JP2010210324A - Road conditions estimating apparatus and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a road conditions estimating apparatus which estimates accurate road conditions even when the distance from a sensor to a road surface fluctuates by the behavior of a vehicle. <P>SOLUTION: A generator 101 generates timing for electromagnetic wave pulse generation. A transmitter 102 generates an electromagnetic wave pulse with timing generated by the generator 101. A receiver 103 receives the electromagnetic wave pulse reflected by an on object under measurement M. A waveform detecting unit 104 detects the waveform of a reflected wave on the basis of the timing provided by the generator 101. An angle measuring/setting unit 105 measures the tilt angle θ of boundary surfaces B1, B2 departing from a transmitting/receiving surface having the transmitter 102 and the receiver 103. A reflection boundary surface position measuring unit 106 measures the position of the boundary surface B1. A waveform characteristics extracting unit 107 extracts waveform characteristics on the basis of the detected waveform, the angle θ, and the position of the boundary surface B1. A road conditions estimating unit 108 estimates road conditions on the basis of the waveform characteristics. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a road surface state estimating apparatus and method for estimating a road surface state using electromagnetic waves.

  In order to support the appropriate driving of automobiles, an advanced transportation system (ITS) that is responsible for the next-generation transportation society has been developed. In intelligent transportation systems, it is conceivable that a road surface condition estimation device provided on the road side estimates the road surface state and transmits the road surface condition to a running vehicle for use in vehicle braking control, traction control, attitude control, etc. ing. As such a conventional road surface state estimating device, a road surface is two-dimensionally scanned by a laser radar sensor fixed above the road surface, distance and reflection intensity are obtained as measurement point information, and visibility indicating atmospheric turbidity is shown. A technique is known in which the reflection intensity is corrected by information and the road surface condition is estimated for each measurement point (for example, Patent Document 1).

JP 2001-83078 A

  However, when the conventional road surface condition estimation device is applied to in-vehicle sensing, the distance from the sensor to the road surface varies depending on the behavior of the vehicle, so that there is a problem that an accurate road surface condition cannot be estimated. there were.

  In order to solve the above problems, the present invention transmits an electromagnetic wave to a road surface, receives an electromagnetic wave reflected by the road surface, detects a waveform of the received electromagnetic wave, and measures an angle between the road surface and a transmission direction, or It sets, extracts the feature of a waveform based on a waveform and the said angle, and estimates a road surface condition based on the feature of a waveform.

  According to the present invention, even if the distance from the sensor to the road surface changes due to vehicle behavior, there is an effect that the road surface condition can be accurately estimated based on the transmission direction of electromagnetic waves and the characteristics of the received reflected wave.

It is a block diagram which shows the structure of Example 1 of the road surface condition estimation apparatus which concerns on this invention. It is a block diagram which shows the structure of Example 1 at the time of using electromagnetic waves as a terahertz wave. It is a block diagram which shows the structure of the modification of Example 1 at the time of using electromagnetic waves as a terahertz wave. It is a perspective view explaining the detailed example of the optical switch 4 for transmission in FIG. It is a perspective view explaining the detailed example of the optical switch 8 for reception in FIG. 3 is a flowchart for explaining an operation in the first embodiment. It is a figure which shows the directional characteristic example of a terahertz transmitter. It is a figure which shows the intensity | strength of the terahertz reflected wave with respect to the kind of reflective surface, and an irradiation direction. 6 is a block diagram illustrating a configuration of Example 2. FIG. 10 is a flowchart illustrating an operation in the second embodiment. 10 is a block diagram illustrating a configuration of Example 3. FIG. 10 is a flowchart for explaining an operation in the third embodiment. It is a figure which shows the relationship between a road surface condition and the characteristic of the reflected waveform of a terahertz wave. It is a side view of the vehicle carrying the road surface condition estimation apparatus of this invention. It is a top view which shows the example of the mounting position to the vehicle body of a terahertz transmitter and a receiver. FIG. 10 is a block diagram illustrating a configuration of a fourth embodiment. 10 is a flowchart illustrating an operation in the fourth embodiment.

  Next, embodiments of the present invention will be described in detail with reference to the drawings. In addition, although each Example demonstrated below is an Example suitable for a vehicle-mounted road surface condition estimation apparatus, it is clear that it can be utilized also for the stationary installation installed in a road side.

  FIG. 1 is a block diagram illustrating a configuration of a road surface condition estimation apparatus according to a first embodiment of the present invention. In FIG. 1, a road surface condition estimation apparatus 1 includes a generator 101 that generates an electromagnetic wave pulse generation timing, a transmitter 102 that transmits the electromagnetic wave pulse to a measurement target (road surface) M at the timing generated by the generator 101, A receiver 103 that receives an electromagnetic wave reflected by the measurement object M, a waveform detector 104 that reconstructs and detects a waveform from the electromagnetic wave received by the receiver 103, and a transmitter 102 and a receiver 103 are installed. An angle measurement / setting unit 105 that measures or sets an angle θ at which the measurement object M is inclined with respect to a plane (hereinafter referred to as a transmission / reception surface), a reflection boundary surface position measurement unit 106 that measures a reflection boundary surface position, A waveform feature extracting unit 107 that extracts a waveform feature based on the waveform detected by the waveform detecting unit 104 and the angle θ, and a road surface condition is estimated based on the feature extracted by the waveform feature extracting unit 107 And a road surface condition estimating unit 108.

  The angle measurement / setting unit 105 is either a detection signal of a sensor (not shown) mounted on a vehicle such as a camera, a laser radar, or an acceleration sensor, or a set angle of a fixture (not shown) attached to the vehicle so that the transmission / reception surface can be tilted. The angle θ between the measurement object M and the transmission / reception surface is measured from one or more combinations. The angle measurement / setting unit 105 outputs the measurement value of the angle θ to the waveform feature extraction unit 107.

  The reflection boundary surface position measurement unit 106 measures the distance between the measurement target M and the transmission / reception surface from a combination of one or more of a camera, a laser radar, an acceleration sensor, a known stage, and sensor installation conditions. The reflection boundary surface position measurement unit 106 outputs the measured distance to the waveform feature extraction unit 107.

  The waveform feature extraction unit 107 extracts waveform features based on the waveform detected by the waveform detection unit 104 and the angle θ. The road surface state estimation unit 108 estimates the road surface state based on the features extracted by the waveform feature extraction unit 107.

Here, the electromagnetic wave pulse radiated from the transmitter 102 may have a wavelength that is partially reflected by the road surface and water, ice, snow, or the like that may be stacked on the road surface. When puddles are formed on the road surface, frozen, or snow is accumulated, the road surface has boundary surfaces B1 and B2. Terahertz waves (0.1 THz to 10 THz, 1 THz = 10 ¹² Hz) are preferably used as the wavelength of the electromagnetic wave pulse. Terahertz waves are undeveloped electromagnetic waves left between radio waves and light, and have both radio wave and light properties. The terahertz wave is reflected at the boundary surface B1 and partly penetrates inside and is reflected at the boundary surface B2. Therefore, the road surface is smooth or scattering from the reflected waveform, or the road surface stacking condition and the layered material Can be estimated.

FIG. 2 is a configuration diagram illustrating the configuration of the first embodiment when the electromagnetic wave is a terahertz wave. In FIG. 2, the road surface condition estimation apparatus 1 uses a femtosecond pulse laser 2 that generates laser light having a pulse width of about 100 fs (1 fs = 10 ⁻¹⁵ s) and pulse light generated by the femtosecond pulse laser 2 for excitation. An applied voltage is applied to the half mirror 3 that divides the pulse light 12 and the synchronous detection pulse light 13, the transmission optical switch 4 that converts the excitation pulse light 12 into a terahertz pulse and emits it, and the transmission optical switch 4. The bias 5, the mirror 6, the mirror 7 having a movable structure for time-delayed scanning of the synchronous detection pulse light 13, and the timing of the synchronous detection pulse light 13 by receiving the terahertz wave reflected by the measurement target M Receiving optical switch 8 for converting to a photocurrent, a current amplifier 9 for amplifying the photocurrent, and a waveform detector for reconstructing the received waveform and detecting the waveform of the terahertz wave 0, and a microcomputer 11 for estimating the road surface condition based on the waveform of the waveform detector 10 has detected.

  For example, when a titanium-added sapphire laser (Ti: Al2O3) is used as the femtosecond pulse laser 2, a pulse width of 12 to 100 fs, a pulse repetition frequency of 10 to 80 MHz, and an output of 500 mW to 2 W are obtained. Further, when a fiber laser is used as the femtosecond pulse laser 2, a pulse width of 502 to 100 fs, a pulse repetition frequency of 10 to 50 MHz, and an output of 30 to 300 mW are obtained.

  The wavelength of the pulsed light generated by the femtosecond pulse laser 2 is that of light corresponding to the band gap (Eg = 1.42 eV in the case of GaAs) of a semiconductor substrate (for example, GaAs) that converts the femtosecond optical pulse into a terahertz wave. This wavelength is equal to or shorter than the wavelength and can excite photocarriers on the LT-GaAs substrate described later with reference to FIG.

  FIG. 4 is a perspective view illustrating a detailed example of the transmission optical switch 4. The transmission optical switch 4 includes a laser converging lens 31 for converging the excitation pulse light 12, a silicon lens 32 for converging the generated terahertz wave pulse, an LT-GaAs substrate 33 which is a GaAs substrate grown at a low temperature, an antenna A pair of electrodes 34 and 35 also serving as a power supply line is provided. The width d of the gap between the electrodes 34 and 35 is, for example, 5 μm to 10 μm, and acts as a minute dipole antenna. A bias 5 for supplying a bias voltage Vb (DC to 10 kHz, about 20 V) is connected between the electrodes 34 and 35. When the excitation pulse light 12 is irradiated to the gap between the electrodes 34 and 35, photocarriers are generated by the photoelectric effect of GaAs, and further, the photocarriers are accelerated by the applied voltage, so that an instantaneous current flows. An electromagnetic wave (ETHz (t) ∝∂J / ∂t) proportional to the time derivative of this current is generated as a terahertz wave pulse on the electrodes 34 and 35 and is radiated by the silicon lens 32. The LT-GaAs substrate 33 preferably has a carrier lifetime of several psec.

  FIG. 5 is a perspective view illustrating a detailed example of the reception optical switch 8. The reception optical switch 8 has basically the same structure as the transmission optical switch 4. The difference from the transmission optical switch is that an ammeter 36 is connected instead of connecting the bias 5 between the electrodes 34 and 35. Actually, not the ammeter 36 but the current amplifier 9 is connected as shown in FIG. In the receiving optical switch 8, since the electrodes 34 and 35 on the LT-GaAs substrate 33, which is a GaAs substrate grown at a low temperature, act as a minute dipole antenna, the terahertz wave focused by the silicon lens 32 and the laser focusing lens 31 are used. By receiving the focused pulse 13 for synchronous detection, the terahertz wave is caused to act as a minute dipole antenna formed between the electrodes 34 and 35, converted into a photocurrent generated in the antenna, and a terahertz wave pulse is received. Synchronous detection is performed to detect this current waveform.

  Here, the principle of synchronous detection will be described. When the pulse width of the synchronous detection pulse light 13 is, for example, 300 fsec, that is, the time gate can perform synchronous detection in a time shorter than 300 fsec (resolution of about 30 fsec). When the terahertz wave pulse width is set to 1000 fsec, for example, sampling is performed with the time gate being gradually delayed by moving the mirror 7 of FIG. 2 little by little. By connecting the sample points thus sampled, the waveform of the terahertz wave pulse can be observed. This technique is called terahertz time domain spectroscopy (TDS).

  Next, the actual operation will be described in two steps. First, for synchronous detection, the propagation optical path length of the terahertz wave is made equal to the optical path length for synchronous detection. That is, the propagation optical path length of the terahertz wave is obtained by adding the round trip distance from the point where the femtosecond optical pulse is divided into two by the half mirror 3 to the measurement target M via the transmission optical switch 4. The optical path for synchronous detection is an optical path length incident on the receiving optical switch 8 through the mirror 6 and the mirror 7 from the point where the femtosecond pulse is divided into two by the half mirror 3. The position of the mirror 7 is adjusted so that the propagation optical path length of the terahertz wave is equal to the optical path length for synchronous detection.

  Next, in order to observe the terahertz wave pulse, the delay time is scanned by moving the position of the mirror 7 which is a synchronous detection scanner. In order to obtain a resolution of about 30 fsec, an optical path displacement operation of 10 μm is performed per step. The maximum amount of displacement is determined by the required acquisition time of the pulse waveform. For example, when sampling a waveform for 100 psec, the maximum value of the amount of displacement is set to 30 mm based on the speed of light.

  Finally, an interval time between sampling points is determined based on the amount of displacement per step and the speed of light, and a terahertz wave reflection waveform is detected based on the amplitude at each sampling point. This portion is the waveform detector 10 in FIG.

  Next, estimation of road surface conditions using reflection of terahertz wave pulses will be described. As shown in FIG. 2, it is assumed that the measurement object M includes a material M2 (for example, concrete) on which a layer of the material M1 (for example, ice or snow) is formed. When this measurement object M is irradiated with a terahertz wave pulse, a part of the terahertz wave is reflected at the boundary surface B1 which is a boundary between air and the substance M1, and the rest enters the inside of the substance M1. The terahertz wave pulse that has entered the inside of the substance M1 reaches the boundary surface B2, which is the boundary between the substance M1 and the substance M2, while being absorbed by the substance M1, and a part of it is reflected, and the rest is absorbed by the substance M2.

  Accordingly, the waveform detection unit 10 outputs the waveform 21 reflected by the boundary surface B1 and the waveform 22 reflected by the boundary surface B2. Actually, a waveform having a small amplitude continues after the waveform 22 due to multiple reflection, but these may be ignored. The time difference Δt between the waveform 21 and the waveform 22 is expressed by the following equation, where D is the thickness of the substance M1, ng is its refractive index, and c is the speed of light.

Δt = (1 / c) × 2 ng × D
When the thickness D is 0, in other words, when the measurement object M is not in a laminated state, Δt is 0, there is no time difference between the waveform 21 and the waveform 22, and only one reflected waveform type is detected. It is clear. Therefore, it is possible to determine whether the road surface state is a laminated state or a non-laminated state based on the number of types of the reflected waveform, and measure the thickness D of the laminated layer formed on the road pavement based on the reflected waveform Δt. can do.

  The correspondence between FIG. 1 and FIG. 2 is as follows. The generator 101 and the transmitter 102 correspond to the transmission optical switch 4, the receiver 103 corresponds to the reception optical switch 8, the current amplifier 9, and the waveform detection unit 104 correspond to the waveform detection unit 10, respectively. Further, the angle measurement / setting unit 105, the reflection boundary surface position measurement unit 106, the waveform feature extraction unit 107, and the road surface condition estimation unit 108 in FIG. 1 are realized by the microcomputer 11 in FIG. For this reason, the microcomputer 11 includes a program for measuring an angle θ between the measurement target M and the transmission / reception surface from a combination of one or more of a camera, a laser radar, an acceleration sensor, a known stage, and sensor installation conditions. A program for measuring the distance between the measuring object M and the transmitter / receiver from a combination of at least one of a camera, laser radar, acceleration sensor, known stage and sensor installation conditions, and a waveform detected by the waveform detector 10 A program for extracting waveform features based on the angle θ and a program for estimating road surface conditions based on the extracted waveform features are provided.

  FIG. 3 is a configuration diagram illustrating a configuration of a modified example of the first embodiment when the electromagnetic wave is a terahertz wave. Instead of the half mirror 3, the mirror 6 and the mirror 7 of FIG. 2, the femtosecond pulse laser 15 for generating the synchronous detection pulse light 13, and the femtosecond pulse laser 2 and the femtosecond pulse laser 15 are different from each other. And a timing control unit 14 for controlling the difference between the pulse generation repetition periods to be constant.

  In the configuration of FIG. 2, the time-delayed scanning of the synchronous detection pulsed light 13 is performed by moving the mirror 7. In the modified example of FIG. 3, the excitation pulsed light 12 generated by the femtosecond pulsed laser 2 is used. On the other hand, time-delayed scanning that sequentially shifts the timing of the synchronous detection pulsed light 13 generated by the femtosecond pulse laser 15 is performed by electronic control. This eliminates the need for a variable optical path length for delaying the synchronous detection pulsed light 13 inside the road surface condition estimating apparatus 1, reducing the size of the road surface condition estimating apparatus 1 and improving the vehicle mountability.

  FIG. 6 is a flowchart for explaining the operation of the road surface condition estimation apparatus 1 according to the first embodiment. First, in step (hereinafter, step is abbreviated as S) 10, femtosecond pulse light is repeatedly generated by a generator 101 at a predetermined cycle, and a terahertz wave pulse is transmitted to a measurement object M by a transmitter 102. Next, in S <b> 12, the receiver 103 receives the reflected terahertz wave pulse from the measurement target M based on the timing generated by the generator 101. Then, the waveform detector 104 reconstructs and detects the received waveform.

  Next, in S14, the angle measurement / setting unit 105 measures the angle of the boundary surface based on the received waveform, or sets the angle of the transmitter 102 and the receiver 103 with respect to the vehicle body, thereby transmitting / receiving the boundary surfaces B1, B2. Measure the angle to the setting surface. The reflection boundary surface position measurement unit 106 measures the positions of the boundary surfaces B1 and B2.

  Next, in S16, the waveform feature extraction unit 107 extracts the feature of the reflected waveform according to the angle of the boundary surface and the detected waveform, and estimates the road surface condition based on the extracted feature. Specifically, for example, as shown in FIG. 8, the types of reflection surfaces are classified into six types according to the types of reflection surfaces and the angles between the transmission / reception surfaces and the reflection surfaces. This classification includes two classifications: the reflection surface is a scattering surface or a smooth surface, and the reflection surface and the transmission / reception surface are parallel reflection, regular reflection, 5 ° oblique incidence, or 10 ° oblique incidence. FIG. 8 is a graph showing the intensity of the reflected wave for 2 × 3 = 6 classifications.

  When the reflecting surface is a scattering surface, the amplitude of the reflected wave is almost the same and does not change in any of the regular reflection, 5 ° oblique incidence, and 10 ° oblique incidence. However, in the case of a smooth surface, regular reflection has the highest reflection intensity, and the intensity of the reflected wave decreases as the angle between the reflection surface and the transmission / reception surface increases. Therefore, the angle of the transmission / reception surface provided with the transmitter 102 and the receiver 103 is set to three types of angles: a vehicle body vertical downward (0 °), an angle inclined by 5 ° from the vertical downward, and an angle inclined by 10 ° from the vertical downward. It can be set by the angle measurement / setting unit 105. Then, by measuring the reflection intensity of the terahertz wave at each angle of 0 °, 5 °, and 10 °, it can be estimated whether the road surface is a scattering surface or a smooth surface.

  Further, as shown in FIG. 7, the reflected wave amplitude value output by the waveform detector 104 is increased or decreased based on the directivity characteristics of the terahertz wave transmitted by the transmission optical switch 4 or the transmitter 102 and the known atmospheric propagation attenuation. By performing the correction, the feature amount can be extracted with higher accuracy. That is, the radiation intensity in the direction perpendicular to the antenna surface of the transmission optical switch 4 or the transmitter 102 which is a terahertz wave transmission antenna, in FIG. 7, the specular reflection direction, and the vertical downward direction of the transmitter 102 mounted on the vehicle body. If 1.0, the radiation intensity attenuates according to the radiation angle. Similarly, the sensitivity of the receiver 103 also decreases with respect to the reflected wave incident on the receiver 103 from an oblique direction. For this reason, the received intensity at 5 ° oblique incidence and 10 ° oblique incidence is corrected by the radiation intensity distribution measured in advance.

  In addition, the reflection from the oblique direction is (1 / cosθ) times the length of the path returning from the transmitter 102 to the receiver 103, and this length is increased, compared to the reflection from the regular reflection surface vertically below. The amount of electromagnetic wave absorption by the air is increased and attenuated by this amount, so this amount is also corrected.

  According to the first embodiment described above, even if the distance from the sensor to the road surface changes due to vehicle behavior, the road surface condition can be accurately estimated based on the transmission direction of the electromagnetic wave and the characteristics of the received reflected wave. effective.

  Further, according to the first embodiment, since the terahertz wave pulse is used as the electromagnetic wave, there is an effect that the road surface condition can be accurately estimated even when the road surface is in a stacked state due to snow accumulation or freezing.

  Further, according to the first embodiment, there is an effect that it is possible to estimate whether the road surface is a smooth surface or a scattering surface by changing the angle at which the electromagnetic wave is applied to the road surface and measuring the intensity of the reflected wave.

  FIG. 9 is a block diagram showing a configuration of the second embodiment of the road surface condition estimating apparatus according to the present invention. In the present embodiment, a reflected waveform correction unit 109 is added to the configuration of the first embodiment. Since other configurations are the same as those in FIG. 1, the same components are denoted by the same reference numerals, and redundant description is omitted.

  The reflected waveform correcting unit 109 is a component that corrects the reflected waveform based on the waveform feature extracted by the waveform feature extracting unit 107.

  Next, the operation of this embodiment will be described with reference to the flowchart of FIG. S10 to S16 are the same as those in the first embodiment shown in FIG. Next, a different part from Example 1 is demonstrated based on FIG. In S18, the reflected waveform correcting unit 109 corrects the reflected waveform based on the reflected waveform feature extracted by the waveform feature extracting unit 107. Specifically, in the case of regular reflection, the reflected waveform is highly similar to the transmission waveform, and therefore, the synthesis of a plurality of waveforms corrects the reflected wave by matching the time with matching using the transmission waveform as a model. In the case of reflection on the scattering surface, the reflection waveform is low in similarity with the transmission waveform, and the scattering waveform is difficult to be restored when combined for a plurality of hours. From the result of transmission / reception with the difference in the angle setting of the three transmission / reception surfaces, the reflection surface is identified as a scatterer, and the reflectance is calculated by integration.

  According to the second embodiment described above, even if the distance from the sensor to the road surface changes due to vehicle behavior, the road surface condition can be accurately estimated based on the electromagnetic wave transmission direction and the characteristics of the received reflected wave. effective.

  Further, according to the second embodiment, since the terahertz wave pulse is used as the electromagnetic wave, there is an effect that the road surface condition can be accurately estimated even when the road surface is in a stacked state due to snow accumulation or freezing.

  Further, according to the second embodiment, there is an effect that it is possible to estimate whether the road surface is a smooth surface or a scattering surface by changing the angle at which the electromagnetic wave is applied to the road surface and measuring the intensity of the reflected wave.

  Furthermore, according to the second embodiment, since the reflected waveform is corrected based on the characteristics of the reflected waveform, the road surface condition can be estimated more accurately.

  FIG. 11: is a block diagram which shows the structure of Example 3 of the road surface condition estimation apparatus which concerns on this invention. In this embodiment, a vehicle momentum calculation unit 110 and a scattering calculation unit 111 are added to the configuration of the first embodiment. Since other configurations are the same as those in FIG. 1, the same components are denoted by the same reference numerals, and redundant description is omitted.

  The vehicle momentum calculation unit 110 is connected to the angle measurement / setting unit 105 and the reflective boundary surface position measurement unit 106, and calculates the pitching, rolling, and yawing of the vehicle based on vehicle speed, three-axis acceleration, steering, acceleration / deceleration operations, and the like. To do.

  The scattering calculation unit 111 is connected to the waveform detection unit 104, the angle measurement / setting unit 105, the reflection boundary surface position measurement unit 106, and the road surface condition estimation unit 108. Then, the scattering calculation unit 111 calculates the degree of scattering of the reflected wave from the measured or set angle of the transmitting / receiving surface, the position of the reflecting surface, and the reflected waveform.

  Next, the operation of the third embodiment will be described with reference to the flowchart of FIG. The operations in S10 to S12 are the same as those in the first embodiment. In S20, the vehicle momentum calculation unit 110 calculates the pitching, rolling, and yawing of the vehicle, and the angle measurement / setting unit 105 measures the angle difference between the road surface vertical direction and the transmission surface vertical direction between the road surface and the transmission / reception surface. Then, the reflection boundary surface position measurement unit 106 measures the distance between the transmission / reception surface and the road surface, and sends it to the scattering calculation unit 111 as reflection angle information of the obtained reflected wave.

  Next, in S <b> 22, the scattering calculation unit 111 calculates the degree of scattering from the received waveform and angle information detected by the waveform detection unit 104. At this time, if a past reflected wave and angle are used for the calculation, the determination can be made with higher accuracy. In addition, because of the terahertz TDS method, when there are boundary surfaces B1 and B2, it is possible to detect with higher accuracy if the road surface stacking information is individually determined.

  Next, in S24, the road surface condition estimation unit 108 refers to a plurality of road surface state models stored in advance as shown in FIG. 13, and determines the degree of scattering of the reflected wave reflected by the measurement object M and the type of the reflected waveform. The road surface condition is estimated according to the number.

  In FIG. 13, when the road surface condition is a standard dry road surface, it is a scattering surface, the scattering degree is the largest (scattering degree 1), it is a non-laminated surface, and the reflected waveform is as shown in FIGS. Since only the waveform 21 is detected and the waveform 22 is not detected, the number of waveform types is one.

  When the road surface condition is a paint-type white line, it is a smooth surface, the degree of scattering is the second largest (scattering degree 2), it is a non-laminated surface, and only the waveform 21 of FIGS. Since 22 is not detected, the number of waveform types is one.

  When the road surface condition is a melt-type white line, it is a smooth surface, the degree of scattering is the second smallest (scattering degree 3), a non-laminated surface, and only the waveform 21 in FIGS. Since 22 is not detected, the number of waveform types is one.

  When the road surface condition is wet, the surface is smooth, the degree of scattering is the smallest (scattering degree 4), the surface is a non-laminated surface, and only the waveform 21 in FIGS. 2 and 3 is detected, and the waveform 22 is not detected. Therefore, the number of waveform types is one.

  When the road surface condition is snowy, it is a scattering surface, the scattering degree is the largest (scattering degree 1), the laminated surface, and the reflected waveforms are detected as waveforms 21 and 22 in FIGS. Is 2.

  When the road surface condition is frozen, it is a scattering surface, the degree of scattering is the second largest (scattering degree 2), it is a laminated surface, and the reflected waveforms are detected as waveforms 21 and 22 in FIGS. Is two.

  FIG. 14 is a side view of a vehicle equipped with the road surface condition estimating apparatus of the present invention. A transmitter 102 and a receiver 103 are installed at the position of the side mirror toward the vertically lower side of the vehicle body. The vehicle motion due to the unevenness of the road surface shows a state in which an inclination θ between the transmission / reception surface provided with the transmitter 102 and the receiver 103 and the road surface is formed.

  In the present embodiment, the angle measurement / setting unit 105 in FIG. 11 can obtain the angle θ in FIG. 14 by the pitching or rolling of the vehicle calculated by the vehicle momentum calculation unit 110.

  FIG. 15 is a plan view showing mounting positions of the transmitter 102 and the receiver 103 in FIG. 11 on the vehicle body 50. As the mounting positions, a position 51 of the left side mirror, positions 52, 53, 54, 55, 56 of the front part of the vehicle body, a position 57 of the right side mirror, and positions of the rear parts 58, 59 of the vehicle body are possible. Reference numerals 41 to 44 are examples of detection areas.

  According to the third embodiment described above, even if the distance from the sensor to the road surface changes due to vehicle behavior, the road surface condition can be accurately estimated based on the transmission direction of the electromagnetic wave and the characteristics of the received reflected wave. effective.

  Further, according to the third embodiment, since the terahertz wave pulse is used as the electromagnetic wave, there is an effect that the road surface condition can be accurately estimated even when the road surface is in a stacked state due to snow accumulation or freezing.

  Further, according to the third embodiment, there is an effect that it is possible to estimate whether the road surface is a smooth surface or a scattering surface by changing the angle at which the electromagnetic wave is applied to the road surface and measuring the intensity of the reflected wave.

  Further, according to the third embodiment, the degree of scattering of reflected waves is calculated, and the degree of road surface condition can be accurately estimated by comparing the degree of scattering and the number of waveform types for each road surface condition stored in advance. is there.

  FIG. 16: is a block diagram which shows the structure of Example 4 of the road surface condition estimation apparatus which concerns on this invention. In this embodiment, a waveform correction unit 112, a correction parameter calculation unit 113, a lens 114, and a direction adjustment unit 115 are added to the configuration of the third embodiment. Since other configurations are the same as those in FIG. 11, the same reference numerals are given to the same components, and redundant descriptions are omitted.

  The waveform correction unit 112 is based on the reflected waveform feature extracted by the waveform feature extraction unit 107, the beam diameter of the terahertz wave transmitted by the transmitter 102, the beam transmission direction, and the delay optical path from the generator 101a to the receiver 103. The delay time 115 is instructed to the correction parameter calculation unit 113.

  The correction parameter calculation unit 113 sets the beam diameter of the terahertz wave pulse instructed from the waveform correction unit 112, the beam transmission direction, the delay time of the delay optical path 115, and the pitching amount and rolling amount of the vehicle body from the vehicle momentum calculation unit 110. Accordingly, the beam diameter of the terahertz wave pulse, the beam transmission direction, and the length of the delay optical path 115 for synchronous detection are changed.

 The lens 114 adjusts the terahertz pulse beam diameter by changing the lens position or refractive index according to the output of the correction parameter calculation unit 113. This lens 114 may be the same as the silicon lens 32 in FIG. 4 illustrating the details of the transmission optical switch 4, or may further include a lens 114 in addition to the silicon lens 32. The lens 114 is provided with a lens position adjuster or a refractive index adjuster (not shown) that adjusts the lens position, and adjusts the size of the beam diameter formed by the terahertz wave pulse beam emitted from the transmitter 102 at the position of the road surface. .

  The lens 114 may be set to have a beam diameter that is optically close to that of parallel light, and may be a combination of several lenses instead of a convex lens. Moreover, you may combine a visible camera by using the lens material of the same refractive index as visible light.

  The direction adjuster 115 is a device that adjusts the transmission direction of the transmission wave pulse in two dimensions or three dimensions according to the output of the correction parameter calculation unit 113. For example, in the case of a shape such as a polygon rotating mirror (polygon mirror), pulse azimuth scanning is possible at high speed. Moreover, even if it is the method of moving a transmission / reception antenna and adjusting a direction mechanically, you may substitute with the antenna technique which performs the beam scanning with a phase difference according to a direction.

  Next, the operation of this embodiment will be described with reference to the flowchart of FIG. Steps S10 to S24 are the same as in the third embodiment. In S26, the waveform correction unit 112 calculates the similarity with the waveform feature for each road surface condition as shown in FIG. 13 or the reflectance of the road surface with respect to the feature amount of the reflected waveform extracted by the waveform feature extraction unit 107. The detection area is set for calculation with high accuracy and for calculating the degree of scattering. Specifically, if the reflection intensity is not sufficiently obtained due to the influence of the vehicle motion, the direction adjustment is performed so that the pulse transmission direction is adjusted in the regular reflection direction based on accumulation of time series data and angle information (not shown). To the instrument 115.

  In addition, if it is determined that the difference between the white line and the road surface is difficult to see by weather measurement or road noise measurement (not shown), and the difference in the degree of scattering needs to be made more sensitive, the beam diameter is narrowed down and small unevenness But make it possible to observe scattering. When it is determined that the difference between the white line and the road surface is easy to see according to a means such as road noise measurement (not shown), the beam diameter is expanded and a wider range is observed.

  In addition, for example, when the distance between the road surface and the transmission / reception surface changes greatly, such as when the load balance of the vehicle is poor or when the unevenness of the vehicle is extremely large and the pitching effect of the vehicle extends over a long period, observation is performed with the delay optical path 115. Change the region and observation center distance. Instead of using the delay optical path 115, a method of changing the pulse train of the generator as shown in “Japanese Patent Application Laid-Open No. 2007-292701; Waveform Observation Method and Waveform Observation Device” by the present inventor may be taken.

  According to the fourth embodiment described above, even if the distance from the sensor to the road surface changes due to vehicle behavior, the road surface condition can be accurately estimated based on the transmission direction of the electromagnetic wave and the characteristics of the received reflected wave. effective.

  Further, according to the fourth embodiment, since the terahertz wave pulse is used as the electromagnetic wave, there is an effect that the road surface condition can be accurately estimated even when the road surface is in a stacked state due to snow accumulation or freezing.

  Further, according to the fourth embodiment, there is an effect that it is possible to estimate whether the road surface is a smooth surface or a scattering surface by changing the angle at which the electromagnetic wave is irradiated onto the road surface and measuring the intensity of the reflected wave.

  According to the fourth embodiment, the degree of scattering of reflected waves is calculated, and the degree of road surface condition can be accurately estimated by comparing the degree of scattering and the number of waveform types for each road surface condition stored in advance. is there.

  Furthermore, according to the fourth embodiment, the terahertz wave beam diameter, the beam transmission direction, and the delay optical path length for synchronous detection can be corrected according to the reflection state of the road surface. Even if it is extremely bad, the road surface condition can be estimated accurately.

DESCRIPTION OF SYMBOLS 1 Road surface condition estimation apparatus 101 Generator 102 Transmitter 103 Receiver 104 Waveform detection part 105 Angle measurement / setting part 106 Reflective boundary surface position measurement part 107 Waveform feature extraction part 108 Road surface condition estimation part

Claims (8)

Electromagnetic wave generating means for generating electromagnetic waves;
Transmission means for transmitting electromagnetic waves to the road surface;
Receiving means for receiving electromagnetic waves reflected on the road surface;
Waveform detection means for detecting the waveform of the received electromagnetic wave;
An angle measuring / setting means for measuring or setting an angle between the road surface and the transmitting means;
Waveform feature extraction means for extracting features of the waveform based on the waveform detected by the waveform detection means and the angle measured or set by the angle measurement / setting means;
Road surface condition estimating means for estimating the road surface condition based on the characteristics of the waveform;
A road surface condition estimating apparatus comprising: The waveform feature extraction means extracts the intensity of the waveform as a waveform feature,
The road surface state estimation device according to claim 1, wherein the road surface state estimation unit estimates the road surface state based on the angle and the intensity of the waveform.   The road surface state estimation apparatus according to claim 2, further comprising a reflected waveform correction unit that corrects a waveform reflected on the road surface based on the waveform feature extracted by the waveform feature extraction unit. The waveform feature extraction means further extracts the number of types of the waveform as waveform features,
The road surface state estimation device according to claim 2 or 3, wherein the road surface state estimation unit estimates the road surface state based on the number of types of the waveform. A scatter calculator that calculates the degree of scattering of the waveform detected by the waveform detector;
5. The road surface state estimation device according to claim 2, wherein the road surface state estimation unit estimates the road surface state based on a degree of scattering of the waveform.   The road surface condition estimating means determines whether the road surface condition is frozen, snowy, wet, or dry, or a white line portion of the road surface, based on the number of types of the waveform and the degree of scattering of the waveform. The road surface state estimating device according to claim 5, wherein the road surface state estimating device is estimated.   The road surface state estimation device according to any one of claims 1 to 6, wherein the electromagnetic wave is a pulse wave in a terahertz band of 0.1 THz to 10 THz. In the road surface condition estimation method for estimating the road surface condition by transmitting the electromagnetic wave to the road surface and receiving the electromagnetic wave reflected on the road surface,
Detect the waveform of the received electromagnetic wave,
Measure or set the angle between the road surface and the electromagnetic wave transmission direction,
Based on the detected waveform and the measured or set angle, extract the characteristics of the waveform,
A road surface state estimation method, wherein a road surface state is estimated based on the extracted waveform characteristics.

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