KR102329413B1 - Method for determining black ice section by analyzing brightness of road surface - Google Patents

Abstract

The present invention relates to a method for determining a black ice section by determining the brightness of a road surface. The method includes: (a) a step in which an image sensor of a camera captures a road surface image and an illuminance sensor of the camera measures an illuminance value of the surroundings; (b) a step of analyzing the pixel value of the image captured by the image sensor and measuring the brightness of a road surface and uniformity based on the illuminance value and the pixel value; (c) a step of determining a state of the road surface and the presence or absence of black ice based on brightness and uniformity values; (d) a step of transmitting black ice information and image sensor location information to an ITS server in a case where it is determined that black ice is present on the road surface; and (e) a step in which the ITS server transmits a black ice warning message to a display terminal on a road near the location of the black ice. The camera is installed at a place where the road can be imaged in whole or in part. The camera communicates with the ITS server by wired or wireless connection.

Description

Method for determining the black ice section by determining the luminance of the road surface {METHOD FOR DETERMINING BLACK ICE SECTION BY ANALYZING BRIGHTNESS OF ROAD SURFACE}

The present invention relates to a method for discriminating a black ice section by discriminating the luminance of a road surface, and more particularly, installing a black ice detection system to deliver black ice generation information to a vehicle traveling in a specific section in advance to ensure a safe section It's about the technology to guide you through.

In addition to the phenomenon of the formation of a thin layer of ice on the road surface due to snow and rain in winter, soot and dust congealed together with snow and rain, and black ice is called 'black ice'.

Black ice often occurs in places with low surface temperatures, such as shady roads, tunnels, mountain corners, and overpasses, and the braking distance on roads where black ice occurs is up to 7 times longer than on general roads. very likely

The existing technology for discriminating black ice detected whether black ice occurred on the road surface through spectral measurement or analysis of road environment information (temperature, humidity, atmospheric pressure, precipitation, etc.).

The existing method requires consideration of various environmental variables, making it difficult to accurately predict the occurrence of black ice.

In recent years, the number of traffic accident injuries and deaths due to domestic road traffic accidents caused by black ice is increasing rapidly.

Freezing on the road surface that the driver is not aware of is much more dangerous than snow and rain conditions.

Since it is common for drivers to decelerate while driving on the road after rain or snowfall, most accidents are minor even if they occur. The risk of causing an accident is high.

In Korea, over the past five years, there have been 6,578 traffic accidents due to road icing, which resulted in approximately 12,000 injuries and 199 deaths. higher

Accordingly, the Ministry of Land, Infrastructure and Transport is reviewing whether it is necessary to designate an additional ice vulnerable section by thoroughly re-investigating the currently designated ice vulnerable section so that an accident caused by black ice does not recur.

As a technical means for achieving the above-described technical problem, the method for determining the black ice section by determining the luminance of the road surface according to an embodiment of the present invention includes: (a) an image sensor of a camera captures a road image, measuring, by the illuminance sensor of the camera, a value of ambient illuminance; (b) analyzing pixel values of images captured by the image sensor, and measuring luminance and uniformity of the road surface based on the illuminance values and pixel values; (c) determining a road surface condition and the presence or absence of black ice based on the luminance and uniformity values; (d) transmitting black ice information and location information of an image sensor to an ITS server when it is determined that there is black ice on the road surface; and (e) transmitting, by the ITS server, a safety phrase guidance message for warning of black ice to a display terminal installed on a road around a place where the black ice is located. Including, the camera may be installed in a place where all or part of the road can be photographed and connected to the ITS server through wired/wireless communication to communicate.

In addition, the step (c) may include: (c-1) calculating pixel values of at least one or more pixels constituting the road surface image; (c-2) a road image pixel value analysis is performed including a distribution of the pixel values, an average value of pixel values, and positions of pixels having a difference greater than or equal to a preset difference from the average value, the illuminance value, and the road image pixel calculating a luminance value of a road surface, an overall uniformity value, and a lane axis uniformity value by referring to a result of the value analysis and comparing it with a preset table; (c-3) determining whether the road surface is in a dry or wet state and whether black ice is present on the road surface based on the luminance value, the overall uniformity value, and the lane axis uniformity value; and , in the preset table, a plurality of data pairs for the illuminance value, the luminance value, the overall uniformity value, and the lane axis uniformity value are specified according to the wet or dry road surface and the state in which black ice is present, ), and may be to additionally store black ice determination thresholds for the luminance value, the overall uniformity value, and the lane axis uniformity value.

In addition, in the step (c-3), the average value of the pixel values measured in the dry road surface environment stored in the preset table, the luminance value of the road surface, the total uniformity value, and the lane axis uniformity value are within a predetermined range from the (c-) determining the state of the road surface as a dry state when the average value of the pixel values calculated in step 2), the luminance value of the road surface, the overall uniformity value, and the lane axis uniformity value are included; and the average value of the pixel values calculated in step (c-2) within a predetermined range from the average value of the pixel values in the wet road environment stored in the preset table, the luminance value of the road, the overall uniformity value, and the lane axis uniformity value, and determining that the road surface is a wet state when the luminance value of the road surface, the overall uniformity value, and the lane axis uniformity value are included.

Also, in the step (c), a distribution map is derived for where candidate pixels having a value greater than or equal to a preset difference from the average value of the pixel values in the road surface image are located, and among the positions of the candidate pixels on the distribution map, the candidate pixels are By extracting a dense location, comparing the pixel values of candidate pixels at the location with a preset threshold, determining whether black ice exists at the location, and comparing the angle with the location at which the camera illuminates the road surface, on the road surface and determining whether the black ice is located on the left/center/right side of the vehicle driving direction, wherein the step (e) includes: when information on black ice is received from the camera, the road surface on which the black ice is located and transmitting a black ice safety phrase guide message to at least one display terminal located in an order close to the camera from a direction opposite to the driving direction of the vehicle to be displayed on the display terminal.

In addition, in step (c), the camera receives information on the presence or absence of black ice from a vehicle traveling on the road surface, and in step (e), the presence or absence of black ice acquired from the camera through the image sensor When both the information on the vehicle and the information on the presence or absence of black ice acquired from the vehicle indicate 'the presence of black ice', the black ice information and the location information of the image sensor are transmitted to the ITS server, and the vehicle is driven on the road surface. The process in which the camera receives information on the presence or absence of black ice from a vehicle that The friction coefficient between the vehicle and the road surface is calculated using the force in the vertical direction and the force in the lateral direction for each wheel, and the condition of the road surface is calculated using the calculated slip ratio and friction coefficient and a preset road surface condition graph. is wet/ice/dry/snow in any one state, and after irradiating infrared light based on the infrared sensor installed in the rear direction of the vehicle, and determining whether the reflectance of light reflected from the road surface is below a threshold value, , when the condition of the road surface indicates ice and the reflectance is equal to or less than a threshold value, it may be determined that black ice is present on the road surface.

The present invention is to solve the problems of the prior art, and proposes a system for discriminating a black ice section by discriminating luminance.

By installing a black ice detection system in overpasses, bridges, and mountainous areas with high winter humidity, where there is a high risk of black ice, information on the occurrence of black ice is transmitted to vehicles entering the section in advance to induce them to safely pass the section at low speed. can

According to the U.S. Traffic Survey Report, research results have been reported that when there is a warning of a danger ahead, about 80% of accidents that actually happen to drivers can be prevented.

Accordingly, it is possible to prevent human accidents due to black ice in advance through the system for discriminating the black ice section by determining the luminance.

In addition, it is possible to secure the convenience and accuracy of black ice-related measurements.

The existing black ice identification method is to estimate the occurrence of black ice by directly grasping the friction coefficient and road surface temperature based on contact with the road surface or external environmental information (temperature, humidity, wind speed, etc.), which is technically difficult to implement and maintain. there was

On the other hand, the method of detecting black ice by analyzing the luminance of the road surface is a method that does not directly contact the road surface. It is a system that is far superior to the technology of

1 is a structural diagram of a system of a method for discriminating a black ice section by discriminating the luminance of a road surface according to an embodiment of the present invention.
2 is a block diagram showing the internal configuration of a server, according to an embodiment of the present invention.
3 is a block diagram illustrating an internal configuration of a camera according to an embodiment of the present invention.
4 is an exemplary diagram of a road lighting luminance reference table according to an embodiment of the present invention.
5 is an exemplary diagram of a black ice determination criterion table according to an embodiment of the present invention.
6 is an operation flowchart of a method of discriminating a black ice section by discriminating the luminance of a road surface according to an embodiment of the present invention.
7 is a block diagram illustrating the configuration of a road surface condition measurement system according to an embodiment of the present invention.
8 is an operation flowchart of measuring the state of the road surface through the slip rate according to an embodiment of the present invention.
9 is a graph table relating to a slip rate and a friction coefficient of a vehicle for each road surface condition according to an embodiment of the present invention.
10 is an operation flowchart of a road surface condition measurement system according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement them. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. . In addition, when a part "includes" a certain component, this means that other components may be further included, rather than excluding other components, unless otherwise stated.

In this specification, a "part" includes a unit realized by hardware, a unit realized by software, and a unit realized using both. In addition, one unit may be implemented using two or more hardware, and two or more units may be implemented by one hardware. Meanwhile, '~ unit' is not limited to software or hardware, and '~ unit' may be configured to be in an addressable storage medium or may be configured to reproduce one or more processors. Thus, as an example, '~' denotes components such as software components, object-oriented software components, class components, and task components, and processes, functions, properties, and procedures. , subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. The functions provided in the components and '~ units' may be combined into a smaller number of components and '~ units' or further separated into additional components and '~ units'. In addition, components and '~ units' may be implemented to play one or more CPUs in a device or secure multimedia card.

The "user terminal" referred to below may be implemented as a computer or portable terminal that can access a server or other terminal through a network. Here, the computer is, for example, a laptop, desktop, laptop, VR HMD (eg, HTC VIVE, Oculus Rift, GearVR, DayDream, PSVR, etc.) equipped with a web browser (WEB Browser), etc. may include. Here, VR HMD is for PC (eg, HTC VIVE, Oculus Rift, FOVE, Deepon, etc.), for mobile (eg, GearVR, DayDream, Storm Horse, Google Cardboard, etc.) Independently implemented Stand Alone models (eg Deepon, PICO, etc.) are included. A portable terminal is, for example, a wireless communication device that guarantees portability and mobility, and includes not only a smart phone, a tablet PC, a wearable device, but also Bluetooth (BLE, Bluetooth Low Energy), NFC, RFID, and ultrasound (Ultrasonic). , infrared, Wi-Fi, Li-Fi, etc. may include various devices equipped with a communication module. In addition, the "network" refers to a connection structure capable of exchanging information between each node, such as terminals and servers, and includes a local area network (LAN), a wide area network (WAN), and the Internet. (WWW: World Wide Web), wired and wireless data networks, telephone networks, wired and wireless television networks, and the like. Examples of wireless data communication networks include 3G, 4G, 5G, 3rd Generation Partnership Project (3GPP), Long Term Evolution (LTE), World Interoperability for Microwave Access (WIMAX), Wi-Fi, Bluetooth communication, infrared communication, ultrasound Communication, Visible Light Communication (VLC), LiFi, etc. are included, but are not limited thereto.

The present invention relates to a method for discriminating a black ice section by determining the luminance of a road surface. It is a technology for providing information on black ice to a user terminal through the ITS server 400 .

Referring to FIG. 1 , a system of a method for determining a black ice section by determining the luminance of a road surface according to an embodiment of the present invention is a road surface 100 , a camera 200 , a lighting device 300 , and an ITS server 400 . ) may be included.

Here, the road surface 100 refers to a surface of a road on which a vehicle or a passenger vehicle on which a person rides travels, and may include lanes for dividing driving directions.

The camera 200 is installed in a place where all or part of the road can be photographed, and can communicate with the ITS server 400 by wire/wireless communication. can be collected.

A camera according to an embodiment of the present invention may include a memory in which a program (or application) for performing a method of determining a black ice section by determining the luminance of a road surface is stored and a processor executing the above program.

In addition, it may be configured to include an image sensor 210 and an illuminance sensor 220 . Here, the processor may perform various functions according to the execution of the program stored in the memory, and detailed components included in the processor may be represented by the luminance measuring unit 230 and the black ice determining unit 240 according to each function.

The lighting device 300 may be installed at a location adjacent to the road surface 100 , and may perform a role of providing a field of view necessary for the road by scanning visible light or infrared rays on the road surface 100 .

When the lighting device 300 installed on the road illuminates the road surface 100 , an appropriate luminance of the road surface 100 may be maintained and the luminance distribution may be uniform.

The light generated from the lighting device 300 includes the road surface luminance (the luminance generated by the road surface reflecting the light flux from the lighting device 300, cd/m2), and the overall uniformity (the ratio of the luminance indicating the uniformity of the road surface luminance distribution). and lane axis equalization (ratio of luminance indicating the uniformity of the visible brightness distribution on the front road surface).

In addition, the lighting device 300 may be divided into a plurality of grades in relation to performance. According to each grade, the luminance standard can be provided separately as average road surface luminance on dry road surface, overall uniformity system, lane axis uniformity system, and comprehensive uniformity system on wet road surface. As a result, the uniformity is reduced, so it can be measured significantly lower than on a dry road surface.

The ITS server 400 may receive information on black ice from the camera 200 and transmit a safety phrase guidance message for warning of black ice to a display terminal installed on a road around a place where the I black ice is located.

In summary, the lighting device 300 acts as a light source on the road surface 100, and the camera 200 captures and analyzes the road surface image and provides it to the ITS server 400 according to the analysis result to determine the black ice section of the road surface. will do

2 is a structural diagram of a server according to an embodiment of the present invention. In this case, the server referred to in this specification may include an ITS server according to an embodiment of the present invention, and may be composed of a DB (DataBase), a processor, a communication module, and a memory.

Referring to FIG. 3 , a camera 200 according to an embodiment of the present invention will be described. The camera 200 may include an image sensor 210 , an illuminance sensor 220 , a luminance measurement unit 230 , and a black ice determination unit 240 .

The image sensor 210 may provide a road surface image obtained by photographing the road surface 100 to the luminance measuring unit 230 .

A road image is a collection of many tiles, and may be composed of square pixels like a mosaic picture, and an image may be formed by combining these pixels.

The image sensor 120 may acquire an image of the road surface 100 using a CCD (Charge Coupled Device) method and a CMOS (Complimentary Metal Oxide Semiconductor) method.

Since the technologies related to CCD and CMOS are prior art, they are not described in detail herein.

The illuminance sensor 220 may measure the illuminance of the surrounding environment in which the camera 200 is installed, and may provide the measured illuminance to the luminance measuring unit 230 .

In this case, the illuminance according to an embodiment of the present invention is a value representing the intensity of light received by a certain surface, and may be calculated at a luminous speed reaching a unit area.

Meanwhile, the luminance measuring unit 230 may perform an operation of measuring the luminance and uniformity of the road surface based on the illuminance value and the pixel value.

To describe this process in detail, the luminance measuring unit 230 measures the illuminance value for the surrounding environment from the illuminance sensor 220 , and the average of pixels from each pixel constituting the road image provided from the image sensor 210 . get the value

In this case, the acquisition of the average value of the pixel may be obtained by performing pixel value analysis of the road surface image including the distribution of pixel values, the average value of the pixel values, and positions of pixels having a difference greater than or equal to a preset difference from the average value. Specifically, the yellow or white route and the road surface part on which the vehicle travels can be distinguished through the overall average value of pixel values and the distribution of each pixel value in the road surface image, and when it is determined that pixels having a difference greater than or equal to a preset difference exist in the road surface part It can be determined that a suspicious object presumed to be black ice is located on the road surface.

Thereafter, the luminance measuring unit 230 refers to the results of the analysis of the illuminance value for the surrounding environment and the road image pixel value, compares it with a preset table, and compares the luminance value of the road surface, the overall uniformity value, and the lane according to a preset algorithm or formula. The axis uniformity value may be calculated and provided to the black ice determination unit 240 . The preset table will be described in detail below.

Referring to FIG. 4 , the preset table contains data pairs for the illuminance value, the luminance value, the overall uniformity value, and the lane axis uniformity value, depending on the grade of the lighting device 300, in which the road surface is wet or dry and black ice is present. A plurality may be defined according to the state, and may be preset prior to the implementation of the present invention.

In addition, a threshold value serving as a criterion for judging black ice with respect to the luminance value, the overall uniformity value, and the lane axis uniformity value in the table may be additionally stored.

In addition, when comparing the amount of light in the surrounding environment, when black ice is present, pixel values of an image photographed through a camera and luminance values measured through a luminance meter may be established as a table in advance through an experiment. In addition, when black ice does not exist, pixel values of an image photographed by a camera and a luminance value measured by a luminance meter may be established as a table in advance through an experiment. This can be established as a table in advance through experimentation. In this case, the table has fields of the illuminance value, the average value of the pixel values of the photographed image, and the luminance value, and has different field values when black ice is present and when it does not exist.

When this table is combined with the table of FIG. 4 described above, a table as shown in FIG. 5 can be secured.

That is, referring to FIG. 5 , even if only the average value of the illuminance value for the surrounding environment and the pixel value of the photographed image is known, the luminance value, the total uniformity value, and the lane axis uniformity value can be known. can determine whether or not

Specifically, the black ice determining unit 240 determines whether the road surface in the photographed image is in a dry or wet state based on the luminance value, the comprehensive uniformity value, and the lane axis uniformity value provided from the luminance measurement unit 240 . operation and determining whether black ice is present on the road surface.

The average value of the pixel values calculated by the luminance measurement unit 230 within a predetermined range from the average value of the pixel values measured in a dry road surface environment stored in a preset table, the luminance value of the road surface, the total uniformity value, and the lane axis uniformity value, the average value of the pixel values, the road surface When the luminance value, the overall uniformity value, and the lane axis uniformity value are included, it may be determined whether the road surface is dry and black ice is present.

In a similar manner, the average value of the pixel values calculated by the luminance measuring unit 230 within a predetermined range from the average value of the pixel values in the wet road environment stored in the preset table, the luminance value of the road surface, the total uniformity value, and the lane axis uniformity value. , when the luminance value of the road surface, the overall uniformity value, and the lane axis uniformity value are included, it may be determined whether the state of the road surface is wet and black ice is present.

For example, it is assumed that the currently captured image has luminance value, total uniformity value, and lane axis uniformity value of 13.1, 0.42, and 0.59, respectively.

Referring to FIG. 5 , the black ice determination unit 240 may search a preset table and determine from which table values 13.1, 0.42, and 0.59 fall within a preset range. Next, the black ice determination unit 240 determines that the luminance value, the overall uniformity value, and the lane axis uniformity value are 13.4, 0.43, and 0.61, respectively, when black ice is present and a dry road surface is present.

In this case, it is possible to determine that the value of the analysis result of the currently photographed image is similar to the value when the black ice is present and the road surface is dry, and the road surface condition can be determined as the dry condition.

Next, an operation of determining whether black ice is present at any position on the road surface will be described. A pixel having a value greater than or equal to a significant difference from an average value of pixel values in a road image captured by the camera 200 is set as a candidate pixel. For example, due to the influence of luminance, the pixel value of the black ice portion may represent a value greater than or equal to a predetermined difference from other portions on the road surface.

By deriving a distribution map for a location where candidate pixels are located, extracting a location where candidate pixels are dense from among locations of candidate pixels on the distribution map, and comparing the pixel value of the candidate pixels at the location with a preset threshold, the black at the location It is possible to determine whether ice is present. For example, since black ice of a very small size does not have a significant effect on driving, it is necessary to detect black ice having a certain size. Therefore, by detecting the part where candidate pixels are dense and comparing it with a threshold defined as an average value of pixel values per unit sub-pixel (9 X 9 pixels) of the candidate pixels, if it is higher than the threshold, black ice is located. can judge

In addition, by comparing the angle at which the camera 200 illuminates the road surface 100 and the corresponding position, it is possible to determine whether the black ice is located on the road surface in the left/center/right side of the vehicle driving direction. For example, assuming that the camera shoots only one route, if a black ice suspicious part is found on the left side of the image taken by the camera, if the camera is shooting in the direction facing the vehicle, enter the vehicle The black ice is located on the right.

Accordingly, when the safety phrase guidance message is transmitted to the display terminal, it can be implemented to include black ice location information in the message.

For example, it is assumed that the currently captured image has luminance value, total uniformity value, and lane axis uniformity value of 9.9, 0.13, and 0.61, respectively.

Referring to FIG. 5 , the black ice determination unit 240 searches a preset table to set the luminance value, the overall uniformity value, and the lane axis uniformity value of 10.0, 0.11, and 0.59 when there is no black ice and the wet road surface is 10.0, 0.11, and 0.59, respectively. figure out what

As a result of analyzing the currently photographed image, it is determined that the value is similar to the value when there is no black ice and there is no black ice, and it can be determined that the condition of the road surface is wet and there is no black ice.

If the camera 200 determines that black ice is present on the road surface 100 through the process described above, the camera transmits the coordinates of the area where the camera 200 is installed to the ITS server 400 .

When the ITS server 400 receives information on black ice from the camera 200, the black ice is transmitted to a plurality of display terminals located in the order close to the place where the camera 200 is installed from the direction opposite to the driving direction of the road surface on which the black ice is located. An ice safety phrase guide message can be transmitted to be displayed on the display terminal.

Among the above-described processes, the process of determining the black ice on the road surface and the process of transmitting the black ice safety phrase guide message through the ITS server 400 may be performed in connection with the vehicle driving on the road surface. It will be described in more detail below.

The camera 200 receives information on the presence or absence of black ice from a vehicle traveling on the road surface 100 , and information on the presence or absence of black ice acquired from the camera 200 through the image sensor 210 and the vehicle When all of the information on the presence or absence of black ice acquired from the server indicates 'the presence of black ice', the black ice information and the location information of the image sensor may be transmitted to the ITS server 400 .

In this case, the process in which the camera receives information on whether black ice exists from the vehicle traveling on the road surface 100 may be performed by the vehicle controller.

The vehicle controller calculates the slip rate for each wheel of the vehicle using the vehicle traveling speed and the wheel speed, and uses the vertical and lateral forces for each wheel to provide friction between the vehicle and the road surface. Calculate the coefficients.

Thereafter, it is determined whether the state of the road surface is any one of wet/ice/dry/snow by using the calculated slip rate and friction coefficient and a preset road surface condition graph.

In addition, after irradiating infrared light based on the infrared sensor installed in the rear direction of the vehicle, it is determined whether the reflectance of the light reflected from the road surface is below a threshold value, the state of the road surface 100 corresponds to ice, and the reflectance is the threshold value In the following cases, it may be determined that black ice is present on the road surface.

With reference to FIG. 6 , an operation sequence of a method of determining a black ice section by determining the luminance of a road surface according to an embodiment of the present invention will be described below.

The camera 200 photographs the road surface 100 and measures the luminance and uniformity of the road surface 100 (S101).

Thereafter, it is determined whether there is a road surface condition and black ice (S102).

At this time, when it is determined that there is black ice on the road surface, the corresponding information is transmitted to the ITS server 400 (S103).

The ITS server 400 transmits a black ice caution phrase guide message to a display terminal around the place where the black ice is located (S104).

Hereinafter, as a further embodiment, the controller of the vehicle calculates a slip ratio for each wheel of the vehicle using the traveling speed and wheel speed of the vehicle, and a force in a vertical direction and a lateral force for each of the wheels After calculating the friction coefficient between the vehicle and the road surface using the force of An embodiment of providing information related to black ice to the camera 200 will be described in detail.

7 is a view for explaining an apparatus for measuring a road surface condition installed in a vehicle according to an embodiment of the present invention.

Referring to FIG. 7 , the apparatus for measuring a road surface condition according to the present invention includes a sensor unit 500 , a road surface condition determination unit 510 , and a black ice detection unit 520 .

The sensor unit 500 includes at least one optical sensor, and the optical sensor may be an infrared sensor or a visible light sensor. Such an optical sensor irradiates light of a specific wavelength to the road surface and receives light reflected from the road surface. The sensor unit 500 may be installed in the front or rear of the vehicle, and irradiates light to the road surface 100 in the front direction or the road surface 100 in the rear direction of the vehicle.

Returning to FIG. 7 , the road surface condition determination unit 510 determines the road surface condition according to the reflectance of light reflected from the road surface. As an embodiment, the road surface condition determination unit 510 may determine the road surface condition as one of dry, wet, snow, and ice.

When it is determined that the road surface condition is frozen, the black ice detection unit 520 detects black ice on the road surface. Black ice is ice formed very thinly on the road surface, and is formed by melting and re-freezing snow or ice in the road. In the case of black ice, since the color of black asphalt is reflected as it is and appears black, it exhibits different optical properties from ice formed by freezing. Since black ice shows the color of asphalt as it is, the reflectance of light to black ice is very low compared to the reflectance of light to ice formed by freezing.

The black ice detector 520 detects black ice using the difference in optical characteristics, and as an example, compares the reflectance of infrared light with a threshold value to detect black ice.

An apparatus for measuring a road surface condition according to an embodiment of the present invention includes a slip rate calculation unit and a road surface condition determination unit.

The slip ratio calculator calculates a slip ratio for each wheel of the vehicle by using the driving speed and the wheel speed of the vehicle. As an example, the traveling speed of the vehicle may be measured using a GPS device or an inertial sensor mounted on the vehicle, and the wheel speed may be measured through a wheel speed sensor.

When the vehicle slip occurs, a difference occurs between the traveling speed and the wheel speed, and the slip ratio may be calculated according to the magnitude of the difference.

The road surface condition determination unit determines the road surface condition by using a friction coefficient between the vehicle and the road surface according to the slip rate calculated by the slip rate calculation unit. The friction coefficient is also calculated for each wheel of the vehicle, and may be calculated according to the force in the vertical direction and the force in the lateral direction for each wheel. Since the friction coefficient according to the slip rate is different according to the condition of the road surface, the road surface condition determination unit 320 may determine the condition of the road surface by using the friction coefficient according to the slip rate of the vehicle.

Meanwhile, the components of the road surface condition measuring apparatus described above in FIG. 7 and above may be variously combined according to embodiments. For example, the road surface condition measuring apparatus may further include a black ice detector, or the road surface condition measuring apparatus of FIG. 7 may determine the road surface condition by additionally calculating the slip rate of the vehicle.

The method for measuring a road surface condition according to the present invention may be performed in the ECU of a vehicle equipped with the above-described road surface condition measurement apparatus or sensor, and below, the road surface condition measurement method performed by the road surface condition measurement apparatus will be described as an embodiment. .

The road surface condition measuring apparatus according to the present invention determines whether the road surface on which the vehicle travels is icy, and when the road surface is icy, detects black ice on the road surface by using an infrared sensor installed in the vehicle.

In the step of determining whether the road surface on which the vehicle is traveling is icy, the road surface condition measuring apparatus may measure the road surface condition according to a slip rate of each of an optical sensor of the vehicle or each wheel of the vehicle, and determine whether the road surface is frozen. When the road surface condition measurement device determines the road surface condition using the vehicle's optical sensor, it irradiates a preset wavelength of visible light or infrared light to the road surface, and determines whether the road surface is icing according to the reflectance of the light reflected from the road surface can do.

When snow is piled up on the road surface, the reflectance of light reflected from the road surface may be greatest, and when the road surface is dry, the reflectance of light reflected from the road surface may be the smallest. In addition, when the road surface is in a wet or frozen state, the reflectance of light reflected from the road surface may be located between the reflectance of the snow-covered state and the dry state. Accordingly, the road surface condition measuring apparatus may determine the road surface condition as one of dry, wet, snowy, and icy according to the reflectance of light reflected from the road surface.

At this time, when the road surface is wet or frozen, the reflectance of light reflected from the road surface may be similar to each other. It makes a difference. In addition, it can be seen that the difference in absorption rates between water and ice is large for light having a wavelength longer or shorter by a predetermined size based on a wavelength of 2.15 μm in the infrared band.

As the difference in absorption is large, there is also a difference in reflectance. Therefore, when the road surface condition measuring device uses a visible light sensor, by irradiating visible light in a wavelength band of 0.4㎛ ~ 0.6㎛ and measuring the reflectance of the irradiated light, the road surface is wet It can be determined whether it is or is frozen. Alternatively, when an infrared sensor is used, the road surface condition measuring device may determine whether the road surface is wet or frozen by irradiating infrared light having a wavelength of 2.055 μm or 2.3 μm and measuring the reflectance of the irradiated light.

When the road surface condition measurement device determines whether the road surface is icy according to the slip rate, the slip rate is highly likely to be the maximum when the road surface is icy. Based on the friction coefficient, it is possible to determine whether the road surface is icy. A detailed method of determining the road surface condition according to the slip rate of the vehicle wheel will be described in detail with reference to FIG. 8 .

In the step of detecting black ice on the road surface using the infrared sensor, the road surface condition measurement device irradiates infrared light to the road surface, and when the reflectance of the light reflected from the road surface is less than a threshold value, it is determined that black ice is present on the road surface. can

Since the infrared image of general ice contains relatively much white color and the infrared image of black ice contains relatively much black color, the reflectance of infrared light on black ice is the reflectance of infrared light on ice on the road surface. lower than The road surface condition measuring apparatus determines that black ice is present on the road surface when the reflectance of infrared light with respect to the road surface is lower than a threshold value.

Because detecting the black ice and judging the road surface condition for the vehicle's next location rather than the vehicle's current location is helpful for safe driving, the road condition measuring device can be designed to irradiate visible or infrared light in the forward direction of the vehicle. can

After all, according to the present invention, since black ice that causes a fatal safety accident can be detected, it is possible to reduce the accident rate due to black ice and promote safe driving of the driver.

8 is a view for explaining a method for measuring a road surface condition according to another embodiment of the present invention, and FIG. 9 is a graph illustrating a relationship between a slip rate and a friction coefficient of a vehicle according to a road surface condition.

The road surface condition measuring apparatus according to the present invention calculates the slip ratio for each wheel of the vehicle using the driving speed and the wheel speed of the vehicle (S201), and uses the friction coefficient between the vehicle and the road surface according to the slip ratio. , the state of the road surface is determined (S202).

In step S201, the road surface condition measuring device may calculate the slip ratio for each wheel of the vehicle by using the difference between the driving speed of the vehicle and the wheel speed, and calculate the slip ratio using [Equation 1] as an embodiment. can When slip occurs due to a slippery road surface, the difference between the driving speed and the wheel speed increases, and thus the slip ratio may be calculated according to the difference between the driving speed and the wheel speed.

Equation 1

In step S202, the road surface condition measuring apparatus may determine the road surface condition by using a friction coefficient according to the maximum slip rate among the slip rates for each wheel.

)는 [수학식 2]와 같이 계산될 수 있다. 여기서,

는 휠에 대한 횡방향의 힘(lateral force)을 나타내며,

는 휠에 대한 수직 방향의 힘(normal force)을 나타낸다.At this time, the coefficient of friction for each wheel (

) can be calculated as in [Equation 2]. here,

is the lateral force on the wheel,

denotes the normal force on the wheel.

Equation 2

The lateral force on the wheel can be calculated from the yaw rate value, wheel speed value, and steering angle of the vehicle inertial sensor, and the vertical force on the wheel is the roll rate of the vehicle inertial sensor. It can be calculated using values, longitudinal and lateral accelerations of the vehicle, and displacement values of the suspension.

As shown in the road surface condition graph shown in FIG. 9 , since the friction coefficient according to the slip rate is different depending on the road surface condition of the vehicle, the condition of the road surface on which the vehicle travels can be determined through the relationship between the slip rate and the friction coefficient. . For example, if the friction coefficient for the wheel having the maximum slip ratio of 0.5 is calculated to be 0.2, the road surface condition measuring apparatus may determine the road surface condition as icing.

If it is determined in step S202 that the road surface is frozen, the road surface condition measuring apparatus may detect black ice on the road surface using an infrared sensor as described in FIG. 7 .

At this time, since black ice is detected through the infrared sensor after it is first determined whether the condition of the road surface is frozen through the wheel sensor, the road surface condition measurement device is determined to be frozen by irradiating infrared light toward the rear of the vehicle. It can detect the presence of black ice on the road surface.

As a further embodiment, the road surface condition measurement apparatus may supplement the road surface condition measurement result through a machine learning classification model.

Specifically, before step S201, a classification model for extracting road surface condition information may be previously built in the road surface condition measurement device or may be connected to a cloud server including the classification model. The ITS server 400 may collect a vast amount of wheel state information from vehicles traveling within a specific area. The wheel state information may include an acceleration signal for the wheel, a geomagnetic signal, an air pressure signal, a temperature signal, and a gyroscope sensing signal. Thereafter, when the collected wheel state information is input through a preset artificial neural network model, it is possible to learn to output one of the road surface state information classified according to a preset criterion. The road surface condition classification criterion may be, for example, ICE/SNOW/WET/DRY, but is not limited thereto. The artificial neural network applied here is not limited in its composition such as DNN (Deep Neural Network), RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), etc., but CNN (Convolution Neural Network) is adopted according to the characteristics of the input value. This is desirable to avoid learning speed and overfitting problems. For example, since a tire has characteristics of deformation or air pressure change at the moment it comes into contact with the ground and falls, such characteristics can be extracted first and set as an input value. In this way, when the CNN model is applied, since it does not require wheel state information for all time periods, the layers of the artificial neural network can be reduced, and accordingly, it can be designed relatively simply to reduce errors and reduce learning speed and road surface conditions. The extraction rate can be improved.

That is, by determining whether the road surface condition value extracted through the road surface condition graph of FIG. 9 matches the road surface condition value extracted through the aforementioned artificial intelligence classification model, the accuracy of estimating the road surface condition can be further improved. When the two road surface condition values match, it may be determined as the corresponding road surface condition value.

10 is a view for explaining a method for measuring a road surface condition according to another embodiment of the present invention.

The road surface condition measuring apparatus according to the present invention irradiates visible light to the road surface and measures the reflectance of the light reflected from the road surface (S301) to determine the road surface condition. Then, infrared light is irradiated to the road surface and the reflectance of the light reflected from the road surface is measured to determine the road surface condition (S302).

In this case, the road surface condition measuring apparatus may calculate the slip ratio for each wheel of the vehicle and use the slip ratio and the friction coefficient together to determine the road surface condition.

The road surface condition measuring apparatus determines whether the road surface condition is icy (S302), and when the road surface is frozen, determines whether black ice is present on the road surface using the reflectance of infrared light (S303).

When it is determined that black ice exists on the road surface, the road surface condition measurement device compiles information indicating that black ice exists at the location where the road surface condition is measured (S304), and a nearby camera 200 or ITS server 400 ) to transmit information about the existence of black ice.

Thereafter, the camera 200 sends the black ice information to the ITS server when both the information on the presence of black ice acquired through the image sensor and the information on the presence or absence of black ice acquired from the vehicle indicate 'the presence of black ice'. and location information of the image sensor. Then, as described above, the ITS server may provide a location where the black ice is present by transmitting a safety phrase message to the display terminal.

An embodiment of the present invention may also be implemented in the form of a recording medium including instructions executable by a computer, such as a program module executed by a computer. Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. Also, computer-readable media may include all computer storage media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

Although the methods and systems of the present invention have been described with reference to specific embodiments, some or all of their components or operations may be implemented using a computer system having a general purpose hardware architecture.

The above description of the present invention is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a dispersed form, and likewise components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the above detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention. do.

100: road surface 200: camera
210: image sensor 220: illuminance sensor
230: luminance measuring unit 240: black ice determining unit
300: lighting device 400: ITS server
500: sensor unit 510: road surface condition determination unit
520: black ice detection unit

Claims (5)

A method for determining a black ice section by determining the luminance of a road surface, the method comprising:
(a) photographing a road image by an image sensor of a camera, and measuring an ambient illuminance value by an illuminance sensor of the camera;
(b) analyzing pixel values of the image captured by the image sensor, and measuring the luminance and uniformity of the road surface based on the illuminance value and the pixel value;
(c) determining a road surface condition and the presence or absence of black ice based on the luminance and uniformity values;
(d) transmitting black ice information and location information of an image sensor to an ITS server when it is determined that there is black ice on the road surface; and
(e) transmitting, by the ITS server, a safety phrase warning message for black ice to a display terminal installed on a road around a place where the black ice is located; including,
The camera is installed in a place where all or part of the road can be photographed and communicates with the ITS server through wired/wireless communication,
Step (c) is,
(c-1) calculating pixel values of at least one or more pixels constituting the road surface image;
(c-2) a road image pixel value analysis is performed including a distribution of the pixel values, an average value of pixel values, and positions of pixels having a difference greater than or equal to a preset difference from the average value, the illuminance value, and the road image pixel calculating a luminance value of a road surface, a comprehensive uniformity value, and a lane axis uniformity value by referring to a result of the value analysis and comparing it with a preset table;
(c-3) determining whether the road surface is in a dry or wet state and whether black ice is present on the road surface based on the luminance value, the overall uniformity value, and the lane axis uniformity value; and ,
In the preset table, a plurality of data pairs for the illuminance value, the luminance value, the overall uniformity value, and the lane axis uniformity value are defined according to the wet or dry state of the road surface and the state in which black ice is present, and (a) A method of determining a black ice section by determining the luminance of a road surface, which is preset before the step and additionally stores black ice determination thresholds for the luminance value, the overall uniformity value, and the lane axis uniformity value . delete According to claim 1,
The step (c-3) is,
The average value of the pixel values calculated in step (c-2) within a predetermined range from the average value of the pixel values measured in the dry road surface environment stored in the preset table, the luminance value of the road surface, the total uniformity value, and the lane axis uniformity value; determining the state of the road surface as a dry state when the luminance value of the road surface, the overall uniformity value, and the lane axis uniformity value are included; and
The average value of the pixel values calculated in step (c-2) within a predetermined range from the average value of the pixel values in the wet road environment stored in the preset table, the luminance value of the road, the overall uniformity value and the lane axis uniformity value, the A method of discriminating a black ice section by determining the luminance of a road surface, comprising: determining the state of the road surface as a wet state when the luminance value of the road surface, the overall uniformity value, and the lane axis uniformity value are included. According to claim 1,
The step (c) is,
A distribution map is derived for a location where candidate pixels having a value greater than or equal to a preset difference from the average value of the pixel values in the road surface image are located, and a location where candidate pixels are dense from among the locations of the candidate pixels on the distribution map is extracted, By comparing the pixel value of the candidate pixels with a preset threshold, it is determined whether black ice exists at the corresponding position, and by comparing the angle at which the camera illuminates the road surface with the corresponding position, black ice on the road surface is located to the left of the vehicle driving direction, Including the step of determining which position is located in the center, and on the right side,
Step (e) is,
When information on black ice is received from the camera, a black ice safety phrase guide message is transmitted and displayed to at least one display terminal located in the order close to the camera from the opposite direction to the driving direction of the road surface on which the black ice is located. A method of determining a black ice section by determining the luminance of a road surface, comprising: displaying on a terminal; . 5. The method of claim 4,
The step (c) is,
The camera receives information on the presence or absence of black ice from a vehicle traveling on the road,
In step (e), when both the information on the presence or absence of black ice acquired from the camera through the image sensor and the information on the presence or absence of black ice acquired from the vehicle indicate 'the presence of black ice', the ITS Transmitting the black ice information and the location information of the image sensor to the server,
The process of receiving, by the camera, information on the presence or absence of black ice from the vehicle traveling on the road surface,
The controller of the vehicle calculates a slip rate for each wheel of the vehicle using the traveling speed and wheel speed of the vehicle, and uses the vertical force and the lateral force for each of the wheels to communicate with the vehicle Calculate the coefficient of friction between the road surfaces, and determine whether the state of the road surface is any one of wet/ice/dry/snow by using the calculated slip ratio and friction coefficient and a preset road surface condition graph,
After irradiating infrared light based on the infrared sensor installed in the rear direction of the vehicle, it is determined whether the reflectance of light reflected from the road surface is less than or equal to a threshold value,
and determining that black ice is present on the road surface when the condition of the road surface indicates ice and the reflectance is less than or equal to a threshold value.

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