLUTION: At least two pieces of driver information selected out of driver information with degree of a wakening reflected driver information with the degree of concentration reflected, and driver information with driving ability reflected are detected, and a driver state determination threshold value for determining the state of the driver is determined based on the average value of the driver and standard deviation of each detected driver information, and vehicle/driving environment information showing a vehicle driving state or an external environment state. The state of the driver is determined based on each detected driver information and the determined driver state determination threshold value. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a driver state determination device and a driving support device, and in particular, a driver state determination device that determines a driver state using an index related to the driver, and a driving support device that uses the driver state determination device. About.

  As a conventional technique for determining an inattentive state of a driver, a technique (for example, Patent Document 1) for discriminating the degree of carelessness by discriminating a slight steering operation following the steering wheel stationary stage and the stationary steering stage, and operation Technology for detecting the degree of driver's carelessness from parameters (parameters including at least one of steering angle, accelerator pedal position, brake pedal position, driver's sitting state, and posture) (for example, Patent Document 2) Etc. are known.

  In addition, as a conventional technique for determining the driver state related to attention, the driver state (lane maintaining driving state, random driving state, side-by-side driving state, And at least one driving state indicating the intention of changing lanes) is known (for example, Patent Document 3).

  Also, change the dozing operation determination method based on the length of the alarm operation time from when the alarm is issued until the alarm is stopped after detecting the dozing operation state using the eye open / closed state or steering state A drowsiness driving alarm device provided with means is also known (for example, Patent Document 4).

  Furthermore, a vehicle control device is also known that includes a warning / awakening processing unit that determines a driver's state based on a line-of-sight direction, a face orientation, and a face position, and prompts attention or arousal based on the determination result (for example, Patent Document 5).

  By the way, as an unsuitable state in the driver state largely related to safe driving, there are a reduction in attention level due to a decrease in alertness, a lack of attention concentration on driving, and a reduction in driving ability. The technique of patent document 1 is intended for a reduction in attention level due to fatigue and arousal reduction in this inappropriate state, and patent document 2 is targeted for lack of attention concentration on driving in this inappropriate state.

Comparing the decline in attention level and lack of attention concentration is a phenomenon different from the decline in attention level due to fatigue and arousal, and lack of attention concentration due to operations other than driving and side effects. Since they are considered to be different, it is desirable to distinguish and distinguish between a reduction in attention level and a lack of attention concentration.
JP 2005-158077 A JP 2003-323700 A JP 2003-80969 A JP 2002-183900 A JP 2005-62911 A

  However, the techniques of Patent Document 1 and Patent Document 2 described above detect inadvertent states using steering wheel operations, accelerator pedals, and brake pedal operations as indices, and these indices relate to driving operations. For this reason, since it varies depending on the driving state (vehicle speed, traffic volume, road shape, etc.), it is difficult to determine an inattentive state using only these indices. For this reason, it is desirable to use an index that does not depend on the driving operation.

  Further, the technique of Patent Document 3 is a technique for determining an inattentive state such as an abrupt driving and a side-by-side driving by detecting a gaze direction and a steering operation amount as an index. Like each technique of patent document 2, since it is related to driving | operation operation and changes with driving | running | working states, it is difficult to determine an inattention state only by these parameters | indexes. For this reason, it is desirable to use or use an index that does not depend on the driving operation.

  In the technique of Patent Document 4 described above, the dozing operation determination method is changed based on the length of the alarm operation time from when the alarm is issued until the alarm is stopped, but the dozing operation determination criterion is changed (optimized). For this reason, there is a possibility that the alarm itself will be annoying, and it is inappropriate as a means for changing the method for determining the drowsy driving state.

  Moreover, in the technique of the above-mentioned Patent Document 5, a side or a drowsiness state is detected, and warning means and awakening means are determined based on the duration of the detection. There is a difference of up to, and it is not uniform. Also, the duration of the dozing state is not necessarily the same as the degree of wakefulness decline or driving ability decline. For this reason, it is possible that appropriate support (warning or awakening) cannot be performed if the support contents are determined by distinguishing the state only by the duration of the dozing state or determining the degree of danger.

  The present invention has been made to solve the above-described problems, and the driver state that is largely involved in safe driving is divided into three elements of arousal level, attention concentration level, and driving ability, and each element is reflected. To provide a driver state determination device capable of detecting a driver state in more detail by detecting at least two pieces of driver information and determining a driver state based on a combination of the detected driver information. Is the first purpose.

  In addition, a second object of the present invention is to provide a driving support device that performs driving support using the driver state determined in more detail using the above-described driver state determination device. .

  In order to achieve the first object, the present invention provides at least two selected from driver information reflecting arousal level, driver information reflecting attention concentration level, and driver information reflecting driving ability. Driver information detecting means for detecting one driver information, a driver information database for storing an average value and a standard deviation of each driver information detected by the driver information detecting means, and a vehicle driving state Alternatively, vehicle / driving environment information detection means for detecting vehicle / driving environment information indicating an external environment state, average values and standard deviations of individual drivers stored in the driver information database, and the vehicle / driving environment information detection Based on the vehicle / driving environment information detected by the means, a determination threshold value determining means for determining a driver state determination threshold value for determining the driver state, and detected by the driver information detection means. Each driver information, and based on the determined driver condition determination threshold by the determination threshold value determining unit is configured to include a determining impaired operation determination means for impaired operation, the.

  In the present invention, the driver state is divided into three elements of the arousal level, the attention concentration level, and the driving ability, driver information reflecting at least two elements is detected, and the average of each detected driver information of the individual driver is detected. A driver state determination threshold value for determining the driver state is determined based on the value and the standard deviation and the vehicle / driving environment information. Then, the driver state is determined based on each detected driver information and the determined driver state determination threshold value.

  In the present invention, since the driver state is determined based on the combination of the driver information reflecting each element of the arousal level, the attention concentration level, and the driving ability, the driver state can be determined in detail. That is, in the present invention, in addition to the concentrated state and the dozing state, which are the main targets of the prior art, for example, the state of abusiveness (a state of arousal but low attention concentration) and a state of conflict with sleepiness ( It is possible to separate and discriminate the state of low arousal but high attention concentration.

  In the present invention, the driver information that reflects the degree of arousal includes, as an index that does not depend on the driving operation, an electroencephalogram, a heartbeat state, an eye-closed time ratio that represents a ratio of a time during which the eyes are closed more than a certain amount, and a face image It is possible to use at least one of a facial expression sleepiness value that is measured from the facial expression information of the facial expression and represents a sleepiness state, and a self-reported sleepiness value reported by the driver.

  The driver information reflecting the attention concentration is a head vibration transmissibility obtained from a driver's head shaking measured by at least one of head acceleration, head image, and neck electromyogram. At least one of the driver's attention concentration target (which can be distinguished between driving and non-driving) measured by the direction of the line of sight can be used. When this attention concentration target information is added, the driver state can be determined more finely.

  In addition, the driver information reflecting the driving ability includes the low-frequency steering amount obtained from the reference steering amount and the steering amount, the accelerator pedal operation amount, the brake pedal operation amount, and the vehicle wobble degree indicating the fluctuation of the vehicle position in the lane width direction. , And at least one of an accelerator pedal operation amount and a brake pedal operation amount for maintaining the inter-vehicle distance from the preceding vehicle can be used. As the low frequency steering amount, the ratio of the two frequency bands can be used as an index in order to reduce the influence of the running state (especially speed and road shape). For example, the ratio between the reference steering amount and the steering amount A low-frequency steering amount ratio obtained from the natural logarithm of can be used.

  In the present invention, the closed eye ratio is used as the driver information reflecting the arousal level and the head vibration transmission rate is used as the driver information reflecting the attention concentration level, or the closed eye is used as the driver information reflecting the arousal level. It is effective to use the head vibration transmissibility and the visual target ratio as the driver information that reflects the degree of attention concentration while using the time ratio.

  Furthermore, in the present invention, it is effective to use the eye-closed time ratio as the driver information that reflects the degree of arousal and to use the low frequency steering amount as the driver information that reflects the driving ability. Further, it is effective to use the head vibration transmissibility as the driver information that reflects the degree of attention concentration, and to use the vehicle wobble degree as the driver information that reflects the driving ability.

  In addition, the driver's condition is determined by using the driver condition determination threshold determined based on the average value and standard deviation of each driver information and the vehicle / driving environment information. The driver state can be determined. Since the driver state determination threshold is determined according to the vehicle / driving environment information, the driver state can be determined according to the vehicle / driving environment.

  Further, in the present invention, since the detected driver information data of the individual driver is used and the driver state determination threshold calculated based on this is used, the level (average value) of the driver information data of the individual driver is used. It is possible to determine the driver's condition that is suitable for or variation (standard deviation).

  As described above, according to the driver state determination apparatus of the present invention, it is possible to determine the exact driver state corresponding to the vehicle and the driving environment while being suitable for the individual driver.

  In order to achieve the second object, the driving support device according to the present invention includes a driver status determination device and a type and timing of driving support according to the driver status determined by the driver status determination means. And driving support control means for controlling the driving support means.

  According to the driving support device of the present invention, optimal driving support according to carelessness can be performed by performing driving support control corresponding to the driver state determined as described above. On the contrary, the troublesomeness caused by unnecessary assistance can be reduced by delaying the presentation of an alarm when the driver is in a good state according to the driving environment.

  As described above, according to the driver state determination device of the present invention, at least two of the driver information reflecting the arousal level, the driver information reflecting the attention concentration level, and the driver information reflecting the driving ability. Since the driver state is determined based on the driver information, an effect that the driver state can be determined in more detail can be obtained.

  In addition, according to the driving support apparatus of the present invention, it is possible to obtain the effect that the driving support according to the driver state determined in more detail can be performed.

  Hereinafter, embodiments of the present invention will be described in detail. In the first embodiment of the present invention, as shown in FIG. 1, a driver information detector 10 is provided for detecting a plurality of driver information of a driver that reflects the degree of arousal and the attention concentration. ing. In the present embodiment, as the driver information, a plurality of pieces of driver information that reflect the arousal level and the attention concentration level are used, and the driver state is determined in detail based on a combination of the plurality of driver information. be able to.

  In the first embodiment, as the driver information reflecting the degree of arousal, as the information that reflects the degree of attention closed and the degree of attention concentration, the head shaking The head vibration transmissibility obtained from the quantity is used.

  For this reason, as shown in FIG. 1, the driver information detector 10, as shown in FIG. 1, uses the camera 10 </ b> A that captures the driver's head from the face side, and calculates the driver's eye closing time from the driver ’s facial image captured by the camera 10 </ b> A. An eye-closing time detector 10B to detect, an acceleration detector 10C to detect head acceleration from the head image of the driver imaged by the camera 10A, and an acceleration sensor 10D to detect vertical acceleration at the lower part of the seat bottom. It is configured.

  Further, a vehicle / driving environment information detector 12 for detecting vehicle / driving environment information, which is information indicating the vehicle driving state or the external environment state, is provided.

  Vehicle / driving environment information includes vehicle speed, vehicle acceleration, vehicle angular acceleration, distance between the front vehicle and the host vehicle, front image information of the host vehicle, weather, time, driving time, and road information from the car navigation (road At least one of type and traffic volume) can be detected.

  The driver information detector 10 and the vehicle / driving environment information detector 12 are connected to a control circuit 16 constituted by a computer. The control circuit 16 is connected with a driver information database 14 for storing driver information data, an average value and a standard deviation of the data, and a driving support means 20.

  As shown in FIG. 1, the driving support means 20 includes a speaker 20 </ b> A that displays driving support information by sound, an information presentation device 20 </ b> B such as car navigation that displays driving support information by an image, and a retractor that winds up a seat belt 18. A seat belt tension control device 20C that controls the tension of the seat belt 18 by controlling (not shown), an air conditioner 20D that generates scent and negative ions, generates oxygen, and adjusts the temperature inside the vehicle, and the seat bottom A sheet vibration device 20E that is provided in the lower portion and vibrates the sheet is provided. In addition, a control unit (not shown) that performs vehicle motion control such as braking force control and steering reaction force control may be provided to compensate for the reduction in driving ability, such as increasing the braking force when the driving ability is reduced. The driving support means 20 may be provided with at least one of these.

  A program for realizing various functions is stored in the control circuit 16, and the functions realized by the control circuit are represented by a functional block diagram. As shown in FIG. 2, data detected by the driver information detector 10 is stored. Driver information detecting means 16D for detecting driver information based on the vehicle, driving environment information detecting means 16E for detecting vehicle / driving environment information based on the data detected by the vehicle / driving environment information detector 12, driving The driver state determination means 16A for determining the driver state based on the driver information detected by the driver information detection means 16D, the information stored in the driver information database 14 and the vehicle / driving environment information detection means 16E are detected. The determination threshold value determining means 16B for determining the determination threshold value and the driving support control means 16C for controlling the driving support means 20 can be represented on the basis of the received information.

  Hereinafter, control according to the program in the control circuit of the present embodiment will be described.

  The driver information detection means 16D detects the driver's eye-closing time ratio X (t) and head vibration transmission rate Y (t) shown in FIG. 3 based on the data detected by the driver information detector 10. And output to the driver state determination means 16A. In addition, the detected eye-closing time ratio X (t) and head vibration transmission rate Y (t) are stored in the driver information database 14 in association with the identification information indicating the driver, and the detected information and information are stored. Using the obtained information, the level (average value) and fluctuation (standard deviation) of the driver are calculated, and the accumulated information is updated.

  Here, the eye closing time ratio X (t) is the ratio of the time during which the eyes are closed at a certain level or more (for example, 80% or more) with respect to the time when the eyes are opened, and the level of X (t) is as shown in FIG. The higher the value, the greater the drowsiness (decreased arousal).

Head vibration transmissibility Y (t) is the acceleration alpha _h in a frequency band which is determined according to the driver in the vertical acceleration of the head shaking amount of the driver, and the acceleration alpha _h in the vertical acceleration of the lower sheet ass From the acceleration α _s in the same frequency band, it is obtained from the natural logarithm of the ratio of the acceleration α _h to the acceleration α _s as shown in the following equation (1). As shown in FIG. 3, the higher the level of head vibration transmission rate Y (t) is, the lower the attention concentration is (the depth of visual recognition is shallow).

Y (t) = ln (α _h (t)) − ln (α _s (t)) (1)
In the driver information database, the driver information data input from the driver information detector 10 is recorded together with the individual driver level (average value) and fluctuation (standard deviation) data, and the recorded individual driver information is recorded. Level (average value) and variation (standard deviation) data are updated.

The data of the driver information database, the updated average values (X _mean , Y _mean ) and standard deviation (X _SD , Y _SD ) are read by the determination threshold value determination means 16B and used for determination threshold value determination. Is done. Further, the determination threshold value determining means 16B includes vehicle / driving environment information such as the vehicle speed detected by the vehicle / driving environment information detecting means 16E, the inter-vehicle distance from the preceding vehicle, and road information (road type) from the car navigation. Entered.

Based on the vehicle / driving environment information input from the vehicle / driving environment information detector 12, the determination threshold determination means 16 </ b> B determines a reference determination threshold (X _th , Y _th ) according to Table 1 below, and a driver information database based on the level of the driver individual input from 14 (average value) and the variation (standard deviation), the reference determination threshold (X _th, Y _th) corrected correction value ^{_{(X th *, Y th *}} ) to calculate the To the driver state determination means 16A.

As shown in Table 1, the reference determination threshold values (X _th , Y _th ) are urban roads, roads dedicated to automobiles (high traffic volume and short inter-vehicle distance), roads dedicated to automobiles (low traffic volume and vehicle speed). Low) and in accordance with vehicle / driving environment information such as mountain roads.

When the average value of the driver information when defining the reference judgment threshold values in Table 1 is M _X0 , M _Y0 and the standard deviation is SD _X0 , SD _Y0 , the average values M _X , M _Y , standard deviations SD _X , SD _Y In the case of a driver having the above, the driver state determination threshold is corrected as follows: X _th ^* , Y _th ^* .

X _th ^* = M _X + SD _X / SD _X0 (X _th −M _X0 ) (2)
^{_{Y th * = M Y + SD}} Y / SD Y0 (Y th -M Y0) ... (3)
Here, the driver state determination threshold value X _th is expressed as a a × SD _X0 larger than M _X0 by the average value M _X0 and the standard deviation SD _X0 of the following equation (4).

X _th = M _X0 + aSD _X0 (4)
However, a is a constant.

Average value M _X, the determination threshold value X _th ^* is the driver of the standard deviation SD _X, represented by the following equation (5) in the same manner by the mean value M _X and the standard deviation SD _X.

X _th ^* = M _X + aSD _X (a is a constant) (5)
Here, a is a constant common to X _th and X _th ^* , and a = 1 / SD _X0 (X _th −M _X0 ) from the equation (4). Equation (2) is obtained.

  Also, the expression (3) can be similarly obtained from the following expression.

Y _th = M _Y0 + bSD _Y0 ,
Y _th ^* = M _Y + bSD _Y
However, b is a constant.

The driver state determination unit 16A uses the data X (t) and Y (t) input from the driver information detection unit 16D as the driver state determination threshold correction value (X _th ^* ) input from the determination threshold determination unit 16B ^. , Y _th ^* ), the driver's individual driver state is determined as shown in FIG. 4, and is output to the driving support control means 16C.

  The determination based on the value corrected by adapting the determination threshold value of FIG. 4 to an individual is determined from the relationship between the attention index and the driver state in Table 2 below.

  When drowsiness is low and attention concentration is low, it is determined to be in a state of disorder. When drowsiness is low and attention concentration is high, it is determined as concentration. When sleepiness is high and attention concentration is low, it is determined to be dozing. If it is determined that sleepiness is high and the concentration of attention is high, it is determined that there is a drowsiness conflict state. As the threshold for determining whether sleepiness at this time is low or high and the threshold for determining whether the attention concentration is low or high, correction values determined by the determination threshold determination means 16B are used as shown in FIG.

  The driving support control unit 16C determines the optimum driving support type and timing according to the driver state and the driving support control example shown in Table 3 below according to the driver state determined by the driver state determination unit 16A. Output to the support means 20. In the driving support means 20, the danger alarm is emitted from the speaker 20A, presented by displaying the danger alarm on the information presentation apparatus 20B, or the danger warning is emitted from the speaker 20A and the information presentation apparatus. Present a danger warning to 20B. Further, the air conditioner 20D is driven as necessary.

  A driving support control example shown in Table 3 will be described. If it is determined to be dozing, it will prompt the presentation of danger information and recommend a break, and if it is determined to be drowsy conflict, it will accelerate the presentation of surrounding danger information and a scent for awakening (negative ions If it is determined that it is in a messy state, it will promptly present a forward danger warning and present a refreshing scent. If it is determined to be in a concentrated state, a danger warning will be presented. Is slower than in the above case.

  In the driving support control described above, when it is determined that the patient is in a drowsiness state or drowsiness conflict state, the tension of the seat belt 18 may be increased by the seat belt tension control device 20C. Thus, when controlling the tension of the seat belt, the magnitude of the tension of the seat belt, the timing of changing the tension, the change time, and the like may be different between the dozing state and the drowsiness conflict state.

  Further, when the air conditioner 20D is driven to generate at least one of negative ions, aroma, oxygen, sound, and vibration, the generation timing, generation amount, generation time, and generation according to the driver state At least one of the types may be changed. For example, when vibration is generated, the amplitude may be changed as the generation amount, and the frequency may be changed as the generation type.

  Further, the air conditioner 20D may be driven to blow cool air for awakening, and the temperature inside the vehicle may be lowered. When controlling the temperature in this way, the change timing, change amount, change direction (whether the temperature is raised or lowered), change time (time during which the temperature is changed), etc., are determined according to the driver state. Can be changed.

  In the present embodiment, the case where the closed eye rate is used as the driver information reflecting the degree of arousal has been described as an example, but instead of the closed eye rate, the brain wave, the heartbeat state, and the facial expression of the face image You may make it use the facial expression sleepiness value measured from information and showing the sleepiness state or the self-reported sleepiness value reported by the driver.

  Moreover, although the example which detects the amount of head fluctuations from a head image was demonstrated, you may make it measure the amount of head fluctuations by a neck electromyogram.

  Next, a second embodiment of the present invention will be described.

  As shown in FIG. 5, in this embodiment, in addition to the first embodiment, a detector 10E for detecting the driver's line of sight and face orientation is provided. The functional block diagram of the control circuit 16 is the same as that in FIG. In the present embodiment, as the driver information, a plurality of pieces of driver information that reflect the arousal level and the attention concentration level are used, and the driver state is determined in detail based on a combination of the plurality of driver information. . In the present embodiment, the closed eye ratio is used as the driver information that reflects the degree of arousal, and the head vibration transmission rate and the visual target ratio are used as the driver information that reflects the degree of attention concentration.

  Next, driving support control by the control circuit of the second embodiment will be described.

  Based on the data detected by the driver information detector 10, the driver information detection means 16 </ b> D, based on the data detected by the driver information detector 10, the eye-closing time ratio X (t), the driver's head vibration transmission rate Y (t), and the visual information The target ratio Z (t) is detected and output to the driver state determination means 16A. Further, X (t), Y (t), and Z (t) data are stored in the driver information database 14.

  Here, the eye closing time ratio X (t) is the ratio of the time during which the eyes are closed at a certain level or more (for example, 80% or more) with respect to the time when the eyes are opened. As shown in FIG. The higher the value, the greater the drowsiness (decreased arousal).

Further, as described above, the head vibration transmission rate Y (t) is the acceleration α _h in the frequency band determined according to the driver in the vertical acceleration of the amount of head fluctuation of the driver, and the seat bottom This is a value obtained by the following equation (6) from acceleration α _s in the same frequency band number as α _h in the vertical acceleration at the bottom. The head vibration transmission rate Y (t) indicates that the higher the level, the lower the attention concentration (the depth of visual recognition is shallower).

Y (t) = ln (α _h (t)) − ln (α _s (t)) (6)
The visual target ratio Z (t) is a ratio of time in which the visual target is classified into objects other than the front and the front, and the respective gaze stop times are totaled. Assuming that the forward gaze stop time is E _f (t) and the gaze stop time to a subject other than the front is E _n (t), the following expression (7) is expressed. The visual target ratio Z (t) indicates that attention is concentrated on driving as the level increases.

Z (t) = E _f (t) / E _n (t) × 100 (7)
The driver information detecting means 16D accumulates each data of the eye closing time ratio X (t), the head vibration transmission ratio Y (t), and the visual target ratio Z (t) in the driver information database 14, and the driver's personal information The level (average value) and fluctuation (standard deviation) data are calculated, and the recorded average value and standard deviation data are updated. The recorded and updated average values (X _mean , Y _mean , Z _mean ) and standard deviation (X _SD , Y _SD , Z _SD ) data are read by the determination threshold value determination means 16B.

  The vehicle / driving environment information detection means 16E takes in the vehicle speed detected by the vehicle / driving environment information detector 12, the distance between the vehicle and the road information (road type) from the car navigation, and the determination threshold value determination means 16B. And output to the driving support control means 16C.

The determination threshold value determination unit 16B determines a reference determination threshold value (X _th , Y _th , Z _th ) according to the following Table 4 based on the vehicle / driving environment information input from the vehicle / driving environment information detection unit 16E, and the driver Based on the average value and standard deviation of the individual driver input from the information database 14, a correction value (X _th ^* , Y _th ^* , Z _th ^* ) obtained by correcting the reference determination threshold value is calculated to calculate the driver state. Output to 16A.

The reference determination threshold _values (X _th , Y _th , Z _th ) are determined in accordance with vehicle / driving environment information such as urban roads, automobile roads, and mountain roads, as in Table 1.

The driver state determination unit 16A uses the data X (t), Y (t), and Z (t) input from the driver information detection unit 16D as the driver state determination battle input from the determination threshold value determination unit 16B. The driver state is checked based on the correction values (X _th ^* , Y _th ^* , Z _th ^* ) of the values based on FIG. 6, and is output to the driving support control means 16C.

In the present embodiment, based on FIG. 7, after determining whether the driver state is one of the concentrated state, the sloppy state, the drowsiness conflict state, and the dozing state, as in FIG. 4, the concentrated state and sleepiness are determined. The attention concentration target is determined again at the Z (t) level for each driver state in the conflict state. When Z (t)> Z _th ^* , the attention concentration target is determined to be driving, and when Z (t) <Z _th ^* , the attention concentration target is determined to be other than driving.

  In the driving support control unit 16C, the optimum type and timing of driving support are determined according to the driver state determined by the driver state determination unit 16A, output to the driving support unit 20, and the driving support unit 20 performs the next operation. Driving assistance is provided as shown in Table 5.

  The driving support control in Table 5 will be described. When the state is a slumber and doze, the control is performed in the same manner as in Table 3. However, when the subject is a drowsiness conflict and the attention-focused subject is driving, the presentation of the surrounding danger warning is accelerated. At the same time, the scent for awakening is presented, and when the drowsiness conflict state and the attention focused object is other than driving, the presentation of the danger warning is accelerated. Also, when driving in the concentrated state and the attention-concentrated object, the presentation of the danger information is delayed, and when in the concentrated state and the attention-concentrating object is other than the driving, the presentation of the forward danger warning is accelerated and the information display device is Use this to guide the locations where accidents occur frequently.

  In the present embodiment, the case where the closed eye rate is used as the driver information reflecting the degree of arousal has been described as an example, but instead of the closed eye rate, the brain wave, the heartbeat state, and the facial expression of the face image You may make it use the facial expression sleepiness value measured from information and showing the sleepiness state or the self-reported sleepiness value reported by the driver.

  Next, a third embodiment of the present invention will be described. In the third embodiment, as shown in FIG. 8, in place of the determination threshold value determining means of the first embodiment, the determination threshold value is determined according to the selection signal input from the support level selection means 16F. Threshold determining means 16G is provided.

  As with the first embodiment, the driver information detection unit 16D detects the driver's eye-closed time ratio X (t) and head vibration transmission rate Y (t) and outputs them to the driver state determination unit 16A. To do. Further, data is accumulated in the driver information database 14.

  Here, the eye closing time ratio X (t) is the ratio of the time during which the eyes are closed more than a fixed amount (for example, 80% or more) with respect to the time of eye opening, as described above, and drowsiness (wakefulness) as X (t) increases. (Decrease) is large.

Head vibration transmissibility Y (t) is the acceleration alpha _h in a frequency band which is determined according to the driver in the vertical acceleration of the head shaking amount of the driver, the same as the alpha _h in the vertical acceleration of the lower sheet ass This value is obtained from the above equation (1) from the acceleration α _S in the frequency band. The higher Y (t), the lower the attention concentration (the depth of visual recognition is shallow).

The driver information database 14 stores the driver information data input from the driver information detection means 16D, and records / updates the data of the driver's individual level (average value) and fluctuation (standard deviation). The recorded and updated average values (X _mean , Y _mean ) and standard deviation (X _SD , Y _SD ) data are output to the determination threshold value determination means 16G.

  In the support level selection means 16F, the frequency with which the driver gives warnings and assistance is selected in three stages (1) to (3), for example, as described below. The selected result is input to the determination threshold value determination unit 16G.

(1) Notification mode: relatively high warning and support (2) Normal mode: normal setting (3) Silent mode: relatively low warning and support The decision threshold decision means 16G is selected by the support level selection means 16F Based on the support level, a reference determination threshold value (X _th , Y _th ) is determined according to Table 6 below, and a correction value (based on the average value and standard deviation of the individual driver input from the driver information database 14 is determined. X _th ^* , Y _th ^* ) are calculated and output to the driver state determination means 16A.

The driver state determination means 16A uses the data X (t) and Y (t) input from the driver information detection means 16D as the driver state determination threshold correction value (X _th ^* , X) input from the determination threshold value determination means 16B. Y _th ^* ) is compared to determine the driver state and output to the driving support control means 16C.

  Next, a fourth embodiment of the present invention will be described.

  In this embodiment, as shown in FIG. 9, a steering angle sensor 10F for detecting a steering angle is provided in place of the acceleration detector 10C and the acceleration sensor 10D of the first embodiment. The functional block diagram of the control circuit 16 is the same as that in FIG. In the present embodiment, a plurality of pieces of driver information that reflect the arousal level and the driving ability are used as the driver information, and the driver state is determined in detail based on a combination of the plurality of pieces of driver information. In the present embodiment, the closed eye time ratio is used as the driver information that reflects the degree of arousal, and the low-frequency steering amount is used as the driver information that reflects the driving ability.

  Next, driving support control by the control circuit of the fourth embodiment will be described.

  Based on the data detected by the driver information detector 10, the driver information detection means 16D detects the driver's eye closing time ratio X (t) and the low frequency steering amount ratio Y (t) shown in FIG. And output to the driver state determination means 16A. Further, X (t) and Y (t) data are stored in the driver information database 14.

  Here, the eye closing time ratio X (t) is the ratio of the time during which the eyes are closed at a certain level or more (for example, 80% or more) with respect to the time of eye opening, as shown in FIG. Thus, the higher the level of X (t), the greater the drowsiness (decrease in alertness).

Further, the low frequency steering amount ratio Y (t) is obtained by the steering angle sensor 10F by using the steering amount in two different frequency bands, that is, the reference steering amount θ ₀ (t) (frequency band f ₀ ) and the steering amount θ (t). ) (Frequency band f) is measured, and is a value obtained from the natural logarithm of the ratio between the reference steering amount θ ₀ (t) and the steering amount θ (t), as shown in the following equation (8). The low frequency steering amount ratio Y (t) indicates that the higher the level, the lower the smoothness of steering (steering ability).
Y (t) = ln (θ (t)) − ln (θ ₀ (t)) (8)

The driver information detection means 16D accumulates each data of the eye closing time ratio X (t) and the low frequency steering amount ratio Y (t) in the driver information database 14, and the individual level (average value) and fluctuation ( Standard deviation) data is calculated, and the recorded average value and standard deviation data are updated. The recorded and updated average values (X _mean , Y _mean ) and standard deviation (X _SD , Y _SD ) data are read by the determination threshold value determination means 16B.

  The vehicle / driving environment information detection means 16E takes in the vehicle speed detected by the vehicle / driving environment information detector 12, the distance between the vehicle and the road information (road type) from the car navigation, and the determination threshold value determination means 16B. And output to the driving support control means 16C.

Based on the vehicle / driving environment information input from the vehicle / driving environment information detecting means 16E, the determination threshold determining means 16B determines the reference judgment thresholds (X _th1 , X _th2 , Y _th1 , Y _th2 ) according to Table 7 below. . As in Table 1, the reference determination threshold _values (X _th1 , X _th2 , Y _th1 , Y _th2 ) are determined according to vehicle / driving environment information such as urban roads, automobile exclusive roads, and mountain roads. Here, two determination thresholds are determined for each of the closed eye time ratio X (t) and the low frequency steering amount ratio Y (t).

Further, in the determination threshold value determination unit 16B, correction values (X _th1 ^* , X _th2 ^* , Y _{th1) obtained} by correcting the reference determination threshold value based on the average value and standard deviation of the individual driver input from the driver information database 14. ^* , Y _th2 ^* ) is calculated and output to the driver state determination means 16A.

Here, the correction of the reference determination threshold will be described in detail.
When the average value of the driver information when defining the reference judgment threshold values in Table 7 is M _X0 , M _Y0 and the standard deviation is SD _X0 , SD _Y0 , the average values M _X , M _Y , standard deviations SD _X , SD _Y The driver state determination threshold _values X _th1 , X _th2 , Y _th1 , Y _th2 are corrected to the following X _th1 ^* , X _th2 ^* , Y _th1 ^* , Y _th2 ^* .

X _th1 ^* = M _X + SD _X / SD _X0 (X _th1 -M _X0 ) (9)
X _th2 ^* = M _X + SD _X / SD _X0 (X _th2 −M _X0 ) (10)
^{_{Y th1 * = M Y + SD}} Y / SD Y0 (Y th1 -M Y0) ... (11)
^{_{Y th2 * = M Y + SD}} Y / SD Y0 (Y th2 -M Y0) ... (12)

Here, the driver state determination threshold value X _th1 is expressed as the following equation (13) as a value a ₁ × SD _X0 larger than M _X0 by the average value M _X0 and the standard deviation SD _X0 .
X _th1 = M _X0 + a ₁ SD _X0 (13)
However, _{a 1} is a constant.

Average value M _X, the determination threshold value X _th1 ^* is the driver of the standard deviation SD _X, represented by the following equation (14) in the same manner by the mean value M _X and the standard deviation SD _X.

X _th1 ^* = M _X + a ₁ SD _X (a ₁ is a constant) (14)
Here, a ₁ is a constant common to X _th1 and X _th1 ^{*. Since} a ₁ = 1 / SD _X0 (X _th1 −M _X0 ) from the equation (13), this is substituted into the equation (14). Then, the above equation (9) is obtained.

  Further, the equations (10) to (12) are similarly obtained from the following equations.

X _th2 = M _X0 + a ₂ SD _Y0 , X _th2 ^* = M _X + a ₂ SD _X (a ₂ is a constant)
Y _th1 = M _Y0 + b ₁ SD _Y0 , Y _th1 ^* = M _Y + b ₁ SD _Y (b ₁ is a constant)
Y _th2 = M _Y0 + b ₂ SD _Y0 , Y _th2 ^* = M _Y + b ₂ SD _Y (b ₂ is a constant)

The driver state determination unit 16A uses the data X (t) and Y (t) input from the driver information detection unit 16D as correction values (X for the driver state determination threshold value input from the determination threshold value determination unit 16B). _th1 ^* , _Xth2 ^* , _Yth1 ^* , _Yth2 ^* ) to determine the driver state based on FIG.

  The determination based on the value corrected by adapting the determination threshold in FIG. 11 to suit the individual is determined from the relationship between sleepiness and driver state in Table 8 below, and the relationship between the driving ability index and driver state in Table 9. ing.

  As shown in Table 8, when X (t) is located in the area indicated by 0 in FIG. 11, there is no decrease in wakefulness, and it is determined that there is no sleepiness, and when it is located in the area indicated by 1. Is determined to have drowsiness and drowsiness, and when located in the region indicated by 2, it is determined that the drowsiness is large and drowsiness is large.

  In addition, as shown in Table 9, when Y (t) is located in the region indicated by A in FIG. 11, it is determined that there is no reduction in driving ability, and when it is located in the region indicated by B. Is determined to be wobbling or having decreased inter-vehicle distance maintenance capability, and driving capability has decreased, and if it is located in the area indicated by C, there is a high possibility of lane departure or rear-end collision. It is determined that the capacity drop is large.

  The driver state determination unit 16A determines the driver state to be one of nine driver states (0-A state to 2-C state) shown in FIG. 11, and sends the determination result to the driving support control unit 16C. Output.

  The driving support control unit 16C determines the optimum driving support type and timing according to the driver state and the driving support control example shown in Table 10 below according to the driver state determined by the driver state determination unit 16A. Output to the support means 20.

  An example of driving support control shown in Table 10 will be described. When it is determined that the state is 0-A, there is no decrease in arousal level and there is no decrease in driving ability, so driving assistance for improving and maintaining arousal and alerting is not provided, and only forward traffic congestion information is presented. . When it is determined to be in the 0-B state, the driving ability is reduced and it is in a messy state, so the surrounding danger information and the accident frequent spot guidance are presented, and information to alert the surroundings is presented. Advance. If it is determined to be in the 0-C state, there is no drowsiness, but there is a high possibility that the driving ability has dropped significantly due to driving aside. Accelerate information presentation to arouse Further, in vehicle motion control, the braking force is increased to cover the decrease in driving ability.

  If it is determined to be in the 1-A state, there will be no decrease in driving ability, but there will be drowsiness. Presents frequent location guidance. When it is determined to be in the 1-B state, drowsiness and driving ability are reduced, so that vibration and scent for improving awakening and maintenance, or oxygen is generated longer than in the 1-A state. A message for guiding the parking to perform stretching is presented, and information is presented to alert the surroundings and a lane departure warning is output early. When it is determined to be in the 1-C state, drowsiness and driving ability are greatly reduced, so vibration and scent for improving and maintaining arousal, or oxygen is generated longer than in the 1-B state. Let In addition, it presents a message to guide the shoulder stop and perform exercises for awakening, as well as information to call attention to the surrounding area and output a lane departure warning, as well as a warning to the front. Information and rear-end collision warning are performed early. Furthermore, in the vehicle motion control, the steering reaction force is increased to cover the decrease in driving ability.

  If the 2-A state is determined, the driving ability is not reduced, but the arousal level is greatly reduced, so that sounds and vibrations for improving and maintaining arousal are generated, and cold air is emitted. It also presents a message that induces breaks, and information on accident location. If the 2-B state is determined, the degree of arousal is greatly reduced and the driving ability is also reduced. Therefore, the sound and vibration for improving and maintaining arousal are generated longer than the 2-A state, and cold air is emitted. Or In addition, a message for guiding the parking to perform stretching is presented, and information presentation for alerting the surroundings and output of a lane departure warning are performed early. When the 2-C state is determined, the arousal level and the driving ability are greatly reduced. Therefore, the sound volume is increased compared to the 2-B state to generate a sound for improving and maintaining arousal, or 2-B Generates vibrations or emits cool air longer than the state. In addition to presenting a message to guide the shoulder stop and perform gymnastics for awakening, not only information to alert the surroundings and output of lane departure warning, but also forward danger information and accident occurrence Provide point guidance early. Furthermore, in the vehicle motion control, the braking force and the steering reaction force are increased to cover the decrease in driving ability.

  The sound, scent, vibration generation time, intensity, size, and type may be changed according to the driver's condition. When displaying information, the color, character / symbol size may be changed. You may make it stand out. Also in the vehicle motion control, the magnitude of the braking force or the steering reaction force may be adjusted.

  Note that as driver information reflecting the driving ability, an accelerator pedal operation amount or a brake pedal operation amount may be used instead of the low frequency steering amount. In this case, as shown in FIG. 9, an accelerator / brake pedal operation amount sensor 10G for detecting an accelerator pedal operation amount and a brake pedal operation amount is attached to the accelerator pedal and the brake pedal. In this case, only the accelerator pedal operation amount sensor for detecting the accelerator pedal operation amount or only the brake pedal operation amount sensor for detecting the brake pedal operation amount may be attached. An accelerator pedal for maintaining the distance between the vehicle and the front vehicle based on the vehicle-to-vehicle distance detected by the vehicle / driving environment information detector 12 and the detection result of the accelerator / brake pedal operation amount sensor 10G. The operation amount or the brake pedal operation amount may be detected and used as driver information reflecting the driving ability.

  Next, a fifth embodiment of the present invention will be described.

  In the present embodiment, as shown in FIG. 12, instead of the eye-closed time detector 10B of the first embodiment, an external environment camera that is mounted on a vehicle and includes a lane in which the vehicle travels and shoots the periphery of the vehicle. 10H and a vehicle wobbling detector 10J for detecting a vehicle wobbling degree indicating a change in the vehicle position in the lane width direction based on images taken by the camera 10H for outside environment.

  FIG. 13 is a functional block diagram of the control circuit 16 in the present embodiment, and driving support selection means 22 is provided in addition to the configuration of FIG. 8 of the third embodiment. The driving assistance selection means 22 is a means for the driver himself to select driving assistance contents in advance. For example, driving assistance is performed according to the driver's state by a button or the like from the displayed driving assistance contents selection items. The content can be selected.

  In this embodiment, a plurality of pieces of driver information that reflect the attention concentration and driving ability are used as the driver information, and the driver state is determined in detail based on a combination of the plurality of pieces of driver information. . In the present embodiment, the head vibration transmissibility obtained from the head shaking amount is used as the driver information reflecting the attention concentration, and the vehicle wobbling degree is used as the driver information reflecting the driving ability.

  Next, driving support control by the control circuit of the fifth embodiment will be described.

  The driver information detection means 16D detects the driver's head vibration transmission rate X (t) and the vehicle wobbling degree Y (t), and outputs them to the driver state determination means 16A. Further, X (t) and Y (t) data are stored in the driver information database 14.

Here, as described above, the head vibration transmission rate X (t) is the acceleration α _h in the frequency band determined according to the driver in the vertical acceleration of the driver's head shaking amount, the seat, This is a value obtained from the following equation (15) from the acceleration α _s in the same frequency band as α _h in the vertical acceleration at the bottom of the bottom. The head vibration transmission rate X (t) indicates that the higher the level, the lower the attention concentration (the depth of visual recognition is shallower).
X (t) = ln (α _h (t)) − ln (α _s (t)) (15)

  Further, the vehicle wobbling degree Y (t) is a value indicating the fluctuation of the vehicle position in the lane width direction. Here, the vehicle wobbling degree Y (t) is the vehicle position in the lane (for example, the center position of the lane width) The standard deviation of the distance from the center position of the vehicle width is calculated. The vehicle wobbling detector 10J detects the vehicle position with respect to the lane based on the image taken by the external environment camera 10H, and calculates the standard deviation. The higher the vehicle wobbling degree Y (t) is, the lower the steering ability is.

The driver information detection means 16D accumulates each data of the head vibration transmission rate X (t) and the vehicle wobbling degree Y (t) in the driver information database 14, and the individual level (average value) and fluctuation ( Standard deviation) data is calculated, and the recorded average value and standard deviation data are updated. Recorded and updated mean value (X _mean, Y _mean), and the standard deviation (X _SD, Y _SD) Each data is read by determining the threshold value determination unit 16B.

  The vehicle / driving environment information detection means 16E takes in the vehicle speed detected by the vehicle / driving environment information detector 12, the distance between the vehicle and the road information (road type) from the car navigation, and the determination threshold value determination means 16B. And output to the driving support control means 16C.

The driver information database 14 stores the driver information data input from the driver information detection means 16D, and records / updates the data of the driver's individual level (average value) and fluctuation (standard deviation). The recorded and updated average values (X _mean , Y _mean ) and standard deviation (X _SD , Y _SD ) data are output to the determination threshold value determination means 16G.

  In the support level selection means 16F, the frequency at which the driver issues an alarm or support in advance is selected in three stages, “notification mode”, “normal mode”, and “silent mode”, as in the third embodiment. The result selected by the driver is input to the determination threshold value determination unit 16G.

The determination threshold value determination unit 16G determines a reference determination threshold value (X _th1 , X _th2 , Y _th1 , Y _th2 ) according to the following Table 11 based on the support level selected by the support level selection unit 16F, and the driver information database. 14, correction values (X _th1 ^* , X _th2 ^* , Y _th1 ^* , Y _th2 ^* ) are calculated on the basis of the average value and standard deviation of the driver input from 14 and output to the driver state determination means 16A. .

The driver state determination means 16A uses the data X (t) and Y (t) input from the driver information detection means 16D as the driver state determination threshold correction value (X _th1 ^* , X) input from the determination threshold value determination means 16B. X _th2 ^* , Y _th1 ^* , Y _th2 ^* ) are compared with each other to determine the driver state and output it to the driving support control means 16C.

  The driving support control unit 16C performs driving support according to the selection result selected in advance by the driving support selection unit 22. The driver preliminarily selects and sets the support contents to be implemented according to the driver state determined by the driver state determination unit 16A using the driving support selection unit 22 before starting driving. The setting contents are stored according to each driver state as shown in Table 10. In this way, since the driver can select the driving assistance content, driving assistance more suitable for the individual driver can be implemented.

  In each of the above embodiments, two pieces of driver information selected from driver information that reflects arousal level, driver information that reflects attention concentration, and driver information that reflects driving ability are detected. The example of determining the driver state is explained, but three pieces of driver information are detected: driver information reflecting the degree of arousal, driver information reflecting the attention concentration, and driver information reflecting the driving ability. Then, the driver state may be determined. In addition, the driver himself may select in advance at least two pieces of driver information used for determining the driver state from the detectable driver information, and the selected driver information may be used. .

  In car driving, a reduction in attention level due to reduced arousal, lack of attention concentration in driving, and a decrease in driving ability are dangerous due to delays in response to brakes, oversight of pedestrians, misoperation, misjudgment, etc. As described above, according to each of the above embodiments, the driver state can be determined in detail without being affected by the traveling state. For example, in addition to a concentration state and a dozing state, it is possible to separate and discriminate such as an absurd state (a state of arousal but low attention concentration), drowsiness and a conflict state (a state of reduced arousal but high attention concentration), and the like.

  In addition, since it can be accurately determined by a method adapted to the individual driver and in accordance with the vehicle / driving environment state, it is possible to provide optimum driving assistance according to the state of the driver at that time. On the contrary, the troublesomeness caused by unnecessary assistance can be reduced by delaying the presentation of an alarm when the driver is in a good state according to the driving environment.

It is the schematic which shows the 1st Embodiment of this invention. It is a functional block diagram which shows the function of each part of the control circuit of the said 1st Embodiment. It is a diagram which shows the time change of a driver | operator's eye-closing time ratio X (t) and head vibration transmissibility Y (t). It is a figure which shows the classification of the driver | operator's individual driver | operator state determined. It is the schematic which shows the 2nd Embodiment of this invention. It is a diagram which shows the time change of the eye-closing time ratio X (t), a driver | operator's head vibration transmission rate Y (t), and the visual target ratio Z (t). It is a figure which shows the classification of the driver | operator's individual driver | operator state determined. It is a functional block diagram which shows the function of each part of the control circuit of the 3rd Embodiment of this invention. It is the schematic which shows the 4th Embodiment of this invention. It is a diagram which shows the time change of a driver | operator's eye-closing time ratio X (t) and the low frequency steering amount ratio Y (t). It is a figure which shows the classification of the driver | operator's individual driver | operator state determined. It is the schematic which shows the 5th Embodiment of this invention. It is a functional block diagram which shows the function of each part of the control circuit of the said 5th Embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Driver | operator information detector 10A Camera 10B Eye-closed time detector 10C Acceleration detector 10D Acceleration sensor 10E Gaze / face direction detector 10F Steering angle sensor 10G Accelerator / brake pedal operation amount sensor 10H Camera for vehicle exterior environment 10J Vehicle / driving environment information detector 14 Driver information database 16 Control circuit 20 Driving support means 20A Speaker 20B Information presentation device 20C Seat belt tension control device 20D Air conditioning device 20E Seat vibration device

Claims (12)

Driver information detecting means for detecting at least two driver information selected from driver information reflecting arousal level, driver information reflecting a degree of attention concentration, and driver information reflecting driving ability;
A driver information database that stores average values and standard deviations of individual drivers of each driver information detected by the driver information detecting means;
Vehicle / driving environment information detecting means for detecting vehicle / driving environment information indicating a vehicle driving state or an external environmental state;
For determining the driver state based on the average value and standard deviation of the individual driver stored in the driver information database and the vehicle / driving environment information detected by the vehicle / driving environment information detecting means. A determination threshold value determining means for determining a driver state determination threshold value;
Based on each driver information detected by the driver information detecting means, and a driver state determining threshold determined by the determination threshold determining means, a driver state determining means for determining a driver state;
A driver state determination device including: The driver information that reflects the degree of arousal is measured based on the brain wave, heart rate state, closed eye ratio that indicates the percentage of time that the eyes are closed for a certain amount of time when the eyes are open, and facial expression information of the facial image, and represents the drowsiness state. At least one of a facial expression sleepiness value and a self-reported sleepiness value declared by the driver,
The driver information reflecting the attention concentration is a head vibration transmissibility obtained from a driver's head shaking measured by at least one of head acceleration, head image, and neck electromyogram, It is at least one of the driver's attention concentration target measured by the direction of gaze,
The driver information reflecting the driving ability includes a low-frequency steering amount obtained from a reference steering amount and a steering amount, an accelerator pedal operation amount, a brake pedal operation amount, a vehicle wobbling degree indicating a change in vehicle position in the lane width direction, 2. The driver state determination device according to claim 1, which is at least one of an accelerator pedal operation amount and a brake pedal operation amount for maintaining a distance between the vehicle and the front vehicle.   The vehicle / driving environment information includes vehicle speed, acceleration of the vehicle, angular acceleration of the vehicle, distance between the preceding vehicle and the own vehicle, front image information of the own vehicle, weather, time, driving time, road type and traffic volume. The driver state determination device according to claim 1, wherein the driver state determination device is at least one of road information from a car navigation including the vehicle information.   The driver state determination apparatus according to any one of claims 1 to 3, further comprising determination threshold value changing means for changing the driver state determination threshold value by an operation from outside. The driver state determination device according to any one of claims 1 to 4,
Driving assistance control means for controlling the driving assistance means at the type and timing of the driving assistance corresponding to the driver state determined by the driver state determination means;
A driving support device including   The driving support device according to claim 5, further comprising driving support selection means for selectively executing driving support by the driving support means by an external operation. The driving support means includes
Information presenting means for presenting information representing driving assistance;
Generating means for generating at least one of negative ions, scents, oxygen, sound, and vibration for relaxation, refreshment, arousal or alerting;
Temperature control means to control the temperature in the car for relaxation, refreshment, awakening or alerting,
Seat belt tension control means for controlling the tension of the seat belt for relaxation, refreshment, awakening, or alerting,
The driving support device according to claim 5, further comprising at least one of vehicle motion control means for performing vehicle motion control for compensating for a decrease in driving ability.   The driving support control means controls the information presentation means to display at least one of presentation timing of information including a warning alert, presentation time, size of information to be presented, shape of information to be presented, and color of information to be presented. Claims for making two changes, presenting a reduction in travel speed, presenting prior information including traffic jam information, presenting information on the surroundings of the vehicle, presenting a high-accident location, and recommending breaks and presenting information therefor 7. The driving support device according to 7.   The driving support control unit controls the generation unit to control at least one of generation timing, generation amount, generation time, and generation type of at least one of negative ions, aroma, oxygen, sound, and vibration. Item 8. The driving support device according to Item 7.   The driving support apparatus according to claim 7, wherein the driving support control unit controls the temperature control unit to control at least one of a change timing, a change amount, a change direction, and a change time of an in-vehicle temperature.   The driving support according to claim 7, wherein the driving support control means controls the seat belt tension control means to control at least one of the magnitude of the tension of the seat belt, the timing of changing the tension, and the changing time. apparatus.   8. The driving support apparatus according to claim 7, wherein the driving support control means controls the vehicle movement control means to control at least one of vehicle movement control timing, vehicle control amount, vehicle control direction, and vehicle control time. .

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