Abstract:
The present invention relates to the measurement of the depth of a contaminant, e.g. snow, found on a roadway or runway from a moving vehicle by measuring the distance between where a beam of light hits the upper surface of the contaminant and where the beam of light should have hit the roadway or runway based on the position of the light source. To eliminate the effects of pitch and roll on the measurements a second light source provides a reference spot, whereby the contaminant depth calculations can be performed independent of the distance between the roadway or runway and the light sources. A video recording device, such as a digital camera, is used to capture images of the spots, whereby the distances can be measured by adding the number of pixels between the spots in the images. The present invention can also be used for determining the surface texture/roughness and the coefficient of friction of the roadway or runway by increasing the sensitivity of the recording device to capture minute changes in relative spot position, and by utilizing complex signal processing to correlate the changes in relative spot position to surface texture/roughness.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
   The present invention claims priority from U.S. patent application Ser. No. 60/539,113 filed Jan. 27, 2004, which is incorporated herein by reference. 

   TECHNICAL FIELD 
   The present invention relates to determining the properties, e.g. rolling resistance of a surface, and in particular to determining the type and/or depth of a contaminant on a roadway or a runway. 
   BACKGROUND OF THE INVENTION 
   Measuring the surface properties of roadways, and in particular runways, is becoming an important part of travel safety, and in determining when and what kind of surface maintenance is required. Aircraft pilots require up to the minute runway condition reports, including the depth of the snow and the consistency, e.g. powder or slush. Devices for measuring the depth of snow range from in-situ sensors, such as those disclosed in German Patent Publications Nos. 3204477 published May 5, 1983 in the name of Wilfried Fritzshe, and 3317298 published Jan. 3, 1985 in the name of Zillober et al, and U.S. Pat. No. 5,686,841 issued Nov. 11, 1997 to Stolarczyk to portable probes for inserting into the snow, such as those disclosed in German Patent Publication No. 19503017, published Sep. 28, 1995, and U.S. Pat. No. 5,864,059 issued Jan. 26, 1999 to Sturm et al. Japanese Patent Publication No. 2000121749 published Apr. 28, 2000 to Taminoe et al, discloses a snow depth measuring device that measures the phase difference between a light directed at the snow and that of the reflected light. All of the aforementioned systems simply measure the snow in a single spot, and therefore require multiple measurements to obtain, at best, an average value. 
   Vehicle mounted systems for measuring the surface roughness of roadways are disclosed in U.S. Patent Publication 2003/137673 published Jul. 24, 2003 in the name of Cox et al, and Swiss Patent No. 666349 issued Jul. 15, 1988 to Slavko Mesaric. Cox et al relies on phase profilometry, i.e. uses shadows for contrasting the surface, to generate a 3-D profile of a surface. Mesaric, on the other hand, measures the distortion of light strips marked along the surface of the road. Neither system provides a simple and easy system for measuring the characteristics of a surface, in particular snow or contaminant depth, while moving along the surface thereof. 
   An object of the present invention is to overcome the shortcomings of the prior art devices by providing a relatively inexpensive and simple device for measuring the surface characteristics of a roadway or runway, while driving thereon. 
   SUMMARY OF THE INVENTION 
   Accordingly, the present invention relates to a device for analyzing a characteristic of a material having an upper surface comprising: 
   a first light source for directing a first beam of light at a first beam angle onto the upper surface forming a first spot; 
   an image recording device for capturing an image of the first spot on the upper surface; and 
   computational means for determining the characteristic of the material based on the position of the first spot in the image relative to a reference point. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The invention will be described in greater detail with reference to the accompanying drawings which represent preferred embodiments thereof, wherein: 
       FIG. 1  illustrates a first embodiment of the present invention mounted on the rear bumper of a vehicle; 
       FIG. 2  is a schematic representation of the area around the vehicle tire track of  FIG. 1 ; 
       FIG. 3  illustrates a second embodiment of the present invention mounted on the rear bumper of a vehicle; 
       FIG. 4  schematically represents the relative relationships between the elements of the embodiment of  FIG. 2 ; 
       FIG. 5  illustrates a response signal from the embodiment of  FIGS. 3 and 4 ; 
       FIG. 6  illustrates the embodiment of  FIGS. 2 and 3  mounted on the roof of a vehicle; 
       FIG. 7  illustrates an alternative to the embodiment of  FIG. 6  with an axle mounted reference point; 
       FIG. 8  illustrates a third embodiment of the present invention mounted on the rear bumper of a vehicle; 
       FIG. 9  schematically represents the relative relationships between the elements of the embodiment of  FIG. 8 ; and 
       FIG. 10  illustrates a combination of the second and third embodiments. 
   

   DETAILED DESCRIPTION 
   With reference to  FIGS. 1 to 5 , the surface property measuring system according to the present invention, generally indicated at  1 , is ideally suited for measuring various characteristics, e.g. kind, depth and consistency, of a contaminant  2 , e.g. snow or water, found on roadway or a runway  3  from a moving vehicle  4 . 
   A simple embodiment of the present invention for measuring contaminant depth is illustrated in  FIG. 1 , and includes a spot light source  5 , such as an LED, laser or lamp assembly, and an image viewing and recording device  6 , such as a video camera, a digital camera or an imaging charge-coupled device (CCD) array mounted on a frame  7 . With reference to  FIG. 2 , if the spot source  5  is mounted on the vehicle  4 , e.g. to bumper or hitch  8 , at a predetermined distance h above the roadway or runway  3  and angled at a predetermined (non 90°) angle θ, the distance DP to where the spot light beam  9  would be expected to intersect the roadway or runway  3  can be calculated, i.e. DP=h tan θ, and stored in an operating computer system  11 . Preferably, the axis of the recording device  6  is positioned in line with the point D. Accordingly, the point D, e.g. the axis of the recording device  6 , becomes a theoretical reference point. In operation, as the vehicle drives over the roadway or runway  3 , the spot light beam  9  will intersect the upper surface of the contaminant  2  forming a spot, approximately 1 mm to 200 mm in diameter, at position L. The recording device  6  captures an image of the spot from the spot light beam  9  for comparison with the reference point D. Having already determined the position of reference point D, the distance DL can then be determined by counting the number of pixels therebetween, and the depth d of the contaminant can be calculated, e.g. d=DL/tan θ. The position of the recording device  6  will also have to be factored into the final calculation, if it is not directly over the spot created by the spot light beam  9 . 
   To supplement the depth calculation, an additional light source  12  is provided to illuminate a tire track  13  left by the wheels  14  of the vehicle  4 . If the recording device  6  is positioned over the tire track  13  a visual image of the cross-section of the contaminant  2  can be transmitted to the driver of the vehicle  4  and even to the central data collection/distribution center. 
   Unfortunately, the aforementioned system does not compensate for the vertical and axial roll of the vehicle  4 , which will change the distance h between the light source  5  and the roadway or runway  3 , and therefore the reference point D, making the subsequent calculation of depth d erroneous. An inclinometer or other suitable device (not shown) can be disposed on the vehicle proximate to the light source  5  to provide an indication that the light source  5  has moved relative to the ground for modifying the above-identified calculation. A second embodiment of the present invention generally indicated by  21 , illustrated in  FIGS. 3 to 7 , also overcomes this shortcoming by providing a second spot light source  16  adjacent the first spot light source  5  on the frame  7  for directing a second spot light beam  22  into the tire track  13  created by the wheels  14  of the vehicle  4 . The second spot light beam  22  creates a second spot at position R, which becomes a second reference point from which the distance LD can be determined without calculating the distance DP. Positioning the two spot light sources  5  and  12  in close proximity enables the depth d calculation to be performed independently of the actual height h. While the second spot R effectively indicates the position of the roadway or runway  3 , i.e. the lower surface of the contaminant  2 , correction factors, accounting for the thin layer of contaminant material compacted in the tire track  13 , can be used to provide an even more accurate depth calculation. The correction factors would depend on the contaminant material, e.g. water, powder snow, slushy snow, and on the calculated depth d. 
   With particular reference to  FIG. 4 , the distance DL can be determined by subtracting the distance between the spots LR from the total distance DR. Accordingly, the depth d becomes d=(DR−LR)/tan α. If the height h was constant, the distance DR could be determined, as above, by simply determining the position of the theoretical reference point D. However, since the height h is not constant an alternative calculation must be performed by operating computer system  26 .
 
Starting with  d =( DR−LR )/tan α  (1)
 
 DR=DP+PQ−RQ   (2)
 
   Since RQ=h tan β and DP=h tan α
 
 DR=h  (tan α−tan β)+ PQ   (3)
 
   Since h−d=(LO+OP)/tan α
 
therefore  h =( LO+OP )/tan α+ d   (4)
         substituting (4) into (3) gives
 
 DR =( LO+OP )(tan α−tan β)/tan α+ d (tan α−tan β)+ PQ   (5)
       

   Substituting (5) into (1) gives
 
 d =( LO+OP )(tan α−tan β)/tan 2   α+d (tan α−tan β)/tan α+ PQ /tan α− LR /tan α
         isolating d gives
 
 d =(−( LO+OP )(tan α−tan β)− PQ  tan α+ LR  tan α)/(tan α tan β)
       

   Alternatively
 
Since  RQ=h  tan β= OQ−OR, h =( OQ−OR )/tan β  (6)
 
   The distance between Laser  1  spot and M=(h-d)tana=LP=LR+RP, and
 
 RP=OQ−OR−PQ  then
 
 LP=LR+OQ−OR−PQ=h  tan α− d  tan α  (7)
 
   Whereby substituting (6) into (7) and solving for d gives
 
 d =(( OR (tan β+tan α)− LR  tan β+ PQ  tan β+ OQ (tan α−tan β))/(tan α tan α)
 
   If α=β then
 
 d =(2 OR−LR+PQ )/tan α
 
   Accordingly, the depth d of the contaminant can be determined from the distances between the spots LO, LR and/or OR, i.e. the number of pixels in the image, along with the equipment configuration constants α, β, OP, PQ, and OQ independent of the height h. 
   A response signal is plotted in  FIG. 5 , which illustrates a typical example obtained from a 300 m stretch of roadway or runway. The upper portion of the signal contains many local peaks and valleys indicative of the surface texture of the contaminant  2 . This portion of the signal is averaged out by the operating computer system  26  to obtain an average snow depth. The coverage of the roadway or runway  3 , i.e. the % of roadway or runway with contaminant  2 , can also be calculated from the response signal illustrated in  FIG. 5 , by simply adding all of the points with snow along the response signal (or zero points without snow) and dividing by the total distance traveled during measurement. 
   A slightly different embodiment is illustrated in  FIG. 6 , in which a frame  27  is mounted on a roof  28  of the vehicle  4 , instead of the bumper  8 . The first and second spot light sources  5  and  12 , mounted on the frame  27 , still direct their beams of light  9  and  22 , respectively, onto the surface of the contaminant  2  and into the tire track  13 , respectively. The recording device  6  can also be positioned on the frame  27  for capturing the positions of the spots L and R from beams  9  and  22 . 
     FIG. 7  illustrates still another embodiment of the present invention, with the recording device  6  and the spot light sources  5  and  12  mounted on the frame  27  secured on the roof  28 , as in  FIG. 5 ; however, the second spot light source  12  is configured to direct a beam of light  32  onto a cylinder  33  mounted on an axle of one of the wheels  14 , while the first spot light source  5  directs the beam of light  9  onto the contaminant  2  adjacent the vehicle  4 . In this embodiment, the distance between the cylinder  33  and the surface  3  is assumed to be constant, whereby the depth d can be determined by the operating computer system  26  from equations similar to those above using the relative positions of the spots determined from the recording device  6 . 
   All of the aforementioned embodiments can also be used to measure the surface roughness and texture of any surface, e.g. roadway or runway, by modifying the spatial resolution and increasing the sensitivity of the recording device  6  to measure minute fluctuations in depth, assuming the spot size is less than the required spatial resolution of the textured surface, e.g. for pavement 0.1 mm to 1.0 mm. The number of frames recorded per second may have to increased, and the recorded signal will have to be processed using dedicated techniques, such as signal frequency filtering and Fast Fourier Transformation (FFT) analysis. Accordingly, instead of measuring the depth of a contaminant relative to the roadway or runway, the system will measure the surface texture or roughness of the roadway or runway relative to a flat reference plane. In the single spot embodiment, the distance between the spot and a fixed point is measured, while in the dual spot embodiments the distance between the two spots is measured. The signal response for this embodiment will look like the upper portion of the signal response from  FIG. 5 , i.e. a series of local maxima and minima, which indicate when the two spots are the farthest apart and closest together. For example: a point at a maximum could represent the situation when the first spot is directed onto a peak on the surface and the second spot is directed into a valley, while a minimum could represent the situation when the first spot is directed into a valley and the second spot is directed onto a peak. 
   The roughness and texture of the surface can be determined from the measured signal analysis by using specific algorithms based on experimental correlations. The frequency of the vehicle&#39;s movement can be filtered out of the signal to provide a more accurate representation of the surface roughness and texture. A predicted friction coefficient for the surface can be determined based on algorithms developed from statistical (correlation/regression) analyses concerning the surface roughness and texture data in relation to friction measurement data. 
   With reference to  FIGS. 8 and 9 , the type of the contaminant  42  and the depth d of the contaminant above the surface  43  can be determined with another embodiment of the present invention generally indicated at  41  mounted on vehicle  44 . The first step is to mount a light source  45  and a recording device  46  attached to a frame  47 , such that a beam of light  49  will reflect off of the surface of the contaminant  42  into the recording device  46 . An optical filter  48   a  can be placed in the path of the beam of light  49  to ensure a specific band of light is incident on the contaminant layer  42 , i.e. to ensure that the contaminant layer, e.g. hydrocarbon, fluoresces. Additional spectral filters  48   b  are positioned in the paths of the reflected light beams for measuring the spectral transmission and/or the fluorescence of the contaminant  42 . Using the spectral and/or the fluorescence information, the computer operating system  51  can determine the type of the contaminant  42 . 
   With particular reference to  FIG. 9 , the second step takes advantage of the beam of light  49  refracting in the contaminant layer  42  forming a second spot at point O 2 , which can be captured by the recording device along with the position of the first spot O 1 . Whether the computer operating system  51  determined the type of the contaminant  42  from the spectral and fluorescence responses or whether the type of the contaminant  42  was already known, the depth d of the contaminant  42  can be determined using the index of refraction of the contaminant n c , the angle α of the light source  45 , and the lateral offset OP as captured by the recording device  46  between a spot on the surface of the contaminant  42  and a spot on the surface  43 , which acts like a reference spot. Typically for water or water based materials an index of refraction of approximately 1.3 to 1.33 can be assumed.
 
Since n c =sin α/sin β and
 
d=OP/tan β
 
Then d=OP/n tan (arcsin α)
 
   Ideally the frame  47  is positioned on the longitudinal axis of the vehicle  44 , in between the tire tracks  53  left by tires  54 , so that the depth d measurement is not influenced thereby. 
   If the two spots O 1  and O 2  are too close together, i.e. the diameters of the two spots O 1  and O 2  are larger than OP/2, they smear into a single spot. Accordingly, the distance OP can be derived from the shape or profile of the single spot, in accordance with known techniques, e.g. the width at 50% of the detected radiance (Gaussian) profile of the total spot footprint is proportional with the distance OP. 
   For Example: the relationship between the total spot width (at 50% radiance profile height) and depth d of water, using a low resolution (320×240 pixels) camera SiPix DV100. Assuming α=30°. 
   
     
       
             
             
             
             
             
             
             
           
         
             
                 
                 
             
           
           
             
                 
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               Spot Image Width 
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               pixels 
             
             
                 
                 
             
           
        
       
     
   
     FIG. 10  illustrates another embodiment  51  of the present invention, similar to that of  FIGS. 3 to 7 , including a first spot light source  5   a  and a first recording device  6   a  mounted on the frame  7 , which is attached to the bumper  8  of the vehicle  4 , for measuring the depth of the contaminant  2  found on the surface  3 . The second spot light source  12  directs the second beam of light into the track  13  left by the tire  14 , thereby providing the reference spot. A third spot light source  5   b  and a second recording device  6   b  are provided: a) for redundancy, i.e. in case the first spot light source  5   a  and the first recording device  5   a  fail, b) for higher accuracy, i.e. to provide two depth measurements at every location to more accurately compensate for both the pitch and the roll of the vehicle, and/or c) for extra measurement, e.g. for determining the type of contaminant, as in the embodiments of  FIGS. 7 and 8 . 
   An additional measurement carried out by operating computer system  61  involves identifying the type of contaminant, e.g. wet/dry snow or slush, from the size, i.e. diameter, and profile shape of the laser spot, e.g. the number of pixels over the illuminated spot, using specific correlation algorithms. The denser the contaminant, the smaller the spot size relative to a reference spot size. Accordingly, an automatic and accurate measure of the contaminants  2  density can be recorded. The size of the spot can be correlated to a simple density scale for communicating to the user or to an existing density scale already in use.