JPH07125560A - Drive-a-car-asleep detector - Google Patents

Abstract

PURPOSE:To extract a corrected steering point accurately, in a drive-a-car-asleep detector used with a corrected steering period. CONSTITUTION:Time series steering angle data detected by a steering angle sensor 10 is subjected to its waveform shaping at a steering waveform shaping part 12, and inputted into a corrected steering period measuring part 14 which compares relative positional relations its aiming steering angle data and another steering angle data of the longitudinal specified number of this steering angle data and plural reference relative position patterns stored in a memory 15 in advance, whereby the corrected steering data alone is extracted. In a corrected steering period analytic part 16, a corrected steering period is calculated by the time differential operation of the corrected steering data extracted and the average operation, and it is compared with a period at the usual time in a subconscious judging part 18.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a drowsy driving detection device, and more particularly to a device for detecting a drowsy driving from the correction steering cycle of a vehicle.

[0002]

2. Description of the Related Art Conventionally, various devices have been developed and mounted for the purpose of improving the safety of vehicle running, and one of them is a drowsiness detection device that detects a drowsiness state of a driver and issues an alarm. .

As a method of detecting a drowsy driving, there are a method of taking a face image of the driver, a method of measuring the pulse of the driver, a method of detecting the steering state of the vehicle, and the like. For example,
Japanese Unexamined Patent Publication No. 60-76424 discloses that the drowsiness is detected when the steering wheel is rotated by a certain angle, and Japanese Unexamined Patent Publication No. 60-157927 discloses a steering angle change within a predetermined time. It is shown that the drowsiness driving is detected because the high frequency component of is higher than a predetermined value.

However, these conventional techniques have a problem that they cannot be detected with sufficient accuracy because a curve running is erroneously detected as a drowsy driving, and a high-frequency component is generated other than during drowsy driving.

Therefore, the applicant of the present application pays attention to the fact that there is a correlation between the driver's consciousness level and the correction steering cycle, and first calculates the correction steering cycle in Japanese Patent Application No. 4-2544694. However, we propose a configuration to detect drowsy driving compared to the normal cycle.

[0006]

However, it is not easy to calculate the correction steering cycle from the detected steering angle data. For example, it is conceivable to differentiate the obtained steering angle data with respect to time and use the point where the steering angle becomes 0 as the correction steering, but the steering vibration due to the reaction force from the road surface and the weak turning back of the driver are also used as the correction steering point at the same time. It may be detected. The present invention has been made in view of the above problems of the prior art, and its object is to accurately extract a corrected steering point from the obtained time-series steering angle data to accurately detect the corrected steering cycle of the driver. An object of the present invention is to provide a drowsy driving detection device capable of detecting drowsiness by using this modified steering cycle.

[0007]

In order to achieve the above object, a drowsy driving detection device according to claim 1 is a drowsy driving detection device for detecting a drowsiness of a driver from the running state of the vehicle. Steering angle detecting means for detecting the steering angle,
Of the obtained steering angle data, a corrected steering extraction means for extracting corrected steering data, a steering cycle calculation means for calculating the corrected steering cycle, and a comparison means for comparing the corrected steering cycle with a reference cycle. The corrected steering extraction means compares the relative positional relationship between the steering angle data of interest and a predetermined number of steering angle data before and after the steering angle data and a plurality of predetermined reference relative position patterns. The corrected steering data is extracted by performing the above.

In order to achieve the above object, the drowsiness driving detection apparatus according to a second aspect of the present invention is the drowsiness driving detection apparatus according to the first aspect, wherein the plurality of reference relative position patterns are first, second, and Comprised of third and fourth patterns, the steering angle data at the time t0 of interest is S (t0), a predetermined number of front and rear steering angle data is S (t),
When A is a positive constant, the first pattern is: S (t) ≤S (t0) (t≤t0) S (t) ≤-A (t-t0) + S (t0) (t> t0) And the second pattern is S (t) ≧ S (t0) (t ≦ t0) S (t) ≧ A (t−t0) + S (t0) (t> t0), and the third pattern Is S (t) ≤-A (t-t0) + S (t0) (t≤t0) S (t) ≤S (t0) (t> t0), and the fourth pattern is S (t). It is characterized in that .gtoreq.A (t-t0) + S (t0) (t.ltoreq.t0) S (t) .gtoreq.S (t0) (t> t0).

[0009]

In the drowsy driving detection apparatus according to the first aspect, the obtained time-series steering angle data is not time-differentiated and the point at which the value is 0 is not the corrected steering point, but the steering angle data of interest. Further, the corrected steering point is extracted from the relative positional relationship of a predetermined number (plurality) of steering angle data before and after that. When the driver intentionally performs the corrective steering, for example, unlike the steering fluctuation caused by the reaction force from the road surface, a specific change appears in a predetermined number of steering angle data before and after the steering fluctuation. Therefore, these peculiar positional relationships are stored in advance as patterns, and the relative positional relationship of the actually obtained steering angle data is compared with these patterns, so that it becomes 0 by the time differentiation and cannot be removed. It is possible to effectively remove the steering fluctuation and extract only the true corrected steering point.

Further, in the dozing driving detection device according to the second aspect, the patterns that appear during the correction steering are classified into four patterns, and if any of these four patterns is determined, it is determined that the correction steering point is set. is there. The number of front and rear steering angle data S (t) and the constant A can be set appropriately.

[0011]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT A preferred embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 shows a block diagram of the configuration of this embodiment. In the figure, a steering angle sensor 10 is provided on a steering shaft or the like of a vehicle and sequentially detects the steering angle. The detected steering angle data is sequentially output to the steering waveform shaping section 12. The steering waveform shaping unit 12 removes a minute fluctuation included in the steering angle data by calculating a moving average of the steering angle data. FIG. 3 shows the waveform of the steering angle data input to the steering waveform shaping unit 12 (FIG. 3A) and the waveform of the steering angle data after calculating the moving average (FIG. 3B). . In FIG. 3B, white circles are correction steering points to be extracted, and x marks are fine adjustment components such as road surface reaction force, that is, points that should not be originally extracted as correction steering points. Then, the shaped steering waveform is output to the correction steering cycle measuring unit 14, and only the correction steering point (circle mark) is extracted by the method described later to calculate the correction steering cycle. The calculated correction steering cycle is output to the correction steering cycle analysis unit 16, and an average cycle for several tens of steerings is calculated and output to the consciousness deterioration determination unit 18. Awareness lowering judgment unit
Reference numeral 8 compares the corrected steering cycle stored in advance with the calculated steering cycle, and a predetermined magnitude result is obtained.
For example, when the correction steering period is longer than 20% in normal times, an operation signal is output to the alarm unit 20, the wakeup unit 22, or the vehicle control unit 24 that automatically operates the brake or the like.

As described above, when the shaped waveform shown in FIG. 3 (B) is differentiated, it becomes 0 points together with the circle mark and the X mark. Therefore, only the circle mark cannot be extracted by the differential extraction method. Therefore, in the present embodiment, the shaped steering waveform is output to the modified steering cycle measuring unit 14 and only the modified steering points are extracted as described below to calculate the modified steering cycle.

FIG. 2 shows a modified steering cycle measuring unit 1 of this embodiment.
4 and the processing flowchart in the correction steering cycle analysis unit 16 are shown. That is, the corrected steering cycle measurement unit 1
Reference numeral 4 designates the shaped waveform at a predetermined frequency (12 in this embodiment).
Sampling is performed at a cycle of 8 ms (S101), and the latest n pieces of sampling data are stored in the memory (S10).
2). Since it is the latest data, the n data are sequentially updated every sampling. It should be noted that the number n is different depending on the sampling time, but it is sufficient that the time is 5 seconds. Next, among the latest n pieces of data stored, the sample point S (t0) at the center position is compared with a predetermined number of sample points S (t) before and after, and the four sample points stored in advance in the memory 15 are compared. It is determined whether any of the patterns is met. These four patterns are shown in FIG. In the figure, the double circle is the sample point S (t0) at the center, the horizontal direction indicates time, and the vertical direction indicates steering angle. In FIG. 4A, the sample points within the time T before and after the sample point S (t0) are as follows: S (t) ≤S (t0) (t≤t0) S (t) ≤-A (t-t0 ) + S (t0) (t> t0) However, this is a pattern for determining whether or not it is in the shaded area indicated by A = R / T. In FIG. 4B, S (t) ≧ S (t0) (T≤t0) S (t) ≥A (t-t0) + S (t0) (t> t0) is a pattern for determining whether or not it is in the shaded area, and FIG. (T) ≤A (t-t0) + S (t0) (t≤t0) S (t) ≤S (t0) (t> t0) This is a pattern for determining whether or not it is in the shaded area. FIG. 4 (D) is in the shaded area indicated by S (t) ≥-A (t-t0) + S (t0) (t≤t0) S (t) ≥S (t0) (t> t0). or not It is a determined pattern. Note that T is 300 ms to 1200 ms and R is 0.
2 to 0.8 deg is suitable, and is set to a value sufficient to exclude the X mark point indicating the corrected steering point due to the steering reaction force shown in FIG. In this embodiment, T = 768 ms,
R = 0.5 deg is used. Further, in FIG. 4, the case where there is no change in the steering angle is also included in the shaded area,
This is because there is a non-steering state in the actual steering waveform (state A in FIG. 5), and this state also needs to be recognized as a part of the correction steering.

The sampling point S (t
0) and the relative positional relationship between a predetermined number of sampling points before and after the sampling point correspond to any of the patterns in FIG. 4, the sampling point is determined to be a corrected steering point (S103), and the time t0 of the sampling point is determined. Is stored in the memory (S104). In this way, it is determined whether or not the sampling points sequentially correspond to the four patterns in FIG. 4, and when it is determined that the sampling points are present, the time of the sampling point is stored, and the memory always stores the latest x corrections. The steering time is stored. The corrected steering cycle analysis unit 16 calculates the time interval of these x corrected steering times stored in the memory by the difference calculation (S
105), and further, the correction steering cycle is calculated by calculating the average of these times (S106). Note that the reason why the corrected steering cycle is determined by calculating the average in this way is that there is some variation in the corrected steering of the driver, so an average of several tens of steerings (30 to 50 steerings) is calculated. This is because it is necessary to increase accuracy. Then, the calculated correction steering cycle is supplied to the consciousness deterioration determining unit 18 as described above, and it is determined whether or not the person is asleep.

As described above, in this embodiment, a plurality of patterns are determined in advance, and whether the relative positional relationship between the steering angle data of interest and a predetermined number of adjacent steering angle data corresponds to any of these patterns. Only the corrected steering point is extracted from the time-series steering angle data by determining whether or not it is calculated, and the corrected steering cycle is calculated. It is possible to calculate a correct correction steering cycle.

[0017]

As described above, according to the dozing driving detection device of the first or second aspect, the corrected steering point is surely extracted from the obtained time-series steering angle data, and the driver's drowsiness is detected. The corrected steering cycle can be accurately detected, and the dozing can be detected using the corrected steering cycle.

[Brief description of drawings]

FIG. 1 is a configuration block diagram of an embodiment of the present invention.

FIG. 2 is a processing flowchart of the embodiment.

FIG. 3 is an explanatory diagram of waveform shaping according to the embodiment.

FIG. 4 is an explanatory diagram of a pattern used when extracting a corrected steering point in the embodiment.

FIG. 5 is an explanatory diagram showing one mode of a non-steering state in the embodiment.

[Explanation of symbols]

 10 Steering Angle Sensor 12 Steering Waveform Shaping Section 14 Corrected Steering Cycle Measurement Section 15 Memory 16 Corrected Steering Cycle Analysis Section 18 Awareness Determining Section 20 Warning Section

Claims (2)

[Claims] 1. A drowsy driving detection device for detecting a driver's dozing from the running state of a vehicle, comprising steering angle detecting means for detecting a steering angle of the vehicle, and corrected steering data among the obtained steering angle data. The correction steering extraction means for extracting the correction steering, the steering cycle calculation means for calculating the correction steering cycle, and the comparison means for comparing the correction steering cycle with a reference cycle. It is possible to extract the corrected steering data by comparing the relative positional relationship between the steering angle data and a predetermined number of steering angle data before and after the steering angle data and a plurality of predetermined reference relative position patterns. A feature of a dozing driving detection device. 2. The dozing driving detection device according to claim 1, wherein the plurality of reference relative position patterns are composed of first, second, third, and fourth patterns, and the time t0 of interest. S (t0) is the steering angle data, S (t) is a predetermined number of steering angle data before and after, and A is a positive constant, the first pattern is S (t) ≤S (t0) (t≤ t0) S (t) ≤-A (t-t0) + S (t0) (t> t0), and the second pattern is: S (t) ≥S (t0) (t≤t0) S (t) ≥A (t-t0) + S (t0) (t> t0), and the third pattern is: S (t) ≤-A (t-t0) + S (t0) (t≤t0) S (t) .Ltoreq.S (t0) (t> t0), and the fourth pattern is: S (t) .gtoreq.A (t-t0) + S (t0) (t.ltoreq.t0) S (t) .gtoreq.S (t0) ( A drowsiness driving detection device, characterized in that t> t0).