JP6260444B2 - Camera device and lens cleaning method - Google Patents

Description

  The present invention relates to a camera device and a lens cleaning method.

  There is known an in-vehicle camera that removes dirt adhered by mud splashing or the like by blowing high-pressure air and high-pressure water onto the glass on the front surface of the camera provided in the vehicle body (see Patent Document 1).

JP 2001-171491 A

  However, when the camera lens is cleaned with the cleaning liquid, bubbles are generated and attached to the lens. If bubbles of the cleaning liquid remain on the lens, there is a problem that an accurate captured image cannot be obtained due to the influence of the bubbles.

  The problem to be solved by the present invention is to clean the lens so that bubbles generated during the cleaning of the lens do not remain on the lens.

  The present invention solves the above problem by increasing the interval at which the cleaning liquid is discharged when it is determined that the lens is in a predetermined bubble adhering state.

  In the present invention, when the lens is in a predetermined bubble adhering state, it is assumed that bubbles generated by the cleaning may remain on the lens, and the lens is cleaned so that bubbles are not formed on the bubbles. Thus, it is possible to obtain an accurate captured image from which the influence of bubbles is eliminated.

1 is a schematic configuration diagram of a vehicle according to an embodiment to which a three-dimensional object detection device of the present invention is applied. It is a top view (three-dimensional object detection by difference waveform information) which shows the driving state of the vehicle of FIG. It is a block diagram of the camera apparatus of FIG. 1, a lens washing | cleaning apparatus, and a solid-object detection apparatus. 4A and 4B are diagrams for explaining the outline of processing of the alignment unit in FIG. 3, in which FIG. 3A is a plan view showing a moving state of the vehicle, and FIG. It is the schematic which shows the mode of the production | generation of the difference waveform by the solid-object detection part of FIG. It is a figure which shows the small area | region divided | segmented by the solid-object detection part of FIG. It is a figure which shows an example of the histogram obtained by the solid-object detection part of FIG. It is a figure which shows the weighting by the solid-object detection part of FIG. It is a figure which shows the process by the smear detection part of FIG. 3, and the calculation process of the difference waveform by it. It is a figure which shows the other example of the histogram obtained by the solid-object detection part of FIG. FIG. 4 is a flowchart (No. 1) illustrating a three-dimensional object detection method using differential waveform information executed by the viewpoint conversion unit, the alignment unit, the smear detection unit, and the three-dimensional object detection unit of FIG. 3. FIG. 4 is a flowchart (part 2) illustrating a three-dimensional object detection method using differential waveform information executed by the viewpoint conversion unit, the alignment unit, the smear detection unit, and the three-dimensional object detection unit of FIG. 3. It is a figure (three-dimensional object detection by edge information) which shows the running state of vehicles of Drawing 1, (a) is a top view showing the positional relationship of a detection field etc., and (b) shows the positional relationship of a detection field etc. in real space. It is a perspective view shown. 4A and 4B are diagrams for explaining the operation of the luminance difference calculation unit in FIG. 3, in which FIG. 3A is a diagram illustrating a positional relationship among attention lines, reference lines, attention points, and reference points in a bird's-eye view image, and FIG. It is a figure which shows the positional relationship of the attention line, reference line, attention point, and reference point. 4A and 4B are diagrams for explaining the detailed operation of the luminance difference calculation unit in FIG. 3, in which FIG. 3A is a diagram illustrating a detection region in a bird's-eye view image, and FIG. It is a figure which shows the positional relationship of a reference point. It is a figure which shows the luminance distribution on an edge line and an edge line, (a) is a figure which shows luminance distribution when a solid object (vehicle) exists in a detection area, (b) is a solid object in a detection area It is a figure which shows the luminance distribution when not doing. FIG. 4 is a flowchart (part 1) illustrating a three-dimensional object detection method using edge information executed by a viewpoint conversion unit, a luminance difference calculation unit, an edge line detection unit, and a three-dimensional object detection unit in FIG. 3; FIG. 4 is a flowchart (part 2) illustrating a three-dimensional object detection method using edge information executed by the viewpoint conversion unit, the luminance difference calculation unit, the edge line detection unit, and the three-dimensional object detection unit of FIG. 3. It is a figure which shows the example of an image for demonstrating edge detection operation | movement. It is a figure for demonstrating the state of the lens of the camera immediately after wash | cleaning a lens. It is a figure which shows an example of the captured image immediately after wash | cleaning a lens. It is a figure for demonstrating the state of the lens of the camera after driving | running | working for a predetermined time after washing | cleaning a lens. It is a figure which shows an example of the captured image imaged after driving | running | working for the predetermined time after washing | cleaning a lens. It is a figure which shows an example of the setting of the peripheral area | region EB. It is a figure which shows an example of the division defined by distance about detection area | region A1, A2. It is a figure which shows an example of the relationship between a vehicle speed and the grade of a three-dimensional object detection suppression. It is a figure which shows an example of the relationship between brightness and the degree of suppression of three-dimensional object detection. It is a flowchart for demonstrating the 1st control procedure of the detection process of the solid object by the solid object detection apparatus which concerns on this embodiment of this invention. It is a flowchart for demonstrating the 2nd control procedure of the detection process of the solid object by the solid object detection apparatus which concerns on this embodiment of this invention. It is a flowchart for demonstrating the 3rd control procedure of the detection process of the solid object by the solid object detection apparatus which concerns on this embodiment of this invention. It is a block diagram which shows the structure of the lens cleaning apparatus of a vehicle-mounted camera. FIG. 26A and FIG. 26B are perspective views showing the configuration of a lens cleaning device for an in-vehicle camera. It is a partially broken perspective view of the lens cleaning device of the in-vehicle camera. FIG. 28A and FIG. 28B are diagrams showing a nozzle tip provided in a lens cleaning device of a vehicle-mounted camera. It is explanatory drawing which shows the arrangement | positioning relationship between the nozzle front-end | tip part provided in the lens cleaning apparatus of a vehicle-mounted camera, and a camera. 30 (a) and 30 (b) are cross-sectional views of a nozzle unit of a lens cleaning device for an in-vehicle camera. It is a figure which shows the outline | summary of the control mechanism of a lens cleaning apparatus. It is a time chart for demonstrating a lens washing | cleaning process. It is a figure which shows an example of the relationship between temperature and the space | interval of discharge timing. It is a figure which shows an example of the relationship between a speed | rate and the space | interval of discharge timing. It is a flowchart which shows the control procedure of the washing | cleaning process of the camera apparatus which concerns on this embodiment of this invention.

<First Embodiment>
FIG. 1 is a schematic configuration diagram of a vehicle according to an embodiment to which a three-dimensional object detection device 1 of the present invention is applied. The three-dimensional object detection device 1 of the present example is careful when the driver of the host vehicle V is driving. Is a device that detects, as an obstacle, other vehicles that are likely to be contacted, for example, other vehicles that may be contacted when the host vehicle V changes lanes. In particular, the three-dimensional object detection device 1 of this example detects another vehicle that travels in an adjacent lane (hereinafter also simply referred to as an adjacent lane) adjacent to the lane in which the host vehicle travels. Further, the three-dimensional object detection device 1 of the present example can calculate the detected movement distance and movement speed of the other vehicle. For this reason, in the example described below, the three-dimensional object detection device 1 is mounted on the own vehicle V, and the three-dimensional object detected around the own vehicle travels in the adjacent lane next to the lane on which the own vehicle V travels. An example of detecting a vehicle will be shown. As shown in the figure, the three-dimensional object detection device 1 of this example includes a camera 10, a vehicle speed sensor 20, a calculator 30, and a lens cleaning unit that cleans the lens 11 with a lens 11 that forms an image around the vehicle. Device 100. The camera 10 of the present embodiment captures images around the vehicle, specifically, the rear, right rear, and left rear of the vehicle. The lens cleaning device 100 will be described in the second embodiment.

  As shown in FIG. 1, the camera 10 is attached to the host vehicle V so that the optical axis is at an angle θ from the horizontal to the lower side at a height h at the rear of the host vehicle V. The camera 10 images a predetermined area in the surrounding environment of the host vehicle V from this position. In the present embodiment, there is one camera 10 provided for detecting a three-dimensional object behind the host vehicle V. However, for other purposes, for example, providing another camera for acquiring an image around the vehicle. You can also. The vehicle speed sensor 20 detects the traveling speed of the host vehicle V, and calculates the vehicle speed from the wheel speed detected by, for example, a wheel speed sensor that detects the rotational speed of the wheel. The computer 30 detects a three-dimensional object behind the vehicle, and calculates a moving distance and a moving speed for the three-dimensional object in this example.

  FIG. 2 is a plan view showing a traveling state of the host vehicle V of FIG. As shown in the figure, the camera 10 images the rear of the vehicle at a predetermined angle of view a. At this time, the angle of view a of the camera 10 is set to an angle of view at which the left and right lanes can be imaged in addition to the lane in which the host vehicle V travels. The area that can be imaged includes detection target areas A1 and A2 on the adjacent lane that is behind the host vehicle V and that is adjacent to the left and right of the travel lane of the host vehicle V. Note that the rear of the vehicle in this embodiment includes not only the rear of the vehicle but also the side of the rear of the vehicle. The area behind the imaged vehicle is set according to the angle of view of the camera 10. Although it is an example, when the right rear of the vehicle along the vehicle length direction is set to zero degrees, it can be set so as to include a region of 0 degrees to 90 degrees, preferably 0 degrees to 70 degrees on the left and right sides from the right rear direction.

  FIG. 3 is a block diagram showing details of the computer 30 of FIG. In FIG. 3, the camera 10, the vehicle speed sensor 20, the illuminance sensor 21, and the lens cleaning device 100 are also illustrated in order to clarify the connection relationship.

As shown in FIG. 3, the computer 30 includes a viewpoint conversion unit 31, an alignment unit 32, a three-dimensional object detection unit 33, a three-dimensional object determination unit 34, a lens state determination unit 38, a control unit 39, and a smear. And a detection unit 40. The computer 30 of this embodiment is a structure regarding the detection block of the solid object using difference waveform information. The computer 30 of this embodiment can also be set as the structure regarding the detection block of the solid object using edge information. In this case, in the configuration shown in FIG. 3, the luminance difference calculation unit 35, the edge line detection unit 36, and the detection block configuration A configured by the alignment unit 32 and the three-dimensional object detection unit 33 are surrounded by a broken line. The detection block configuration B including the three-dimensional object detection unit 37 can be replaced. Of course, both of the detection block configuration A and the detection block configuration B are provided, and it is possible to detect a three-dimensional object using difference waveform information and to detect a three-dimensional object using edge information. . When the detection block configuration A and the detection block configuration B are provided, either the detection block configuration A or the detection block configuration B can be operated according to environmental factors such as brightness. Each configuration will be described below.
In the present embodiment, the computer 30 of the three-dimensional object detection apparatus 1 includes the lens state determination unit 38. However, the control device 110 of the lens cleaning device 100 may include the lens state determination unit 38. In this case, the computer 30 acquires the determination result of the lens state from the lens state determination unit 38.

<Detection of three-dimensional object by differential waveform information>
The three-dimensional object detection device 1 according to the present embodiment detects a three-dimensional object existing in the right detection area or the left detection area behind the vehicle based on image information obtained by the monocular camera 1 that images the rear of the vehicle.

  The viewpoint conversion unit 31 inputs captured image data of a predetermined area obtained by imaging with the camera 10 and converts the input captured image data into a bird's-eye image data in a bird's-eye view state. The state viewed from a bird's-eye view is a state viewed from the viewpoint of a virtual camera looking down from above, for example, vertically downward. This viewpoint conversion can be executed as described in, for example, Japanese Patent Application Laid-Open No. 2008-219063. The viewpoint conversion of captured image data to bird's-eye view image data is based on the principle that a vertical edge peculiar to a three-dimensional object is converted into a straight line group passing through a specific fixed point by viewpoint conversion to bird's-eye view image data. This is because a planar object and a three-dimensional object can be distinguished if used. Note that the result of the image conversion processing by the viewpoint conversion unit 31 is also used in detection of a three-dimensional object by edge information described later.

  The alignment unit 32 sequentially inputs the bird's-eye image data obtained by the viewpoint conversion of the viewpoint conversion unit 31, and aligns the positions of the inputted bird's-eye image data at different times. 4A and 4B are diagrams for explaining the outline of the processing of the alignment unit 32, where FIG. 4A is a plan view showing the moving state of the host vehicle V, and FIG. 4B is an image showing the outline of the alignment.

  As shown in FIG. 4A, it is assumed that the host vehicle V at the current time is located at V1, and the host vehicle V one hour before is located at V2. Further, the other vehicle VX is located in the rear direction of the own vehicle V and is in parallel with the own vehicle V, the other vehicle VX at the current time is located at V3, and the other vehicle VX one hour before is located at V4. Suppose you were. Furthermore, it is assumed that the host vehicle V has moved a distance d at one time. One hour before may be a time that is past a predetermined time (for example, one control cycle) from the current time, or may be a time that is past an arbitrary time.

In this state, the bird's-eye image PB _t at the current time is as shown in Figure 4 (b). In the bird's-eye image PB _t, becomes a rectangular shape for the white line drawn on the road surface, but a relatively accurate is a plan view state, tilting occurs about the position of another vehicle VX at position V3. Similarly, with respect to the bird's-eye view image PB _{t-1 one} hour before, the white line drawn on the road surface is rectangular and is in a state of being relatively accurately viewed in plan, but about the other vehicle VX at the position V4. Falls down. As described above, the vertical edges of solid objects (including the edges that rise in the three-dimensional space from the road surface in addition to the vertical edges in the strict sense) are straight lines along the collapse direction by the viewpoint conversion processing to bird's-eye view image data. This is because the plane image on the road surface does not include a vertical edge, but such a fall does not occur even when the viewpoint is changed.

The alignment unit 32 performs alignment of the bird's-eye images PB _t and PB _t−1 as described above on the data. At this time, the alignment unit 32 is offset a bird's-eye view image PB _t-1 before one unit time, to match the position and bird's-eye view image PB _t at the current time. The image on the left side and the center image in FIG. 4B show a state that is offset by the movement distance d ′. This offset amount d ′ is a movement amount on the bird's-eye view image data corresponding to the actual movement distance d of the host vehicle V shown in FIG. It is determined based on the time until the time.

In addition, after the alignment, the alignment unit 32 takes the difference between the bird's-eye images PB _t and PB _t−1 and generates data of the difference image PD _t . Here, the pixel value of the difference image PD _t may be an absolute value of the difference between the pixel values of the bird's-eye images PB _t and PB _t−1 , and the absolute value is predetermined in order to cope with a change in illuminance environment. It may be set to “1” when the threshold value p is exceeded and “0” when the threshold value p is not exceeded. The image on the right side of FIG. 4B is the difference image PD _t . The threshold value p may be set in advance, or may be changed according to a control command corresponding to a detection result of a lens state determination unit 38 of the control unit 39 described later.

Returning to FIG. 3, the three-dimensional object detection unit 33 detects a three-dimensional object based on the data of the difference image PD _t shown in FIG. At this time, the three-dimensional object detection unit 33 of this example also calculates the movement distance of the three-dimensional object in the real space. In detecting the three-dimensional object and calculating the movement distance, the three-dimensional object detection unit 33 first generates a differential waveform. The moving distance per time of the three-dimensional object is used for calculating the moving speed of the three-dimensional object. The moving speed of the three-dimensional object can be used to determine whether or not the three-dimensional object is a vehicle.

Three-dimensional object detection unit 33 of the present embodiment when generating the differential waveform sets a detection area in the difference image PD _t. The three-dimensional object detection device 1 of the present example is another vehicle that the driver of the host vehicle V pays attention to, in particular, the lane in which the host vehicle V that may be contacted when the host vehicle V changes lanes travels. Another vehicle traveling in the adjacent lane is detected as a detection target. For this reason, in this example which detects a solid object based on image information, two detection areas are set on the right side and the left side of the host vehicle V in the image obtained by the camera 1. Specifically, in the present embodiment, rectangular detection areas A1 and A2 are set on the left and right sides behind the host vehicle V as shown in FIG. The other vehicle detected in the detection areas A1 and A2 is detected as an obstacle traveling in the adjacent lane adjacent to the lane in which the host vehicle V is traveling. Such detection areas A1 and A2 may be set from a relative position with respect to the host vehicle V, or may be set based on the position of the white line. When setting the position of the white line as a reference, the movement distance detection device may use, for example, an existing white line recognition technique.

  Further, the three-dimensional object detection unit 33 recognizes the sides (sides along the traveling direction) of the set detection areas A1 and A2 on the own vehicle V side as the ground lines L1 and L2 (FIG. 2). In general, the ground line means a line in which the three-dimensional object contacts the ground. However, in the present embodiment, the ground line is set as described above, not a line in contact with the ground. Even in this case, from experience, the difference between the ground line according to the present embodiment and the ground line obtained from the position of the other vehicle VX is not too large, and there is no problem in practical use.

FIG. 5 is a schematic diagram illustrating how a differential waveform is generated by the three-dimensional object detection unit 33 illustrated in FIG. 3. As shown in FIG. 5, the three-dimensional object detection unit 33 calculates a differential waveform from a portion corresponding to the detection areas A <b> 1 and A <b> 2 in the difference image PD _t (right diagram in FIG. 4B) calculated by the alignment unit 32. DW _t is generated. At this time, the three-dimensional object detection unit 33 generates a differential waveform DW _t along the direction in which the three-dimensional object falls by viewpoint conversion. In the example shown in FIG. 5, only the detection area A1 is described for convenience, but the difference waveform DW _t is also generated for the detection area A2 by the same procedure.

More specifically, the three-dimensional object detection unit 33 defines a line La in the direction in which the three-dimensional object falls on the data of the difference image DW _t . Then, the three-dimensional object detection unit 33 counts the number of difference pixels DP indicating a predetermined difference on the line La. Here, the difference pixel DP indicating a predetermined difference has a predetermined threshold value when the pixel value of the difference image DW _t is an absolute value of the difference between the pixel values of the bird's-eye images PB _t and PB _t−1. If the pixel value of the difference image DW _t is expressed as “0” or “1”, the pixel indicates “1”.

  The three-dimensional object detection unit 33 counts the number of difference pixels DP, and then obtains an intersection CP between the line La and the ground line L1. Then, the three-dimensional object detection unit 33 associates the intersection CP with the count number, determines the horizontal axis position based on the position of the intersection CP, that is, the position on the vertical axis in the right diagram of FIG. The axis position, that is, the position on the left-right axis in the right diagram of FIG. 5 is determined and plotted as the number of counts at the intersection CP.

Similarly, the three-dimensional object detection unit 33 defines lines Lb, Lc... In the direction in which the three-dimensional object falls, counts the number of difference pixels DP, and determines the horizontal axis position based on the position of each intersection CP. Then, the vertical axis position is determined from the count number (number of difference pixels DP) and plotted. The three-dimensional object detection unit 33 generates the differential waveform DW _t as shown in the right diagram of FIG.

As shown in the left diagram of FIG. 5, the line La and the line Lb in the direction in which the three-dimensional object collapses have different distances overlapping the detection area A1. For this reason, if the detection area A1 is filled with the difference pixels DP, the number of difference pixels DP is larger on the line La than on the line Lb. For this reason, when the three-dimensional object detection unit 33 determines the vertical axis position from the count number of the difference pixels DP, the three-dimensional object detection unit 33 is normalized based on the distance at which the lines La and Lb in the direction in which the three-dimensional object falls and the detection area A1 overlap. Turn into. As a specific example, in the left diagram of FIG. 5, there are six difference pixels DP on the line La, and there are five difference pixels DP on the line Lb. For this reason, in determining the vertical axis position from the count number in FIG. 5, the three-dimensional object detection unit 33 normalizes the count number by dividing it by the overlap distance. Thus, as shown in the difference waveform DW _t, the line La on the direction the three-dimensional object collapses, the value of the differential waveform DW _t corresponding to Lb is substantially the same.

After the generation of the differential waveform DW _t , the three-dimensional object detection unit 33 calculates the movement distance by comparison with the differential waveform DW _t−1 one time before. That is, the three-dimensional object detection unit 33 calculates the movement distance from the time change of the difference waveforms DW _t and DW _t−1 .

More specifically, the three-dimensional object detection unit 33 divides the differential waveform DW _t into a plurality of small regions DW _{t1 to} DW _tn (n is an arbitrary integer equal to or greater than 2) as shown in FIG. FIG. 6 is a diagram illustrating the small areas DW _{t1 to} DW _tn divided by the three-dimensional object detection unit 33. The small regions DW _{t1 to} DW _tn are divided so as to overlap each other, for example, as shown in FIG. For example, the small area DW _t1 and the small area DW _t2 overlap, and the small area DW _t2 and the small area DW _t3 overlap.

Next, the three-dimensional object detection unit 33 obtains an offset amount (amount of movement of the differential waveform in the horizontal axis direction (vertical direction in FIG. 6)) for each of the small regions DW _{t1 to} DW _tn . Here, the offset amount is determined from the difference between the differential waveform DW _t in the difference waveform DW _t-1 and the current time before one unit time (distance in the horizontal axis direction). At this time, three-dimensional object detection unit 33, for each small area _DW t1 _{~DW tn,} when moving the differential waveform _{DW t1} before one unit time in the horizontal axis direction, the differential waveform DW _t at the current time The position where the error is minimized (the position in the horizontal axis direction) is determined, and the amount of movement in the horizontal axis between the original position of the differential waveform DW _t-1 and the position where the error is minimized is obtained as an offset amount. Then, the three-dimensional object detection unit 33 counts the offset amount obtained for each of the small areas DW _{t1 to} DW _tn and forms a histogram.

FIG. 7 is a diagram illustrating an example of a histogram obtained by the three-dimensional object detection unit 33. As shown in FIG. 7, the offset amount, which is the amount of movement that minimizes the error between each of the small areas DW _{t1 to} DW _tn and the differential waveform DW _t-1 one time before, has some variation. For this reason, the three-dimensional object detection unit 33 forms a histogram of offset amounts including variations, and calculates a movement distance from the histogram. At this time, the three-dimensional object detection unit 33 calculates the moving distance of the three-dimensional object from the maximum value of the histogram. That is, in the example illustrated in FIG. 7, the three-dimensional object detection unit 33 calculates the offset amount indicating the maximum value of the histogram as the movement distance τ ^* . The moving distance τ ^* is a relative moving distance of the other vehicle VX with respect to the host vehicle V. For this reason, when calculating the absolute movement distance, the three-dimensional object detection unit 33 calculates the absolute movement distance based on the obtained movement distance τ ^* and the signal from the vehicle speed sensor 20.

Incidentally, the three-dimensional object detection unit 33 Upon histogram is weighted for each of a plurality of small areas _DW t1 _{~DW tn,} the offset amount determined for each small area _DW t1 _{~DW tn} histogram of counts in response to the weight May be. FIG. 8 is a diagram illustrating weighting by the three-dimensional object detection unit 33.

As shown in FIG. 8, the small region DW _m (m is an integer of 1 to n−1) is flat. That is, in the small area DW _m , the difference between the maximum value and the minimum value of the number of pixels indicating a predetermined difference is small. Three-dimensional object detection unit 33 to reduce the weight for such small area DW _m. This is because the flat small area DW _m has no characteristics and is likely to have a large error in calculating the offset amount.

On the other hand, the small area DW _{m + k} (k is an integer equal to or less than nm) is rich in undulations. That is, in the small area DW _m , the difference between the maximum value and the minimum value of the number of pixels indicating a predetermined difference is large. Three-dimensional object detection unit 33 increases the weight for such small area DW _m. This is because the small region DW _{m + k} rich in undulations is characteristic and there is a high possibility that the offset amount can be accurately calculated. By weighting in this way, the calculation accuracy of the movement distance can be improved.

Although dividing the differential waveform DW _t into a plurality of small areas DW _t1 ~DW _tn in the above embodiment in order to improve the calculation accuracy of the moving distance, if the calculation accuracy of the moving distance is not less required small regions DW _t1 It is not necessary to divide into ~ DW _tn . In this case, the three-dimensional object detection unit 33 calculates the movement distance from the offset amount of the differential waveform DW _t when the error between the differential waveform DW _t and the differential waveform DW _t−1 is minimized. That is, the method for obtaining the offset amount of the difference waveform DW _t in the difference waveform DW _t-1 and the current time before one unit time is not limited to the above disclosure.

  Returning to FIG. 3, the computer 30 includes a smear detection unit 40. The smear detection unit 40 detects a smear generation region from data of a captured image obtained by imaging with the camera 10. Since smear is a whiteout phenomenon that occurs in a CCD image sensor or the like, the smear detection unit 40 may be omitted when the camera 10 using a CMOS image sensor or the like that does not generate such smear is employed.

FIG. 9 is an image diagram for explaining the processing by the smear detection unit 40 and the calculation processing of the differential waveform DW _t thereby. First, it is assumed that data of the captured image P in which the smear S exists is input to the smear detection unit 40. At this time, the smear detection unit 40 detects the smear S from the captured image P. There are various methods for detecting the smear S. For example, in the case of a general CCD (Charge-Coupled Device) camera, the smear S is generated only in the downward direction of the image from the light source. For this reason, in this embodiment, a region having a luminance value equal to or higher than a predetermined value from the lower side of the image to the upper side of the image and continuous in the vertical direction is searched, and this is identified as a smear S generation region.

In addition, the smear detection unit 40 generates smear image SP data in which the pixel value is set to “1” for the place where the smear S occurs and the other place is set to “0”. After the generation, the smear detection unit 40 transmits the data of the smear image SP to the viewpoint conversion unit 31. In addition, the viewpoint conversion unit 31 to which the data of the smear image SP is input converts the viewpoint into a state of bird's-eye view. As a result, the viewpoint conversion unit 31 generates data of the smear bird's-eye view image SB _t . After the generation, the viewpoint conversion unit 31 transmits the data of the smear bird's-eye view image SB _t to the alignment unit 33. In addition, the viewpoint conversion unit 31 transmits the data of the smear bird's-eye view image SB _{t−1 one} hour before to the alignment unit 33.

The alignment unit 32 performs alignment of the smear bird's-eye images SB _t and SB _t−1 on the data. The specific alignment is similar to the case where the alignment of the bird's-eye images PB _t and PB _t−1 is executed on the data. Further, after the alignment, the alignment unit 32 performs a logical sum on the smear S generation region of each smear bird's-eye view image SB _t , SB _t−1 . Thereby, the alignment part 32 produces | generates the data of mask image MP. After the generation, the alignment unit 32 transmits the data of the mask image MP to the three-dimensional object detection unit 33.

The three-dimensional object detection unit 33 sets the count number of the frequency distribution to zero for the portion corresponding to the smear S generation region in the mask image MP. That is, when the differential waveform DW _t as shown in FIG. 9 is generated, the three-dimensional object detection unit 33 sets the count number SC by the smear S to zero and generates a corrected differential waveform DW _t ′. Become.

  In the present embodiment, the three-dimensional object detection unit 33 obtains the moving speed of the vehicle V (camera 10), and obtains the offset amount for the stationary object from the obtained moving speed. After obtaining the offset amount of the stationary object, the three-dimensional object detection unit 33 calculates the moving distance of the three-dimensional object after ignoring the offset amount corresponding to the stationary object among the maximum values of the histogram.

  FIG. 10 is a diagram illustrating another example of the histogram obtained by the three-dimensional object detection unit 33. When a stationary object exists in addition to the other vehicle VX within the angle of view of the camera 10, two maximum values τ1 and τ2 appear in the obtained histogram. In this case, one of the two maximum values τ1, τ2 is the offset amount of the stationary object. For this reason, the three-dimensional object detection unit 33 calculates the offset amount for the stationary object from the moving speed, ignores the maximum value corresponding to the offset amount, and calculates the moving distance of the three-dimensional object using the remaining maximum value. To do.

  Even if the offset amount corresponding to the stationary object is ignored, when there are a plurality of maximum values, it is assumed that there are a plurality of other vehicles VX within the angle of view of the camera 10. However, it is very rare that a plurality of other vehicles VX exist in the detection areas A1 and A2. For this reason, the three-dimensional object detection unit 33 stops calculating the movement distance.

Next, a solid object detection procedure based on differential waveform information will be described. 11 and 12 are flowcharts showing the three-dimensional object detection procedure of this embodiment. As shown in FIG. 11, first, the computer 30 inputs data of the image P captured by the camera 10, and generates a smear image SP by the smear detector 40 (S1). Next, the viewpoint conversion unit 31 generates data of the bird's-eye view image PB _t from the data of the captured image P from the camera 10, and also generates data of the smear bird's-eye view image SB _t from the data of the smear image SP (S2).

Then, the alignment unit 33 aligns the data of the bird's-eye view image PB _{t and} the data of the bird's-eye view image PB _{t-1 one} hour ago, and the data of the smear bird's-eye view image SB _t and the smear bird's-eye view one hour ago. The data of the image SB _t-1 is aligned (S3). After this alignment, the alignment unit 33 generates data for the difference image PD _t and also generates data for the mask image MP (S4). Then, three-dimensional object detection unit 33, the data of the difference image PD _t, and a one unit time before the difference image _{PD t-1} of the data, generates a difference waveform DW _t (S5). After generating the differential waveform DW _t , the three-dimensional object detection unit 33 sets the count number corresponding to the generation area of the smear S in the differential waveform DW _t to zero, and suppresses the influence of the smear S (S6).

Thereafter, the three-dimensional object detection unit 33 determines whether or not the peak of the differential waveform DW _t is greater than or _equal to the first threshold value α (S7). The first threshold value α can be set in advance and can be changed according to the control command of the control unit 39 shown in FIG. 3, and details thereof will be described later. Here, when the peak of the difference waveform DW _t is not equal to or greater than the first threshold value α, that is, when there is almost no difference, it is considered that there is no three-dimensional object in the captured image P. For this reason, when it is determined that the peak of the differential waveform DW _t is not equal to or greater than the first threshold value α (S7: NO), the three-dimensional object detection unit 33 does not have a three-dimensional object and has another vehicle as an obstacle. It is determined not to do so (FIG. 12: S16). Then, the processes shown in FIGS. 11 and 12 are terminated.

On the other hand, when it is determined that the peak of the difference waveform DW _t is equal to or greater than the first threshold value α (S7: YES), the three-dimensional object detection unit 33 determines that a three-dimensional object exists, and sets the difference waveform DW _t to a plurality of difference waveforms DW _t . The area is divided into small areas DW _{t1 to} DW _tn (S8). Next, the three-dimensional object detection unit 33 performs weighting for each of the small regions DW _{t1 to} DW _tn (S9). Thereafter, the three-dimensional object detection unit 33 calculates an offset amount for each of the small regions DW _{t1 to} DW _tn (S10), and generates a histogram with the weights added (S11).

  Then, the three-dimensional object detection unit 33 calculates a relative movement distance that is a movement distance of the three-dimensional object with respect to the host vehicle V based on the histogram (S12). Next, the three-dimensional object detection unit 33 calculates the absolute movement speed of the three-dimensional object from the relative movement distance (S13). At this time, the three-dimensional object detection unit 33 calculates the relative movement speed by differentiating the relative movement distance with respect to time, and adds the own vehicle speed detected by the vehicle speed sensor 20 to calculate the absolute movement speed.

  Thereafter, the three-dimensional object detection unit 33 determines whether or not the absolute movement speed of the three-dimensional object is 10 km / h or more and the relative movement speed of the three-dimensional object with respect to the host vehicle V is +60 km / h or less (S14). When both are satisfied (S14: YES), the three-dimensional object detection unit 33 determines that the three-dimensional object is the other vehicle VX (S15). Then, the processes shown in FIGS. 11 and 12 are terminated. On the other hand, when either one is not satisfied (S14: NO), the three-dimensional object detection unit 33 determines that there is no other vehicle (S16). Then, the processes shown in FIGS. 11 and 12 are terminated.

  In this embodiment, the rear side of the host vehicle V is set as the detection areas A1 and A2, and the other vehicle VX that travels in the adjacent lane that travels next to the travel lane of the host vehicle that the host vehicle V should pay attention to while traveling. In particular, whether or not there is a possibility of contact when the host vehicle V changes lanes. This is to determine whether or not there is a possibility of contact with another vehicle VX traveling in the adjacent lane adjacent to the traveling lane of the own vehicle when the own vehicle V changes lanes. For this reason, the process of step S14 is performed. That is, assuming that the system according to this embodiment is operated on a highway, if the speed of a three-dimensional object is less than 10 km / h, even if another vehicle VX exists, Since it is located far behind the vehicle V, there are few problems. Similarly, when the relative moving speed of the three-dimensional object with respect to the own vehicle V exceeds +60 km / h (that is, when the three-dimensional object is moving at a speed higher than 60 km / h than the speed of the own vehicle V), the lane is changed. In some cases, since the vehicle is moving in front of the host vehicle V, there is little problem. For this reason, it can be said that the other vehicle VX which becomes a problem at the time of lane change is judged in step S14.

  In step S14, determining whether the absolute moving speed of the three-dimensional object is 10 km / h or more and the relative moving speed of the three-dimensional object with respect to the host vehicle V is +60 km / h or less has the following effects. For example, depending on the mounting error of the camera 10, the absolute moving speed of the stationary object may be detected to be several km / h. Therefore, by determining whether the speed is 10 km / h or more, it is possible to reduce the possibility of determining that the stationary object is the other vehicle VX. Further, depending on the noise, the relative speed of the three-dimensional object with respect to the host vehicle V may be detected at a speed exceeding +60 km / h. Therefore, the possibility of erroneous detection due to noise can be reduced by determining whether the relative speed is +60 km / h or less.

  The threshold value of the relative movement speed for determining the other vehicle VX in step S14 can be arbitrarily set. For example, -20 km / h or more and 100 km / h or less can be set as the threshold value for the relative movement speed. Here, the negative lower limit value is a lower limit value of the moving speed when the detected object moves rearward of the host vehicle VX, that is, when the detected object flows backward. This threshold value can be set in advance as appropriate, but can be changed in accordance with a control command of the control unit 39 described later.

  Furthermore, instead of the processing in step S14, it may be determined that the absolute movement speed is not negative or not 0 km / h. Further, in the present embodiment, since emphasis is placed on whether or not there is a possibility of contact when the host vehicle V changes lanes, when another vehicle VX is detected in step S15, the driver of the host vehicle is notified. A warning sound may be emitted or a display corresponding to a warning may be performed by a predetermined display device.

  In step S15, it is determined whether or not the three-dimensional object detected by the three-dimensional object detection unit 33 is continuously detected for a predetermined time T or longer. If the three-dimensional object is continuously detected for a predetermined time T or longer, the process proceeds to step S16, and it is determined that the three-dimensional object is another vehicle existing in the right detection area A1 or the left detection area A2. To do. On the other hand, when that is not right, it progresses to step S17 and it is judged that there is no other vehicle.

Thus, according to the detection procedure of the three-dimensional object based on the difference waveform information of this example, the number of pixels indicating a predetermined difference is counted on the data of the difference image PD _t along the direction in which the three-dimensional object falls by viewpoint conversion. The difference waveform DW _t is generated by frequency distribution. Here, the pixel indicating the predetermined difference on the data of the difference image PD _t is a pixel that has changed in an image at a different time, in other words, a place where a three-dimensional object exists. For this reason, the difference waveform DW _t is generated by counting the number of pixels along the direction in which the three-dimensional object collapses and performing frequency distribution at the location where the three-dimensional object exists. In particular, since the number of pixels is counted along the direction in which the three-dimensional object falls, the differential waveform DW _t is generated from the information in the height direction for the three-dimensional object. Then, the moving distance of the three-dimensional object is calculated from the time change of the differential waveform DW _t including the information in the height direction. For this reason, compared with the case where only one point of movement is focused on, the detection location before the time change and the detection location after the time change are specified including information in the height direction. The same location is likely to be obtained, and the movement distance is calculated from the time change of the same location, so that the calculation accuracy of the movement distance can be improved.

In addition, the count number of the frequency distribution is set to zero for the portion corresponding to the smear S generation region in the differential waveform DW _t . As a result, the waveform portion generated by the smear S in the differential waveform DW _t is removed, and a situation in which the smear S is mistaken as a three-dimensional object can be prevented.

Further, the moving distance of the three-dimensional object is calculated from the offset amount of the differential waveform DW _t when the error of the differential waveform DW _t generated at different times is minimized. For this reason, the movement distance is calculated from the offset amount of the one-dimensional information called the waveform, and the calculation cost can be suppressed in calculating the movement distance.

Further, the differential waveform DW _t generated at different times is divided into a plurality of small regions DW _{t1 to} DW _tn . By dividing this into multiple small areas DW _t1 ~DW _tn, so that the obtained plurality of waveforms showing the respective locations of the three-dimensional object. Also, determine the offset amount when the error of each waveform for each small area _DW t1 _{~DW tn} is minimized by histogram by counting the offset amount determined for each small area _DW t1 _{~DW tn,} The moving distance of the three-dimensional object is calculated. For this reason, the offset amount is obtained for each part of the three-dimensional object, and the movement distance is obtained from a plurality of offset amounts, so that the calculation accuracy of the movement distance can be improved.

Further, the weighting for each of a plurality of small areas _DW t1 _{~DW tn,} histogram of counts in accordance with the offset amount obtained for each small area _DW t1 _{~DW tn} the weight. For this reason, the moving distance can be calculated more appropriately by increasing the weight for the characteristic area and decreasing the weight for the non-characteristic area. Therefore, the calculation accuracy of the moving distance can be further improved.

For each of the small regions DW _{t1 to} DW _tn of the differential waveform DW _t , the weight is increased as the difference between the maximum value and the minimum value of the number of pixels indicating a predetermined difference is larger. For this reason, the characteristic undulation region having a large difference between the maximum value and the minimum value has a larger weight, and the flat region having a small undulation has a smaller weight. Here, since it is easier to obtain the offset amount more accurately in the shape of the undulating area than in the flat area, the moving distance is calculated by increasing the weight in the area where the difference between the maximum value and the minimum value is large. The accuracy can be further improved.

Further, the moving distance of the three-dimensional object is calculated from the maximum value of the histogram obtained by counting the offset amount obtained for each of the small areas DW _{t1 to} DW _tn . For this reason, even if there is a variation in the offset amount, a more accurate movement distance can be calculated from the maximum value.

  Further, since the offset amount for the stationary object is obtained and this offset amount is ignored, it is possible to prevent a situation in which the calculation accuracy of the moving distance of the three-dimensional object is lowered due to the stationary object. In addition, if there are a plurality of maximum values after ignoring the offset amount corresponding to the stationary object, the calculation of the moving distance of the three-dimensional object is stopped. For this reason, it is possible to prevent a situation in which an erroneous movement distance having a plurality of maximum values is calculated.

  In the above embodiment, the vehicle speed of the host vehicle V is determined based on a signal from the vehicle speed sensor 20, but the present invention is not limited to this, and the speed may be estimated from a plurality of images at different times. In this case, a vehicle speed sensor becomes unnecessary, and the configuration can be simplified.

In the above-described embodiment, the captured image at the current time and the image one hour before are converted into a bird's-eye view, the converted bird's-eye view is aligned, the difference image PD _t is generated, and the generated difference image PD _{Although t} is evaluated along the falling direction (the falling direction of the three-dimensional object when the captured image is converted into a bird's eye view), the differential waveform DW _t is generated, but the present invention is not limited to this. For example, only the image one hour before is converted into a bird's-eye view, the converted bird's-eye view is converted into an equivalent to the image captured again, a difference image is generated between this image and the current time image, and the generated difference image The differential waveform DW _t may be generated by evaluating along the direction corresponding to the falling direction (that is, the direction in which the falling direction is converted into the direction on the captured image). That is, the three-dimensional object when the image of the current time and the image of one hour before are aligned, the difference image PD _t is generated from the difference between the two images subjected to the alignment, and the difference image PD _t is converted into a bird's eye view The bird's-eye view does not necessarily have to be clearly generated as long as the evaluation can be performed along the direction in which the user falls.

《Detection of solid objects by edge information》
Next, a three-dimensional object detection block B that can be operated instead of the three-dimensional object detection block A shown in FIG. 3 will be described. The three-dimensional object detection block B detects a three-dimensional object using edge information configured by the luminance difference calculation unit 35, the edge line detection unit 36, and the three-dimensional object detection unit 37. FIGS. 13A and 13B are diagrams illustrating an imaging range and the like of the camera 10 in FIG. 3. FIG. 13A is a plan view, and FIG. 13B is a perspective view in real space on the rear side from the host vehicle V. Show. As shown in FIG. 13A, the camera 10 has a predetermined angle of view a, and images the rear side from the host vehicle V included in the predetermined angle of view a. Similarly to the case shown in FIG. 2, the angle of view “a” of the camera 10 is set so that the imaging range of the camera 10 includes the adjacent lane in addition to the lane in which the host vehicle V travels.

Detection area A1, A2 of the present embodiment is in a plan view (a state of being bird's view) a trapezoidal shape, location of the detection areas A1, A2, size and shape, based on the distance d ₁ to d ₄ determines Is done. The detection areas A1 and A2 in the example shown in the figure are not limited to a trapezoidal shape, but may be other shapes such as a rectangle when viewed from a bird's eye view as shown in FIG.

  Here, the distance d1 is a distance from the host vehicle V to the ground lines L1 and L2. The ground lines L1 and L2 mean lines on which a three-dimensional object existing in the lane adjacent to the lane in which the host vehicle V travels contacts the ground. The purpose of the present embodiment is to detect other vehicles VX and the like (including two-wheeled vehicles) traveling in the left and right lanes adjacent to the lane of the host vehicle V on the rear side of the host vehicle V. For this reason, a distance d1 which is a position to be the ground lines L1 and L2 of the other vehicle VX is obtained from a distance d11 from the own vehicle V to the white line W and a distance d12 from the white line W to a position where the other vehicle VX is predicted to travel. It can be determined substantially fixedly.

  Further, the distance d1 is not limited to being fixedly determined, and may be variable. In this case, the computer 30 recognizes the position of the white line W with respect to the host vehicle V by a technique such as white line recognition, and determines the distance d11 based on the recognized position of the white line W. Thereby, the distance d1 is variably set using the determined distance d11. In the following embodiment, since the position where the other vehicle VX travels (distance d12 from the white line W) and the position where the host vehicle V travels (distance d11 from the white line W) are roughly determined, the distance d1 is It shall be fixedly determined.

  The distance d2 is a distance extending from the rear end portion of the host vehicle V in the vehicle traveling direction. The distance d2 is determined so that the detection areas A1 and A2 are at least within the angle of view a of the camera 10. In particular, in the present embodiment, the distance d2 is set so as to be in contact with the range divided into the angle of view a. The distance d3 is a distance indicating the length of the detection areas A1, A2 in the vehicle traveling direction. This distance d3 is determined based on the size of the three-dimensional object to be detected. In the present embodiment, since the detection target is the other vehicle VX or the like, the distance d3 is set to a length including the other vehicle VX.

  As shown in FIG. 13B, the distance d4 is a distance indicating a height that is set to include a tire such as the other vehicle VX in the real space. The distance d4 is a length shown in FIG. 13A in the bird's-eye view image. The distance d4 may be a length that does not include a lane that is further adjacent to the left and right adjacent lanes in the bird's-eye view image (that is, a lane that is adjacent to two lanes). If the lane adjacent to the two lanes is included from the lane of the own vehicle V, there is another vehicle VX in the adjacent lane on the left and right of the own lane that is the lane in which the own vehicle V is traveling, or in the lane adjacent to the two lanes This is because it becomes impossible to distinguish whether there is another vehicle VX.

  As described above, the distances d1 to d4 are determined, and thereby the positions, sizes, and shapes of the detection areas A1 and A2 are determined. More specifically, the position of the upper side b1 of the detection areas A1 and A2 forming a trapezoid is determined by the distance d1. The starting point position C1 of the upper side b1 is determined by the distance d2. The end point position C2 of the upper side b1 is determined by the distance d3. The side b2 of the detection areas A1 and A2 having a trapezoidal shape is determined by a straight line L3 extending from the camera 10 toward the starting point position C1. Similarly, a side b3 of trapezoidal detection areas A1 and A2 is determined by a straight line L4 extending from the camera 10 toward the end position C2. The position of the lower side b4 of the detection areas A1 and A2 having a trapezoidal shape is determined by the distance d4. Thus, the area surrounded by the sides b1 to b4 is set as the detection areas A1 and A2. As shown in FIG. 13B, the detection areas A <b> 1 and A <b> 2 are true squares (rectangles) in the real space behind the host vehicle V.

  Returning to FIG. 3, the viewpoint conversion unit 31 inputs captured image data of a predetermined area obtained by imaging by the camera 10. The viewpoint conversion unit 31 performs viewpoint conversion processing on the input captured image data to the bird's-eye image data in a bird's-eye view state. The bird's-eye view is a state seen from the viewpoint of a virtual camera looking down from above, for example, vertically downward (or slightly obliquely downward). This viewpoint conversion process can be realized by a technique described in, for example, Japanese Patent Application Laid-Open No. 2008-219063.

  The luminance difference calculation unit 35 calculates a luminance difference with respect to the bird's-eye view image data subjected to viewpoint conversion by the viewpoint conversion unit 31 in order to detect the edge of the three-dimensional object included in the bird's-eye view image. For each of a plurality of positions along a vertical imaginary line extending in the vertical direction in the real space, the brightness difference calculating unit 35 calculates a brightness difference between two pixels in the vicinity of each position. The luminance difference calculation unit 35 can calculate the luminance difference by either a method of setting only one vertical virtual line extending in the vertical direction in the real space or a method of setting two vertical virtual lines.

  A specific method for setting two vertical virtual lines will be described. The brightness difference calculation unit 35 applies a first vertical imaginary line corresponding to a line segment extending in the vertical direction in the real space and a vertical direction in the real space different from the first vertical imaginary line with respect to the bird's-eye view image that has undergone viewpoint conversion. A second vertical imaginary line corresponding to the extending line segment is set. The luminance difference calculation unit 35 continuously obtains a luminance difference between a point on the first vertical imaginary line and a point on the second vertical imaginary line along the first vertical imaginary line and the second vertical imaginary line. Hereinafter, the operation of the luminance difference calculation unit 35 will be described in detail.

  As shown in FIG. 14A, the luminance difference calculation unit 35 corresponds to a line segment extending in the vertical direction in the real space and passes through the detection area A1 (hereinafter referred to as the attention line La). Set). In addition, unlike the attention line La, the luminance difference calculation unit 35 corresponds to a line segment extending in the vertical direction in the real space and also passes through the second vertical virtual line Lr (hereinafter referred to as a reference line Lr) passing through the detection area A1. Set. Here, the reference line Lr is set at a position separated from the attention line La by a predetermined distance in the real space. Note that the line corresponding to the line segment extending in the vertical direction in the real space is a line that spreads radially from the position Ps of the camera 10 in the bird's-eye view image. This radially extending line is a line along the direction in which the three-dimensional object falls when converted to bird's-eye view.

  The luminance difference calculation unit 35 sets a point of interest Pa (a point on the first vertical imaginary line) on the line of interest La. In addition, the luminance difference calculation unit 35 sets a reference point Pr (a point on the second vertical plate) on the reference line Lr. The attention line La, the attention point Pa, the reference line Lr, and the reference point Pr have the relationship shown in FIG. 14B in the real space. As is clear from FIG. 14B, the attention line La and the reference line Lr are lines extending in the vertical direction in the real space, and the attention point Pa and the reference point Pr are substantially the same height in the real space. This is the point that is set. Note that the attention point Pa and the reference point Pr do not necessarily have the same height, and an error that allows the attention point Pa and the reference point Pr to be regarded as the same height is allowed.

  The luminance difference calculation unit 35 calculates a luminance difference between the attention point Pa and the reference point Pr. If the luminance difference between the attention point Pa and the reference point Pr is large, it is considered that an edge exists between the attention point Pa and the reference point Pr. Therefore, the edge line detection unit 36 shown in FIG. 3 detects an edge line based on the luminance difference between the attention point Pa and the reference point Pr.

  This point will be described in more detail. FIG. 15 is a diagram illustrating a detailed operation of the luminance difference calculation unit 35, in which FIG. 15 (a) shows a bird's-eye view image in a bird's-eye view state, and FIG. 15 (b) is shown in FIG. 15 (a). It is the figure which expanded a part B1 of the bird's-eye view image. Although only the detection area A1 is illustrated and described in FIG. 15, the luminance difference is calculated in the same procedure for the detection area A2.

  When the other vehicle VX is reflected in the captured image captured by the camera 10, the other vehicle VX appears in the detection area A1 in the bird's-eye view image as shown in FIG. As shown in the enlarged view of the area B1 in FIG. 15A in FIG. 15B, it is assumed that the attention line La is set on the rubber part of the tire of the other vehicle VX on the bird's-eye view image. In this state, the luminance difference calculation unit 35 first sets the reference line Lr. The reference line Lr is set along the vertical direction at a position away from the attention line La by a predetermined distance in the real space. Specifically, in the three-dimensional object detection device 1 according to the present embodiment, the reference line Lr is set at a position separated from the attention line La by 10 cm in real space. Thereby, the reference line Lr is set on the wheel of the tire of the other vehicle VX that is separated from the rubber of the tire of the other vehicle VX by, for example, 10 cm on the bird's eye view image.

  Next, the luminance difference calculation unit 35 sets a plurality of attention points Pa1 to PaN on the attention line La. In FIG. 15B, for the convenience of explanation, six attention points Pa1 to Pa6 (hereinafter simply referred to as attention points Pai when showing arbitrary points) are set. Note that the number of attention points Pa set on the attention line La may be arbitrary. In the following description, it is assumed that N attention points Pa are set on the attention line La.

  Next, the luminance difference calculation unit 35 sets the reference points Pr1 to PrN so as to be the same height as the attention points Pa1 to PaN in the real space. Then, the luminance difference calculation unit 35 calculates the luminance difference between the attention point Pa and the reference point Pr having the same height. Thereby, the brightness | luminance difference calculation part 35 calculates the brightness | luminance difference of two pixels for every some position (1-N) along the vertical imaginary line extended in the perpendicular direction in real space. For example, the luminance difference calculating unit 35 calculates a luminance difference between the first attention point Pa1 and the first reference point Pr1, and the second difference between the second attention point Pa2 and the second reference point Pr2. Will be calculated. Thereby, the luminance difference calculation unit 35 continuously calculates the luminance difference along the attention line La and the reference line Lr. That is, the luminance difference calculation unit 35 sequentially obtains the luminance difference between the third to Nth attention points Pa3 to PaN and the third to Nth reference points Pr3 to PrN.

  The luminance difference calculation unit 35 repeatedly executes the above-described processing such as setting the reference line Lr, setting the attention point Pa and the reference point Pr, and calculating the luminance difference while shifting the attention line La in the detection area A1. That is, the luminance difference calculation unit 35 repeatedly executes the above processing while changing the positions of the attention line La and the reference line Lr by the same distance in the extending direction of the ground line L1 in the real space. For example, the luminance difference calculation unit 35 sets the reference line Lr as the reference line Lr in the previous processing, sets the reference line Lr for the attention line La, and sequentially obtains the luminance difference. It will be.

  Returning to FIG. 3, the edge line detection unit 36 detects an edge line from the continuous luminance difference calculated by the luminance difference calculation unit 35. For example, in the case illustrated in FIG. 15B, the first attention point Pa <b> 1 and the first reference point Pr <b> 1 are located in the same tire portion, and thus the luminance difference is small. On the other hand, the second to sixth attention points Pa2 to Pa6 are located in the rubber part of the tire, and the second to sixth reference points Pr2 to Pr6 are located in the wheel part of the tire. Therefore, the luminance difference between the second to sixth attention points Pa2 to Pa6 and the second to sixth reference points Pr2 to Pr6 increases. For this reason, the edge line detection unit 36 may detect that an edge line exists between the second to sixth attention points Pa2 to Pa6 and the second to sixth reference points Pr2 to Pr6 having a large luminance difference. it can.

Specifically, when detecting the edge line, the edge line detection unit 36 firstly follows the following Equation 1 to determine the i-th attention point Pai (coordinate (xi, yi)) and the i-th reference point Pri (coordinate ( xi ′, yi ′)) and the i th attention point Pai are attributed.
[Equation 1]
When I (xi, yi)> I (xi ′, yi ′) + t s (xi, yi) = 1
When I (xi, yi) <I (xi ′, yi ′) − t s (xi, yi) = − 1
Otherwise s (xi, yi) = 0

  In Equation 1, t represents a threshold value, I (xi, yi) represents the luminance value of the i-th attention point Pai, and I (xi ′, yi ′) represents the luminance value of the i-th reference point Pri. . According to Equation 1, when the luminance value of the attention point Pai is higher than the luminance value obtained by adding the threshold value t to the reference point Pri, the attribute s (xi, yi) of the attention point Pai is “1”. Become. On the other hand, when the luminance value of the attention point Pai is lower than the luminance value obtained by subtracting the threshold value t from the reference point Pri, the attribute s (xi, yi) of the attention point Pai is “−1”. When the luminance value of the attention point Pai and the luminance value of the reference point Pri are in other relationships, the attribute s (xi, yi) of the attention point Pai is “0”. The threshold value t can be set in advance and can be changed in accordance with a control command issued by the control unit 39 shown in FIG. 3, and details thereof will be described later.

Next, the edge line detection unit 36 determines whether or not the attention line La is an edge line from the continuity c (xi, yi) of the attribute s along the attention line La based on Equation 2 below.
[Equation 2]
When s (xi, yi) = s (xi + 1, yi + 1) (and excluding 0 = 0),
c (xi, yi) = 1
Other than the above
c (xi, yi) = 0

  When the attribute s (xi, yi) of the attention point Pai and the attribute s (xi + 1, yi + 1) of the adjacent attention point Pai + 1 are the same, the continuity c (xi, yi) is ‘1’. When the attribute s (xi, yi) of the attention point Pai is not the same as the attribute s (xi + 1, yi + 1) of the adjacent attention point Pai + 1, the continuity c (xi, yi) is “0”.

  Next, the edge line detection unit 36 obtains the sum for the continuity c of all attention points Pa on the attention line La. The edge line detection unit 36 normalizes the continuity c by dividing the obtained sum of continuity c by the number N of points of interest Pa. The edge line detection unit 36 determines that the attention line La is an edge line when the normalized value exceeds the threshold θ. The threshold value θ is a value set in advance through experiments or the like. The threshold value θ may be set in advance, or may be changed according to a control command corresponding to a determination result of a lens state determination unit 38 of the control unit 39 described later.

That is, the edge line detection unit 36 determines whether or not the attention line La is an edge line based on Equation 3 below. Then, the edge line detection unit 36 determines whether or not all the attention lines La drawn on the detection area A1 are edge lines.
[Equation 3]
Σc (xi, yi) / N> θ

  Returning to FIG. 3, the three-dimensional object detection unit 37 detects a three-dimensional object based on the amount of edge lines detected by the edge line detection unit 36. As described above, the three-dimensional object detection device 1 according to the present embodiment detects an edge line extending in the vertical direction in real space. The fact that many edge lines extending in the vertical direction are detected means that there is a high possibility that a three-dimensional object exists in the detection areas A1 and A2. For this reason, the three-dimensional object detection unit 37 detects a three-dimensional object based on the amount of edge lines detected by the edge line detection unit 36. Furthermore, prior to detecting the three-dimensional object, the three-dimensional object detection unit 37 determines whether or not the edge line detected by the edge line detection unit 36 is correct. The three-dimensional object detection unit 37 determines whether or not the luminance change along the edge line of the bird's-eye view image on the edge line is larger than a predetermined threshold value. When the luminance change of the bird's-eye view image on the edge line is larger than the threshold value, it is determined that the edge line is detected by erroneous determination. On the other hand, when the luminance change of the bird's-eye view image on the edge line is not larger than the threshold value, it is determined that the edge line is correct. This threshold value is a value set in advance by experiments or the like.

  FIG. 16 is a diagram illustrating the luminance distribution of the edge line. FIG. 16A illustrates the edge line and the luminance distribution when another vehicle VX as a three-dimensional object exists in the detection area A1, and FIG. Indicates an edge line and a luminance distribution when there is no solid object in the detection area A1.

  As shown in FIG. 16A, it is assumed that the attention line La set in the tire rubber portion of the other vehicle VX is determined to be an edge line in the bird's-eye view image. In this case, the luminance change of the bird's-eye view image on the attention line La is gentle. This is because the tire of the other vehicle VX is extended in the bird's-eye view image by converting the image captured by the camera 10 into a bird's-eye view image. On the other hand, as shown in FIG. 16B, it is assumed that the attention line La set in the white character portion “50” drawn on the road surface in the bird's-eye view image is erroneously determined as an edge line. In this case, the brightness change of the bird's-eye view image on the attention line La has a large undulation. This is because a portion with high brightness in white characters and a portion with low brightness such as a road surface are mixed on the edge line.

  Based on the difference in luminance distribution on the attention line La as described above, the three-dimensional object detection unit 37 determines whether or not the edge line is detected by erroneous determination. When the luminance change along the edge line is larger than a predetermined threshold, the three-dimensional object detection unit 37 determines that the edge line is detected by erroneous determination. And the said edge line is not used for the detection of a solid object. Thereby, white characters such as “50” on the road surface, weeds on the road shoulder, and the like are determined as edge lines, and the detection accuracy of the three-dimensional object is prevented from being lowered.

Specifically, the three-dimensional object detection unit 37 calculates the luminance change of the edge line by any one of the following mathematical formulas 4 and 5. The luminance change of the edge line corresponds to the evaluation value in the vertical direction in the real space. Equation 4 below evaluates the luminance distribution by the sum of the squares of the differences between the i-th luminance value I (xi, yi) on the attention line La and the adjacent i + 1-th luminance value I (xi + 1, yi + 1). . Equation 5 below evaluates the luminance distribution by the sum of the absolute values of the differences between the i-th luminance value I (xi, yi) on the attention line La and the adjacent i + 1-th luminance value I (xi + 1, yi + 1). To do.
[Equation 4]
Evaluation value in the vertical equivalent direction = Σ [{I (xi, yi) −I (xi + 1, yi + 1)} ² ]
[Equation 5]
Evaluation value in the vertical equivalent direction = Σ | I (xi, yi) −I (xi + 1, yi + 1) |

In addition, not only Formula 5 but also Formula 6 below, the threshold value t2 is used to binarize the attribute b of the adjacent luminance value, and the binarized attribute b is summed for all the attention points Pa. Also good.
[Equation 6]
Evaluation value in the vertical equivalent direction = Σb (xi, yi)
However, when | I (xi, yi) −I (xi + 1, yi + 1) |> t2,
b (xi, yi) = 1
Other than the above
b (xi, yi) = 0

  When the absolute value of the luminance difference between the luminance value of the attention point Pai and the luminance value of the reference point Pri is larger than the threshold value t2, the attribute b (xi, yi) of the attention point Pa (xi, yi) is “1”. Become. If the relationship is other than that, the attribute b (xi, yi) of the attention point Pai is '0'. This threshold value t2 is set in advance by an experiment or the like in order to determine that the attention line La is not on the same three-dimensional object. Then, the three-dimensional object detection unit 37 sums up the attributes b for all the attention points Pa on the attention line La, obtains an evaluation value in the vertical equivalent direction, and determines whether the edge line is correct.

  Next, a three-dimensional object detection method using edge information according to the present embodiment will be described. 17 and 18 are flowcharts showing details of the three-dimensional object detection method according to the present embodiment. In FIG. 17 and FIG. 18, for the sake of convenience, the processing for the detection area A1 will be described, but the same processing is executed for the detection area A2.

  As shown in FIG. 17, first, in step S21, the camera 10 captures an image of a predetermined area specified by the angle of view a and the attachment position. Next, in step S22, the viewpoint conversion unit 31 inputs the captured image data captured by the camera 10 in step S21, performs viewpoint conversion, and generates bird's-eye view image data.

  Next, the brightness | luminance difference calculation part 35 sets attention line La on detection area | region A1 in step S23. At this time, the luminance difference calculation unit 35 sets a line corresponding to a line extending in the vertical direction in the real space as the attention line La. Next, the brightness | luminance difference calculation part 35 sets the reference line Lr on detection area | region A1 in step S24. At this time, the luminance difference calculation unit 35 sets a reference line Lr that corresponds to a line segment extending in the vertical direction in the real space and is separated from the attention line La by a predetermined distance in the real space.

  Next, the brightness | luminance difference calculation part 35 sets several attention point Pa on attention line La in step S25. At this time, the luminance difference calculation unit 35 sets the attention points Pa as many as not causing a problem at the time of edge detection by the edge line detection unit 36. In step S26, the luminance difference calculation unit 35 sets the reference point Pr so that the attention point Pa and the reference point Pr are substantially the same height in the real space. Thereby, the attention point Pa and the reference point Pr are arranged in a substantially horizontal direction, and it becomes easy to detect an edge line extending in the vertical direction in the real space.

  Next, in step S27, the luminance difference calculation unit 35 calculates the luminance difference between the attention point Pa and the reference point Pr that have the same height in the real space. Next, the edge line detection unit 36 calculates the attribute s of each attention point Pa in accordance with Equation 1 above. Next, in step S28, the edge line detection unit 36 calculates the continuity c of the attribute s of each attention point Pa in accordance with Equation 2 above. Next, in step S29, the edge line detection unit 36 determines whether or not the value obtained by normalizing the total sum of continuity c is greater than the threshold value θ according to the above formula 3. When it is determined that the normalized value is larger than the threshold θ (S29: YES), the edge line detection unit 36 detects the attention line La as an edge line in step S30. Then, the process proceeds to step S31. When it is determined that the normalized value is not larger than the threshold θ (S29: NO), the edge line detection unit 36 does not detect the attention line La as an edge line, and the process proceeds to step S31. This threshold value θ can be set in advance, but can be changed in accordance with a control command to the control unit 39.

  In step S31, the computer 30 determines whether or not the processing in steps S23 to S30 has been executed for all the attention lines La that can be set on the detection area A1. If it is determined that the above processing has not been performed for all the attention lines La (S31: NO), the processing returns to step S23, a new attention line La is set, and the processing up to step S31 is repeated. On the other hand, when it is determined that the above process has been performed for all the attention lines La (S31: YES), the process proceeds to step S32 in FIG.

  In step S32 in FIG. 18, the three-dimensional object detection unit 37 calculates a luminance change along the edge line for each edge line detected in step S30 in FIG. 17. The three-dimensional object detection unit 37 calculates the luminance change of the edge line according to any one of the above formulas 4, 5, and 6. Next, in step S33, the three-dimensional object detection unit 37 excludes edge lines whose luminance change is larger than a predetermined threshold from the edge lines. That is, it is determined that an edge line having a large luminance change is not a correct edge line, and the edge line is not used for detecting a three-dimensional object. As described above, this is to prevent characters on the road surface, roadside weeds, and the like included in the detection area A1 from being detected as edge lines. Therefore, the predetermined threshold value is a value set based on a luminance change generated by characters on the road surface, weeds on the road shoulder, or the like obtained in advance by experiments or the like.

  Next, in step S34, the three-dimensional object detection unit 37 determines whether the amount of the edge line is equal to or greater than the second threshold value β. The second threshold value β can be obtained and set in advance by experiments or the like, and can be changed in accordance with a control command issued by the control unit 39 shown in FIG. 3, details of which will be described later. For example, when a four-wheeled vehicle is set as the three-dimensional object to be detected, the second threshold value β is set based on the number of edge lines of the four-wheeled vehicle that have appeared in the detection region A1 in advance through experiments or the like. When it is determined that the amount of the edge line is equal to or larger than the second threshold β (S34: YES), the solid object detected by the three-dimensional object detection unit 33 is continuously detected over a predetermined time T (S35). : YES), the three-dimensional object detection unit 37 detects that a three-dimensional object exists in the detection area A1 in step S36 (S36). On the other hand, when it is determined that the amount of the edge line is not equal to or greater than the second threshold value β (S34: NO), the solid object detected by the three-dimensional object detection unit 33 has not been continuously detected for a predetermined time T or more. In the case (S35: NO), the three-dimensional object detection unit 37 determines that there is no three-dimensional object in the detection area A1 (S37). The second threshold value β can be set in advance, but can be changed according to a control command to the control unit 39. It should be noted that all the detected three-dimensional objects may be determined to be other vehicles VX that travel in the adjacent lane adjacent to the lane in which the host vehicle V travels, and the detected three-dimensional object is a characteristic of the other vehicle VX. It may be determined whether or not the vehicle is another vehicle VX traveling in the adjacent lane in consideration of the relative speed with respect to the host vehicle V.

  As described above, according to the three-dimensional object detection method using the edge information of the present embodiment, in order to detect the three-dimensional object existing in the detection areas A1 and A2, the vertical direction in the real space with respect to the bird's-eye view image A vertical imaginary line is set as a line segment extending to. Then, for each of a plurality of positions along the vertical imaginary line, a luminance difference between two pixels in the vicinity of each position can be calculated, and the presence or absence of a three-dimensional object can be determined based on the continuity of the luminance difference.

  Specifically, the attention line La corresponding to the line segment extending in the vertical direction in the real space and the reference line Lr different from the attention line La are set for the detection areas A1 and A2 in the bird's-eye view image. Then, a luminance difference between the attention point Pa on the attention line La and the reference point Pr on the reference line Lr is continuously obtained along the attention line La and the reference line La. In this way, the luminance difference between the attention line La and the reference line Lr is obtained by continuously obtaining the luminance difference between the points. In the case where the luminance difference between the attention line La and the reference line Lr is high, there is a high possibility that there is an edge of the three-dimensional object at the set position of the attention line La. Thereby, a three-dimensional object can be detected based on a continuous luminance difference. In particular, in order to compare brightness with vertical virtual lines extending in the vertical direction in real space, even if the three-dimensional object is stretched according to the height from the road surface by converting it to a bird's-eye view image, This detection process is not affected. Therefore, according to the method of this example, the detection accuracy of a three-dimensional object can be improved.

  In this example, the luminance difference between two points having substantially the same height near the vertical imaginary line is obtained. Specifically, the luminance difference is obtained from the attention point Pa on the attention line La and the reference point Pr on the reference line Lr, which are substantially the same height in the real space, and thus the luminance when there is an edge extending in the vertical direction. The difference can be detected clearly.

  Furthermore, in this example, the attention point Pa is attributed based on the luminance difference between the attention point Pa on the attention line La and the reference point Pr on the reference line Lr, and attribute continuity c along the attention line La is obtained. Therefore, it is determined whether the attention line La is an edge line. Therefore, the boundary between the high luminance area and the low luminance area is detected as an edge line, and edge detection is performed in accordance with a natural human sense. Can do. This effect will be described in detail. FIG. 19 is a diagram illustrating an example of an image for explaining the processing of the edge line detection unit 36. In this image example, a first striped pattern 101 showing a striped pattern in which a high brightness area and a low brightness area are repeated, and a second striped pattern showing a striped pattern in which a low brightness area and a high brightness area are repeated. 102 is an adjacent image. Further, in this image example, a region where the brightness of the first striped pattern 101 is high and a region where the brightness of the second striped pattern 102 is low are adjacent to each other, and a region where the brightness of the first striped pattern 101 is low and the second striped pattern 102. Is adjacent to a region with high brightness. The portion 103 located at the boundary between the first striped pattern 101 and the second striped pattern 102 tends not to be perceived as an edge depending on human senses.

  On the other hand, since the low luminance region and the high luminance region are adjacent to each other, if the edge is detected only by the luminance difference, the part 103 is recognized as an edge. However, since the edge line detection unit 36 determines the part 103 as an edge line only when there is continuity in the attribute of the luminance difference in addition to the luminance difference in the part 103, the edge line detection unit 36 An erroneous determination of recognizing a part 103 that is not recognized as an edge line as a sensation as an edge line can be suppressed, and edge detection according to a human sensation can be performed.

  Furthermore, in this example, when the luminance change of the edge line detected by the edge line detection unit 36 is larger than a predetermined threshold value, it is determined that the edge line has been detected by erroneous determination. When the captured image acquired by the camera 10 is converted into a bird's-eye view image, the three-dimensional object included in the captured image tends to appear in the bird's-eye view image in a stretched state. For example, as described above, when the tire of the other vehicle VX is stretched, since one portion of the tire is stretched, the luminance change of the bird's-eye view image in the stretched direction tends to be small. On the other hand, when a character or the like drawn on the road surface is erroneously determined as an edge line, the bird's-eye view image includes a high luminance region such as a character portion and a low luminance region such as a road surface portion. In this case, the brightness change in the stretched direction tends to increase in the bird's-eye view image. Therefore, by determining the luminance change of the bird's-eye view image along the edge line as in this example, the edge line detected by the erroneous determination can be recognized, and the detection accuracy of the three-dimensional object can be improved.

  Next, the lens state determination unit 38 will be described. The lens state determination unit 38 of the present embodiment determines whether or not a predetermined bubble attachment state in which bubbles are attached to the lens 11 based on the captured image of the camera 10. In the present embodiment, the lens 11 is cleaned using a lens cleaning device 100 described later. During the cleaning of the lens 11, bubbles are generated and adhere to the lens 11. The cleaning liquid used for this cleaning is water or water containing a detergent. The detergent includes cleaning components such as a surfactant, a chelating agent, and an enzyme. When a detergent, particularly a detergent containing a surfactant, is used, foam is generated during washing. Moreover, even if it is a case where it wash | cleans using water, a bubble may arise with the detergent and organic substance which remain | survived on the lens 11 surface.

Here, three typical methods for determining whether or not bubbles are attached to the lens 11 and the lens 11 is in a predetermined bubble attached state will be described.
The first method is a method of determining whether or not the lens 11 is in a predetermined bubble adhesion state based on the edge mode corresponding to the bubble image. First, the lens state determination unit 38 of the present embodiment detects an edge of a predetermined curvature value range from the captured image of the camera 10. Edges detected due to the presence of bubbles tend to exhibit curvatures that approximate arcs. For this reason, the curvature value range to be detected is defined based on the curvature of the circle. The lens state determination unit 38 of the present embodiment determines that bubbles are attached to the lens 11 when an edge of a predetermined curvature value range is detected from the captured image. Next, the lens state determination unit 38 of the present embodiment determines that the lens 11 is in a predetermined bubble adhesion state when a predetermined number or more of edges in a predetermined curvature value range are detected in one frame of the captured image. To do. If the number of bubbles adhering to the lens 11 is small, the possibility of inducing a false detection of a three-dimensional object or another vehicle is low. This is because there is a high possibility of inducing a false detection of a three-dimensional object or another vehicle when the bubble is attached.

  The second method is a method for determining whether or not the lens 11 is in a predetermined bubble adhesion state based on a change in an edge corresponding to an image of a bumper or the like of the host vehicle. First, the lens state determination unit 38 of the present embodiment stores an edge of a reference image captured by the camera 10 whose installation position and imaging characteristics are specified. The reference image is an image corresponding to an edge of a fixed object such as a bumper of the own vehicle, a license plate of the own vehicle, or a cover of the camera 10 of the own vehicle, which is always reflected in an image captured by the camera 10. When bubbles are attached to the lens 11 of the camera 10, a change occurs in the edge of the stored reference image. For example, if bubbles are attached to the lens 11, the bubbles disturb the image corresponding to the edge of the fixed object, so that the edge of the fixed object such as a bumper cannot be clearly seen. Specifically, a phenomenon is observed in which the edge length (representative value such as an average value) obtained from the reference image is shortened and the number of edges integrated as continuous edges is reduced. The lens state determination unit 38 of the present embodiment determines that the lens 11 is in a predetermined bubble adhering state when there is a change of a predetermined amount or more compared to the stored edge of the reference image. This is because the same edge as the reference image is detected for a fixed object, but the bubble image of the lens 11 affects the captured image, and an edge different from the reference image is detected. If the number of bubbles adhering to the lens 11 is small and the change in the edge of the reference image is small, the possibility of inducing a false detection of a three-dimensional object or another vehicle is low. This is because if the change in the edge of the image is large, there is a high possibility of inducing erroneous detection of a three-dimensional object or another vehicle.

  The third method is a method for determining whether or not the lens 11 is in a predetermined bubble adhering state based on a change in brightness of the captured image. First, the lens state determination unit 38 of the present embodiment stores the brightness of the captured image of the camera 10 whose installation position and imaging characteristics are specified. In this embodiment, the average value of the brightness of the entire captured image is stored as the brightness of the captured image. The brightness of the captured image may be stored in association with the brightness outside the vehicle. This is because there is a difference in brightness outside the vehicle depending on the region and time, which affects the brightness of the captured image. When bubbles are attached to the lens 11 of the camera 10, the brightness of the stored captured image changes. When bubbles are attached to the lens 11, the bubbles diffuse light, so that the brightness of the captured image becomes brighter. The camera 10 mounted on the vehicle is generally provided with a light shielding plate in a protective case in order to suppress the influence of the brightness of the outside world, and the brightness of the portion corresponding to the portion covered by the light shielding plate is suppressed low, Reduce the average brightness of the entire captured image. However, if bubbles are attached to the lens 11, the reflected light also enters the portion covered by the light shielding plate, and there is a tendency to increase the average brightness of the entire captured image. According to the experiments by the inventors, even if water is attached to the lens 11, the light is not reflected to the portion covered with the light shielding plate, and the change in the brightness of the entire captured image is small. When the foreign matter attached to the lens 11 is a bubble, the brightness of the captured image changes significantly. In the present embodiment, this characteristic is used, and when the brightness of the entire captured image changes brightly, it is determined that bubbles are attached to the lens 11. Then, the lens state determination unit 38 of the present embodiment determines that the lens 11 is in a predetermined bubble adhesion state when the brightness of the stored captured image becomes brighter than a predetermined value. If the change in brightness of the captured image is small and the amount of bubbles adhering to the lens 11 is small, the possibility of inducing a false detection of a three-dimensional object or other vehicle is low, while the change in the brightness of the captured image is a predetermined value. As described above, when a large amount of bubbles are attached to the lens 11, it is determined that there is a high possibility of inducing a false detection of a three-dimensional object or another vehicle.

  The lens state determination unit 38 according to the present embodiment determines whether or not the lens 11 is in a predetermined bubble adhering state by the method described above, and the determination result is determined as a three-dimensional object detection unit 33, 37, a three-dimensional object determination unit. 34 or the control unit 39.

Here, the state of the lens 11 after cleaning and the captured image after cleaning will be described.
FIG. 20A is a diagram for explaining the state of the lens 11 immediately after the lens 11 is cleaned, and FIG. 20B is a diagram illustrating an example of the captured image K1 immediately after the lens 11 is cleaned. FIG. 21A is a diagram for explaining the state of the lens of the camera after running for a predetermined time after cleaning the lens, and FIG. 21B is an image of the captured image K2 taken after running for a predetermined time after washing the lens. It is a figure which shows an example. In addition, the lens 11 of the present embodiment is a translucent member interposed between the imaging target and the imaging element, and has a function of controlling the optical path by refraction of light. Including the cover.

  As shown in FIGS. 20A and 21A, the image information K1 and K2 obtained through the lens 11 includes the image of the road surface RD of the road on which the host vehicle V travels and the sky SK behind the road RD. Including images. The images on the lower side of FIGS. 20A and 21A are images of the license plate LP and the bumper BP, and the upper light ink portion is an image corresponding to the case C of the camera 10. Further, when bubbles are attached to the lens 11, the image information captured through the lens 11 is affected. In particular, the edge of the image of the license plate LP and the edge of the image of the case C are affected. Furthermore, when bubbles are attached to the lens 11, the bubbles reflect light, and light is also sent to the portion covered by the case C, so that the brightness of image information captured through the lens 11 changes.

  As shown in FIG. 20A, immediately after the lens 11 is cleaned, bubbles generated by the cleaning are discretely attached to the entire surface of the lens 11. When bubbles adhere to the lens 11, an image of the bubbles is reflected in image information captured through the lens 11. FIG. 20B shows the distribution of bubbles generated by the cleaning in the captured image K1 captured immediately after the lens 11 is cleaned. The bubbles BU are discretely distributed over the entire captured image K1.

  According to the experiments by the inventors, when the vehicle travels after the lens 11 is washed, the bubbles on the lens 11 tend to move from the central portion 0 of the captured image toward the peripheral edge of the lens 11. When the host vehicle travels after cleaning the lens 11, it was confirmed that bubbles on the lens 11 gather at the boundary of the lens 11 with the case C and the edge of the lens 11 as shown in FIG. 21A. FIG. 21B shows the distribution of bubbles generated by the cleaning in the captured image K2 captured after the vehicle travels after the lens 11 is cleaned. As time further elapses, the bubbles are blown away or broken and disappear from the lens 11.

  The bubbles BU on the lens 11 gather in a predetermined area. The area where the bubbles BU are gathered is a predetermined area separated from the central portion 0 of the captured image K2 by a predetermined distance or more. In the present embodiment, this region is referred to as a “peripheral region” for identification. The predetermined distance away from the central part 0 can be defined for each direction from the central part 0. For example, a predetermined region, that is, a “peripheral region” may be defined at a position separated by a predetermined distance x1 from the central part 0 in the + x direction, or at a position separated by a predetermined distance x2 from the central part 0 in the −y direction. An area, that is, a “peripheral area” may be defined. The distances x1 and x2 may be the same value or different values. Similarly, the peripheral area may be defined at a position separated by a predetermined distance y1 from the central part 0 in the + y direction, or the peripheral area may be defined at a position separated from the central part 0 by the predetermined distance y2 in the −y direction. Also good. The distances y1 and y2 may be the same value or different values. Although not particularly limited, in the present embodiment, an area corresponding to columns k1 to k3 and rows m1 to m6 (EB1 area indicated by light ink) shown in FIG. 21B is defined as a peripheral area. In the present embodiment, an area corresponding to columns k13 to k15 and rows m1 to m6 shown in FIG. 21B is defined as a peripheral area (EB2 area indicated by light ink). In the present embodiment, an area corresponding to rows m1 to m2 and columns k1 to k15 (EB3 area indicated by light ink) is defined as a peripheral area. In this embodiment, an area corresponding to rows m5 to m6 and columns k1 to k15 is defined as a peripheral area. The distance defining the peripheral region is not limited to the x direction and the y direction, and can be defined in any direction around 360 degrees around the central portion 0. You may define the outer side (edge side of the lens 11) of the circular arc and elliptical arc defined on the basis of the center part 0 as a peripheral region.

  According to the inventors' experiment, in particular, there was a tendency for bubbles to gather in a predetermined upper region of the captured image K2. The upper region is a region separated from the central portion 0 of the captured image K2 by a predetermined distance or more and separated from the vehicle body (bumper, license plate) of the host vehicle V by a predetermined distance or more in the + y direction. For this reason, in this embodiment, the area | region corresponding to row m1-m2 and column k1-k15 is defined as the peripheral area | region EB3.

  The bubble BU moves on the surface of the lens 11 over time. In particular, when the host vehicle V travels, it moves faster. An image of the bubble BU generated by the cleaning of the lens 11 is reflected in the captured image after the cleaning. The image BU of the bubble BU moves as the bubble moves. The image information K1 and K2 imaged by the lens 11 to which bubbles are attached changes every time the host vehicle V moves. For this reason, the edge of the moving bubble image BU may be detected as the edge of an object that moves relative to the host vehicle V in the image information K1 and K2.

  If the lens state determination unit 38 determines that the lens 11 is in a predetermined bubble adhesion state, the captured image may be affected. When the image conversion process is performed using the image information K2 captured through the lens 11 to which the bubble BU is attached as illustrated in FIGS. 20A and 21A, differential waveform information and edge information corresponding to the bubble image BU are derived. Is done. If differential waveform information or edge information is calculated by the above-described method based on such image information and the three-dimensional object detection process is performed, the cleaning liquid bubble image W may be erroneously recognized as an image of the other vehicle VX.

  According to experiments by the inventors, it has been found that the speed at which the generated bubble BU moves on the lens 11 tends to increase as the vehicle speed of the host vehicle V increases. Moreover, it turned out that the time until the bubble BU reaches the peripheral region EB is shorter as the vehicle speed of the host vehicle V is higher. It has been found that the faster the vehicle speed of the host vehicle V, the faster the bubble BBU disappears from the surface of the lens 11.

《Final judgment of solid object》
Returning to FIG. 3, a method for determining a three-dimensional object in the present embodiment will be described. The three-dimensional object detection device 1 of this example includes the above-described two three-dimensional object detection unit 33 (or three-dimensional object detection unit 37), a three-dimensional object determination unit 34, a lens state determination unit 38, and a control unit 39. Based on the detection result by the three-dimensional object detection unit 33 (or the three-dimensional object detection unit 37), the three-dimensional object determination unit 34 determines whether or not the detected three-dimensional object is the other vehicle VX existing in the detection areas A1 and A2. Judgment finally. The three-dimensional object detection unit 33 (or the three-dimensional object detection unit 37) and the three-dimensional object determination unit 34 detect a three-dimensional object reflecting the determination result of the lens state determination unit 38 in accordance with an instruction from the control unit 39.

  The three-dimensional object determination unit 34 will be described. The three-dimensional object determination unit 34 of the present embodiment finally determines whether or not the three-dimensional object detected by the three-dimensional object detection units 33 and 37 is the other vehicle VX existing in the detection areas A1 and A2. Specifically, the three-dimensional object determination unit 34 determines the three-dimensional object when the number of peaks of the difference waveform extracted from the difference waveform information, the peak value, and the like are within a predetermined value range and the moving speed of the three-dimensional object is within the predetermined value range. Is finally determined whether or not the vehicle VX exists in the detection areas A1 and A2. The three-dimensional object determination unit 34, when the state in which it is determined that the three-dimensional object is the other vehicle VX existing in the detection areas A1 and A2 continues for a predetermined time or more, the other vehicle in which the three-dimensional object exists in the detection areas A1 and A2. You may finally judge that it is VX.

  The three-dimensional object detection unit 37 is configured so that the three-dimensional object exists in the detection areas A1 and A2 when the continuity of the edges extracted from the edge information, the normalized value of the sum, the amount of edge lines, and the like are within a predetermined value range. It is finally determined whether or not the vehicle is VX. The three-dimensional object detection unit 37 detects the three-dimensional object in the detection areas A1 and A2 when the state in which it is determined that the three-dimensional object is the other vehicle VX existing in the detection areas A1 and A2 continues for a predetermined time or longer. You may finally judge that it is VX.

Further, the three-dimensional object determination unit 34 of the present embodiment uses the other vehicle VX in which the three-dimensional object exists in the detection areas A1 and A2 when the variation in the relative speed of the detected three-dimensional object is within a predetermined variation evaluation value range. Judge that there is. Specifically, when the evaluation value of the variation such as the standard deviation of the relative speed of the three-dimensional object calculated from the captured image of each frame is within a predetermined variation evaluation value range, the three-dimensional object exists in the detection areas A1 and A2. It is determined that the vehicle is another vehicle VX.
When a foreign object adheres to the lens 11 of the camera 10, a three-dimensional object may be erroneously detected based on an image corresponding to the foreign object. However, the variation in the relative speed of the three-dimensional object (virtual image) erroneously detected due to the foreign substance of the lens 11 is smaller than the variation in the three-dimensional object (real image) detected due to the three-dimensional object that actually exists. . In addition, variations in the relative speed of three-dimensional objects (virtual images) that are falsely detected due to natural objects such as plants and trees placed on the shoulder side of the road, or shadows of buildings, are attributed to actual three-dimensional objects. Larger than the variation in the detected three-dimensional object (real image). In the present embodiment, a predetermined variation evaluation value range is defined based on this characteristic. The lower limit value RL of the variation evaluation value range in the present embodiment is a representative value (average value, median value, mode value) of the relative speed variation of a three-dimensional object (virtual image) that is erroneously detected due to a foreign substance attached to the lens 11. Etc.). On the other hand, the lower limit value RU of the variation evaluation value range is a representative value of the relative speed variation of a three-dimensional object (virtual image) that is erroneously detected due to a natural object such as vegetation arranged on the shoulder side of a road or a shadow of a building. The value is smaller than (average value, median value, mode value, etc.). The width RW of the variation evaluation value range is between the lower limit value RL of the variation evaluation value range and the lower limit value RU of the variation evaluation value range.

  Since the determination of the three-dimensional object described above is performed based on the detection result of the three-dimensional object, the detection result of the three-dimensional object affects the determination result of the three-dimensional object. In other words, in the three-dimensional object detection process, if the output of the result that the three-dimensional object is detected is suppressed, the output of the result that the three-dimensional object is another vehicle is suppressed. On the other hand, in the detection process of the three-dimensional object, if the output of the result that the three-dimensional object is detected is promoted, the output of the result that the three-dimensional object is another vehicle is promoted.

  When the three-dimensional object determination unit 34 determines that the detected three-dimensional object is the other vehicle VX existing in the detection areas A1 and A2, processing such as notification to the occupant is executed. The three-dimensional object determination unit 34 can suppress determining that the detected three-dimensional object is the other vehicle VX according to the control command of the control unit 39. The control unit 39 generates a control command according to the determination result of the lens state determination unit 38.

  By the way, as shown in FIGS. 20A and 20B and FIGS. 21A and 21B, when bubbles BU adhere to the lens 11, the captured image acquired through the lens 11 is affected. In the present embodiment, in order to reduce the influence of the bubble BU attached to the lens 11 on the determination result of the three-dimensional object, the lens state determination unit 38 determines that the lens 11 is in the predetermined bubble attachment state described above. In this case, the detection of a three-dimensional object and the determination that the detected three-dimensional object is another vehicle are suppressed.

  When it is determined that the lens 11 is in the above-described predetermined bubble adhesion state, the control unit 39 of the present embodiment erroneously detects a three-dimensional object detected due to the presence of the bubble BU attached to the lens 11. A control command for preventing the vehicle from being determined as another vehicle VX is generated and sent to the three-dimensional object detection units 33 and 37 and the three-dimensional object determination unit 34. Since the computer 30 of the present embodiment is a computer, control commands for the three-dimensional object detection process, the three-dimensional object determination process, and the lens state determination process may be incorporated in advance in the programs of the respective processes, or may be transmitted at the time of execution.

  The control part 39 of this embodiment suppresses that a solid object is detected with the following method. In the present embodiment, the “three-dimensional object” includes “another vehicle VX”. The control unit 39 suppresses the detection of the three-dimensional object and the determination that the detected three-dimensional object is another vehicle.

  First, when the lens state determination unit 38 determines that the lens 11 is in the above-described predetermined bubble adhesion state, the control unit 39 of the present embodiment determines a predetermined value defined in the captured image of the camera 10. The detection of the three-dimensional object is suppressed based on the image included in the peripheral region. As described above, the bubble BU attached to the lens 11 moves in a direction away from the central portion 0 when the host vehicle V travels. Then, as shown in FIGS. 21A and 21B, there is a tendency to remain in the peripheral area EB, which is an area separated from the central portion 0 by a predetermined distance or more. Since the bubbles BU moved to the peripheral area EB overlap and exist at a high density, there is a possibility that the accuracy of the three-dimensional object detection and the three-dimensional object determination is lowered. For this reason, the control unit 39 of the present embodiment sets a peripheral region EB in the left peripheral portion EB1, the right peripheral portion EB2, or the upper peripheral portion EB3 of the captured image K2, as shown in FIG. 21B. Of course, depending on the position of the camera 10 and the shape of the lens 11, two or more of the left peripheral edge EB1, the right peripheral edge EB2, or the upper peripheral edge EB3 may be set in combination. The control part 39 suppresses that a solid object is detected from this peripheral area EB and the detected solid object is determined to be another vehicle.

  Specifically, the control unit 39 may mask the peripheral area EB so that the image information is not acquired as information used for determining the three-dimensional object. The control unit 39 may delete the image information corresponding to the peripheral area EB from the acquired captured image. When the control unit 39 performs the three-dimensional object detection process or the three-dimensional object determination process based on the image information corresponding to the peripheral area EB, the control unit 39 sets a threshold value used in the three-dimensional object detection process or the three-dimensional object determination process to an area other than the peripheral area EB. It is good also as a value different from the threshold value of each process based on the image information corresponding to. A method for suppressing the detection of a three-dimensional object and the determination of another vehicle by changing the threshold will be described later.

  As described above, in the present embodiment, the three-dimensional object is detected from the peripheral area EB that is defined in advance on the outer peripheral side of the captured image, and it is suppressed that the detected three-dimensional object is determined to be another vehicle. It is possible to suppress detection of a three-dimensional object (including other vehicles) from image information in a region where BU is likely to stay. As a result, it is possible to suppress erroneous determination of an image caused by the bubble BU attached to the lens 11 as a three-dimensional object (including another vehicle). On the other hand, for the regions other than the peripheral region EB, the detection of the three-dimensional object and the determination that the detected three-dimensional object is another vehicle are not suppressed, and therefore the influence of the bubble BU attached to the lens 11 is not affected. While suppressing, the detection of a three-dimensional object and the determination of a three-dimensional object can be continuously performed from image information with a low influence of the bubble BU. As a result, a highly reliable three-dimensional object detection result can be output.

  Further, according to experiments by the inventors, it has been confirmed that the bubbles on the lens 11 tend to move upward rather than the lower side and the left and right side of the lens 11. The upper side of the lens 11 is a direction along a direction substantially opposite to the direction of gravity. For this reason, as shown in FIG. 22A, the control unit 39 of the present embodiment defines a peripheral region EB corresponding to a captured image or a portion that is separated from the central portion of the lens 11 by a predetermined distance upward. In the present embodiment, the control unit 39 sets the peripheral area EB along the peripheral edge F of the case C of the camera 10. The control part 39 of this embodiment suppresses that a solid object is detected from this peripheral area | region EB, and it is judged that the detected solid object is another vehicle. The peripheral area EB may be defined based on the central portion 0 of the captured image, or may be defined based on the central portion of the lens 11. Thus, in this embodiment, based on the tendency of the movement of the bubble BU attached to the lens 11 of the in-vehicle camera 10, the peripheral region EB is located at a position separated from the center of the captured image or the lens 11 by a predetermined distance upward. Define For this reason, it is possible to suppress detection of a three-dimensional object (including other vehicles) based on image information captured at a portion where there is a high probability that bubbles are present on the lens 11. As a result, it is possible to prevent an image resulting from the bubble BU attached to the lens 11 from being erroneously determined as a three-dimensional object (including other vehicles).

  The control unit 39 according to the present embodiment suppresses the detection of the three-dimensional object according to the distance from the host vehicle V in the detection areas A1 and A2 set for detecting the three-dimensional object. The control unit 39 suppresses the detection of the three-dimensional object when the distance from the host vehicle V is the first distance when the distance from the host vehicle is the second distance that is closer than the first distance. It is higher than the extent which suppresses that a solid thing is detected. In the detection areas A1 and A2, detection of a three-dimensional object is more strongly suppressed in a place far from the host vehicle V than in a place closer to the host vehicle. In the detection areas A1 and A2 corresponding to positions far from the host vehicle V, solid objects (including other vehicles) are difficult to detect. In the detection areas A1 and A2, the detection of the three-dimensional object may be suppressed so that the three-dimensional object (including other vehicles) is less likely to be detected as the distance from the host vehicle V increases. When performing the three-dimensional object detection process or the three-dimensional object determination process based on the image information corresponding to the detection areas A1 and A2, the control unit 39 sets a threshold value used in the three-dimensional object detection process or the three-dimensional object determination process from the host vehicle V. It is assumed that the region where the distance is relatively far is less likely to detect the three-dimensional object (including other vehicles) than the region where the distance from the host vehicle V is relatively close. A method for suppressing the detection of a three-dimensional object and the determination of another vehicle by changing the threshold will be described later.

  As shown in FIG. 22B, the control unit 39 defines a section E4 of the detection area A1 from the vicinity of the license plate LP at a predetermined distance along the direction EX1 that is separated from the license plate LP along the arrow EX toward the vanishing point. , Section E3, section E2, and section E1 are set. The distances between the sections E4, E3, E2, and E1 may be constant, may be a gradually decreasing distance, or may be a gradually increasing distance. Further, according to the characteristics of the lens 11 and the like, the distances between the section E2 and the section E3 on the center side of the detection area A1 may be set longer than the distance between the section E4 at the near end and the section E1 at the far end. Here, the detection area A1 on the right rear side of the host vehicle V will be described as an example, but the same applies to the detection area A2 on the left rear side of the host vehicle V. The controller 39 can set the section E4, the section E3, the section E2, and the section E1 of the detection area A2 from the vicinity of the license plate LP at predetermined distances along the direction EX2 that is separated from the license plate LP.

  Thus, in this embodiment, the detection of a three-dimensional object (including other vehicles) is suppressed as the distance from the host vehicle V increases. For this reason, it can suppress relatively strongly that it is judged that a solid thing exists based on a picked-up image caught in a part (the upper side of lens 11) where bubble BU tends to stay. On the other hand, the control unit 39 relatively gently suppresses the determination that the three-dimensional object exists in the region close to the host vehicle V in the detection regions A1 and A2. Thereby, while suppressing the influence of the bubble BU on the lens 11, the three-dimensional object (including other vehicles) in the portion close to the host vehicle V can be relatively easily detected. As a result, a highly reliable three-dimensional object detection result can be output.

  Secondly, the control unit 39 of the present embodiment responds to the detected speed of the host vehicle V when the lens state determination unit 38 determines that the lens 11 is in the predetermined bubble adhesion state. Thus, the detection of a three-dimensional object is suppressed. Similar to the first method, detecting a three-dimensional object includes determining that a three-dimensional object is present and determining that the three-dimensional object is another vehicle. The control part 39 of this embodiment detects that the solid object in the 2nd speed higher than the 1st speed is detected, the degree which suppresses that the detected solid object in the 1st speed of the own vehicle V is detected. Higher than the degree of suppression. When the speed is low, the detection of the three-dimensional object and the determination that the detected three-dimensional object is another vehicle are strongly suppressed than when the speed is high. Of course, the lower the speed, the stronger the detection of the three-dimensional object and the determination that the detected three-dimensional object is another vehicle may be strongly suppressed. In the present embodiment, the speed of the host vehicle V is acquired by the vehicle speed sensor 20 provided in the host vehicle V.

  As described above, the bubble BU attached to the lens 11 moves from the central portion 0 of the captured image, that is, the central portion of the lens 11 toward the periphery thereof. The bubble BU moves outward from the edge of the lens 11 and disappears from the surface of the lens 11. According to the inventors' experiment, it was confirmed that the bubble BU tends to disappear from the lens 11 when the speed of the host vehicle V is higher than when the speed of the host vehicle V is low. When the speed of the host vehicle V is slower, the bubbles BU tend to stay on the lens 11. Based on this knowledge, the control unit 39 of the present embodiment controls the degree of suppressing the detection of the three-dimensional object at the detected first speed of the host vehicle V at the second speed higher than the first speed. Is made stronger than the degree to suppress the detection. Here, the strength of the degree of suppression is realized by adjusting a threshold value or the like. For example, when it is difficult to detect a three-dimensional object (including other vehicles) by changing the threshold value to be higher, the threshold value is changed to be higher to increase the degree of suppression. The greater the difference between before and after the change, the greater the degree of suppression. The relationship between the vehicle speed and the degree to which detection of a three-dimensional object (including other vehicles) is not particularly limited, and may be a linear relationship as in Pattern 1 shown in FIG. 23A. As shown in the pattern 2 in the figure, a relationship showing multi-stage changes may be used, or as shown in the pattern 3 in the figure, a relationship showing curved changes may be used. Thus, in the environment where the speed of the host vehicle V is low and the bubble BU on the lens 11 is likely to remain, the detection of a three-dimensional object (including other vehicles) is suppressed. Thereby, not only generation | occurrence | production of the bubble BU but the environment where the bubble BU which changes with vehicle speeds extinguishes is considered, and the detection of a three-dimensional object (including other vehicles) can be suppressed appropriately.

  In the present embodiment, the degree of suppressing the detection of a three-dimensional object (including other vehicles) can be adjusted by widening the peripheral area EB where the detection is suppressed. Specifically, the control unit 39 of the present embodiment makes the area of the peripheral region EB at the detected first speed wider than the area of the peripheral region EB at the second speed higher than the first speed. When the speed is low, detection of a three-dimensional object can be suppressed by setting the peripheral area EB wider than when the speed is high. In this way, in the environment where the speed of the host vehicle V is low and the bubble BU on the lens 11 is likely to remain, the peripheral region EB is widened. Therefore, in consideration of the environment where the bubble BU corresponding to the vehicle speed disappears, The detection of solid objects (including other vehicles) can be suppressed appropriately.

  Thirdly, when the lens state determination unit 38 determines that the lens 11 is in the predetermined bubble adhesion state, the control unit 39 of the present embodiment detects a three-dimensional object at the first brightness. The degree to which the three-dimensional object is detected at the second brightness brighter than the first brightness is made stronger. When the brightness around the detected vehicle V is relatively dark, the detection of a three-dimensional object is suppressed more than when the brightness is bright. Similar to the first method, detecting a three-dimensional object includes determining that a three-dimensional object is present and determining that the three-dimensional object is another vehicle. The control unit 39 of the present embodiment controls the degree to which the three-dimensional object at the first brightness around the detected vehicle V is detected from the three-dimensional object at the second brightness brighter than the first brightness. Make it stronger than the degree to suppress detection. When the brightness is dark, detection of a three-dimensional object (including another vehicle) is more strongly suppressed than when the brightness is bright. In the present embodiment, the brightness around the host vehicle V is acquired by the illuminance sensor 21 included in the host vehicle V. The control unit 39 may estimate the brightness around the host vehicle V based on the location where the host vehicle V exists and the current time. At this time, the control unit 39 may estimate the correct brightness around the host vehicle V with reference to the sunset time and the sunrise time. The control unit 39 may estimate the brightness around the host vehicle V with reference to the weather information.

  According to the experiments by the inventors, it was confirmed that the influence of the bubble BU attached to the lens 11 on the accuracy of the result of the detection processing of the three-dimensional object is larger as the ambient brightness is lower. Based on this knowledge, the control unit 39 of the present embodiment suppresses detection of a three-dimensional object when the brightness around the detected vehicle V is darker than when it is bright. The relationship between the vehicle speed and the degree to which detection of a three-dimensional object (including other vehicles) is not particularly limited, and may be a linear relationship as in Pattern 1 shown in FIG. 23B. As shown in the pattern 2 in the figure, a relationship showing multi-stage changes may be used, or as shown in the pattern 3 in the figure, a relationship showing curved changes may be used. In this way, in an environment where the brightness around the host vehicle V is dark and erroneous detection is likely to occur due to the influence of the bubble BU on the lens 11, detection of a three-dimensional object (including other vehicles) is suppressed. . Accordingly, it is possible to appropriately suppress the detection of a three-dimensional object (including another vehicle) in consideration of even the brightness environment around the host vehicle V.

  In the present embodiment, the degree of suppressing the detection of a three-dimensional object (including other vehicles) can be adjusted by widening the peripheral area EB where the detection is suppressed. Specifically, the control unit 39 of the present embodiment sets the area of the peripheral area EB at the first brightness around the detected vehicle V to the area of the peripheral area EB at the second brightness brighter than the first brightness. By making it wider than this, detection of a three-dimensional object is suppressed. As described above, in the environment where the surrounding brightness of the host vehicle V is dark and the bubble BU on the lens 11 affects the detection result of the three-dimensional object, the peripheral area EB is widened. In consideration of this, detection of a three-dimensional object (including other vehicles) can be suppressed appropriately.

  The computer 30 of this embodiment further includes a light source detection unit 301. The light source detection unit 301 of the present embodiment detects a light source existing behind the host vehicle V. Specifically, the light source detection unit 301 detects a high-luminance region corresponding to a light source such as a headlight of another vehicle VX that travels behind the host vehicle V and a streetlight of a road on which the host vehicle V travels. The light source detection unit 301 calculates the luminance distribution of the captured image and extracts a region having a relatively higher luminance than other regions. And the area | region which shows the brightness | luminance more than a predetermined | prescribed luminance value among the extracted area | regions is detected as a high-intensity area | region. The “predetermined luminance value” that is a threshold value for detecting the high luminance region is set according to the brightness of the headlight, streetlight, etc. of the other vehicle VX measured through experiments. Further, the “predetermined luminance value” is preferably set according to the brightness of the headlights, street lamps, etc. of the other vehicle VX measured by experiments at night when the brightness of the host vehicle VX is low. The light source detection unit 301 of the present embodiment is a region having a luminance higher than that of other regions and having a luminance equal to or higher than a predetermined luminance value, a region having a predetermined area (number of pixels) or higher as a high luminance region. Detect as. The “predetermined area (number of pixels)” that is a threshold for detecting the high luminance area can be set according to the imaging characteristics of the camera 10 and the positions and sizes of the detection areas A1 and A2. Specifically, it is set according to the size of the corresponding high-luminance region such as the headlight and streetlight of the other vehicle VX measured by the experiment. Measured by experiment.

  The light source detection unit 301 of the present embodiment measures the distance between the host vehicle V and the light source based on the detected size of the high brightness area on the image. When the light source is the headlight of the other vehicle VX, the light source detection unit 301 measures the distance between the host vehicle V and the other vehicle VX based on the detected size of the high brightness area on the image. A method for detecting a light source such as a headlight or a streetlight of another vehicle VX based on a captured image of the camera 10 mounted on the host vehicle V and a method for measuring a distance from the host vehicle V to the light source are not particularly limited. The technique known at the time of filing this application can be used as appropriate.

  The control unit 39 of the present embodiment relaxes the degree of suppression when the detection of the three-dimensional object is suppressed according to the detected distance between the light source and the vehicle. This is because when the light source is detected, the possibility of erroneous detection due to the influence of the bubble BU is reduced, so that the necessity of suppressing the detection of the three-dimensional object is reduced. The control unit 39 of the present embodiment is configured such that the degree of relaxation of suppression at the first distance from the detected light source to the host vehicle V is at a second distance longer than the first distance from the detected light source to the host vehicle V. Make it stronger than the degree of mitigation. As the light source is closer to the host vehicle (the distance from the host vehicle V to the light source is shorter), the degree of suppression when the detection of the three-dimensional object is suppressed may be reduced. According to the experiments by the inventors, the reliability of the detection result of the rear other vehicle VX based on the light source is high. When a light source existing behind the host vehicle V is detected, there is a high possibility that another vehicle Vx exists behind the host vehicle V. When the light source behind the host vehicle V is detected, the control unit 39 according to the present embodiment determines that the erroneous detection caused by the presence of the bubbles of the lens 11 is unlikely to occur, and the three-dimensional object is difficult to detect. The degree of suppression control set to be relaxed. Specifically, the threshold value that has been changed so as to be difficult to detect a three-dimensional object is changed to a low value, and the threshold value that is changed to be low so that a three-dimensional object is difficult to be detected. In addition, the threshold range that is set narrowly is changed so as to make it difficult to detect the three-dimensional object. As described above, when the light source behind the host vehicle V is detected, the degree to which the detection of the other vehicle VX is suppressed is reduced when the distance to the light source is short than when the distance is long. When a light source behind the host vehicle V is detected, the other vehicle VX is detected under default conditions when the distance from the light source is short. Thereby, the other vehicle VX can be detected with high accuracy while eliminating the influence of the bubble BU adhering to the lens 11.

  When the light source behind the host vehicle V is detected, the control unit 39 of the present embodiment determines that the erroneous detection caused by the presence of the bubbles of the lens 11 is less likely to occur, and the three-dimensional object detection unit 33, 37, the peripheral area EB that is set so as to be difficult to detect the three-dimensional object is narrowed. The control unit 39 determines the degree of reduction in the area of the peripheral area EB according to the distance between the light source existing behind the vehicle and the host vehicle V. The extent to which the three-dimensional object detection units 33 and 37 reduce the area of the peripheral area EB at the first distance from the detected light source to the host vehicle V is longer than the first distance from the detected light source to the host vehicle V. The area of the peripheral area EB at the second distance is set larger than the degree of reduction. Thus, when a light source behind the host vehicle V is detected, the area of the peripheral region EB in which the detection of the other vehicle VX is suppressed is reduced as the distance from the light source is closer. That is, when a light source behind the host vehicle V is detected, the other vehicle VX is detected under the default condition when the distance from the light source is closer than when the distance from the light source is longer. To do. Thereby, the other vehicle VX can be detected with high accuracy while eliminating the influence of the bubble BU adhering to the lens 11.

As described above, the three-dimensional object is detected by the three-dimensional object detection units 33 and 37 and / or the three-dimensional object determination unit 37 determines that the three-dimensional object is another vehicle (synonymous with the detection of another vehicle. ), The control unit 39 changes each threshold value used for each process so that it is difficult to detect compared to the initial value, standard value, and other set values, or an output value compared with each threshold value. Is changed so that it is difficult to detect.
When mitigating the process of suppressing the detection of a three-dimensional object, the threshold values changed during the suppression process are returned so as to approach the initial value, standard value, and other set values, and compared with the threshold values. The output value is changed so that it can be easily detected.

  The details of the processing are as follows.

  When the three-dimensional object detection unit 33 that detects the three-dimensional object using the difference waveform information detects the three-dimensional object when the difference waveform information is equal to or greater than the predetermined first threshold value α, the control unit 39 determines that the lens 11 is the predetermined value. If it is determined that the three-dimensional object is attached, a control command for changing the first threshold value α so as to make it difficult to detect the three-dimensional object is generated, and this control command is output to the three-dimensional object detection unit 33.

  Similarly, when the three-dimensional object detection unit 33 detects a three-dimensional object when the differential waveform information is greater than or equal to the predetermined first threshold value α, the control unit 39 determines that the lens 11 is in a predetermined bubble adhesion state. In the case of the image of the bird's-eye view, the control command is generated by counting the number of pixels indicating a predetermined difference and changing the frequency distribution value to be low and outputting the control command. To the unit 38.

  When the three-dimensional object detection unit 33 that detects the three-dimensional object using the difference waveform information extracts the number of pixels indicating a pixel value equal to or greater than the threshold value p as the number of pixels indicating a predetermined difference, the control unit 39 Is determined to be in a predetermined bubble adhering state, a control command for changing the threshold value p so as to make it difficult to detect a three-dimensional object is generated, and this control command is output to the three-dimensional object detection hand unit 38.

  Similarly, when the three-dimensional object detection unit 33 extracts the number of pixels indicating a pixel value equal to or greater than the threshold p as the number of pixels indicating a predetermined difference, the control unit 39 determines that the lens 11 is in a predetermined bubble adhesion state. If a bird's-eye view image is converted to a viewpoint, a control command is generated and output along with the direction in which the three-dimensional object falls, and the number of pixels extracted on the difference image is reduced. It outputs to the object detection part 38. For example, the control unit 39 determines that the three-dimensional object is detected by the three-dimensional object detection unit 33 (or the three-dimensional object detection unit 37) or that the three-dimensional object is finally the other vehicle VX by the three-dimensional object determination unit 34. In order to prevent the result from being obtained, the detection areas A1 and A2 are partially masked, or the threshold value and output value used for detection and determination are adjusted.

  When the three-dimensional object detection unit 37 that detects a three-dimensional object using edge information extracts an edge line based on a pixel indicating a luminance difference equal to or greater than a predetermined threshold t, the control unit 39 determines that the lens 11 is in a predetermined bubble adhesion state. If it is determined that the three-dimensional object is not detected, a control command for changing the predetermined threshold t so as to be difficult to detect the three-dimensional object is generated, and the control command is output to the three-dimensional object detection unit 37.

  Similarly, when the three-dimensional object detection unit 37 that detects a three-dimensional object using edge information extracts an edge line based on a pixel that shows a luminance difference equal to or greater than a predetermined threshold t, the control unit 39 determines that the lens 11 is a predetermined bubble. If it is determined that the pixel is in the attached state, a control command for changing and outputting the luminance value of the pixel is generated, and the control command is output to the three-dimensional object detection unit 37.

  When the three-dimensional object detection unit 37 that detects a three-dimensional object using edge information detects a three-dimensional object based on an edge line having a length equal to or greater than the threshold value θ included in the edge information, the control unit 39 has the lens 11 If it is determined that the state is the predetermined bubble adhesion state, a control command for changing the threshold value θ so as to make it difficult to detect a three-dimensional object is generated, and this control command is output to the three-dimensional object detection unit 37.

  Similarly, when the three-dimensional object detection unit 37 that detects a three-dimensional object using edge information detects a three-dimensional object based on an edge line having a length equal to or greater than the threshold value θ included in the edge information, the control unit 39 includes a lens When it is determined that 11 is in a predetermined bubble adhesion state, a control command is generated for changing the value of the length of the edge line of the detected edge information to be output, and the control command is output to the three-dimensional object detection unit. To 37.

  The number of edge lines having a length equal to or greater than a predetermined length included in the edge information, for example, the number of edge lines having a length equal to or greater than the threshold θ is included in the edge information by the three-dimensional object detection unit 37 that detects the solid object using the edge information is equal to or greater than the second threshold β. In the case of detecting a three-dimensional object based on whether or not the three-dimensional object is detected, the control unit 39 determines that the three-dimensional object is difficult to detect when the lens 11 is determined to be in a predetermined bubble adhering state. A control command for changing β high is generated, and this control command is output to the three-dimensional object detection unit 37.

  The number of edge lines having a length equal to or greater than a predetermined length included in the edge information, for example, the number of edge lines having a length equal to or greater than the threshold θ is included in the edge information by the three-dimensional object detection unit 37 that detects the solid object using the edge information is equal to or greater than the second threshold β. In the case of detecting a three-dimensional object based on the determination of whether or not the control unit 39 determines that the lens 11 is in a predetermined bubble adhering state, the number of edge lines having a detected length equal to or greater than the predetermined length is determined. Is output to the three-dimensional object detection unit 37.

  When the three-dimensional object determination unit 34 determines that the three-dimensional object is another vehicle when the detected moving speed of the three-dimensional object is equal to or higher than a predetermined speed, the control unit 39 If 11 is determined to be in a predetermined bubble adhesion state, a control command is generated to change the predetermined speed to be a lower limit when determining that the three-dimensional object is another vehicle so that the three-dimensional object is not easily detected. The control command is output to the three-dimensional object determination unit 34.

  Similarly, when the three-dimensional object determination unit 34 determines that the three-dimensional object is another vehicle when the movement speed of the detected three-dimensional object is equal to or higher than a predetermined speed, the control unit 39 When it is determined that 11 is in a predetermined bubble adhesion state, the moving speed of the three-dimensional object compared with the predetermined speed that is the lower limit when determining that the three-dimensional object is another vehicle is changed and output. A control command is generated, and the control command is output to the three-dimensional object determination unit 34.

  When the three-dimensional object determination unit 34 determines that the three-dimensional object is another vehicle when the detected moving speed of the three-dimensional object is less than a predetermined speed, the control unit 39 When it is determined that 11 is in a predetermined bubble adhering state, a control command for changing the predetermined speed, which is an upper limit when determining that the three-dimensional object is another vehicle, is generated, and this control command is used as the three-dimensional object. The data is output to the determination unit 34.

  Similarly, when the movement speed of the three-dimensional object detected by the three-dimensional object determination unit 34 is less than a predetermined speed set in advance, when determining that the three-dimensional object is another vehicle, the control unit 39 causes the lens 11 to be If it is determined that the predetermined bubble is attached, a control command is generated to change the moving speed of the three-dimensional object higher than the predetermined speed that is the upper limit when determining that the three-dimensional object is another vehicle. The control command is output to the three-dimensional object determination unit 34.

  Here, the “movement speed” includes the absolute speed of the three-dimensional object and the relative speed of the three-dimensional object with respect to the host vehicle. The absolute speed of the three-dimensional object may be calculated from the relative speed of the three-dimensional object, and the relative speed of the three-dimensional object may be calculated from the absolute speed of the three-dimensional object.

  Hereinafter, based on the flowchart of FIG. 24A-FIG. 24C, the control procedure of the solid-object detection apparatus 1 of this embodiment is demonstrated.

FIG. 24A is a flowchart illustrating a control procedure of a process for suppressing the detection of a three-dimensional object by setting the peripheral area EB.
First, in step S61 shown in FIG. 24A, the lens state determination unit 38 determines whether or not bubbles are attached to the lens 11 and a predetermined bubble attachment state is present. As described above, the “bubble adhering state” defined for determining whether or not to perform the three-dimensional object detection suppression process is the number of detected edges and / or the detection density of the bubble BU, and the own vehicle V. It can be defined on the basis of the amount of change in the edge of a fixed object such as the bumper, license plate, or camera 10 case, and the amount of change in the brightness of bubbles in the entire image.

  When the bubble BU adheres to the lens 11 and it is evaluated as a predetermined “bubble attachment state”, the process proceeds to step S62, and a peripheral region EB in which detection of a three-dimensional object is suppressed is set. The peripheral area EB can be an area separated by a predetermined distance from the center of the captured image. In particular, in the present embodiment, the area is set on the upper side of the lens 11 (on the side opposite to the direction of its own weight).

  In step S63, processing for suppressing the detection of a three-dimensional object is executed. In accordance with a command from the control unit 39, the three-dimensional object detection units 33 and 37 mask the peripheral area EB and do not detect a three-dimensional object from the image information corresponding to the peripheral area EB.

  Similarly, in step S64, processing for suppressing detection of a three-dimensional object is executed. In accordance with a command from the control unit 39, when the three-dimensional object detection units 33 and 37 perform a process of detecting a three-dimensional object from image information corresponding to the peripheral area EB, the three-dimensional object has various threshold values used for the three-dimensional object detection. It changes so that it is hard to detect, and it changes and outputs the output value compared with various threshold values so that a solid thing is hard to be detected.

Incidentally, the first threshold value α is for determining the peak of the differential waveform DW _t in step S7 of FIG. The threshold value θ is a threshold value for determining a value (edge length) obtained by normalizing the sum of the continuity c of the attribute of each attention point Pa in step S29 of FIG. 17, and the second threshold value β is the step of FIG. 34 is a threshold value for evaluating the amount (number) of edge lines. In this way, by changing the determination threshold value higher, the detection sensitivity is adjusted so that the other vehicle VX traveling next to the traveling lane of the host vehicle V is hard to be detected. It is possible to prevent erroneous detection as the vehicle VX. Other threshold values are changed as described above.

In step 641, according to the instruction of the control unit 39, the three-dimensional object detection units 33 and 37 perform a process of detecting a three-dimensional object from the image information corresponding to the detection areas A1 and A2, and the own vehicle V (license plate or the like). As the distance from the object increases, the various thresholds used for detecting the three-dimensional object are changed so that the three-dimensional object is difficult to detect, and the output value compared with the various threshold values is changed so that the three-dimensional object is difficult to detect. To do. The control unit 39 according to the present embodiment outputs a control command that counts the number of pixels indicating a predetermined difference on the difference image of the bird's eye view image and outputs a low frequency distribution value to the three-dimensional object detection unit 33. The value obtained by counting the number of pixels indicating a predetermined difference on the difference image of the bird's-eye view image and performing frequency distribution is the value on the vertical axis of the difference waveform DW _t generated in step S5 of FIG.

  In addition, the control unit 39 according to the present embodiment outputs a control command for outputting the detected edge information to the three-dimensional object detection unit 37. The detected edge information includes the length of the edge line that is a value obtained by normalizing the sum of the continuity c of the attribute of each attention point Pa in step S29 in FIG. 17, and the amount of edge line in step 34 in FIG. It is. When it is determined that the lens 11 is in the predetermined bubble adhesion state, the control unit 39 does not detect the three-dimensional object in the next process so that it is not detected as a three-dimensional object from the captured image of the predetermined peripheral area. The value obtained by normalizing the sum of the continuity c of the attribute of each attention point Pa or the amount of the edge line is changed to be low. In this way, by reducing the output value, the detection sensitivity can be adjusted so that the other vehicle VX traveling next to the traveling lane of the host vehicle V is difficult to be detected. Therefore, the foreign matter attached to the lens 11 is removed from the adjacent lane. It is possible to prevent erroneous detection as the traveling other vehicle VX.

  In subsequent step S65, a three-dimensional object (another vehicle) is detected based on the difference waveform information or the edge information. Further, in step S66, it is determined whether or not the three-dimensional object detected in step S65 is another vehicle VX. If the three-dimensional object is another vehicle VX, a determination result that there is another vehicle in step S67. When the three-dimensional object is not the other vehicle VX, a determination result that no other vehicle exists is output in step S68. The processes in step S65 and step S66 are the detection process of the other vehicle VX based on the difference waveform information described in FIGS. 11 and 12, and the detection process of the other vehicle VX based on the edge information described in FIGS. Common. If no three-dimensional object is detected in step S65, it may be determined that there is no other vehicle, or the three-dimensional object detection process may be terminated.

FIG. 24B is a flowchart illustrating a control procedure of processing for suppressing detection of a three-dimensional object according to the vehicle speed of the host vehicle V.
First, in step S61 shown in FIG. 24B, the lens state determination unit 38 determines whether bubbles are attached to the lens 11 and are in a predetermined bubble attachment state by a method similar to the method described in FIG. 24A. .

  When the lens state determination unit 38 has a bubble BU attached to the lens 11 and evaluates it as a predetermined “bubble attachment state”, the process proceeds to step S71. In step S <b> 71, the control unit 39 acquires the vehicle speed of the host vehicle V from the vehicle speed sensor 20. In subsequent step S72, the peripheral area EB in which the detection of the three-dimensional object is suppressed is set in the three-dimensional object detection units 33 and 37. The peripheral area EB is set by the method described above.

  In step S73, a process for suppressing the detection of the three-dimensional object is executed. In accordance with a command from the control unit 39, the three-dimensional object detection units 33 and 37 set the peripheral region EB wider as the vehicle speed is lower. The three-dimensional object detection units 33 and 37 mask the peripheral area EB, and do not detect a three-dimensional object from the image information corresponding to the peripheral area EB.

Similarly, in step S74, processing for suppressing detection of a three-dimensional object is executed. In accordance with a command from the control unit 39, the three-dimensional object detection units 33 and 37 increase various threshold values used for the three-dimensional object detection when performing a process of detecting the three-dimensional object from the image information corresponding to the peripheral area EB. The output value compared with various threshold values is output low. The threshold value and the output value are changed by the method described above.
And the process of step S65-S68 which performs the process of step S65-S68 is the same procedure as the process of step S65-S68 demonstrated in FIG. 24A.

FIG. 24C is a flowchart illustrating a control procedure of a process of suppressing detection of a three-dimensional object according to the brightness around the host vehicle V.
First, in step S61 shown in FIG. 24C, the lens state determination unit 38 determines whether bubbles are attached to the lens 11 and are in a predetermined bubble attachment state by a method similar to the method described in FIG. 24A. .

  If the lens state determination unit 38 has attached the bubble BU to the lens 11 and has evaluated it as a predetermined “bubble attachment state”, the process proceeds to step S81. In step S <b> 71, the control unit 39 acquires the brightness around the host vehicle V from the illuminance sensor 21. In the subsequent step S82, the three-dimensional object detection units 33 and 37 are set to the peripheral area EB in which the detection of the three-dimensional object is suppressed. The peripheral area EB is set by the method described above.

  In step S83, processing for suppressing the detection of a three-dimensional object is executed. In accordance with a command from the control unit 39, the three-dimensional object detection units 33 and 37 set the peripheral region EB wider as the brightness around the host vehicle V becomes darker. The three-dimensional object detection units 33 and 37 mask the peripheral area EB, and do not detect a three-dimensional object from the image information corresponding to the peripheral area EB.

  Similarly, in step S84, processing for suppressing detection of a three-dimensional object is executed. In accordance with a command from the control unit 39, the three-dimensional object detection units 33 and 37 increase various threshold values used for the three-dimensional object detection when performing a process of detecting the three-dimensional object from the image information corresponding to the peripheral area EB. The output value compared with various threshold values is output low. The threshold value and the output value are changed by the method described above. And the process of step S65-S68 which performs the process of step S65-S68 is the same procedure as the process of step S65-S68 demonstrated in FIG. 24A.

  According to the three-dimensional object detection device 1 and the three-dimensional object detection method according to this embodiment of the present invention configured and operating as described above, the following effects are obtained.

[1] According to the three-dimensional object detection device 1 of the present embodiment of the present invention, when the bubble BU adheres to the lens 11 and is determined to be in the predetermined bubble adhesion state, the predetermined object defined in the captured image is used. Since the three-dimensional object is suppressed from being detected based on the image included in the peripheral area EB, the influence of the bubble BU attached to the lens 11 on the detection result of the three-dimensional object is reduced. It can be detected. That is, according to the three-dimensional object detection device 1 of the present embodiment of the present invention, it is possible to suppress detection of a three-dimensional object (including other vehicles) from the image information of an area where the bubble BU is likely to stay. It can reduce that the image resulting from the bubble BU adhering to 11 is erroneously determined as a three-dimensional object (including other vehicles). As a result, a highly reliable three-dimensional object detection result can be output.

[2] According to the three-dimensional object detection device 1 of the present embodiment of the present invention, the degree to which detection of the detected three-dimensional object at the first speed of the host vehicle V is higher than the first speed. It is set higher than the degree of suppressing the detection of the three-dimensional object at the second speed. Thereby, in the environment where the speed of the own vehicle V is low and the bubble BU on the lens 11 is likely to remain, it is possible to suppress detection of a three-dimensional object (including other vehicles). As a result, it is possible to appropriately suppress detection of a three-dimensional object (including other vehicles) in consideration of the disappearance environment of the bubble BU according to the vehicle speed.

[3] According to the three-dimensional object detection device 1 of the present embodiment of the present invention, the degree to which detection of a three-dimensional object at the first brightness around the detected vehicle V is suppressed from the first brightness. Is made stronger than the degree to suppress the detection of the three-dimensional object at the bright second brightness. Thereby, in the environment where the brightness around the host vehicle V is dark and erroneous detection is likely to occur due to the influence of the bubble BU on the lens 11, it is possible to suppress detection of a three-dimensional object (including another vehicle). As a result, it is possible to appropriately suppress detection of a three-dimensional object (including other vehicles) in consideration of the environment of brightness around the host vehicle V that increases or decreases the influence degree of the bubble BU.

[4] Since the three-dimensional object detection device 1 according to the present embodiment of the present invention suppresses detection of a three-dimensional object based on an image included in a predetermined peripheral area EB according to the vehicle speed or brightness, the host vehicle Considering even the environment of brightness around V, detection of a three-dimensional object (including other vehicles) can be appropriately suppressed.

[5] In the three-dimensional object detection device 1 of the present embodiment of the present invention, the area of the peripheral area EB is determined according to the detected speed, and the area of the peripheral area EB at the detected first speed is determined as the first speed. It is made wider than the area of the peripheral region EB at a higher second speed. In this way, in the environment where the speed of the host vehicle V is low and the bubble BU on the lens 11 is likely to remain, the peripheral region EB is widened. Therefore, in consideration of the environment where the bubble BU corresponding to the vehicle speed disappears, The detection of solid objects (including other vehicles) can be suppressed appropriately.

[6] In the three-dimensional object detection device 1 of the present embodiment of the present invention, the area of the peripheral area EB at the detected first brightness is larger than the area of the peripheral area EB at the second brightness that is brighter than the first brightness. Make it wide. As described above, in the environment where the surrounding brightness of the host vehicle V is dark and the bubble BU on the lens 11 affects the detection result of the three-dimensional object, the peripheral area EB is widened. In consideration of this, detection of a three-dimensional object (including other vehicles) can be suppressed appropriately.

[7] The three-dimensional object detection device 1 of the present embodiment of the present invention sets the peripheral region EB in a predetermined upper region that is separated by a predetermined distance or more along a direction substantially opposite to the gravitational direction in the captured image. 11 can suppress the detection of a three-dimensional object (including other vehicles) based on image information captured at a portion having a high probability that bubbles are present. As a result, it is possible to prevent an image resulting from the bubble BU attached to the lens 11 from being erroneously determined as a three-dimensional object (including other vehicles).

[8] The three-dimensional object detection device 1 according to the present embodiment of the present invention strongly suppresses detection of a three-dimensional object at a place far from the host vehicle V from a place near the host vehicle V in the detection areas A1 and A2. To do. For this reason, it is relatively strongly suppressed that the three-dimensional object is present based on the captured image captured in the portion where the bubble BU is likely to stay, and the portion where the bubble BU does not accumulate is three-dimensionally performed as usual. Can determine the existence of an object. As a result, a highly reliable three-dimensional object detection result can be output.

[9] The three-dimensional object detection device 1 of the present embodiment of the present invention is configured such that the degree of relaxation of suppression at the first distance from the detected light source to the host vehicle V is the first from the detected light source to the host vehicle V. The degree of relaxation of suppression at the second distance longer than the distance is made stronger. When the light source behind the host vehicle V is detected, the three-dimensional object detection device 1 according to the present embodiment determines that a false detection caused by the presence of bubbles in the lens 11 is unlikely to occur, and the three-dimensional object is detected. The degree of suppression control set so as to be difficult to be performed is reduced. Thereby, the other vehicle VX can be detected with high accuracy while eliminating the influence of the bubble BU adhering to the lens 11.

[10] The three-dimensional object detection device 1 of the present embodiment of the present invention reduces the area of the peripheral area EB at the first distance from the detected light source to the host vehicle V to the extent that the host vehicle V is detected from the detected light source. The area of the peripheral area EB at the second distance longer than the first distance is made larger than the degree of reduction. When a light source behind the host vehicle V is detected, the other vehicle VX is detected under the default condition when the distance from the light source is closer than when the distance from the light source is longer. Thereby, the other vehicle VX can be detected with high accuracy while eliminating the influence of the bubble BU adhering to the lens 11.

[11] The three-dimensional object detection device 1 of the present embodiment of the present invention aligns the positions of the bird's-eye view images at different times on the bird's-eye view, and is generated based on the difference image of the aligned bird's-eye view images. The three-dimensional object can be detected with high accuracy based on the difference waveform information.

[12] The three-dimensional object detection device 1 of the present embodiment of the present invention detects a three-dimensional object with high accuracy based on edge information detected along the direction in which the three-dimensional object falls when the viewpoint is converted into a bird's-eye view image. it can.

[13] When the three-dimensional object detection method of the present embodiment of the present invention is used, the same effects as those of the three-dimensional object detection device 1 described above are achieved.

  The camera 10 corresponds to an imaging unit according to the present invention, and the viewpoint conversion unit 31 corresponds to an image conversion unit according to the present invention. The alignment unit 32, the three-dimensional object detection unit 33, the three-dimensional object determination unit 34, and the control The unit 39 corresponds to the three-dimensional object detection means according to the present invention, and the luminance difference calculation unit 35, the edge line detection unit 36, the three-dimensional object detection unit 37, the three-dimensional object determination unit 34, and the control unit 39 are the three-dimensional object according to the present invention. The lens state determination unit 38 corresponds to a lens state determination unit, the vehicle speed sensor 20 corresponds to a vehicle speed sensor, the illuminance sensor 21 corresponds to a brightness detection unit, and the light source detection unit 301 corresponds to an object detection unit. It corresponds to light source detection means. The lens cleaning device 100 corresponds to a lens cleaning unit, the control device 110 of the cleaning device corresponds to a cleaning control unit, and the lens state determination unit 38 of the control device 110 corresponds to a lens state determination unit.

  The “distribution information” in the present invention is such that the luminance difference is greater than or equal to a predetermined threshold in the direction in which the three-dimensional object falls when the viewpoint is converted to the bird's-eye view image on the bird's-eye view image obtained by the viewpoint conversion unit 31 (image conversion means). It is the information regarding the distribution of pixels. The “distribution information” includes at least “difference waveform information” and “edge information” in the present invention.

  The alignment unit 32 according to the present embodiment aligns the positions of the bird's-eye view images at different times on the bird's-eye view, and obtains the aligned bird's-eye view image. This can be performed with accuracy according to the type and required detection accuracy. It may be a strict alignment process such as aligning positions based on the same time and the same position, or may be a loose alignment process that grasps the coordinates of each bird's-eye view image.

Second Embodiment
Hereinafter, the camera apparatus 1000 of this embodiment will be described.
An example of an embodiment of the camera apparatus 1000 according to the second embodiment is shown in FIG. In this embodiment, about the part which is common with the solid-object detection apparatus 1 of 1st Embodiment, in order to avoid the overlapping description, the description is used. The lens cleaning device 100 according to the present embodiment will be described as an example applied to the three-dimensional object detection device 1 described in the first embodiment. However, the lens cleaning device 100 according to the present embodiment may be applied to various types of travel support devices that use captured images of the camera device 1000. it can.

  The camera device 1000 of this embodiment includes a camera 10 and a lens cleaning device 100. The camera apparatus 1000 according to the present embodiment may include the three-dimensional object detection apparatus 1 described in the first embodiment. In the first embodiment, the method of reducing the influence of bubbles generated by cleaning the lens 11 on the accuracy of the determination result of the three-dimensional object detection process has been described from the viewpoint of controlling the three-dimensional object detection process. The camera apparatus 1000 according to the present embodiment has a viewpoint of controlling the cleaning method of the lens 11 as a method of reducing the influence of bubbles generated by the lens cleaning apparatus 100 cleaning the lens 11 on the detection result of the three-dimensional object. It explains from.

  First, an example of the lens cleaning device 100 provided in the camera device 1000 according to the present embodiment will be described with reference to FIGS. FIG. 25 is a block diagram illustrating a configuration of a lens cleaning device for an in-vehicle camera according to an embodiment of the present invention. As shown in FIG. 25, the lens cleaning device 100 according to this embodiment includes a cleaning liquid tank 2 that accumulates cleaning liquid, a cleaning liquid pump 3 that sends out the cleaning liquid accumulated in the cleaning liquid tank 2, and an air pump 5 that sends out compressed air. And a nozzle 7 that discharges cleaning liquid, compressed air, or a mixture of the cleaning liquid and compressed air toward the lens surface of the camera 10. The lens cleaning device 100 cleans the lens 11 using the cleaning liquid stored in the cleaning liquid tank 2.

  Furthermore, the cleaning liquid pipe 4 that guides the cleaning liquid sent out by the cleaning liquid pump 3 to the secondary tank 13 that accumulates the cleaning liquid, and the air that leads the compressed air sent out by the air pump 5 to the nozzle 7 of the nozzle unit 22. A pipe 6 and a control device 110 that controls the operation of the cleaning liquid pump 3 and the air pump 5 are provided.

  FIG. 26A is a perspective view showing a state in which the lens cleaning device 100 according to this embodiment is installed in the camera 10 mounted on the rear part of the vehicle, and FIG. 26B is shown in FIG. It is the figure which looked at the lens washing | cleaning apparatus 100 from the "A" direction. As shown in FIG. 26A, a nozzle unit 22 that is also fixed to the rear of the vehicle and cleans the surface of the lens 11 is provided in the vicinity of the side of the camera 10 fixed to the rear of the vehicle. The nozzle unit 22 is provided with a nozzle 7 that ejects cleaning liquid and compressed air toward the surface of the lens 11 and a cap 7d. As shown in FIG. 26 (b), the nozzle 7 is provided with two discharge ports 10a and 10b for ejecting cleaning liquid and compressed air at the tip thereof. In other words, the cleaning liquid and the compressed air are ejected from the discharge ports 10 a and 10 b of the nozzle 7 toward the surface of the lens 11, thereby removing foreign matters attached to the surface of the lens 11.

  FIG. 27 is a partially broken perspective view of the nozzle unit 22 shown in FIG. As shown in FIG. 27, the nozzle 7 provided on the tip side of the nozzle unit 22 is provided with an air passage 12 for introducing compressed air at the center thereof, and a cleaning liquid is introduced on both the left and right sides of the air passage 12. Cleaning liquid passages 11a and 11b are provided. The tips of the air passage 12 and the cleaning liquid passages 11a and 11b are bent at substantially right angles so as to face the surface of the lens 11 of the camera 10.

  Further, a secondary tank 13 for temporarily accumulating the cleaning liquid is provided upstream of the cleaning liquid passages 11a and 11b. A plug 13 a for connecting the cleaning liquid pipe 4 and a plug 13 b for connecting the air pipe 6 are provided on the side of the secondary tank 13, and the plug 13 b is connected to the secondary tank 13. It is connected to the air passage 12 through a flow path provided below. That is, the compressed air introduced into the nozzle unit 22 via the plug 13b is directly introduced into the air passage 12.

  The plug 13a is connected to the secondary tank 13, and the cleaning liquid supplied via the plug 13a flows into the secondary tank 13 from above. At this time, the pipe connected from the plug 13a to the secondary tank 13 faces the vertical direction as indicated by reference numeral 23 in FIG. Details of the pipe 23 will be described later.

  As shown in FIG. 27, the bottom of the secondary tank 13 is connected to two systems of cleaning liquid passages 11a and 11b. Therefore, the compressed air sent out from the air pump 5 shown in FIG. 25 is introduced into the air passage 12 of the nozzle 7 via the air pipe 6, while the cleaning liquid sent out from the cleaning liquid pump 3 is sent to the secondary tank. After being accumulated in 13, the cleaning liquid passages 11a and 11b of the two systems are introduced.

  FIG. 28B is an explanatory diagram showing a detailed configuration of the nozzle tip, and shows a cross-sectional view of a portion denoted by reference numeral P1 shown in FIG. As shown in FIG. 28B, the tip of the nozzle 7 is provided with an air passage 12 at the center, and two cleaning liquid passages 11a and 11b are provided so as to sandwich the air passage 12.

  The cleaning liquid passages 11a and 11b are connected to the front end portions 15a and 15b. At this time, the flow passage areas of the front end portions 15a and 15b are made smaller than the flow passage areas of the cleaning liquid passages 11a and 11b. Therefore, the flow rate of the cleaning liquid flowing through the cleaning liquid passages 11a and 11b increases in the tip portions 15a and 15b.

  On the other hand, the tip of the air passage 12 is branched into two tip portions 14a and 14b. The flow passage areas of the tip portions 14 a and 14 b are smaller than the flow passage area of the air passage 12. Therefore, the flow rate of the compressed air flowing through the air passage 12 increases when passing through the tip portions 14a and 14b.

  And the front-end | tip part 15a of one washing | cleaning liquid channel | path 11a and the one front-end | tip part 14a of the air path 12 merge, and it is set as the merge path 16a, and this front-end | tip is made into the discharge outlet 10a (refer FIG.26 (b)). . Further, the tip portion 15b of the other cleaning liquid passage 11b and the other tip portion 14b of the air passage 12 merge to form a merge channel 16b, which is the discharge port 10b (see FIG. 26B). At this time, the combined flow path 16a and the combined flow path 16b are directed in the direction of spreading toward the distal end side.

  Therefore, when the cleaning liquid sent out from the cleaning liquid pump 3 shown in FIG. 25 is accumulated in the secondary tank 13 and the compressed air is sent out from the air pump 5, the compressed air is jetted at a higher flow rate. When the compressed air is injected, the cleaning liquid passages 11a and 11b become negative pressure, and the cleaning liquid accumulated in the secondary tank 13 is sucked. For this reason, the compressed air and the cleaning liquid are sprayed from the discharge ports 10 a and 10 b via the two combined flow paths 16 a and 16 b and sprayed onto the surface of the lens 11. At this time, as shown in FIG. 29, the liquid in which the cleaning liquid and the compressed air are mixed is ejected in the spreading direction, and the entire surface of the lens 11 can be cleaned.

  Further, as shown in FIG. 28B, the ejection surface 7a at the tip of the nozzle 7 is configured to protrude forward from the surrounding side surface 7b. Therefore, it is possible to prevent the cleaning liquid sprayed from the discharge ports 10 a and 10 b from adhering to the side surface 7 b of the nozzle 7. Specifically, it is possible to prevent the cleaning liquid from adhering to the regions indicated by reference numerals P2 and P3 in FIG.

  FIG. 30B is a cross-sectional view of the nozzle unit 22 shown in FIG. 30A viewed from the “D” direction. As shown in FIG. 30B, a slight gap is provided between the bottom surface 7 c of the nozzle 7 and the surface of the camera 10. Furthermore, the width of the gap is configured to become narrower toward the back side. With such a configuration, even when the cleaning liquid enters between the bottom surface 7c of the nozzle 7 and the top surface 1b of the camera 10, the cleaning liquid is gradually pushed out to the back side of the gap portion between the nozzle 7 and the camera 10 by the surface tension. The light is emitted to the outside from the left and right sides of the camera 10 when viewed from the front. In other words, the presence of a slight gap between the bottom surface 7c of the nozzle 7 and the top surface 1b of the camera 10 can avoid problems such as the cleaning liquid staying and solidifying.

  Further, as shown in FIG. 30 (b), a supply port 13c for supplying a cleaning liquid into the secondary tank 13 is provided at the upper part of the secondary tank 13 provided on the upstream side of the nozzle 7. The supply port 13c is provided with a pipe 23 that faces in the vertical direction. The pipe 23 is connected to the plug 13a shown in FIG. When the supply of the cleaning liquid from the cleaning liquid pump 3 (see FIG. 25) is stopped by the piping 23 being directed vertically, the cleaning liquid accumulated in the pipe irregularly flows into the secondary tank 13. Can be avoided. That is, it is possible to prevent the cleaning liquid from flowing into the secondary tank 13 due to vibration or the like when the inside of the secondary tank 13 is empty.

  A check valve 24 is provided on the upper surface of the secondary tank 13. The check valve 24 is, for example, an umbrella valve, and when the pressure in the secondary tank 13 becomes negative, the valve is released and outside air is introduced from the vent hole 25 so that the pressure in the secondary tank 13 is reduced. When positive pressure is reached, the valve is closed to prevent release to the outside air.

  Further, as shown in FIG. 30 (b), the bottom surface 13d of the secondary tank 13 is inclined so as to descend toward the front side (left side in the figure), and the outlet piping and nozzle of the secondary tank 13 Similarly, the cleaning liquid passages 11 a and 11 b and the air passage 12 (see FIG. 27) provided in 7 are inclined so as to descend toward the front side. By adopting such a configuration, the cleaning liquid accumulated in the secondary tank 13 does not stay in a certain place, and surely flows to the downstream side due to the inclination of each part.

  Next, the control device 110 that controls the cleaning operation of the lens cleaning device 100 will be described. FIG. 31 shows a schematic configuration of the lens cleaning device 100 of the present embodiment. As shown in FIG. 31, the lens cleaning device 100 is formed at the cleaning liquid tank 2 that stores the cleaning liquid at least temporarily, the flow path 3 that conveys the cleaning liquid supplied from the cleaning liquid tank 2, and the end of the flow path 3. The discharge ports 10a and 10b for discharging the cleaning liquid W to the surface of the lens 11, the air compressor 5 for compressing the gas supplied from the outside, the tube 6 for transporting the compressed gas, and the end of the tube 6 are formed. The nozzles 14a and 14b for blowing the gas E on the surface of the lens 11 are provided.

  The control device 110 controls the operations of the above components of the lens cleaning device 100. The control device 110 includes a lens state determination unit 38, a temperature acquisition unit 111, and a vehicle speed acquisition unit 112. The control device 110 causes the lens cleaning device 100 to execute a control program according to a predetermined lens cleaning process defined in advance. The lens cleaning device 100 cleans the lens 11 according to the lens cleaning process under the instruction of the control device 110. In the present embodiment, the control device 110 of the lens cleaning device 100 includes the lens state determination unit 38, but the computer 30 of the three-dimensional object detection device 1 may include the lens state determination unit 38. In this case, the lens cleaning device 100 acquires the determination result of the lens state from the lens state determination unit 38 included in the computer 30 of the three-dimensional object detection device 1.

  The lens cleaning device 100 according to the present embodiment is a cleaning mode in which a cleaning liquid and compressed air are jetted to clean the lens 11, a drying mode in which only compressed air is sent and water droplets attached to the lens 11 are removed, and the cleaning liquid is intermittent. In particular, there are three modes: a wet mode in which the surface of the lens 11 is discharged to wet the surface of the lens 11.

  Here, the basic operation will be described. In the cleaning mode, when both the cleaning liquid pump 3 and the air pump 5 are driven at time t1, the cleaning liquid stored in the cleaning liquid tank 2 is supplied to the secondary tank 13 via the cleaning liquid pipe 4, and the secondary tank The cleaning liquid is accumulated in 13. Compressed air delivered from the air pump 5 is introduced into the air passage 12 in the nozzle 7 shown in FIG. 27 via the air pipe 6, and then the compressed air is supplied to the tip portion shown in FIG. 28 (b). 14a and 14b are sent toward the combined flow paths 16a and 16b. At this time, since the flow path areas of the front end portions 14a and 14b are set to be smaller than those of the air passage 12, the air flow rate is increased at the front end portions 14a and 14b. Accordingly, the tip portions 15a and 15b of the cleaning liquid passages 11a and 11b on the downstream side of the combined flow paths 16a and 16b become negative pressure, the cleaning liquid accumulated in the secondary tank 13 is sucked, and the sucked cleaning liquid is washed with the cleaning liquid passage 11a. , 11b and flows into the combined flow paths 16a, 16b.

  As a result, the cleaning liquid is mist-like and injected together with the compressed air from the combined flow paths 16a and 16b. Accordingly, the mist-like cleaning liquid can be ejected and sprayed onto the surface of the lens 11 from the discharge ports 10a and 10b which are the tips of the joint channels 16a and 16b. For this reason, the foreign material adhering to the surface of the lens 11 can be removed by the synergistic action of the mist-like cleaning liquid and the air pressure. That is, in the cleaning mode, the air pump 5 is operated to inject compressed air from the discharge ports 10a and 10b, and to suck the cleaning liquid supplied to the cleaning liquid passages 11a and 11b with a negative pressure generated by the injection of the compressed air. Then, the cleaning liquid is jetted from the discharge ports 10a and 10b, and the lens surface 11 is washed with the jetted compressed air and the cleaning liquid.

  When all the cleaning liquid in the secondary tank 13 is jetted, only compressed air is jetted thereafter, and water droplets attached to the lens 11 can be removed by this compressed air.

  The drying mode will be described. In the drying mode, only the air pump 5 is driven in a state where the cleaning liquid is not accumulated in the secondary tank 13. Specifically, the cleaning liquid pump 3 is stopped, and the air pump 5 is driven at time t10 to t11 (for example, 2 seconds). Then, the compressed air is jetted from the discharge ports 10 a and 10 b through the front end portions 14 a and 14 b of the air passage 12 and the combined flow paths 16 a and 16 b, and is blown onto the surface of the lens 11. As a result, water droplets attached to the surface of the lens 11 of the camera 10 can be removed by air pressure.

  At this time, as shown in FIG. 30 (b), the pipe 23 connected to the secondary tank 13 is oriented substantially vertically, and the bottom face 13d of the secondary tank 13 and the pipe for the cleaning liquid are directed downward. Since it is inclined to face, no cleaning liquid remains in the secondary tank 13 and its piping. For this reason, even when the compressed air is injected and the inside of the secondary tank 13 becomes a negative pressure, it is possible to prevent the cleaning liquid from being introduced into the combined flow paths 16a and 16b, and to prevent the cleaning liquid from being mixed into the compressed air. it can. For this reason, when the compressed air is ejected to remove water droplets attached to the lens 11, it is possible to avoid the problem that the cleaning liquid mixed in the compressed air adheres to the lens 11 again. In other words, in the dry mode, the surface of the lens 11 is cleaned by supplying compressed air from the air pump 5 to the air pipe 6 and injecting compressed air from the discharge ports 10a and 10b in a state where the supply of the cleaning liquid is interrupted. .

  Next, the lens wetting mode will be described. In the lens wetting mode, the cleaning liquid is supplied from the cleaning liquid pump 3 into the secondary tank 13 and the air pump 5 is intermittently driven to discharge the cleaning liquid onto the surface of the lens 11. Specifically, the cleaning liquid pump 3 is driven at time t20 to t21 to accumulate the cleaning liquid in the secondary tank 13, and then the air pump 5 is intermittently driven a plurality of times during time T1 at time t22. The cleaning solution is dropped on the surface of the lens 11 little by little. For example, the cleaning liquid is dropped in small amounts (for example, 0.25 ml) on the surface of the lens 11 at a time t22 to t23 of 30 msec.

Although the content of the lens cleaning process in the present embodiment is not particularly limited, the lens cleaning process of the present embodiment includes a cleaning liquid replenishing process, a lens wetting process, a cleaning process, and a drying process, which are preparation processes.

  FIG. 32 is a time chart showing the lens cleaning process of the present embodiment. In the lens cleaning process of the present embodiment, a “cleaning liquid replenishment process A” for replenishing the cleaning liquid tank 2 with a cleaning liquid necessary for performing the cleaning process in advance, and a cleaning liquid W is discharged to the lens 11 in order to wet the surface of the lens 11. A “lens wetting step B”, a “cleaning step C” that discharges the cleaning liquid W onto the lens 11 to wash away dirt on the surface of the lens 11, and a “drying step D” that evaporates the cleaning liquid W and dries the surface of the lens 11 It is repeatedly executed in order of → B → C → D. In the “lens wetting step B” of the present embodiment, in order to spread the cleaning liquid over the entire surface of the lens 11, the cleaning liquid is discharged and air is sprayed a plurality of times at predetermined intervals. Accordingly, the cleaning liquid is intermittently sprayed on the surface of the lens 11. The specific operation of each process is in accordance with the operation of each mode described above.

  As shown in FIG. 32, the control device 110 sends the cleaning liquid necessary for cleaning to the cleaning liquid tank 2 at the timing TG0. The cleaning liquid tank 2 of the present embodiment temporarily stores the cleaning liquid used for the lens cleaning process. In the present embodiment, 1.0 ml of the cleaning liquid is stored in the cleaning liquid tank 2. When the cleaning process is started, “lens wetting step B” is first executed. In the “lens wetting step A”, the cleaning liquid is intermittently discharged onto the surface of the lens 11 at intervals of 20 s. In this embodiment, 0.25 ml of the cleaning liquid is discharged three times at intervals of 20 s. In the present embodiment, air is discharged in synchronization with the discharge of the cleaning liquid. The timing of blowing air may be the same as the timing of discharging the cleaning liquid, or may be slightly delayed.

  The amount of the cleaning liquid stored in the cleaning liquid tank 2 is appropriately determined according to the cleaning process. The control device 110 according to the present embodiment causes the cleaning liquid tank 101 to have an amount larger than the total discharge amount obtained by multiplying the number of times the cleaning liquid is discharged onto the lens during the lens cleaning process by the amount of the cleaning liquid discharged at one time. Determine the amount of cleaning liquid to be stored. In the example of the cleaning process shown in FIG. 23, the controller 110 multiplies the total number of discharges (0) by multiplying the number of times the cleaning liquid is discharged onto the lens (three times) by the amount of cleaning liquid discharged at one time (0.25 ml). 1.0 ml of cleaning liquid, which is larger than .75 ml), is stored in the cleaning liquid tank 2. At the timing when the discharge of the cleaning liquid three times is completed, 0.25 ml of the cleaning liquid remains in the cleaning tank 101. The remaining cleaning liquid leaks to the surface of the lens 11 without air blowing. Without air blowing, the amount of foam generated when the cleaning liquid is discharged is small. In addition, the cleaning liquid leaking onto the lens 11 at the end causes the bubbles formed on the surface of the lens 11 to be washed away by the cleaning liquid discharged with the previous air blowing.

  In the present embodiment, since the cleaning liquid tank 2 stores an amount larger than the total discharge amount, which is obtained by multiplying the number of times the cleaning liquid is discharged onto the lens by the amount of the cleaning liquid discharged at one time, the last of the lens wetting step B In addition, the cleaning liquid can be leaked from the cleaning liquid tank 2 to the surface of the lens 11. Then, bubbles remaining on the surface of the lens 11 can be washed away by the cleaning liquid leaking from the cleaning liquid tank 2.

  The control device 110 ends the “lens wetting step B” at the timing TG2, and then starts the “cleaning step C”, and discharges the cleaning liquid W onto the surface of the lens 11 for about 2 seconds to 10 seconds. In the present embodiment, the cleaning process P10 for 3 seconds is performed. After the completion timing TG3, the “drying step D” is started, and a drying air blowing process P20 for blowing gas onto the surface of the lens 11 is performed for about 30 seconds.

  In the lens cleaning device 100 according to the present embodiment, when the lens state determination unit 38 determines that the lens 11 is in the predetermined bubble adhesion state, the interval of the ejection timing in the lens cleaning process is set to the predetermined bubble adhesion state. Change it longer than if it is determined not.

  Since the operation of the lens state determination unit 38 of this embodiment is the same as that of the first embodiment, the description in the first embodiment is cited. Moreover, since the determination method of whether the lens 11 of the lens state determination part 38 is a predetermined | prescribed bubble adhesion state is common to 1st Embodiment, the description in 1st Embodiment is used. In the present embodiment, as shown in FIG. 3, the control device 110 of the lens cleaning device 100 includes a lens state determination unit 38.

  When it is determined that the lens 11 is in a predetermined bubble adhering state, the lens cleaning device 100 according to the present embodiment discharges the cleaning liquid at the discharge timing P1 and the discharge timing at the lens wetting step B in the lens cleaning step shown in FIG. The interval between P2 and / or the interval between the discharge timing P2 and the discharge timing P3 is changed longer than when it is determined that the predetermined bubble adhesion state is not established. In the example shown in FIG. 32, an example in which ejection is performed three times is shown. The discharge timing to be extended may be a pair of discharge timing intervals, or may be two or more pairs of intervals. In addition, when there are a plurality of intervals between a pair of ejection timings, an extension process may be performed for some of the intervals, or an extension process may be performed for all the intervals. When the extension process is performed for a plurality of intervals, the extents of the intervals may be the same or different. The interval (time) after the extension may be determined by adding a predetermined additional time to the interval before the extension (the interval when it is determined that the predetermined bubble is not attached), or the interval before the extension (the predetermined interval). You may determine by multiplying a predetermined coefficient (> 1.0) to the space | interval when it is judged that it is not a bubble adhesion state.

  The length of time for extending the discharge timing interval when it is determined that the predetermined bubble adhesion state is not present (the length of the additional time) is the size of the lens 11, the curvature, and the lens cleaning device. It can be determined appropriately according to the cleaning performance of 100 or the like. In the present embodiment, the length of the extension time (the length of the additional time, the magnitude of the coefficient to be multiplied) is set according to the state change of the bubble adhesion state of the lens 11. As a first method, the length of the extension time can be determined according to a change in the image corresponding to the bubble BU. For example, the extension time can be shortened as the reduction rate of the number of edges due to the image of the bubble BU is high, and the extension time can be lengthened as the reduction rate of the number of edges due to the image of the bubble BU is low. This is because if the number of edges due to the bubble BU is high, the time until the bubble disappears can be estimated to be short. As a second method, the length of the extension time can be determined according to a change in the edge of a fixed object such as a bumper. For example, the extension time is shortened as the increase rate of the edge length corresponding to the fixed object is high, and the extension time is lengthened as the increase rate of the edge length corresponding to the fixed object is low. This is because if the increasing rate of the edge length corresponding to the fixed object is high, it can be estimated that the time until the fixed object that is blurred due to the influence of the bubble BU becomes clearly visible (the bubble disappears) is short. As a third method, the length of the extension time can be determined according to the change in brightness of the captured image due to the presence of the bubble BU. For example, the extension time is shortened as the brightness decrease rate of the captured image is large, and the extension time is lengthened as the brightness increase rate of the captured image is large. This is because it can be estimated that the time until the bubble disappears is short if the reduction rate of the brightness of the captured image due to the bubble BU is high.

  The interval before the extension process is an interval of the discharge timing of the cleaning liquid that is executed when the lens 11 is not determined to be in the predetermined bubble adhering state. The interval of the discharge timing when it is not determined that the predetermined bubble adhering state may be a default time (interval) defined in advance in the lens cleaning step, or is applied according to the lens cleaning mode. It may be a time (interval).

  As described with reference to FIGS. 20A to 21B in the first embodiment, when the lens 11 is washed, bubbles BU adhere to the surface thereof. In some cases, the bubble BU adheres to the lens 11 and a predetermined bubble adhesion state occurs. When the cleaning liquid is further discharged to the lens 11 in a predetermined bubble adhesion state, bubbles are formed on the bubbles, and the time until the bubbles disappear from the lenses 11 becomes longer. In this embodiment, the interval of the discharge timing of the cleaning liquid is changed longer than the discharge timing when it is determined that the lens 11 is not in the predetermined bubble adhesion state so that the cleaning liquid is not further discharged to the lens 11 in the predetermined bubble adhesion state. Thereby, it can prevent that a bubble is formed on a bubble. As a result, the bubbles adhering to the lens 11 can be quickly disappeared while cleaning the lens 11 using the cleaning liquid.

  The inventors have specified, through experiments, cleaning conditions in which the bubble BU tends to remain on the lens 11 in the lens 11 cleaning step. In the cleaning process, when the cleaning liquid for the next cleaning is discharged to the lens 11 before the bubbles generated by the previous cleaning disappear, new bubbles are formed on the bubbles until the bubbles disappear. The tendency which time became long was confirmed. When bubbles are formed on the bubbles, the bubbles do not disappear from the lens 11 over a relatively long time, and the amount of bubbles remaining on the lens 11 tends to increase. When the bubbles are formed on the lens 11 by discharging the cleaning liquid once and the bubbles are formed on the lens 11 by discharging the cleaning liquid twice, the volume of the bubbles on the lens 11 is substantially the same. Even when the bubbles are formed, the time from when the bubbles are formed until the bubbles disappear is when the cleaning liquid is discharged twice to form bubbles on the lens 11 and the cleaning liquid is discharged once. It was longer than when foam was formed on the top. The clear reason is unknown, but when bubbles are formed by discharging the cleaning liquid multiple times, the previously formed bubbles are covered with new bubbles, and the bubbles may not be easily destroyed. is there.

  In the first embodiment described above, the method of reducing the influence of the bubbles on the detection of the three-dimensional object when the bubbles adhere to the lens 11 by performing the process of suppressing the detection of the three-dimensional object has been described. In the present embodiment, the foam remains on the lens 11 by proposing a cleaning method that suppresses the formation of the foam on the foam, which is the previous stage of the state in which the foam is difficult to disappear. You can avoid it. If bubbles remain on the lens 11, the bubble image affects the captured image, which may reduce the accuracy of detection of the three-dimensional object described in the first embodiment. In the present embodiment, the lens 11 is cleaned so that bubbles of the cleaning liquid do not remain on the lens 11, so that image noise caused by the bubbles can be prevented from being included in the captured image. As a result, a three-dimensional object can be detected with high accuracy based on the obtained captured image.

  In addition, when it is determined that the lens 11 is in a predetermined bubble adhering state, the lens cleaning device 100 of the present embodiment increases the discharge amount of the cleaning liquid in the lens cleaning process. The increased discharge amount is a discharge amount applied when the lens 11 is not in a predetermined bubble adhesion state. By extending the discharge timing interval, the bubble BU on the lens 11 decreases or disappears at the next extension timing after the extension. Here, the remaining bubble BU can be eliminated from the lens 11 by discharging a relatively large amount of cleaning liquid. Further, when the discharge amount per time is increased, since the cleaning liquid stored in the cleaning liquid tank 2 is a fixed amount, the number of dischargeable times in one cleaning process is reduced. When the number of ejections decreases, the interval of ejection timing in one cleaning process becomes longer. That is, by increasing the discharge amount, the same effect as extending the discharge timing interval is obtained.

  The lens cleaning device 100 according to the present embodiment includes a temperature acquisition unit 111. The temperature acquisition unit 111 acquires the temperature of the lens 11 in the cleaning environment. The temperature acquisition unit 111 acquires the outside air temperature, the cleaning liquid temperature, and the temperature of the lens 11 as the temperature of the cleaning environment of the lens 11. A thermometer for measuring each temperature may be provided. The temperature acquisition unit 111 of this embodiment acquires temperature information from a thermometer provided in the host vehicle V.

  The lens cleaning device 100 according to the present embodiment determines the discharge timing interval according to the detected temperature. In determining the discharge timing, the lens cleaning device 100 makes the interval of the discharge timing at the first temperature detected by the temperature acquisition unit 111 longer than the interval of the discharge timing at the second temperature lower than the first temperature. The process of extending the discharge timing interval based on this temperature may be performed for the discharge timing interval before the extension or for the interval after the extension. When extending the interval of the discharge timing after the extension, the time added to the interval of the discharge timing when it is determined that it is not in the predetermined bubble adhering state during the extension process may be lengthened. A coefficient (> 1.0) for multiplying the interval of the ejection timing when it is determined that the state is not the predetermined bubble adhesion state may be increased.

  The lens cleaning device 100 according to the present embodiment stores in advance a correspondence relationship between the temperature and the interval (time) of the discharge timing. The correspondence temperature between the temperature and the interval (time) of the discharge timing is not particularly limited, and may be a linear relationship as shown in pattern 1 shown in FIG. 33A or as shown in pattern 2 in FIG. In addition, a relationship indicating a multi-stage change may be used, or a relationship indicating a curved change may be used as shown in a pattern 3 in FIG.

  In the lens cleaning device 100 of the present embodiment, when the temperature in the cleaning environment is high, the interval of the ejection timing is made longer than when the temperature in the cleaning environment is low. When the temperature in the cleaning environment is high, bubbles are likely to be generated in the cleaning liquid, and the generated bubbles are difficult to disappear. In the present embodiment, in the high temperature state, since the interval of the discharge timing is relatively long, the next cleaning liquid can be discharged after the bubbles are reduced or eliminated. As a result, the lens 11 can be washed so that bubbles are not formed on the bubbles.

  The lens cleaning device 100 according to the present embodiment includes a vehicle speed acquisition unit 112. The vehicle speed acquisition unit 112 acquires the speed of the host vehicle V. The vehicle speed acquisition unit 112 of this embodiment acquires temperature information from the vehicle speed sensor 20 provided in the host vehicle V.

  The lens cleaning device 100 according to the present embodiment determines the interval of the discharge timing according to the detected vehicle speed. In determining the discharge timing, the lens cleaning device 100 makes the interval of the discharge timing at the first vehicle speed detected by the vehicle speed acquisition unit 112 longer than the interval of the discharge timing at the second vehicle speed higher than the first vehicle speed. The process of extending the interval of the discharge timing based on the vehicle speed may be performed for the interval of the discharge timing when it is determined that the predetermined bubble adhering state is not established, or may be performed for the interval after the extension. When extending the interval of the discharge timing after the extension, the time added to the quasi-interval when it is determined that it is not in the predetermined bubble adhering state at the time of the extension process may be lengthened. The coefficient (> 1.0) for multiplying the interval when it is determined that it is not in the state of bubble adhesion may be increased.

  The lens cleaning device 100 according to the present embodiment stores in advance a correspondence relationship between the vehicle speed and the discharge timing interval (time). The correspondence temperature between the vehicle speed and the discharge timing interval (time) is not particularly limited, and may be a linear relationship as shown in pattern 1 shown in FIG. 33B, or as shown in pattern 2 in FIG. In addition, a relationship indicating a multi-stage change may be used, or a relationship indicating a curved change may be used as shown in a pattern 3 in FIG.

  In the lens cleaning device 100 of the present embodiment, when the vehicle speed is low, the interval of the discharge timing is made longer than when the vehicle speed is high. When the vehicle speed is high, the bubbles are easily blown off, and the bubbles easily disappear from the surface of the lens 11. On the other hand, when the vehicle speed is low, the bubbles tend to stay on the lens 11 without being blown away. In the present embodiment, when the vehicle speed is low, the discharge timing interval is relatively long, so that the next cleaning liquid can be discharged after the bubbles are reduced or eliminated. As a result, the lens 11 can be washed so that bubbles are not formed on the bubbles. Further, when the vehicle speed is high, the road surface sand and the like are wound up violently, so that the lens 11 is easily soiled. In the present embodiment, when the vehicle speed is high, the supply timing of the cleaning liquid is relatively shorter than when the vehicle speed is low. Therefore, the cleaning liquid can be discharged to the lens 11 to frequently wash away sand and the like.

  Hereinafter, based on the flowchart of FIG. 34, the control procedure of the control apparatus 110 of the washing | cleaning apparatus 100 of this embodiment is demonstrated.

  First, in step S91, the lens state determination unit 38 of the present embodiment determines the state of bubbles adhering to the lens 11. Since the determination method of the state of the lens 11 is common to the determination method in the first embodiment, the description thereof is used. In step S92, when the lens state determination unit 38 determines that the lens 11 is in the predetermined bubble adhesion state, the process proceeds to step S93.

  In step S <b> 93, the control device 110 of the present embodiment extends the discharge timing interval when it is determined that the predetermined bubble adhesion state is not established. The amount of extension of the discharge timing interval can be determined according to the change in the state of bubble adhesion of the lens. In step S94, the control device 110 increases the discharge amount of the cleaning liquid applied when it is determined that the predetermined bubble adhering state is not achieved. After step S93, step S94 may be skipped and the process may proceed to step S95.

  Returning to step S92, if the lens state determination unit 38 of the present embodiment determines that the lens 11 is not in the predetermined bubble adhesion state, the process proceeds to step S99. In step S99, the control device 110 maintains the interval of the discharge timing applied when it is determined that the predetermined bubble adhering state is not established. In step S100, control device 110 maintains the discharge amount of the cleaning liquid applied when it is determined that the predetermined bubble adhering state is not achieved. After step S99, step S100 may be skipped and the process may proceed to step S95.

  In step S95, the control device 110 according to the present embodiment corrects the discharge timing interval and / or the discharge amount applied when it is determined that the predetermined bubble adhering state is not detected, according to the temperature in the cleaning environment.

  In step S95, the control device 110 of the present embodiment corrects the discharge timing interval and / or the discharge amount applied when it is determined that the predetermined bubble adhering state is not established, according to the vehicle speed. Both the process of step S94 and the process of step S95 may be executed, or only one of them may be executed.

  In step S97, the control device 110 according to the present embodiment determines the cleaning start timing, and when the cleaning start timing comes, the process proceeds to step S98 to execute the cleaning process.

  According to the camera device 1000, the lens cleaning device 100, and the lens cleaning method according to the embodiment of the present invention configured and operated as described above, the following effects can be obtained.

  [1] According to the camera apparatus 1000 of the present embodiment, when the lens is in a predetermined bubble adhesion state, the cleaning liquid discharge timing interval is not in the predetermined bubble adhesion state so that the cleaning liquid is not further discharged. The discharge timing is changed to be longer than the discharge timing interval when it is determined. Thereby, it can prevent that a bubble is formed on a bubble. As a result, the bubbles adhering to the lens 11 can be quickly disappeared while cleaning the lens 11 using the cleaning liquid.

  [2] The camera device 1000 of the present embodiment increases the discharge amount of the cleaning liquid in the lens cleaning process when it is determined that the lens 11 is in a predetermined bubble adhesion state. By extending the discharge timing interval, the bubble BU on the lens 11 decreases or disappears at the next extension timing after the extension. Here, the remaining bubble BU can be eliminated from the lens 11 by discharging a relatively large amount of cleaning liquid.

  [3] In the camera device 1000 of the present embodiment, when the temperature in the cleaning environment is high, the interval between the ejection timings is made longer than when the temperature in the cleaning environment is low. When the temperature in the cleaning environment is high, bubbles are likely to be generated in the cleaning liquid, and the generated bubbles are difficult to disappear. In the present embodiment, in the high temperature state, since the interval of the discharge timing is relatively long, the next cleaning liquid can be discharged after the bubbles are reduced or eliminated. As a result, the lens 11 can be washed so that bubbles are not formed on the bubbles.

  [4] When the vehicle speed is low, the camera apparatus 1000 of the present embodiment makes the discharge timing interval longer than when the vehicle speed is high. When the vehicle speed is high, the bubbles are easily blown off, and the bubbles easily disappear from the surface of the lens 11. On the other hand, when the vehicle speed is low, the bubbles tend to stay on the lens 11 without being blown away. In the present embodiment, when the vehicle speed is low, the discharge timing interval is relatively long, so that the next cleaning liquid can be discharged after the bubbles are reduced or eliminated. As a result, the lens 11 can be washed so that bubbles are not formed on the bubbles.

  [5] Since the camera apparatus 1000 of the present embodiment stores a larger amount of cleaning liquid in the cleaning liquid tank 2 than the total discharge amount obtained by multiplying the number of times the cleaning liquid is discharged onto the lens by the amount of cleaning liquid discharged at one time. At the end of the lens wetting step B, the cleaning liquid can be leaked from the cleaning liquid tank 2 to the surface of the lens 11. Then, bubbles remaining on the surface of the lens 11 can be washed away by the cleaning liquid leaking from the cleaning liquid tank 2. Thereby, it is possible to prevent bubbles from remaining on the surface of the lens 11.

  [6] When the lens cleaning method of the present embodiment is used, the same operational effects as the camera device 1000 including the lens cleaning device 100 described above can be obtained.

  The camera 10 corresponds to an imaging unit according to the present invention, the lens state determination unit 38 corresponds to a lens state determination unit, the vehicle speed sensor 20 corresponds to a vehicle speed sensor, and the illuminance sensor 21 corresponds to a brightness detection unit. The lens cleaning device 100 corresponds to a lens cleaning unit, the cleaning control device 110 corresponds to a cleaning control unit, and the lens state determination unit 38 of the control device 110 corresponds to a lens state determination unit. The temperature acquisition unit 111 corresponds to a temperature acquisition unit, and the vehicle speed acquisition unit 112 corresponds to a vehicle speed acquisition unit.

1000 ... Camera device 1 ... Solid object detection device 10 ... Camera 11 ... Lens 20 ... Vehicle speed sensor 30 ... Computer 31 ... Viewpoint conversion unit 32 ... Positioning unit 33, 37 ... Solid object detection unit 34 ... Solid object judgment unit 35 ... Luminance Difference calculation unit 36 ... edge detection unit 38 ... lens state determination unit 39 ... control unit 40 ... smear detection unit 100 ... lens cleaning device 110 ... control device 101 ... cleaning water tank 102 ... cleaning water flow path 103a, 103b ... dropping port 104 ... air compressor 105 ... air channel 106a, 106b ... spout a ... angle A1, A2 ... detection area CP ... intersection DP ... differential pixel _{DW t, DW} t _'... differential waveform _{DW t1 ~DW m, DW m +} k ~DW tn ... small regions L1, L2 ... ground line La, the line P ... captured image on the direction Lb ... three-dimensional object collapses PB t _... bird's-eye view image PD t _... difference image MP Mask image S ... smear SP ... smear image SB t _... smear bird's-eye view image V ... vehicle VX ... other vehicle 2 cleaning liquid tank 3 cleaning liquid pump 4 washing liquid pipe 5 the air pump 6 air pipe 7 nozzle 7a jetting surface 7b side 7c bottom 7d cap 8 Control part 10a, 10b Discharge port 11a, 11b Cleaning liquid passage 12 Air passage 13 Secondary tank 13a, 13b Plug 13c Supply port 13d Bottom surface 14a, 14b Tip part 15a, 15b Tip part 16a, 16b Joint channel 22 Nozzle unit 23 Piping 24 Check valve 25 Vent hole 30 Vehicle information

Claims (6)

Imaging means mounted on the vehicle;
A lens cleaning means for cleaning the lens according to a predetermined lens cleaning process in which a discharge timing for discharging the cleaning liquid onto the lens included in the imaging means is defined;
Based on a captured image captured by the imaging unit, a lens state determination unit that determines whether or not a predetermined bubble adhesion state in which bubbles have adhered to the lens;
When it is determined that the lens is in the predetermined bubble adhering state, the lens cleaning unit performs the lens cleaning more than the discharge timing interval applied when it is determined that the lens is not in the predetermined bubble adhering state. A camera apparatus characterized in that an interval of the ejection timing in the process is changed long.   2. The camera according to claim 1, wherein the lens cleaning unit increases a discharge amount of the cleaning liquid in the lens cleaning step when it is determined that the lens is in the predetermined bubble adhering state. apparatus. A temperature acquisition means for acquiring a temperature of a cleaning environment when the lens cleaning step is performed;
The lens cleaning means determines an interval of the ejection timing according to the acquired temperature,
3. The camera device according to claim 1, wherein an interval of the ejection timing at the acquired first temperature is longer than an interval of the ejection timing at a second temperature lower than the first temperature. Vehicle speed acquisition means for acquiring the speed of the vehicle,
The lens cleaning means determines an interval of the discharge timing according to the acquired vehicle speed,
The interval of the discharge timing at the acquired first vehicle speed is longer than the interval of the discharge timing at a second vehicle speed higher than the first vehicle speed. The camera device described. The lens cleaning means includes a cleaning liquid tank that temporarily stores the cleaning liquid used in the lens cleaning step.
The lens cleaning means cleans the lens using a cleaning liquid stored in the cleaning liquid tank,
The lens cleaning means determines the amount of the cleaning liquid stored in the cleaning liquid tank,
The amount of the cleaning liquid stored in the determined cleaning liquid tank is calculated by multiplying the number of times the cleaning liquid is discharged onto the lens during the lens cleaning step by the total amount of the cleaning liquid discharged at one time. The camera device according to claim 1, wherein the camera device is large. A lens cleaning method executed by a camera device, comprising: a camera including a lens; and a lens cleaning device that cleans the lens according to a predetermined lens cleaning process in which a discharge timing for discharging a cleaning liquid onto the lens is defined at least. ,
Determining whether the lens is in a predetermined bubble adhesion state based on a captured image of the camera;
And a step of extending an interval of the ejection timing in the lens cleaning step when it is determined that the lens is in the predetermined bubble adhering state.