Patent Publication Number: US-11391845-B2

Title: Fog determination apparatus, fog determination method, and computer readable medium

Description:
TECHNICAL FIELD 
     The present invention relates to a technology to determine the density of fog. 
     BACKGROUND ART 
     Patent Literature 1 describes a technology to decide whether fog is present around a vehicle. 
     In Patent Literature 1, electromagnetic waves are transmitted to an area around the vehicle and reflection points are determined based on reflected waves of the electromagnetic waves. A plurality of determined reflection points with which the distance between the reflection points is within a certain range are classified as one segment. When the rate of second reflection points existing on scanning lines of electromagnetic waves passing through a first segment, which is a segment of first reflection points, is high, it is decided that the first segment is fog. 
     CITATION LIST 
     Patent Literature 
     Patent Literature 1: JP 2009-42177 A 
     SUMMARY OF INVENTION 
     Technical Problem 
     In the technology described in Patent Literature 1, when the density of fog is high, the number of electromagnetic waves that pass through the fog is small, resulting in a low rate of second reflection points existing on scanning lines of electromagnetic waves passing through the first segment. Therefore, it is difficult to determine that fog is present. 
     It is an object of the present invention to appropriately determine the density of fog. 
     Solution to Problem 
     A fog determination apparatus according to the present invention includes 
     a point data acquisition unit to acquire a set of point data, each piece of the point data indicating reflection points obtained by an optical sensor that receives reflected light of an emitted light beam reflected at the reflection points, and being a pair of first point data indicating a first reflection point, which is a reflection point of a given light beam, and second point data indicating a second reflection point, which is a reflection point at which an intensity of reflected light of the given light beam is lower when compared with the first reflection point; and 
     a fog determination unit to determine a density of fog based on a distribution of a distance between the first reflection point and the second reflection point concerning the point data included in the set acquired by the point data acquisition unit. 
     Advantageous Effects of Invention 
     In the present invention, the density of fog is determined based on a distribution of a distance between a first reflection point and a second reflection point. The distribution of the distance between the first reflection point and the second reflection point varies with the density of fog, so that the density of fog can be appropriately determined. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a configuration diagram of a fog determination apparatus  10  according to a first embodiment; 
         FIG. 2  is a flowchart illustrating overall operation of the fog determination apparatus  10  according to the first embodiment; 
         FIG. 3  is a diagram describing point data according to the first embodiment; 
         FIG. 4  is a flowchart of a fog determination process according to the first embodiment; 
         FIG. 5  is a diagram describing the fog determination process according to the first embodiment; 
         FIG. 6  is a configuration diagram of the fog determination apparatus  10  according to a first variation; 
         FIG. 7  is a flowchart illustrating overall operation of the fog determination apparatus  10  according to a second embodiment; 
         FIG. 8  is a diagram describing point data when fog is present according to the second embodiment; 
         FIG. 9  is a flowchart of a fog determination process according to the second embodiment; 
         FIG. 10  is a diagram describing a variance calculation process according to the second embodiment; 
         FIG. 11  is a configuration diagram of the fog determination apparatus  10  according to a third embodiment; 
         FIG. 12  is a flowchart illustrating overall operation of the fog determination apparatus  10  according to the third embodiment; 
         FIG. 13  is a configuration diagram of the fog determination apparatus  10  according to a fourth embodiment; 
         FIG. 14  is a flowchart illustrating overall operation of the fog determination apparatus  10  according to the fourth embodiment; 
         FIG. 15  is a diagram describing a threshold value setting process according to the fourth embodiment; 
         FIG. 16  is a configuration diagram of the fog determination apparatus  10  according to a fifth embodiment; 
         FIG. 17  is a flowchart illustrating overall operation of the fog determination apparatus  10  according to the fifth embodiment; 
         FIG. 18  is a diagram describing information to be stored in a reliability storage unit  32  according to the fifth embodiment; 
         FIG. 19  is a configuration diagram of the fog determination apparatus  10  according to a fourth variation; and 
         FIG. 20  is a flowchart illustrating overall operation of the fog determination apparatus  10  according to the fourth variation. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     First Embodiment 
     ***Description of Configuration*** 
     Referring to  FIG. 1 , a configuration of a fog determination apparatus  10  according to a first embodiment will be described. 
     The fog determination apparatus  10  is a computer, such as an electronic control unit (ECU), to be mounted on a mobile object  100 . 
     In the first embodiment, the mobile object  100  is a vehicle. However, the mobile object  100  is not limited to the vehicle, and may be other types such as a ship or an airplane. The fog determination apparatus  10  may be implemented in a form integrated with or a form inseparable from the mobile object  100  or another component illustrated in the drawing, or may be implemented in a form detachable from or a form separable from the mobile object  100  or another component illustrated in the drawing. 
     The fog determination apparatus  10  includes hardware of a processor  11 , a memory  12 , a storage  13 , and a communication interface  14 . The processor  11  is connected with other hardware components via signal lines and controls the other hardware components. 
     The processor  11  is an integrated circuit (IC) that performs processing. 
     Specific examples of the processor  11  are a central processing unit (CPU), a digital signal processor (DSP), and a graphics processing unit (GPU). 
     The memory  12  is a storage device to temporarily store data. Specific examples of the memory  12  are a static random access memory (SRAM) and a dynamic random access memory (DRAM). 
     The storage  13  is a storage device to store data. A specific example of the storage  13  is a hard disk drive (HDD). Alternatively, the storage  13  may be a portable recording medium, such as a Secure Digital (SD, registered trademark) memory card, CompactFlash (CF, registered trademark), a NAND flash, a flexible disk, an optical disc, a compact disc, a Blu-ray (registered trademark) disc, or a digital versatile disc (DVD). 
     The communication interface  14  is an interface for communication with external devices. Specific examples of the communication interface  14  are an Ethernet (registered trademark) port, a Universal Serial Bus (USB) port, and a High-Definition Multimedia Interface (HDMI, registered trademark) port. 
     The communication interface  14  is connected with an optical sensor  41  mounted on the mobile object  100 . The optical sensor  41  is a device that emits a light beam, which is a beam of light, and receives reflected light of the emitted light beam reflected at a reflection point. A specific example of the optical sensor  41  is a LiDAR (Light Detection and Ranging). 
     The fog determination apparatus  10  includes, as functional components, a point data acquisition unit  21  and a fog determination unit  22 . The functions of the functional components of the fog determination apparatus  10  are realized by software. 
     The storage  13  stores programs for realizing the functions of the functional components of the fog determination apparatus  10 . These programs are loaded into the memory  12  by the processor  11  and executed by the processor  11 . This realizes the functions of the functional components of the fog determination apparatus  10 . 
     The storage  13  realizes the function of a decision information storage unit  31 . 
       FIG. 1  illustrates only one processor  11 . However, a plurality of processors  11  may be included, and the plurality of processors  11  may cooperate to execute the programs for realizing the functions. 
     ***Description of Operation*** 
     Referring to  FIGS. 2 to 5 , operation of the fog determination apparatus  10  according to the first embodiment will be described. 
     The operation of the fog determination apparatus  10  according to the first embodiment corresponds to a fog determination method according to the first embodiment. The operation of the fog determination apparatus  10  according to the first embodiment also corresponds to processes of a fog determination program according to the first embodiment. 
     Referring to  FIG. 2 , the overall operation of the fog determination apparatus  10  according to the first embodiment will be described. 
     (Step S 11 : Point Data Acquisition Process) 
     The point data acquisition unit  21  acquires, via the communication interface  14 , a set of point data indicating reflection points obtained by the optical sensor  41  that receives reflected light of an emitted light beam reflected at the reflection points. 
     Point data is a pair of first point data indicating a first reflection point, which is a reflection point of a given light beam emitted by the optical sensor  41 , and second point data indicating a second reflection point, which is a reflection point at which the intensity of reflected light of the given light beam is lower than that at the first reflection point. In the first embodiment, the first reflection point is a reflection point with the highest intensity of reflected light, and the second reflection point is a reflection point with the second highest intensity of reflected light after the first reflection point. 
     As illustrated in  FIG. 3 , the optical sensor  41  emits a light beam, which is a beam of light. When fog is present, the light forming the light beam is first reflected by some fog particles that are scattered sparsely in vertical and depth directions. In most cases, the reflected light of reflection at a position near the optical sensor  41  has the highest intensity. Therefore, a reflection point at which reflection has occurred at a position near the optical sensor  41  becomes the first reflection point. The light that has passed through the fog particles and the light reflected by the fog particles are reflected by other fog particles or an obstacle such as a vehicle around the mobile object  100 . In most cases, the reflected light of this reflection has the second highest intensity, so that a reflection point at which this reflection has occurred becomes the second reflection point. 
     (Step S 12 : Clustering Process) 
     The point data acquisition unit  21  performs clustering on the point data included in the set acquired in step S 11 . 
     Specifically, the point data acquisition unit  21  performs clustering on the point data included in the set based on the position of at least one of the first reflection point and the second reflection point so as to generate one or more clusters. As a method for clustering the point data, an existing clustering technique may be used. For example, the point data acquisition unit  21  groups pieces of point data with which the distance between the positions of the respective first reflection points is within a certain distance into one cluster. 
     In this description, the point data acquisition unit  21  performs clustering. However, the point data acquisition unit  21  may acquire a set of point data on which clustering has been performed. That is, clustering of point data may be performed in an ECU for clustering that is separate from the fog determination apparatus  10 , and the point data acquisition unit  21  may acquire a set of point data on which clustering has been performed in the ECU for clustering. 
     (Step S 13 : Fog Determination Process) 
     The fog determination unit  22  determines the density of fog based on a distribution of the distance between the first reflection point and the second reflection point concerning the point data included in the set acquired in step S 11 . The fog determination unit  22  here determines the density of fog based on a distribution of the distance between the first reflection point and the second reflection point concerning the point data clustered into one cluster in step S 12 . 
     Specifically, the fog determination unit  22  determines the density of fog by comparing a distribution pattern of the distance corresponding to each density of fog with the distribution of the distance concerning the point data included in the set. In the first embodiment, the fog determination unit  22  determines the density of fog by comparing a histogram pattern of frequencies of the distance corresponding to each density of fog with a histogram of frequencies of the distance concerning the point data included in the set. 
     Referring to  FIGS. 4 and 5 , a fog determination process according to the first embodiment (step S 13  in  FIG. 2 ) will be described. 
     (Step S 21 : Histogram Generation Process) 
     As illustrated in (A) of  FIG. 5 , the fog determination unit  22  generates a histogram representing a distribution of the distance between the first reflection point and the second reflection point concerning the point data clustered into one cluster in step S 12 . 
     Specifically, the fog determination unit  22  determines the number of pieces of point data for each length of the distance, and divides each determined number of pieces of point data by the number of pieces of point data included in the cluster so as to calculate a frequency for each length of the distance. The fog determination unit  22  generates a histogram indicating the calculated frequencies. 
     In the first embodiment, the decision information storage unit  31  stores distribution patterns of the distance between the first reflection point and the second reflection point for each density of fog. Specifically, the decision information storage unit  31  stores histograms of frequencies of the distance between the first reflection point and the second reflection point for each density of fog. 
     The process of step S 22  is performed using each of the histogram patterns stored in the decision information storage unit  31  as a target pattern. 
     (Step S 22 : Comparison Process) 
     As illustrated in (B) of  FIG. 5 , the fog determination unit  22  compares the target pattern with the histogram generated in step S 21  to determine the density of fog. 
     Specifically, the fog determination unit  22  retrieves the target pattern from the decision information storage unit  31 . The fog determination unit  22  compares the retrieved target pattern with the histogram generated in step S 21 . As a method for comparison, an existing similarity comparison technique may be used. In the first embodiment, the fog determination unit  22  treats bins of a histogram as vectors, and calculates a similarity between vectors of the retrieved pattern and vectors of the histogram generated in step S 21  based on the Euclidean distance or histogram intersection. This is not limiting, and the fog determination unit  22  may perform comparison using techniques such a support-vector machine (SVM), AdaBoost, and supervised learning of a multilayer perceptron. 
     (Step S 23 : Density Determination Process) 
     The fog determination unit  22  determines a pattern with which the highest similarity is calculated in step S 22 , out of the histogram patterns stored in the decision information storage unit  31 . The fog determination unit  22  determines that the density of fog corresponding to the determined pattern is the density of fog around the mobile object  100 . 
     In Example 1 of  FIG. 5 , the histogram generated in step S 21  is highly similar to a pattern of fog with a visibility of 15 m (denoted as fog  15  in  FIG. 5 ). Therefore, it is determined in Example 1 that fog with a visibility of 15 m is present. In Example 2 in  FIG. 5 , the histogram generated in step S 21  is highly similar to a pattern of no fog. Therefore, it is determined in Example 2 that no fog is present. 
     Note that determining the density of fog is not limited to determining a level of density out of a plurality of levels of density of fog, but also includes determining whether fog with a density greater than or equal to a certain level is present. That is, determining the density of fog includes deciding whether fog is present. 
     ***Effects of First Embodiment*** 
     As described above, the fog determination apparatus  10  according to the first embodiment determines the density of fog based on the distribution of the distance between the first reflection point and the second reflection point. The distribution of the distance between the first reflection point and the second reflection point varies with the density of fog, so that the density of fog can be appropriately determined. 
     &lt;First Variation&gt; 
     In the first embodiment, the functional components are realized by software. As a first variation, however, the functional components may be realized by hardware. With regard to this first variation, differences from the first embodiment will be described. 
     Referring to  FIG. 6 , a configuration of the fog determination apparatus  10  according to the first variation will be described. 
     When the functional components are realized by hardware, the fog determination apparatus  10  includes an electronic circuit  15 , in place of the processor  11 , the memory  12 , and the storage  13 . The electronic circuit  15  is a dedicated circuit that realizes the functions of the functional components, the memory  12 , and the storage  13 . 
     The electronic circuit  15  is assumed to be a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, a logic IC, a gate array (GA), an application specific integrated circuit (ASIC), or a field-programmable gate array (FPGA). 
     The functional components may be realized by one electronic circuit  15 , or the functional components may be distributed among and realized by a plurality of electronic circuits  15 . 
     &lt;Second Variation&gt; 
     As a second variation, some of the functional components may be realized by hardware, and the rest of the functional components may be realized by software. 
     Each of the processor  11 , the memory  12 , the storage  13 , and the electronic circuit  15  is referred to as processing circuitry. That is, the functions of the functional components are realized by the processing circuitry. 
     &lt;Third Variation&gt; 
     In the first embodiment, the fog determination apparatus  10  is realized by one computer such as an ECU. However, the fog determination apparatus  10  may be realized by a plurality of computers such as ECUs. 
     Second Embodiment 
     A second embodiment differs from the first embodiment in that the density of fog is determined based on whether reflection points are distributed in an arcuate shape around the optical sensor  41 . In the second embodiment, this difference will be described, and description of the same portions will be omitted. 
     ***Description of Operation*** 
     Referring to  FIGS. 7 to 10 , operation of the fog determination apparatus  10  according to the second embodiment will be described. 
     The operation of the fog determination apparatus  10  according to the second embodiment corresponds to a fog determination method according to the second embodiment. The operation of the fog determination apparatus  10  according to the second embodiment also corresponds to processes of a fog determination program according to the second embodiment. 
     Referring to  FIG. 7 , the overall operation of the fog determination apparatus  10  according to the second embodiment will be described. 
     (Step S 31 : Point Data Acquisition Process) 
     The point data acquisition unit  21  acquires a set of point data indicating reflection points obtained by the optical sensor  41  that receives reflected light of an emitted light beam reflected at the reflection points. 
     In the second embodiment, unlike in the first embodiment, point data need not be a pair of first point data and second point data. In the second embodiment, point data may indicate only one reflection point. 
     (Step S 32 : Fog Determination Process) 
     The fog determination unit  22  determines the density of fog based on whether the reflection points are distributed in an arcuate shape around the optical sensor  41  when the reflection points indicated by the point data included in the set acquired in step S 31  are seen in an overhead view. 
     That is, the fog determination unit  22  transforms the set of point data indicating the reflection points illustrated in (A) of  FIG. 8  into an overhead view as illustrated in (B) of  FIG. 8 . That is, the fog determination unit  22  projects the reflection points indicated by the set of point data onto a coordinate system in depth and horizontal directions. When fog is present, the light beam is reflected uniformly around the optical sensor  41 , so that the reflection points are distributed in an arcuate shape around the optical sensor  41 . Note that, in (B) of  FIG. 8 , the reflection points are distributed not in a circular shape but in an arcuate shape. This is because there are no reflection points at the position where the mobile object  100  is located. 
     Referring to  FIG. 9 , a fog determination process according to the second embodiment (step S 32  in  FIG. 7 ) will be described. 
     (Step S 41 : Circle Approximation Process) 
     The fog determination unit  22  calculates a circle approximated by the least-squares method of the circle, using as inputs depth and horizontal coordinates of the reflection points indicated by the point data included in the set acquired in step S 31 . 
     Specifically, the fog determination unit  22  inputs depth and horizontal coordinates (x i , y i ) of a reflection point indicated by point data i (i=1, . . . , n) included in the set into the least-squares equations of the circle indicated in Formula 1 to calculate center coordinates (A, B) and a radius C of the circle to be approximated. 
     
       
         
           
             
               
                 
                   
                     
                       
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     (Step S 42 : Variance Calculation Process) 
     The fog determination unit  22  treats each piece of point data included in the set acquired in step S 31  as target point data, and calculates a distance d from the reflection point indicated by the target point data to the circle calculated in step S 41 . That is, as illustrated in  FIG. 10 , the fog determination unit  22  calculates, as the distance d, the length from the reflection point to the circle on a straight line that is drawn from the reflection point indicated by the target point data and is perpendicular to the tangent of the circle. Then, the fog determination unit  22  calculates a variance value of the distance d. 
     (Step S 43 : Density Determination Process) 
     The fog determination unit  22  determines the density of fog based on the variance value calculated in step S 42 . The fog determination unit  22  determines a higher density of fog as the variance value is smaller. 
     In the second embodiment, the decision information storage unit  31  stores threshold values of the variance value for each density of fog. The fog determination unit  22  determines the density of fog by comparing the variance value calculated in step S 42  with the threshold values for each density of fog stored in the decision information storage unit  31 . 
     ***Effects of Second Embodiment*** 
     As described above, the fog determination apparatus  10  according to the second embodiment determines the density of fog based on whether reflection points are distributed in an arcuate shape around the optical sensor  41 . When fog is present, reflection points are distributed in an arcuate shape around the optical sensor  41 . Therefore, it is possible to appropriately determine whether fog is present. 
     The fog determination apparatus  10  according to the second embodiment determines the density of fog based on the variance value of the distance d from each of the reflection points to the circle. The variance value varies with the density of fog, so that the density of fog can be appropriately determined. 
     Third Embodiment 
     A third embodiment differs from the first and second embodiments in that the density of fog is determined by a combination of the method for determining the density of fog described in the first embodiment and the method for determining the density of fog described in the second embodiment. In the third embodiment, this difference will be described, and description of the same portions will be omitted. 
     ***Description of Configuration*** 
     Referring to  FIG. 11 , a configuration of the fog determination apparatus  10  according to the third embodiment will be described. 
     The fog determination apparatus  10  differs from those in the first and second embodiments in that the fog determination unit  22  includes a first determination unit  23 , a second determination unit  24 , and an overall determination unit  25 . 
     ***Description of Operation*** 
     Referring to  FIG. 12 , operation of the fog determination apparatus  10  according to the third embodiment will be described. 
     The operation of the fog determination apparatus  10  according to the third embodiment corresponds to a fog determination method according to the third embodiment. The operation of the fog determination apparatus  10  according to the third embodiment also corresponds to processes of a fog determination program according to the third embodiment. 
     (Step S 51 : Point Data Acquisition Process) 
     The point data acquisition unit  21  acquires a set of point data. 
     In the third embodiment, point data is a pair of first point data and second point data. 
     (Step S 52 : First Determination Process) 
     The first determination unit  23  determines the density of fog as a first density based on a distribution of the distance between the first reflection point and the second reflection point. That is, the first determination unit  23  determines the density of fog by the method described in the first embodiment. 
     (Step S 53 : Second Determination Process) 
     The second determination unit  24  calculates a circle approximated by the reflection points when the reflection points indicated by the point data included in the set are seen in an overhead view, and determines the density of fog as a second density based on a variance of the distance between the calculated circle and each of the reflection points. That is, the second determination unit  24  determines the density of fog by the method described in the second embodiment. 
     At this time, the second determination unit  24  may use only the first point data included in the point data, or may use both the first point data and the second point data. 
     (Step S 54 : Overall Determination Process) 
     The overall determination unit  25  determines the density of fog based on the first density determined in step S 52  and the second density determined in step S 53 . 
     For example, assume that each of the first density and the second density has determined that fog is present or no fog is present. In this case, the overall determination unit  25  determines that fog is present if both the first density and the second density indicate that fog is present, and determines that no fog is present in other cases. 
     For example, assume that each of the first density and the second density has determined a level of density of fog out of a plurality of levels. In this case, the overall determination unit  25  determines the density of fog by comparing the sum of a weighted value of the first density and a weighted value of the second density with a threshold value set for each level of density of fog. That is, the overall determination unit  25  determines the density of fog by comparing θ1X+θ2Y with a threshold value th set for each level of density, where the first density is X, the second density is Y, the weight of the first density is θ1, and the weight of the second density is θ2. 
     ***Effects of Third Embodiment*** 
     As described above, the fog determination apparatus  10  according to the third embodiment determines the density of fog by a combination of the methods described in the first and second embodiments. This allows the density of fog to be determined with high accuracy. 
     Fourth Embodiment 
     A fourth embodiment differs from the first to third embodiments in that a sensor threshold value of a sensor for identifying an obstacle is set depending on the density of fog that has been determined. In the fourth embodiment, this difference will be described, and description of the same portions will be omitted. 
     ***Description of Configuration*** 
     Referring to  FIG. 13 , a configuration of the fog determination apparatus  10  according to the fourth embodiment will be described. 
     The fog determination apparatus  10  differs from those in the first to third embodiments in that a recognition unit  26  and a threshold value setting unit  27  are included. 
     ***Description of Operation*** 
     Referring to  FIGS. 14 and 15 , operation of the fog determination apparatus  10  according to the fourth embodiment will be described. 
     The operation of the fog determination apparatus  10  according to the fourth embodiment corresponds to a fog determination method according to the fourth embodiment. The operation of the fog determination apparatus  10  according to the fourth embodiment also corresponds to processes of a fog determination program according to the fourth embodiment. 
     Referring to  FIG. 14 , the overall operation of the fog determination apparatus  10  according to the fourth embodiment will be described. 
     Step S 61  is the process to determine the density of fog described in the first to third embodiments. 
     (Step S 62 : Threshold Value Setting Process) 
     The threshold value setting unit  27  sets the sensor threshold value of the sensor for identifying an obstacle depending on the density of fog determined in step S 61 . 
     Referring to  FIG. 15 , a specific example will be described. 
       FIG. 15  illustrates a case in which a camera is used as the sensor and tail lamps of a vehicle are identified. 
     When tail lamps are identified using the camera, a boundary line that linearly distinguishes tail lamps and others is used as the sensor threshold value on a UV plane of YUV data. Thus, the threshold value setting unit  27  sets this boundary line depending on the density of fog. The boundary line can be expressed as V=a·U+b. Thus, the threshold value setting unit  27  sets the values of a and b depending on the density of fog. 
     As illustrated in  FIG. 15 , when no fog is present, the threshold value setting unit  27  sets the boundary line, which is the sensor threshold value, to a higher value in order to prevent red light emitting objects other than tail lamps from being mistakenly recognized as tail lamps. When fog is present, the threshold value setting unit  27  sets the boundary line, which is the sensor threshold value, to a lower value in order to facilitate recognition of red light emitting objects as tail lamps. 
     Note that  FIG. 15  illustrates an example of setting the sensor threshold value for two cases, one in which fog is present and one in which no fog is present. However, the threshold value setting unit  27  may set the sensor threshold value for each of a plurality of levels of density of fog. In this case, the boundary line, which is the sensor threshold value, is set to a lower value as the density of fog is greater. 
     (Step S 63 : Recognition Process) 
     The recognition unit  26  recognizes an obstacle, using the sensor threshold value set in step S 62 . 
     In the example in  FIG. 15 , the recognition unit  26  detects tail lamps in the image data obtained by the camera, using the boundary line set in step S 62 . 
     ***Effects of Fourth Embodiment*** 
     As described above, the fog determination apparatus  10  according to the fourth embodiment sets the sensor threshold value depending on the density of fog. This allows an obstacle to be appropriately recognized. 
     Fifth Embodiment 
     A fifth embodiment differs from the first to fourth embodiments in that a sensor to be used for identifying an obstacle is decided depending on the density of fog. In the fifth embodiment, this difference will be described, and description of the same portions will be omitted. 
     Note that an example in which a function is added to the first to third embodiments will be described here. However, the function may also be added to the fourth embodiment. 
     ***Description of Configuration*** 
     Referring to  FIG. 16 , a configuration of the fog determination apparatus  10  according to the fifth embodiment will be described. 
     The fog determination apparatus  10  differs from those of the first to third embodiments in that the recognition unit  26  and a sensor decision unit  28  are included. Another difference from the first to third embodiments is that the storage  13  realizes the function of a reliability storage unit  32 . 
     ***Description of Operation*** 
     Referring to  FIGS. 17 and 18 , operation of the fog determination apparatus  10  according to the fifth embodiment will be described. 
     The operation of the fog determination apparatus  10  according to the fifth embodiment corresponds to a fog determination method according to the fifth embodiment. The operation of the fog determination apparatus  10  according to the fifth embodiment also corresponds to processes of a fog determination program according to the fifth embodiment. 
     Referring to  FIG. 17 , the overall operation of the fog determination apparatus  10  according to the fifth embodiment will be described. 
     Step S 71  is the process to determine the density of fog described in the first to third embodiments. 
     (Step S 72 : Sensor Decision Process) 
     The sensor decision unit  28  decides the sensor to be used for identifying an obstacle depending on the density of fog determined in step S 71 . 
     Specifically, the reliability storage unit  32  stores reliabilities depending on the distance, separately for each density of fog and for each sensor mounted on the mobile object  100 . As illustrated in  FIG. 18 , when a camera, a millimeter wave radar, and a LiDAR are mounted on the mobile object  100  as sensors, the reliability storage unit  32  stores reliabilities depending on the distance for each of the camera, the millimeter wave radar, and the LiDAR, separately for each density of fog.  FIG. 18  illustrates reliabilities depending on the distance in a case in which fog is present and a case in which no fog is present. The reliabilities for each of the sensors are obtained empirically. 
     The sensor decision unit  28  refers to the reliability storage unit  32 , and decides, as the sensor to be used for identifying an obstacle, a sensor having a high reliability in the case of the density of fog determined in step S 71 . The sensor decision unit  28  may decide the sensor to be used for identifying an obstacle separately for each length of the distance. 
     For example, the sensor decision unit  28  decides to use the LiDAR and the camera when no fog is present, and decides to use the millimeter wave radar and the camera when fog is present. 
     (Step S 73 : Recognition Process) 
     The recognition unit  26  recognizes an obstacle, using the sensor decided in step S 72 . 
     ***Effects of Fifth Embodiment*** 
     As described above, the fog determination apparatus  10  according to the fifth embodiment decides the sensor to be used for identifying an object depending on the density of fog. This allows an obstacle to be appropriately recognized. 
     ***Other Configuration*** 
     &lt;Fourth Variation&gt; 
     In the fifth embodiment, the function is added to the first to third embodiments. However, the function may also be added to the fourth embodiment. 
     In this case, as illustrated in  FIG. 19 , the fog determination apparatus  10  includes the threshold value setting unit  27  in addition to the functional components illustrated in  FIG. 16 . As illustrated in  FIG. 20 , in step S 82  the sensor decision unit  28  decides the sensor to be used, and then in step S 83  the threshold value setting unit  27  decides the sensor threshold value for the decided sensor. 
     Note that the processes of steps S 81 , S 82 , and S 84  are the same as the processes of steps S 71 , S 72 , and S 73  in  FIG. 17 . Also note that the process of step S 83  is the same as the process of step S 62  in  FIG. 14 . 
     The embodiments and variations of the present invention have been described above. Any ones of these embodiments and variations may be implemented in combination. Alternatively, any one or ones of these embodiments and variations may be partially implemented. Note that the present invention is not limited to the above embodiments and variations, and various modifications can be made as necessary. 
     REFERENCE SIGNS LIST 
       10 : fog determination apparatus,  11 : processor,  12 : memory,  13 : storage,  14 : communication interface,  15 : electronic circuit,  21 : point data acquisition unit,  22 : fog determination unit,  23 : first determination unit,  24 : second determination unit,  25 : overall determination unit,  26 : recognition unit,  27 : threshold value setting unit,  28 : sensor decision unit,  31 : decision information storage unit,  32 : reliability storage unit,  100 : mobile object