JP2000180378A - Road surface state detector - Google Patents

Abstract

PROBLEM TO BE SOLVED: To ensure safety from the aspect of a road passage by detecting whether a road surface is in a gloss state within a wide range of a road and also especially enabling the detection of the road surface state in front of a vehicle. SOLUTION: A camera is arranged so as to take the image of a predetermined range containing the light irradiation position on a road surface M irradiated with the light from a light source 11 and the delivery range P1 of the image taken by the camera is preset and a part of high brightness equal to or more than a threshold value preset with respect to the image contained in this delivery range P1 is extracted as a partial image Ss1 based on regularly reflected light and, when this extracted partial image Ss1 has an area equal to or more than a preset reference value, it is judged that there is gloss on a road surface.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a road condition detecting device for detecting road condition by mainly detecting glossiness of a road surface for road management and vehicle control.

[0002]

2. Description of the Related Art It is important to grasp the road surface condition such as whether the road surface is dry or wet, in order to ensure safety on road traffic.

[0003] As a device for grasping such a road surface condition, there is a device for detecting the presence or absence of gloss on a road surface (for example, see Japanese Patent Application Laid-Open No. 01-8499).

As shown in FIG. 30, this conventional device includes a light projecting section 50 for irradiating light onto a road surface M, and a regular reflection light of the light emitted from the light projecting section 50 onto the road surface M. A first light receiving unit 51 for detecting the intensity, and a second light receiving unit 52 for detecting the intensity of the diffusely reflected light from the road surface M,
These components 50, 51, and 52 are attached to, for example, a gantry 54 erected on the road side.

In this configuration, when the road surface M is in a dry state, since the road surface M is not glossy, only light having a diffuse component is generated as reflected light from the road surface M. By receiving the diffusely reflected light, a light intensity signal having a certain level is output. However, since the specularly reflected light hardly enters the first light receiving portion 51, the light intensity signal obtained by the first light receiving portion 51 is obtained. Is extremely low. Therefore, at this time, it is determined that the road surface M is in a dry state.

On the other hand, when the road surface M is in a wet state such as being wet with rain, the road surface M becomes glossy.
The reflected light from the road surface M includes not only diffusely reflected light but also regular reflected light. Therefore, not only the light intensity signal is output from the second light receiving unit 52, but also a light intensity signal having a large output level from the first light receiving unit 51 is output.
Therefore, when the outputs of the light intensity signals of the first and second light receiving units 51 and 52 are both large, it is determined that the road surface is in a wet state.

The output of the light intensity signals of the first and second light receiving sections 51 and 52 both increases when the road surface M is in a frozen state as well as in a wet state. Then, when the road surface is in a wet state or a frozen state, the two are collectively referred to as a glossy state without distinction between the two.

When the road surface M is in a glossy state, there is a risk of the vehicle slipping, and the driver or the like is informed of the risk.

[0009]

However, FIG.
In the device shown in FIG. 1, the mounting positions of the light projecting unit 50 and the first and second light receiving units 52 and 54 need to be adjusted with high precision in advance, and only a part of the road surface M is detected. It is not sufficient when it is necessary to grasp the road condition over a certain wide range.

Further, by mounting the light projecting unit 50 and the light receiving units 52 and 54 at the front part of the vehicle, it detects the glossiness of the road surface while traveling and informs the driver of danger or directly controls the vehicle. An apparatus for performing this is also considered.

However, also in this case, the glossy state can be detected only on the road surface state directly below the vehicle mounting portion.
Since the road surface state ahead of the vehicle that the vehicle is about to travel cannot be detected, the responsiveness is insufficient to give feedback to the driver or the vehicle control to avoid danger.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems, and can detect whether or not a road surface is glossy over a wider range. An object of the present invention is to make it possible to detect a state and to ensure safety on road traffic.

[0013]

The road condition detecting apparatus according to the present invention employs the following structure to solve the above-mentioned problems.

That is, according to the first aspect of the present invention, a camera is installed so that a predetermined range including a light irradiation position on a road surface irradiated by a light source can be photographed, and a cutout range of an image photographed by the camera is set. With respect to an image included in the cutout range set in advance, a high-brightness portion equal to or higher than a preset threshold value is extracted as a partial image based on regular reflection light, and the extracted partial image is set in advance. When the area is equal to or larger than the reference value, it is determined that the road surface is glossy.

According to the second aspect of the present invention, a camera is installed so that a predetermined range including a light irradiation position on a road surface irradiated by a light source can be photographed, and a predetermined threshold value is set for an image photographed by the camera. The above high-luminance portion is extracted as a partial image based on specular reflection light, and when the aspect ratio of the extracted partial image is equal to or greater than a preset reference value, it is determined that the road surface is glossy. It is characterized by.

According to a third aspect of the present invention, in the configuration of the second aspect, when there are three or more partial images having the high luminance and the aspect ratio of which is equal to or more than a predetermined reference value, each of the partial images is Only when all the vectors passing on the long axis go to the same point, the partial images are all determined to be images based on specular reflection light.

According to a fourth aspect of the present invention, in the configuration according to any one of the first to third aspects, when a plurality of the high luminance partial images are present close to each other,
When all of these partial images are located on a common straight line, the group of partial images is determined to be an image based on regular reflection light.

According to a fifth aspect of the present invention, in the configuration according to any one of the first to fourth aspects, first and second thresholds are set for the image obtained by the camera. , A high-luminance partial image equal to or higher than the first threshold is extracted as a regular reflection component, and a middle-luminance partial image equal to or lower than the first threshold and equal to or higher than a second threshold is extracted as a diffuse reflection component. It is characterized in that the gloss level of the road surface is detected from the relationship between the two partial images.

According to a sixth aspect of the present invention, in any one of the first to fifth aspects, the camera is provided so that not only the light irradiation position on the road surface of the light source but also the range including the light source can be photographed. The threshold value for extracting an image is determined based on the luminance level of the light source, and the threshold values are updated at regular intervals.

According to a seventh aspect of the present invention, in the configuration of any one of the first to sixth aspects, the light source is a reflected light from a reflector on a roadside, which is irradiated by a luminous body provided in the vehicle. It is characterized by having.

According to the invention of claim 8, in the configuration of any one of claims 1 to 7, the temporal fluctuation amount of the area of the high brightness partial image is detected, and the fluctuation amount is referred to. It is characterized in that the road surface condition is determined.

According to a ninth aspect of the present invention, in any one of the first to eighth aspects, the camera is provided with a filter having a predetermined frequency characteristic.

[0023]

(Embodiment 1) FIG. 1 is an explanatory view showing an installation state of a camera constituting the apparatus on a road in a road surface state detection apparatus according to Embodiment 1 of the present invention.

As shown in FIG.
, The camera 2 uses the streetlights 11, 12, 13,... As light sources on the road surface M illuminated by the light sources 11, 12, 13,. It is installed so that a relatively wide range including the light irradiation location can be photographed. Note that here, for simplicity,
It is assumed that the camera 3 can photograph an area including three street lights 11 to 13 and a road surface M corresponding thereto.

The road surface condition detecting device 1 performs arithmetic processing on an image signal obtained by photographing with the camera 2 to perform a road surface condition
An arithmetic processing unit 3 including a computer or the like for detecting (presence or absence of gloss) is provided.

Next, the operation of detecting the road surface state in the road surface state detecting device 1 having this configuration will be described with reference to the flowchart shown in FIG.

An image signal obtained by photographing with the camera 2 is
It is digitized and taken in the arithmetic processing unit 3 as image data (step 1).

Here, when the road surface M is in a dry state,
Since the road surface M has no luster, only the diffuse reflection light is generated from the road surface M. Therefore, the camera 2 is, for example, shown in FIG.
(a), the image _{S L 1, S L 2,} S L 3 of the light incident directly from the street lamps 11 to 13, will be taken and the image Sk1, Sk2, Sk3 the diffuse reflection light .

On the other hand, when the road surface M is in a glossy state,
The reflected light from the road surface M includes not only diffusely reflected light but also regular reflected light. Therefore, the camera 2 is, for example, shown in FIG.
As shown in (b), images S _L 1, S _L 2, and S _L 3 of light directly incident from the street lights 11 to 13, images Ss 1, Ss 2, and Ss 3 of specularly reflected light of the street lights 1, and street lights 11 to 11. All 13 images Sk1, Sk2 and Sk3 of the diffuse reflection light are taken.

The images SL1, SL2 and SL3 of the light directly incident from the streetlights 11 to 13 have no direct relation in determining the road surface condition. Therefore, in the first embodiment, the light from the streetlights 11 to 13 is used. As shown in FIG. 6, when the camera 1 is installed, the cut-out ranges P1, P2, and P3 of the image on the road surface M are set in advance, and a predetermined The threshold value Eth1 is set in advance.

Then, the arithmetic processing unit 3 compares the images included in the above-described cutout ranges P1, P2, and P3 with the threshold value Eth, and converts the images into black and white binary images.
(Steps 2 and 3). That is, white is set when the luminance level of the image included in the cutout range P1 is equal to or higher than the threshold value Eth, and black when the luminance level is lower than the threshold value Eth.

Next, the contents of the binarization process will be described more specifically. Note that each of the cutout ranges P1, P2, P
3 are the same, so that only one extraction range, for example, P1 will be described here.

When the road surface M is in a dry state, only the image Sk1 based on the diffuse reflection light can be obtained, and the luminance level of the image Sk1 of the diffuse reflection light is lower than that of the image based on the regular reflection light. The brightness level of the image Sk1 is less than the threshold value Eth, and when this is converted into a binary image, the entire cutout range P becomes black.

On the other hand, as shown in FIG. 7A, in the glossy state, the image S based on the diffuse reflected light
Together with k1, an image Ss1 based on specular reflection light is obtained at the same time. At this time, since the image Ss1 based on the specular reflection light has a sufficiently large luminance level than the image Sk1 based on the diffuse reflection light, the image Ss1 is equal to or larger than the threshold value Eth. When this is converted into a binary image, FIG. As shown in the figure, the portion corresponding to the image Ss1 of the regular reflection light on the road surface M is white, and the other portions are black. Hereinafter, the image of the portion with relatively high luminance extracted in this manner is simply referred to as a partial image.

Next, a gloss detection process is performed on the partial image Ss1 (step 4).

In the gloss detection process, as shown in the flowchart of FIG. 4, the area A1 of the partial image Ss1 (actually, the number of pixels of the image Ss1) is measured (step 6), and the measured area A1 is determined in advance. A comparison is made with the set reference value Ath (step 7). If the measured area A1 is equal to or greater than the reference value Ath, it is determined that the road surface M is in a glossy state (step 8). If the measured area A1 is equal to or less than the reference value Ath, it is determined that the road surface M is glossy and dry (step 8). Step 9).

The above processing is performed for each of the cutout ranges P1, P2, P3.
By performing each of the operations, the state of the road surface can be detected over a wide range that can be photographed by the camera 2.

(Embodiment 2) In Embodiment 1 described above, when the camera 1 is installed, the image cutout range P on the road surface M is set.
1, P2 and P3 are set in advance. In that case,
In each case, depending on the installation location of the camera 1 on the road N, the cutout ranges P1, P2, and P3 on which the regular reflection light Ss1, Ss2, and Ss3 can be incident on the road surface M must be set. It takes. When the camera 2 is vibrated (for example, due to an earthquake) and the field of view is shifted, as shown by a broken line in FIG. 7A, the cutout range P1 includes the streetlight 11 instead of the road surface M. At this time, the direct light from the street lamp 11 is regarded as the regular reflection light Ss1 from the road surface M, and there is a possibility that the road surface M is erroneously detected as being in a glossy state.

Therefore, in the second embodiment, the partial image Ss of the regular reflection light obtained when the road surface M is in the glossy state.
Focusing on the patterns 1, Ss2, and Ss3, the specular reflection component is considered when the pattern is a long ellipse, and the light source is considered when the pattern is not a long ellipse but close to a circle. To do it. That is, the specularly reflected light to the camera 2 includes the light sources 11 to 13, the road surface M, and the camera 2.
, The relationship of incident angle = reflection angle holds, so that the partial images Ss1, Ss2, S
As shown in FIG. 7B, the pattern of s3 has a long elliptical shape having a certain length along the reflection direction, and thus can be distinguished from the pattern based on the light source.

The specific processing contents of the arithmetic processing unit 3 of the second embodiment will be described with reference to the flowchart shown in FIG. Note that, also in the second embodiment, in order to simplify the description, the camera 3 includes three street lights 11 to 11.
13 and an area including the road surface M corresponding thereto is installed.

An image signal obtained by photographing with the camera 2 is digitized by the arithmetic processing section 3 and taken in as image data (step 10).

Next, the arithmetic processing unit 3 converts the fetched image into a binary image and extracts a pattern of a high-luminance partial image (step 11). The processing content in that case is described in the first embodiment.
Is the same as For example, when the road surface M is in a glossy state, it is based on binarized partial images S _L 1, S _L 2, S _L 3 based on light directly incident from the street lamps 11 to 13 and the regular reflection light of the street lamp 1. Binarized partial images Ss1, Ss
2, Ss3.

Next, the extracted partial images S _L 1 and S _L
2, S _L3 , Ss1, Ss2, and Ss3 are subjected to the following processing. Here, one partial image Ss1 will be described as an example, but other partial images S _L1 , S _L2 , S
_The processing contents are the same for L3, Ss2, and Ss3.

First, as shown in FIG. 9A, a predetermined image area Q including this partial image Ss1 (however, this image area Q is smaller than the cutout range P1 described in the first embodiment)
Is set, and the center of gravity O 'of the partial image Ss1 is set.
Is calculated (step 12). Then, as shown in FIG. 9 (b), an orthogonal coordinate system (X 'axis-Y' axis) with the center of gravity position O 'as the origin is set. Subsequently, as shown in FIG.
This image area Q is rotated about the center of gravity position O ′ and the rotation angle θ
Are sequentially rotated by an angle width of Δθ, the widths D and L of the images projected on the X ′ axis and the Y ′ axis of the partial image Ss1 are obtained, and the aspect ratio H (= L / D) of both is obtained. ) Is calculated.
By repeating this process from θ = −90 ° to θ = + 90 °, a peak curve of the aspect ratio H with the change of the angle θ is obtained as shown in FIG. 9D. Therefore, the maximum value Hp of the aspect ratio H is determined from this curve. (Steps 13-1
9).

Then, the maximum value Hp of the aspect ratio H is compared with a preset reference value Hth (step 20). As the reference value Hth in this case, for example, L = 2D, that is, the length in the long axis direction is set to twice (H = 2) the length in the short axis direction.

As described above, the patterns of the partial images Ss1, Ss2, and Ss3 based on the specularly reflected light when the road surface M is in a glossy state have an oblong shape having a certain length along the reflection direction. The aspect ratio H is equal to the reference value Hth
That is all. Therefore, in this case, it is determined that the road surface M is in a glossy state (step 21).

On the other hand, since the pattern of the partial images S _L 1, S _L 2, S _L 3 of the light directly incident on the camera 2 from the street lamps 11 to 13 is substantially circular, the aspect ratio H is not more than the reference value Hth. Become. Therefore, when H <Hth, the street lights 11 to 1
It is highly possible that the partial images S _L 1, S _L 2, and S _L 3 due to 3 are not included in the partial image based on the specularly reflected light. partial image _{S L 1, S L 2,} S L 3 is from white to black (step 2
2).

The above processing is performed by using a partial image S _L having high brightness.
1, S _L2 , S _L3 , Ss1, Ss2, Ss3 (Step 23).

In this way, as in the first embodiment, it is not necessary to set the cutout ranges P1, P2, and P3 in advance at a location corresponding to the road surface in accordance with the installation location of the camera 2 each time. It can be determined whether M is in a glossy state.

However, when the street lights 11 to 13 are, for example, elongated fluorescent lights, the light directly incident on the camera 2 from the light source is determined by the judgment based on the aspect ratio H alone, as shown in FIG. At 20, it is determined that H> Hth, which may be erroneously recognized as regular reflection light. To cope with this, it is more preferable to add the following processing.

Now, assuming that an image as shown in FIG. 10A is taken by the camera 2, at the time when the processing of the flowchart shown in FIG. 8 is completed, as shown in FIG. Only the partial images Ss1, Ss2, Ss3 satisfying ≧ Hth remain.

Therefore, each of these partial images Ss1, Ss
2, Ss3 only when all the vectors passing on the long axis go to the same point, the partial images Ss1, Ss2, Ss
No. 3 judges that the images are all based on specularly reflected light.

In this way, even if the light source is an elongated fluorescent lamp, the light source is not erroneously detected as the regular reflection light from the road surface M. Properties can be further enhanced.

The specific processing operation will be described with reference to the flowchart shown in FIG. Note that the processing of each step shown in FIG. 11 is performed in Step 2 of the flowchart of FIG.
The processing is performed after the processing of step 3.

As shown in FIG. 12, each partial image Ss
1, Ss2, Ss3, the rotation angles θmax1, θmax2, θmax3 corresponding to the maximum value Mp of the aspect ratio are obtained (step 31). The unit vectors v1, v2, and v3 starting from the barycentric positions O'1, O'2, and O'3 of Ss1, Ss2, and Ss3 are determined (step 32). And
Straight line R overlapping in the direction of each unit vector v1, v2, v3
The equations of 1, R2 and R3 are obtained (step 33).

Next, the intersection coordinates C12 of the straight lines R1 and R2 passing through the partial images Ss1 and Ss2 are calculated (step 34), and then the intersection coordinates of the straight lines R1 and R3 passing through the partial images Ss1 and Ss3. C13 is calculated (step 34). Then, it is checked whether or not both intersection coordinates C12 and C13 match (step 35).

When both intersection coordinates C12 and C13 match, it is determined that these partial images Ss1, Ss2 and Ss3 are all glossy because they are based on regular reflection light (step 37). On the other hand, when the intersection coordinates C12 and C13 do not match, these partial images Ss1, Ss2, Ss3
At least one of them is not based on the specular reflection light and is determined to be undetectable (step 38).

In this way, even if the light source is an elongated fluorescent light, the light source is not erroneously detected as the regular reflection light from the road surface M. Can be further increased.

(Modifications) The following modifications are conceivable for the first and second embodiments.

When the road surface M is not flat but uneven, the specularly reflected light does not form a simple oblong pattern, but is divided into a plurality of patterns according to the unevenness, depending on the direction in which the camera 2 shoots. Sometimes.

That is, as shown in FIG. 13 (a), even if a place where specularly reflected light of the road surface M is likely to be incident is set in advance as the cutout range P1 of the image, the road surface M at that place is set. Is irregular, the specularly reflected light from the portion corresponding to the concave portion does not enter the camera 2. Therefore, the partial image after the binarization processing should originally be one partial image Ss1 if there are no irregularities, but as shown in FIG. 13B, three or more partial images Ss1a, Ss1
b, Ss1c. Then, even if the area of each of the partial images Ss1a, Ss1b, and Ss1c is calculated and compared with the threshold value as in the first embodiment, the area of each partial image is all equal to or smaller than the threshold value. Embodiment 2
Even when the aspect ratio is calculated and compared with the threshold value, the aspect ratios of the respective partial images all fall below the threshold value. That is, the light is not determined to be the original regular reflection light, and the road surface M may be erroneously detected as not being in the glossy state.

In order to eliminate such inconvenience, when a predetermined image area Q is set, a group (three in this example) of partial images Ss1a adjacent to the predetermined image area Q is set.
ＳSs1c to Ss1c, the partial images Ss1a to Ss1c are processed by the same processing as in the flowchart shown in FIG.
An equation of each straight line overlapping in the direction of the unit vector 1c is obtained, and when these straight lines substantially overlap each other, the group of partial images Ss1a to Ss1c is based on specular reflection light and the road surface is in a glossy state. Judge.

By doing so, even if the road surface becomes uneven due to aging of the road, erroneous recognition can be prevented.

In the first and second embodiments, the presence / absence of gloss is detected based on the binarized partial image.
The present invention is not limited to this. In detecting the degree of gloss, three threshold values Eth1 and Eth2
A valued image may be used.

As an example, steps 3 and 4 of the flowchart shown in FIG. 3 in the first embodiment can be replaced with the processing contents of the flowchart shown in FIG.

That is, two threshold values ETh are set in advance.
1, Eth2 (where Eth1> Eth2)
For example, an image included in one cutout range P1 as shown in FIG. 15A is compared with threshold values Eth1 and Eth2, and as shown in FIG.
The above partial images Ss are shown in white, the partial images Sk that are equal to or more than Eth2 and less than Eth1 are shown in gray, and the others are shown in black (step 40). The white partial image Ss is an image based on the regular reflection light from the road surface M, and the gray partial image Sk is an image based on the diffuse reflection light.

Then, for each of the partial images Ss1 and Sk1, the areas As1 and Ak1 (the number of pixels) are obtained (step 41), and then the ratio of both As1 and Ak1 (= As1 / Ak1)
Is determined as the gloss level K (step 42).

Partial image Ss1 of specular reflected light reflected on camera 2
And the area Ak of the partial image Sk1 of the diffuse reflected light.
The relationship with 1 is that when the degree of gloss K increases, the light from the light source has a large specular reflection component, and the area Ak1 of the partial image Sk1 of the diffuse reflection light decreases.

Therefore, two thresholds Kth1 and Kth2 (where Kth1 <Kth2) are set in advance for discriminating the degree of gloss, and the degree of gloss K is set to these thresholds Kth
1 and Kth2 (steps 43 and 44).

If the glossiness K is equal to or smaller than Kth1, it is determined that the road surface M is not in a glossy state (step 4).
5) If the value is equal to or larger than Eth1 and smaller than Eth2 (step 4)
6) The road surface M is glossy but the degree is small
(Step 46) If Eth2 or more, it is determined that the road surface M is in a glossy state and its degree is large (Step 4).
7).

As described above, the two threshold values Eth1, Eth
If a ternary image is provided by providing 2, the degree of gloss K can be detected.

In the case of the second embodiment, the ternary image can be similarly processed. Further, the image is not limited to the ternarization, and it is also possible to convert the image to a quaternary or more.

The threshold values Eth for binarizing the image in the first and second embodiments and the threshold values Eth1 and Eth2 for binarizing the image in the above-described modified examples are both after initial setting. Is not changed, but with such a fixed value, if the light sources 11 to 13 are deteriorated and the light emission power is reduced, they will be affected.

Therefore, in order to eliminate this inconvenience, it is possible to make these threshold values Eth, Eth1, and Eth2 variable according to the state of the light source.

As an example, a case will be described in which the threshold values Eth1 and Eth2 for ternarizing an image in the above-described modified example can be changed.

As shown in FIG. 16 (a), not only the cutout range P1 of the image corresponding to the road surface M is set in advance, but also the cutout range L1 of the portion including the light source 11 is set at the same time. The luminance level E of the light source 11 within the cutout range L1 is measured. Then, based on the luminance level E,
The threshold values Eth1 and Eth2 for converting an image are determined as follows.

Since the luminance level of the image Ss1 based on the regular reflection light is almost the same as the luminance level of the light source 11, the threshold value is set to Eth1 = k1 · E (for example, k1 = 0.5). If the reference road surface M is black, the luminance level of the image Sk1 is reduced by one digit or more. Therefore, the threshold value is set to Eth2 = k2 · E (for example, k2 = 0.05).

As described above, the cut-out range L1
From the value of the luminance level E of the light source 11 within the threshold value Eth
1 and Eth2, and updating these threshold values Eth1 and Eth2, there is no effect even if the light emission power is reduced due to the aging of the light source 11, and is not affected as shown in FIG.
Value images Ss1 and Sk1 can be obtained.

Although the case where a ternary image is obtained has been described here, the threshold value Eth for binarizing the image in the first and second embodiments is also set to Eth = k · E (for example, k = 0.5) as a matter of course.

In the first and second embodiments, when a thermometer is added to the road surface condition detection device 1, when it is determined that the road surface M is in a glossy condition, it is possible to distinguish between wet and frozen.

For example, in the case of the first embodiment, as shown in the flowchart of FIG. 4, the area A1 of the partial image Ss1 is compared with the reference value Ath (step 7), and it is immediately determined whether or not there is a gloss state (step 7). Steps 8, 9) Instead,
As shown in FIG. 17, the area A1 of the partial image Ss1 is compared with the reference value Ath (step 7), and the area A1 is compared with the reference value Ath.
If the road surface M is larger, the road surface M is in a glossy state.
Subsequently, it is determined whether or not the temperature measured by the thermometer is 0 ° C. or less (step 50).
Is determined to be frozen (step 51). Also, 0 ° C
Is exceeded, it is determined that the road surface M is in a wet state (step 52). Further, the area A of the partial image Ss1
If 1 is smaller than the reference value Ath, the average value of the luminance levels of all the pixels within the cut-out range Sr is calculated (step 53), and this average value is compared with a preset threshold ath. (Step 54). If the average value is less than the threshold value ath, it is determined that the road surface M is in a dry state (step 55), and if the average value is not less than the threshold value ata, it is determined that the road surface M has snow (step 55). 56).

Further, even if a thermometer is not provided, it is possible to determine whether the road surface M is in a wet state or a frozen state by detecting the partial image based on the regular reflection light, for example, the area A1 of Ss1, continuously. .

For example, as shown in FIG. 18, when the road surface M is in a wet state, the surface of the partial image Ss1 based on the regular reflection light changes over time because the surface fluctuates as compared with the frozen state. . Therefore, the wet or frozen state can be distinguished by the magnitude of the fluctuation.

For example, instead of the processing of the flowchart of FIG. 17, as shown in the flowchart of FIG. 19, the area A1 of the partial image Ss1 is compared with the reference value Ath (step 7), and the area A1 is smaller than the reference value Ath. If it is larger, the road surface M is in a glossy state, so that the area of the partial image Ss1 is successively calculated over a certain period of time, and the maximum value A1max and the minimum value A1min of the area within that time are obtained (step S1). 60, 61). And both A1ma
The difference between x and A1min (= A1max-A1min) is calculated as the fluctuation B1 of the specularly reflected light (step 62). Next, the fluctuation B1 is compared with a preset reference value Bth (step 63).
Is equal to or smaller than the reference value Bth, it is determined that the road surface M is frozen (step 51). If the fluctuation B1 exceeds the reference value Bth, it is determined that the road surface M is in a wet state.
(Step 65).

In the case where the area A1 of the partial image Ss1 is smaller than the reference value Ath in step 7, the processing shown in FIG.
(Steps 53 to 56)
Here, the description is omitted.

In each of the first and second embodiments, the streetlight 1
Although the description has been given of the case where the light sources 1 to 13 are used, the present invention is not limited to this. For example, as shown in FIG. The traffic signal control at the intersection can also be performed based on the detection output.

In this case, the traffic light 20 has a wavelength of light of red.
Since the three types are switched to yellow and green, the camera 2 can be made less susceptible to external noise by providing the camera 2 with a filter that matches the wavelength of the color to be used as a light source in each color.

For example, as shown in the flowchart of FIG. 21, when it is determined that the road surface M is glossy and dangerous, the lighting time of the yellow traffic light is lengthened and the traffic light of the crossing road is switched to green. Slow down. As a result, it is possible to prevent the vehicle from coming into contact with the vehicle from the crossing road when the vehicle cannot be stopped by sudden braking.

Streetlights 11 to 1 in Embodiments 1 and 2
3 or the traffic light 20 in the above-mentioned modified example,
Not only when the position of the light source is fixed, but also when the light source
The present invention is applicable to the case of moving up.

That is, as shown in FIG. 22 (a), by using the light of the head lamp 32 of the vehicle 30 passing through the road surface M as a light source, the light is not at discrete positions such as the street lights 11 to 13, By obtaining an image as shown in FIG. 22 (b), it is possible to detect the gloss state at continuous positions along the road N.

In this case, since the passing time of the vehicle 30 varies, it is more convenient to output the detection time together.

The camera is not limited to the one where the installation position is fixed. For example, as shown in FIG.
Camera 2 is installed so that you can observe the front of the vehicle
If the light source is the backlight of the vehicle ahead, based on the same principle, an image as shown in FIG.
The glossiness of the road surface can be detected. Then, by informing the degree of gloss of the road surface M by image or voice based on the detection result, it is possible to encourage the driver to drive safely.

Further, the reflector 3 is provided on the road side of the road N or the like.
4 and the reflected light when the light from the headlamp 32 of the vehicle 30 is reflected by the reflector 34 is used as a secondary light source.
Using the same principle, an image as shown in FIG.
It is also possible to detect the luster state of the vehicle and inform the driver of the road surface state.

In this case, as shown in the modified example, the vehicle 30 does not need to be present in front of the vehicle. Can be grasped.

(Application Example) The following application example is also conceivable using the road surface condition detecting device of the present invention.

FIG. 25 shows a medicine spreading vehicle equipped with the road surface condition detecting device 1 according to the present invention.

When the control unit 38 of the medicine spraying vehicle 36 determines that the road surface condition is frozen based on the detection result of the glossy condition input from the road condition detection device 1 according to the present invention, the medicine spraying machine 40 To spray thawing agent.

FIG. 26 shows a configuration of a road information system using the road surface state detecting device 1 according to the present invention.

As shown in FIG. 26 (a), the control unit 43 of the road patrol car 42 transmits the information of the glossy state detection result input from the road surface state detection device 1 according to the present invention to the road information by the radio unit 44. It is transmitted to the management station 45.

As shown in FIG. 26 (b), the road information management station 45 displays the information on, for example, a road information display board 46 provided in each service area or the like, thereby
Road surface information can be provided to road users.

FIG. 27 shows a configuration of an auto cruise as an example of an automobile control system using the road surface state detecting device 1 according to the present invention.

The automatic following control unit (ECU) 50 is connected to a distance measuring device 51 such as a laser radar, a speed sensor 52 for obtaining a speed from the rotation of wheels, and a road surface condition detecting device 1 according to the present invention. Have been.

The ECU 50 includes the respective devices 51, 5
The accelerator control device 53 and the brake control device are controlled based on the information on the distance, speed, and road surface condition output from the vehicle 2 and 1 so that the required braking distance to be maintained with another vehicle during traveling is an appropriate value. 54 is controlled. In particular, when the road surface condition is grasped by the device 1 of the present invention and the road surface is determined to be a slippery road surface at the time of freezing, the braking effect is reduced, so the necessary braking distance is set longer.

FIG. 28 shows an appropriate braking distance according to the traveling speed. The curve F1 in the figure is for a normal dry road surface, the curve F2 is for a slippery frozen road surface, and the curve F2 always secures a longer distance from the curve F1.

The speed and distance measuring device 51 of the speed sensor 52
When the output value of the distance from the vehicle is plotted on this graph, if it is higher than this curve F1 (or F2), it is recognized that the distance to another vehicle is sufficient, and the accelerator is turned on. If the vehicle falls below the curve F1 (or F2), it recognizes that the distance to the other vehicle is insufficient, turns off the accelerator, and controls the brake. An example of specific control is shown in the flowchart of FIG.

As described above, by preparing appropriate curves F1 and F2 suitable for a change in the braking distance depending on the road surface condition, safe and smooth automatic traveling can be performed.

[0107]

According to the present invention, the following effects can be obtained.

(1) According to the first and second aspects of the present invention, it is possible to detect whether the road surface is in a glossy state over a wide range of the road, and thus it is possible to secure safety on road traffic.

(2) In particular, according to the second aspect of the present invention, it is possible to distinguish between light directly entering from a light source and specularly reflected light from a road surface without setting an image cutting range on the road surface in advance. Since it is possible, the trouble when installing the camera can be saved.

(3) According to the third aspect of the present invention, even when the light source is an elongated fluorescent lamp, it can be distinguished from the regular reflection light from the road surface, so that erroneous detection of the road surface state can be prevented.

(4) According to the fourth aspect of the invention, even when the road surface is not flat but uneven, it is possible to determine whether the light is specularly reflected light from the road surface.

(5) According to the fifth aspect of the invention, by setting a plurality of threshold levels, it is possible to detect the degree of gloss of the road surface.

(6) According to the sixth aspect of the invention, even if the light source deteriorates and the light emission power decreases, it can be reliably determined whether or not the light is specularly reflected from the road surface.

(7) According to the seventh aspect of the present invention, even if there is no other vehicle in front, the road surface condition can be grasped only by irradiating the light of the headlamp of the own vehicle toward the reflector. So flexible.

(8) According to the eighth aspect of the present invention, when it is detected that the road surface is in a glossy state, it can be distinguished between a wet state and a frozen state without providing a thermometer.

(9) According to the ninth aspect of the present invention, for example, only light of a specific wavelength can be photographed as an image. Therefore, even when a traffic light is used as a light source, the influence of external noise can be reduced.

[Brief description of the drawings]

FIG. 1 is an explanatory diagram showing an installation state of a camera constituting the apparatus on a road in a road surface state detection apparatus according to a first embodiment of the present invention;

FIG. 2 is a block diagram illustrating a configuration of a road surface state detection device according to the first embodiment of the present invention.

FIG. 3 is a flowchart for explaining the operation of an arithmetic processing unit of the road surface state detecting device according to the first embodiment of the present invention;

FIG. 4 is a flowchart showing details of the details of gloss detection processing in FIG. 3;

FIG. 5 is an explanatory diagram of images taken by a camera when a road surface is in a dry state and in a glossy state.

FIG. 6 is an explanatory diagram in a case where an image cutting range is set in the first embodiment of the present invention;

FIG. 7 is an explanatory diagram of a binarization process according to the first embodiment of the present invention.

FIG. 8 is a flowchart illustrating an operation of an arithmetic processing unit according to the second embodiment of the present invention.

FIG. 9 is an explanatory diagram of gloss detection processing based on the flowchart of FIG. 8;

FIG. 10 is an explanatory diagram of gloss detection processing content according to the second embodiment.

FIG. 11 is a flowchart showing a regular reflection light discriminating operation in the second embodiment;

FIG. 12 is an explanatory diagram of the content of a process of determining regular reflection light based on the flowchart of FIG. 11;

FIG. 13 is an explanatory diagram of a partial image based on regular reflection light generated by unevenness of a road surface.

FIG. 14 is a flowchart for detecting a gloss level of a road surface;

FIG. 15 is a diagram illustrating a case where a partial image based on regular reflection light and a partial image based on diffuse reflection light are extracted by performing ternarization processing on an image.

FIG. 16 is an explanatory diagram of a case where a threshold value for extracting an image can be changed;

FIG. 17 is a flowchart for determining whether a road surface is wet or frozen based on a thermometer.

FIG. 18 is a diagram for explaining that the degree of fluctuation of the area of a partial image based on regular reflection light varies depending on whether the road surface is in a wet state or a frozen state.

FIG. 19 is a flowchart for determining whether the road surface is wet or frozen based on the degree of fluctuation of the area of the partial image based on specular reflection light.

FIG. 20 is an explanatory diagram when a traffic light is used as a light source for detecting a road surface state;

FIG. 21 is a flowchart of a control operation when signal control is performed using a traffic light as a light source.

FIG. 22 is an explanatory diagram when a headlight of a vehicle is used as a light source for detecting a road surface state;

FIG. 23 is an explanatory diagram in the case where light from a tail lamp of a vehicle ahead is used as a light source for detecting a road surface state.

FIG. 24 is an explanatory diagram of a case where a reflector provided on a road side of a road is used as a secondary light source for detecting a road surface state;

FIG. 25 is an explanatory view showing a medicine spraying vehicle provided with the road surface condition detecting device according to the present invention.

FIG. 26 is an explanatory diagram of a case where a road information system is configured by providing a road surface state detection device according to the present invention in a road patrol car;

FIG. 27 is a block diagram when a vehicle control system is configured using the road surface state detection device according to the present invention.

FIG. 28 is a diagram illustrating the vehicle control system shown in FIG.
Characteristic diagrams showing the relationship between the traveling speed and the appropriate braking distance according to the case where the road surface is frozen and the case where the road surface is dry

FIG. 29 In the vehicle control system shown in FIG.
Flowchart for explaining operation when brake control is performed based on the characteristic diagram of FIG.

FIG. 30 is a configuration diagram of a conventional road surface state detection device.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Road surface condition detection device, 2 ... Camera, 3 ... Operation processing part,
4 ..., 6 ..., 8 ..., 10 ..., 11-13 ... Streetlights (light sources),
N: road; M: road surface; P1 to P3: cutout range; Q: image area; Ss1 to Ss3: partial image based on specularly reflected light; Sk
1 to Sk3: partial image based on diffuse reflection light, S _L 1 to S _L
3: Partial image based on incident light from a light source.

Claims (9)

[Claims] A camera is installed so that a predetermined range including a light irradiation position on a road surface irradiated by a light source can be photographed, and a cutout range of an image shot by the camera is set in advance, and the cutout range is set. When a high-luminance portion equal to or greater than a preset threshold value is extracted as a partial image based on specular reflection light, and the extracted partial image has an area equal to or greater than a preset reference value, A road surface condition detecting device that determines that the road surface is glossy. 2. A camera is installed so as to be able to photograph a predetermined range including a light irradiation position on a road surface irradiated by a light source, and a high-luminance portion of an image photographed by the camera which is equal to or higher than a predetermined threshold value. Is extracted as a partial image based on regular reflection light, and when the aspect ratio of the extracted partial image is equal to or greater than a preset reference value, it is determined that the road surface is glossy. Detection device. 3. When there are three or more partial images having high luminance and an aspect ratio equal to or higher than a predetermined reference value, all vectors passing along the long axis of each partial image are directed to the same point. The road surface state detecting device according to claim 2, wherein only in such a case, the partial images are determined to be images based on specularly reflected light. 4. When a plurality of high-brightness partial images are present close to each other, and when all of these partial images are located on a common straight line, the group of partial images is correct. The road surface state detecting device according to claim 1, wherein the road surface state detecting device determines that the image is based on the reflected light. 5. An image obtained by photographing with the camera is set with first and second thresholds, two large and small, and a high-brightness partial image equal to or larger than the first threshold is used as a specular reflection component. The method is characterized in that a partial image having a middle luminance that is equal to or less than one threshold value and equal to or greater than a second threshold value is extracted as a diffuse reflection component, and a gloss level of a road surface is detected from a relationship between the extracted two partial images. The road surface condition detecting device according to claim 1. 6. Not only the light irradiation position on the road surface of the light source but also
A camera is installed so that an area including the light source can be photographed, threshold values for image extraction are determined based on the luminance level of the light source, and these threshold values are updated at regular intervals. The road surface condition detecting device according to any one of claims 1 to 5, wherein: 7. The road surface according to claim 1, wherein the light source is reflected light from a reflector on a roadside, which is illuminated by a light emitter provided in the vehicle. State detection device. 8. The method according to claim 1, wherein a temporal fluctuation amount of an area of the high-brightness partial image is detected, and a road surface state is determined with reference to the fluctuation amount. A road surface state detection device according to any of the above items. 9. The road surface condition detecting device according to claim 1, wherein the camera includes a filter having a predetermined frequency characteristic.