Vehicle road surface condition determination device

Abstract

To provide a road surface state determination device for a vehicle, which can accurately determine a state of a road surface in front in a traveling direction without erroneous determination while suppressing a device cost.SOLUTION: In a vehicle control device, a road surface state determination device mounted on a vehicle includes one or more processors and one or more memories communicably connected to the one or more processors, and the road surface state determination device determines a state of a road surface in a non-contact manner. The processors use a light source emitting each of three near-infrared lights having respective wavelengths different from one another to irradiate the road surface with the three near-infrared lights and perform primary determination as to whether or not a type of the road surface is a snow accumulated state in precedence over other types and then perform secondary determination as to which one of the other types the type of the road surface is on the basis of the three near-infrared lights reflected by the road surface and received by a light reception sensor.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a road surface condition determination device capable of determining the condition of a road surface on which a vehicle is traveling in a non-contact manner. [Background technology]

[0002] Vehicles are a convenient means of transportation, and for example, people can drive cars to various places. In order to further improve driving safety, it is important to accurately determine the road surface conditions in the direction of travel of the vehicle.

[0003] For example, Patent Document 1 proposes a technology in which near-infrared light of at least three wavelengths, namely a wavelength that is poorly absorbed by both water and ice, a wavelength that is poorly absorbed by ice but easily absorbed by water, and a wavelength that is absorbed to the same extent by both water and ice, is irradiated from a light source 2 onto an object, and the light reflected by the object from the irradiated near-infrared light of each wavelength is detected, and the amount of reflected light detected is calculated and processed to determine the road surface condition. Furthermore, for example, Patent Document 2 proposes a technology in which a bandpass filter is provided to correspond to light in a plurality of different specific wavelength bands, and the road surface condition is determined to be either dry, wet, with a water film, frozen, or snow-covered based on the output value obtained by irradiating the light in the plurality of specific wavelength bands. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-046936 [Patent Document 2] Japanese Patent Application Laid-Open No. 2010-164521 Summary of the Invention [Problem to be solved by the invention]

[0005] Current technologies, including those disclosed in the above-mentioned patent documents, do not adequately meet market needs, and the following problems exist. In other words, since the above-mentioned patent documents also use near-infrared light of three different wavelengths to determine the condition of the road surface, it can be said that this is useful in that it allows for easy determination of the road surface condition using a non-contact method.

[0006] However, to further improve vehicle driving safety, it is important to further improve the accuracy of road surface condition judgment. In particular, when judging road surface conditions using near-infrared light of three wavelengths, it is difficult to distinguish between wet and frozen conditions. Therefore, there is a need for a judgment technology that can prevent erroneous judgment of road surface conditions while maintaining a simple configuration.

[0007] The present disclosure has been made in consideration of the above-mentioned problems as an example, and aims to provide a road surface condition determination device for a vehicle that can accurately determine the condition of the road surface ahead in the direction of travel without making an erroneous determination while keeping device costs down. [Means for solving the problem]

[0008] In order to solve the above problem, a road surface condition determination device mounted on a vehicle in one embodiment of the present disclosure is a road surface condition determination device that includes one or more processors and one or more memories communicatively connected to the one or more processors, and determines the condition of the road surface in a non-contact manner, wherein the processor uses a light source that irradiates three near-infrared lights of different wavelengths onto the road surface, and based on the three near-infrared lights reflected from the road surface and received by a light receiving sensor, makes a primary determination as to whether the type of the road surface is snow-covered, giving priority to other types, and then makes a secondary determination as to which of the other types the type of the road surface is. [Effects of the Invention]

[0009] According to the present disclosure, it is possible to accurately determine the condition of the road surface ahead in the direction of travel of the vehicle without making erroneous determinations while keeping costs down. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram showing an example of the configuration of a vehicle equipped with a road surface condition determination device according to an embodiment; [Figure 2] FIG. 2 is a block diagram showing an example of the configuration of a road surface condition determination device and peripheral devices. [Figure 3] 3 is a flowchart showing a road surface condition determination method that can be executed by the road surface condition determination device of the present embodiment. [Figure 4] 1 is a graph showing the absorbance of three types of near-infrared light used in this embodiment for ice and water. [Figure 5] FIG. 3 is a schematic diagram showing an example of polar coordinate data used in the present embodiment. [Figure 6] FIG. 10 is a schematic diagram showing an example of the result of calculating the Euclidean distance (radius) in a polar coordinate system applicable to snow accumulation (SNOW) determination. [Figure 7] FIG. 10 is a schematic diagram showing an example of the results of calculating polar coordinates (θ) in a polar coordinate system applicable to freezing (ICE) determination. [Figure 8] FIG. 1 is a schematic diagram showing an example of a moisture index and a determination threshold for determining whether the object is dry or wet. DETAILED DESCRIPTION OF THE INVENTION

[0011] Next, preferred embodiments for carrying out the present disclosure will be described. Furthermore, configurations other than those described in detail below may be supplemented appropriately with known vehicle structures and on-board systems, including various known on-board sensors.

[0012] [Vehicle 200] 1 shows an example of the configuration of a vehicle 200 according to this embodiment. In the following, a four-wheel drive automobile is exemplified as a vehicle suitable for this embodiment, but the present invention may also be applied to automobiles other than four-wheel vehicles, such as motorcycles, as long as the purpose of this disclosure is not impaired.

[0013] <Overall vehicle configuration> Fig. 1 is a schematic diagram showing an example of the configuration of a vehicle 200 equipped with a road surface condition determination device 100 according to this embodiment. The vehicle 200 shown in Fig. 1 is configured as a four-wheel drive vehicle in which drive torque output from a drive power source 9 that generates drive torque for the vehicle is transmitted to a left front wheel 3LF, a right front wheel 3RF, a left rear wheel 3LR, and a right rear wheel 3RR (hereinafter collectively referred to as "wheels 3" unless a distinction is required). The drive power source 9 may be an internal combustion engine such as a gasoline engine or a diesel engine, a drive motor, or both an internal combustion engine and a drive motor.

[0014] Vehicle 200 may be an electric vehicle equipped with two drive motors, for example, a front-wheel drive motor and a rear-wheel drive motor, or may be an electric vehicle equipped with drive motors corresponding to each of wheels 3. Furthermore, if vehicle 200 is an electric vehicle or a hybrid electric vehicle, vehicle 200 is equipped with a secondary battery that stores power supplied to the drive motors, and a motor or a generator such as a fuel cell that generates power to charge the battery.

[0015] The vehicle 200 is equipped with a driving force source 9, an electric steering device 15, and a brake fluid pressure control unit 20 as devices used to control the driving of the vehicle. The driving force source 9 outputs driving torque that is transmitted to the front drive shaft 5F and the rear drive shaft 5R via a transmission, a front wheel differential mechanism 7F, and a rear wheel differential mechanism 7R (not shown). The driving of the driving force source 9 and the transmission is controlled by a vehicle control device 41 that includes one or more electronic control units (ECUs: Electronic Control Units).

[0016] The front-wheel drive shaft 5F is provided with an electric steering device 15. The electric steering device 15 includes an electric motor and a gear mechanism (not shown), and is controlled by a vehicle control device 41 to adjust the steering angles of the left front wheel 3LF and the right front wheel 3RF. During manual driving, the vehicle control device 41 controls the electric steering device 15 based on the steering angle of the steering wheel 13 operated by the driver.

[0017] The brake system of the vehicle 200 is configured as a hydraulic brake system. A brake fluid pressure control unit 20 adjusts the hydraulic pressure supplied to brake calipers 17LF, 17RF, 17LR, and 17RR (hereinafter collectively referred to as "brake calipers 17" unless a distinction is required) provided on the front, rear, left, and right drive wheels 3LF, 3RF, 3LR, and 3RR, respectively, to generate braking force. The drive of the brake fluid pressure control unit 20 is controlled by a vehicle control device 41. If the vehicle 1 is an electric vehicle or a hybrid electric vehicle, the brake fluid pressure control unit 20 is used in conjunction with regenerative braking using a drive motor.

[0018] The vehicle control device 41 includes one or more electronic control devices that control the drive of the driving force source 9 that outputs the driving torque of the vehicle 200, the steering wheel 13 or the electric steering device 15 that controls the steering angle of the steering wheels, and the brake fluid pressure control unit 20 that controls the braking force of the vehicle 200. The vehicle control device 41 may also have a function of controlling the drive of a transmission that changes the speed of the output output from the driving force source 9 and transmits it to the wheels 3. The vehicle control device 41 is configured to be able to acquire information transmitted from a road surface condition determination device 100, which will be described later, and is configured to be able to perform vehicle control based on the result of estimation of the friction coefficient of the road surface by this road surface condition determination device 100.

[0019] The vehicle 200 may also be equipped with an ambient environment sensor 31, a light receiving sensor 32, an occupant monitoring sensor 33, a biological sensor 34, a vehicle condition sensor 35, a GPS (Global Positioning System) sensor 37, a vehicle-to-vehicle communication unit 39, a navigation system 40, an HMI (Human Machine Interface) 43, and a light source 47 capable of irradiating three near-infrared lights of different wavelengths onto the road surface.

[0020] Among these, the ambient environment sensor 31 includes a road surface temperature sensor for detecting the temperature of the road surface, an unevenness detection sensor for detecting unevenness on the road surface, and a moisture sensor for detecting the amount of moisture on the road surface, as described below. The sensor for detecting the road surface temperature may be any of various known temperature sensors, such as those exemplified in JP 2015-038516 A. The unevenness detection sensor for detecting unevenness on the road surface may be, for example, the device (road surface unevenness detection sensor) disclosed in JP 2004-138549 A, or any of various known means or laser rangefinders described in JP 2013-61690 A. The moisture sensor for detecting the amount of moisture on the road surface may be, for example, any of various known moisture detection sensors, such as those exemplified in JP 2006-46936 A.

[0021] Furthermore, the surrounding environment sensor 31 in this embodiment may be configured to include front imaging cameras 31LF and 31RF, a rear imaging camera 31R, and a LiDAR (Light Detection And Ranging) 31S.

[0022] The front photographing cameras 31LF, 31RF, the rear photographing camera 31R, and the LiDAR 31S constitute a surrounding environment sensor for acquiring information about the surrounding environment of the vehicle 200. The front photographing cameras 31LF, 31RF and the rear photographing camera 31R photograph the area in front of or behind the vehicle 200 and generate image data. The front photographing cameras 31LF, 31RF and the rear photographing camera 31R are equipped with imaging elements such as CCDs (Charged-Coupled Devices) or CMOSs ​​(Complementary Metal-Oxide-Semiconductors), and can transmit the generated image data to the road surface condition determination device 100.

[0023] 1, the front imaging cameras 31LF, 31RF are configured as a stereo camera including a pair of left and right cameras, and the rear imaging camera 31R is configured as a so-called monocular camera, but each may be either a stereo camera or a monocular camera. In addition to the front imaging cameras 31LF, 31RF and the rear imaging camera 31R, the vehicle 200 may also be equipped with a known camera that is mounted on a side mirror, for example, to capture images of the left rear or right rear.

[0024] The LiDAR 31S transmits optical waves and receives reflected waves of the optical waves, and detects an object and the distance to the object based on the time between transmitting the optical waves and receiving the reflected waves. The LiDAR 31S can transmit the detection data to the road surface condition determination device 100. The vehicle 200 may be equipped with one or more known sensors, such as a radar sensor such as a millimeter-wave radar, or an ultrasonic sensor, instead of or in addition to the LiDAR 31S, as the surrounding environment sensor 31 for acquiring information about the surrounding environment.

[0025] The light-receiving sensor 32 has a function of receiving near-infrared light that is irradiated by a light source 47 that irradiates near-infrared light containing three wavelengths similar to that described in Patent Document 1 and that is reflected by the road surface. There are no particular limitations on the light-receiving sensor 32, and various known sensors can be used as long as they receive the near-infrared light described above. Note that the light source 47 can also be a known light-emitting diode or semiconductor laser device that can irradiate near-infrared light of the wavelengths described above.

[0026] As shown in FIG. 4, the near-infrared light emitted from the light source 47 has a first wavelength λ , which is relatively less affected by moisture. A , a second wavelength λ that is not easily absorbed by ice but is easily absorbed by water (i.e., the influence of water is large and the influence of ice is small). B , and a third wavelength λ that is easily absorbed by ice but not easily absorbed by water (i.e., the influence of water is small and the influence of ice is large). C For example, the first wavelength λ AThe second wavelength λ is preferably 980 nm. B is preferably selected from 1370 to 1450 nm, and the third wavelength λ C It is preferable to select the wavelength from 1470 to 1550 nm. The timing at which the light source 47 irradiates the road surface with the near-infrared light of at least three wavelengths may be arbitrary, and for example, the light source 47 may irradiate the near-infrared light at the timing disclosed in Patent Document 1.

[0027] The occupant monitoring sensor 33 may also be configured to include an in-vehicle camera 33c. The interior camera 33c is composed of one or more known sensors that detect information about the driver of the vehicle 200. The interior camera 33c is equipped with an imaging element such as a CCD or CMOS, captures images of the interior of the vehicle, and generates image data. The interior camera 33c can transmit the generated image data to the road surface condition determination device 100. In this embodiment, the interior camera 33c is positioned so that it can capture images of the driver of the vehicle 200. There may be only one interior camera 33c installed, or multiple interior cameras 33c may be installed.

[0028] The biosensor 34 detects the driver's biometric information and transmits the detected data to the road surface condition determination device 100. The biosensor 34 may be any of various known sensors, such as a radio wave Doppler sensor for detecting the driver's heartbeat or a non-wearable pulse sensor for detecting the driver's pulse. The biosensor 34 may also be an electrode set embedded in the steering wheel 13 for measuring the driver's heartbeat or electrocardiogram.

[0029] The vehicle condition sensor 35 is composed of one or more known sensors that detect the operation state and behavior of the vehicle 1. The vehicle condition sensor 35 includes at least one of a steering angle sensor, an accelerator position sensor, a brake stroke sensor, a brake pressure sensor, and an engine speed sensor, and detects the operation state of the vehicle 1, such as the steering angle of the steering wheel 13 or the steering wheels, the accelerator position, the brake operation amount, and the engine speed. The vehicle condition sensor 35 also includes at least one of a vehicle speed sensor, an acceleration sensor, and an angular velocity sensor, and detects the vehicle behavior, such as the vehicle speed, longitudinal acceleration, lateral acceleration, and yaw rate. The vehicle condition sensor 35 also includes a sensor that detects the operation state of a turn signal, and a sensor that detects the inclination state of the vehicle 1, and detects the inclination state of the road. The vehicle condition sensor 35 can transmit a sensor signal containing the detected information to the road surface condition determination device 100.

[0030] The vehicle-to-vehicle communication unit 39 is an interface for communicating with vehicles traveling around the vehicle 200 (hereinafter also referred to as "other vehicles"). The navigation system 40 is a known navigation system that sets a driving route to a destination set by the occupant and notifies the driver of the driving route. A GPS sensor 37 is connected to the navigation system 40, and receives satellite signals from GPS satellites via the GPS sensor 37 to obtain position information of the vehicle 200 on map data. Note that instead of the GPS sensor 37, an antenna that receives satellite signals from another satellite system that identifies the position of the vehicle 200 may be used.

[0031] The HMI 43 is driven by the road surface condition determination device 100 and presents various information to the driver by means of image display, audio output, etc. The HMI 43 includes, for example, a display device provided in the instrument panel and a speaker provided in the vehicle. The display device may have the function of the display device of the navigation system 40. The HMI 43 may also include a head-up display that displays an image on the front window of the vehicle 200.

[0032] [Road surface condition determination device 100] Next, a specific configuration example of the road surface condition determining device 100 according to this embodiment that determines the road surface condition (type) of the traveling vehicle 200 will be described.

[0033] FIG. 2 is a block diagram showing an example of the configuration of the road surface condition determining device 100 according to this embodiment. The road surface condition determination device 100 is connected to sensors SR (such as an ambient environment sensor 31, an occupant monitoring sensor 33, a biological sensor 34, a vehicle condition sensor 35, and a GPS sensor 37) via a dedicated line or communication means such as a CAN (Controller Area Network) or a LIN (Local Inter Net). The road surface condition determination device 100 is also connected to the above-mentioned vehicle-to-vehicle communication unit 39, a navigation system 40, a vehicle control device 41, and an HMI 43 via a dedicated line or communication means such as a CAN or a LIN. The road surface condition determination device 100 is also configured to be connectable to an external network NET, such as the Internet, via a known communication means 45.

[0034] The road surface condition determination device 100 of this embodiment includes a control unit 50 and a known storage unit (memory 60 and database 70). The control unit 50 is configured with one or more processors such as CPUs (Central Processing Units). Part or all of the control unit 50 may be configured with updatable firmware or the like, or may be a program module or the like executed by commands from the CPU or the like. Of the storage units, the memory 60 is configured with a known memory device such as RAM (Random Access Memory) or ROM (Read Only Memory).

[0035] Furthermore, the database 70 of the storage unit described above is configured with a known updatable recording medium, such as an SSD (Solid State Drive), HDD (Hard Disk Drive), USB flash drive, or storage device. However, the number and type of the storage units described above are not particularly limited in this embodiment. Furthermore, at least some of the information in the database 70 may be stored in a known external server. The storage unit of this embodiment may be configured to record information such as computer programs executed by the control unit 50, various parameters used in arithmetic processing, detection data, and arithmetic results.

[0036] In addition, the database 70 in this embodiment may be configured to store first threshold data FTD of Euclidean distance (radius) used to determine snow accumulation (SNOW) in a polar coordinate system, second threshold data STD of polar coordinate (θ) used to determine ice (ICE) in a polar coordinate system, and third threshold data TTD of moisture index used to determine whether the condition is dry (DRY) or wet (WET), as will be described later.

[0037] As shown in FIG. 2, the control unit 50 of this embodiment includes a near-infrared light transmitting and receiving unit 51, a road surface condition determining unit 52, and a vehicle control unit 55.

[0038] The near-infrared light transmitting and receiving unit 51 has a function of controlling the light source 47 capable of emitting the above-mentioned three near-infrared light beams having different wavelengths, and emitting these three near-infrared light beams onto the road surface on which the vehicle 200 is traveling. The near-infrared light transmitting and receiving unit 51 also has a function of receiving the near-infrared light beams emitted from the light source 47 and reflected by the above-mentioned road surface, via a known light receiving unit (not shown).

[0039] The road surface condition determination unit 52 has a function of determining the condition of the road surface on which the vehicle 200 is traveling, based on the above-mentioned three types of near-infrared light reflected from the road surface and received by the near-infrared light transmitting and receiving unit 51. In this case, as will be described later, the road surface condition determination unit 52 may perform a primary determination as to whether the type of the road surface is snow-covered (SNOW) or not, giving priority to other types, and then perform a secondary determination as to whether the type of the road surface is any of the other types (DRY, ICE, WET). Furthermore, in this secondary determination, the road surface condition determination unit 52 may determine priority as to whether the type of the road surface is icy (ICE) or not, and then determine whether the type of the road surface is dry (DRY) or wet (WET).

[0040] 5, the road surface condition determination unit 52 may have a function of determining the road surface condition from a determination threshold based on a polar coordinate system with axes representing the wavelengths of the three near-infrared lights, based on the received light amounts of the three near-infrared lights reflected by the road surface and received by the near-infrared light transmitting and receiving unit 51. Note that the polar coordinate system shown in FIG. 5 indicates the received light amounts of the near-infrared lights of the wavelengths shown on each axis as values ​​converted into voltages (for example, in the range of about several mmV to several thousand mmV). After careful consideration, the inventors have concluded that in this embodiment, setting judgment thresholds for determining each road surface condition (snow-covered condition, frozen condition, dry condition, and wet condition) based on the characteristics of the road surface of near-infrared light having each wavelength shown in Table 1 will contribute to improving accuracy.

[0041] [Table 1]

[0042] Specifically, in a dry state, the unevenness of the road surface stands out relatively compared to other states, so the diffuse light component increases, and it can be said that there is almost no absorption by the moisture on the road surface.In addition, in a wet state, the specular reflection component of near-infrared light increases due to the water film that forms on the road surface, while the amount of light received decreases, and it can be said that there is absorption by the moisture on the road surface.

[0043] In addition, in snowy conditions, the amount of light received is relatively large because the scattering caused by snow crystals and other factors is more pronounced than in other conditions. In frozen conditions, although there is some scattered light, the absorption of long wavelength components by water and ice is large.

[0044] Therefore, in the primary determination described above, the road surface condition determination unit 52 of this embodiment first calculates the amount of light received by the light receiving sensor 32 in the three near-infrared light beams in equation (1) for calculating the Euclidean distance (radius) in the polar coordinate system. In this case, in equation (1), "x(n)" is the wavelength λ A indicates the amount of near-infrared light received, and "y(n)" is the wavelength λ B indicates the amount of near-infrared light received, and "z(n)" is the wavelength λ C The figure shows the amount of near-infrared light received.

[0045]

number

[0046] Next, in the secondary determination, the road surface condition determination unit 52 calculates the polar coordinates (angle θ(n)) in the polar coordinate system using the formula (2) based on the amount of light received by the light receiving sensor 32 in the three near-infrared light beams. In this case, in formula (2), "x(n)" is the wavelength λ A indicates the amount of near-infrared light received, and "y(n)" is the wavelength λ B indicates the amount of near-infrared light received, and "z(n)" is the wavelength λ C The figure shows the amount of near-infrared light received.

[0047]

number

[0048] Furthermore, the road surface condition determination unit 52 may determine the type of road surface on which the vehicle is traveling using a moisture index MI, which is a ratio of wavelengths that are easily absorbed by water to wavelengths that are not easily absorbed by water. More specifically, the road surface condition determination unit 52 of this embodiment determines the type of road surface on which the vehicle is traveling using a moisture index MI, which is a ratio of wavelengths that are easily absorbed by water to wavelengths that are not easily absorbed by water, among the three types of near-infrared light described above. B ) of the received light amount RA1, the wavelength that is not easily absorbed by water (first wavelength λ A The moisture index MI, which is the ratio of the amount of received light RA2 to the amount of received light RA2, can be used to determine whether the road surface is dry or wet. In this case, the moisture index MI can be expressed by the following equation (3):

[0049]

number

[0050] The vehicle control unit 55 has a function of controlling the vehicle 200 based on the road surface condition determined by the road surface condition determination unit 52. Examples of vehicle control based on such road surface conditions include control to alert the occupants via the HMI 43, and control to adjust the drive torque of the vehicle 200 via the vehicle control device 41 in accordance with the road surface condition.

[0051] <Method for determining road surface conditions> Next, a method for determining the state of a road surface on which the vehicle 200 travels in this embodiment will be described with reference to FIG. 3. In the following, the road surface state will be described by taking as an example which of the four road surface states, dry (DRY), wet (WET), snow-covered (SNOW), and icy (ICE), as described above. However, the above-described road surface state is a known example, and other known road surface states, such as packed snow, may be applied as long as they can be determined using the above-described three amounts of received near-infrared light. Furthermore, in determining the road surface in this embodiment, a state that spans at least two of the above-described states (for example, both SNOW and WET) may be determined.

[0052] The method of estimating the friction coefficient described below is performed by the road surface condition determining device 100 in a non-contact manner. First, in step 10, the near-infrared light transmitting and receiving unit 51 controls the light source 47 to irradiate the road surface with the three near-infrared lights having the above-mentioned wavelengths that are different from one another. Next, in step 11, the near-infrared light transmitting and receiving unit 51 determines whether or not the light receiving sensor 32 has received each of the three near-infrared lights reflected from the road surface.

[0053] If it is determined in step 11 that the three types of near-infrared light have been received, then in the following step 12, the road surface condition determination unit 52 first determines whether the type of road surface is a "snow-covered (SNOW)" or not. That is, the road surface condition determination unit 52 makes a primary determination of whether the type of road surface is a snow-covered state, prioritizing the other types, based on the three types of near-infrared light reflected from the road surface and received by the light-receiving sensor 32.

[0054] More specifically, the road surface condition determination unit 52 performs the above primary determination by calculating the amount of light received by the light receiving sensor 32 for each of the three near-infrared light beams in equation (1) that calculates the Euclidean distance (radius) in the polar coordinate system shown in Figure 5. At this time, the road surface condition determination unit 52 determines whether or not r(n) calculated by equation (1) exceeds first threshold data FTD, based on first threshold data FTD that can distinguish between snow-covered (SNOW) conditions and other conditions, as shown in FIG. 6. The first threshold data FTD can be calculated in advance through experiments, simulations, etc., and stored in the database 70, etc. In this example, as an example, an average value for each state is calculated through experiments, etc., and the first threshold data FTD is set based on ±2σ of this average value.

[0055] If r(n) calculated in step 12 exceeds the first threshold data FTD, the road surface condition is determined to be a "snow-covered (SNOW) condition" and the process proceeds to step 16. On the other hand, if r(n) calculated in step 12 does not exceed the first threshold data FTD, a secondary determination is made in the following step 13 as to whether the type of road surface is any type other than snow cover (SNOW).

[0056] Specifically, in the secondary determination, it is preferable that the road surface condition determination unit 52 first determines whether the type of road surface is frozen (ICE) by incorporating the amount of light received by the three near-infrared light beams received by the light receiving sensor 32 into equation (2) that calculates the polar coordinate (angle (θ)) in the polar coordinate system shown in Figure 5.

[0057] At this time, the road surface condition determination unit 52 determines whether the angle θ(n) calculated by equation (2) exceeds the second threshold data STD, based on the second threshold data STD that can distinguish between an icy (ICE) state and other states (dry or wet), as shown in FIG. 7. The second threshold data STD can be calculated in advance through experiments, simulations, etc., and stored in the database 70, etc. In this example, as an example, an average value for each state is calculated through experiments, etc., and the angle information, which is the threshold value described above, is set based on ±2σ of this average value.

[0058] If θ(n) calculated in step 13 exceeds the second threshold data STD, the road surface condition is determined to be an “icy (ICE) condition” and the process proceeds to step 16. On the other hand, if θ(n) calculated in step 13 does not exceed the second threshold data STD, a secondary determination is made as to whether the road surface type is dry or wet in the following steps 14 and 15. In this embodiment, the wet state is determined before the dry state, but the dry state may be determined first, or these determinations may be made substantially simultaneously.

[0059] That is, in this embodiment, the road surface condition determination unit 52 determines whether the road surface is in a dry state or a wet state using the moisture index MI described above in steps 14 and 15. At this time, the road surface condition determination unit 52 determines whether the moisture index calculated by equation (3) exceeds (or falls below) third threshold data TTD, based on third threshold data TTD that can distinguish between a dry state and a wet state, as shown in Fig. 8 . The third threshold data TTD can be calculated in advance through experiments, simulations, etc., and stored in the database 70, etc. In this example, as an example, an average value for each state is calculated through experiments, etc., and the threshold value of the moisture index is set based on ±2σ of this average value.

[0060] If the calculated moisture index exceeds the third threshold data TTD, the road surface condition is determined to be "DRY", whereas if the calculated moisture index does not exceed the third threshold data TTD, the road surface condition is determined to be "WET". In this way, it is preferable that the road surface condition determination unit 52, in the secondary determination, first determines whether the type of the road surface is frozen or not, and then determines whether the type of the road surface is dry or wet.

[0061] After the state of the road surface on which the vehicle is traveling is determined as described above, in step 16, this determined state of the road surface is reflected in the vehicle control of the traveling vehicle 200. More specifically, for example, the vehicle control device 41 may perform control to adjust the drive torque of the vehicle 200 based on the state of the road surface determined with higher accuracy.

[0062] In the next step 20, it is determined whether the system of the vehicle 200 has been stopped, and if it is determined that the system is OFF, this process is completed, whereas if the vehicle 200 is still traveling, the process returns to step 1 and the above-described process is repeated. Therefore, for example, if the weather changes from rainy to sunny while the vehicle 200 is traveling, the road surface condition determination device 100 will determine the road surface condition again.

[0063] According to the road surface condition determination device 100 and road surface condition determination method for the vehicle 200 in this embodiment described above, it is possible to accurately determine the condition of the road surface on which the vehicle 200 is traveling in accordance with various traveling environments. Furthermore, according to this embodiment, since it determines whether the road surface is slippery or not (i.e., whether the road surface is snowy (SNOW) or icy (ICE)) before any other methods, even if an erroneous determination is made, the driving force of the vehicle is suppressed, thereby further improving traveling stability.

[0064] While the preferred embodiments of the present disclosure have been described above with reference to the accompanying drawings, the present disclosure is not limited to such examples. In other words, it is clear that a person skilled in the art would attempt further modifications to the above-described embodiments, and it is understood that these modifications also fall within the technical scope of the present disclosure.

[0065] For example, the first threshold data FTD to the third threshold data TTD in the above-described embodiment may have optimum thresholds for each region, etc. Therefore, the road surface condition determining device 100 may determine the road surface condition based on threshold data for each region divided into predetermined regions (for example, prefectures, provinces, etc.) based on, for example, the position information of the vehicle from the GPS sensor 37.

[0066] In addition, in step 12 in the above embodiment, after it is determined that there is snow (SNOW) in the vehicle, the process proceeds to step 16. However, the present disclosure is not limited to this embodiment, and the following additional determination step may be included between step 12 and step 16. That is, since the snowy (SNOW) state is similar to the "concrete" or "white line" state in which the road surface is white, a distinction may be further made between the snowy (SNOW) state and these states.

[0067] More specifically, in this additional determination step, the moisture index MI described above may be calculated and compared with a predetermined threshold value to distinguish between "snow (SNOW)" and "concrete or white line." If the moisture index MI when the snow (SNOW) condition is provisionally determined is equal to or greater than a predetermined moisture content, the additional determination step can officially determine the condition as "snow (SNOW)." Note that the threshold value in this additional determination step, like the other threshold values, may be calculated in advance by experiment or simulation and stored in the database 70, etc. [Explanation of symbols]

[0068] 200 vehicles 100 Road surface condition determination device 31 Ambient environment sensor 32 Light receiving sensor 41 Vehicle control device 47 Light source 50 Control device 51 Near-infrared light transmitting and receiving unit 52 Road surface condition determination unit 55 Vehicle control unit

Claims

1. one or more processors; one or more memories communicatively coupled to the one or more processors; A road surface condition determination device for determining the condition of a road surface in a non-contact manner, comprising: The processor: irradiating the road surface with near-infrared light using a light source that irradiates three near-infrared light beams having different wavelengths; Based on the three types of near-infrared light reflected from the road surface and received by a light receiving sensor, a primary determination is made as to whether the type of the road surface is snow-covered or not, prioritizing it over other types, and then a secondary determination is made as to which of the other types the type of the road surface is. Road surface condition determination device.

2. The processor: In the secondary determination, it is determined first whether the type of the road surface is frozen, and then it is determined whether the type of the road surface is dry or wet. The road surface condition determination device according to claim 1 .

3. one or more processors; one or more memories communicatively coupled to the one or more processors; A road surface condition determination device for determining the condition of a road surface in a non-contact manner, comprising: The processor: irradiating the road surface with three near-infrared light beams having different wavelengths using light sources that respectively irradiate the three near-infrared light beams; determining the state of the road surface from a determination threshold based on a polar coordinate system having axes corresponding to the wavelengths of the three near-infrared lights reflected from the road surface and received by the light receiving sensor; Road surface condition determination device.

4. The processor: By incorporating the three near-infrared light beams received by the light receiving sensor into equation (1) for calculating the Euclidean distance (radius) in the polar coordinate system, a primary determination is made as to whether the type of road surface is snow-covered or not, with priority given to other types. The road surface condition determination device according to claim 3.

5. The processor: By incorporating the three near-infrared light beams received by the light receiving sensor into equation (2) for calculating the polar coordinate (θ) in the polar coordinate system, a secondary determination is performed after the primary determination to determine whether the road surface type is frozen or not, taking priority over the remaining types. The road surface condition determination device according to claim 4.

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