JP3411460B2 - Vehicle driving condition monitoring device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle driving condition monitoring apparatus for monitoring a driving condition of a driver of a vehicle and issuing a warning if necessary.

[0002]

2. Description of the Related Art A response delay time of a driver and a deviation amount between a vehicle position and a driving lane are estimated based on a steering amount and a vehicle speed of a vehicle, and the estimated response delay time and deviation amount and a normal state A driving situation monitoring device that compares the response delay time and the deviation amount to determine the driving situation of a driver (for example, an abnormal steering state due to a decrease in driving ability due to the driver's drowsiness or fatigue) has been used in the past. It is known (Japanese Unexamined Patent Publication No. 5-85221).

In this apparatus, a statistical process for calculating an average value or a standard deviation of characteristic values such as the deviation amount is performed, and the steering abnormality of the driver is determined using the processed characteristic value.

[0004]

However, in the case of performing statistical processing, for example, in the case of calculating the average value of 10 detection data and comparing the average value with the reference value to judge the driving situation, The problem is how to calculate the average value with a small amount of detected data at the beginning of operation. Although the above publication does not describe this point, generally, for example, when two pieces of detection data are obtained, the determination is performed using the average value of the two pieces of detection data. for that reason,
There was a problem that the possibility of erroneous determination as abnormal is high even though the operating condition is not actually abnormal at the beginning of operation.

The present invention has been made paying attention to this point, and in the case of determining the driving situation by using the statistical processing,
An object of the present invention is to provide a vehicle driving condition monitoring device capable of preventing erroneous determination at the beginning of driving.

[0006]

In order to achieve the above object, the invention according to claim 1 is a vehicle driving condition monitoring apparatus for monitoring a driving condition of a driver of a vehicle, the driving according to the behavior of the vehicle. A driving situation value detection means for detecting at least one driving situation value of a situation situation value, a driving situation value according to the operation situation of the driver, and a driving situation value according to the state of the driver, and a plurality of stored values in sequence. Ring bag for storing
And the ring buffer for each of the sampling time points.
Stored in the ring buffer.
A statistical processing unit that performs statistical processing on the driving status value , a determination unit that determines whether the driving status of the driver is appropriate based on the statistical processing result, and a vehicle speed of the vehicle.
Vehicle speed detection means to detect and the detected vehicle speed is a predetermined upper and lower limit
When it is within the range, the judgment by the judgment means is permitted.
The statistical processing means sets a predetermined value that is difficult to determine to be abnormal as an initial value of a plurality of driving situation values that are the target of the statistical processing when the vehicle starts driving, and thereafter, The initial value is sequentially updated to the detected driving condition value in accordance with the detection of the driving condition value, and the statistical processing is performed.

According to a second aspect of the present invention, in the vehicle operating condition monitoring apparatus according to the first aspect, the statistical processing means sets the predetermined value to 0.

According to a third aspect of the present invention, in the vehicle driving condition monitoring apparatus according to the first aspect, the statistical processing means performs an average value calculation as the statistical processing.

According to a fourth aspect of the present invention, in the vehicle driving condition monitoring apparatus according to the first aspect, the statistical processing means performs standard deviation calculation as the statistical processing.

According to a fifth aspect of the present invention, in the vehicle driving situation monitoring device according to the first aspect, the driving situation value detecting means includes the parameter value indicating the behavior of the vehicle as the driving situation value, It is characterized in that a deviation amount between at least one of a parameter value indicating a driver's operation status and a parameter value indicating the driver's state and a predetermined reference value is used.

[0011]

[0012] The invention described in claim 6 is the vehicle driving condition monitoring apparatus according to claim 1, wherein the statistical processing means, when the vehicle speed obtained by the detected falls below the predetermined lower limit value, the initial value It is characterized by setting.

According to a seventh aspect of the present invention, in the vehicle driving condition monitoring apparatus according to the first aspect, the yaw rate detecting means for detecting the yaw rate of the vehicle and the determination when the detected yaw rate is equal to or lower than a predetermined yaw rate. And a determination permission unit that permits the determination by the unit.

According to an eighth aspect of the invention, there is provided a vehicle driving condition monitoring device for monitoring a driving condition of a vehicle driver,
Driving status value detecting means for detecting at least one driving status value according to the behavior of the vehicle, a driving status value according to the operation status of the driver, and a driving status value according to the state of the driver. And to store multiple stored values sequentially
Of the ring buffer and the plurality of operation status values detected by shifting the sampling time point from each other at each sampling time point.
Sequentially store and update in the ring buffer,
A statistical processing means for performing statistical processing on the driving status value stored in, and a judgment means for judging whether or not the driving status of the driver is appropriate based on the statistical processing result,
The statistical processing means sets a predetermined value that is difficult to determine to be abnormal as an initial value of a plurality of driving status values to be subject to the statistical processing at the time of starting the driving of the vehicle, and thereafter, with the detection of the driving status value. Then, the initial value is sequentially updated to the detected driving situation value, the statistical processing is performed, and the driving situation value detecting means, as the driving situation value, a parameter value indicating the behavior of the vehicle, the driver's It is characterized in that at least one of a parameter value indicating an operating condition and a parameter value indicating the driver's state and a deviation amount from a predetermined reference value are used.

[0015]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a block diagram showing the configuration of a vehicle driving condition monitoring apparatus according to an embodiment of the present invention. The apparatus is driven by a prime mover such as an internal combustion engine or an electric motor, and has a steering system. It is installed. In the figure, on the input side of the microcomputer 1, a yaw rate sensor 10 for detecting the yaw rate of the vehicle,
A vehicle speed sensor 12 for detecting the traveling speed of the vehicle and a turn signal switch 11 for detecting the driver's intention to change lanes are connected. In addition, an alarm unit 24 is connected to the output side of the microcomputer 1 to issue an alarm as needed during the monitoring of the driving condition of the driver. The alarm unit 24 is composed of, for example, a lamp, a buzzer, a sound generator, and the like.

Signal memory unit 1 of the microcomputer 1
4, the reference line estimation unit 16, the lateral displacement amount calculation unit 19, the deviation amount calculation unit 20, the driving ability estimation unit 21, and the determination unit 22 represent the functions of the microcomputer 1 as blocks.

The signal memory unit 14 includes the sensors 10, 12
Also, the input signal from the switch 11 is stored, the yaw rate data and the vehicle speed data for the past T1 seconds (for example, 30 seconds) from the present are updated every T2 seconds (for example, 10 seconds) and output to the reference line calculation unit 16.

The reference line calculation unit 16 time-integrates the input yaw rate YR (see FIG. 2A) to obtain the yaw angle YA.
(See (b) in the figure), and a reference line (see a broken line in (b) in the figure) is calculated based on the data of the yaw angle YA. Specifically, this calculation is performed using the well-known least squares method as follows.

For example, assuming that the yaw angles YA1, YA2, YA3 are obtained at times t1, t2, t3, when the reference line is approximated by a linear expression, YA1 = b1 + b2t1 + e1 YA2 = b1 + b2t2 + e2 YA3 = b1 + b2 + 3 + e3. Here, e1 to e3 are residuals, and b1 and b2 are determined so that the sum of squares of these residuals is minimized.
In the case of approximation by a quadratic equation, YA1 = b1 + b2t1 + b3t1 ² + e1 YA2 = b1 + b2t2 + b3t2 ² + e2 YA3 = b1 + b2t3 + b3t3 ² + e3, and b1 to b3 are determined so that the sum of squares of the residuals is minimized. In the case of approximating with a cubic equation, YA1 = b1 + b2t1 + b3t1 ² + b4t1 ³ + e
1 YA2 = b1 + b2t2 + b3t2 ² + b4t2 ³ + e
2 YA3 = b1 + b2t3 + b3t3 ² + b4t3 ³ + e
3, b1 to b4 are determined so that the sum of squared residuals is minimized.

When the number of data is large, the order is similarly increased and approximation is performed.

In the present embodiment, the reference line is first obtained by a linear expression, and the reference yaw angle YA corresponding to the reference line is subtracted from the yaw angle YA to calculate the corrected yaw angle YAM (see FIG. 2C). , To the lateral displacement amount calculation unit 19.

The lateral displacement amount calculator 19 first determines the corrected yaw angle Y.
Applying AM and vehicle speed V to the following equation, lateral displacement differential amount DYK
(See FIG. 2D) is calculated.

DYK = V × sin (YAM) Furthermore, the lateral displacement amount YK is calculated by integrating the lateral displacement differential amount DYK over time (FIG. 2 (e)). When the difference between the maximum value YKMAX and the minimum value YKMIN of the lateral displacement amount YK is equal to or greater than the predetermined value α2, the approximation order of the reference line is increased to find the reference line again, and the lateral displacement amount YK is calculated.
This is repeated until (YKMAX-YKMIN) <α2. However, in the present embodiment, the approximation of the predetermined order k0 or more is not performed as described later.

The deviation amount calculator 20 calculates the deviation amount ΔDIF2 based on the lateral displacement amount YK. Deviation amount ΔDIF2
Is calculated as, for example, the area of the shaded portion in FIG. 2E (time integrated value of the absolute value of the lateral displacement amount YK).
The standard deviation of the K value or the difference between the maximum value and the minimum value may be used.

The driving ability estimating unit 21 determines the deviation amount ΔDIF2
Is performed to estimate the driver's ability, and the determination unit 22 determines the driving condition according to the estimation result and the presence or absence of the blinker operation.
A signal for instructing 4 to issue an alarm is output.

As described above, in the present embodiment, the reference line is calculated based on the detected yaw angle YA, and the deviation amount ΔDIF calculated from the lateral displacement amount YK representing the deviation from the reference line.
Since the driving condition is determined based on 2, it is possible to accurately determine the condition regardless of the condition of the road surface and individual differences of the driver.
Further, since the warning is given in consideration of the operation state of the blinker, it is possible to prevent the driver from erroneously determining that the vehicle is abnormal when the course is changed.

3 and 4 are flowcharts showing the procedure of processing in the microcomputer 1. The reference line estimating unit 16, the lateral displacement amount calculating unit 19, the deviation amount calculating unit 20, the driving ability estimating unit 21, and the determining unit are described above. The function of 22 is specifically shown in FIG.
And 4 are realized.

First, in step S1, the sample data is initialized. Specifically, all the storage values of the ring buffer for sequentially storing a plurality of detected deviation amounts ΔDIF2 used in the statistical processing described later are set to “0”. That is, when statistical processing is performed using N (> 2) sample data, all N stored values in the ring buffer are set to “0” (see time t0 in FIG. 7). In the following step S2, the approximation order k is initialized to "0", and then the yaw rate YR and the vehicle speed V for T1 seconds are fetched every T2 seconds (step S3). Then, the minimum value VMIN of the vehicle speed V fetched in T1 seconds is the first predetermined vehicle speed V1 (for example, 30
(km / h) or less (step S4), the VM
If IN ≦ V1, the process returns to step S1.

On the other hand, when VMIN> V1, the vehicle speed V
It is determined whether or not the maximum value VMAX of is greater than or equal to a second predetermined vehicle speed V2 (for example, 120 km / h) higher than the first predetermined vehicle speed V1 (step S5), and if VMAX ≧ V2, the process returns to step S2. When VMAX ≦ V2, it is determined whether or not the maximum value YRMAX of the yaw rate YR is larger than the predetermined yaw rate YR0 (step S6).
If YRMAX> YR0, it is highly possible that the order k will become the predetermined order k0 (for example, 3) or more in the processing of step S7 and subsequent steps, and therefore the processing returns to step S2 in order to reduce the calculation amount.

When YRMAX≤YR0 in step S6, the order k is incremented by "1" (step S7), and it is determined whether or not the order k is smaller than a predetermined order k0 (step S8). Since k <k0 is initially set, the reference line is calculated (step S9) and the lateral displacement amount YK is calculated (step S10). And the lateral displacement YK
Of the maximum value YKMAX and the minimum value YKMIN is smaller than a predetermined value α2 (step S11),
When (DYKMAX-DYKMIN) ≧ α2,
Returning to step S7, the order of approximation of the reference line is increased by one to calculate the reference line again, and the process is repeated until the answer to step S11 becomes affirmative (YES). However, step S8
When k = k0, the process returns to step S2.

In step S11 (YKMAX-YKMI
N) <α2, the process proceeds to step S12 (FIG. 4) to calculate the deviation amount ΔDIF2 (area of the shaded portion in FIG. 2E), and then estimates the driving ability of the driver based on the deviation amount ΔDIF2. Yes (step S13). This estimation is specifically performed as follows.

First, the deviation amount ΔDIF2 is calculated m times (for example, 6 times) and n times (for example, 12 times) by changing the sampling time of the yaw rate YR and the vehicle speed V, and the calculated deviation amount ΔDIF2 is sequentially stored in the ring buffer. To do. Then, the average value ΔDIFAVE of m ΔDIF2 values and the standard deviation σDIF and the average value ΔDIFAV of n ΔDIF values
Calculate E3. Then, whether the average value ΔDIFAVE is larger than the predetermined deviation amount ΔDIFTH and the standard deviation σ
Depending on whether DIF is larger than a predetermined threshold value σTH, FIG.
The driving ability levels A to D are determined as shown in FIG. Where ΔDIFAVE ≦ ΔDIFTH and σDIF ≦ σT
When it is H, the deviation amount is small on average and its variation is small, so it is estimated that the driving ability is the highest (level A). On the other hand, when ΔDIFAVE> ΔDIFTH and σDIF ≦ σTH, the deviation amount is large on average and the variation is small, so it is estimated that the driving ability is the lowest (level D). Also, σDIF> σT
When H is H, it is estimated that the smaller the ΔDIFAVE value is, the higher the driving ability is, and when ΔDIFAVE ≦ ΔDIFTH is level B, when ΔDIFAVE> ΔDIFTH is level C.

Further, the number NOV (= 0 to m) of m ΔDIF2 values exceeding a predetermined value is calculated, and this NO
The driving ability levels E to I are determined according to the V value. That is, when m = 4, the driving abilities are set to E, F, G, H, and I corresponding to NOV = 0, 1, 2, 3, and 4, respectively.

Then, the above driving ability levels A to C and E
Based on ~ I, the overall driving ability is determined as shown in FIG. That is, the average value Δ of n ΔDIF2 values
If the predetermined threshold value of DIFAVE3 is ΔDIF3TH,
Level A, B and E, or ΔDIFAVE3 <ΔDI
When F3TH, it is judged as "normal", and when levels A, B and F, G and ΔDIFAVE3 ≧ ΔDIF3TH or levels C and E, F, G and ΔDIFAVE3 ≧ Δ
When DIF3TH, "warning level 1" is determined, and levels A, B, C and H, I and ΔDIFAVE3 ≧ ΔDI
At F3TH, or level D and ΔDIFAVE3
When ≧ ΔDIF3TH, it is determined as “warning level 2”.

The average value ΔDI of n ΔDIF2 values
Without using FAVE3, it is judged to be "normal" when the levels are A, B and E, and "warning level 1" when the levels are A, B and F, G or when the levels are C, E, F and G. It may be determined that when the level is A, B, C and H, I or the level is D, the "warning level 2" is determined.

In this way, a plurality of deviation amounts ΔDIF2
By determining the driving ability of the driver based on the average value and the standard deviation (variation) of, the driving ability can be more accurately determined (estimated).

Returning to FIG. 4, in step S14, it is determined whether or not the driving ability is low, that is, whether the driving ability estimated in step S13 is the warning level 1 or 2, and this answer is affirmative (YES). In case of, it is determined whether or not the blinker is operated (step S15). as a result,
When the driving ability is not the warning level 1 or 2, or when the blinker is operated, the process immediately returns to step S2,
When the driving ability is the warning level 1 or 2, and the winker is not operated, it is determined that the driving situation is abnormal, and a signal for instructing to issue an alarm is output to the alarm unit 24 (step S16). , And returns to step S2.

In this case, at the warning level 2, it is desirable to make the warning sound louder than at the warning level 1 or to make both the lamp lighting and the buzzer sound.
Further, when the warning level is 2, a fail safe action such as decelerating the vehicle speed may be performed.

In the judgment of steps S4 to S6, the average value VA is used instead of the minimum value VMIN or maximum value VMAX of the vehicle speed V or the maximum value YRMAX of the yaw rate YR.
VE or YRAVE may be used.

As described above, according to the present embodiment, the average values ΔDIFAVE and ΔDIF of the plurality of deviation amounts ΔDIF2.
By determining the driving ability of the driver based on AVE3 and the standard deviation σDIF, the driving ability can be determined (estimated) more accurately, and more detailed warning and fail-safe action can be performed. Further, the average values ΔDIFAVE, ΔDIFAVE3 and the standard deviation σDI
The ΔDIF2 values (n and m ring buffer storage values) for calculating F are all “0” at the start of the determination process.
To the state where the deviation amount ΔDIF2 = 0 and there is no deviation from the reference line (step S
Since it is made 1), it is possible to prevent erroneous determination as abnormal at the beginning of operation.

More specifically, for example, when N = 6, the storage value of the ring buffer which stores the sample data di (i = 1, 2, 3, ...) (corresponding to ΔDIF2 in the above example) is As shown in FIG. 7, it changes over time. That is, all are initialized to "0" at the start of processing (time t0), and the initial value "0" is sequentially updated to the sample data di every time the sample data di is obtained. Thus, for example, the average value AVE at time t1
1 becomes (0 + d1) / 6, and the average value AVE3 at time t3 becomes (0 + d1 + d2 + d3) / 6,
The average value AVE6 at time t6 is (d1 + d2 + d
3 + d4 + d5 + d6) / 6. Therefore, for example, at time t3, AVE3 = (d1 + d2 + d3)
It is possible to reduce the possibility of erroneous determination of abnormality as compared with the case of setting / 3.

The present invention is not limited to the above-described embodiment, but various modifications can be made. For example,
In the initialization processing of step S1, all sample data for statistical processing was initialized to "0", but 0
It may be set to a slightly larger predetermined value. That is, the driving condition may be set to a value that makes it difficult to determine that the driving condition is abnormal.

Further, in the above-mentioned embodiment, the lateral displacement amount YK is used as the parameter indicating the behavior of the vehicle, but the similar processing may be performed using the lateral displacement differential amount DYK.

Further, in the above-described embodiment, when the statistical processing is performed using the parameter ΔDIF2 representing the behavior of the vehicle to determine the abnormality of the driving condition, the sample data for the statistical processing is provided at the start of the determination processing. Although the initialization is made to be a predetermined value that makes it difficult to determine that an abnormality has occurred, this initialization method can also be applied to a case where statistical processing is performed in another abnormality determination method as described below.

For example, as disclosed in Japanese Examined Patent Publication No. 54-24569, a method for determining dozing on the basis of the operation frequency of the steering wheel and accelerator, Japanese Examined Patent Publication No. 4-75560.
Japanese Patent Laid-Open No. 5-24460 discloses a method of detecting the upper body position of a driver with a camera and making a drowsiness determination based on the periodic fluctuation of the position. A technique for detecting a skin potential and detecting a tension state and a decreased arousal state. As shown in Japanese Patent Laid-Open No. 5-96971, sleep on the basis of biological information such as a driver's brain waves, facial expressions, and body temperature. Detecting method, or Japanese Patent Laid-Open No. Hei 5
In the method of detecting the lateral displacement by photographing the front of the runway with a camera and detecting the doze based on the lateral displacement as shown in Japanese Patent Publication No. 69957, the initial stage for the statistical processing as described above. The conversion processing may be performed. That is, it can be applied not only to the behavior of the vehicle but also to the determination of abnormal driving based on the driving operation state of the driver and the driver's state (posture, body temperature, etc.).

Further, in the above-described embodiment, it is determined whether or not the winker is operated (step S15 in FIG. 4).
Is a data acquisition process for the yaw rate YR and the vehicle speed V (see FIG. 3).
The step S2) may be performed immediately after the step S2), and when the blinker operation is performed, the process may immediately return to the step S2 without performing processing such as reference line calculation.

Further, in the above-described embodiment, the warning to the driver is one that appeals to the driver's sight or hearing. However, the present invention is not limited to this, and a method that directly acts on the driver, such as a seat, is used. The vehicle may be vibrated, tension may be applied to the seat belt, a specific scent may be released into the vehicle compartment, or the operating state of the air conditioner may be changed. As a result, the driver can be more surely notified of the deterioration of the driving situation.

Further, in the above-described embodiment, the yaw rate is detected by the yaw rate sensor 10, but instead of this, the output of the wheel speed sensor and the vehicle speed sensor or the steering angle sensor for detecting the steering angle of the steering wheel and the lateral direction. The yaw rate may be calculated using the output of the acceleration sensor or the like.

Further, in the above-described embodiment, the yaw angle Y
Although the reference line is estimated based on A, the reference line may be estimated based on the yaw rate YR or the lateral displacement amount YK.

[0051]

As described above in detail, according to the vehicle driving condition monitoring apparatus of the first aspect, statistical processing is performed on a plurality of driving condition values detected by shifting sampling points, and the statistical processing result is obtained. It is determined whether or not the driving situation of the driver is appropriate based on, as the initial value of the plurality of driving situation values to be the subject of the statistical processing at the start of driving the vehicle, a predetermined value that is difficult to determine as abnormal is used, After that, the statistical value is updated by sequentially updating the initial value to the detected operating status value in accordance with the detection of the operating status value, so that it is possible to prevent erroneous determination at the beginning of the operation with a small amount of sample data. .

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of a vehicle driving condition monitoring apparatus according to an embodiment of the present invention.

FIG. 2 is a diagram showing detection data and a transition of parameters calculated based on the detection data.

FIG. 3 is a flowchart showing a procedure of processing executed by the microcomputer shown in FIG.

4 is a flowchart showing a procedure of processing executed by the microcomputer of FIG.

FIG. 5 is a diagram showing a map for determining a driving ability level of a driver.

FIG. 6 is a diagram showing a map for determining a driving ability level of a driver.

FIG. 7 is a diagram showing a transition of a storage value of a ring buffer used for statistical processing.

[Explanation of symbols]

1 Microcomputer (statistical processing means, determination means) 10 Yaw rate sensor (driving status value detection means) 11 blinker switch 12 Vehicle speed sensor (driving status value detection means) 24 Alarm unit

─────────────────────────────────────────────────── --- Continuation of the front page (56) References JP-A-8-249600 (JP, A) JP-A-6-179334 (JP, A) JP-A-7-9880 (JP, A) JP-A-6- 293228 (JP, A) (58) Fields surveyed (Int.Cl. ⁷ , DB name) G08G 1/16 B60K 25/00-28/16 G06B 19/00-21/24

Claims (8)

(57) [Claims] 1. A vehicle driving condition monitoring apparatus for monitoring a driving condition of a driver of a vehicle, the driving condition value according to the behavior of the vehicle, the driving condition value according to the operation condition of the driver, and the driver. Driving condition value detecting means for detecting at least one driving condition value of the driving condition values according to the state, a ring buffer for sequentially storing a plurality of stored values, and a plurality of the driving conditions detected by shifting sampling points. Statistical processing means for sequentially storing and updating status values in the ring buffer at each sampling time point and performing statistical processing on the driving status values stored in the ring buffer; and a driving status of the driver based on the statistical processing result. Determining means for determining whether the vehicle speed is appropriate, vehicle speed detecting means for detecting the vehicle speed of the vehicle, and when the detected vehicle speed is within a predetermined upper and lower limit range, And a determination permission unit that permits the determination by the determination unit, wherein the statistical processing unit is a predetermined value that is difficult to determine to be abnormal as an initial value of a plurality of driving situation values that are the targets of the statistical processing when the vehicle starts to operate. Is set, and thereafter, the initial value is sequentially updated to the detected driving condition value in accordance with the detection of the driving condition value, and the statistical processing is performed, and the vehicle driving condition monitoring device. 2. The vehicle driving condition monitoring apparatus according to claim 1, wherein the statistical processing unit sets the predetermined value to 0. 3. The vehicle driving condition monitoring apparatus according to claim 1, wherein the statistical processing means performs an average value calculation as the statistical processing. 4. The vehicle driving condition monitoring apparatus according to claim 1, wherein the statistical processing means performs a standard deviation calculation as the statistical processing. 5. The driving situation value detecting means, as the driving situation value, at least a parameter value indicating a behavior of the vehicle, a parameter value indicating an operation situation of the driver, and a parameter value indicating a state of the driver. The vehicle driving condition monitoring device according to claim 1, wherein a deviation amount between one and a predetermined reference value is used. 6. The vehicle driving condition monitoring apparatus according to claim 1, wherein the statistical processing means sets the initial value when the detected vehicle speed is lower than the predetermined lower limit value. 7. The yaw rate detecting means for detecting the yaw rate of the vehicle, and the determination permitting means for permitting the determination by the determining means when the detected yaw rate is less than or equal to a predetermined yaw rate are provided. The vehicle driving condition monitoring device described. 8. A vehicle driving condition monitoring apparatus for monitoring a driving condition of a driver of a vehicle, comprising: a driving condition value according to a behavior of the vehicle; a driving condition value according to an operation condition of the driver; and the driver. Driving condition value detecting means for detecting at least one driving condition value of the driving condition values according to the state, a ring buffer for sequentially storing a plurality of stored values, and a plurality of the driving conditions detected at different sampling times. Situational values are sequentially transferred to the ring buffer at each sampling time
Stored and updated, the operation stored in the ring buffer
A statistical processing unit that performs statistical processing on the situation value , and a determination unit that determines whether or not the driving status of the driver is appropriate based on the statistical processing result, and the statistical processing unit starts driving the vehicle. Sometimes, as the initial value of the plurality of driving situation values that are the subject of the statistical processing, a predetermined value that is difficult to determine as abnormal is set, and thereafter, the initial value is detected with the detection of the driving situation value, and the detected driving situation value Sequentially updated to perform the statistical processing, the driving situation value detecting means, as the driving situation value, a parameter value indicating the behavior of the vehicle, a parameter value indicating the operation situation of the driver and the driver A vehicle driving condition monitoring apparatus characterized by using a deviation amount between at least one of parameter values indicating a state and a predetermined reference value.