JPH11223517A - Road surface state detector - Google Patents

Abstract

PROBLEM TO BE SOLVED: To stably detect road surface state without malfunctioning in a road surface state detector mounted on a vehicle and detecting road surface the vehicle is running even with colored pavement, shining pavement or painted pavement. SOLUTION: The state of road surface 20 after a tire 5 of a vehicle has passed is detected with a sensor 1 and the state of road surface 20 where a tire 5 has not passed is detected with a sensor 2. By comparing the output values of these sensors 1 and 2, the road state is judged. For example, it is judged to be snowy road when the two output values differ much, to be wet road when the two values slightly differ, and to be dry road when the two values differ little.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a vehicle mounted on a vehicle,
BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a road surface state detection device that optically detects a road surface state, and more particularly to a technology for stably detecting a color pavement road without causing a malfunction.

[0002]

2. Description of the Related Art Conventionally, as a vehicle-mounted optical road surface state detecting device, a glossiness is calculated based on the light intensity of a vertical deflection component and a horizontal deflection component contained in light reflected from a road surface. One that determines the state of the road surface such as freezing, wetness, and dryness is known (for example, see Japanese Patent Application Laid-Open No. 58-158439).

[0003]

However, in recent years,
By coloring the road pavement surface or applying a material that shines when the light shines, it attracts the driver's attention and transmits vibration when the vehicle speeds up or when the vehicle speed increases Roads that encourage low-speed driving have been developed for the purpose of improving safety. In such a road, when a road surface state is detected using a road surface state detection device as disclosed in the above publication, for example, white asphalt is erroneously determined to be in a snow-covered state, or glittering asphalt is in a wet state. There is a case that it is erroneously determined that there is.

The present invention has been made in order to solve the above-mentioned problems, and stabilizes the road surface condition without causing a malfunction even on a color pavement, a glowing pavement, or a pavement with paint. And can be detected,
In particular, it is an object of the present invention to provide a vehicle-mounted road surface condition detection device that can reliably detect whether or not the surface is dry, regardless of the pavement of the road surface.

[0005]

SUMMARY OF THE INVENTION In order to achieve the above object, the present invention relates to a road surface condition detecting device mounted on a vehicle for detecting the condition of a road surface on which the vehicle runs, and comprising: A first optical sensor having a field of view and detecting a signal according to a road surface condition, and a second optical sensor having a field of view on a road surface through which a vehicle tire does not pass and detecting a signal according to the road surface condition , The first optical sensor and the second
And a determination means for comparing the output values of the optical sensors and determining the road surface state based on the comparison result.

[0006] In this configuration, for example, when the road surface is a snowy road surface, the tire trace is carved on the road surface due to the running of the vehicle, so the output waveform from the first optical sensor includes the tread of the tire. The repetition of the cycle according to the pattern appears. In addition, a fine waveform corresponding to the snow particle size appears in the output waveform from the second optical sensor. As described above, when the road surface is a snowy road surface, a large difference appears between the output waveform from the first optical sensor and the output waveform from the second optical sensor. In addition, when the road surface is wet asphalt, the running of the vehicle causes tire marks to remain and water splashes. Therefore, the output waveform from the first optical sensor and the output waveform from the second optical sensor include: Some changes occur. Furthermore, when the road surface is dry asphalt, no influence appears on the road surface as the tire passes through the road surface, so that the output waveform from the first optical sensor and the output waveform from the second optical sensor The output waveform is almost the same. As described above, since the output waveforms from the two optical sensors change depending on the road surface condition, the determination unit determines the similarity between the output waveforms from the two optical sensors to determine the road surface condition. it can.

In the present invention, the first and second optical sensors may have respective fields of view on a road surface behind the tire in the traveling direction and a road surface in front of the traveling direction of the tire.
With this configuration, the same operation as the above-described claim 1 can be obtained.

Further, the present invention is arranged at a position rearward of the first optical sensor with respect to the traveling direction of the vehicle, has a field of view on a road surface through which tires of the vehicle have passed, and outputs a signal corresponding to the road surface condition. The apparatus may further include a third optical sensor for detecting, and the determination unit may determine a road surface state by comparing output values from the first, second, and third optical sensors.

In this configuration, for example, when the road surface is a snowy road surface, tire traces are carved on the road surface due to running of the vehicle, so the output waveforms from the first and third optical sensors include: Repetition of the cycle according to the tread pattern of the tire appears. For this reason, the output waveform from the first optical sensor and the output waveform from the third optical sensor are substantially equal, and the output waveform from the second optical sensor and the output waveform from the third optical sensor are different from each other. Will be very different. When the road surface is wet asphalt, the water on the road surface is repelled by the tires due to the running of the vehicle, but thereafter, the water on the road surface returns to the state before being repelled by the tires. Is closer to the output waveform from the second optical sensor and slightly different from the output waveform from the first optical sensor. As described above, when the road surface is a snowy road surface and when the road surface is wet asphalt, a change appears in the output waveforms from the three optical sensors. By determining the degree of similarity of the output waveform from the optical sensor and the degree of similarity between the output waveform from the second optical sensor and the output waveform from the third optical sensor, it is possible to distinguish between a snowy road surface and a wet road surface. it can.

[0010]

Embodiments of the present invention will be described below with reference to the drawings. (First Embodiment) FIG. 1 is a configuration diagram of a road surface condition detecting device according to the present embodiment. In FIG. 1, it is assumed that the vehicle moves from the near side to the far side. Road surface condition detection device 10
Is mounted on a vehicle and determines the state of the road surface 20 on which the vehicle travels, and is based on two sensors 1 and 2 which are reflection type optical sensors and signals from these two sensors 1 and 2 Comparison determination unit 4 that determines the state of road surface 20
(Determination means). The sensor 1 (first optical sensor) has a field of view on the road surface 20 through which the tire 5 (front wheel) has passed, and detects the intensity of light reflected from the road surface 20. The sensor 2 (second optical sensor) is arranged side by side with the sensor 1 in a lateral direction orthogonal to the traveling direction of the vehicle, and has a field of view on a road surface 20 through which the tire 5 does not pass.

FIG. 2 is an internal configuration diagram of the sensor. The sensor 1 and the sensor 2 have the same configuration, and a light projecting element 12 that projects light toward a road surface 20 via a light projecting lens 11;
A driving driver circuit 13 for driving the light emitting element 12 based on a driving signal from the comparison / determination unit 4; a light receiving element 15 for receiving light reflected from a road surface via a light receiving lens 14; A signal amplifier 16 for amplifying the signal and outputting the amplified signal to the comparison / determination unit 4.

FIG. 3 is a block diagram of the comparison / determination unit. The comparison / determination unit 4 includes two analog / digital converters 21 (hereinafter, referred to as AD converters) that convert respective output signals from the sensors 1 and 2 into digital signals, and signal waveforms detected by the sensors 1 and 2. As a sample waveform in the memory 22
, A frequency analysis unit 24 that performs frequency analysis on the waveform stored in the memory 22, and a similarity between the two waveforms is determined based on the frequency analysis result by the frequency analysis unit 24. A correlation operation unit 25 for obtaining a correlation value to be indicated, and a road surface state determination unit 26 for determining a road surface state based on the operation result by the correlation value operation unit 25
It consists of:

Here, a change in the light intensity of the reflected light detected by the sensors 1 and 2 when the road surface condition changes will be described with reference to FIG. FIG. 4 (a) (b) (c)
Shows the state of the road surface 20 detected by the sensors 1 and 2 when the road surface is a snowy road surface, a wet road surface, and dry ordinary black asphalt, respectively, and the waveform of the light intensity of the reflected light detected by the sensors 1 and 2 FIG.

When the road surface is a snowy road surface, as shown in FIG. 4A, the trace of the tire 5 is carved on the road surface on which the tire 5 has passed. The cycle repetition according to the tread pattern appears. Further, a fine waveform corresponding to the snow particle size appears in the output waveform s2 from the sensor 2 having a visual field on a road surface on which the tire 5 does not pass. Therefore, the output waveform s1 from the sensor 1 and the output waveform s2 from the sensor 2 are significantly different.

When the road surface is a wet road surface, FIG.
As shown in (1), in addition to the diffuse reflection component, the sensors 1 and 2 receive a regular reflection component corresponding to the unevenness of the road surface and the degree of wetness. For this reason, in these sensors 1 and 2, a waveform with an unstable period having a large amplitude appears. Immediately after the tire 5 passes, a tire mark remains and a water splash occurs on the road surface, so that the output waveform s1 from the sensor 1 slightly changes compared to the output waveform s2 from the sensor 2.

When the road surface is dry asphalt, as shown in FIG. 4C, even if the tire 5 passes, the road surface is not affected, so that the output waveform s1 from the sensor 1 and the output from the sensor 2 The waveform s2 is substantially equal.

Next, output waveforms s1, from the sensors 1, 2
A method for determining a road surface using s2 will be described with reference to FIG. 5 (a), 5 (b), 5 (c) and 5 (d) show the outputs from the sensors 1 and 2 when the road surface is a snowy road surface, a wet road surface, a dry normal black asphalt and a dry glittering asphalt, respectively. FIG. 9 is a diagram illustrating frequency analysis results for waveforms s1 and s2 and correlation values obtained from the frequency analysis results. The results of frequency analysis of the output waveforms s1 and s2 from the sensors 1 and 2 in the respective road surface conditions are referred to as sp1 and sp2, respectively. In these figures, the horizontal axis represents the frequency and the vertical axis represents the intensity of the light quantity, and the sum of the light quantities of all the frequencies is normalized as 1.

When the two output waveforms sp1 and sp2 overlap each other, if the area of the non-overlapping portion is small, it means that the two output waveforms s1 and s2 are similar, and the area of the non-overlapping portion is large. Means that the two output waveforms s1 and s2 are different. Here, two output waveforms sp
Since the area of the portion where the two sp1 and sp2 do not overlap (hereinafter referred to as the correlation value H) can be expressed by the following equation, the two output waveforms s1 and s are calculated based on the correlation value H.
2 can be obtained. H (s1, s2) = ∫ | sp1 (f) −sp2 (f) |
df

When the road surface is a snowy road surface, as shown in FIG. 5A, in sp1, the frequency corresponding to the tread pattern of the tire increases, so that the area of the non-overlapping portion increases, resulting in a correlation. Value H (s1, s2)
Is a very large value.

When the road surface is a wet road surface, FIG.
As shown in (1), there is no significant difference between sp1 and sp2, and the correlation value H (s1, s2) is smaller than the correlation value on the snowy road surface described above.

When the road surface is ordinary black dry asphalt, as shown in FIG.
2 has substantially the same waveform, as shown in FIG. 5C, sp1 and sp2 are also substantially equal, and as a result, the correlation value H (s1, s2) becomes an extremely small value.

When the road surface is dry asphalt in which a member that shines like glass on asphalt, the output waveform from the sensor 2 may include a regular reflection component as shown in FIG. Since it occurs frequently, it has a waveform similar to that of wet. In addition, since the road surface is not affected even when the tire 5 passes, the output waveforms from the sensor 1 and the sensor 2 are substantially the same, and as a result, the correlation value H (s1, s2) becomes an extremely small value. Become.

Next, a method of determining the road surface state by the comparison determination unit 4 will be described with reference to the flowchart of FIG. When the road surface state detecting operation starts, the sampling control unit 23 stores the output waveforms s2 and s1 from the sensor 2 and the sensor 1 in the memory 22 (S
1, S2). Next, the frequency analysis unit 24 performs a frequency analysis on the output waveforms s1 and s2, calculates frequency analysis results sp1 and sp2 (S3), and calculates a correlation value calculation unit 25.
Calculates the correlation value H (s1, s2) between s1 and s2 based on the frequency analysis results sp1, sp2 (S4). Next, the road surface state determination unit 26 calculates the correlation value H (s1, s
2) is compared with a preset first threshold value (S
5) If the correlation value H (s1, s2) is larger than the first threshold value, it is determined that the vehicle is on a snowy road surface (S6).
In S5, if the correlation value H (s1, s2) is not larger than the first threshold value, the road surface condition determination unit 26 sets the correlation value H (s1, s2) to a second threshold value set in advance. If the correlation value H (s1, s2) is not smaller than the second threshold value, it is determined that the apparatus is in a wet state (S8). At S7, the correlation value H (s1,
If s2) is smaller than the second threshold, it is determined that the asphalt is dry asphalt (S9). Note that the second threshold value is an extremely small value as compared with the first threshold value.

As described above, according to the road surface condition detecting device 10 according to the present embodiment, the output waveform s1 from the road surface 20 through which the tire 5 has passed and the output waveform s2 from the road surface 20 through which the tire 5 has not passed. The road surface condition can be determined from the correlation value H, so that the conventional road surface detecting device based on glossiness cannot accurately determine the color paved road, the shiny paved road, or the paved road with paint. Also, it is possible to stably determine the road surface state without causing a malfunction.

(Second Embodiment) FIG. 7 is a configuration diagram of a main part of a road surface condition detecting device according to a second embodiment. The road surface state detection device 10 according to the present embodiment includes an image detector 30
(Camera). The image detector 30 obtains an output waveform from the road surface 20 through which the tire 5 passes and an output waveform from the road surface 20 through which the tire 5 does not pass. That is, the image detector 30 is disposed so that its light-receiving field of view includes a boundary between the range of the road surface 20 where the tire 5 touches the ground and the range of the road surface 20 where the tire 5 does not touch the ground. The light projecting unit 31 that projects light toward the road surface 20 uniformly irradiates the light receiving field of the image detector 30. The image detected by the image detector 30 is a BNC (bayo
net locktype N connector) output
(See FIG. 3).

It is assumed that an xy-axis image as shown in FIG. 8 is obtained by the image detector 30. Area 1 is an image of the road surface 20 through which the tire 5 has passed, and area 2 is an image of the road surface 20 through which the tire 5 has not passed. Since the output waveforms s1 (i) and s2 (i) based on the respective areas can be expressed by the following arithmetic expressions, the frequency analysis is performed on these two output waveforms in the same manner as in the first embodiment. And calculating the correlation value H,
Even on a color pavement, a glowing pavement, or a pavement with paint, a road surface state can be stably detected without causing a malfunction.

(Equation 1)

(Third Embodiment) FIGS. 9A and 9B are configuration diagrams of a road surface state detecting device according to a third embodiment.
FIG. 2 is a diagram viewed from the side of the vehicle 6 and from the rear with respect to the traveling direction of the vehicle 6. FIG. 10 is a diagram showing the positional relationship between the field of view of the sensor of the device and the ground contact surface of the tire.
In this road surface condition detecting device 10, the sensors 2 and 1 are arranged on the track of the tire 5 in front of and behind the tire 5, respectively, and have a field of view on the road surface 20 in front of and behind the tire 5 in the traveling direction. And

In the configuration in which the sensor 1 and the sensor 2 are arranged side by side in the direction orthogonal to the traveling direction of the vehicle as shown in FIG. 1 described above, as shown in FIG. When the vehicle travels along 20w, a white line 20w enters the field of view of the sensor 2 and the output waveforms from the two sensors 1 and 2 are different from each other. Will be detected. In contrast, FIG.
(A), by arranging the sensors 1 and 2 behind and in front of the tire 5 in parallel to the traveling direction of the vehicle as shown in FIG. 10, the vehicle is moved to the white line 20w as shown in FIG.
, The white line 20w does not enter the field of view of the sensor 2, and the occurrence of erroneous determination can be avoided.

(Fourth Embodiment) FIG. 12 is a block diagram of a road surface state detecting device according to a fourth embodiment. In the present embodiment, the road surface state detection device 10 of FIG. 3 described above is further provided with an odometer 27 that detects the mileage of the vehicle based on the rotation speed of the tire, and compares the mileage L detected by the odometer 27. This is provided to the sampling control unit 23 of the determination unit 4.

As in the embodiment shown in FIG.
When the two sensors 2 and 1 are arranged before and after the tire 5, respectively, when crossing a white line 20w such as a pedestrian crossing painted on the road surface in a direction perpendicular to the traveling direction of the vehicle, the following problem occurs. Occurs. For example, as shown in FIG. 13, if the field of view of the sensor 2 captures a white line 20 w and the field of view of the sensor 1 captures a normal road surface (black asphalt), the output waveforms from both sensors 2 and 1 Is different, so that even if the road surface is dry, an erroneous determination is made that the road surface is not dry.

This problem can be solved if the sensor 1 can detect the same position as the position detected by the sensor 2. That is, when the sensor 1 arrives at the position where the sensor 2 has detected the signal waveform while the vehicle is running, the signal waveform from the sensor 1 may be detected and the correlation value between the two waveforms may be obtained. Therefore, in this embodiment, when the odometer 27 detects that the vehicle has advanced from the position at which the sensor 2 has detected the waveform by the distance between the two sensors 2 and 1, the signal waveform from the sensor 1 is changed. Detected. As a result, occurrence of erroneous determination can be avoided.

Next, the road surface state detecting device 10 of the present embodiment
FIG. 1 shows a method of sampling the waveforms from the sensors 1 and 2 and a method of calculating the correlation value by the comparison / determination unit 4 constituting
4 will be described with reference to the time chart. The sampling control unit 23 receives the traveling distance L from the odometer 27 and calculates the traveling distance (internal distance Lx) that has been integrated since the sensor operation. Next, the sampling control unit 23
Initializes the internal distance Lx to 0 when the internal distance Lx becomes the distance Ls between the arrangements of the sensors 1 and 2, and
A sampling start signal is output, and waveforms from the sensors 1 and 2 are sampled in the memory 22. Next, the correlation calculator 25 calculates a correlation value using the frequency analysis result of the sampling waveform. However, the waveform to be correlated is the waveform of the sensor 2 detected immediately before the waveform from the sensor 1.

(Fifth Embodiment) FIG. 15 is a block diagram of a road surface state detecting device according to a fifth embodiment. In the present embodiment, a ground speed meter is used as the odometer 27 in the fourth embodiment. The odometer 28 based on the ground speed meter calculates a travel distance L based on a ground speed sensor 28a and a ground speed v detected from the ground speed sensor 28a.
And a travel distance calculation unit 28b that calculates the distance. In the one that detects the traveling distance of the vehicle based on the rotation speed of the tire as described in the fourth embodiment, when the tire slips, the speed that is faster than the actual speed is detected, and as a result, the sensor 1 and the sensor The detection position of No. 2 is shifted. On the other hand, when the ground speed meter is used as in the present embodiment, the traveling distance can be accurately detected even if the tire slips, so that the road surface state can be determined with higher accuracy.

(Sixth Embodiment) FIG. 16 is a block diagram of a vehicle equipped with a road surface state detecting device according to a sixth embodiment, and FIG. 17 is a diagram showing a positional relationship of a field of view of a sensor on a road surface. In the present embodiment, the road surface condition detection device 10 having the sensor 1 and the sensor 2 shown in FIG.
At a position behind the sensor 1 with respect to the traveling direction of the vehicle 6,
It further includes a sensor 3 (third optical sensor) having a field of view on the road surface on which the tire 5 of the vehicle 6 has passed.

Changes in output waveforms s1, s2, and s3 obtained by the three sensors 1, 2, 3 will be described with reference to FIG. FIGS. 18 (a), (b) and (c) show the case where the road surface is a wet road surface, respectively.
FIG. 7 is a diagram showing output waveforms s2, s1, and s3 from a sensor 3. If the road surface 20 is a wet road surface, a tire mark remains on the road surface 20 immediately after the tire 5 has passed and a water splash occurs, so that the output waveform s1 slightly changes as compared with the output waveform s2. After that, when the sensor 3 passes, the water on the road surface 20 tries to return to the state before being hit by the tire, so that a waveform close to the waveform of the sensor 2 is obtained.

When the road surface 20 is a snowy road surface (not shown), the running of the vehicle 4 causes the tire marks to be removed from the road surface 2.
Since it is engraved on 0, the output waveforms from the sensors 1 and 3 have a repetition of a cycle corresponding to the tread pattern of the tire 5. For this reason, the output waveform s1 from the sensor 1 and the output waveform s3 from the sensor 3 are substantially equal, and the output waveform s2 from the sensor 2 and the output waveform s3 from the sensor 3 are significantly different.

Further, when the road surface 20 is made of dry asphalt (not shown), the influence of the tire 5 passing through the road surface 20 does not appear on the road surface 20. , 3 output waveforms s1, s
2 and s3 are almost equal.

From the above results, the correlation value H (s1, s2) between the output waveform s2 and the output waveform s1 is more than a predetermined value, and the correlation value H (s1, s) between the output waveform s1 and the output waveform s3.
If 3) is equal to or greater than a predetermined value, it can be determined that the road surface is a wet road surface. Basically, the correlation value increases in the order of snow, wet, and dry. However, when the road surface is a compacted snowy road, the trace of the tire 5 is also thin, so that it is easy to mistake for wet. In a wet state, which can be called submergence, the manner of playing water is large, and the correlation value is likely to be large. In the present embodiment, by comparing the degree of similarity between the waveforms immediately after stepping on the tire 5 and after a while, it is possible to increase the accuracy of separating the snowy road surface from the wet road surface. This takes advantage of the fact that snow is solid and non-fluid, while wet is liquid and fluid.

A method of determining the road surface state by the comparison determination section 4 in the present embodiment will be described with reference to the flowchart of FIG. First, the output waveforms s2, s1, and s3 from the sensor 2, the sensor 1, and the sensor 3 are acquired (S
11, S12, S13), and then these output waveforms s2,
A frequency analysis is performed on each of s1 and s3, and frequency analysis results sp1, sp2, and sp3 are calculated (S1
4). Next, based on the frequency analysis results sp1 and sp2, the correlation value H (s) between the output waveform s1 and the output waveform s2
1, s2) is calculated (S15), and further, a correlation value H (s1, s3) between the output waveform s1 and the output waveform s3 is calculated based on the frequency analysis results sp1, sp3 (S16).
Subsequently, the correlation value H (s1, s2) is compared with a preset third threshold value (S17), and the correlation value H (s1, s1, s2) is determined.
If s2) is larger than the third threshold value, it is determined that the vehicle is on a snowy road surface (S18). Correlation value H (s1, s
If 2) is not greater than the third threshold, the correlation value H
(S1, s2) is compared with a preset fourth threshold value (S19). If the correlation value H (s1, s2) is not smaller than the fourth threshold value, the correlation value H ( s1, s
3) is compared with a preset fifth threshold value (S
20), if the correlation value H (s1, s3) is not larger than the fifth threshold value, it is determined that the vehicle is on a snowy road surface (S1).
8). In S20, the correlation value H (s1, s3)
Is larger than the fifth threshold value, it is determined that the vehicle is on a wet road surface (S21). In S19, the correlation value H (s
If (1, s2) is smaller than the fourth threshold value, it is determined that the vehicle is on a dry road surface (S22). Note that the fourth threshold value is an extremely small value as compared with the third threshold value.

(Seventh Embodiment) The present embodiment is a road surface state detecting device in the case where the vehicle has a mechanism for cutting ice on the road surface. FIGS. 20 (a) and 20 (b) are diagrams showing the surface condition of ice when a normal tire is used and when a chain-mounted tire or a spike tire is used, respectively. FIG. 20 (a) shows the state on the asphalt road surface. The tread pattern 33 is slightly attached to the surface of the ice 31 of FIG.
At 0 (b), a mark 34 of a chain or a spike tire is carved on the surface of the ice 32 on the road surface. For this reason, in the case where ice is on the surface like black ice, etc., the correlation value based on the output waveforms from two or more sensors as described above becomes smaller in normal tire use, Equipped with a chain or the like for a road surface state that is difficult to detect, a frozen state of the road surface can be detected.

(Eighth Embodiment) FIG. 21 shows a medicine spraying vehicle equipped with a road surface condition detecting device according to an eighth embodiment. The medicine spraying vehicle 40 is provided with the above-described road surface state detecting device 1.
0 and a medicine sprayer control unit 4 for controlling the medicine sprayer 41 based on the output from the road surface state detecting device 10.
2 is provided. The defrosting agent 43 is sprayed only when the road surface state detecting device 10 determines that the road surface is a snowy road surface. This eliminates the need to spray the thawing agent on the dry road surface, and saves the amount of thawing agent to be sprayed. In addition, it is possible to prevent natural destruction due to salt damage and deterioration of the pavement road.

The control method of the medicine sprayer 41 by the medicine sprayer control section 42 will be described with reference to the flowchart of FIG. First, the road surface state detection device 10 detects the road surface state (S31), and determines whether the road surface is a snowy road surface or a frozen road surface (S32), and the determination is YES.
In the case of, the medicine sprayer control unit 42 controls the medicine sprayer 41 to spray the thawing agent 43 (S3).
3). If the determination in S32 is NO, the thawing agent 44
Do not spray.

(Ninth Embodiment) FIG. 23 (a) is a schematic diagram showing a road information system using a road surface state detecting device according to a ninth embodiment, and FIG. 23 (b) is controlled by the road information system. FIG. 3 is a diagram showing an example of a road information display board. The road information system 50 provides the road surface condition to the driver by displaying the road surface condition detected by the road patrol car 51 on a road information display panel 52 installed in a service area or the like. The road patrol car 51 includes the above-described road surface state detection device 10, a wireless device 54 that transmits the road surface state output by the road surface state detection device 10 to the road information management station 53, and the road surface state detection device 10, the wireless device 54, and the like. And a control unit 55 for controlling. By mounting the road surface condition detecting device 10 of the present invention on the road patrol car 51, it is possible to inform the driver of accurate road surface information.

(Tenth Embodiment) FIG. 24 shows an auto cruise system using a road surface condition detecting device according to a tenth embodiment. An automatic tracking control unit 61 (ECU) that controls the entire auto cruise system 60 includes a distance measuring device 62 such as a laser radar, a speed sensor 63 that detects a speed from the rotation of a wheel, and the above-described first to seventh embodiments. Three of the road surface state detection devices 10 as shown in the embodiment are connected, and information on the following distance, speed, and road surface state is input from each of them. In addition, the automatic tracking control unit 61
Is connected to an accelerator control unit 64 and a brake control unit 65, so that the own vehicle is in front of an obstacle (another vehicle running).
The accelerator and the brake are controlled so that the distance to the vehicle becomes a predetermined value.

A method for setting the following distance according to the speed in the auto cruise system 60 will be described with reference to FIG. FIG. 25 is a speed control map. Curves F1 and F2 indicate accelerator and brake when the road surface is determined to be a dry road surface and when the road surface is determined to be a winter road surface such as snow and ice. The curve F2 is a guide for control, and the curve F2 is designed to secure a longer inter-vehicle distance for the same speed than the curve F1.

When the road surface state detecting device 10 determines that the road surface is a dry road surface, the automatic following controller 61
The output value from the speed sensor 63 and the output value from the distance measuring device 62 are plotted on a graph. If the output value is higher than the curve F1, it is recognized that the distance to another vehicle is sufficient, and the accelerator is set to O
The accelerator controller 64 is controlled so as to be N. When the output value from the speed sensor 63 and the output value from the distance measuring device 62 fall below the curve F1, the automatic following control unit 61 recognizes that the distance to another vehicle is insufficient, and The accelerator control device 64 is controlled to be turned off, and the brake control device 65 is controlled to control the brake. When the road surface state detection device 10 determines that the road surface is a winter road surface such as snow or ice, the automatic following controller 61 switches from the curve F1 to the curve F2, and, based on the curve F2, as described above. The accelerator control device 64 and the brake control device 65 are controlled.

The speed control method by the automatic following control unit 61 will be described with reference to the flowchart of FIG. When the automatic control of the vehicle is started, the distance to the obstacle ahead is detected by the distance measuring device 62, the speed of the vehicle is detected by the speed sensor 63, and the road surface condition is detected by the road condition detecting device 10 (S41, S42, S42). S4
3). The road surface condition detection device 10 determines whether the road surface is a dry road surface (S44). If it is determined that the road surface is a dry road surface, the F1 curve is selected on the speed control map (S44).
45). When it is determined that the road surface is a snowy road surface, a wet road surface, or the like, an F2 curve is selected on the speed control map (S46). Next, the detected speed and distance are plotted on the speed control map (S47), and it is checked whether the plot point is located above or below the selected curve (S4).
8) If it is below the curve, the inter-vehicle distance is determined to be insufficient, the accelerator is turned off, and brake control is performed (S49). If the plot point is above the selected curve, the inter-vehicle distance is determined to be sufficient and the accelerator is turned on (S50). Thus, according to the auto cruise system according to the present embodiment, when the road surface is in a slippery state such as a snowy road surface, the inter-vehicle distance is set to be longer, so that safe automatic traveling can be realized.

The present invention is not limited to the above embodiment, but can be variously modified. For example, a combination of the first embodiment of FIG. 1 and the third embodiment of FIG.
The first embodiment of the present invention and the sixth embodiment of FIG. 16 can be combined.

[0049]

As described above, according to the road condition detecting apparatus of the present invention, the state of the road after the tire of the vehicle has passed is detected by the first optical sensor, and the condition of the road where the tire of the vehicle does not pass is detected. Is detected by the second optical sensor, and the road surface state is determined based on the output values from these two optical sensors. For example, when the output values from the two optical sensors are significantly different from each other, Is a snowy road surface, a wet road surface when the output values from the two optical sensors show a slight change, and a dry road surface when the output values from the two optical sensors hardly change. The road surface can be determined. in this way,
Between the sensor output from the road surface after the tire has passed and the sensor output from the road surface where the tire does not pass, the road surface may be a color paved road, a shiny paved road, or even a paved road with paint, Since a difference appears depending on the road surface state, the road surface state can be reliably detected without causing a malfunction.

Further, by arranging the respective fields of view of the first and second optical sensors in the rear and front directions in the traveling direction of the tire, it is possible to obtain the same effect as in the above-described first embodiment, and to achieve a white line. Erroneous determination that can occur when the vehicle travels along the road can be avoided.

Further, a third optical sensor is further disposed at a position rearward of the first optical sensor with respect to the traveling direction of the vehicle. By detecting the state of the road surface after the elapse of the time, it is possible to determine and detect a snowy road surface and a wet road surface from the similarity of the output waveforms of both sensors.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a road surface state detection device according to a first embodiment of the present invention.

FIG. 2 is an internal configuration diagram of the road surface condition detection device.

FIG. 3 is a block diagram of a comparison / determination unit included in the road surface state detection device.

4 (a), (b) and (c) show the positions of the visual fields of two sensors constituting the above-mentioned road surface condition detection device when the road surface is a snowy road surface, a wet road surface, or a dry normal asphalt, respectively. FIG. 7 is a diagram showing output waveforms from the first embodiment.

FIGS. 5 (a), (b), (c), and (d) are diagrams for explaining a method of determining a road surface state in the case of a snowy road surface, a wet road surface, a dry normal asphalt, and a dry glittering asphalt, respectively. FIG.

FIG. 6 is a flowchart showing a road surface determination method by the road surface state detection device.

FIG. 7 is a configuration diagram of a road surface condition detection device according to a second embodiment of the present invention.

FIG. 8 is a diagram illustrating an example of an image obtained by a camera of the road surface state detection device.

FIGS. 9A and 9B are configuration diagrams of a road surface state detecting device according to a third embodiment of the present invention.

FIG. 10 is a diagram showing a position of a visual field of a sensor constituting the road surface state detecting device.

11A is a diagram showing the position of the field of view of two sensors arranged side by side in the direction orthogonal to the direction of travel of the vehicle, and FIG. It is a figure showing the field of view of a sensor at the time of arranging two sensors.

FIG. 12 is a block diagram of a road surface condition detecting device according to a fourth embodiment of the present invention.

FIG. 13 is a diagram showing a positional relationship of a visual field of a sensor constituting the road surface state detecting device.

FIG. 14 is a time chart of sampling control by the road surface state detecting device.

FIG. 15 is a block diagram of a road surface state detecting device according to a fifth embodiment of the present invention.

FIG. 16 is a configuration diagram of a road surface condition detecting device according to a sixth embodiment of the present invention.

FIG. 17 is a diagram showing positions of visual fields of three sensors constituting the road surface state detecting device.

FIGS. 18 (a), (b) and (c) are diagrams showing output waveforms from sensor 2, sensor 1 and sensor 3 when the road surface is a wet road surface, respectively.

FIG. 19 is a flowchart illustrating a road surface determination method according to a sixth embodiment.

FIG. 20 is a diagram illustrating a state of a road surface detected by a road surface state detection device according to a seventh embodiment of the present invention;
(A) shows the state of ice when a normal tire is used,
(B) shows the state of ice when a chain is used.

FIG. 21 is a configuration diagram of a medicine sprayer equipped with a road surface condition detecting device according to an eighth embodiment of the present invention.

FIG. 22 is a flowchart showing the operation of the medicine spraying vehicle.

FIG. 23A is a configuration diagram of a road information system using a road surface state detection device according to a ninth embodiment of the present invention,
(B) is a diagram showing an example of a road display board constituting the road information system.

FIG. 24 is a block diagram of an auto cruise system using a road surface state detecting device according to a tenth embodiment of the present invention.

FIG. 25 is a diagram showing a speed control map used for setting an inter-vehicle distance according to a speed in the auto cruise system.

FIG. 26 is a flowchart showing the operation of the auto cruise system.

[Explanation of symbols]

 Reference Signs List 1 sensor (first optical sensor) 2 sensor (second optical sensor) 3 sensor (third optical sensor) 4 comparison / determination unit (determination unit) 5 tire 6 vehicle 10 road surface state detection device

Claims (3)

[Claims] 1. A road surface condition detecting device mounted on a vehicle and detecting a state of a road surface on which the vehicle travels, the device having a field of view on a road surface through which tires of the vehicle have passed, and detecting a signal corresponding to the road surface condition. A first optical sensor, a second optical sensor having a field of view on a road surface through which tires of the vehicle do not pass, and detecting a signal according to a road surface condition; and a first optical sensor and a second optical sensor. A road surface state detection device comprising: a determination unit that compares respective output values and determines a road surface state based on the comparison result. 2. The apparatus according to claim 1, wherein the first and second optical sensors have respective visual fields on a road surface behind the tire in the traveling direction and a road surface in the traveling direction in front of the tire. Road surface condition detection device. 3. A third sensor which is disposed at a position rearward of the first optical sensor with respect to a traveling direction of the vehicle, has a field of view on a road surface through which tires of the vehicle have passed, and detects a signal corresponding to a road surface condition. 2. The optical sensor according to claim 1, wherein the determination unit determines a road surface state by comparing output values from the first, second, and third optical sensors. Or the road surface condition detecting device according to claim 2.