JPS601574B2 - Road surface condition detection method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to a method for detecting a road surface condition, particularly a frozen road surface condition.

Ensuring the safety of drivers by taking appropriate measures to deal with traffic disturbances caused by frozen roads, snow accumulation, etc. is a very serious issue in traffic control systems. It is necessary to quickly and accurately grasp the road surface condition.

To this end, various methods have been proposed for detecting road surface conditions using light reflection, but all of these methods can only detect the dry, wet, and snowy conditions of the road surface; The determination was made by measuring the road surface temperature or air temperature with a thermometer and comparing this measured temperature with the freezing temperature. However, the freezing temperature
There is a problem in that if the freezing temperature is used as a standard, the determination of the frozen state becomes inaccurate because it decreases due to the application of snow-melting agents and changes depending on the location where the road surface condition is to be detected and the weather conditions. This invention has been made in view of the above circumstances, and provides a method that can accurately detect the frozen state of a road surface without being affected by snow melting agents or other substances.

The method of the present invention will be explained in detail below with reference to the drawings.
In FIG. 1, a pillar 5 is erected on the negative side of the road 4, and a support arm 6 extends upward from the vicinity of the upper end of the pillar 5 toward the upper side of the road 4. Then, a floodlight 3 is mounted on the top of the support column 5.
Support arm 6': Infrared light receiver 1 and visible light receiver 2
are installed respectively. The projector 3 projects a reference light toward the road surface in order to collect road surface condition signals, and is arranged so as to be directed at an appropriate angle of incidence at an appropriate location on the road surface, for example, at the center of the middle direction of the road. ing. The magnitude of the incident angle does not affect the determination of the road surface condition, which will be described later. As a light source for the projector 3, for example, a mercury lamp whose emission spectrum includes not only visible light but also near-infrared light is preferable. The light from the light source is collected by a suitable optical system and projected onto the road surface. The light receiving paths 1 and 2 are the light emitting path 3.
It receives the diffusely reflected light of the light reflected from the road surface projected from the road surface and converts it into an electrical signal. The light receiver 1 receives near-infrared light among the diffusely reflected light from the road surface, and the light receiving element is preferably made of lead sulfide (PbS) or lead selenide (P daughter e). The wavelength of about 1.
An infrared transmitting filter is provided that transmits infrared light in the range of 4 to 2.5 (〃). The light receiver 2 receives visible light among the diffusely reflected light from the road surface, and the light receiving element is preferably a photo diode or a photo transistor, and a filter that transmits only visible light is placed in front of the light receiving surface of the light receiving element. Evening is set. In Fig. 2, the reflected infrared light signal output from the receiver 1 is intensified to an appropriate level by an intensifier 11, and then sent to a low-pass filter 12 to remove disturbance noise. . The output of filter 12 is input to comparators 13 and 14. The reflected light signal of visible light outputted from the light receiver 2 is similarly intensified by an intensifier 21 and then sent to a comparator 23 through a low-pass filter 22 . If necessary, the light source of the projector 3 is modulated at an appropriate frequency to increase the respective reflected light signals 11, 2.
It is preferable to demodulate at the subsequent stage of 1. Incidentally, the surface of snow exhibits a diffusing surface with a light reflectance of nearly 100% for visible light, but as the wavelength of light becomes longer, the reflectance decreases due to absorption by moisture. The solid line in FIG. 3 shows the relative reflectance characteristic curve of the snow surface with respect to the reflectance of barium sulfate when the wavelength is changed. This graph shows the same tendency even if the reflection angle is different. The reason why the reflectance of a snow surface drastically decreases in the infrared light region is due to absorption by moisture, so the reflectance of a road surface containing moisture (wet) similarly shows an extremely small value in the infrared light region. However, when water freezes and becomes ice, no absorption band is generated due to water, and the reflectance becomes larger than that of water or snow, as shown by the broken line in FIG.
The difference in reflectance between ice, water, and snow is that the wavelength is 1.4 (mm).
) is clear in the wavelength range above. The reduced-pass filter filter is applied to four road conditions: when the road surface is dry (dry), when the road surface is wet (humid), when there is snow on the road surface, and when the moisture on the road surface is frozen. 12,
Table 1 shows an example of the results of measuring the levels of the output signals of No. 22, and how the output levels are arranged in order of magnitude based on the results.

Here, the reflected light signal of infrared light is an average value for wavelengths of 1.4 to 2.5 (mu). As mentioned above in Table 1, infrared light is absorbed by moisture, so the amount of reflected light is small in snowy and wet conditions.

Snow conditions observed in infrared light include conditions in which snow, mud, and water are mixed (hereinafter referred to as snow jam), and conditions in which dust is attached to the snow surface (hereinafter referred to as black snow). There is. In a frozen state, infrared light is not absorbed, so the value is larger than in a snowy or wet state. Furthermore, in a dry state, the road surface becomes a diffusion surface, so the output level of the filter 12 is relatively high. For visible light, when there is snow on the road surface, the snow creates a diffusion surface with a light reflectance of nearly 100%, so the output level of the filter 22 exhibits a very large value. Snow cover conditions in visible light only refer to snow that appears white, and do not include snow jams or black snow. On the other hand, in a humid state where the road surface is wet, the road surface becomes a mirror surface, so the specularly reflected light component increases, but the diffusely reflected light component decreases, so the output level of the filter 22 is a low value. Since a dry road surface is a diffusive surface with low light reflectance, its value is between that of snow and wet road surface. The amount of diffusely reflected light in a snow jam or black snow condition is approximately the same level as in this dry condition. Also,
The frozen state includes a mirrored state and a state with many irregularities, and the amount of diffusely reflected light often changes depending on each state, so it is not shown in Table 1, but it is roughly the same as the dry state. level. Discrimination level AI of comparator 13
is set between the output level of the filter 12 in a frozen state and the same output level in a snowy or wet state, and when the same output level exceeds this discrimination level AI, the output signal from the comparator 13 is " 1” occurs.

Further, the discrimination level A2 of the comparator 14 is set between the output level of the filter 2 in a dry state and the same output level in a frozen state, and when the same output level is less than this discrimination level A2, the comparator 14 Output signal “1” from
” occurs. Therefore, according to the information from the reflected infrared light signal, if (output of comparator 13, output of comparator 14) is (1, 0), it is a dry state, and if (1, 1), it is a frozen state. , (0, 1), it means snow or wet conditions. Similarly, the discrimination level B of the comparator 23
is set between the output level of the filter 22 in a dry state and the same output level in a wet state, and when the same output level exceeds this discrimination level B, an output signal "1" is output from the comparator 23. occurs.

Therefore, according to the information from the reflected light signal of visible light,
If the output of the comparator 23 is (1), it means a snowy or dry state, and if it is (0), it means a wet state. Such results are also shown in Table 1. Comparators 13, 14
, 23 are sent to three microprocessors. The microprocessor 30 makes a final determination of the road surface condition based on the road surface condition determination result based on information from infrared light and the road surface condition determination result based on information from visible light. , frozen, wet and snowy 4
classified into types.

The final determination by microprocessor 30 is made based on the combinations in Table 2. Table 2 The combinations in Table 2 are just examples, and by changing the values of the discrimination levels AI, A2, and B of the comparators 13, 14, and 23, the combinations in Table 2 may also be changed.

For example, if discrimination level B is set to filter level 2 in snowy conditions,
Alternatively, another comparator may be provided in addition to the comparator 23 so that the output level of the filter 22 can be set between the output level of the filter 22 and the same output level in the dry state. It can also be divided into three wet states. Furthermore, in Table 2, the combinations of dry and wet and frozen and wet may be treated as errors. As mentioned above, snow jams and black snow conditions are included in snowy or wet conditions based on infrared reflected light signals, so even snow jams and black snow conditions It can be determined to be snowfall in the same way as white snow.

Since the vehicle travels on the road 4, the reflected light from the irradiation area of the projector 3 is blocked each time the vehicle passes through the irradiation area. Generally, the time the vehicle passes through the irradiation area is short, and the time the reflected light is not blocked is longer. Therefore,
A minimum detection time longer than the light blocking time due to the passage of a vehicle is determined, and if the outputs of the comparators 13, 14, and 23 do not change during this minimum detection time, the outputs are treated as regular signals and input to the microprocessor 3. It is preferable to FIG. 4 shows a circuit that performs the same processing as the microprocessor described above.

The outputs of comparators 13, 14, and 23 are sent to a resistor 41. The above-mentioned minimum detection time is set in the timer 44, and is temporarily stored in the register 41 when the outputs of the comparators 13, 14, 23 do not change during this minimum detection time. The signal stored in the register 41 is then sent to the decoder 42.
sent to. There are eight combinations of the outputs of the comparators 13, 14, and 23, two of which are impossible. The decoder 42 outputs signals resulting from the above six combinations and sends them to the OR circuit 43. The OR circuit 43 is this 6
Using the same combinations as shown in Table 2 from the street signals, four types of signals are generated: dry, frozen, wet and snowy. In the above example, the data regarding the reflected infrared light signal has a wavelength of 1.
．． It is obtained from the average value of light in the range of 4 to 2.5 (mountain surface), but as is clear from the graph in Figure 3, the wavelength is 1.6.
Since the difference in reflectivity between water and ice is significant at wavelengths of 2.0 and 2.0 (mountain surfaces), it is more preferable to extract only signals of such wavelengths and use them as data for road surface condition determination. Also,
Although diffusely reflected light from the road surface is received, the road surface condition can also be determined by receiving specularly reflected light whose angle of incidence on the road surface is equal to the angle of reflection. In this case, the magnitude of the output level for each road surface condition will be different from that shown in Table 1. As explained in detail above, this invention detects the frozen state based on the difference in absorption rate of near-infrared light between water and ice. It is possible to accurately detect the frozen state of the road surface.

[Brief explanation of drawings]

Figure 1 is a configuration diagram showing the arrangement of the emitter and receiver;
FIG. 2 is a block diagram of an apparatus for implementing the method according to the present invention, FIG. 3 is a graph showing reflectance characteristics of snow, and FIG. 4 is a block diagram showing another example of a road surface condition determination circuit. 1...Receiver for infrared light, 2...Receiver for visible light, 3
...Floodlight, 4...Road, 13,14
, 23...Comparator, 30...Microprocessor, 42...Decoder, 43...
OR circuit. Figure 1 Figure 2 Figure 3 Figure 4

Claims (1)

[Claims] 1. Using infrared light in a wavelength range where the reflectance of a road surface containing moisture is small enough to be distinguishable from the reflectance of a frozen road surface,
This infrared light is emitted from above the road surface to the road surface, the reflected light from the road surface is received, and this reflected light signal is discriminated using a reference value according to the type of road surface condition to be determined, and the discrimination result is A road surface condition detection method that detects at least a frozen state of a road surface. 2. The road surface condition detection method according to claim 1, wherein the wavelength range of the infrared light is 1.4 (μm) or more. 3. Claim 1, in which the types of road surface conditions to be determined are dry conditions, frozen conditions, and wet or snowy conditions.
The road surface condition detection method described in section. 4 In addition to the above infrared light, visible light reflected from the road surface is discriminated using a reference value according to the type of road surface condition to be discriminated, and the combination of this discrimination result and the above infrared light discrimination result is used to at least The road surface condition detection method according to claim 1, which detects frozen conditions, wet conditions, and snow conditions. 5. Claim 4, wherein the types of road surface conditions to be determined are dry, frozen, wet, and snowy.
The road surface condition detection method described in section.