WO2021106030A1 - Obstacle detection device - Google Patents

Obstacle detection device Download PDF

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Publication number
WO2021106030A1
WO2021106030A1 PCT/JP2019/045918 JP2019045918W WO2021106030A1 WO 2021106030 A1 WO2021106030 A1 WO 2021106030A1 JP 2019045918 W JP2019045918 W JP 2019045918W WO 2021106030 A1 WO2021106030 A1 WO 2021106030A1
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WIPO (PCT)
Prior art keywords
obstacle
calculated
unit
condition
reflection point
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PCT/JP2019/045918
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French (fr)
Japanese (ja)
Inventor
裕 小野寺
浩章 村上
真一 原瀬
亘 辻田
元気 山下
Original Assignee
三菱電機株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by 三菱電機株式会社 filed Critical 三菱電機株式会社
Priority to PCT/JP2019/045918 priority Critical patent/WO2021106030A1/en
Priority to JP2021560765A priority patent/JP7224491B2/en
Publication of WO2021106030A1 publication Critical patent/WO2021106030A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes

Definitions

  • the present invention relates to an obstacle detection device.
  • a device for detecting an obstacle in the surrounding area with respect to the vehicle has been developed by using a distance measuring sensor provided in the vehicle.
  • a distance measuring sensor provided in the vehicle.
  • the left area or the right area is collectively referred to as a “side area”.
  • an obstacle detection device is called an "obstacle detection device”.
  • a parking support system using an obstacle detection device has been developed. That is, a parking space (hereinafter referred to as “parking space”) in the lateral region is detected based on the detection result by the obstacle detection device. Next, control for assisting parking with respect to the detected parking space (hereinafter referred to as “parking support control”) is executed.
  • Patent Document 1 discloses a technique for detecting a parking space. More specifically, a technique for determining the depth limit of a parking space based on the distribution width of a plurality of reverberant signals collected in the measurement window is disclosed (see, for example, the abstract of Patent Document 1).
  • the obstacle detection device In the parking support system, it is required to accurately detect the parking space and accurately execute the parking support control. Therefore, when a plurality of obstacles are present in the lateral region, the obstacle detection device is required to detect each obstacle. In addition, it is required to identify the type of each obstacle and to determine the position of each obstacle.
  • parking obstacle an obstacle that can interfere with parking
  • the curb and the parking obstacle are present.
  • it is required to identify whether the individual obstacles are curbs or parking obstacles.
  • it is required to determine at least the position of parking obstacles. Further, it is required to output a signal indicating the determined position.
  • the technique described in Patent Document 1 determines the depth limit of the parking space based on the distribution width of a plurality of echo signals collected in the measurement window.
  • the technique described in Patent Document 1 does not detect individual obstacles when a plurality of obstacles are present in the lateral region. Therefore, when a plurality of obstacles exist in the lateral region, there is a problem that the type of each obstacle cannot be identified. Further, at this time, there is a problem that the position of each obstacle cannot be determined.
  • An object of the present invention is to provide an object detection device.
  • the obstacle detection device of the present invention uses a distance measuring sensor provided in the vehicle to detect an obstacle group in a lateral region with respect to a moving vehicle, and a discontinuous part in the obstacle group. Multiple parts included in the obstacle group by analyzing the discontinuous part detection part to detect, the analysis area extraction part to extract the analysis area based on the discontinuous part, and the frequency distribution related to a plurality of reflection points in the analysis area.
  • a grouping unit that sets a plurality of reflection point groups corresponding to an individual obstacle, distinguishes whether or not each of the plurality of obstacles is a curb, and each of the plurality of obstacles is a parking obstacle. It includes an identification unit that identifies whether or not it is an object, and an output unit that outputs a signal indicating at least the position of the parking obstacle when the distance between the curb and the parking obstacle is less than or equal to a predetermined distance. ..
  • the present invention since it is configured as described above, when the curb and the parking obstacle are arranged close to each other, it is possible to output at least a signal indicating the position of the parking obstacle.
  • FIG. 1 It is a block diagram which shows the main part of the parking support system including the obstacle detection device which concerns on Embodiment 1.
  • FIG. It is a block diagram which shows the main part of the obstacle detection part in the obstacle detection device which concerns on Embodiment 1.
  • FIG. It is a block diagram which shows the main part of the grouping part in the obstacle detection apparatus which concerns on Embodiment 1.
  • FIG. It is a block diagram which shows the main part of the identification part in the obstacle detection apparatus which concerns on Embodiment 1.
  • FIG. It is a block diagram which shows the hardware composition of the obstacle detection apparatus which concerns on Embodiment 1.
  • FIG. It is a block diagram which shows the other hardware configuration of the obstacle detection apparatus which concerns on Embodiment 1.
  • FIG. 10A is an explanatory diagram showing an example of four obstacles in the lateral region and an example of a plurality of reflection points corresponding to each of the four obstacles.
  • FIG. 10B is an explanatory diagram showing an example of the distance between reflection points with respect to time.
  • Examples of two obstacles in one analysis area, examples of multiple reflection points corresponding to each of the two obstacles, and two reflections corresponding to the two obstacles one-to-one It is explanatory drawing which shows the example of a point group. It is explanatory drawing which shows the example of the frequency distribution for analysis in the 1st analysis part. It is explanatory drawing which shows the example of the frequency distribution for analysis in the 2nd analysis part. It is explanatory drawing which shows the example of the frequency distribution for analysis in the 2nd analysis part. Examples of three obstacles in one analysis area, examples of multiple reflection points corresponding to each of the three obstacles, and three reflections one-to-one with the three obstacles. It is explanatory drawing which shows the example of a point group.
  • FIG. 23A is an explanatory diagram showing an example of five obstacles in the lateral region and an example of a plurality of reflection points corresponding to each of the five obstacles.
  • FIG. 23B is an explanatory diagram showing an example of the variance value of the distance measurement value with respect to time.
  • FIG. 23C is an explanatory diagram showing an example of the amount of change in the dispersion value with respect to time. It is explanatory drawing which shows the example of one threshold value and two ranges in a feature amount coordinate system.
  • FIG. It is a block diagram which shows the main part of the grouping part in the obstacle detection apparatus which concerns on Embodiment 2.
  • FIG. 1 is a block diagram showing a main part of a parking support system including an obstacle detection device according to the first embodiment.
  • FIG. 2 is a block diagram showing a main part of an obstacle detection unit in the obstacle detection device according to the first embodiment.
  • FIG. 3 is a block diagram showing a main part of the grouping unit in the obstacle detection device according to the first embodiment.
  • FIG. 4 is a block diagram showing a main part of the identification unit in the obstacle detection device according to the first embodiment.
  • a parking support system including an obstacle detection device according to the first embodiment will be described with reference to FIGS. 1 to 4.
  • the vehicle 1 has a distance measuring sensor 2, an obstacle detection device 100, and a parking support device 200.
  • the distance measuring sensor 2, the obstacle detection device 100, and the parking support device 200 constitute a main part of the parking support system 300.
  • the distance measuring sensor 2 is composed of a TOF (Time of Flight) type distance measuring sensor.
  • the ranging sensor 2 uses, for example, ultrasonic waves, radio waves (more specifically, millimeter waves) or light (more specifically, laser light).
  • ultrasonic waves, radio waves, light, and the like used by the distance measuring sensor 2 are collectively referred to as “exploration waves”.
  • the exploration wave transmitted or transmitted by the ranging sensor 2 may be referred to as a “transmitted wave”.
  • the exploration wave reflected or reflected by the obstacle O may be referred to as a "reflected wave”.
  • the exploration wave received or received by the ranging sensor 2 may be referred to as a “received wave”.
  • the distance measuring sensor 2 is provided on the left side of the vehicle 1. Alternatively, the distance measuring sensor 2 is provided on the right side of the vehicle 1. Alternatively, the distance measuring sensor 2 is provided on each of the left side portion of the vehicle 1 and the right side portion of the vehicle 1.
  • the distance measuring sensor 2 provided on the left side of the vehicle 1 moves to the left region at a predetermined time interval ⁇ T when the vehicle 1 is moving at a speed V of PV or less at a predetermined speed (for example, 30 km / h). It transmits exploration waves. Further, the distance measuring sensor 2 provided on the left side of the vehicle 1 receives the reflected wave by the obstacle group OG in the left region. On the other hand, the distance measuring sensor 2 provided on the right side of the vehicle 1 transmits an exploration wave to the right region at a predetermined time interval ⁇ T when the vehicle 1 is moving at a speed V equal to or less than a predetermined speed PV. Is what you do. Further, the distance measuring sensor 2 provided on the right side of the vehicle 1 receives the reflected wave by the obstacle group OG in the right region.
  • the obstacle group OG includes 0 obstacle O, 1 obstacle O, or a plurality of obstacle O.
  • Individual obstacles O are, for example, walls, other parked vehicles (hereinafter referred to as "parked vehicles"), guard rails, electric poles, poles, signs, plants, pedestrians, bicycles, wheelchairs, strollers, curbs, wheel chocks or It is composed of steps.
  • the obstacle O having a height H less than the threshold value H_th_1 is referred to as a "road surface obstacle”.
  • an obstacle O having a height H of the threshold value H_th_1 or more and less than the threshold value H_th_2 may be referred to as a “road obstacle”.
  • an obstacle O having a height H equal to or higher than the threshold value H_th_2 may be referred to as a "running obstacle”.
  • the traveling obstacle has a height H large enough to come into contact with the bumper portion of the vehicle 1.
  • Traveling obstacles include, for example, walls, parked vehicles, guardrails, electric poles, poles, signs, plants, pedestrians, bicycles, wheelchairs and strollers.
  • the road obstacle has a height H so small that it cannot come into contact with the bumper portion of the vehicle 1, and has a height H that is large to some extent because it is difficult for the vehicle 1 to get over it.
  • Road obstacles include, for example, curbs and wheel chocks.
  • the road surface obstacle has a height H so small that it cannot come into contact with the bumper portion of the vehicle 1, and has a height H that is easy to get over by the vehicle 1 and is small to some extent.
  • the road surface obstacle includes, for example, a step.
  • the obstacle O having a height H less than the threshold value H_th_3 may be referred to as a "low profile obstacle”.
  • an obstacle O having a height H equal to or higher than the threshold value H_th_3 may be referred to as a “tall obstacle”.
  • the threshold value H_th_3 is set to a value equivalent to, for example, the threshold value H_th_2.
  • the traveling obstacle is included in the tall obstacle, and the road obstacle and the road surface obstacle are included in the low-back obstacle.
  • the threshold value H_th_3 is set to a value equivalent to the threshold value H_th_1.
  • the traveling obstacle and the road obstacle are included in the tall obstacle, and the road surface obstacle is included in the low back obstacle.
  • the obstacle O having a width W less than the threshold value W_th_1 may be referred to as a "narrow obstacle”.
  • an obstacle O having a width W equal to or greater than the threshold value W_th_2 may be referred to as a "wide obstacle”.
  • the width W is the width with respect to the front-rear direction of the vehicle 1 (that is, the moving direction of the vehicle 1).
  • Wide obstacles include, for example, walls, guardrails, curbs and steps.
  • Narrow obstacles include, for example, utility poles, poles, signs, plants, pedestrians, bicycles, wheelchairs and strollers.
  • the threshold value W_th_1 for identifying narrow obstacles is set to, for example, 1 meter.
  • the moving obstacle O is sometimes called a "dynamic obstacle".
  • Dynamic obstacles include, for example, pedestrians, bicycles, wheelchairs and strollers.
  • the stationary obstacle O among the narrow obstacles may be referred to as a "static obstacle”.
  • Static obstacles include, for example, utility poles, poles, signs and plants.
  • the obstacle detection device 100 is composed of, for example, an electronic control unit (hereinafter referred to as "ECU").
  • the obstacle detection device 100 includes an obstacle detection unit 11, a discontinuous unit detection unit 12, an analysis area extraction unit 13, a grouping unit 14, an identification unit 15, and an output unit 16.
  • the parking support device 200 is composed of, for example, an ECU.
  • the parking support device 200 has a parking support control unit 21.
  • the obstacle detection device 100 has a function of acquiring information indicating the speed V of the vehicle 1 (hereinafter referred to as "vehicle speed information").
  • vehicle speed information is acquired by, for example, CAN (Control Area Network) communication.
  • the obstacle detection device 100 has a function of determining whether or not the vehicle 1 is moving at a speed V equal to or lower than a predetermined speed PV by using the acquired vehicle speed information.
  • the obstacle detection device 100 has a function of acquiring information indicating the position of the vehicle 1 and the direction of the vehicle 1 (hereinafter referred to as “vehicle position information").
  • vehicle position information is acquired by, for example, CAN communication.
  • the obstacle detection device 100 stores in advance information indicating the installation position of the distance measurement sensor 2 in the vehicle 1 and the installation direction of the distance measurement sensor 2 in the vehicle 1 (hereinafter referred to as “sensor installation position information”).
  • the obstacle detection device 100 has a function of calculating the position of the distance measuring sensor 2 and the direction of the distance measuring sensor 2 by using the acquired vehicle position information and the stored sensor installation position information. ..
  • the obstacle detection device 100 has a function of acquiring information indicating the yaw rate of the vehicle 1 (hereinafter referred to as "yaw rate information”) and information indicating the steering angle of the vehicle 1 (hereinafter referred to as “steering angle information”). doing.
  • the yaw rate information and the steering angle information are acquired by, for example, CAN communication.
  • the sensor installation position information is stored in advance in the obstacle detection device 100.
  • the obstacle detection device 100 has a function of calculating the position of the vehicle 1 and the direction of the vehicle 1 by using the acquired yaw rate information and the steering angle information.
  • the obstacle detection device 100 uses the stored sensor installation position information to determine the position of the distance measuring sensor 2 and the orientation of the distance measuring sensor 2 based on the calculated position of the vehicle 1 and the orientation of the vehicle 1. It has a function to calculate.
  • the function of determining whether or not the vehicle 1 is moving at a speed V of a predetermined speed PV or less is referred to as a "vehicle speed determination function”. Further, the function of calculating the position of the distance measuring sensor 2 and the orientation of the distance measuring sensor 2 is referred to as a "sensor position calculation function”.
  • the obstacle detection unit 11 includes a transmission signal output unit 31, a reception signal acquisition unit 32, a distance measurement value calculation unit 33, and a coordinate value calculation unit 34.
  • the transmission signal output unit 31 transmits an electric signal (hereinafter referred to as “transmission signal”) TS corresponding to the transmission wave at a predetermined time interval ⁇ T. It is output to the distance measuring sensor 2. As a result, the transmission signal output unit 31 causes the distance measuring sensor 2 to transmit the transmitted wave at a predetermined time interval ⁇ T. Whether or not the vehicle 1 is moving at a speed V equal to or lower than a predetermined speed PV is determined by the vehicle speed determination function.
  • the received signal acquisition unit 32 acquires an electrical signal (hereinafter referred to as “received signal”) RS corresponding to the received wave by the distance measuring sensor 2.
  • the distance measurement value calculation unit 33 calculates the distance measurement value D by the TOF method using the received signal RS.
  • Various known techniques can be used to calculate the distance measurement value D by the TOF method. Detailed description of these techniques will be omitted.
  • the coordinate value calculation unit 34 uses the distance measurement value D to indicate the position of the RP at the point where the exploration wave is reflected by the obstacle O (hereinafter referred to as “reflection point”) (hereinafter referred to as “reflection point coordinate value”). It may be that.) C_X and C_Y are calculated.
  • the coordinate values C_X and C_Y are, for example, the first axis (hereinafter referred to as "X-axis”) along the front-rear direction of the vehicle 1 (that is, the moving direction of the vehicle 1) and the left-right direction of the vehicle 1 (that is, the moving direction of the vehicle 1). It is a coordinate value in a coordinate system (hereinafter referred to as "XY coordinate system”) having a second axis (hereinafter referred to as "Y axis”) along the orthogonal direction).
  • the coordinate value calculation unit 34 calculates the coordinate values C_X and C_Y by obtaining the following vectors. That is, the coordinate value calculation unit 34 has a start point corresponding to the position of the distance measuring sensor 2 at the time when the corresponding exploration wave is transmitted, and has a direction corresponding to the direction of the distance measuring sensor 2 at that time. However, a vector having a magnitude corresponding to the corresponding distance measurement value D is obtained. At this time, the position of the distance measuring sensor 2 and the orientation of the distance measuring sensor 2 are calculated by the sensor position calculation function. This vector is a vector in the XY coordinate system.
  • the coordinate value C_X may be referred to as "X coordinate value”.
  • the coordinate value C_Y may be referred to as a "Y coordinate value”.
  • the direction along the X axis may be referred to as "X direction”.
  • the direction along the Y axis may be referred to as "Y direction” or "depth direction”.
  • the side far from the vehicle 1 with respect to an arbitrary point in the XY coordinate system may be referred to as the "back side”.
  • the side closer to the vehicle 1 with respect to an arbitrary point in the XY coordinate system may be referred to as the "front side".
  • the information indicating the waveform of the received signal RS corresponding to each reflection point RP is referred to as "waveform information”.
  • the information indicating the distance measurement value D corresponding to each reflection point RP is referred to as “distance measurement value information”.
  • the information indicating the coordinate values C_X and C_Y corresponding to the individual reflection point RP is referred to as “coordinate value information”.
  • information including waveform information, ranging value information and coordinate value information is referred to as "reflection point information”.
  • the obstacle detection unit 11 outputs the reflection point information to the discontinuous unit detection unit 12 and the analysis area extraction unit 13.
  • the processes executed by the obstacle detection unit 11 may be collectively referred to as "obstacle detection process". That is, the obstacle detection process outputs the transmission signal TS, the reception signal RS, the distance measurement value D, the coordinate values C_X and C_Y, and the reflection point information. It includes processing and so on.
  • the obstacle detection process is executed.
  • the coordinate values C_X and C_Y indicating the positions of the plurality of reflection point RPs are calculated.
  • a plurality of reflection point RPs corresponding to the obstacle group OG are detected.
  • the obstacle group OG is detected.
  • the discontinuous unit detection unit 12 acquires the reflection point information output by the obstacle detection unit 11.
  • the discontinuous portion detecting unit 12 detects the discontinuous portion (hereinafter referred to as “discontinuous portion”) DP in the obstacle group OG by using the acquired reflection point information.
  • the discontinuous unit detection unit 12 outputs information indicating the detected discontinuous unit DP (hereinafter referred to as “discontinuous unit information”) to the analysis area extraction unit 13.
  • the processes executed by the discontinuous portion detection unit 12 may be collectively referred to as “discontinuous portion detection processing". That is, the discontinuous portion detection process includes a process of acquiring reflection point information, a process of detecting the discontinuous portion DP, a process of outputting discontinuous portion information, and the like.
  • the analysis area extraction unit 13 acquires the discontinuous unit information output by the discontinuous unit detection unit 12.
  • the analysis area extraction unit 13 extracts the area for analysis (hereinafter referred to as “analysis area”) AA by the grouping unit 14 by using the acquired discontinuous part information.
  • the analysis region AA is a region formed by dividing the lateral region LA based on the discontinuous portion DP. A specific example of the analysis region AA will be described later with reference to FIG.
  • each analysis region AA contains a plurality of reflection point RPs.
  • the analysis area extraction unit 13 acquires the reflection point information output by the obstacle detection unit 11.
  • the analysis area extraction unit 13 outputs the reflection point information corresponding to the plurality of reflection point RPs included in the individual analysis area AA of the acquired reflection point information to the grouping unit 14. That is, the analysis area extraction unit 13 outputs the reflection point information for each analysis area AA to the grouping unit 14.
  • the processes executed by the analysis area extraction unit 13 may be collectively referred to as "analysis area extraction process". That is, the analysis area extraction process includes a process of acquiring discontinuous part information, a process of extracting the analysis area AA, a process of acquiring the reflection point information, a process of outputting the reflection point information for each analysis area AA, and the like. ..
  • the grouping unit 14 acquires the reflection point information output by the analysis area extraction unit 13.
  • the grouping unit 14 uses the acquired reflection point information to group a plurality of reflection point RPs included in each analysis area AA into individual obstacles O in each analysis area AA.
  • the corresponding reflection point group PG is set.
  • one analysis area AA of the plurality of analysis areas AA includes a plurality of reflection point RPs corresponding to one obstacle O
  • the plurality of reflection point RPs are grouped. By doing so, one reflection point group PG corresponding to the one obstacle O is set.
  • the other analysis region AA of the plurality of analysis regions AA includes a plurality of reflection point RPs corresponding to the plurality of obstacles O
  • the plurality of reflection point RPs are included.
  • a plurality of reflection point group PGs corresponding to the plurality of obstacles O on a one-to-one basis are set.
  • the grouping unit 14 has a first analysis unit 41 and a second analysis unit 42.
  • the first analysis unit 41 creates a frequency distribution FD_Y indicating the number of reflection point RPs with respect to the Y coordinate value C_Y by using the reflection point information corresponding to each analysis region AA.
  • the first analysis unit 41 analyzes the created frequency distribution FD_Y. More specifically, the first analysis unit 41 executes the peak separation process for the created frequency distribution FD_Y. As a result, one or more frequency groups FG_Y are set.
  • the second analysis unit 42 creates a frequency distribution FD_X indicating the number of reflection point RPs with respect to the X coordinate value C_X by using the reflection point information corresponding to each frequency group FG_Y.
  • the second analysis unit 42 analyzes the created frequency distribution FD_X. More specifically, the second analysis unit 42 executes the peak separation process for the created frequency distribution FD_X. As a result, one or more frequency groups FG_X are set.
  • the grouping unit 14 sets the reflection point cloud group PG corresponding to each obstacle O based on the analysis result by the first analysis unit 41 and the analysis result by the second analysis unit 42.
  • a specific example of the method of setting the reflection point group PG will be described later with reference to FIGS. 11 to 18.
  • each reflection point group PG includes a plurality of reflection point RPs.
  • the grouping unit 14 outputs the reflection point information corresponding to the plurality of reflection point RPs included in the individual reflection point group PG among the acquired reflection point information to the identification unit 15. That is, the grouping unit 14 outputs the reflection point information for each reflection point group PG to the identification unit 15.
  • grouping process the processes executed by the grouping unit 14 may be collectively referred to as "grouping process". That is, in the grouping process, the process of acquiring the reflection point information for each analysis area AA, the process of setting the reflection point group PG corresponding to each obstacle O, and the process of outputting the reflection point information for each reflection point group PG are output. It includes processing and so on.
  • the identification unit 15 acquires the reflection point information output by the grouping unit 14.
  • the identification unit 15 uses the acquired reflection point information to identify the type of obstacle O corresponding to each reflection point group PG.
  • the identification unit 15 has a width determination unit 51, a position determination unit 52, and a height determination unit 53.
  • the width determination unit 51 determines the width of each reflection point group PG with respect to the X direction by using the acquired reflection point information. As a result, the width W of each obstacle O with respect to the X direction is determined. The width determination unit 51 determines whether or not each obstacle O is a wide obstacle based on the result of the determination. Further, the width determination unit 51 determines whether or not each obstacle O is a narrow obstacle based on the result of the determination.
  • the position determination unit 52 determines the position of each reflection point group PG with respect to the X direction by using the acquired reflection point information. As a result, the position of each obstacle O with respect to the X direction is determined. Further, the position determination unit 52 determines the position of each reflection point group PG with respect to the depth direction by using the acquired reflection point information. As a result, the position of each obstacle O with respect to the depth direction is determined.
  • the height determination unit 53 determines the height H of each obstacle O by using the acquired reflection point information. Thereby, for example, it is determined whether the individual obstacle O is a traveling obstacle, a road obstacle, or a road surface obstacle.
  • the identification unit 15 identifies whether or not each obstacle O is a curb based on the judgment result of at least one of these judgment units (51, 52, 53). A specific example of a method for identifying whether or not each obstacle O is a curb will be described later. Further, the identification unit 15 identifies whether or not each obstacle O is a parking obstacle based on the determination result by at least one of these determination units (51, 52, 53). .. A specific example of a method for identifying whether or not each obstacle O is a parking obstacle will be described later.
  • the processes executed by the identification unit 15 may be collectively referred to as "identification processing". That is, the identification process includes a process of determining the width W of each obstacle O, a process of determining the position of each obstacle O, a process of determining the height H of each obstacle O, and an individual obstacle. It includes a process of identifying the type of O.
  • the output unit 16 outputs a signal indicating the result of the identification process (hereinafter referred to as "identification result signal”) to the parking support control unit 21.
  • the identification result signal is information indicating whether or not each obstacle O is a curb, information indicating whether or not each obstacle O is a parking obstacle, and the position of each obstacle O. It contains information indicating. Therefore, when the curb and the parking obstacle are included in the obstacle group OG and the curb and the parking obstacle are arranged close to each other (that is, when the distance between the curb and the parking obstacle is less than a predetermined distance), The identification result signal indicates at least the position of the parking obstacle.
  • the processing executed by the output unit 16 may be collectively referred to as "output processing". That is, the output process includes a process of outputting an identification result signal and the like.
  • the parking support control unit 21 acquires the identification result signal output by the output unit 16.
  • the parking support control unit 21 detects the parking space in the side region LA by using the acquired identification result signal.
  • the parking support control unit 21 executes parking support control for the detected parking space. Specifically, for example, the parking support control unit 21 executes control for realizing so-called "automatic parking”.
  • Various known techniques can be used for parking support control. Detailed description of these techniques will be omitted.
  • the obstacle detection device 100 has a processor 61 and a memory 62.
  • the memory 62 stores programs for realizing the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16.
  • the processor 61 reads and executes such a program, the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16 are realized. ..
  • the obstacle detection device 100 has a processing circuit 63.
  • the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16 are realized by the dedicated processing circuit 63.
  • the obstacle detection device 100 has a processor 61, a memory 62, and a processing circuit 63 (not shown).
  • some of the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16 are performed by the processor 61 and the memory 62.
  • the remaining functions are realized by the dedicated processing circuit 63.
  • the processor 61 is composed of one or a plurality of processors.
  • processors for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a microprocessor, a microcontroller, or a DSP (Digital Signal Processor) is used.
  • CPU Central Processing Unit
  • GPU Graphics Processing Unit
  • DSP Digital Signal Processor
  • the memory 62 is composed of one or a plurality of non-volatile memories. Alternatively, the memory 62 is composed of one or more non-volatile memories and one or more volatile memories. That is, the memory 62 is composed of one or a plurality of memories. Each memory uses, for example, a semiconductor memory or a magnetic disk. More specifically, each volatile memory uses, for example, a RAM (Random Access Memory).
  • the individual non-volatile memory is, for example, a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmory), an EEPROM (Electrically Erasable Programmory) drive, or a hard disk drive that uses a hard disk drive, a hard disk, or a drive solid state drive.
  • ROM Read Only Memory
  • flash memory an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmory), an EEPROM (Electrically Erasable Programmory) drive
  • EEPROM Electrically Erasable Programmory
  • the processing circuit 63 is composed of one or a plurality of digital circuits. Alternatively, the processing circuit 63 is composed of one or more digital circuits and one or more analog circuits. That is, the processing circuit 63 is composed of one or a plurality of processing circuits.
  • the individual processing circuits are, for example, ASIC (Application Special Integrated Circuit), PLD (Programmable Logic Device), FPGA (Field Programmable Gate Array), FPGA (Field Program Is.
  • the parking support device 200 has a processor 71 and a memory 72.
  • the memory 72 stores a program for realizing the function of the parking support control unit 21.
  • the function of the parking support control unit 21 is realized by the processor 71 reading and executing such a program.
  • the parking support device 200 has a processing circuit 73.
  • the function of the parking support control unit 21 is realized by the dedicated processing circuit 73.
  • the parking support device 200 has a processor 71, a memory 72, and a processing circuit 73 (not shown).
  • some of the functions of the parking support control unit 21 are realized by the processor 71 and the memory 72, and the remaining functions are realized by the dedicated processing circuit 73.
  • the processor 71 is composed of one or a plurality of processors.
  • the individual processors use, for example, CPUs, GPUs, microprocessors, microcontrollers or DSPs.
  • the memory 72 is composed of one or a plurality of non-volatile memories.
  • the memory 72 is composed of one or more non-volatile memories and one or more volatile memories. That is, the memory 72 is composed of one or a plurality of memories.
  • Each memory uses, for example, a semiconductor memory or a magnetic disk. More specifically, each volatile memory uses, for example, RAM. Further, each non-volatile memory uses, for example, a ROM, a flash memory, an EPROM, an EEPROM, a solid state drive, or a hard disk drive.
  • the processing circuit 73 is composed of one or a plurality of digital circuits. Alternatively, the processing circuit 73 is composed of one or more digital circuits and one or more analog circuits. That is, the processing circuit 73 is composed of one or a plurality of processing circuits.
  • the individual processing circuits use, for example, ASIC, PLD, FPGA, SoC or system LSI.
  • the operation of the parking support system 300 will be described focusing on the operations of the obstacle detection device 100 and the parking support device 200.
  • the obstacle detection unit 11 executes the obstacle detection process (step ST1).
  • the discontinuous portion detection unit 12 executes the discontinuous portion detection process (step ST2).
  • the analysis area extraction unit 13 executes the analysis area extraction process (step ST3).
  • the grouping unit 14 executes the grouping process (step ST4).
  • the identification unit 15 executes the identification process (step ST5).
  • the output unit 16 executes the output process (step ST6).
  • the parking support control unit 21 executes parking support control (step ST7).
  • Each of the obstacles O_1 and O_2 is composed of parked vehicles.
  • Obstacle O_3 is composed of curbs.
  • Obstacle O_4 is composed of utility poles or poles.
  • TR indicates a movement route of the vehicle 1 at a speed V of a predetermined speed PV or less.
  • a plurality of reflection points RP_1, RP_2, RP_3, and RP_4 corresponding to the obstacle group OG are detected.
  • Four reflection points RP_4 corresponding to are detected.
  • the exploration wave propagates while gradually spreading in the air. Therefore, there may be a plurality of propagation paths (so-called “paths”) of the exploration wave from the transmission by the distance measurement sensor 2 to the reception by the distance measurement sensor 2.
  • the ranging sensor 2 transmits the exploration wave at a predetermined time interval ⁇ T.
  • the transmitted exploration wave may be sequentially reflected by N obstacles O.
  • the first to Nth reflected waves may be sequentially received.
  • the nth reflected wave among the first to Nth reflected waves is referred to as an "nth wave".
  • N is an arbitrary integer of 2 or more.
  • n is an arbitrary integer from 1 to N.
  • the transmitted exploration wave may be sequentially reflected by two obstacles O_3 and O_4.
  • the first wave and the second wave are sequentially received.
  • the installation height of the distance measuring sensor 2 in the vehicle 1 is set to a height of about several tens of centimeters with respect to the road surface. Therefore, for an obstacle O having a small height H (for example, a road obstacle or a road surface obstacle), when the distance measuring sensor 2 transmits a search wave, the transmitted search wave may not be irradiated. As a result, the reflected wave may not be received by the distance measuring sensor 2 for the obstacle O having a small height H.
  • H for example, a road obstacle or a road surface obstacle
  • the reflection point RP may include one or more reflection point RPs corresponding to the first wave and one or more reflection point RPs corresponding to the second wave.
  • the four reflection points RP_4 corresponding to the obstacle O_4 include one reflection point RP_4 corresponding to the first wave and three reflection points RP_4 corresponding to the second wave. It has been. That is, in the figure, circles ( ⁇ ) indicate individual reflection point RPs corresponding to the first wave. Further, in the figure, triangle marks ( ⁇ ) indicate individual reflection point RPs corresponding to the second wave.
  • the distance d between each of the two adjacent reflection point RPs among the plurality of reflection point RPs corresponding to the nth wave of the plurality of reflection point RPs corresponding to the obstacle group OG is “reflected”. It is called “point-to-point distance”.
  • the distance d between reflection points is the Euclidean distance in the XY coordinate system.
  • FIG. 10B shows an example of the distance d between reflection points with respect to time for a plurality of reflection point RPs corresponding to the first wave.
  • the time axis corresponds to the X axis in the XY coordinate system.
  • the discontinuous portion detection unit 12 calculates the distance d between reflection points.
  • the discontinuous portion detecting unit 12 detects the discontinuous portion DP when the following conditions (hereinafter referred to as “first condition”) are satisfied with respect to the calculated distance d between reflection points. That is, the first condition is that the distance d between reflection points exceeds a predetermined threshold value d_th.
  • the distance d between reflection points exceeds the threshold value d_th at time t_1.
  • the distance d between reflection points exceeds the threshold value d_th at time t_2.
  • the distance d between reflection points exceeds the threshold value d_th at time t_2.
  • the distance d between reflection points exceeds the threshold value d_th at time t_2.
  • one discontinuous portion DP_2 is detected.
  • the side region LA is divided into three regions by the two discontinuous portions DP_1 and DP_2.
  • three analysis regions AA_1, AA_2, and AA_3 are extracted.
  • FIG. 11 shows an example of a plurality of reflection points RP_3 and RP_4 included in one analysis area AA_2. As shown in FIG. 11, 14 reflection points RP_3 corresponding to the obstacle O_3 and 4 reflection points RP_4 corresponding to the obstacle O_4 are included in the analysis region AA_2.
  • the first analysis unit 41 creates a frequency distribution FD_Y related to a plurality of reflection points RP_3 and RP_4 in the analysis region AA_2.
  • FIG. 12 shows an example of the frequency distribution FD_Y.
  • the frequency distribution FD_Y includes the frequency corresponding to the plurality of reflection points RP_3 (F_Y_1 in the figure) and the frequency corresponding to the plurality of reflection points RP_4 (F_Y_2 in the figure).
  • the first analysis unit 41 executes peak separation processing for the frequency distribution FD_Y.
  • two frequency groups FG_Y_1 and FG_Y_2 are set. That is, the frequency group FG_Y_1 corresponds to a plurality of reflection points RP_3. Further, the frequency group FG_Y_2 corresponds to a plurality of reflection points RP_4.
  • the second analysis unit 42 creates a frequency distribution FD_X_1 related to a plurality of reflection points RP_3 corresponding to the frequency group FG_Y_1.
  • FIG. 13 shows an example of the frequency distribution FD_X_1.
  • the frequency distribution FD_X_1 includes frequencies (F_X_1 in the figure) corresponding to a plurality of reflection points RP_3.
  • the second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_1. As a result, one frequency group FG_X_1 is set. That is, the frequency group FG_X_1 corresponds to a plurality of reflection points RP_3.
  • the second analysis unit 42 creates a frequency distribution FD_X_2 related to a plurality of reflection points RP_4 corresponding to the frequency group FG_Y_2.
  • FIG. 14 shows an example of the frequency distribution FD_X_2.
  • the frequency distribution FD_X_2 includes frequencies (F_X_2 in the figure) corresponding to a plurality of reflection points RP_4.
  • the second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_2. As a result, one frequency group FG_X_2 is set. That is, the frequency group FG_X_2 corresponds to a plurality of reflection points RP_4.
  • the grouping unit 14 sets one reflection point group PG_1 corresponding to the frequency group FG_Y_1 and the frequency group FG_X_1. Further, the grouping unit 14 sets one reflection point group PG_2 corresponding to the frequency group FG_Y_2 and the frequency group FG_X_2. As a result, as shown in FIG. 11, two reflection point groups PG_1 and PG_2 corresponding to two obstacles O_3 and O_4 are set one-to-one.
  • FIG. 15 shows an example of a plurality of reflection points RP_3, RP_4, and RP_5 included in one analysis area AA_2.
  • 21 reflection points RP_3 corresponding to the obstacle O_3, 4 reflection points RP_4 corresponding to the obstacle O_4, and 4 reflection points RP_5 corresponding to the obstacle O_5 are located in the analysis region AA_2.
  • the obstacle O_5 is composed of, for example, a signboard.
  • the first analysis unit 41 creates a frequency distribution FD_Y related to a plurality of reflection points RP_3, RP_4, and RP_5 for the analysis area AA_2.
  • FIG. 16 shows an example of the frequency distribution FD_Y.
  • the frequency distribution FD_Y includes the frequency corresponding to the plurality of reflection points RP_3 (F_Y_1 in the figure) and the frequency corresponding to the plurality of reflection points RP_4 and RP_5 (F_Y_2 in the figure).
  • the first analysis unit 41 executes peak separation processing for the frequency distribution FD_Y.
  • two frequency groups FG_Y_1 and FG_Y_2 are set. That is, the frequency group FG_Y_1 corresponds to a plurality of reflection points RP_3. Further, the frequency group FG_Y_2 corresponds to a plurality of reflection points RP_4 and RP_5.
  • the second analysis unit 42 creates a frequency distribution FD_X_1 related to a plurality of reflection points RP_3 corresponding to the frequency group FG_Y_1.
  • FIG. 17 shows an example of the frequency distribution FD_X_1.
  • the frequency distribution FD_X_1 includes frequencies (F_X_1 in the figure) corresponding to a plurality of reflection points RP_3.
  • the second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_1. As a result, one frequency group FG_X_1 is set. That is, the frequency group FG_X_1 corresponds to a plurality of reflection points RP_3.
  • the second analysis unit 42 creates a frequency distribution FD_X_2 related to a plurality of reflection points RP_4 and RP_5 corresponding to the frequency group FG_Y_2.
  • FIG. 18 shows an example of the frequency distribution FD_X_2.
  • the frequency distribution FD_X_2 includes a frequency corresponding to a plurality of reflection points RP_4 (F_X_2_1 in the figure) and a frequency corresponding to the plurality of reflection points RP_5 (F_X_2_2 in the figure).
  • the second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_2.
  • two frequency groups FG_X_2_1 and FG_X_2_2 are set. That is, the frequency group FG_X_2_1 corresponds to a plurality of reflection points RP_4. Further, the frequency group FG_X_2_2 corresponds to a plurality of reflection points RP_5.
  • the grouping unit 14 sets one reflection point group PG_1 corresponding to the frequency group FG_Y_1 and the frequency group FG_X_1. Further, the grouping unit 14 sets one reflection point group PG_2_1 corresponding to the frequency group FG_Y_1 and the frequency group FG_X_2_1. Further, the grouping unit 14 sets one reflection point group PG_2_2 corresponding to the frequency group FG_Y_2 and the frequency group FG_X_2_2. As a result, as shown in FIG. 15, three reflection point groups PG_1, PG_2_1, PG_2, which correspond one-to-one with the three obstacles O_3, O_4, O_5 are set.
  • a range in which the frequency F continuously exceeds a predetermined value may be extracted as one frequency group FG.
  • a clustering method such as the k-nearest neighbor method may be used.
  • the height determination unit 53 uses the waveform information included in the reflection point information corresponding to each reflection point RP, and the intensity of the received signal RS corresponding to each reflection point RP (hereinafter referred to as “received signal intensity”). Two feature quantities FA1 and FA2 related to SS are detected. Each of the feature quantities FA1 and FA2 has a correlation with the received signal strength SS.
  • the feature amount FA1 is referred to as “first feature amount”. Further, the feature amount FA2 is referred to as a “second feature amount”. Further, a waveform indicating the received signal strength SS with respect to time is referred to as a “received signal waveform”. FIG. 19 shows an example of the received signal waveform.
  • the height determination unit 53 detects the width (hereinafter referred to as “waveform width”) WW of the portion where the received signal strength SS in the received signal waveform exceeds a predetermined threshold value SS_th.
  • the height determination unit 53 uses the detected waveform width WW for the first feature amount FA1 or the second feature amount FA2.
  • the height determination unit 53 detects the area (hereinafter referred to as “waveform area”) WA of the portion where the received signal strength SS in the received signal waveform exceeds the threshold value SS_th.
  • the height determination unit 53 uses the detected waveform area WA for the first feature amount FA1 or the second feature amount FA2.
  • the height determination unit 53 detects the maximum value (hereinafter referred to as “waveform height”) WH of the height of the portion where the received signal strength SS in the received signal waveform exceeds the threshold value SS_th.
  • the height determination unit 53 uses the detected waveform height WH for the first feature amount FA1 or the second feature amount FA2.
  • the height determination unit 53 detects any two values of the waveform width WW, the waveform area WA, and the waveform height WH for each reflection point RP.
  • the height determination unit 53 uses one of the two detected values for the first feature amount FA1 and uses the other one of the two detected values. Used for the second feature amount FA2.
  • each reflection point group PG includes a plurality of reflection point RPs. Therefore, for each reflection point group PG, a plurality of first feature quantities FA1 corresponding to the plurality of reflection point RPs are detected, and a plurality of second feature quantities corresponding to the plurality of reflection point RPs are detected. FA2 is detected.
  • the height determination unit 53 calculates a statistic (hereinafter, sometimes referred to as “first statistic”) S1 based on a plurality of corresponding first feature amounts FA1 for each reflection point group PG. Further, the height determination unit 53 calculates a statistic (hereinafter, may be referred to as “second statistic value”) S2 based on a plurality of corresponding second feature amounts FA2 for each reflection point group PG.
  • various statistics can be used for the first statistic S1.
  • an instantaneous value, an average value, a variance value, or a median value obtained by a plurality of first feature quantities FA1 can be used.
  • a value obtained by combining any two or more of these values can be used.
  • various statistics can be used for the second statistic S2.
  • an instantaneous value, an average value, a variance value, or a median value obtained by a plurality of second feature quantities FA2 can be used.
  • a value obtained by combining any two or more of these values can be used.
  • a coordinate system having a first axis corresponding to the first statistic S1 and having a second axis corresponding to the second statistic S2 is referred to as a "feature amount coordinate system".
  • the height determination unit 53 is preset with threshold values S_th_1 and S_th_2 in the feature coordinate system.
  • FIG. 20 shows an example of the threshold values S_th_1 and S_th_2.
  • the threshold value S_th_1 corresponds to the threshold value H_th_1 related to the discrimination between the road surface obstacle and the road obstacle.
  • the threshold value S_th_2 corresponds to the threshold value H_th_2 related to the discrimination between the road obstacle and the traveling obstacle.
  • the height determination unit 53 plots the statistics S1 and S2 corresponding to the individual reflection point cloud PGs in the feature coordinate system.
  • the height determination unit 53 determines that the corresponding obstacle O is a road surface obstacle.
  • the height determination unit 53 determines that the corresponding obstacle O is a road obstacle.
  • the plotted statistics S1 and S2 are included in the range R_3 of the threshold value S_th_2 or more, the height determination unit 53 determines that the corresponding obstacle O is a traveling obstacle.
  • the height determination unit 53 determines that the corresponding obstacle O is a road surface obstacle. Determine. Further, when the statistics S1-2 and S2_2 corresponding to the other one reflection point group PG are included in the range R_2 (see FIG. 20), the height determination unit 53 indicates that the corresponding obstacle O is a road obstacle. To determine. Further, when the statistics S1_3 and S2_3 corresponding to the other one reflection point group PG are included in the range R_3 (see FIG. 20), the height determination unit 53 indicates that the corresponding obstacle O is a traveling obstacle. To determine.
  • the width determination unit 51 determines that a certain obstacle O is a wide obstacle, and the height determination unit 53 determines that it is a road obstacle. In this case, the identification unit 15 identifies that the obstacle O is a curb. If not, the identification unit 15 identifies that the obstacle O is not a curb.
  • the identification unit 15 determines that the obstacle O is a parking obstacle. If not, the identification unit 15 identifies that the obstacle O is not a parking obstacle.
  • the identification unit 15 identifies that the traveling obstacle is a parking obstacle.
  • the width determination unit 51 determines that the first obstacle O is a wide obstacle, and the height determination unit 53 determines that it is a road obstacle or a road surface obstacle. Further, it is assumed that the width determination unit 51 determines that the second obstacle O is a narrow obstacle. Further, it is assumed that the position determination unit 52 determines that the second obstacle O is located behind the first obstacle O.
  • the identification unit 15 identifies that the first obstacle O is not a parking obstacle and that the second obstacle O is a parking obstacle. In other words, the identification unit 15 identifies the second obstacle O as a parking obstacle regardless of the determination result of the height H of the second obstacle O by the height determination unit 53.
  • the accuracy of determining the height H by the height determining unit 53 may decrease due to the small number of corresponding reflection point RPs.
  • a narrow obstacle located on the back side of a curb or a step is likely to be a traveling obstacle (for example, a utility pole, a pole, or a signboard). Therefore, the identification unit 15 identifies the second obstacle O as a parking obstacle regardless of the determination result of the height H.
  • the width determination unit 51 determines that the first obstacle O is a wide obstacle. Further, it is assumed that the position determination unit 52 determines that the second obstacle O is located behind the first obstacle O.
  • the identification unit 15 identifies that the first obstacle O is not a parking obstacle. In other words, the identification unit 15 identifies that the first obstacle O is not a parking obstacle, regardless of the determination result of the height H of the first obstacle O by the height determination unit 53.
  • the traveling obstacle usually has a height H larger than the mounting height of the distance measuring sensor 2 in the vehicle 1. Therefore, when there is another obstacle behind the wide obstacle and the wide obstacle is a traveling obstacle, the reflected wave from the other obstacle is received by the distance measuring sensor 2. It is considered that there is no such thing. Therefore, the identification unit 15 identifies the first obstacle O as not being a parking obstacle regardless of the determination result of the height H.
  • the distance d_Y between reflection points in the Y direction between two obstacles O is determined according to the position of the two obstacles O in the real space.
  • the distance d_X between the reflection points in the X direction of each obstacle O is determined according to the speed V of the vehicle 1, and the time interval ⁇ T at which the exploration wave is transmitted by the distance measuring sensor 2. It is decided according to. That is, the lower the speed V of the vehicle 1, the smaller the distance d_X between the reflection points, and the denser the arrangement of the reflection points RP in the X direction. On the other hand, the higher the speed V of the vehicle 1, the larger the distance d_X between the reflection points, so that the arrangement of the reflection points RP in the X direction becomes sparse.
  • the shorter the time interval ⁇ T the smaller the distance d_X between the reflection points, and the denser the arrangement of the reflection points RP in the X direction.
  • the time interval ⁇ T becomes larger, the distance d_X between the reflection points becomes larger, so that the arrangement of the reflection points RP in the X direction becomes sparse.
  • the distance d_Y between the reflection points between the reflection points RP_3_1 and RP_4_1 depends on the position of the obstacles O_3 and O_4 in the real space. It is fixed.
  • the distance d_X between the reflection points between the reflection points RP_3_1 and RP_3_2, that is, the distance d_X between the reflection points between the reflection points RP_4_1 and RP_4_2 is determined according to the velocity V and according to the time interval ⁇ T. It is decided.
  • the distance between the reflection points d_X may be larger than the distance d_Y between the reflection points, as shown in FIG.
  • the distance between reflection points d_Y may be smaller than the distance between reflection points d_X.
  • the grouping unit in the conventional obstacle detection device includes the two reflection point RPs in the same reflection point group PG for each of the two reflection point RPs adjacent to each other when the distance d between the reflection points is small.
  • the two reflection point RPs are included in the reflection point group PGs different from each other.
  • the reflection points RP_3_1 and RP_3_2 and the reflection points RP_1 and RP_4_2 may be included in the same reflection point group PG due to the small distance d_Y between the reflection points. It was. Further, since the distance d_X between the reflection points is large, the reflection point RP_3_1 and the reflection point RP_3_2 are included in the reflection point group PG different from each other, and the reflection point RP_1 and the reflection point RP_4_2 are included in the reflection point group PG different from each other. There was a problem that there was something. That is, there is a problem that the reflection point group PG corresponding to each obstacle O cannot be set accurately.
  • the grouping unit 14 in the obstacle detection device 100 sets the reflection point group PG by executing the peak separation processing for each of the frequency distributions FD_Y and FD_X in each analysis region AA as described above. To do.
  • the reflection point cloud group PG corresponding to each obstacle O can be accurately set in each analysis region AA.
  • two reflection point cloud group PGs corresponding to two obstacles O_3 and O_4 can be set one-to-one.
  • the reflection point group PG corresponding to the curb and the reflection point corresponding to the parking obstacle A group PG can be set.
  • the reflection point group setting process it is preferable to use a plurality of reflection point RPs corresponding to the first wave to the Nth wave. As a result, the reflection point cloud group PG corresponding to each obstacle O can be set more accurately.
  • the discontinuous portion detection unit 12 may use the distance d between the reflection points in the plurality of reflection point RPs corresponding to the nth wave for the discontinuous portion detection process. That is, the discontinuous portion detection unit 12 replaces the plurality of reflection point RPs corresponding to the first wave with the plurality of reflection point RPs corresponding to the second wave or the plurality of reflection points corresponding to the third wave. The distance d between reflection points in the RP may be used for the discontinuous portion detection process.
  • the obstacle O_6 is composed of, for example, a step.
  • square marks ( ⁇ ) indicate individual reflection point RPs corresponding to the third wave.
  • the discontinuous portions DP_1 and DP_2 may not be detected.
  • two discontinuous portions DP_1 and DP_2 can be detected by using the distance d between the reflection points in the plurality of reflection point RPs corresponding to the second wave. Therefore, it is preferable to use the distance d between the reflection points in the plurality of reflection point RPs corresponding to the second wave.
  • the discontinuous portion detection unit 12 uses each of the first wave to the Nth wave instead of using the distance d between the reflection points in the plurality of reflection point RPs corresponding to the nth wave for the discontinuous portion detection process.
  • the distance d between the reflection points in the plurality of reflection point RPs corresponding to the above may be used for the discontinuous portion detection process. As a result, the discontinuous portion DP can be detected more reliably.
  • the discontinuous part detection process is not limited to the one based on the first condition.
  • the discontinuous portion detecting unit 12 may detect the discontinuous portion DP as follows.
  • FIG. 23A there are five obstacles O_1 to O_4 and O_6 in the lateral region LA.
  • a plurality of reflection points RP_1, RP_2, RP_3, RP_4, RP_6 corresponding to the obstacle group OG are detected.
  • the nine reflection points RP_1 corresponding to the obstacle O_1 the nine reflection points RP_2 corresponding to the obstacle O_2, the twelve reflection points RP_3 corresponding to the obstacle O_3, and the obstacle O_4.
  • the corresponding four reflection points RP_4 and the 26 reflection points RP_6 corresponding to the obstacle O_6 are detected.
  • the discontinuous unit detection unit 12 calculates the variance value s in one or more distance measurement values D corresponding to each transmitted wave.
  • the discontinuous unit detection unit 12 calculates the amount of change ⁇ s of the calculated variance value s by performing time differentiation with respect to the calculated variance value s.
  • FIG. 23B shows an example of the variance value s with respect to time.
  • FIG. 23C shows an example of the amount of change ⁇ s with respect to time.
  • the time axis corresponds to the X axis.
  • the discontinuous unit detection unit 12 detects the discontinuous unit DP when the following conditions (hereinafter referred to as “second condition”) are satisfied for the calculated change amount ⁇ s. That is, the second condition is that the amount of change ⁇ s exceeds a predetermined threshold value ⁇ s_th.
  • the variance value s of the distance measurement value D corresponding to the reflected wave (including the first wave and the second wave) by the obstacles O_6 and O_1 is the reflected wave (third) by the obstacles O_6 and O_3.
  • the waves reflected by obstacles O_6, O_3, and O_4 (the first wave, the second wave, and the third wave) that are smaller than the variance value s of the ranging value D corresponding to the first wave and the second wave). It is smaller than the variance value s of the ranging value D corresponding to).
  • the dispersion value s of the ranging value D corresponding to the reflected wave (including the first wave and the second wave) by the obstacles O_6 and O_2 is the reflected wave (the first wave and the second wave) by the obstacles O_6 and O_3. It is smaller than the variance value s of the ranging value D corresponding to (including waves), and corresponds to the reflected waves (including the first wave, the second wave, and the third wave) by the obstacles O_6, O_3, and O_4. It is smaller than the variance value s of the distance measurement value D to be measured.
  • the second condition is satisfied at time t_1, and one discontinuous portion DP_1 is detected. Then, at time t_2, the second condition is satisfied and one discontinuous portion DP_2 is detected. That is, two discontinuous portions DP_1 and DP_2 are detected.
  • the dispersion value s may be the dispersion value of the ranging value D corresponding to all of the first wave to the Nth wave, or any two or more of the first wave to the Nth wave. It may be a variance value of the ranging value D corresponding to n waves. However, from the viewpoint of more reliably including the distance measurement value D corresponding to the reflected wave due to the obstacle O having a small height H (for example, a curb or a step) in the calculation of the dispersion value s, all of the first wave to the Nth wave. It is more preferable to use the variance value of the ranging value D corresponding to.
  • the discontinuous part detection process is not limited to the one based on the first condition or the second condition.
  • the discontinuous portion detecting unit 12 may detect the discontinuous portion DP as follows.
  • the discontinuous portion detection unit 12 has a plurality of sets of reflection point coordinate values calculated by the obstacle detection unit 11 from the time when the immediately preceding discontinuous portion DP is detected to the present time (hereinafter, "first reflection point"). It may be referred to as "coordinate value”.)
  • first reflection point a reflection point coordinate value calculated by the obstacle detection unit 11 from the time when the immediately preceding discontinuous portion DP is detected to the present time. It may be referred to as "coordinate value”.
  • a regression line or a regression curve in the XY coordinate system is calculated.
  • the regression curve is, for example, an arc-shaped or parabolic-shaped curve.
  • Various known techniques eg, least squares method
  • the discontinuous portion detection unit 12 includes the calculated regression line or regression curve, and at least one set of reflection point coordinate values newly calculated by the obstacle detection unit 11 (hereinafter, “second reflection point coordinate value”). In some cases, the distances from C_X and C_Y are calculated. The discontinuous unit detection unit 12 compares the calculated distance with a predetermined threshold value. When the calculated distance exceeds the threshold value, the discontinuous unit detecting unit 12 detects the time point corresponding to this distance as the discontinuous unit DP.
  • the threshold value is set to, for example, a constant multiple of the so-called “residual distribution".
  • the residual distribution indicates the degree of variation in the distribution of a plurality of sets of first reflection point coordinate values C_X and C_Y around the regression line or the regression curve.
  • the regression line or the regression curve corresponds to the uncalculated predicted values of the second reflection point coordinate values C_X and C_Y based on the continuity of the calculated first plurality of reflection point coordinate values C_X and C_Y. .. Further, the distance between the regression line or the regression curve and the second reflection point coordinate values C_X and C_Y corresponds to the residual related to the predicted value.
  • the discontinuous unit detection unit 12 satisfies the condition that the value indicating the residual value related to the predicted value (hereinafter referred to as “residual value”) exceeds a predetermined threshold value (hereinafter referred to as “third condition”).
  • residual value the value indicating the residual value related to the predicted value
  • third condition a predetermined threshold value
  • the discontinuous unit detection unit 12 may detect the discontinuous unit DP when the first condition and the second condition are satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when the first condition and the third condition are satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when the second condition and the third condition are satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when the first condition, the second condition, and the third condition are satisfied. That is, the discontinuous portion detecting unit 12 may detect the discontinuous portion DP under a plurality of conditions.
  • the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the first condition and the second condition is satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the first condition and the third condition is satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the second condition and the third condition is satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the first condition, the second condition, and the third condition is satisfied. That is, the discontinuous portion detecting unit 12 may detect the discontinuous portion DP under a plurality of conditions.
  • the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least two of the first condition, the second condition, and the third condition are satisfied. That is, the discontinuous portion detecting unit 12 may detect the discontinuous portion DP based on the result of majority voting under a plurality of conditions.
  • the detection accuracy of the discontinuous portion DP can be improved.
  • the discontinuous part DP can be detected accurately.
  • the analysis region extraction unit 13 When a predetermined time or a predetermined distance elapses in a state where the discontinuous portion DP is not detected by the discontinuous portion detecting unit 12, the analysis region extraction unit 13 newly divides the side region LA regardless of the discontinuous portion DP.
  • the analysis area AA may be set. In other words, the analysis area extraction unit 13 may divide the one analysis area AA into a plurality of analysis areas AA when the width of one analysis area AA exceeds a predetermined width. ..
  • the predetermined width is set to, for example, a value about twice the width of the parking space for the vehicle 1.
  • the analysis area extraction unit 13 is a discontinuous unit.
  • a new analysis area AA may be set by dividing the side area LA regardless of the DP.
  • the analysis area extraction unit 13 converts the one analysis area AA into a plurality of analysis areas AA. It may be divided.
  • the subsequent processing that is, the analysis area extraction processing, the grouping processing, the identification processing and the output processing
  • the discontinuous portion DP can be executed. Parking assistance control can be performed.
  • the amount of reflection point information corresponding to each analysis region AA can be reduced. As a result, it is possible to reduce the size of the storage area for reflection point information corresponding to each analysis area AA.
  • the identification unit 15 determines whether the individual obstacle O is a low-profile obstacle. It may be used to determine whether it is a tall obstacle.
  • the threshold value S_th_3 in the feature amount coordinate system is preset in the height determination unit 53.
  • FIG. 24 shows an example of the threshold value S_th_3.
  • the threshold value S_th_3 corresponds to the threshold value H_th_3 related to the discrimination between the low-back obstacle and the high-back obstacle.
  • the height determination unit 53 plots the statistics S1 and S2 corresponding to the individual reflection point cloud PGs in the feature coordinate system.
  • the height determination unit 53 determines that the corresponding obstacle O is a low-profile obstacle.
  • the height determination unit 53 determines that the corresponding obstacle O is a tall obstacle.
  • the height determination unit 53 indicates that the corresponding obstacle O is a low-profile obstacle. To determine. Further, when the statistics S1_5 and S2_5 corresponding to the other one reflection point group PG are included in the range R_5 (see FIG. 24), the height determination unit 53 indicates that the corresponding obstacle O is a tall obstacle. Determine if there is.
  • the exploration wave may be reflected multiple times between the obstacle O and the vehicle 1.
  • so-called “multiple reflected waves” may be received.
  • the reflection point RP corresponding to the multiple reflected wave is a so-called “virtual image”.
  • the imaginary image has a Y coordinate value C_Y corresponding to a value obtained by an integral multiple of 2 or more with respect to the distance between the obstacle O and the vehicle 1. It is preferable that the imaginary image is excluded from the target of the identification process.
  • the identification unit 15 has a Y coordinate value C_Y corresponding to a value obtained by an integral multiple of 2 or more with respect to the distance between the wide obstacle and the vehicle 1 for the wide obstacle located on the foremost side with respect to the vehicle 1.
  • the reflection point cloud group PG may be excluded from the target of the identification process. As a result, the virtual image based on the multiple reflected waves can be excluded from the target of the identification process.
  • the output unit 16 obtains information about the parking obstacle from the identification result signal. It may be excluded. In other words, when the parking obstacle is located behind the curb, the output unit 16 outputs information about the parking obstacle only when the distance between the curb and the parking obstacle is less than or equal to a predetermined distance. It may be included in the identification result signal.
  • the parking support system 300 may include a plurality of distance measuring sensors instead of one distance measuring sensor 2. That is, the plurality of distance measuring sensors may be provided on each of the left side portion of the vehicle 1, the right side portion of the vehicle 1, or the left side portion of the vehicle 1 and the right side portion of the vehicle 1.
  • the first statistic S1 is a plurality of first feature quantities related to the plurality of transmissions / receptions when a plurality of transmissions / receptions are realized by one or more transmissions / receptions by each of the plurality of distance measuring sensors. It may be a statistic based on FA1. Further, the second statistic S2 may be a statistic based on a plurality of second feature quantities FA2 related to the transmission / reception of the plurality of times.
  • the obstacle detection device 100 uses the distance measuring sensor 2 provided in the vehicle 1 to detect the obstacle group OG in the lateral region LA with respect to the moving vehicle 1 together with the obstacle detection unit 11.
  • the discontinuous part detection unit 12 that detects the discontinuous part DP in the obstacle group OG
  • the analysis area extraction unit 13 that extracts the analysis area AA based on the discontinuous part DP
  • a plurality of reflection point RPs in the analysis area AA By analyzing the frequency distributions FD_Y and FD_X related to the above, a grouping unit 14 for setting a plurality of reflection point group PGs corresponding to a plurality of obstacles O included in the obstacle group OG, and a plurality of obstacles.
  • the distance between the curb and the parking obstacle is predetermined with the identification unit 15 that identifies whether each of the O's is a curb or not and whether each of the plurality of obstacles O is a parking obstacle. It includes an output unit 16 that outputs at least a signal (identification result signal) indicating the position of a parking obstacle when the distance is less than or equal to the distance.
  • the reflection point group PG corresponding to the curb and the reflection point group PG corresponding to the parking obstacle can be set. Can be done. As a result, at least a signal indicating the position of the parking obstacle (identification result signal) can be output.
  • the discontinuous portion detection unit 12 detects the discontinuous portion DP when the first condition is satisfied, and the first condition is between the reflection points in the plurality of reflection point RPs corresponding to the nth wave.
  • the distance d is calculated, it is a condition that the calculated distance d between reflection points exceeds the threshold value d_th.
  • the discontinuous unit detection unit 12 detects the discontinuous unit DP when the second condition is satisfied, and the second condition is in one or more distance measurement values D corresponding to each transmitted wave.
  • the variance value s is calculated, it is a condition that the calculated change amount ⁇ s exceeds the threshold value ⁇ s_th when the change amount ⁇ s of the calculated dispersion value s is calculated.
  • the discontinuous portion detecting unit 12 detects the discontinuous portion DP when the third condition is satisfied, and the third condition is the continuity in the calculated reflection point coordinate values C_X and C_Y.
  • the calculated residual value I is a condition that exceeds the threshold value.
  • the discontinuous portion detecting unit 12 detects the discontinuous portion DP when at least one of the first condition and the second condition is satisfied, and the first condition is a plurality of corresponding nth waves.
  • the condition is that the calculated distance d between the reflection points exceeds the threshold value d_th
  • the second condition is 1 corresponding to each transmitted wave.
  • the dispersion value s for more than one distance measurement value D is calculated, when the change amount ⁇ s of the calculated dispersion value s is calculated, the calculated change amount ⁇ s exceeds the threshold value ⁇ s_th. is there.
  • the discontinuous portion detecting unit 12 detects the discontinuous portion DP when the first condition and the third condition are satisfied, and the first condition is a plurality of reflection point RPs corresponding to the nth wave.
  • the condition is that the calculated distance d between the reflection points exceeds the threshold value d_th
  • the third condition is the calculated plurality of sets of reflection point coordinate values C_X and C_Y.
  • the predicted value of at least one set of uncalculated reflection point coordinate values C_X and C_Y is calculated based on the continuity in, and the residual value related to the calculated predicted value is calculated, the calculated value is calculated.
  • the condition is that the residual value exceeds the threshold value.
  • the discontinuous unit detecting unit 12 detects the discontinuous unit DP when at least one of the second condition and the third condition is satisfied, and the second condition corresponds to each transmission wave.
  • the condition that the calculated change amount ⁇ s exceeds the threshold value ⁇ s_th when the change amount ⁇ s of the calculated variance value s is calculated.
  • the third condition is that when the predicted values of at least one set of uncalculated reflection point coordinate values C_X and C_Y are calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values C_X and C_Y.
  • the residual value related to the calculated predicted value it is a condition that the calculated residual value exceeds the threshold value.
  • the discontinuous portion detecting unit 12 detects the discontinuous portion DP when at least one of the first condition, the second condition and the third condition is satisfied, and the first condition is the nth wave.
  • the condition is that the calculated distance d between the reflection points exceeds the threshold value d_th
  • the second condition is the transmitted wave of each time.
  • the dispersion value s in one or more distance measurement values D corresponding to is calculated, when the change amount ⁇ s of the calculated dispersion value s is calculated, the calculated change amount ⁇ s sets the threshold value ⁇ s_th.
  • the third condition is that the predicted values of at least one set of uncalculated reflection point coordinate values C_X and C_Y are calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values C_X and C_Y.
  • the residual value related to the calculated predicted value it is a condition that the calculated residual value exceeds the threshold value.
  • the analysis area extraction unit 13 divides the analysis area AA into a plurality of analysis areas AA when the calculated number of the distance measurement values D corresponding to the analysis area AA exceeds a predetermined number. As a result, the amount of reflection point information corresponding to each analysis region AA can be reduced. As a result, it is possible to reduce the size of the storage area for reflection point information corresponding to each analysis area AA.
  • Embodiment 2 Normally, when the parking support system 300 searches for a parking space, the vehicle 1 moves in a direction along the longitudinal direction of a wide obstacle (for example, a curb or a step). Therefore, the arrangement direction of the plurality of reflection point RPs corresponding to the wide obstacle (hereinafter referred to as “reflection point arrangement direction”) is parallel or substantially parallel to the moving direction of the vehicle 1. That is, the reflection point arrangement direction is parallel to or substantially parallel to the X-axis.
  • parallel or substantially parallel is simply referred to as "parallel”.
  • FIG. 25 shows an example of a plurality of reflection points RP_3 and RP_4 corresponding to a plurality of obstacles O_3 and O_4 in one analysis region AA_2 in such a state.
  • the first analysis unit 41 creates a frequency distribution FD_Y related to a plurality of reflection points RP_3 and RP_4 in the analysis region AA_2.
  • FIG. 26 shows an example of the frequency distribution FD_Y.
  • the frequency distribution FD_Y includes frequencies (F_Y in the figure) corresponding to a plurality of reflection points RP_3 and RP_4.
  • the first analysis unit 41 executes peak separation processing for the frequency distribution FD_Y. As a result, one frequency group FG_Y corresponding to the plurality of reflection points RP_3 and RP_4 is set.
  • the second analysis unit 42 creates a frequency distribution FD_X related to a plurality of reflection points RP_3 and RP_4 corresponding to the frequency group FG_Y.
  • FIG. 27 shows an example of the frequency distribution FD_X.
  • the frequency distribution FD_X includes frequencies (F_X in the figure) corresponding to a plurality of reflection points RP_3 and RP_4.
  • the second analysis unit 42 executes peak separation processing for the frequency distribution FD_X. As a result, one frequency group FG_X corresponding to the plurality of reflection points RP_3 and RP_4 is set.
  • the grouping unit 14 sets one reflection point group PG corresponding to the frequency group FG_Y and the frequency group FG_X. As a result, as shown in FIG. 25, one reflection point group PG corresponding to the two obstacles O_3 and O_4 is set.
  • the obstacle detection device is intended to solve such a problem.
  • FIG. 28 is a block diagram showing a main part of the parking support system including the obstacle detection device according to the second embodiment.
  • FIG. 29 is a block diagram showing a main part of the grouping unit in the obstacle detection device according to the second embodiment. The obstacle detection device according to the second embodiment will be described with reference to FIGS. 28 and 29.
  • FIG. 28 the same blocks as those shown in FIG. 1 are designated by the same reference numerals, and the description thereof will be omitted. Further, in FIG. 29, the same blocks as those shown in FIG. 3 are designated by the same reference numerals, and the description thereof will be omitted.
  • the vehicle 1 has a distance measuring sensor 2, an obstacle detection device 100a, and a parking support device 200.
  • the distance measuring sensor 2, the obstacle detection device 100a, and the parking support device 200 constitute a main part of the parking support system 300a.
  • the obstacle detection device 100a includes an obstacle detection unit 11, a discontinuous unit detection unit 12, an analysis area extraction unit 13, a grouping unit 14a, an identification unit 15, and an output unit 16.
  • the grouping unit 14a has a first analysis unit 41, a second analysis unit 42, and a correction unit 43.
  • the correction unit 43 sets the individual reflection point coordinate values C_X and C_Y included in the reflection point information acquired by the grouping unit 14a. By correcting, the reflection point arrangement direction is made parallel to the moving direction of the vehicle 1. A specific example of the correction method by the correction unit 43 will be described with reference to FIGS. 31 and 32.
  • the first analysis unit 41 uses the Y coordinate value C_Y corrected by the correction unit 43 to create the frequency distribution FD_Y. Further, the second analysis unit 42 uses the X coordinate value C_X corrected by the correction unit 43 to create the frequency distribution FD_X.
  • grouping processes the processes executed by the grouping unit 14a may be collectively referred to as "grouping processes". That is, the grouping process executed by the grouping unit 14a corrects the individual reflection point coordinate values C_X and C_Y in addition to the same processing as the processing included in the grouping process executed by the grouping unit 14. It includes processing and so on.
  • each function of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14a, the identification unit 15, and the output unit 16 is realized by the processor 61 and the memory 62. It may be present, or it may be realized by a dedicated processing circuit 63.
  • the operation of the parking support system 300a will be described focusing on the operations of the obstacle detection device 100a and the parking support device 200.
  • the same steps as those shown in FIG. 9 are designated by the same reference numerals, and the description thereof will be omitted.
  • step ST4a the grouping unit 14a executes the grouping process.
  • steps ST5 to ST7 are executed.
  • the correction unit 43 sets a straight line (hereinafter referred to as "reference straight line”) SL_ref parallel to the X axis. Further, the correction unit 43 detects the straight line SL along the reflection point arrangement direction by using the reflection point information acquired by the grouping unit 14a. Next, the correction unit 43 calculates the angle ⁇ of the straight line SL with respect to the reference straight line SL_ref.
  • the correction unit 43 obtains the reflection point positions so that the positions of all the reflection point RPs in the corresponding analysis region AA rotate at a rotation angle ( ⁇ ) corresponding to the calculated angle ⁇ .
  • the individual reflection point coordinate values C_X and C_Y included in the information are corrected.
  • the rotation it is possible to realize a state in which the reflection point arrangement direction is parallel to the moving direction of the vehicle 1.
  • any point in the XY coordinate system can be used as the center of the rotation.
  • the center of rotation is shared by all reflection point RPs in the corresponding analysis region AA.
  • the correction unit 43 may detect the straight line SL by executing the straight line detection using the Hough transform on the plurality of reflection point RPs in the corresponding analysis region AA.
  • the correction unit 43 may detect the straight line SL by executing the straight line detection using the RANSAC (Random Sample Consensus) algorithm.
  • RANSAC Random Sample Consensus
  • M is an arbitrary integer of 2 or more.
  • the correction unit 43 indicates the number of reflection point RPs with respect to the Y coordinate value C_Y in a state where the positions of all reflection point RPs in the corresponding analysis region AA are rotated at a rotation angle ( ⁇ _1) corresponding to the angle ⁇ _1. Create a frequency distribution FD_ ⁇ _1. Further, the correction unit 43 has the number of reflection point RPs with respect to the Y coordinate value C_Y in a state where the positions of all reflection point RPs in the corresponding analysis region AA are rotated at a rotation angle ( ⁇ _2) corresponding to the angle ⁇ _2. Create a frequency distribution FD_ ⁇ _2 showing.
  • the correction unit 43 creates frequency distributions FD_ ⁇ _3 to FD_ ⁇ _M corresponding to the rotation angles ( ⁇ _3 to ⁇ _M), respectively. As a result, M frequency distributions FD_ ⁇ _1 to FD_ ⁇ _M are created.
  • any point in the XY coordinate system can be used as the center of the rotation.
  • the center of rotation is shared by all reflection point RPs in the corresponding analysis region AA.
  • the correction unit 43 calculates the maximum value F_max in each of the created frequency distributions FD_ ⁇ _1 to FD_ ⁇ _M. As a result, M maximum values F_max_1 to F_max_M corresponding to M frequency distributions FD_ ⁇ _1 to FD_ ⁇ _M on a one-to-one basis are calculated.
  • the correction unit 43 selects the largest value among the M maximum values F_max_1 to F_max_M.
  • the correction unit 43 selects an angle ⁇ corresponding to the selected value among the M angles ⁇ _1 to ⁇ _M.
  • the correction unit 43 obtains the reflection point positions so that the positions of all the reflection point RPs in the corresponding analysis region AA rotate at a rotation angle ( ⁇ ) corresponding to the selected angle ⁇ .
  • the individual reflection point coordinate values C_X and C_Y included in the information are corrected.
  • the angles ⁇ _1 to ⁇ _M may be set to different values. In other words, each of the angles ⁇ _1 to ⁇ _M may be set to any value. However, it is more preferable that the angles ⁇ _1 to ⁇ _M are set to the following values.
  • the angles ⁇ _1 to ⁇ _M are preferably set to values obtained by dividing the angle range ⁇ of the lower limit value ⁇ _min or more and the upper limit value ⁇ _max or less into M equal parts.
  • the lower limit value ⁇ _min is a value based on the following equation (1).
  • the upper limit value ⁇ _max is a value based on the following equation (2).
  • ⁇ _min ⁇ c ⁇ ( ⁇ w / 2) (1)
  • ⁇ _max ⁇ c + ( ⁇ w / 2) (2)
  • this is in consideration of not irradiating the obstacle O in the angle range below the lower limit value ⁇ _min with the exploration wave. Further, this is in consideration of not irradiating the obstacle O in the angle range exceeding the upper limit value ⁇ _max with the exploration wave.
  • the obstacle detection device 100a can employ various modifications similar to those described in the first embodiment. Further, the parking support system 300a can adopt various modifications similar to those described in the first embodiment.
  • the grouping unit 14a corrects the individual reflection point coordinate values C_X and C_Y so that the reflection point arrangement direction is parallel to the movement direction of the vehicle 1.
  • the reflection point cloud group PG corresponding to each obstacle O can be set regardless of the course of the vehicle 1.
  • FIG. 33 is a block diagram showing a main part of the parking support system including the obstacle detection device according to the third embodiment.
  • FIG. 34 is a block diagram showing a main part of the identification unit in the obstacle detection device according to the third embodiment. The obstacle detection device according to the third embodiment will be described with reference to FIGS. 33 and 34.
  • FIG. 33 the same blocks as those shown in FIG. 1 are designated by the same reference numerals, and the description thereof will be omitted.
  • FIG. 34 the same blocks as those shown in FIG. 4 are designated by the same reference numerals, and the description thereof will be omitted.
  • the vehicle 1 has a distance measuring sensor 2, an obstacle detection device 100b, and a parking support device 200a.
  • the distance measuring sensor 2, the obstacle detection device 100b, and the parking support device 200a constitute a main part of the parking support system 300b.
  • the obstacle detection device 100b includes an obstacle detection unit 11, a discontinuous unit detection unit 12, an analysis area extraction unit 13, a grouping unit 14, an identification unit 15a, and an output unit 16.
  • the parking support device 200a has a parking support control unit 21a.
  • the identification unit 15a has a width determination unit 51, a position determination unit 52, a height determination unit 53, and a movement determination unit 54.
  • the motion determination unit 54 determines whether or not each obstacle O identified as a parking obstacle by the identification unit 15a is a dynamic obstacle by using the reflection point information acquired by the identification unit 15a. It is something to do. A specific example of the determination method by the motion determination unit 54 will be described later.
  • the processes executed by the identification unit 15a may be collectively referred to as "identification processing". That is, the identification process executed by the identification unit 15a determines whether or not each parking obstacle is a dynamic obstacle, in addition to the same process as the process included in the identification process executed by the identification unit 15. It includes the process of making a judgment.
  • the output unit 16 outputs a signal indicating the result of the identification process, that is, the identification result signal to the parking support control unit 21a.
  • the identification result signal in the third embodiment includes information indicating whether or not each obstacle O is a curb, information indicating whether or not each obstacle O is a parking obstacle, and individual obstacles.
  • the information indicating whether or not each parking obstacle is a dynamic obstacle is included.
  • the parking support control unit 21a executes parking support control similar to the parking support control executed by the parking support control unit 21. That is, the parking support control unit 21a executes control for realizing automatic parking, for example.
  • the parking support control unit 21a executes a control for sounding the horn of the vehicle 1 and excludes the dynamic obstacle from the target of avoidance in automatic parking. It has become.
  • This utilizes the fact that the dynamic obstacle usually includes a human being, but when the vehicle 1 sounds a horn, it is highly probable that the dynamic obstacle portion moves so as to avoid the vehicle 1. As a result, it is possible to prevent the vehicle 1 from making unnecessary avoidance in automatic parking.
  • each function of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15a, and the output unit 16 is realized by the processor 61 and the memory 62. It may be present, or it may be realized by a dedicated processing circuit 63.
  • the hardware configuration of the main part of the parking support device 200a is the same as that described with reference to FIGS. 7 and 8 in the first embodiment. Therefore, illustration and description will be omitted. That is, the function of the parking support control unit 21a may be realized by the processor 71 and the memory 72, or may be realized by the dedicated processing circuit 73.
  • FIG. 35 the operation of the parking support system 300b will be described focusing on the operations of the obstacle detection device 100b and the parking support device 200a.
  • the same steps as those shown in FIG. 9 are designated by the same reference numerals, and the description thereof will be omitted.
  • step ST5a the process of step ST6 is executed.
  • step ST7a the parking support control
  • the motion determination unit 54 executes frequency analysis on the waveform of the received signal RS corresponding to each reflection point RP by using the waveform information included in the reflection point information corresponding to each reflection point RP. As a result, the first Doppler shift amount is calculated. Next, the motion determination unit 54 subtracts the component due to the movement of the vehicle 1 from the calculated first Doppler shift amount. As a result, the second Doppler shift amount is calculated. At this time, the component due to the movement of the vehicle 1 is calculated using the vehicle speed information.
  • the vehicle speed information is, for example, acquired by the obstacle detection device 100b by CAN communication.
  • the first Doppler shift amount is the Doppler shift amount based on the relative movement of the corresponding obstacle O with respect to the vehicle 1.
  • the second Doppler shift amount is a Doppler shift amount based on the absolute movement of the corresponding obstacle O.
  • the motion determination unit 54 calculates the moving speed of the corresponding obstacle O based on the calculated second Doppler shift amount and the speed of sound at the time when the corresponding reflected wave is received.
  • the speed of sound at that time is calculated using information indicating the temperature outside the vehicle at that time (hereinafter referred to as "temperature information”) and information indicating humidity outside the vehicle at that time (hereinafter referred to as “humidity information").
  • temperature information information indicating the temperature outside the vehicle at that time
  • humidity information information indicating humidity outside the vehicle at that time.
  • the temperature information and humidity information are, for example, acquired by the obstacle detection device 100b by CAN communication.
  • the motion determination unit 54 compares the calculated movement speed with a predetermined threshold value. When the movement speed is larger than the threshold value, the movement determination unit 54 determines that the corresponding obstacle O is a dynamic obstacle. If not, the motion determination unit 54 determines that the corresponding obstacle O is not a dynamic obstacle.
  • the received signal waveform corresponding to the dynamic obstacle has a plurality of peak portions P in the judgment time window (hereinafter referred to as “judgment window”) JW having a predetermined width w. That is, the received signal waveform corresponding to the dynamic obstacle has a substantially forest-like peak portion P.
  • FIG. 36 shows an example of a received signal waveform having three peak portions P_1, P_2, and P_3 in the determination window JW.
  • the width w is set to a value corresponding to, for example, the threshold value W_th_1 for identification of a narrow obstacle.
  • the surface shape of a static obstacle (for example, a utility pole, pole or signboard) is simpler than the surface shape of a dynamic obstacle (for example, a pedestrian). Therefore, the received signal waveform corresponding to the static obstacle has one peak portion P in the determination window JW. That is, the received signal waveform corresponding to the static obstacle has a substantially plate-shaped peak portion P.
  • FIG. 37 shows an example of a received signal waveform having one peak portion P in the determination window JW.
  • the motion determination unit 54 uses the waveform information included in the reflection point information corresponding to each reflection point RP, and the number of peak portions P in the determination window JW in the received signal waveform corresponding to each reflection point EP. Is calculated. When the calculated number is a predetermined number (for example, two) or more, the motion determination unit 54 determines that the corresponding obstacle O is a dynamic obstacle. If not, the motion determination unit 54 determines that the corresponding obstacle O is not a dynamic obstacle.
  • the obstacle detection device 100b can employ various modifications similar to those described in the first embodiment. Further, the parking support system 300b can adopt various modifications similar to those described in the first embodiment.
  • the obstacle detection device 100b may have a grouping unit 14a instead of the grouping unit 14.
  • the obstacle detection device 100b can employ various modifications similar to those described in the second embodiment.
  • the identification unit 15a determines whether or not the parking obstacle is a dynamic obstacle. Thereby, the determination result of whether or not the parking obstacle is a dynamic obstacle can be used for the parking support control. As a result, more appropriate parking support control can be realized.
  • the obstacle detection device of the present invention can be used in a parking support system.

Abstract

An obstacle detection device (100) that comprises an obstacle detection unit (11) that uses a distance measurement sensor (2) that is provided to a vehicle (1) to detect an obstacle group (OG) in a lateral area (A) that is beside the vehicle (1) during movement, a discontinuous part detection unit (12) that detects discontinuous parts (DP) of the obstacle group (OG), an analysis area extraction unit (13) that extracts analysis areas (AA) that are based on the discontinuous parts (DP), a grouping unit (14) that analyzes frequency distributions (FD_Y, FD_X) for pluralities of reflection points (RP) in the analysis areas (AA) and thereby establishes a plurality of reflection point groups (PG) that correspond to a plurality of obstacles (O) that are included in the obstacle group (OG), an identification unit (15) that identifies whether each of the plurality of obstacles (O) is a curb and that also identifies whether each of the plurality of obstacles (O) is a parking obstacle, and an output unit (16) that, when the distance between a curb and a parking obstacle is at or below a prescribed distance, outputs a signal that indicates at least the location of the parking obstacle.

Description

障害物検知装置Obstacle detector
　本発明は、障害物検知装置に関する。 The present invention relates to an obstacle detection device.
　従来、車両に設けられた測距センサを用いて、当該車両に対する周囲の領域における障害物を検知する装置が開発されている。特に、車両が低速度にて移動しているとき、当該車両に対する左方の領域（以下「左方領域」という。）又は当該車両に対する右方の領域（以下「右方領域」という。）における障害物を検知する装置が開発されている。以下、左方領域又は右方領域を総称して「側方領域」という。また、かかる装置を「障害物検知装置」という。 Conventionally, a device for detecting an obstacle in the surrounding area with respect to the vehicle has been developed by using a distance measuring sensor provided in the vehicle. In particular, when the vehicle is moving at a low speed, in the area on the left side of the vehicle (hereinafter referred to as "left area") or the area on the right side of the vehicle (hereinafter referred to as "right area"). Devices for detecting obstacles have been developed. Hereinafter, the left area or the right area is collectively referred to as a “side area”. Further, such a device is called an "obstacle detection device".
　また、従来、障害物検知装置を用いた駐車支援システムが開発されている。すなわち、障害物検知装置による検知結果に基づき、側方領域における駐車用の空間（以下「駐車スペース」という。）が検知される。次いで、当該検知された駐車スペースに対する駐車を支援するための制御（以下「駐車支援制御」という。）が実行される。 Also, conventionally, a parking support system using an obstacle detection device has been developed. That is, a parking space (hereinafter referred to as "parking space") in the lateral region is detected based on the detection result by the obstacle detection device. Next, control for assisting parking with respect to the detected parking space (hereinafter referred to as "parking support control") is executed.
　ここで、特許文献１には、駐車スペースを検知する技術が開示されている。より具体的には、測定ウィンドウ内にて収集された複数の反響信号の分布幅に基づき駐車スペースの奥行き限度を確定する技術が開示されている（例えば、特許文献１の要約参照。）。 Here, Patent Document 1 discloses a technique for detecting a parking space. More specifically, a technique for determining the depth limit of a parking space based on the distribution width of a plurality of reverberant signals collected in the measurement window is disclosed (see, for example, the abstract of Patent Document 1).
国際公開第２００７／０１４５９５号International Publication No. 2007/014595
　駐車支援システムにおいては、駐車スペースを正確に検知すること及び駐車支援制御を正確に実行することが求められる。このため、複数個の障害物が側方領域に存在するとき、障害物検知装置においては、個々の障害物を検知することが求められる。また、個々の障害物の種別を識別すること及び個々の障害物の位置を判断することなどが求められる。 In the parking support system, it is required to accurately detect the parking space and accurately execute the parking support control. Therefore, when a plurality of obstacles are present in the lateral region, the obstacle detection device is required to detect each obstacle. In addition, it is required to identify the type of each obstacle and to determine the position of each obstacle.
　例えば、縁石が側方領域に存在しており、かつ、駐車の妨げとなり得る障害物（以下「駐車障害物」という。）が側方領域に存在している場合において、縁石及び駐車障害物が互いに近接配置されているとき、個々の障害物が縁石であるか駐車障害物であるかを識別することが求められる。また、少なくとも駐車障害物の位置を判断することが求められる。また、当該判断された位置を示す信号を出力することが求められる。 For example, when a curb is present in the lateral area and an obstacle that can interfere with parking (hereinafter referred to as "parking obstacle") is present in the lateral area, the curb and the parking obstacle are present. When placed in close proximity to each other, it is required to identify whether the individual obstacles are curbs or parking obstacles. In addition, it is required to determine at least the position of parking obstacles. Further, it is required to output a signal indicating the determined position.
　ここで、上記のとおり、特許文献１記載の技術は、測定ウィンドウ内にて収集された複数の反響信号の分布幅に基づき駐車スペースの奥行き限度を確定するものである。換言すれば、特許文献１記載の技術は、複数個の障害物が側方領域に存在するとき、個々の障害物を検知するものではない。したがって、複数個の障害物が側方領域に存在するとき、個々の障害物の種別を識別することができない問題があった。また、このとき、個々の障害物の位置を判断することができない問題があった。 Here, as described above, the technique described in Patent Document 1 determines the depth limit of the parking space based on the distribution width of a plurality of echo signals collected in the measurement window. In other words, the technique described in Patent Document 1 does not detect individual obstacles when a plurality of obstacles are present in the lateral region. Therefore, when a plurality of obstacles exist in the lateral region, there is a problem that the type of each obstacle cannot be identified. Further, at this time, there is a problem that the position of each obstacle cannot be determined.
　本発明は、上記のような課題を解決するためになされたものであり、縁石及び駐車障害物が互いに近接配置されているとき、少なくとも駐車障害物の位置を示す信号を出力することができる障害物検知装置を提供することを目的とする。 The present invention has been made to solve the above problems, and when the curb and the parking obstacle are arranged close to each other, at least a signal indicating the position of the parking obstacle can be output. An object of the present invention is to provide an object detection device.
　本発明の障害物検知装置は、車両に設けられた測距センサを用いて、移動中の車両に対する側方領域における障害物群を検知する障害物検知部と、障害物群における非連続部を検知する非連続部検知部と、非連続部に基づく解析領域を抽出する解析領域抽出部と、解析領域における複数個の反射点に係る度数分布を解析することにより、障害物群に含まれる複数個の障害物に対応する複数個の反射点群を設定するグループ化部と、複数個の障害物の各々が縁石であるか否かを識別するとともに、複数個の障害物の各々が駐車障害物であるか否かを識別する識別部と、縁石と駐車障害物間の距離が所定距離以下であるとき、少なくとも駐車障害物の位置を示す信号を出力する出力部と、を備えるものである。 The obstacle detection device of the present invention uses a distance measuring sensor provided in the vehicle to detect an obstacle group in a lateral region with respect to a moving vehicle, and a discontinuous part in the obstacle group. Multiple parts included in the obstacle group by analyzing the discontinuous part detection part to detect, the analysis area extraction part to extract the analysis area based on the discontinuous part, and the frequency distribution related to a plurality of reflection points in the analysis area. A grouping unit that sets a plurality of reflection point groups corresponding to an individual obstacle, distinguishes whether or not each of the plurality of obstacles is a curb, and each of the plurality of obstacles is a parking obstacle. It includes an identification unit that identifies whether or not it is an object, and an output unit that outputs a signal indicating at least the position of the parking obstacle when the distance between the curb and the parking obstacle is less than or equal to a predetermined distance. ..
　本発明によれば、上記のように構成したので、縁石及び駐車障害物が互いに近接配置されているとき、少なくとも駐車障害物の位置を示す信号を出力することができる。 According to the present invention, since it is configured as described above, when the curb and the parking obstacle are arranged close to each other, it is possible to output at least a signal indicating the position of the parking obstacle.
実施の形態１に係る障害物検知装置を含む駐車支援システムの要部を示すブロック図である。It is a block diagram which shows the main part of the parking support system including the obstacle detection device which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置における障害物検知部の要部を示すブロック図である。It is a block diagram which shows the main part of the obstacle detection part in the obstacle detection device which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置におけるグループ化部の要部を示すブロック図である。It is a block diagram which shows the main part of the grouping part in the obstacle detection apparatus which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置における識別部の要部を示すブロック図である。It is a block diagram which shows the main part of the identification part in the obstacle detection apparatus which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置のハードウェア構成を示すブロック図である。It is a block diagram which shows the hardware composition of the obstacle detection apparatus which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置の他のハードウェア構成を示すブロック図である。It is a block diagram which shows the other hardware configuration of the obstacle detection apparatus which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置を含む駐車支援システムにおける駐車支援装置のハードウェア構成を示す説明図である。It is explanatory drawing which shows the hardware configuration of the parking support device in the parking support system including the obstacle detection device which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置を含む駐車支援システムにおける駐車支援装置の他のハードウェア構成を示す説明図である。It is explanatory drawing which shows the other hardware configuration of the parking support device in the parking support system including the obstacle detection device which concerns on Embodiment 1. FIG. 実施の形態１に係る障害物検知装置を含む駐車支援システムの動作を示すフローチャートである。It is a flowchart which shows the operation of the parking support system including the obstacle detection device which concerns on Embodiment 1. FIG. 図１０Ａは、側方領域における４個の障害物の例、及び当該４個の障害物の各々に対応する複数個の反射点の例を示す説明図である。図１０Ｂは、時間に対する反射点間距離の例を示す説明図である。FIG. 10A is an explanatory diagram showing an example of four obstacles in the lateral region and an example of a plurality of reflection points corresponding to each of the four obstacles. FIG. 10B is an explanatory diagram showing an example of the distance between reflection points with respect to time. １個の解析領域における２個の障害物の例、当該２個の障害物の各々に対応する複数個の反射点の例、及び当該２個の障害物と一対一に対応する２個の反射点群の例を示す説明図である。Examples of two obstacles in one analysis area, examples of multiple reflection points corresponding to each of the two obstacles, and two reflections corresponding to the two obstacles one-to-one. It is explanatory drawing which shows the example of a point group. 第１解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 1st analysis part. 第２解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 2nd analysis part. 第２解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 2nd analysis part. １個の解析領域における３個の障害物の例、当該３個の障害物の各々に対応する複数個の反射点の例、及び当該３個の障害物と一対一に対応する３個の反射点群の例を示す説明図である。Examples of three obstacles in one analysis area, examples of multiple reflection points corresponding to each of the three obstacles, and three reflections one-to-one with the three obstacles. It is explanatory drawing which shows the example of a point group. 第１解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 1st analysis part. 第２解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 2nd analysis part. 第２解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 2nd analysis part. 受信信号波形における波形幅、波形面積及び波形高さの例を示す説明図である。It is explanatory drawing which shows the example of the waveform width, the waveform area and the waveform height in the received signal waveform. 特徴量座標系における２個の閾値及び３個の範囲の例を示す説明図である。It is explanatory drawing which shows the example of 2 threshold value and 3 ranges in a feature amount coordinate system. Ｘ方向に対する反射点間距離がＹ方向に対する反射点間距離よりも大きい状態の例を示す説明図である。It is explanatory drawing which shows the example of the state which the distance between reflection points with respect to X direction is larger than the distance between reflection points with respect to Y direction. 側方領域における５個の障害物の例、及び当該５個の障害物の各々に対応する複数個の反射点の例を示す説明図である。It is explanatory drawing which shows the example of 5 obstacles in a side region, and the example of a plurality of reflection points corresponding to each of the 5 obstacles. 図２３Ａは、側方領域における５個の障害物の例、及び当該５個の障害物の各々に対応する複数個の反射点の例を示す説明図である。図２３Ｂは、時間に対する測距値の分散値の例を示す説明図である。図２３Ｃは、時間に対する分散値の変化量の例を示す説明図である。FIG. 23A is an explanatory diagram showing an example of five obstacles in the lateral region and an example of a plurality of reflection points corresponding to each of the five obstacles. FIG. 23B is an explanatory diagram showing an example of the variance value of the distance measurement value with respect to time. FIG. 23C is an explanatory diagram showing an example of the amount of change in the dispersion value with respect to time. 特徴量座標系における１個の閾値及び２個の範囲の例を示す説明図である。It is explanatory drawing which shows the example of one threshold value and two ranges in a feature amount coordinate system. １個の解析領域における２個の障害物の例、当該２個の障害物の各々に対応する複数個の反射点の例、及び当該２個の障害物と一対一に対応しない１個の反射点群の例を示す説明図である。Examples of two obstacles in one analysis area, examples of multiple reflection points corresponding to each of the two obstacles, and one reflection that does not correspond one-to-one with the two obstacles. It is explanatory drawing which shows the example of a point group. 第１解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 1st analysis part. 第２解析部における解析用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for analysis in the 2nd analysis part. 実施の形態２に係る障害物検知装置を含む駐車支援システムの要部を示すブロック図である。It is a block diagram which shows the main part of the parking support system including the obstacle detection device which concerns on Embodiment 2. FIG. 実施の形態２に係る障害物検知装置におけるグループ化部の要部を示すブロック図である。It is a block diagram which shows the main part of the grouping part in the obstacle detection apparatus which concerns on Embodiment 2. FIG. 実施の形態２に係る障害物検知装置を含む駐車支援システムの動作を示すフローチャートである。It is a flowchart which shows the operation of the parking support system including the obstacle detection device which concerns on Embodiment 2. 補正部における補正用の回転角度の例を示す説明図である。It is explanatory drawing which shows the example of the rotation angle for correction in a correction part. 補正部における補正用の度数分布の例を示す説明図である。It is explanatory drawing which shows the example of the frequency distribution for correction in a correction part. 実施の形態３に係る障害物検知装置を含む駐車支援システムの要部を示すブロック図である。It is a block diagram which shows the main part of the parking support system including the obstacle detection device which concerns on Embodiment 3. 実施の形態３に係る障害物検知装置における識別部の要部を示すブロック図である。It is a block diagram which shows the main part of the identification part in the obstacle detection device which concerns on Embodiment 3. FIG. 実施の形態３に係る障害物検知装置を含む駐車支援システムの動作を示すフローチャートである。It is a flowchart which shows the operation of the parking support system including the obstacle detection device which concerns on Embodiment 3. 判断窓内に３個のピーク部を有する受信信号波形の例を示す説明図である。It is explanatory drawing which shows the example of the received signal waveform which has three peak part in a judgment window. 判断窓内に１個のピーク部を有する受信信号波形の例を示す説明図である。It is explanatory drawing which shows the example of the received signal waveform which has one peak part in the judgment window.
　以下、この発明をより詳細に説明するために、この発明を実施するための形態について、添付の図面に従って説明する。 Hereinafter, in order to explain the present invention in more detail, a mode for carrying out the present invention will be described with reference to the accompanying drawings.
実施の形態１．
　図１は、実施の形態１に係る障害物検知装置を含む駐車支援システムの要部を示すブロック図である。図２は、実施の形態１に係る障害物検知装置における障害物検知部の要部を示すブロック図である。図３は、実施の形態１に係る障害物検知装置におけるグループ化部の要部を示すブロック図である。図４は、実施の形態１に係る障害物検知装置における識別部の要部を示すブロック図である。図１～図４を参照して、実施の形態１に係る障害物検知装置を含む駐車支援システムについて説明する。 Embodiment 1.
FIG. 1 is a block diagram showing a main part of a parking support system including an obstacle detection device according to the first embodiment. FIG. 2 is a block diagram showing a main part of an obstacle detection unit in the obstacle detection device according to the first embodiment. FIG. 3 is a block diagram showing a main part of the grouping unit in the obstacle detection device according to the first embodiment. FIG. 4 is a block diagram showing a main part of the identification unit in the obstacle detection device according to the first embodiment. A parking support system including an obstacle detection device according to the first embodiment will be described with reference to FIGS. 1 to 4.
　図１に示す如く、車両１は、測距センサ２、障害物検知装置１００及び駐車支援装置２００を有している。測距センサ２、障害物検知装置１００及び駐車支援装置２００により、駐車支援システム３００の要部が構成されている。 As shown in FIG. 1, the vehicle 1 has a distance measuring sensor 2, an obstacle detection device 100, and a parking support device 200. The distance measuring sensor 2, the obstacle detection device 100, and the parking support device 200 constitute a main part of the parking support system 300.
　測距センサ２は、ＴＯＦ（Ｔｉｍｅ　ｏｆ　Ｆｌｉｇｈｔ）方式の測距センサにより構成されている。測距センサ２は、例えば、超音波、電波（より具体的にはミリ波）又は光（より具体的にはレーザ光）を用いるものである。以下、測距センサ２により用いられる超音波、電波又は光などを総称して「探査波」という。また、測距センサ２により送信される又は送信された探査波を「送信波」ということがある。また、障害物Ｏにより反射される又は反射された探査波を「反射波」ということがある。また、測距センサ２により受信される又は受信された探査波を「受信波」ということがある。 The distance measuring sensor 2 is composed of a TOF (Time of Flight) type distance measuring sensor. The ranging sensor 2 uses, for example, ultrasonic waves, radio waves (more specifically, millimeter waves) or light (more specifically, laser light). Hereinafter, ultrasonic waves, radio waves, light, and the like used by the distance measuring sensor 2 are collectively referred to as “exploration waves”. Further, the exploration wave transmitted or transmitted by the ranging sensor 2 may be referred to as a “transmitted wave”. Further, the exploration wave reflected or reflected by the obstacle O may be referred to as a "reflected wave". Further, the exploration wave received or received by the ranging sensor 2 may be referred to as a “received wave”.
　測距センサ２は、車両１の左側部に設けられている。または、測距センサ２は、車両１の右側部に設けられている。または、測距センサ２は、車両１の左側部及び車両１の右側部の各々に設けられている。 The distance measuring sensor 2 is provided on the left side of the vehicle 1. Alternatively, the distance measuring sensor 2 is provided on the right side of the vehicle 1. Alternatively, the distance measuring sensor 2 is provided on each of the left side portion of the vehicle 1 and the right side portion of the vehicle 1.
　車両１の左側部に設けられた測距センサ２は、車両１が所定速度（例えば３０キロメートル毎時）ＰＶ以下の速度Ｖにて移動しているとき、所定の時間間隔ΔＴにて左方領域に探査波を送信するものである。また、車両１の左側部に設けられた測距センサ２は、左方領域内の障害物群ＯＧによる反射波を受信するものである。他方、車両１の右側部に設けられた測距センサ２は、車両１が所定速度ＰＶ以下の速度Ｖにて移動しているとき、所定の時間間隔ΔＴにて右方領域に探査波を送信するものである。また、車両１の右側部に設けられた測距センサ２は、右方領域内の障害物群ＯＧによる反射波を受信するものである。 The distance measuring sensor 2 provided on the left side of the vehicle 1 moves to the left region at a predetermined time interval ΔT when the vehicle 1 is moving at a speed V of PV or less at a predetermined speed (for example, 30 km / h). It transmits exploration waves. Further, the distance measuring sensor 2 provided on the left side of the vehicle 1 receives the reflected wave by the obstacle group OG in the left region. On the other hand, the distance measuring sensor 2 provided on the right side of the vehicle 1 transmits an exploration wave to the right region at a predetermined time interval ΔT when the vehicle 1 is moving at a speed V equal to or less than a predetermined speed PV. Is what you do. Further, the distance measuring sensor 2 provided on the right side of the vehicle 1 receives the reflected wave by the obstacle group OG in the right region.
　以下、車両１の左側部に測距センサ２が設けられている例を中心に説明する。 Hereinafter, an example in which the distance measuring sensor 2 is provided on the left side of the vehicle 1 will be mainly described.
　ここで、障害物群ＯＧは、０個の障害物Ｏ、１個の障害物Ｏ又は複数個の障害物Ｏを含むものである。個々の障害物Ｏは、例えば、壁、駐車中の他車両（以下「駐車車両」という。）、ガードレール、電柱、ポール、看板、植木、歩行者、自転車、車いす、ベビーカー、縁石、車輪止め又は段差により構成されている。 Here, the obstacle group OG includes 0 obstacle O, 1 obstacle O, or a plurality of obstacle O. Individual obstacles O are, for example, walls, other parked vehicles (hereinafter referred to as "parked vehicles"), guard rails, electric poles, poles, signs, plants, pedestrians, bicycles, wheelchairs, strollers, curbs, wheel chocks or It is composed of steps.
　以下、障害物Ｏの高さＨに対する２個の閾値Ｈ＿ｔｈ＿１，Ｈ＿ｔｈ＿２が設定されているとき（Ｈ＿ｔｈ＿１＜Ｈ＿ｔｈ＿２）、閾値Ｈ＿ｔｈ＿１未満の高さＨを有する障害物Ｏを「路面障害物」ということがある。また、閾値Ｈ＿ｔｈ＿１以上かつ閾値Ｈ＿ｔｈ＿２未満の高さＨを有する障害物Ｏを「路上障害物」ということがある。また、閾値Ｈ＿ｔｈ＿２以上の高さＨを有する障害物Ｏを「走行障害物」ということがある。 Hereinafter, when two threshold values H_th_1 and H_th_2 with respect to the height H of the obstacle O are set (H_th_1 <H_th_2), the obstacle O having a height H less than the threshold value H_th_1 is referred to as a "road surface obstacle". is there. Further, an obstacle O having a height H of the threshold value H_th_1 or more and less than the threshold value H_th_2 may be referred to as a “road obstacle”. Further, an obstacle O having a height H equal to or higher than the threshold value H_th_2 may be referred to as a "running obstacle".
　走行障害物は、車両１のバンパ部に接触し得る程度に大きい高さＨを有している。走行障害物は、例えば、壁、駐車車両、ガードレール、電柱、ポール、看板、植木、歩行者、自転車、車いす及びベビーカーを含むものである。路上障害物は、車両１のバンパ部に接触し得ない程度に小さい高さＨを有しており、かつ、車両１による乗り越えが困難である程度に大きい高さＨを有している。路上障害物は、例えば、縁石及び車輪止めを含むものである。路面障害物は、車両１のバンパ部に接触し得ない程度に小さい高さＨを有しており、かつ、車両１による乗り越えが容易である程度に小さい高さＨを有している。路面障害物は、例えば、段差を含むものである。 The traveling obstacle has a height H large enough to come into contact with the bumper portion of the vehicle 1. Traveling obstacles include, for example, walls, parked vehicles, guardrails, electric poles, poles, signs, plants, pedestrians, bicycles, wheelchairs and strollers. The road obstacle has a height H so small that it cannot come into contact with the bumper portion of the vehicle 1, and has a height H that is large to some extent because it is difficult for the vehicle 1 to get over it. Road obstacles include, for example, curbs and wheel chocks. The road surface obstacle has a height H so small that it cannot come into contact with the bumper portion of the vehicle 1, and has a height H that is easy to get over by the vehicle 1 and is small to some extent. The road surface obstacle includes, for example, a step.
　また、障害物Ｏの高さＨに対する１個の閾値Ｈ＿ｔｈ＿３が設定されているとき、閾値Ｈ＿ｔｈ＿３未満の高さＨを有する障害物Ｏを「低背障害物」ということがある。また、閾値Ｈ＿ｔｈ＿３以上の高さＨを有する障害物Ｏを「高背障害物」ということがある。 Further, when one threshold value H_th_3 is set for the height H of the obstacle O, the obstacle O having a height H less than the threshold value H_th_3 may be referred to as a "low profile obstacle". Further, an obstacle O having a height H equal to or higher than the threshold value H_th_3 may be referred to as a “tall obstacle”.
　閾値Ｈ＿ｔｈ＿３は、例えば、閾値Ｈ＿ｔｈ＿２と同等の値に設定されている。この場合、走行障害物が高背障害物に含まれるものであり、かつ、路上障害物及び路面障害物が低背障害物に含まれるものである。または、例えば、閾値Ｈ＿ｔｈ＿３は、閾値Ｈ＿ｔｈ＿１と同等の値に設定されている。この場合、走行障害物及び路上障害物が高背障害物に含まれるものであり、かつ、路面障害物が低背障害物に含まれるものである。 The threshold value H_th_3 is set to a value equivalent to, for example, the threshold value H_th_2. In this case, the traveling obstacle is included in the tall obstacle, and the road obstacle and the road surface obstacle are included in the low-back obstacle. Alternatively, for example, the threshold value H_th_3 is set to a value equivalent to the threshold value H_th_1. In this case, the traveling obstacle and the road obstacle are included in the tall obstacle, and the road surface obstacle is included in the low back obstacle.
　また、障害物Ｏの幅Ｗに対する２個の閾値Ｗ＿ｔｈ＿１，Ｗ＿ｔｈ＿２が設定されているとき（Ｗ＿ｔｈ＿１＜Ｗ＿ｔｈ＿２）、閾値Ｗ＿ｔｈ＿１未満の幅Ｗを有する障害物Ｏを「狭幅障害物」ということがある。また、閾値Ｗ＿ｔｈ＿２以上の幅Ｗを有する障害物Ｏを「広幅障害物」ということがある。ここで、幅Ｗは、車両１の前後方向（すなわち車両１の移動方向）に対する幅である。 Further, when two threshold values W_th_1 and W_th_2 are set for the width W of the obstacle O (W_th_1 <W_th_2), the obstacle O having a width W less than the threshold value W_th_1 may be referred to as a "narrow obstacle". .. Further, an obstacle O having a width W equal to or greater than the threshold value W_th_2 may be referred to as a "wide obstacle". Here, the width W is the width with respect to the front-rear direction of the vehicle 1 (that is, the moving direction of the vehicle 1).
　広幅障害物は、例えば、壁、ガードレール、縁石及び段差を含むものである。狭幅障害物は、例えば、電柱、ポール、看板、植木、歩行者、自転車、車いす及びベビーカーを含むものである。狭幅障害物の識別に係る閾値Ｗ＿ｔｈ＿１は、例えば、１メートルに設定されている。 Wide obstacles include, for example, walls, guardrails, curbs and steps. Narrow obstacles include, for example, utility poles, poles, signs, plants, pedestrians, bicycles, wheelchairs and strollers. The threshold value W_th_1 for identifying narrow obstacles is set to, for example, 1 meter.
　また、狭幅障害物のうちの移動している障害物Ｏを「動的障害物」ということがある。動的障害物は、例えば、歩行者、自転車、車いす及びベビーカーを含むものである。また、狭幅障害物のうちの静止している障害物Ｏを「静的障害物」ということがある。静的障害物は、例えば、電柱、ポール、看板及び植木を含むものである。 Also, among narrow obstacles, the moving obstacle O is sometimes called a "dynamic obstacle". Dynamic obstacles include, for example, pedestrians, bicycles, wheelchairs and strollers. Further, the stationary obstacle O among the narrow obstacles may be referred to as a "static obstacle". Static obstacles include, for example, utility poles, poles, signs and plants.
　以下、側方領域ＬＡに障害物群ＯＧが存在している場合において、障害物群ＯＧに複数個の障害物Ｏが含まれているときの例を中心に説明する。 Hereinafter, an example in which an obstacle group OG exists in the lateral region LA and a plurality of obstacles O are included in the obstacle group OG will be mainly described.
　障害物検知装置１００は、例えば、電子制御ユニット（以下「ＥＣＵ」と記載する。）により構成されている。障害物検知装置１００は、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４、識別部１５及び出力部１６を有している。駐車支援装置２００は、例えば、ＥＣＵにより構成されている。駐車支援装置２００は、駐車支援制御部２１を有している。 The obstacle detection device 100 is composed of, for example, an electronic control unit (hereinafter referred to as "ECU"). The obstacle detection device 100 includes an obstacle detection unit 11, a discontinuous unit detection unit 12, an analysis area extraction unit 13, a grouping unit 14, an identification unit 15, and an output unit 16. The parking support device 200 is composed of, for example, an ECU. The parking support device 200 has a parking support control unit 21.
　障害物検知装置１００は、車両１の速度Ｖを示す情報（以下「車両速度情報」という。）を取得する機能を有している。車両速度情報は、例えば、ＣＡＮ（Ｃｏｎｔｒｏｌｌｅｒ　Ａｒｅａ　Ｎｅｔｗｏｒｋ）通信により取得される。障害物検知装置１００は、当該取得された車両速度情報を用いて、車両１が所定速度ＰＶ以下の速度Ｖにて移動中であるか否かを判定する機能を有している。 The obstacle detection device 100 has a function of acquiring information indicating the speed V of the vehicle 1 (hereinafter referred to as "vehicle speed information"). The vehicle speed information is acquired by, for example, CAN (Control Area Network) communication. The obstacle detection device 100 has a function of determining whether or not the vehicle 1 is moving at a speed V equal to or lower than a predetermined speed PV by using the acquired vehicle speed information.
　障害物検知装置１００は、車両１の位置及び車両１の向きを示す情報（以下「車両位置情報」という。）を取得する機能を有している。車両位置情報は、例えば、ＣＡＮ通信により取得される。障害物検知装置１００には、車両１における測距センサ２の設置位置及び車両１における測距センサ２の設置方向を示す情報（以下「センサ設置位置情報」という。）が予め記憶されている。障害物検知装置１００は、当該取得された車両位置情報及び当該記憶されているセンサ設置位置情報を用いて、測距センサ２の位置及び測距センサ２の向きを算出する機能を有している。 The obstacle detection device 100 has a function of acquiring information indicating the position of the vehicle 1 and the direction of the vehicle 1 (hereinafter referred to as "vehicle position information"). The vehicle position information is acquired by, for example, CAN communication. The obstacle detection device 100 stores in advance information indicating the installation position of the distance measurement sensor 2 in the vehicle 1 and the installation direction of the distance measurement sensor 2 in the vehicle 1 (hereinafter referred to as “sensor installation position information”). The obstacle detection device 100 has a function of calculating the position of the distance measuring sensor 2 and the direction of the distance measuring sensor 2 by using the acquired vehicle position information and the stored sensor installation position information. ..
　または、障害物検知装置１００は、車両１のヨーレートを示す情報（以下「ヨーレート情報」という。）及び車両１の操舵角を示す情報（以下「操舵角情報」という。）を取得する機能を有している。ヨーレート情報及び操舵角情報は、例えば、ＣＡＮ通信により取得される。障害物検知装置１００には、センサ設置位置情報が予め記憶されている。障害物検知装置１００は、当該取得されたヨーレート情報及び操舵角情報を用いて、車両１の位置及び車両１の向きを算出する機能を有している。障害物検知装置１００は、当該記憶されているセンサ設置位置情報を用いて、当該算出された車両１の位置及び車両１の向きに基づき、測距センサ２の位置及び測距センサ２の向きを算出する機能を有している。 Alternatively, the obstacle detection device 100 has a function of acquiring information indicating the yaw rate of the vehicle 1 (hereinafter referred to as "yaw rate information") and information indicating the steering angle of the vehicle 1 (hereinafter referred to as "steering angle information"). doing. The yaw rate information and the steering angle information are acquired by, for example, CAN communication. The sensor installation position information is stored in advance in the obstacle detection device 100. The obstacle detection device 100 has a function of calculating the position of the vehicle 1 and the direction of the vehicle 1 by using the acquired yaw rate information and the steering angle information. The obstacle detection device 100 uses the stored sensor installation position information to determine the position of the distance measuring sensor 2 and the orientation of the distance measuring sensor 2 based on the calculated position of the vehicle 1 and the orientation of the vehicle 1. It has a function to calculate.
　以下、車両１が所定速度ＰＶ以下の速度Ｖにて移動中であるか否かを判定する機能を「車両速度判定機能」という。また、測距センサ２の位置及び測距センサ２の向きを算出する機能を「センサ位置算出機能」という。 Hereinafter, the function of determining whether or not the vehicle 1 is moving at a speed V of a predetermined speed PV or less is referred to as a "vehicle speed determination function". Further, the function of calculating the position of the distance measuring sensor 2 and the orientation of the distance measuring sensor 2 is referred to as a "sensor position calculation function".
　図２に示す如く、障害物検知部１１は、送信信号出力部３１、受信信号取得部３２、測距値算出部３３及び座標値算出部３４を有している。 As shown in FIG. 2, the obstacle detection unit 11 includes a transmission signal output unit 31, a reception signal acquisition unit 32, a distance measurement value calculation unit 33, and a coordinate value calculation unit 34.
　送信信号出力部３１は、車両１が所定速度ＰＶ以下の速度Ｖにて移動中であるとき、送信波に対応する電気信号（以下「送信信号」という。）ＴＳを所定の時間間隔ΔＴにて測距センサ２に出力するものである。これにより、送信信号出力部３１は、測距センサ２に所定の時間間隔ΔＴにて送信波を送信させるものである。車両１が所定速度ＰＶ以下の速度Ｖにて移動中であるか否かは、車両速度判定機能により判定される。 When the vehicle 1 is moving at a speed V equal to or lower than a predetermined speed PV, the transmission signal output unit 31 transmits an electric signal (hereinafter referred to as “transmission signal”) TS corresponding to the transmission wave at a predetermined time interval ΔT. It is output to the distance measuring sensor 2. As a result, the transmission signal output unit 31 causes the distance measuring sensor 2 to transmit the transmitted wave at a predetermined time interval ΔT. Whether or not the vehicle 1 is moving at a speed V equal to or lower than a predetermined speed PV is determined by the vehicle speed determination function.
　受信信号取得部３２は、測距センサ２による受信波に対応する電気信号（以下「受信信号」という。）ＲＳを取得するものである。 The received signal acquisition unit 32 acquires an electrical signal (hereinafter referred to as “received signal”) RS corresponding to the received wave by the distance measuring sensor 2.
　測距値算出部３３は、受信信号ＲＳを用いて、ＴＯＦ法による測距値Ｄを算出するものである。ＴＯＦ法による測距値Ｄの算出には、公知の種々の技術を用いることができる。これらの技術についての詳細な説明は省略する。 The distance measurement value calculation unit 33 calculates the distance measurement value D by the TOF method using the received signal RS. Various known techniques can be used to calculate the distance measurement value D by the TOF method. Detailed description of these techniques will be omitted.
　座標値算出部３４は、測距値Ｄを用いて、障害物Ｏにより探査波が反射された地点（以下「反射点」という。）ＲＰの位置を示す座標値（以下「反射点座標値」ということがある。）Ｃ＿Ｘ，Ｃ＿Ｙを算出するものである。座標値Ｃ＿Ｘ，Ｃ＿Ｙは、例えば、車両１の前後方向（すなわち車両１の移動方向）に沿う第１軸（以下「Ｘ軸」という。）及び車両１の左右方向（すなわち車両１の移動方向に対する直交方向）に沿う第２軸（以下「Ｙ軸」という。）を有する座標系（以下「ＸＹ座標系」という。）における座標値である。 The coordinate value calculation unit 34 uses the distance measurement value D to indicate the position of the RP at the point where the exploration wave is reflected by the obstacle O (hereinafter referred to as “reflection point”) (hereinafter referred to as “reflection point coordinate value”). It may be that.) C_X and C_Y are calculated. The coordinate values C_X and C_Y are, for example, the first axis (hereinafter referred to as "X-axis") along the front-rear direction of the vehicle 1 (that is, the moving direction of the vehicle 1) and the left-right direction of the vehicle 1 (that is, the moving direction of the vehicle 1). It is a coordinate value in a coordinate system (hereinafter referred to as "XY coordinate system") having a second axis (hereinafter referred to as "Y axis") along the orthogonal direction).
　具体的には、例えば、座標値算出部３４は、以下のようなベクトルを求めることにより座標値Ｃ＿Ｘ，Ｃ＿Ｙを算出する。すなわち、座標値算出部３４は、対応する探査波が送信された時点における測距センサ２の位置に相当する始点を有し、かつ、当該時点における測距センサ２の向きに相当する向きを有し、かつ、対応する測距値Ｄに相当する大きさを有するベクトルを求める。このとき、測距センサ２の位置及び測距センサ２の向きは、センサ位置算出機能により算出される。このベクトルは、ＸＹ座標系におけるベクトルである。 Specifically, for example, the coordinate value calculation unit 34 calculates the coordinate values C_X and C_Y by obtaining the following vectors. That is, the coordinate value calculation unit 34 has a start point corresponding to the position of the distance measuring sensor 2 at the time when the corresponding exploration wave is transmitted, and has a direction corresponding to the direction of the distance measuring sensor 2 at that time. However, a vector having a magnitude corresponding to the corresponding distance measurement value D is obtained. At this time, the position of the distance measuring sensor 2 and the orientation of the distance measuring sensor 2 are calculated by the sensor position calculation function. This vector is a vector in the XY coordinate system.
　以下、座標値Ｃ＿Ｘを「Ｘ座標値」ということがある。また、座標値Ｃ＿Ｙを「Ｙ座標値」ということがある。また、Ｘ軸に沿う方向を「Ｘ方向」ということがある。また、Ｙ軸に沿う方向を「Ｙ方向」又は「奥行き方向」ということがある。また、Ｙ方向について、ＸＹ座標系における任意の点に対して、車両１から遠い側を「奥側」ということがある。また、Ｙ方向について、ＸＹ座標系における任意の点に対して、車両１に近い側を「手前側」ということがある。 Hereinafter, the coordinate value C_X may be referred to as "X coordinate value". Further, the coordinate value C_Y may be referred to as a "Y coordinate value". Further, the direction along the X axis may be referred to as "X direction". Further, the direction along the Y axis may be referred to as "Y direction" or "depth direction". Further, in the Y direction, the side far from the vehicle 1 with respect to an arbitrary point in the XY coordinate system may be referred to as the "back side". Further, in the Y direction, the side closer to the vehicle 1 with respect to an arbitrary point in the XY coordinate system may be referred to as the "front side".
　以下、個々の反射点ＲＰに対応する受信信号ＲＳの波形を示す情報を「波形情報」という。また、個々の反射点ＲＰに対応する測距値Ｄを示す情報を「測距値情報」という。また、個々の反射点ＲＰに対応する座標値Ｃ＿Ｘ，Ｃ＿Ｙを示す情報を「座標値情報」という。また、波形情報、測距値情報及び座標値情報を含む情報を「反射点情報」という。障害物検知部１１は、反射点情報を非連続部検知部１２及び解析領域抽出部１３に出力するものである。 Hereinafter, the information indicating the waveform of the received signal RS corresponding to each reflection point RP is referred to as "waveform information". Further, the information indicating the distance measurement value D corresponding to each reflection point RP is referred to as "distance measurement value information". Further, the information indicating the coordinate values C_X and C_Y corresponding to the individual reflection point RP is referred to as "coordinate value information". Further, information including waveform information, ranging value information and coordinate value information is referred to as "reflection point information". The obstacle detection unit 11 outputs the reflection point information to the discontinuous unit detection unit 12 and the analysis area extraction unit 13.
　以下、障害物検知部１１により実行される処理を総称して「障害物検知処理」ということがある。すなわち、障害物検知処理は、送信信号ＴＳを出力する処理、受信信号ＲＳを取得する処理、測距値Ｄを算出する処理、座標値Ｃ＿Ｘ，Ｃ＿Ｙを算出する処理、及び反射点情報を出力する処理などを含むものである。 Hereinafter, the processes executed by the obstacle detection unit 11 may be collectively referred to as "obstacle detection process". That is, the obstacle detection process outputs the transmission signal TS, the reception signal RS, the distance measurement value D, the coordinate values C_X and C_Y, and the reflection point information. It includes processing and so on.
　側方領域ＬＡに障害物群ＯＧが存在している場合において、１個の障害物Ｏ又は複数個の障害物Ｏが障害物群ＯＧに含まれているとき、障害物検知処理が実行されることにより、複数個の反射点ＲＰの各々の位置を示す座標値Ｃ＿Ｘ，Ｃ＿Ｙが算出される。換言すれば、障害物群ＯＧに対応する複数個の反射点ＲＰが検知される。これにより、障害物群ＯＧが検知される。 When the obstacle group OG exists in the lateral region LA and one obstacle O or a plurality of obstacle O is included in the obstacle group OG, the obstacle detection process is executed. As a result, the coordinate values C_X and C_Y indicating the positions of the plurality of reflection point RPs are calculated. In other words, a plurality of reflection point RPs corresponding to the obstacle group OG are detected. As a result, the obstacle group OG is detected.
　非連続部検知部１２は　障害物検知部１１により出力された反射点情報を取得するものである。非連続部検知部１２は、当該取得された反射点情報を用いて、障害物群ＯＧにおける非連続的な部位（以下「非連続部」という。）ＤＰを検知するものである。非連続部ＤＰの検知方法の具体例については、図１０を参照して後述する。非連続部検知部１２は、当該検知された非連続部ＤＰを示す情報（以下「非連続部情報」という。）を解析領域抽出部１３に出力するものである。 The discontinuous unit detection unit 12 acquires the reflection point information output by the obstacle detection unit 11. The discontinuous portion detecting unit 12 detects the discontinuous portion (hereinafter referred to as “discontinuous portion”) DP in the obstacle group OG by using the acquired reflection point information. A specific example of the method of detecting the discontinuous portion DP will be described later with reference to FIG. The discontinuous unit detection unit 12 outputs information indicating the detected discontinuous unit DP (hereinafter referred to as “discontinuous unit information”) to the analysis area extraction unit 13.
　以下、非連続部検知部１２により実行される処理を総称して「非連続部検知処理」ということがある。すなわち、非連続部検知処理は、反射点情報を取得する処理、非連続部ＤＰを検知する処理、及び非連続部情報を出力する処理などを含むものである。 Hereinafter, the processes executed by the discontinuous portion detection unit 12 may be collectively referred to as "discontinuous portion detection processing". That is, the discontinuous portion detection process includes a process of acquiring reflection point information, a process of detecting the discontinuous portion DP, a process of outputting discontinuous portion information, and the like.
　解析領域抽出部１３は、非連続部検知部１２により出力された非連続部情報を取得するものである。解析領域抽出部１３は、当該取得された非連続部情報を用いて、グループ化部１４による解析用の領域（以下「解析領域」という。）ＡＡを抽出するものである。ここで、解析領域ＡＡは、非連続部ＤＰに基づき側方領域ＬＡを分割してなる領域である。解析領域ＡＡの具体例については、図１０を参照して後述する。通常、個々の解析領域ＡＡは、複数個の反射点ＲＰを含むものである。 The analysis area extraction unit 13 acquires the discontinuous unit information output by the discontinuous unit detection unit 12. The analysis area extraction unit 13 extracts the area for analysis (hereinafter referred to as “analysis area”) AA by the grouping unit 14 by using the acquired discontinuous part information. Here, the analysis region AA is a region formed by dividing the lateral region LA based on the discontinuous portion DP. A specific example of the analysis region AA will be described later with reference to FIG. Usually, each analysis region AA contains a plurality of reflection point RPs.
　解析領域抽出部１３は、障害物検知部１１により出力された反射点情報を取得するものである。解析領域抽出部１３は、当該取得された反射点情報のうちの個々の解析領域ＡＡに含まれる複数個の反射点ＲＰに対応する反射点情報をグループ化部１４に出力するものである。すなわち、解析領域抽出部１３は、解析領域ＡＡ毎の反射点情報をグループ化部１４に出力するものである。 The analysis area extraction unit 13 acquires the reflection point information output by the obstacle detection unit 11. The analysis area extraction unit 13 outputs the reflection point information corresponding to the plurality of reflection point RPs included in the individual analysis area AA of the acquired reflection point information to the grouping unit 14. That is, the analysis area extraction unit 13 outputs the reflection point information for each analysis area AA to the grouping unit 14.
　以下、解析領域抽出部１３により実行される処理を総称して「解析領域抽出処理」ということがある。すなわち、解析領域抽出処理は、非連続部情報を取得する処理、解析領域ＡＡを抽出する処理、反射点情報を取得する処理、及び解析領域ＡＡ毎の反射点情報を出力する処理などを含むものである。 Hereinafter, the processes executed by the analysis area extraction unit 13 may be collectively referred to as "analysis area extraction process". That is, the analysis area extraction process includes a process of acquiring discontinuous part information, a process of extracting the analysis area AA, a process of acquiring the reflection point information, a process of outputting the reflection point information for each analysis area AA, and the like. ..
　グループ化部１４は、解析領域抽出部１３により出力された反射点情報を取得するものである。グループ化部１４は、当該取得された反射点情報を用いて、個々の解析領域ＡＡに含まれる複数個の反射点ＲＰをグループ化することにより、個々の解析領域ＡＡにおける個々の障害物Ｏに対応する反射点群ＰＧを設定するものである。 The grouping unit 14 acquires the reflection point information output by the analysis area extraction unit 13. The grouping unit 14 uses the acquired reflection point information to group a plurality of reflection point RPs included in each analysis area AA into individual obstacles O in each analysis area AA. The corresponding reflection point group PG is set.
　例えば、複数個の解析領域ＡＡのうちの１個の解析領域ＡＡに１個の障害物Ｏに対応する複数個の反射点ＲＰが含まれている場合、当該複数個の反射点ＲＰがグループ化されることにより、当該１個の障害物Ｏに対応する１個の反射点群ＰＧが設定される。また、複数個の解析領域ＡＡのうちの他の１個の解析領域ＡＡに複数個の障害物Ｏに対応する複数個の反射点ＲＰが含まれている場合、当該複数個の反射点ＲＰがグループ化されることにより、当該複数個の障害物Ｏと一対一に対応する複数個の反射点群ＰＧが設定される。 For example, when one analysis area AA of the plurality of analysis areas AA includes a plurality of reflection point RPs corresponding to one obstacle O, the plurality of reflection point RPs are grouped. By doing so, one reflection point group PG corresponding to the one obstacle O is set. Further, when the other analysis region AA of the plurality of analysis regions AA includes a plurality of reflection point RPs corresponding to the plurality of obstacles O, the plurality of reflection point RPs are included. By grouping, a plurality of reflection point group PGs corresponding to the plurality of obstacles O on a one-to-one basis are set.
　ここで、図３に示す如く、グループ化部１４は、第１解析部４１及び第２解析部４２を有している。 Here, as shown in FIG. 3, the grouping unit 14 has a first analysis unit 41 and a second analysis unit 42.
　第１解析部４１は、個々の解析領域ＡＡに対応する反射点情報を用いて、Ｙ座標値Ｃ＿Ｙに対する反射点ＲＰの個数を示す度数分布ＦＤ＿Ｙを作成するものである。第１解析部４１は、当該作成された度数分布ＦＤ＿Ｙを解析するものである。より具体的には、第１解析部４１は、当該作成された度数分布ＦＤ＿Ｙに対するピーク分離処理を実行するものである。これにより、１個以上の度数群ＦＧ＿Ｙが設定される。 The first analysis unit 41 creates a frequency distribution FD_Y indicating the number of reflection point RPs with respect to the Y coordinate value C_Y by using the reflection point information corresponding to each analysis region AA. The first analysis unit 41 analyzes the created frequency distribution FD_Y. More specifically, the first analysis unit 41 executes the peak separation process for the created frequency distribution FD_Y. As a result, one or more frequency groups FG_Y are set.
　第２解析部４２は、個々の度数群ＦＧ＿Ｙに対応する反射点情報を用いて、Ｘ座標値Ｃ＿Ｘに対する反射点ＲＰの個数を示す度数分布ＦＤ＿Ｘを作成するものである。第２解析部４２は、当該作成された度数分布ＦＤ＿Ｘを解析するものである。より具体的には、第２解析部４２は、当該作成された度数分布ＦＤ＿Ｘに対するピーク分離処理を実行するものである。これにより、１個以上の度数群ＦＧ＿Ｘが設定される。 The second analysis unit 42 creates a frequency distribution FD_X indicating the number of reflection point RPs with respect to the X coordinate value C_X by using the reflection point information corresponding to each frequency group FG_Y. The second analysis unit 42 analyzes the created frequency distribution FD_X. More specifically, the second analysis unit 42 executes the peak separation process for the created frequency distribution FD_X. As a result, one or more frequency groups FG_X are set.
　グループ化部１４は、第１解析部４１による解析結果及び第２解析部４２による解析結果に基づき、個々の障害物Ｏに対応する反射点群ＰＧを設定するものである。反射点群ＰＧの設定方法の具体例については、図１１～図１８を参照して後述する。 The grouping unit 14 sets the reflection point cloud group PG corresponding to each obstacle O based on the analysis result by the first analysis unit 41 and the analysis result by the second analysis unit 42. A specific example of the method of setting the reflection point group PG will be described later with reference to FIGS. 11 to 18.
　通常、個々の反射点群ＰＧは、複数個の反射点ＲＰを含むものである。グループ化部１４は、上記取得された反射点情報のうちの個々の反射点群ＰＧに含まれる複数個の反射点ＲＰに対応する反射点情報を識別部１５に出力するものである。すなわち、グループ化部１４は、反射点群ＰＧ毎の反射点情報を識別部１５に出力するものである。 Normally, each reflection point group PG includes a plurality of reflection point RPs. The grouping unit 14 outputs the reflection point information corresponding to the plurality of reflection point RPs included in the individual reflection point group PG among the acquired reflection point information to the identification unit 15. That is, the grouping unit 14 outputs the reflection point information for each reflection point group PG to the identification unit 15.
　以下、グループ化部１４により実行される処理を総称して「グループ化処理」ということがある。すなわち、グループ化処理は、解析領域ＡＡ毎の反射点情報を取得する処理、個々の障害物Ｏに対応する反射点群ＰＧを設定する処理、及び反射点群ＰＧ毎の反射点情報を出力する処理などを含むものである。 Hereinafter, the processes executed by the grouping unit 14 may be collectively referred to as "grouping process". That is, in the grouping process, the process of acquiring the reflection point information for each analysis area AA, the process of setting the reflection point group PG corresponding to each obstacle O, and the process of outputting the reflection point information for each reflection point group PG are output. It includes processing and so on.
　識別部１５は、グループ化部１４により出力された反射点情報を取得するものである。識別部１５は、当該取得された反射点情報を用いて、個々の反射点群ＰＧに対応する障害物Ｏの種別を識別するものである。 The identification unit 15 acquires the reflection point information output by the grouping unit 14. The identification unit 15 uses the acquired reflection point information to identify the type of obstacle O corresponding to each reflection point group PG.
　ここで、図４に示す如く、識別部１５は、幅判断部５１、位置判断部５２及び高さ判断部５３を有している。 Here, as shown in FIG. 4, the identification unit 15 has a width determination unit 51, a position determination unit 52, and a height determination unit 53.
　幅判断部５１は、上記取得された反射点情報を用いて、Ｘ方向に対する個々の反射点群ＰＧの幅を判断するものである。これにより、Ｘ方向に対する個々の障害物Ｏの幅Ｗが判断される。幅判断部５１は、当該判断の結果に基づき、個々の障害物Ｏが広幅障害物であるか否かを判断するものである。また、幅判断部５１は、当該判断の結果に基づき、個々の障害物Ｏが狭幅障害物であるか否かを判断するものである。 The width determination unit 51 determines the width of each reflection point group PG with respect to the X direction by using the acquired reflection point information. As a result, the width W of each obstacle O with respect to the X direction is determined. The width determination unit 51 determines whether or not each obstacle O is a wide obstacle based on the result of the determination. Further, the width determination unit 51 determines whether or not each obstacle O is a narrow obstacle based on the result of the determination.
　位置判断部５２は、上記取得された反射点情報を用いて、Ｘ方向に対する個々の反射点群ＰＧの位置を判断するものである。これにより、Ｘ方向に対する個々の障害物Ｏの位置が判断される。また、位置判断部５２は、上記取得された反射点情報を用いて、奥行き方向に対する個々の反射点群ＰＧの位置を判断するものである。これにより、奥行き方向に対する個々の障害物Ｏの位置が判断される。 The position determination unit 52 determines the position of each reflection point group PG with respect to the X direction by using the acquired reflection point information. As a result, the position of each obstacle O with respect to the X direction is determined. Further, the position determination unit 52 determines the position of each reflection point group PG with respect to the depth direction by using the acquired reflection point information. As a result, the position of each obstacle O with respect to the depth direction is determined.
　高さ判断部５３は、上記取得された反射点情報を用いて、個々の障害物Ｏの高さＨを判断するものである。これにより、例えば、個々の障害物Ｏが走行障害物、路上障害物又は路面障害物のうちのいずれであるかが判断される。 The height determination unit 53 determines the height H of each obstacle O by using the acquired reflection point information. Thereby, for example, it is determined whether the individual obstacle O is a traveling obstacle, a road obstacle, or a road surface obstacle.
　個々の障害物Ｏの幅Ｗの判断には、公知の種々の技術を用いることができる。また、個々の障害物Ｏの位置の判断には、公知の種々の技術を用いることができる。これらの技術についての詳細な説明は省略する。これに対して、個々の障害物Ｏの高さＨの判断方法の具体例については、図１９及び図２０を参照して後述する。 Various known techniques can be used to determine the width W of each obstacle O. In addition, various known techniques can be used to determine the position of each obstacle O. Detailed description of these techniques will be omitted. On the other hand, a specific example of the method of determining the height H of each obstacle O will be described later with reference to FIGS. 19 and 20.
　識別部１５は、これらの判断部（５１，５２，５３）のうちの少なくとも１個の判断部による判断結果に基づき、個々の障害物Ｏが縁石であるか否かを識別する。個々の障害物Ｏが縁石であるか否かの識別方法の具体例については後述する。また、識別部１５は、これらの判断部（５１，５２，５３）のうちの少なくとも１個の判断部による判断結果に基づき、個々の障害物Ｏが駐車障害物であるか否かを識別する。個々の障害物Ｏが駐車障害物であるか否かの識別方法の具体例については後述する。 The identification unit 15 identifies whether or not each obstacle O is a curb based on the judgment result of at least one of these judgment units (51, 52, 53). A specific example of a method for identifying whether or not each obstacle O is a curb will be described later. Further, the identification unit 15 identifies whether or not each obstacle O is a parking obstacle based on the determination result by at least one of these determination units (51, 52, 53). .. A specific example of a method for identifying whether or not each obstacle O is a parking obstacle will be described later.
　以下、識別部１５により実行される処理を総称して「識別処理」ということがある。すなわち、識別処理は、個々の障害物Ｏの幅Ｗを判断する処理、個々の障害物Ｏの位置を判断する処理、個々の障害物Ｏの高さＨを判断する処理、及び個々の障害物Ｏの種別を識別する処理などを含むものである。 Hereinafter, the processes executed by the identification unit 15 may be collectively referred to as "identification processing". That is, the identification process includes a process of determining the width W of each obstacle O, a process of determining the position of each obstacle O, a process of determining the height H of each obstacle O, and an individual obstacle. It includes a process of identifying the type of O.
　出力部１６は、識別処理の結果を示す信号（以下「識別結果信号」という。）を駐車支援制御部２１に出力するものである。 The output unit 16 outputs a signal indicating the result of the identification process (hereinafter referred to as "identification result signal") to the parking support control unit 21.
　ここで、識別結果信号は、個々の障害物Ｏが縁石であるか否かを示す情報、個々の障害物Ｏが駐車障害物であるか否かを示す情報、及び個々の障害物Ｏの位置を示す情報を含むものである。したがって、障害物群ＯＧに縁石及び駐車障害物が含まれる場合において、縁石及び駐車障害物が互いに近接配置されているとき（すなわち縁石と駐車障害物間の距離が所定距離以下であるとき）、識別結果信号は、少なくとも駐車障害物の位置を示すものである。 Here, the identification result signal is information indicating whether or not each obstacle O is a curb, information indicating whether or not each obstacle O is a parking obstacle, and the position of each obstacle O. It contains information indicating. Therefore, when the curb and the parking obstacle are included in the obstacle group OG and the curb and the parking obstacle are arranged close to each other (that is, when the distance between the curb and the parking obstacle is less than a predetermined distance), The identification result signal indicates at least the position of the parking obstacle.
　以下、出力部１６により実行される処理を総称して「出力処理」ということがある。すなわち、出力処理は、識別結果信号を出力する処理などを含むものである。 Hereinafter, the processing executed by the output unit 16 may be collectively referred to as "output processing". That is, the output process includes a process of outputting an identification result signal and the like.
　駐車支援制御部２１は、出力部１６により出力された識別結果信号を取得するものである。駐車支援制御部２１は、当該取得された識別結果信号を用いて、側方領域ＬＡにおける駐車スペースを検知するものである。駐車支援制御部２１は、当該検知された駐車スペースに対する駐車支援制御を実行するものである。具体的には、例えば、駐車支援制御部２１は、いわゆる「自動駐車」を実現するための制御を実行するものである。駐車支援制御には、公知の種々の技術を用いることができる。これらの技術についての詳細な説明は省略する。 The parking support control unit 21 acquires the identification result signal output by the output unit 16. The parking support control unit 21 detects the parking space in the side region LA by using the acquired identification result signal. The parking support control unit 21 executes parking support control for the detected parking space. Specifically, for example, the parking support control unit 21 executes control for realizing so-called "automatic parking". Various known techniques can be used for parking support control. Detailed description of these techniques will be omitted.
　次に、図５及び図６を参照して、障害物検知装置１００の要部のハードウェア構成について説明する。 Next, the hardware configuration of the main part of the obstacle detection device 100 will be described with reference to FIGS. 5 and 6.
　図５に示す如く、障害物検知装置１００は、プロセッサ６１及びメモリ６２を有している。メモリ６２には、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４、識別部１５及び出力部１６の機能を実現するためのプログラムが記憶されている。かかるプログラムをプロセッサ６１が読み出して実行することにより、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４、識別部１５及び出力部１６の機能が実現される。 As shown in FIG. 5, the obstacle detection device 100 has a processor 61 and a memory 62. The memory 62 stores programs for realizing the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16. When the processor 61 reads and executes such a program, the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16 are realized. ..
　または、図６に示す如く、障害物検知装置１００は、処理回路６３を有している。この場合、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４、識別部１５及び出力部１６の機能が専用の処理回路６３により実現される。 Alternatively, as shown in FIG. 6, the obstacle detection device 100 has a processing circuit 63. In this case, the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16 are realized by the dedicated processing circuit 63.
　または、障害物検知装置１００は、プロセッサ６１、メモリ６２及び処理回路６３を有している（不図示）。この場合、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４、識別部１５及び出力部１６の機能のうちの一部の機能がプロセッサ６１及びメモリ６２により実現されるとともに、残余の機能が専用の処理回路６３により実現される。 Alternatively, the obstacle detection device 100 has a processor 61, a memory 62, and a processing circuit 63 (not shown). In this case, some of the functions of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15, and the output unit 16 are performed by the processor 61 and the memory 62. At the same time, the remaining functions are realized by the dedicated processing circuit 63.
　プロセッサ６１は、１個又は複数個のプロセッサにより構成されている。個々のプロセッサは、例えば、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）、ＧＰＵ（Ｇｒａｐｈｉｃｓ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）、マイクロプロセッサ、マイクロコントローラ又はＤＳＰ（Ｄｉｇｉｔａｌ　Ｓｉｇｎａｌ　Ｐｒｏｃｅｓｓｏｒ）を用いたものである。 The processor 61 is composed of one or a plurality of processors. As each processor, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a microprocessor, a microcontroller, or a DSP (Digital Signal Processor) is used.
　メモリ６２は、１個又は複数個の不揮発性メモリにより構成されている。または、メモリ６２は、１個又は複数個の不揮発性メモリ及び１個又は複数個の揮発性メモリにより構成されている。すなわち、メモリ６２は、１個又は複数個のメモリにより構成されている。個々のメモリは、例えば、半導体メモリ又は磁気ディスクを用いたものである。より具体的には、個々の揮発性メモリは、例えば、ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）を用いたものである。また、個々の不揮発性メモリは、例えば、ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、フラッシュメモリ、ＥＰＲＯＭ（Ｅｒａｓａｂｌｅ　Ｐｒｏｇｒａｍｍａｂｌｅ　Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、ＥＥＰＲＯＭ（Ｅｌｅｃｔｒｉｃａｌｌｙ　Ｅｒａｓａｂｌｅ　Ｐｒｏｇｒａｍｍａｂｌｅ　Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）、ソリッドステートドライブ又はハードディスクドライブを用いたものである。 The memory 62 is composed of one or a plurality of non-volatile memories. Alternatively, the memory 62 is composed of one or more non-volatile memories and one or more volatile memories. That is, the memory 62 is composed of one or a plurality of memories. Each memory uses, for example, a semiconductor memory or a magnetic disk. More specifically, each volatile memory uses, for example, a RAM (Random Access Memory). Further, the individual non-volatile memory is, for example, a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmory), an EEPROM (Electrically Erasable Programmory) drive, or a hard disk drive that uses a hard disk drive, a hard disk, or a drive solid state drive. Is.
　処理回路６３は、１個又は複数個のデジタル回路により構成されている。または、処理回路６３は、１個又は複数個のデジタル回路及び１個又は複数個のアナログ回路により構成されている。すなわち、処理回路６３は、１個又は複数個の処理回路により構成されている。個々の処理回路は、例えば、ＡＳＩＣ（Ａｐｐｌｉｃａｔｉｏｎ　Ｓｐｅｃｉｆｉｃ　Ｉｎｔｅｇｒａｔｅｄ　Ｃｉｒｃｕｉｔ）、ＰＬＤ（Ｐｒｏｇｒａｍｍａｂｌｅ　Ｌｏｇｉｃ　Ｄｅｖｉｃｅ）、ＦＰＧＡ（Ｆｉｅｌｄ　Ｐｒｏｇｒａｍｍａｂｌｅ　Ｇａｔｅ　Ａｒｒａｙ）、ＳｏＣ（Ｓｙｓｔｅｍ　ｏｎ　ａ　Ｃｈｉｐ）又はシステムＬＳＩ（Ｌａｒｇｅ　Ｓｃａｌｅ　Ｉｎｔｅｇｒａｔｉｏｎ）を用いたものである。 The processing circuit 63 is composed of one or a plurality of digital circuits. Alternatively, the processing circuit 63 is composed of one or more digital circuits and one or more analog circuits. That is, the processing circuit 63 is composed of one or a plurality of processing circuits. The individual processing circuits are, for example, ASIC (Application Special Integrated Circuit), PLD (Programmable Logic Device), FPGA (Field Programmable Gate Array), FPGA (Field Program Is.
　次に、図７及び図８を参照して、駐車支援装置２００の要部のハードウェア構成について説明する。 Next, the hardware configuration of the main part of the parking support device 200 will be described with reference to FIGS. 7 and 8.
　図７に示す如く、駐車支援装置２００は、プロセッサ７１及びメモリ７２を有している。メモリ７２には、駐車支援制御部２１の機能を実現するためのプログラムが記憶されている。かかるプログラムをプロセッサ７１が読み出して実行することにより、駐車支援制御部２１の機能が実現される。 As shown in FIG. 7, the parking support device 200 has a processor 71 and a memory 72. The memory 72 stores a program for realizing the function of the parking support control unit 21. The function of the parking support control unit 21 is realized by the processor 71 reading and executing such a program.
　または、図８に示す如く、駐車支援装置２００は、処理回路７３を有している。この場合、駐車支援制御部２１の機能が専用の処理回路７３により実現される。 Alternatively, as shown in FIG. 8, the parking support device 200 has a processing circuit 73. In this case, the function of the parking support control unit 21 is realized by the dedicated processing circuit 73.
　または、駐車支援装置２００は、プロセッサ７１、メモリ７２及び処理回路７３を有している（不図示）。この場合、駐車支援制御部２１の機能のうちの一部の機能がプロセッサ７１及びメモリ７２により実現されるとともに、残余の機能が専用の処理回路７３により実現される。 Alternatively, the parking support device 200 has a processor 71, a memory 72, and a processing circuit 73 (not shown). In this case, some of the functions of the parking support control unit 21 are realized by the processor 71 and the memory 72, and the remaining functions are realized by the dedicated processing circuit 73.
　プロセッサ７１は、１個又は複数個のプロセッサにより構成されている。個々のプロセッサは、例えば、ＣＰＵ、ＧＰＵ、マイクロプロセッサ、マイクロコントローラ又はＤＳＰを用いたものである。 The processor 71 is composed of one or a plurality of processors. The individual processors use, for example, CPUs, GPUs, microprocessors, microcontrollers or DSPs.
　メモリ７２は、１個又は複数個の不揮発性メモリにより構成されている。または、メモリ７２は、１個又は複数個の不揮発性メモリ及び１個又は複数個の揮発性メモリにより構成されている。すなわち、メモリ７２は、１個又は複数個のメモリにより構成されている。個々のメモリは、例えば、半導体メモリ又は磁気ディスクを用いたものである。より具体的には、個々の揮発性メモリは、例えば、ＲＡＭを用いたものである。また、個々の不揮発性メモリは、例えば、ＲＯＭ、フラッシュメモリ、ＥＰＲＯＭ、ＥＥＰＲＯＭ、ソリッドステートドライブ又はハードディスクドライブを用いたものである。 The memory 72 is composed of one or a plurality of non-volatile memories. Alternatively, the memory 72 is composed of one or more non-volatile memories and one or more volatile memories. That is, the memory 72 is composed of one or a plurality of memories. Each memory uses, for example, a semiconductor memory or a magnetic disk. More specifically, each volatile memory uses, for example, RAM. Further, each non-volatile memory uses, for example, a ROM, a flash memory, an EPROM, an EEPROM, a solid state drive, or a hard disk drive.
　処理回路７３は、１個又は複数個のデジタル回路により構成されている。または、処理回路７３は、１個又は複数個のデジタル回路及び１個又は複数個のアナログ回路により構成されている。すなわち、処理回路７３は、１個又は複数個の処理回路により構成されている。個々の処理回路は、例えば、ＡＳＩＣ、ＰＬＤ、ＦＰＧＡ、ＳｏＣ又はシステムＬＳＩを用いたものである。 The processing circuit 73 is composed of one or a plurality of digital circuits. Alternatively, the processing circuit 73 is composed of one or more digital circuits and one or more analog circuits. That is, the processing circuit 73 is composed of one or a plurality of processing circuits. The individual processing circuits use, for example, ASIC, PLD, FPGA, SoC or system LSI.
　次に、図９を参照して、駐車支援システム３００の動作について、障害物検知装置１００及び駐車支援装置２００の動作を中心に説明する。 Next, with reference to FIG. 9, the operation of the parking support system 300 will be described focusing on the operations of the obstacle detection device 100 and the parking support device 200.
　まず、障害物検知部１１が障害物検知処理を実行する（ステップＳＴ１）。次いで、非連続部検知部１２が非連続部検知処理を実行する（ステップＳＴ２）。次いで、解析領域抽出部１３が解析領域抽出処理を実行する（ステップＳＴ３）。次いで、グループ化部１４がグループ化処理を実行する（ステップＳＴ４）。次いで、識別部１５が識別処理を実行する（ステップＳＴ５）。次いで、出力部１６が出力処理を実行する（ステップＳＴ６）。次いで、駐車支援制御部２１が駐車支援制御を実行する（ステップＳＴ７）。 First, the obstacle detection unit 11 executes the obstacle detection process (step ST1). Next, the discontinuous portion detection unit 12 executes the discontinuous portion detection process (step ST2). Next, the analysis area extraction unit 13 executes the analysis area extraction process (step ST3). Next, the grouping unit 14 executes the grouping process (step ST4). Next, the identification unit 15 executes the identification process (step ST5). Next, the output unit 16 executes the output process (step ST6). Next, the parking support control unit 21 executes parking support control (step ST7).
　次に、図１０を参照して、非連続部検知部１２による非連続部ＤＰの検知方法の具体例について説明する。また、解析領域抽出部１３により抽出される解析領域ＡＡの具体例について説明する。 Next, with reference to FIG. 10, a specific example of the method of detecting the discontinuous portion DP by the discontinuous portion detecting unit 12 will be described. Further, a specific example of the analysis area AA extracted by the analysis area extraction unit 13 will be described.
　いま、図１０Ａに示す如く、側方領域ＬＡに４個の障害物Ｏ＿１～Ｏ＿４が存在している。障害物Ｏ＿１，Ｏ＿２の各々は、駐車車両により構成されている。障害物Ｏ＿３は、縁石により構成されている。障害物Ｏ＿４は、電柱又はポールにより構成されている。図中、ＴＲは、所定速度ＰＶ以下の速度Ｖによる車両１の移動経路を示している。 Now, as shown in FIG. 10A, there are four obstacles O_1 to O_4 in the lateral region LA. Each of the obstacles O_1 and O_2 is composed of parked vehicles. Obstacle O_3 is composed of curbs. Obstacle O_4 is composed of utility poles or poles. In the figure, TR indicates a movement route of the vehicle 1 at a speed V of a predetermined speed PV or less.
　この場合、障害物検知処理が実行されることにより、障害物群ＯＧに対応する複数個の反射点ＲＰ＿１，ＲＰ＿２，ＲＰ＿３，ＲＰ＿４が検知される。具体的には、例えば、障害物Ｏ＿１に対応する１０個の反射点ＲＰ＿１、障害物Ｏ＿２に対応する１０個の反射点ＲＰ＿２、障害物Ｏ＿３に対応する１２個の反射点ＲＰ＿３、及び障害物Ｏ＿４に対応する４個の反射点ＲＰ＿４が検知される。 In this case, by executing the obstacle detection process, a plurality of reflection points RP_1, RP_2, RP_3, and RP_4 corresponding to the obstacle group OG are detected. Specifically, for example, 10 reflection points RP_1 corresponding to the obstacle O_1, 10 reflection points RP_2 corresponding to the obstacle O_2, 12 reflection points RP_3 corresponding to the obstacle O_3, and an obstacle O_4. Four reflection points RP_4 corresponding to are detected.
　ここで、探査波は、空気中を次第に広がりながら伝搬する。このため、測距センサ２により送信されてから測距センサ２により受信されるまでの探査波の伝搬経路（いわゆる「パス」）は、複数存在し得るものである。 Here, the exploration wave propagates while gradually spreading in the air. Therefore, there may be a plurality of propagation paths (so-called “paths”) of the exploration wave from the transmission by the distance measurement sensor 2 to the reception by the distance measurement sensor 2.
　上記のとおり、測距センサ２は、探査波を所定の時間間隔ΔＴにて送信する。測距センサ２が探査波を１回送信したとき、当該送信された探査波がＮ個の障害物Ｏにより順次反射されることがある。これにより、第１番目～第Ｎ番目の反射波が順次受信されることがある。以下、第１番目～第Ｎ番目の反射波のうちの第ｎ番目の反射波を「第ｎ波」という。ここで、Ｎは、２以上の任意の整数である。また、ｎは、１～Ｎのうちの任意の整数である。 As described above, the ranging sensor 2 transmits the exploration wave at a predetermined time interval ΔT. When the distance measuring sensor 2 transmits the exploration wave once, the transmitted exploration wave may be sequentially reflected by N obstacles O. As a result, the first to Nth reflected waves may be sequentially received. Hereinafter, the nth reflected wave among the first to Nth reflected waves is referred to as an "nth wave". Here, N is an arbitrary integer of 2 or more. Further, n is an arbitrary integer from 1 to N.
　例えば、測距センサ２が探査波を１回送信したとき、当該送信された探査波が２個の障害物Ｏ＿３，Ｏ＿４により順次反射されることがある。これにより、第１波及び第２波が順次受信される。 For example, when the ranging sensor 2 transmits an exploration wave once, the transmitted exploration wave may be sequentially reflected by two obstacles O_3 and O_4. As a result, the first wave and the second wave are sequentially received.
　通常、車両１における測距センサ２の設置高さは、路面に対する数十センチメートル程度の高さに設定されている。このため、小さい高さＨを有する障害物Ｏ（例えば路上障害物又は路面障害物）については、測距センサ２が探査波を送信したとき、当該送信された探査波が照射されないことがある。この結果、小さい高さＨを有する障害物Ｏについては、測距センサ２により反射波が受信されないことがある。 Normally, the installation height of the distance measuring sensor 2 in the vehicle 1 is set to a height of about several tens of centimeters with respect to the road surface. Therefore, for an obstacle O having a small height H (for example, a road obstacle or a road surface obstacle), when the distance measuring sensor 2 transmits a search wave, the transmitted search wave may not be irradiated. As a result, the reflected wave may not be received by the distance measuring sensor 2 for the obstacle O having a small height H.
　このため、小さい高さＨを有する障害物Ｏに対する奥側に大きい高さＨを有する障害物Ｏ（例えば走行障害物）が存在するとき、大きい高さＨを有する障害物Ｏに対応する複数個の反射点ＲＰには、第１波に対応する１個以上の反射点ＲＰと第２波に対応する１個以上の反射点ＲＰとが含まれる状態となることがある。 Therefore, when there is an obstacle O having a large height H (for example, a traveling obstacle) on the back side of the obstacle O having a small height H, a plurality of obstacles O corresponding to the obstacle O having a large height H are present. The reflection point RP may include one or more reflection point RPs corresponding to the first wave and one or more reflection point RPs corresponding to the second wave.
　図１０Ａに示す例においては、障害物Ｏ＿４に対応する４個の反射点ＲＰ＿４に、第１波に対応する１個の反射点ＲＰ＿４と第２波に対応する３個の反射点ＲＰ＿４とが含まれている。すなわち、図中、丸印（○）は、第１波に対応する個々の反射点ＲＰを示している。また、図中、三角印（△）は、第２波に対応する個々の反射点ＲＰを示している。 In the example shown in FIG. 10A, the four reflection points RP_4 corresponding to the obstacle O_4 include one reflection point RP_4 corresponding to the first wave and three reflection points RP_4 corresponding to the second wave. It has been. That is, in the figure, circles (◯) indicate individual reflection point RPs corresponding to the first wave. Further, in the figure, triangle marks (Δ) indicate individual reflection point RPs corresponding to the second wave.
　以下、障害物群ＯＧに対応する複数個の反射点ＲＰのうちの第ｎ波に対応する複数個の反射点ＲＰのうちの互いに隣接する各２個の反射点ＲＰ間の距離ｄを「反射点間距離」という。反射点間距離ｄは、ＸＹ座標系におけるユークリッド距離である。図１０Ｂは、第１波に対応する複数個の反射点ＲＰについて、時間に対する反射点間距離ｄの例を示している。ここで、時間軸は、ＸＹ座標系におけるＸ軸に対応している。 Hereinafter, the distance d between each of the two adjacent reflection point RPs among the plurality of reflection point RPs corresponding to the nth wave of the plurality of reflection point RPs corresponding to the obstacle group OG is “reflected”. It is called "point-to-point distance". The distance d between reflection points is the Euclidean distance in the XY coordinate system. FIG. 10B shows an example of the distance d between reflection points with respect to time for a plurality of reflection point RPs corresponding to the first wave. Here, the time axis corresponds to the X axis in the XY coordinate system.
　非連続部検知部１２は、反射点間距離ｄを算出する。非連続部検知部１２は、当該算出された反射点間距離ｄについて、以下の条件（以下「第１条件」という。）が満たされたとき、非連続部ＤＰを検知する。すなわち、第１条件は、反射点間距離ｄが所定の閾値ｄ＿ｔｈを超えるという条件である。 The discontinuous portion detection unit 12 calculates the distance d between reflection points. The discontinuous portion detecting unit 12 detects the discontinuous portion DP when the following conditions (hereinafter referred to as “first condition”) are satisfied with respect to the calculated distance d between reflection points. That is, the first condition is that the distance d between reflection points exceeds a predetermined threshold value d_th.
　図１０Ｂに示す例においては、時刻ｔ＿１にて反射点間距離ｄが閾値ｄ＿ｔｈを超える。これにより、１個の非連続部ＤＰ＿１が検知される。次いで、時刻ｔ＿２にて反射点間距離ｄが閾値ｄ＿ｔｈを超える。これにより、１個の非連続部ＤＰ＿２が検知される。 In the example shown in FIG. 10B, the distance d between reflection points exceeds the threshold value d_th at time t_1. As a result, one discontinuous portion DP_1 is detected. Then, at time t_2, the distance d between reflection points exceeds the threshold value d_th. As a result, one discontinuous portion DP_2 is detected.
　すなわち、図１０に示す例においては、２個の非連続部ＤＰ＿１，ＤＰ＿２が検知される。２個の非連続部ＤＰ＿１，ＤＰ＿２により、側方領域ＬＡが３個の領域に分割される。これにより、３個の解析領域ＡＡ＿１，ＡＡ＿２，ＡＡ＿３が抽出される。 That is, in the example shown in FIG. 10, two discontinuous portions DP_1 and DP_2 are detected. The side region LA is divided into three regions by the two discontinuous portions DP_1 and DP_2. As a result, three analysis regions AA_1, AA_2, and AA_3 are extracted.
　次に、図１１～図１８を参照して、グループ化部１４による反射点群ＰＧの設定方法の具体例について説明する。 Next, with reference to FIGS. 11 to 18, a specific example of a method of setting the reflection point group PG by the grouping unit 14 will be described.
　図１１は、１個の解析領域ＡＡ＿２に含まれる複数個の反射点ＲＰ＿３，ＲＰ＿４の例を示している。図１１に示す如く、障害物Ｏ＿３に対応する１４個の反射点ＲＰ＿３及び障害物Ｏ＿４に対応する４個の反射点ＲＰ＿４が解析領域ＡＡ＿２に含まれている。 FIG. 11 shows an example of a plurality of reflection points RP_3 and RP_4 included in one analysis area AA_2. As shown in FIG. 11, 14 reflection points RP_3 corresponding to the obstacle O_3 and 4 reflection points RP_4 corresponding to the obstacle O_4 are included in the analysis region AA_2.
　この場合、まず、第１解析部４１は、解析領域ＡＡ＿２について、複数個の反射点ＲＰ＿３，ＲＰ＿４に係る度数分布ＦＤ＿Ｙを作成する。図１２は、度数分布ＦＤ＿Ｙの例を示している。図１２に示す如く、度数分布ＦＤ＿Ｙは、複数個の反射点ＲＰ＿３に対応する度数（図中Ｆ＿Ｙ＿１）及び複数個の反射点ＲＰ＿４に対応する度数（図中Ｆ＿Ｙ＿２）を含むものとなる。第１解析部４１は、度数分布ＦＤ＿Ｙに対するピーク分離処理を実行する。これにより、２個の度数群ＦＧ＿Ｙ＿１，ＦＧ＿Ｙ＿２が設定される。すなわち、度数群ＦＧ＿Ｙ＿１は、複数個の反射点ＲＰ＿３に対応するものである。また、度数群ＦＧ＿Ｙ＿２は、複数個の反射点ＲＰ＿４に対応するものである。 In this case, first, the first analysis unit 41 creates a frequency distribution FD_Y related to a plurality of reflection points RP_3 and RP_4 in the analysis region AA_2. FIG. 12 shows an example of the frequency distribution FD_Y. As shown in FIG. 12, the frequency distribution FD_Y includes the frequency corresponding to the plurality of reflection points RP_3 (F_Y_1 in the figure) and the frequency corresponding to the plurality of reflection points RP_4 (F_Y_2 in the figure). The first analysis unit 41 executes peak separation processing for the frequency distribution FD_Y. As a result, two frequency groups FG_Y_1 and FG_Y_2 are set. That is, the frequency group FG_Y_1 corresponds to a plurality of reflection points RP_3. Further, the frequency group FG_Y_2 corresponds to a plurality of reflection points RP_4.
　次いで、第２解析部４２は、度数群ＦＧ＿Ｙ＿１に対応する複数個の反射点ＲＰ＿３に係る度数分布ＦＤ＿Ｘ＿１を作成する。図１３は、度数分布ＦＤ＿Ｘ＿１の例を示している。図１３に示す如く、度数分布ＦＤ＿Ｘ＿１は、複数個の反射点ＲＰ＿３に対応する度数（図中Ｆ＿Ｘ＿１）を含むものとなる。第２解析部４２は、度数分布ＦＤ＿Ｘ＿１に対するピーク分離処理を実行する。これにより、１個の度数群ＦＧ＿Ｘ＿１が設定される。すなわち、度数群ＦＧ＿Ｘ＿１は、複数個の反射点ＲＰ＿３に対応するものである。 Next, the second analysis unit 42 creates a frequency distribution FD_X_1 related to a plurality of reflection points RP_3 corresponding to the frequency group FG_Y_1. FIG. 13 shows an example of the frequency distribution FD_X_1. As shown in FIG. 13, the frequency distribution FD_X_1 includes frequencies (F_X_1 in the figure) corresponding to a plurality of reflection points RP_3. The second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_1. As a result, one frequency group FG_X_1 is set. That is, the frequency group FG_X_1 corresponds to a plurality of reflection points RP_3.
　次いで、第２解析部４２は、度数群ＦＧ＿Ｙ＿２に対応する複数個の反射点ＲＰ＿４に係る度数分布ＦＤ＿Ｘ＿２を作成する。図１４は、度数分布ＦＤ＿Ｘ＿２の例を示している。図１４に示す如く、度数分布ＦＤ＿Ｘ＿２は、複数個の反射点ＲＰ＿４に対応する度数（図中Ｆ＿Ｘ＿２）を含むものとなる。第２解析部４２は、度数分布ＦＤ＿Ｘ＿２に対するピーク分離処理を実行する。これにより、１個の度数群ＦＧ＿Ｘ＿２が設定される。すなわち、度数群ＦＧ＿Ｘ＿２は、複数個の反射点ＲＰ＿４に対応するものである。 Next, the second analysis unit 42 creates a frequency distribution FD_X_2 related to a plurality of reflection points RP_4 corresponding to the frequency group FG_Y_2. FIG. 14 shows an example of the frequency distribution FD_X_2. As shown in FIG. 14, the frequency distribution FD_X_2 includes frequencies (F_X_2 in the figure) corresponding to a plurality of reflection points RP_4. The second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_2. As a result, one frequency group FG_X_2 is set. That is, the frequency group FG_X_2 corresponds to a plurality of reflection points RP_4.
　次いで、グループ化部１４は、度数群ＦＧ＿Ｙ＿１及び度数群ＦＧ＿Ｘ＿１に対応する１個の反射点群ＰＧ＿１を設定する。また、グループ化部１４は、度数群ＦＧ＿Ｙ＿２及び度数群ＦＧ＿Ｘ＿２に対応する１個の反射点群ＰＧ＿２を設定する。これにより、図１１に示す如く、２個の障害物Ｏ＿３，Ｏ＿４と一対一に対応する２個の反射点群ＰＧ＿１，ＰＧ＿２が設定される。 Next, the grouping unit 14 sets one reflection point group PG_1 corresponding to the frequency group FG_Y_1 and the frequency group FG_X_1. Further, the grouping unit 14 sets one reflection point group PG_2 corresponding to the frequency group FG_Y_2 and the frequency group FG_X_2. As a result, as shown in FIG. 11, two reflection point groups PG_1 and PG_2 corresponding to two obstacles O_3 and O_4 are set one-to-one.
　図１５は、１個の解析領域ＡＡ＿２に含まれる複数個の反射点ＲＰ＿３，ＲＰ＿４，ＲＰ＿５の例を示している。図１１に示す如く、障害物Ｏ＿３に対応する２１個の反射点ＲＰ＿３、障害物Ｏ＿４に対応する４個の反射点ＲＰ＿４、及び障害物Ｏ＿５に対応する４個の反射点ＲＰ＿５が解析領域ＡＡ＿２に含まれている。障害物Ｏ＿５は、例えば、看板により構成されている。 FIG. 15 shows an example of a plurality of reflection points RP_3, RP_4, and RP_5 included in one analysis area AA_2. As shown in FIG. 11, 21 reflection points RP_3 corresponding to the obstacle O_3, 4 reflection points RP_4 corresponding to the obstacle O_4, and 4 reflection points RP_5 corresponding to the obstacle O_5 are located in the analysis region AA_2. include. The obstacle O_5 is composed of, for example, a signboard.
　この場合、まず、第１解析部４１は、解析領域ＡＡ＿２について、複数個の反射点ＲＰ＿３，ＲＰ＿４，ＲＰ＿５に係る度数分布ＦＤ＿Ｙを作成する。図１６は、度数分布ＦＤ＿Ｙの例を示している。図１６に示す如く、度数分布ＦＤ＿Ｙは、複数個の反射点ＲＰ＿３に対応する度数（図中Ｆ＿Ｙ＿１）及び複数個の反射点ＲＰ＿４，ＲＰ＿５に対応する度数（図中Ｆ＿Ｙ＿２）を含むものとなる。第１解析部４１は、度数分布ＦＤ＿Ｙに対するピーク分離処理を実行する。これにより、２個の度数群ＦＧ＿Ｙ＿１，ＦＧ＿Ｙ＿２が設定される。すなわち、度数群ＦＧ＿Ｙ＿１は、複数個の反射点ＲＰ＿３に対応するものである。また、度数群ＦＧ＿Ｙ＿２は、複数個の反射点ＲＰ＿４，ＲＰ＿５に対応するものである。 In this case, first, the first analysis unit 41 creates a frequency distribution FD_Y related to a plurality of reflection points RP_3, RP_4, and RP_5 for the analysis area AA_2. FIG. 16 shows an example of the frequency distribution FD_Y. As shown in FIG. 16, the frequency distribution FD_Y includes the frequency corresponding to the plurality of reflection points RP_3 (F_Y_1 in the figure) and the frequency corresponding to the plurality of reflection points RP_4 and RP_5 (F_Y_2 in the figure). The first analysis unit 41 executes peak separation processing for the frequency distribution FD_Y. As a result, two frequency groups FG_Y_1 and FG_Y_2 are set. That is, the frequency group FG_Y_1 corresponds to a plurality of reflection points RP_3. Further, the frequency group FG_Y_2 corresponds to a plurality of reflection points RP_4 and RP_5.
　次いで、第２解析部４２は、度数群ＦＧ＿Ｙ＿１に対応する複数個の反射点ＲＰ＿３に係る度数分布ＦＤ＿Ｘ＿１を作成する。図１７は、度数分布ＦＤ＿Ｘ＿１の例を示している。図１７に示す如く、度数分布ＦＤ＿Ｘ＿１は、複数個の反射点ＲＰ＿３に対応する度数（図中Ｆ＿Ｘ＿１）を含むものとなる。第２解析部４２は、度数分布ＦＤ＿Ｘ＿１に対するピーク分離処理を実行する。これにより、１個の度数群ＦＧ＿Ｘ＿１が設定される。すなわち、度数群ＦＧ＿Ｘ＿１は、複数個の反射点ＲＰ＿３に対応するものである。 Next, the second analysis unit 42 creates a frequency distribution FD_X_1 related to a plurality of reflection points RP_3 corresponding to the frequency group FG_Y_1. FIG. 17 shows an example of the frequency distribution FD_X_1. As shown in FIG. 17, the frequency distribution FD_X_1 includes frequencies (F_X_1 in the figure) corresponding to a plurality of reflection points RP_3. The second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_1. As a result, one frequency group FG_X_1 is set. That is, the frequency group FG_X_1 corresponds to a plurality of reflection points RP_3.
　次いで、第２解析部４２は、度数群ＦＧ＿Ｙ＿２に対応する複数個の反射点ＲＰ＿４，ＲＰ＿５に係る度数分布ＦＤ＿Ｘ＿２を作成する。図１８は、度数分布ＦＤ＿Ｘ＿２の例を示している。図１８に示す如く、度数分布ＦＤ＿Ｘ＿２は、複数個の反射点ＲＰ＿４に対応する度数（図中Ｆ＿Ｘ＿２＿１）及び複数個の反射点ＲＰ＿５に対応する度数（図中Ｆ＿Ｘ＿２＿２）を含むものとなる。第２解析部４２は、度数分布ＦＤ＿Ｘ＿２に対するピーク分離処理を実行する。これにより、２個の度数群ＦＧ＿Ｘ＿２＿１，ＦＧ＿Ｘ＿２＿２が設定される。すなわち、度数群ＦＧ＿Ｘ＿２＿１は、複数個の反射点ＲＰ＿４に対応するものである。また、度数群ＦＧ＿Ｘ＿２＿２は、複数個の反射点ＲＰ＿５に対応するものである。 Next, the second analysis unit 42 creates a frequency distribution FD_X_2 related to a plurality of reflection points RP_4 and RP_5 corresponding to the frequency group FG_Y_2. FIG. 18 shows an example of the frequency distribution FD_X_2. As shown in FIG. 18, the frequency distribution FD_X_2 includes a frequency corresponding to a plurality of reflection points RP_4 (F_X_2_1 in the figure) and a frequency corresponding to the plurality of reflection points RP_5 (F_X_2_2 in the figure). The second analysis unit 42 executes peak separation processing for the frequency distribution FD_X_2. As a result, two frequency groups FG_X_2_1 and FG_X_2_2 are set. That is, the frequency group FG_X_2_1 corresponds to a plurality of reflection points RP_4. Further, the frequency group FG_X_2_2 corresponds to a plurality of reflection points RP_5.
　次いで、グループ化部１４は、度数群ＦＧ＿Ｙ＿１及び度数群ＦＧ＿Ｘ＿１に対応する１個の反射点群ＰＧ＿１を設定する。また、グループ化部１４は、度数群ＦＧ＿Ｙ＿２及び度数群ＦＧ＿Ｘ＿２＿１に対応する１個の反射点群ＰＧ＿２＿１を設定する。また、グループ化部１４は、度数群ＦＧ＿Ｙ＿２及び度数群ＦＧ＿Ｘ＿２＿２に対応する１個の反射点群ＰＧ＿２＿２を設定する。これにより、図１５に示す如く、３個の障害物Ｏ＿３，Ｏ＿４，Ｏ＿５と一対一に対応する３個の反射点群ＰＧ＿１，ＰＧ＿２＿１，ＰＧ＿２＿２が設定される。 Next, the grouping unit 14 sets one reflection point group PG_1 corresponding to the frequency group FG_Y_1 and the frequency group FG_X_1. Further, the grouping unit 14 sets one reflection point group PG_2_1 corresponding to the frequency group FG_Y_1 and the frequency group FG_X_2_1. Further, the grouping unit 14 sets one reflection point group PG_2_2 corresponding to the frequency group FG_Y_2 and the frequency group FG_X_2_2. As a result, as shown in FIG. 15, three reflection point groups PG_1, PG_2_1, PG_2, which correspond one-to-one with the three obstacles O_3, O_4, O_5 are set.
　ここで、第１解析部４１及び第２解析部４２の各々におけるピーク分離処理には、公知の種々の技術を用いることができる。例えば、度数Ｆが連続的に所定値を超えている範囲が１個の度数群ＦＧとして抽出されるものであっても良い。また、例えば、ｋ近傍法等のクラスタリング手法が用いられるものであっても良い。 Here, various known techniques can be used for the peak separation processing in each of the first analysis unit 41 and the second analysis unit 42. For example, a range in which the frequency F continuously exceeds a predetermined value may be extracted as one frequency group FG. Further, for example, a clustering method such as the k-nearest neighbor method may be used.
　次に、図１９及び図２０を参照して、高さ判断部５３による個々の障害物Ｏの高さＨの判断方法の具体例について説明する。 Next, with reference to FIGS. 19 and 20, a specific example of a method for determining the height H of each obstacle O by the height determination unit 53 will be described.
　高さ判断部５３は、個々の反射点ＲＰに対応する反射点情報に含まれる波形情報を用いて、個々の反射点ＲＰに対応する受信信号ＲＳの強度（以下「受信信号強度」という。）ＳＳに関する２個の特徴量ＦＡ１，ＦＡ２を検知する。特徴量ＦＡ１，ＦＡ２の各々は、受信信号強度ＳＳに対する相関を有するものである。 The height determination unit 53 uses the waveform information included in the reflection point information corresponding to each reflection point RP, and the intensity of the received signal RS corresponding to each reflection point RP (hereinafter referred to as “received signal intensity”). Two feature quantities FA1 and FA2 related to SS are detected. Each of the feature quantities FA1 and FA2 has a correlation with the received signal strength SS.
　以下、特徴量ＦＡ１を「第１特徴量」という。また、特徴量ＦＡ２を「第２特徴量」という。また、時間に対する受信信号強度ＳＳを示す波形を「受信信号波形」という。図１９は、受信信号波形の例を示している。 Hereinafter, the feature amount FA1 is referred to as "first feature amount". Further, the feature amount FA2 is referred to as a "second feature amount". Further, a waveform indicating the received signal strength SS with respect to time is referred to as a “received signal waveform”. FIG. 19 shows an example of the received signal waveform.
　具体的には、例えば、高さ判断部５３は、受信信号波形における受信信号強度ＳＳが所定の閾値ＳＳ＿ｔｈを超えている部位の幅（以下「波形幅」という。）ＷＷを検知する。高さ判断部５３は、当該検知された波形幅ＷＷを第１特徴量ＦＡ１又は第２特徴量ＦＡ２に用いる。 Specifically, for example, the height determination unit 53 detects the width (hereinafter referred to as “waveform width”) WW of the portion where the received signal strength SS in the received signal waveform exceeds a predetermined threshold value SS_th. The height determination unit 53 uses the detected waveform width WW for the first feature amount FA1 or the second feature amount FA2.
　また、例えば、高さ判断部５３は、受信信号波形における受信信号強度ＳＳが閾値ＳＳ＿ｔｈを超えている部位の面積（以下「波形面積」という。）ＷＡを検知する。高さ判断部５３は、当該検知された波形面積ＷＡを第１特徴量ＦＡ１又は第２特徴量ＦＡ２に用いる。 Further, for example, the height determination unit 53 detects the area (hereinafter referred to as “waveform area”) WA of the portion where the received signal strength SS in the received signal waveform exceeds the threshold value SS_th. The height determination unit 53 uses the detected waveform area WA for the first feature amount FA1 or the second feature amount FA2.
　また、例えば、高さ判断部５３は、受信信号波形における受信信号強度ＳＳが閾値ＳＳ＿ｔｈを超えている部位の高さの最大値（以下「波形高さ」という。）ＷＨを検知する。高さ判断部５３は、当該検知された波形高さＷＨを第１特徴量ＦＡ１又は第２特徴量ＦＡ２に用いる。 Further, for example, the height determination unit 53 detects the maximum value (hereinafter referred to as “waveform height”) WH of the height of the portion where the received signal strength SS in the received signal waveform exceeds the threshold value SS_th. The height determination unit 53 uses the detected waveform height WH for the first feature amount FA1 or the second feature amount FA2.
　すなわち、高さ判断部５３は、個々の反射点ＲＰについて、波形幅ＷＷ、波形面積ＷＡ及び波形高さＷＨのうちのいずれか２個の値を検知する。高さ判断部５３は、当該検知された２個の値のうちの１個の値を第１特徴量ＦＡ１に用いるとともに、当該検知された２個の値のうちの他の１個の値を第２特徴量ＦＡ２に用いる。 That is, the height determination unit 53 detects any two values of the waveform width WW, the waveform area WA, and the waveform height WH for each reflection point RP. The height determination unit 53 uses one of the two detected values for the first feature amount FA1 and uses the other one of the two detected values. Used for the second feature amount FA2.
　上記のとおり、個々の反射点群ＰＧは、複数個の反射点ＲＰを含むものである。このため、個々の反射点群ＰＧについて、複数個の反射点ＲＰに対応する複数個の第１特徴量ＦＡ１が検知されるとともに、複数個の反射点ＲＰに対応する複数個の第２特徴量ＦＡ２が検知される。高さ判断部５３は、個々の反射点群ＰＧについて、対応する複数個の第１特徴量ＦＡ１による統計量（以下「第１統計量」ということがある。）Ｓ１を算出する。また、高さ判断部５３は、個々の反射点群ＰＧについて、対応する複数個の第２特徴量ＦＡ２による統計量（以下「第２統計値」ということがある。）Ｓ２を算出する。 As described above, each reflection point group PG includes a plurality of reflection point RPs. Therefore, for each reflection point group PG, a plurality of first feature quantities FA1 corresponding to the plurality of reflection point RPs are detected, and a plurality of second feature quantities corresponding to the plurality of reflection point RPs are detected. FA2 is detected. The height determination unit 53 calculates a statistic (hereinafter, sometimes referred to as “first statistic”) S1 based on a plurality of corresponding first feature amounts FA1 for each reflection point group PG. Further, the height determination unit 53 calculates a statistic (hereinafter, may be referred to as “second statistic value”) S2 based on a plurality of corresponding second feature amounts FA2 for each reflection point group PG.
　ここで、第１統計量Ｓ１には、種々の統計量を用いることができる。例えば、第１統計量Ｓ１には、複数個の第１特徴量ＦＡ１による瞬時値、平均値、分散値又は中央値を用いることができる。または、例えば、第１統計量Ｓ１には、これらの値のうちの任意の２個以上の値を組み合わせてなる値を用いることができる。 Here, various statistics can be used for the first statistic S1. For example, for the first statistic S1, an instantaneous value, an average value, a variance value, or a median value obtained by a plurality of first feature quantities FA1 can be used. Alternatively, for example, for the first statistic S1, a value obtained by combining any two or more of these values can be used.
　同様に、第２統計量Ｓ２には、種々の統計量を用いることができる。例えば、第２統計量Ｓ２には、複数個の第２特徴量ＦＡ２による瞬時値、平均値、分散値又は中央値を用いることができる。または、例えば、第２統計量Ｓ２には、これらの値のうちの任意の２個以上の値を組み合わせてなる値を用いることができる。 Similarly, various statistics can be used for the second statistic S2. For example, for the second statistic S2, an instantaneous value, an average value, a variance value, or a median value obtained by a plurality of second feature quantities FA2 can be used. Alternatively, for example, for the second statistic S2, a value obtained by combining any two or more of these values can be used.
　以下、第１統計量Ｓ１に対応する第１軸を有し、かつ、第２統計量Ｓ２に対応する第２軸を有する座標系を「特徴量座標系」という。高さ判断部５３には、特徴量座標系における閾値Ｓ＿ｔｈ＿１，Ｓ＿ｔｈ＿２が予め設定されている。図２０は、閾値Ｓ＿ｔｈ＿１，Ｓ＿ｔｈ＿２の例を示している。ここで、閾値Ｓ＿ｔｈ＿１は、路面障害物と路上障害物との識別に係る閾値Ｈ＿ｔｈ＿１に対応するものである。また、閾値Ｓ＿ｔｈ＿２は、路上障害物と走行障害物との識別に係る閾値Ｈ＿ｔｈ＿２に対応するものである。 Hereinafter, a coordinate system having a first axis corresponding to the first statistic S1 and having a second axis corresponding to the second statistic S2 is referred to as a "feature amount coordinate system". The height determination unit 53 is preset with threshold values S_th_1 and S_th_2 in the feature coordinate system. FIG. 20 shows an example of the threshold values S_th_1 and S_th_2. Here, the threshold value S_th_1 corresponds to the threshold value H_th_1 related to the discrimination between the road surface obstacle and the road obstacle. Further, the threshold value S_th_2 corresponds to the threshold value H_th_2 related to the discrimination between the road obstacle and the traveling obstacle.
　高さ判断部５３は、個々の反射点群ＰＧに対応する統計量Ｓ１，Ｓ２を特徴量座標系にプロットする。当該プロットされた統計量Ｓ１，Ｓ２が閾値Ｓ＿ｔｈ＿１以下の範囲Ｒ＿１に含まれる場合、高さ判断部５３は、対応する障害物Ｏが路面障害物であると判断する。当該プロットされた統計量Ｓ１，Ｓ２が閾値Ｓ＿ｔｈ＿１，Ｓ＿ｔｈ＿２間の範囲Ｒ＿２に含まれる場合、高さ判断部５３は、対応する障害物Ｏが路上障害物であると判断する。当該プロットされた統計量Ｓ１，Ｓ２が閾値Ｓ＿ｔｈ＿２以上の範囲Ｒ＿３に含まれる場合、高さ判断部５３は、対応する障害物Ｏが走行障害物であると判断する。 The height determination unit 53 plots the statistics S1 and S2 corresponding to the individual reflection point cloud PGs in the feature coordinate system. When the plotted statistics S1 and S2 are included in the range R_1 equal to or less than the threshold value S_th_1, the height determination unit 53 determines that the corresponding obstacle O is a road surface obstacle. When the plotted statistics S1 and S2 are included in the range R_2 between the threshold values S_th_1 and S_th_2, the height determination unit 53 determines that the corresponding obstacle O is a road obstacle. When the plotted statistics S1 and S2 are included in the range R_3 of the threshold value S_th_2 or more, the height determination unit 53 determines that the corresponding obstacle O is a traveling obstacle.
　例えば、ある１個の反射点群ＰＧに対応する統計量Ｓ１＿１，Ｓ２＿１が範囲Ｒ＿１に含まれる場合（図２０参照）、高さ判断部５３は、対応する障害物Ｏが路面障害物であると判別する。また、他の１個の反射点群ＰＧに対応する統計量Ｓ１＿２，Ｓ２＿２が範囲Ｒ＿２に含まれる場合（図２０参照）、高さ判断部５３は、対応する障害物Ｏが路上障害物であると判別する。また、他の１個の反射点群ＰＧに対応する統計量Ｓ１＿３，Ｓ２＿３が範囲Ｒ＿３に含まれる場合（図２０参照）、高さ判断部５３は、対応する障害物Ｏが走行障害物であると判別する。 For example, when the statistics S1-1 and S2_1 corresponding to a certain reflection point group PG are included in the range R_1 (see FIG. 20), the height determination unit 53 determines that the corresponding obstacle O is a road surface obstacle. Determine. Further, when the statistics S1-2 and S2_2 corresponding to the other one reflection point group PG are included in the range R_2 (see FIG. 20), the height determination unit 53 indicates that the corresponding obstacle O is a road obstacle. To determine. Further, when the statistics S1_3 and S2_3 corresponding to the other one reflection point group PG are included in the range R_3 (see FIG. 20), the height determination unit 53 indicates that the corresponding obstacle O is a traveling obstacle. To determine.
　次に、識別部１５による個々の障害物Ｏが縁石であるか否かの識別方法の具体例について説明する。また、識別部１５による個々の障害物Ｏが駐車障害物であるか否かの識別方法の具体例について説明する。 Next, a specific example of a method of identifying whether or not each obstacle O by the identification unit 15 is a curb will be described. Further, a specific example of a method of identifying whether or not each obstacle O by the identification unit 15 is a parking obstacle will be described.
〈縁石に係る識別方法の具体例〉
　ある障害物Ｏについて、幅判断部５１により広幅障害物であると判断されて、かつ、高さ判断部５３により路上障害物であると判断されたものとする。この場合、識別部１５は、この障害物Ｏが縁石であると識別する。そうでない場合、識別部１５は、この障害物Ｏが縁石でないと識別する。 <Specific example of identification method for curbs>
It is assumed that the width determination unit 51 determines that a certain obstacle O is a wide obstacle, and the height determination unit 53 determines that it is a road obstacle. In this case, the identification unit 15 identifies that the obstacle O is a curb. If not, the identification unit 15 identifies that the obstacle O is not a curb.
〈駐車障害物に係る判断方法の第１具体例〉
　ある障害物Ｏについて、高さ判断部５３により走行障害物であると判断されたものとする。この場合、識別部１５は、この障害物Ｏが駐車障害物であると判断する。そうでない場合、識別部１５は、この障害物Ｏが駐車障害物でないと識別する。 <First specific example of the judgment method for parking obstacles>
It is assumed that a certain obstacle O is determined to be a running obstacle by the height determination unit 53. In this case, the identification unit 15 determines that the obstacle O is a parking obstacle. If not, the identification unit 15 identifies that the obstacle O is not a parking obstacle.
　すなわち、側方領域ＬＡにおける走行障害物は、車両１の駐車の妨げとなる蓋然性が高い。そこで、識別部１５は、かかる走行障害物が駐車障害物であると識別するのである。 That is, there is a high possibility that a traveling obstacle in the lateral region LA will hinder the parking of the vehicle 1. Therefore, the identification unit 15 identifies that the traveling obstacle is a parking obstacle.
〈駐車障害物に係る判断方法の第２具体例〉
　第１の障害物Ｏについて、幅判断部５１により広幅障害物であると判断されて、かつ、高さ判断部５３により路上障害物又は路面障害物であると判断されたものとする。また、第２の障害物Ｏについて、幅判断部５１により狭幅障害物であると判断されたものとする。また、位置判断部５２により、第１の障害物Ｏに対する奥側に第２の障害物Ｏが位置していると判断されたものとする。 <Second specific example of the judgment method for parking obstacles>
It is assumed that the width determination unit 51 determines that the first obstacle O is a wide obstacle, and the height determination unit 53 determines that it is a road obstacle or a road surface obstacle. Further, it is assumed that the width determination unit 51 determines that the second obstacle O is a narrow obstacle. Further, it is assumed that the position determination unit 52 determines that the second obstacle O is located behind the first obstacle O.
　この場合、識別部１５は、第１の障害物Ｏが駐車障害物でないと識別するとともに、第２の障害物Ｏが駐車障害物であると識別する。換言すれば、識別部１５は、高さ判断部５３による第２の障害物Ｏの高さＨの判断結果にかかわらず、第２の障害物Ｏが駐車障害物であると識別する。 In this case, the identification unit 15 identifies that the first obstacle O is not a parking obstacle and that the second obstacle O is a parking obstacle. In other words, the identification unit 15 identifies the second obstacle O as a parking obstacle regardless of the determination result of the height H of the second obstacle O by the height determination unit 53.
　すなわち、狭幅障害物については、対応する反射点ＲＰの個数が少ないことにより、高さ判断部５３による高さＨの判断精度が低下する可能性がある。他方、通常、縁石又は段差に対する奥側に位置する狭幅障害物は、走行障害物（例えば電柱、ポール又は看板）である蓋然性が高い。そこで、識別部１５は、第２の障害物Ｏについて、高さＨの判断結果にかかわらず、駐車障害物であると識別するのである。 That is, for narrow obstacles, the accuracy of determining the height H by the height determining unit 53 may decrease due to the small number of corresponding reflection point RPs. On the other hand, usually, a narrow obstacle located on the back side of a curb or a step is likely to be a traveling obstacle (for example, a utility pole, a pole, or a signboard). Therefore, the identification unit 15 identifies the second obstacle O as a parking obstacle regardless of the determination result of the height H.
〈駐車障害物に係る判断方法の第３具体例〉
　第１の障害物Ｏについて、幅判断部５１により広幅障害物であると判断されたものとする。また、位置判断部５２により、第１の障害物Ｏに対する奥側に第２の障害物Ｏが位置していると判断されたものとする。 <Third specific example of the judgment method for parking obstacles>
It is assumed that the width determination unit 51 determines that the first obstacle O is a wide obstacle. Further, it is assumed that the position determination unit 52 determines that the second obstacle O is located behind the first obstacle O.
　この場合、識別部１５は、第１の障害物Ｏが駐車障害物でないと識別する。換言すれば、識別部１５は、高さ判断部５３による第１の障害物Ｏの高さＨの判断結果にかかわらず、第１の障害物Ｏが駐車障害物でないと識別する。 In this case, the identification unit 15 identifies that the first obstacle O is not a parking obstacle. In other words, the identification unit 15 identifies that the first obstacle O is not a parking obstacle, regardless of the determination result of the height H of the first obstacle O by the height determination unit 53.
　すなわち、通常、走行障害物は、車両１における測距センサ２の取付け高さよりも大きい高さＨを有している。このため、広幅障害物に対する奥側に他の障害物が存在する場合において、当該広幅障害物が走行障害物であるとき、当該他の障害物による反射波が測距センサ２により受信されることはないと考えられる。そこで、識別部１５は、第１の障害物Ｏについて、高さＨの判断結果にかかわらず、駐車障害物でないと識別するのである。 That is, the traveling obstacle usually has a height H larger than the mounting height of the distance measuring sensor 2 in the vehicle 1. Therefore, when there is another obstacle behind the wide obstacle and the wide obstacle is a traveling obstacle, the reflected wave from the other obstacle is received by the distance measuring sensor 2. It is considered that there is no such thing. Therefore, the identification unit 15 identifies the first obstacle O as not being a parking obstacle regardless of the determination result of the height H.
　次に、図２１を参照して、障害物検知装置１００の効果について、グループ化部１４の効果を中心に説明する。 Next, with reference to FIG. 21, the effect of the obstacle detection device 100 will be described focusing on the effect of the grouping unit 14.
　通常、２個の障害物Ｏ間におけるＹ方向に対する反射点間距離ｄ＿Ｙは、実空間における当該２個の障害物Ｏの位置に応じて定まるものである。これに対して、個々の障害物ＯにおけるＸ方向に対する反射点間距離ｄ＿Ｘは、車両１の速度Ｖに応じて定まるものであり、かつ、測距センサ２により探査波が送信される時間間隔ΔＴに応じて定まるものである。すなわち、車両１の速度Ｖが低いほど、反射点間距離ｄ＿Ｘが小さくなることにより、Ｘ方向に対する反射点ＲＰの配置が密になる。他方、車両１の速度Ｖが高いほど、反射点間距離ｄ＿Ｘが大きくなることにより、Ｘ方向に対する反射点ＲＰの配置が疎になる。また、時間間隔ΔＴが小さいほど、反射点間距離ｄ＿Ｘが小さくなることにより、Ｘ方向に対する反射点ＲＰの配置が密になる。他方、時間間隔ΔＴが大きいほど、反射点間距離ｄ＿Ｘが大きくなることにより、Ｘ方向に対する反射点ＲＰの配置が疎になる。 Normally, the distance d_Y between reflection points in the Y direction between two obstacles O is determined according to the position of the two obstacles O in the real space. On the other hand, the distance d_X between the reflection points in the X direction of each obstacle O is determined according to the speed V of the vehicle 1, and the time interval ΔT at which the exploration wave is transmitted by the distance measuring sensor 2. It is decided according to. That is, the lower the speed V of the vehicle 1, the smaller the distance d_X between the reflection points, and the denser the arrangement of the reflection points RP in the X direction. On the other hand, the higher the speed V of the vehicle 1, the larger the distance d_X between the reflection points, so that the arrangement of the reflection points RP in the X direction becomes sparse. Further, the smaller the time interval ΔT, the smaller the distance d_X between the reflection points, and the denser the arrangement of the reflection points RP in the X direction. On the other hand, as the time interval ΔT becomes larger, the distance d_X between the reflection points becomes larger, so that the arrangement of the reflection points RP in the X direction becomes sparse.
　例えば、図２１に示す例において、反射点ＲＰ＿３＿１，ＲＰ＿４＿１間の反射点間距離ｄ＿Ｙ、すなわち反射点ＲＰ＿３＿２，ＲＰ＿４＿２間の反射点間距離ｄ＿Ｙは、実空間における障害物Ｏ＿３，Ｏ＿４の位置に応じて定まるものである。これに対して、反射点ＲＰ＿３＿１，ＲＰ＿３＿２間の反射点間距離ｄ＿Ｘ、すなわち反射点ＲＰ＿４＿１，ＲＰ＿４＿２間の反射点間距離ｄ＿Ｘは、速度Ｖに応じて定まるものであり、かつ、時間間隔ΔＴに応じて定まるものである。 For example, in the example shown in FIG. 21, the distance d_Y between the reflection points between the reflection points RP_3_1 and RP_4_1, that is, the distance d_Y between the reflection points between the reflection points RP_3_2 and RP_4_2 depends on the position of the obstacles O_3 and O_4 in the real space. It is fixed. On the other hand, the distance d_X between the reflection points between the reflection points RP_3_1 and RP_3_2, that is, the distance d_X between the reflection points between the reflection points RP_4_1 and RP_4_2 is determined according to the velocity V and according to the time interval ΔT. It is decided.
　ここで、Ｘ方向に対する反射点ＲＰの配置が疎であるとき、図２１に示す如く、反射点間距離ｄ＿Ｘが反射点間距離ｄ＿Ｙよりも大きくなることがある。換言すれば、反射点間距離ｄ＿Ｙが反射点間距離ｄ＿Ｘよりも小さくなることがある。 Here, when the arrangement of the reflection point RPs in the X direction is sparse, the distance between the reflection points d_X may be larger than the distance d_Y between the reflection points, as shown in FIG. In other words, the distance between reflection points d_Y may be smaller than the distance between reflection points d_X.
　従来の障害物検知装置におけるグループ化部は、互いに隣接する各２個の反射点ＲＰについて、反射点間距離ｄが小さいときは当該２個の反射点ＲＰを互いに同一の反射点群ＰＧに含めるものであり、かつ、反射点間距離ｄが大きいときは当該２個の反射点ＲＰを互いに異なる反射点群ＰＧに含めるものであった。 The grouping unit in the conventional obstacle detection device includes the two reflection point RPs in the same reflection point group PG for each of the two reflection point RPs adjacent to each other when the distance d between the reflection points is small. When the distance d between the reflection points is large, the two reflection point RPs are included in the reflection point group PGs different from each other.
　このため、図２１に示す例において、反射点間距離ｄ＿Ｙが小さいことにより、反射点ＲＰ＿３＿１，ＲＰ＿３＿２と反射点ＲＰ＿４＿１，ＲＰ＿４＿２とが互いに同一の反射点群ＰＧに含まれることがあるという問題があった。また、反射点間距離ｄ＿Ｘが大きいことにより、反射点ＲＰ＿３＿１と反射点ＲＰ＿３＿２とが互いに異なる反射点群ＰＧに含まれるとともに、反射点ＲＰ＿４＿１と反射点ＲＰ＿４＿２とが互いに異なる反射点群ＰＧに含まれることがあるという問題があった。すなわち、個々の障害物Ｏに対応する反射点群ＰＧを正確に設定することができないという問題があった。 Therefore, in the example shown in FIG. 21, there is a problem that the reflection points RP_3_1 and RP_3_2 and the reflection points RP_1 and RP_4_2 may be included in the same reflection point group PG due to the small distance d_Y between the reflection points. It was. Further, since the distance d_X between the reflection points is large, the reflection point RP_3_1 and the reflection point RP_3_2 are included in the reflection point group PG different from each other, and the reflection point RP_1 and the reflection point RP_4_2 are included in the reflection point group PG different from each other. There was a problem that there was something. That is, there is a problem that the reflection point group PG corresponding to each obstacle O cannot be set accurately.
　これに対して、障害物検知装置１００におけるグループ化部１４は、上記のとおり、個々の解析領域ＡＡにおいて、度数分布ＦＤ＿Ｙ，ＦＤ＿Ｘの各々に対するピーク分離処理を実行することにより反射点群ＰＧを設定するものである。これにより、個々の解析領域ＡＡにおいて、個々の障害物Ｏに対応する反射点群ＰＧを正確に設定することができる。例えば、図２１に示す例においても、２個の障害物Ｏ＿３，Ｏ＿４と一対一に対応する２個の反射点群ＰＧを設定することができる。 On the other hand, the grouping unit 14 in the obstacle detection device 100 sets the reflection point group PG by executing the peak separation processing for each of the frequency distributions FD_Y and FD_X in each analysis region AA as described above. To do. As a result, the reflection point cloud group PG corresponding to each obstacle O can be accurately set in each analysis region AA. For example, also in the example shown in FIG. 21, two reflection point cloud group PGs corresponding to two obstacles O_3 and O_4 can be set one-to-one.
　すなわち、側方領域ＬＡにて縁石（Ｏ＿３）と駐車障害物（Ｏ＿４）とが互いに近接配置されている場合であっても、縁石に対応する反射点群ＰＧと駐車障害物に対応する反射点群ＰＧとを設定することができる。 That is, even when the curb (O_3) and the parking obstacle (O_4) are arranged close to each other in the lateral region LA, the reflection point group PG corresponding to the curb and the reflection point corresponding to the parking obstacle A group PG can be set.
　なお、上記のとおり、非連続部検知処理においては、第ｎ波（例えば第１波）に対応する複数個の反射点ＲＰが用いられるものであった。これに対して、反射点群設定処理においては、第１波～第Ｎ波に対応する複数個の反射点ＲＰを用いるのが好適である。これにより、個々の障害物Ｏに対応する反射点群ＰＧを更に正確に設定することができる。 As described above, in the discontinuous portion detection process, a plurality of reflection point RPs corresponding to the nth wave (for example, the first wave) are used. On the other hand, in the reflection point group setting process, it is preferable to use a plurality of reflection point RPs corresponding to the first wave to the Nth wave. As a result, the reflection point cloud group PG corresponding to each obstacle O can be set more accurately.
　次に、図２２を参照して、非連続部検知部１２の変形例について説明する。 Next, a modified example of the discontinuous portion detection unit 12 will be described with reference to FIG. 22.
　上記のとおり、非連続部検知部１２は、第ｎ波に対応する複数個の反射点ＲＰにおける反射点間距離ｄを非連続部検知処理に用いるものであれば良い。すなわち、非連続部検知部１２は、第１波に対応する複数個の反射点ＲＰに代えて、第２波に対応する複数個の反射点ＲＰ又は第３波に対応する複数個の反射点ＲＰにおける反射点間距離ｄを非連続部検知処理に用いるものであっても良い。 As described above, the discontinuous portion detection unit 12 may use the distance d between the reflection points in the plurality of reflection point RPs corresponding to the nth wave for the discontinuous portion detection process. That is, the discontinuous portion detection unit 12 replaces the plurality of reflection point RPs corresponding to the first wave with the plurality of reflection point RPs corresponding to the second wave or the plurality of reflection points corresponding to the third wave. The distance d between reflection points in the RP may be used for the discontinuous portion detection process.
　例えば、図２２に示す如く、側方領域ＬＡに５個の障害物Ｏ＿１～Ｏ＿４，Ｏ＿６が存在しているものとする。障害物Ｏ＿６は、例えば、段差により構成されている。図中、四角印（□）は、第３波に対応する個々の反射点ＲＰを示している。 For example, as shown in FIG. 22, it is assumed that five obstacles O_1 to O_4 and O_6 exist in the lateral region LA. The obstacle O_6 is composed of, for example, a step. In the figure, square marks (□) indicate individual reflection point RPs corresponding to the third wave.
　この場合、第１波に対応する複数個の反射点ＲＰにおける反射点間距離ｄが非連続部検知処理に用いられる場合、非連続部ＤＰ＿１，ＤＰ＿２が検知されないことがある。これに対して、第２波に対応する複数個の反射点ＲＰにおける反射点間距離ｄを用いることにより、２個の非連続部ＤＰ＿１，ＤＰ＿２を検知することができる。したがって、第２波に対応する複数個の反射点ＲＰにおける反射点間距離ｄを用いるのが好適である。 In this case, when the distance d between the reflection points in the plurality of reflection point RPs corresponding to the first wave is used for the discontinuous portion detection process, the discontinuous portions DP_1 and DP_2 may not be detected. On the other hand, two discontinuous portions DP_1 and DP_2 can be detected by using the distance d between the reflection points in the plurality of reflection point RPs corresponding to the second wave. Therefore, it is preferable to use the distance d between the reflection points in the plurality of reflection point RPs corresponding to the second wave.
　なお、非連続部検知部１２は、第ｎ波に対応する複数個の反射点ＲＰにおける反射点間距離ｄを非連続部検知処理に用いるのに代えて、第１波～第Ｎ波の各々に対応する複数個の反射点ＲＰにおける反射点間距離ｄを非連続部検知処理に用いるものであっても良い。これにより、非連続部ＤＰをより確実に検知することができる。 The discontinuous portion detection unit 12 uses each of the first wave to the Nth wave instead of using the distance d between the reflection points in the plurality of reflection point RPs corresponding to the nth wave for the discontinuous portion detection process. The distance d between the reflection points in the plurality of reflection point RPs corresponding to the above may be used for the discontinuous portion detection process. As a result, the discontinuous portion DP can be detected more reliably.
　次に、図２３を参照して、非連続部検知部１２の他の変形例について説明する。 Next, with reference to FIG. 23, another modification of the discontinuous portion detection unit 12 will be described.
　非連続部検知処理は、第１条件によるものに限定されるものではない。非連続部検知部１２は、以下のようにして非連続部ＤＰを検知するものであっても良い。 The discontinuous part detection process is not limited to the one based on the first condition. The discontinuous portion detecting unit 12 may detect the discontinuous portion DP as follows.
　いま、図２３Ａに示す如く、側方領域ＬＡに５個の障害物Ｏ＿１～Ｏ＿４，Ｏ＿６が存在している。この場合、障害物検知処理が実行されることにより、障害物群ＯＧに対応する複数個の反射点ＲＰ＿１，ＲＰ＿２，ＲＰ＿３，ＲＰ＿４，ＲＰ＿６が検知される。具体的には、例えば、障害物Ｏ＿１に対応する９個の反射点ＲＰ＿１、障害物Ｏ＿２に対応する９個の反射点ＲＰ＿２、障害物Ｏ＿３に対応する１２個の反射点ＲＰ＿３、障害物Ｏ＿４に対応する４個の反射点ＲＰ＿４、及び障害物Ｏ＿６に対応する２６個の反射点ＲＰ＿６が検知される。 Now, as shown in FIG. 23A, there are five obstacles O_1 to O_4 and O_6 in the lateral region LA. In this case, by executing the obstacle detection process, a plurality of reflection points RP_1, RP_2, RP_3, RP_4, RP_6 corresponding to the obstacle group OG are detected. Specifically, for example, the nine reflection points RP_1 corresponding to the obstacle O_1, the nine reflection points RP_2 corresponding to the obstacle O_2, the twelve reflection points RP_3 corresponding to the obstacle O_3, and the obstacle O_4. The corresponding four reflection points RP_4 and the 26 reflection points RP_6 corresponding to the obstacle O_6 are detected.
　非連続部検知部１２は、各回の送信波に対応する１個以上の測距値Ｄにおける分散値ｓを算出する。非連続部検知部１２は、当該算出された分散値ｓに対する時間微分をすることにより、当該算出された分散値ｓの変化量Δｓを算出する。図２３Ｂは、時間に対する分散値ｓの例を示している。図２３Ｃは、時間に対する変化量Δｓの例を示している。上記のとおり、時間軸は、Ｘ軸に対応している。 The discontinuous unit detection unit 12 calculates the variance value s in one or more distance measurement values D corresponding to each transmitted wave. The discontinuous unit detection unit 12 calculates the amount of change Δs of the calculated variance value s by performing time differentiation with respect to the calculated variance value s. FIG. 23B shows an example of the variance value s with respect to time. FIG. 23C shows an example of the amount of change Δs with respect to time. As mentioned above, the time axis corresponds to the X axis.
　非連続部検知部１２は、当該算出された変化量Δｓについて、以下の条件（以下「第２条件」という。）が満たされたとき、非連続部ＤＰを検知する。すなわち、第２条件は、変化量Δｓが所定の閾値Δｓ＿ｔｈを超えるという条件である。 The discontinuous unit detection unit 12 detects the discontinuous unit DP when the following conditions (hereinafter referred to as “second condition”) are satisfied for the calculated change amount Δs. That is, the second condition is that the amount of change Δs exceeds a predetermined threshold value Δs_th.
　図２３に示す例において、障害物Ｏ＿６，Ｏ＿１による反射波（第１波及び第２波を含む。）に対応する測距値Ｄの分散値ｓは、障害物Ｏ＿６，Ｏ＿３による反射波（第１波及び第２波を含む。）に対応する測距値Ｄの分散値ｓよりも小さく、かつ、障害物Ｏ＿６，Ｏ＿３，Ｏ＿４による反射波（第１波、第２波及び第３波を含む。）に対応する測距値Ｄの分散値ｓよりも小さい。また、障害物Ｏ＿６，Ｏ＿２による反射波（第１波及び第２波を含む。）に対応する測距値Ｄの分散値ｓは、障害物Ｏ＿６，Ｏ＿３による反射波（第１波及び第２波を含む。）に対応する測距値Ｄの分散値ｓよりも小さく、かつ、障害物Ｏ＿６，Ｏ＿３，Ｏ＿４による反射波（第１波、第２波及び第３波を含む。）に対応する測距値Ｄの分散値ｓよりも小さい。 In the example shown in FIG. 23, the variance value s of the distance measurement value D corresponding to the reflected wave (including the first wave and the second wave) by the obstacles O_6 and O_1 is the reflected wave (third) by the obstacles O_6 and O_3. The waves reflected by obstacles O_6, O_3, and O_4 (the first wave, the second wave, and the third wave) that are smaller than the variance value s of the ranging value D corresponding to the first wave and the second wave). It is smaller than the variance value s of the ranging value D corresponding to). Further, the dispersion value s of the ranging value D corresponding to the reflected wave (including the first wave and the second wave) by the obstacles O_6 and O_2 is the reflected wave (the first wave and the second wave) by the obstacles O_6 and O_3. It is smaller than the variance value s of the ranging value D corresponding to (including waves), and corresponds to the reflected waves (including the first wave, the second wave, and the third wave) by the obstacles O_6, O_3, and O_4. It is smaller than the variance value s of the distance measurement value D to be measured.
　これにより、時刻ｔ＿１にて第２条件が満たされて、１個の非連続部ＤＰ＿１が検知される。次いで、時刻ｔ＿２にて第２条件が満たされて、１個の非連続部ＤＰ＿２が検知される。すなわち、２個の非連続部ＤＰ＿１，ＤＰ＿２が検知される。 As a result, the second condition is satisfied at time t_1, and one discontinuous portion DP_1 is detected. Then, at time t_2, the second condition is satisfied and one discontinuous portion DP_2 is detected. That is, two discontinuous portions DP_1 and DP_2 are detected.
　なお、分散値ｓは、第１波～第Ｎ波の全てに対応する測距値Ｄの分散値であっても良く、又は、第１波～第Ｎ波のうちの任意の２以上の第ｎ波に対応する測距値Ｄの分散値であっても良い。ただし、小さい高さＨを有する障害物Ｏ（例えば縁石又は段差）による反射波に対応する測距値Ｄをより確実に分散値ｓの算出に含める観点から、第１波～第Ｎ波の全てに対応する測距値Ｄの分散値を用いるのがより好適である。 The dispersion value s may be the dispersion value of the ranging value D corresponding to all of the first wave to the Nth wave, or any two or more of the first wave to the Nth wave. It may be a variance value of the ranging value D corresponding to n waves. However, from the viewpoint of more reliably including the distance measurement value D corresponding to the reflected wave due to the obstacle O having a small height H (for example, a curb or a step) in the calculation of the dispersion value s, all of the first wave to the Nth wave. It is more preferable to use the variance value of the ranging value D corresponding to.
　次に、非連続部検知部１２の他の変形例について説明する。 Next, another modification of the discontinuous portion detection unit 12 will be described.
　非連続部検知処理は、第１条件又は第２条件によるものに限定されるものではない。非連続部検知部１２は、以下のようにして非連続部ＤＰを検知するものであっても良い。 The discontinuous part detection process is not limited to the one based on the first condition or the second condition. The discontinuous portion detecting unit 12 may detect the discontinuous portion DP as follows.
　すなわち、非連続部検知部１２は、直前の非連続部ＤＰが検知された時点から現時点までの間に障害物検知部１１により算出された複数組の反射点座標値（以下「第１反射点座標値」ということがある。）Ｃ＿Ｘ，Ｃ＿Ｙについて、ＸＹ座標系における回帰直線又は回帰曲線を算出する。回帰曲線は、例えば、円弧状又は放物線状の曲線である。回帰直線又は回帰曲線の算出には、公知の種々の技術（例えば最小二乗法）を用いることができる。 That is, the discontinuous portion detection unit 12 has a plurality of sets of reflection point coordinate values calculated by the obstacle detection unit 11 from the time when the immediately preceding discontinuous portion DP is detected to the present time (hereinafter, "first reflection point"). It may be referred to as "coordinate value".) For C_X and C_Y, a regression line or a regression curve in the XY coordinate system is calculated. The regression curve is, for example, an arc-shaped or parabolic-shaped curve. Various known techniques (eg, least squares method) can be used to calculate the regression line or the regression curve.
　次いで、非連続部検知部１２は、当該算出された回帰直線又は回帰曲線と、障害物検知部１１により新たに算出された少なくとも１組の反射点座標値（以下「第２反射点座標値」ということがある。）Ｃ＿Ｘ，Ｃ＿Ｙとの距離を算出する。非連続部検知部１２は、当該算出された距離を所定の閾値と比較する。非連続部検知部１２は、当該算出された距離が閾値を超えている場合、この距離に対応する時点を非連続部ＤＰとして検知する。 Next, the discontinuous portion detection unit 12 includes the calculated regression line or regression curve, and at least one set of reflection point coordinate values newly calculated by the obstacle detection unit 11 (hereinafter, “second reflection point coordinate value”). In some cases, the distances from C_X and C_Y are calculated. The discontinuous unit detection unit 12 compares the calculated distance with a predetermined threshold value. When the calculated distance exceeds the threshold value, the discontinuous unit detecting unit 12 detects the time point corresponding to this distance as the discontinuous unit DP.
　このとき、閾値は、例えば、いわゆる「残差分布」に対する定数倍の値に設定される。残差分布は、回帰直線又は回帰曲線の周囲における複数組の第１反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙの分布のばらつきの程度を示すものである。 At this time, the threshold value is set to, for example, a constant multiple of the so-called "residual distribution". The residual distribution indicates the degree of variation in the distribution of a plurality of sets of first reflection point coordinate values C_X and C_Y around the regression line or the regression curve.
　ここで、回帰直線又は回帰曲線は、算出済みの複数組の第１反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙにおける連続性に基づく未算出の第２反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙの予測値に対応している。また、回帰直線又は回帰曲線と第２反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙとの距離は、当該予測値に係る残差に対応している。 Here, the regression line or the regression curve corresponds to the uncalculated predicted values of the second reflection point coordinate values C_X and C_Y based on the continuity of the calculated first plurality of reflection point coordinate values C_X and C_Y. .. Further, the distance between the regression line or the regression curve and the second reflection point coordinate values C_X and C_Y corresponds to the residual related to the predicted value.
　すなわち、非連続部検知部１２は、当該予測値に係る残差を示す値（以下「残差値」という。）が所定の閾値を超えるという条件（以下「第３条件」という。）が満たされたとき、非連続部ＤＰを検知するものである。これにより、例えば、複数個の反射点ＲＰが曲線状に配置されている場合であっても、非連続部ＤＰを検知することができる。 That is, the discontinuous unit detection unit 12 satisfies the condition that the value indicating the residual value related to the predicted value (hereinafter referred to as “residual value”) exceeds a predetermined threshold value (hereinafter referred to as “third condition”). When it is done, the discontinuous part DP is detected. Thereby, for example, even when a plurality of reflection point RPs are arranged in a curved shape, the discontinuous portion DP can be detected.
　次に、非連続部検知部１２の他の変形例について説明する。 Next, another modification of the discontinuous portion detection unit 12 will be described.
　非連続部検知部１２は、第１条件及び第２条件が満たされたとき、非連続部ＤＰを検知するものであっても良い。または、非連続部検知部１２は、第１条件及び第３条件が満たされたとき、非連続部ＤＰを検知するものであっても良い。または、非連続部検知部１２は、第２条件及び第３条件が満たされたとき、非連続部ＤＰを検知するものであっても良い。または、非連続部検知部１２は、第１条件、第２条件及び第３条件が満たされたとき、非連続部ＤＰを検知するものであっても良い。すなわち、非連続部検知部１２は、複数個の条件により非連続部ＤＰを検知するものであっても良い。 The discontinuous unit detection unit 12 may detect the discontinuous unit DP when the first condition and the second condition are satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when the first condition and the third condition are satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when the second condition and the third condition are satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when the first condition, the second condition, and the third condition are satisfied. That is, the discontinuous portion detecting unit 12 may detect the discontinuous portion DP under a plurality of conditions.
　または、非連続部検知部１２は、第１条件及び第２条件のうちの少なくとも一方が満たされたとき、非連続部ＤＰを検知するものであっても良い。または、非連続部検知部１２は、第１条件及び第３条件のうちの少なくとも一方が満たされたとき、非連続部ＤＰを検知するものであっても良い。または、非連続部検知部１２は、第２条件及び第３条件のうちの少なくとも一方が満たされたとき、非連続部ＤＰを検知するものであっても良い。または、非連続部検知部１２は、第１条件、第２条件及び第３条件のうちの少なくとも一つが満たされたとき、非連続部ＤＰを検知するものであっても良い。すなわち、非連続部検知部１２は、複数個の条件により非連続部ＤＰを検知するものであっても良い。 Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the first condition and the second condition is satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the first condition and the third condition is satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the second condition and the third condition is satisfied. Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least one of the first condition, the second condition, and the third condition is satisfied. That is, the discontinuous portion detecting unit 12 may detect the discontinuous portion DP under a plurality of conditions.
　または、非連続部検知部１２は、第１条件、第２条件及び第３条件のうちの少なくとも二つが満たされたとき、非連続部ＤＰを検知するものであっても良い。すなわち、非連続部検知部１２は、複数個の条件による多数決の結果に基づき非連続部ＤＰを検知するものであっても良い。 Alternatively, the discontinuous unit detecting unit 12 may detect the discontinuous unit DP when at least two of the first condition, the second condition, and the third condition are satisfied. That is, the discontinuous portion detecting unit 12 may detect the discontinuous portion DP based on the result of majority voting under a plurality of conditions.
　このように、複数個の条件を用いることにより、非連続部ＤＰの検知精度を向上することができる。換言すれば、非連続部ＤＰを正確に検知することができる。 In this way, by using a plurality of conditions, the detection accuracy of the discontinuous portion DP can be improved. In other words, the discontinuous part DP can be detected accurately.
　次に、解析領域抽出部１３の変形例について説明する。 Next, a modified example of the analysis area extraction unit 13 will be described.
　解析領域抽出部１３は、非連続部検知部１２により非連続部ＤＰが検知されない状態にて所定時間又は所定距離が経過したとき、非連続部ＤＰにかかわらず側方領域ＬＡを区切ることにより新たな解析領域ＡＡを設定するものであっても良い。換言すれば、解析領域抽出部１３は、１個の解析領域ＡＡの幅が所定幅を超えたとき、当該１個の解析領域ＡＡを複数個の解析領域ＡＡに分割するものであっても良い。所定幅は、例えば、車両１用の駐車スペースの幅に対する２倍程度の値に設定される。 When a predetermined time or a predetermined distance elapses in a state where the discontinuous portion DP is not detected by the discontinuous portion detecting unit 12, the analysis region extraction unit 13 newly divides the side region LA regardless of the discontinuous portion DP. The analysis area AA may be set. In other words, the analysis area extraction unit 13 may divide the one analysis area AA into a plurality of analysis areas AA when the width of one analysis area AA exceeds a predetermined width. .. The predetermined width is set to, for example, a value about twice the width of the parking space for the vehicle 1.
　または、解析領域抽出部１３は、非連続部検知部１２により非連続部ＤＰが検知されない状態にて障害物検知部１１による測距値Ｄの算出数が所定数を超えたとき、非連続部ＤＰにかかわらず側方領域ＬＡを区切ることにより新たな解析領域ＡＡを設定するものであっても良い。換言すれば、解析領域抽出部１３は、１個の解析領域ＡＡに対応する測距値Ｄの算出数が所定数を超えたとき、当該１個の解析領域ＡＡを複数個の解析領域ＡＡに分割するものであっても良い。 Alternatively, when the number of distance measurement values D calculated by the obstacle detection unit 11 exceeds a predetermined number in a state where the discontinuous unit DP is not detected by the discontinuous unit detection unit 12, the analysis area extraction unit 13 is a discontinuous unit. A new analysis area AA may be set by dividing the side area LA regardless of the DP. In other words, when the number of calculated distance measurement values D corresponding to one analysis area AA exceeds a predetermined number, the analysis area extraction unit 13 converts the one analysis area AA into a plurality of analysis areas AA. It may be divided.
　これにより、非連続部ＤＰが検知されない場合であっても、非連続部検知処理に対する後段の処理（すなわち解析領域抽出処理、グループ化処理、識別処理及び出力処理）を実行することができるとともに、駐車支援制御を実行することができる。また、個々の解析領域ＡＡに対応する反射点情報の量の低減することができる。これにより、個々の解析領域ＡＡに対応する反射点情報用の記憶領域の小型化を図ることができる。 As a result, even when the discontinuous portion DP is not detected, the subsequent processing (that is, the analysis area extraction processing, the grouping processing, the identification processing and the output processing) for the discontinuous portion detection processing can be executed, and the discontinuous portion DP can be executed. Parking assistance control can be performed. In addition, the amount of reflection point information corresponding to each analysis region AA can be reduced. As a result, it is possible to reduce the size of the storage area for reflection point information corresponding to each analysis area AA.
　次に、図２４を参照して、識別部１５の変形例について説明する。 Next, a modified example of the identification unit 15 will be described with reference to FIG. 24.
　識別部１５は、個々の障害物Ｏが路面障害物、路上障害物及び走行障害物のうちのいずれであるかを判断するのに代えて、個々の障害物Ｏが低背障害物であるか高背障害物であるかを判断するものであっても良い。 Instead of determining whether the individual obstacle O is a road surface obstacle, a road obstacle, or a running obstacle, the identification unit 15 determines whether the individual obstacle O is a low-profile obstacle. It may be used to determine whether it is a tall obstacle.
　すなわち、高さ判断部５３には、特徴量座標系における閾値Ｓ＿ｔｈ＿３が予め設定されている。図２４は、閾値Ｓ＿ｔｈ＿３の例を示している。ここで、閾値Ｓ＿ｔｈ＿３は、低背障害物と高背障害物との識別に係る閾値Ｈ＿ｔｈ＿３に対応するものである。 That is, the threshold value S_th_3 in the feature amount coordinate system is preset in the height determination unit 53. FIG. 24 shows an example of the threshold value S_th_3. Here, the threshold value S_th_3 corresponds to the threshold value H_th_3 related to the discrimination between the low-back obstacle and the high-back obstacle.
　高さ判断部５３は、個々の反射点群ＰＧに対応する統計量Ｓ１，Ｓ２を特徴量座標系にプロットする。当該プロットされた統計量Ｓ１，Ｓ２が閾値Ｓ＿ｔｈ＿３未満の範囲Ｒ＿４に含まれる場合、高さ判断部５３は、対応する障害物Ｏが低背障害物であると判断する。当該プロットされた統計量Ｓ１，Ｓ２が閾値Ｓ＿ｔｈ＿３以上の範囲Ｒ＿５に含まれる場合、高さ判断部５３は、対応する障害物Ｏが高背障害物であると判断する。 The height determination unit 53 plots the statistics S1 and S2 corresponding to the individual reflection point cloud PGs in the feature coordinate system. When the plotted statistics S1 and S2 are included in the range R_4 below the threshold value S_th_3, the height determination unit 53 determines that the corresponding obstacle O is a low-profile obstacle. When the plotted statistics S1 and S2 are included in the range R_5 having the threshold value S_th_3 or more, the height determination unit 53 determines that the corresponding obstacle O is a tall obstacle.
　例えば、ある１個の反射点群ＰＧに対応する統計量Ｓ１＿４，Ｓ２＿４が範囲Ｒ＿４に含まれる場合（図２４参照）、高さ判断部５３は、対応する障害物Ｏが低背障害物であると判別する。また、他の１個の反射点群ＰＧに対応する統計量Ｓ１＿５，Ｓ２＿５が範囲Ｒ＿５に含まれる場合（図２４参照）、高さ判断部５３は、対応する障害物Ｏが高背障害物であると判別する。 For example, when the statistics S1_4 and S2_4 corresponding to a certain reflection point group PG are included in the range R_4 (see FIG. 24), the height determination unit 53 indicates that the corresponding obstacle O is a low-profile obstacle. To determine. Further, when the statistics S1_5 and S2_5 corresponding to the other one reflection point group PG are included in the range R_5 (see FIG. 24), the height determination unit 53 indicates that the corresponding obstacle O is a tall obstacle. Determine if there is.
　次に、識別部１５の他の変形例について説明する。 Next, another modification of the identification unit 15 will be described.
　広幅障害物であり、かつ、走行障害物である障害物Ｏが存在する場合、当該障害物Ｏと車両１間にて探査波が複数回反射されることがある。これにより、いわゆる「多重反射波」が受信されることがある。多重反射波に対応する反射点ＲＰは、いわゆる「虚像」である。虚像は、当該障害物Ｏと車両１間の距離に対する２以上の整数倍の値に対応するＹ座標値Ｃ＿Ｙを有するものとなる。虚像は、識別処理の対象から除外されるのが好適である。 If there is an obstacle O that is a wide obstacle and a running obstacle, the exploration wave may be reflected multiple times between the obstacle O and the vehicle 1. As a result, so-called "multiple reflected waves" may be received. The reflection point RP corresponding to the multiple reflected wave is a so-called "virtual image". The imaginary image has a Y coordinate value C_Y corresponding to a value obtained by an integral multiple of 2 or more with respect to the distance between the obstacle O and the vehicle 1. It is preferable that the imaginary image is excluded from the target of the identification process.
　そこで、識別部１５は、車両１に対して最も手前側に位置する広幅障害物について、当該広幅障害物と車両１間の距離に対する２以上の整数倍の値に対応するＹ座標値Ｃ＿Ｙを有する反射点群ＰＧを識別処理の対象から除外するものであって良い。これにより、多重反射波に基づく虚像を識別処理の対象から除外することができる。 Therefore, the identification unit 15 has a Y coordinate value C_Y corresponding to a value obtained by an integral multiple of 2 or more with respect to the distance between the wide obstacle and the vehicle 1 for the wide obstacle located on the foremost side with respect to the vehicle 1. The reflection point cloud group PG may be excluded from the target of the identification process. As a result, the virtual image based on the multiple reflected waves can be excluded from the target of the identification process.
　次に、出力部１６の変形例について説明する。 Next, a modified example of the output unit 16 will be described.
　出力部１６は、縁石に対する奥側に駐車障害物が位置している場合において、当該縁石と当該駐車障害物間の距離が所定距離よりも大きいとき、当該駐車障害物に関する情報を識別結果信号から除外するものであっても良い。換言すれば、出力部１６は、縁石に対する奥側に駐車障害物が位置している場合、当該縁石と当該駐車障害物間の距離が所定距離以下であるときのみ、当該駐車障害物に関する情報を識別結果信号に含めるものであっても良い。 When the parking obstacle is located behind the curb and the distance between the curb and the parking obstacle is larger than a predetermined distance, the output unit 16 obtains information about the parking obstacle from the identification result signal. It may be excluded. In other words, when the parking obstacle is located behind the curb, the output unit 16 outputs information about the parking obstacle only when the distance between the curb and the parking obstacle is less than or equal to a predetermined distance. It may be included in the identification result signal.
　これにより、駐車支援制御に不要な情報が識別結果信号に含まれるのを回避することができる。この結果、障害物検知装置１００と駐車支援装置２００間の通信量を低減することができるとともに、駐車支援装置２００における演算量を低減することができる。 This makes it possible to prevent information unnecessary for parking support control from being included in the identification result signal. As a result, the amount of communication between the obstacle detection device 100 and the parking support device 200 can be reduced, and the amount of calculation in the parking support device 200 can be reduced.
　次に、駐車支援システム３００の変形例について説明する。 Next, a modified example of the parking support system 300 will be described.
　駐車支援システム３００は、１個の測距センサ２に代えて、複数個の測距センサを含むものであっても良い。すなわち、車両１の左側部、車両１の右側部、又は車両１の左側部及び車両１の右側部の各々に当該複数個の測距センサが設けられているものであっても良い。 The parking support system 300 may include a plurality of distance measuring sensors instead of one distance measuring sensor 2. That is, the plurality of distance measuring sensors may be provided on each of the left side portion of the vehicle 1, the right side portion of the vehicle 1, or the left side portion of the vehicle 1 and the right side portion of the vehicle 1.
　この場合、第１統計量Ｓ１は、当該複数個の測距センサの各々による１回以上の送受信により複数回分の送受信が実現されるとき、当該複数回分の送受信に係る複数個の第１特徴量ＦＡ１による統計量であっても良い。また、第２統計量Ｓ２は、当該複数回分の送受信に係る複数個の第２特徴量ＦＡ２による統計量であっても良い。 In this case, the first statistic S1 is a plurality of first feature quantities related to the plurality of transmissions / receptions when a plurality of transmissions / receptions are realized by one or more transmissions / receptions by each of the plurality of distance measuring sensors. It may be a statistic based on FA1. Further, the second statistic S2 may be a statistic based on a plurality of second feature quantities FA2 related to the transmission / reception of the plurality of times.
　以上のように、障害物検知装置１００は、車両１に設けられた測距センサ２を用いて、移動中の車両１に対する側方領域ＬＡにおける障害物群ＯＧを検知する障害物検知部１１と、障害物群ＯＧにおける非連続部ＤＰを検知する非連続部検知部１２と、非連続部ＤＰに基づく解析領域ＡＡを抽出する解析領域抽出部１３と、解析領域ＡＡにおける複数個の反射点ＲＰに係る度数分布ＦＤ＿Ｙ，ＦＤ＿Ｘを解析することにより、障害物群ＯＧに含まれる複数個の障害物Ｏに対応する複数個の反射点群ＰＧを設定するグループ化部１４と、複数個の障害物Ｏの各々が縁石であるか否かを識別するとともに、複数個の障害物Ｏの各々が駐車障害物であるか否かを識別する識別部１５と、縁石と駐車障害物間の距離が所定距離以下であるとき、少なくとも駐車障害物の位置を示す信号（識別結果信号）を出力する出力部１６と、を備える。グループ化部１４を備えることにより、縁石及び駐車障害物が互いに近接配置されている場合であっても、縁石に対応する反射点群ＰＧ及び駐車障害物に対応する反射点群ＰＧを設定することができる。これにより、少なくとも駐車障害物の位置を示す信号（識別結果信号）を出力することができる。 As described above, the obstacle detection device 100 uses the distance measuring sensor 2 provided in the vehicle 1 to detect the obstacle group OG in the lateral region LA with respect to the moving vehicle 1 together with the obstacle detection unit 11. , The discontinuous part detection unit 12 that detects the discontinuous part DP in the obstacle group OG, the analysis area extraction unit 13 that extracts the analysis area AA based on the discontinuous part DP, and a plurality of reflection point RPs in the analysis area AA. By analyzing the frequency distributions FD_Y and FD_X related to the above, a grouping unit 14 for setting a plurality of reflection point group PGs corresponding to a plurality of obstacles O included in the obstacle group OG, and a plurality of obstacles. The distance between the curb and the parking obstacle is predetermined with the identification unit 15 that identifies whether each of the O's is a curb or not and whether each of the plurality of obstacles O is a parking obstacle. It includes an output unit 16 that outputs at least a signal (identification result signal) indicating the position of a parking obstacle when the distance is less than or equal to the distance. By providing the grouping unit 14, even when the curb and the parking obstacle are arranged close to each other, the reflection point group PG corresponding to the curb and the reflection point group PG corresponding to the parking obstacle can be set. Can be done. As a result, at least a signal indicating the position of the parking obstacle (identification result signal) can be output.
　また、非連続部検知部１２は、第１条件が満たされたとき非連続部ＤＰを検知するものであり、第１条件は、第ｎ波に対応する複数個の反射点ＲＰにおける反射点間距離ｄが算出される場合において、当該算出された反射点間距離ｄが閾値ｄ＿ｔｈを超えるという条件である。第１条件を用いることにより、非連続部ＤＰの検知を実現することができる。 Further, the discontinuous portion detection unit 12 detects the discontinuous portion DP when the first condition is satisfied, and the first condition is between the reflection points in the plurality of reflection point RPs corresponding to the nth wave. When the distance d is calculated, it is a condition that the calculated distance d between reflection points exceeds the threshold value d_th. By using the first condition, it is possible to realize the detection of the discontinuous portion DP.
　また、非連続部検知部１２は、第２条件が満たされたとき非連続部ＤＰを検知するものであり、第２条件は、各回の送信波に対応する１個以上の測距値Ｄにおける分散値ｓが算出される場合において、当該算出された分散値ｓの変化量Δｓが算出されるとき、当該算出された変化量Δｓが閾値Δｓ＿ｔｈを超えるという条件である。第２条件を用いることにより、非連続部ＤＰの検知を実現することができる。 Further, the discontinuous unit detection unit 12 detects the discontinuous unit DP when the second condition is satisfied, and the second condition is in one or more distance measurement values D corresponding to each transmitted wave. When the variance value s is calculated, it is a condition that the calculated change amount Δs exceeds the threshold value Δs_th when the change amount Δs of the calculated dispersion value s is calculated. By using the second condition, it is possible to realize the detection of the discontinuous portion DP.
　また、非連続部検知部１２は、第３条件が満たされたとき非連続部ＤＰを検知するものであり、第３条件は、算出済みの複数組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙにおける連続性に基づき未算出の少なくとも１組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙの予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である。第３条件を用いることにより、非連続部ＤＰの検知を実現することができる。 Further, the discontinuous portion detecting unit 12 detects the discontinuous portion DP when the third condition is satisfied, and the third condition is the continuity in the calculated reflection point coordinate values C_X and C_Y. When the predicted values of at least one set of uncalculated reflection point coordinate values C_X and C_Y are calculated based on the above, and the residual value related to the calculated predicted value is calculated, the calculated residual value Is a condition that exceeds the threshold value. By using the third condition, it is possible to realize the detection of the discontinuous portion DP.
　また、非連続部検知部１２は、第１条件及び第２条件のうちの少なくとも一方が満たされたとき非連続部ＤＰを検知するものであり、第１条件は、第ｎ波に対応する複数個の反射点ＲＰにおける反射点間距離ｄが算出される場合において、当該算出された反射点間距離ｄが閾値ｄ＿ｔｈを超えるという条件であり、第２条件は、各回の送信波に対応する１個以上の測距値Ｄにおける分散値ｓが算出される場合において、当該算出された分散値ｓの変化量Δｓが算出されるとき、当該算出された変化量Δｓが閾値Δｓ＿ｔｈを超えるという条件である。複数個の条件を用いることにより、非連続部ＤＰを精度良く検知することができる。 Further, the discontinuous portion detecting unit 12 detects the discontinuous portion DP when at least one of the first condition and the second condition is satisfied, and the first condition is a plurality of corresponding nth waves. When the distance d between the reflection points in the number of reflection points RP is calculated, the condition is that the calculated distance d between the reflection points exceeds the threshold value d_th, and the second condition is 1 corresponding to each transmitted wave. When the dispersion value s for more than one distance measurement value D is calculated, when the change amount Δs of the calculated dispersion value s is calculated, the calculated change amount Δs exceeds the threshold value Δs_th. is there. By using a plurality of conditions, the discontinuous portion DP can be detected with high accuracy.
　また、非連続部検知部１２は、第１条件及び第３条件が満たされたとき非連続部ＤＰを検知するものであり、第１条件は、第ｎ波に対応する複数個の反射点ＲＰにおける反射点間距離ｄが算出される場合において、当該算出された反射点間距離ｄが閾値ｄ＿ｔｈを超えるという条件であり、第３条件は、算出済みの複数組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙにおける連続性に基づき未算出の少なくとも１組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙの予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である。複数個の条件を用いることにより、非連続部ＤＰを精度良く検知することができる。 Further, the discontinuous portion detecting unit 12 detects the discontinuous portion DP when the first condition and the third condition are satisfied, and the first condition is a plurality of reflection point RPs corresponding to the nth wave. When the distance d between the reflection points in the above is calculated, the condition is that the calculated distance d between the reflection points exceeds the threshold value d_th, and the third condition is the calculated plurality of sets of reflection point coordinate values C_X and C_Y. When the predicted value of at least one set of uncalculated reflection point coordinate values C_X and C_Y is calculated based on the continuity in, and the residual value related to the calculated predicted value is calculated, the calculated value is calculated. The condition is that the residual value exceeds the threshold value. By using a plurality of conditions, the discontinuous portion DP can be detected with high accuracy.
　また、非連続部検知部１２は、第２条件及び第３条件のうちの少なくとも一方が満たされたとき非連続部ＤＰを検知するものであり、第２条件は、各回の送信波に対応する１個以上の測距値Ｄにおける分散値ｓが算出される場合において、当該算出された分散値ｓの変化量Δｓが算出されるとき、当該算出された変化量Δｓが閾値Δｓ＿ｔｈを超えるという条件であり、第３条件は、算出済みの複数組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙにおける連続性に基づき未算出の少なくとも１組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙの予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である。複数個の条件を用いることにより、非連続部ＤＰを精度良く検知することができる。 Further, the discontinuous unit detecting unit 12 detects the discontinuous unit DP when at least one of the second condition and the third condition is satisfied, and the second condition corresponds to each transmission wave. When the variance value s for one or more ranging values D is calculated, the condition that the calculated change amount Δs exceeds the threshold value Δs_th when the change amount Δs of the calculated variance value s is calculated. The third condition is that when the predicted values of at least one set of uncalculated reflection point coordinate values C_X and C_Y are calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values C_X and C_Y. When the residual value related to the calculated predicted value is calculated, it is a condition that the calculated residual value exceeds the threshold value. By using a plurality of conditions, the discontinuous portion DP can be detected with high accuracy.
　また、非連続部検知部１２は、第１条件、第２条件及び第３条件のうちの少なくとも一つが満たされたとき非連続部ＤＰを検知するものであり、第１条件は、第ｎ波に対応する複数個の反射点ＲＰにおける反射点間距離ｄが算出される場合において、当該算出された反射点間距離ｄが閾値ｄ＿ｔｈを超えるという条件であり、第２条件は、各回の送信波に対応する１個以上の測距値Ｄにおける分散値ｓが算出される場合において、当該算出された分散値ｓの変化量Δｓが算出されるとき、当該算出された変化量Δｓが閾値Δｓ＿ｔｈを超えるという条件であり、第３条件は、算出済みの複数組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙにおける連続性に基づき未算出の少なくとも１組の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙの予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である。複数個の条件を用いることにより、非連続部ＤＰを精度良く検知することができる。 Further, the discontinuous portion detecting unit 12 detects the discontinuous portion DP when at least one of the first condition, the second condition and the third condition is satisfied, and the first condition is the nth wave. When the distance d between the reflection points in the plurality of reflection point RPs corresponding to is calculated, the condition is that the calculated distance d between the reflection points exceeds the threshold value d_th, and the second condition is the transmitted wave of each time. In the case where the dispersion value s in one or more distance measurement values D corresponding to is calculated, when the change amount Δs of the calculated dispersion value s is calculated, the calculated change amount Δs sets the threshold value Δs_th. The third condition is that the predicted values of at least one set of uncalculated reflection point coordinate values C_X and C_Y are calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values C_X and C_Y. In this case, when the residual value related to the calculated predicted value is calculated, it is a condition that the calculated residual value exceeds the threshold value. By using a plurality of conditions, the discontinuous portion DP can be detected with high accuracy.
　また、解析領域抽出部１３は、解析領域ＡＡに対応する測距値Ｄの算出数が所定数を超えたとき、解析領域ＡＡを複数個の解析領域ＡＡに分割する。これにより、個々の解析領域ＡＡに対応する反射点情報の量を低減することができる。この結果、個々の解析領域ＡＡに対応する反射点情報用の記憶領域の小型化を図ることができる。 Further, the analysis area extraction unit 13 divides the analysis area AA into a plurality of analysis areas AA when the calculated number of the distance measurement values D corresponding to the analysis area AA exceeds a predetermined number. As a result, the amount of reflection point information corresponding to each analysis region AA can be reduced. As a result, it is possible to reduce the size of the storage area for reflection point information corresponding to each analysis area AA.
実施の形態２．
　通常、駐車支援システム３００が駐車スペースを探索するとき、車両１は、広幅障害物（例えば縁石又は段差）の長手方向に沿う方向に移動する。このため、広幅障害物に対応する複数個の反射点ＲＰの配列方向（以下「反射点配列方向」という。）は、車両１の移動方向に対して平行又は略平行な状態となる。すなわち、反射点配列方向は、Ｘ軸に対して平行又は略平行な状態となる。以下、平行又は略平行を総称して単に「平行」という。 Embodiment 2.
Normally, when the parking support system 300 searches for a parking space, the vehicle 1 moves in a direction along the longitudinal direction of a wide obstacle (for example, a curb or a step). Therefore, the arrangement direction of the plurality of reflection point RPs corresponding to the wide obstacle (hereinafter referred to as "reflection point arrangement direction") is parallel or substantially parallel to the moving direction of the vehicle 1. That is, the reflection point arrangement direction is parallel to or substantially parallel to the X-axis. Hereinafter, parallel or substantially parallel is simply referred to as "parallel".
　しかしながら、車両１の進路によっては、反射点配列方向が車両１の移動方向に対して非平行な状態となることがある。図２５は、かかる状態における１個の解析領域ＡＡ＿２における複数個の障害物Ｏ＿３，Ｏ＿４に対応する複数個の反射点ＲＰ＿３，ＲＰ＿４の例を示している。 However, depending on the course of the vehicle 1, the reflection point arrangement direction may be non-parallel to the moving direction of the vehicle 1. FIG. 25 shows an example of a plurality of reflection points RP_3 and RP_4 corresponding to a plurality of obstacles O_3 and O_4 in one analysis region AA_2 in such a state.
　この場合、まず、第１解析部４１は、解析領域ＡＡ＿２について、複数個の反射点ＲＰ＿３，ＲＰ＿４に係る度数分布ＦＤ＿Ｙを作成する。図２６は、度数分布ＦＤ＿Ｙの例を示している。図２６に示す如く、度数分布ＦＤ＿Ｙは、複数個の反射点ＲＰ＿３，ＲＰ＿４に対応する度数（図中Ｆ＿Ｙ）を含むものとなる。第１解析部４１は、度数分布ＦＤ＿Ｙに対するピーク分離処理を実行する。これにより、複数個の反射点ＲＰ＿３，ＲＰ＿４に対応する１個の度数群ＦＧ＿Ｙが設定される。 In this case, first, the first analysis unit 41 creates a frequency distribution FD_Y related to a plurality of reflection points RP_3 and RP_4 in the analysis region AA_2. FIG. 26 shows an example of the frequency distribution FD_Y. As shown in FIG. 26, the frequency distribution FD_Y includes frequencies (F_Y in the figure) corresponding to a plurality of reflection points RP_3 and RP_4. The first analysis unit 41 executes peak separation processing for the frequency distribution FD_Y. As a result, one frequency group FG_Y corresponding to the plurality of reflection points RP_3 and RP_4 is set.
　次いで、第２解析部４２は、度数群ＦＧ＿Ｙに対応する複数個の反射点ＲＰ＿３，ＲＰ＿４に係る度数分布ＦＤ＿Ｘを作成する。図２７は、度数分布ＦＤ＿Ｘの例を示している。図２７に示す如く、度数分布ＦＤ＿Ｘは、複数個の反射点ＲＰ＿３，ＲＰ＿４に対応する度数（図中Ｆ＿Ｘ）を含むものとなる。第２解析部４２は、度数分布ＦＤ＿Ｘに対するピーク分離処理を実行する。これにより、複数個の反射点ＲＰ＿３，ＲＰ＿４に対応する１個の度数群ＦＧ＿Ｘが設定される。 Next, the second analysis unit 42 creates a frequency distribution FD_X related to a plurality of reflection points RP_3 and RP_4 corresponding to the frequency group FG_Y. FIG. 27 shows an example of the frequency distribution FD_X. As shown in FIG. 27, the frequency distribution FD_X includes frequencies (F_X in the figure) corresponding to a plurality of reflection points RP_3 and RP_4. The second analysis unit 42 executes peak separation processing for the frequency distribution FD_X. As a result, one frequency group FG_X corresponding to the plurality of reflection points RP_3 and RP_4 is set.
　次いで、グループ化部１４は、度数群ＦＧ＿Ｙ及び度数群ＦＧ＿Ｘに対応する１個の反射点群ＰＧを設定する。これにより、図２５に示す如く、２個の障害物Ｏ＿３，Ｏ＿４に対応する１個の反射点群ＰＧが設定される。 Next, the grouping unit 14 sets one reflection point group PG corresponding to the frequency group FG_Y and the frequency group FG_X. As a result, as shown in FIG. 25, one reflection point group PG corresponding to the two obstacles O_3 and O_4 is set.
　このように、反射点配列方向が車両１の移動方向に対して非平行であるとき、個々の解析領域ＡＡにおいて、個々の障害物Ｏに対応する反射点群ＰＧを正確に設定することができないという問題が生ずる。実施の形態２に係る障害物検知装置は、かかる問題の解消を図るものである。 As described above, when the reflection point arrangement direction is non-parallel to the movement direction of the vehicle 1, it is not possible to accurately set the reflection point group PG corresponding to each obstacle O in each analysis region AA. The problem arises. The obstacle detection device according to the second embodiment is intended to solve such a problem.
　図２８は、実施の形態２に係る障害物検知装置を含む駐車支援システムの要部を示すブロック図である。図２９は、実施の形態２に係る障害物検知装置におけるグループ化部の要部を示すブロック図である。図２８及び図２９を参照して、実施の形態２に係る障害物検知装置について説明する。 FIG. 28 is a block diagram showing a main part of the parking support system including the obstacle detection device according to the second embodiment. FIG. 29 is a block diagram showing a main part of the grouping unit in the obstacle detection device according to the second embodiment. The obstacle detection device according to the second embodiment will be described with reference to FIGS. 28 and 29.
　なお、図２８において、図１に示すブロックと同様のブロックには同一符号を付して説明を省略する。また、図２９において、図３に示すブロックと同様のブロックには同一符号を付して説明を省略する。 Note that, in FIG. 28, the same blocks as those shown in FIG. 1 are designated by the same reference numerals, and the description thereof will be omitted. Further, in FIG. 29, the same blocks as those shown in FIG. 3 are designated by the same reference numerals, and the description thereof will be omitted.
　図２８に示す如く、車両１は、測距センサ２、障害物検知装置１００ａ及び駐車支援装置２００を有している。測距センサ２、障害物検知装置１００ａ及び駐車支援装置２００により、駐車支援システム３００ａの要部が構成されている。障害物検知装置１００ａは、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４ａ、識別部１５及び出力部１６を有している。図２９に示す如く、グループ化部１４ａは、第１解析部４１、第２解析部４２及び補正部４３を有している。 As shown in FIG. 28, the vehicle 1 has a distance measuring sensor 2, an obstacle detection device 100a, and a parking support device 200. The distance measuring sensor 2, the obstacle detection device 100a, and the parking support device 200 constitute a main part of the parking support system 300a. The obstacle detection device 100a includes an obstacle detection unit 11, a discontinuous unit detection unit 12, an analysis area extraction unit 13, a grouping unit 14a, an identification unit 15, and an output unit 16. As shown in FIG. 29, the grouping unit 14a has a first analysis unit 41, a second analysis unit 42, and a correction unit 43.
　補正部４３は、反射点配列方向が車両１の移動方向に対して非平行な状態であるとき、グループ化部１４ａにより取得された反射点情報に含まれる個々の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙを補正することにより、反射点配列方向が車両１の移動方向に対して平行な状態にするものである。補正部４３による補正方法の具体例については、図３１及び図３２を参照して説明する。 When the reflection point arrangement direction is non-parallel to the movement direction of the vehicle 1, the correction unit 43 sets the individual reflection point coordinate values C_X and C_Y included in the reflection point information acquired by the grouping unit 14a. By correcting, the reflection point arrangement direction is made parallel to the moving direction of the vehicle 1. A specific example of the correction method by the correction unit 43 will be described with reference to FIGS. 31 and 32.
　第１解析部４１は、補正部４３による補正後のＹ座標値Ｃ＿Ｙを度数分布ＦＤ＿Ｙの作成に用いるようになっている。また、第２解析部４２は、補正部４３による補正後のＸ座標値Ｃ＿Ｘを度数分布ＦＤ＿Ｘの作成に用いるようになっている。 The first analysis unit 41 uses the Y coordinate value C_Y corrected by the correction unit 43 to create the frequency distribution FD_Y. Further, the second analysis unit 42 uses the X coordinate value C_X corrected by the correction unit 43 to create the frequency distribution FD_X.
　以下、グループ化部１４ａにより実行される処理を総称して「グループ化処理」ということがある。すなわち、グループ化部１４ａにより実行されるグループ化処理は、グループ化部１４により実行されるグループ化処理に含まれる処理と同様の処理に加えて、個々の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙを補正する処理などを含むものである。 Hereinafter, the processes executed by the grouping unit 14a may be collectively referred to as "grouping processes". That is, the grouping process executed by the grouping unit 14a corrects the individual reflection point coordinate values C_X and C_Y in addition to the same processing as the processing included in the grouping process executed by the grouping unit 14. It includes processing and so on.
　障害物検知装置１００ａの要部のハードウェア構成は、実施の形態１にて図５及び図６を参照して説明したものと同様である。このため、図示及び説明を省略する。すなわち、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４ａ、識別部１５及び出力部１６の各々の機能は、プロセッサ６１及びメモリ６２により実現されるものであっても良く、又は専用の処理回路６３により実現されるものであっても良い。 The hardware configuration of the main part of the obstacle detection device 100a is the same as that described with reference to FIGS. 5 and 6 in the first embodiment. Therefore, illustration and description will be omitted. That is, each function of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14a, the identification unit 15, and the output unit 16 is realized by the processor 61 and the memory 62. It may be present, or it may be realized by a dedicated processing circuit 63.
　次に、図３０を参照して、駐車支援システム３００ａの動作について、障害物検知装置１００ａ及び駐車支援装置２００の動作を中心に説明する。なお、図３０において、図９に示すステップと同様のステップには同一符号を付して説明を省略する。 Next, with reference to FIG. 30, the operation of the parking support system 300a will be described focusing on the operations of the obstacle detection device 100a and the parking support device 200. In FIG. 30, the same steps as those shown in FIG. 9 are designated by the same reference numerals, and the description thereof will be omitted.
　まず、ステップＳＴ１～ＳＴ３の処理が実行される。次いで、グループ化部１４ａがグループ化処理を実行する（ステップＳＴ４ａ）。次いで、ステップＳＴ５～ＳＴ７の処理が実行される。 First, the processes of steps ST1 to ST3 are executed. Next, the grouping unit 14a executes the grouping process (step ST4a). Next, the processes of steps ST5 to ST7 are executed.
　次に、図３１を参照して、補正部４３による補正方法の第１具体例について説明する。 Next, with reference to FIG. 31, a first specific example of the correction method by the correction unit 43 will be described.
　まず、補正部４３は、Ｘ軸に対して平行な直線（以下「基準直線」という。）ＳＬ＿ｒｅｆを設定する。また、補正部４３は、グループ化部１４ａにより取得された反射点情報を用いて、反射点配列方向に沿う直線ＳＬを検出する。次いで、補正部４３は、基準直線ＳＬ＿ｒｅｆに対する直線ＳＬの角度θを算出する。 First, the correction unit 43 sets a straight line (hereinafter referred to as "reference straight line") SL_ref parallel to the X axis. Further, the correction unit 43 detects the straight line SL along the reflection point arrangement direction by using the reflection point information acquired by the grouping unit 14a. Next, the correction unit 43 calculates the angle θ of the straight line SL with respect to the reference straight line SL_ref.
　次いで、補正部４３は、対応する解析領域ＡＡにおける全ての反射点ＲＰの位置が当該算出された角度θに応じた回転角度（－θ）にて回転するように、上記取得された反射点位置情報に含まれる個々の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙを補正する。当該回転により、反射点配列方向が車両１の移動方向に対して平行な状態を実現することができる。 Next, the correction unit 43 obtains the reflection point positions so that the positions of all the reflection point RPs in the corresponding analysis region AA rotate at a rotation angle (−θ) corresponding to the calculated angle θ. The individual reflection point coordinate values C_X and C_Y included in the information are corrected. By the rotation, it is possible to realize a state in which the reflection point arrangement direction is parallel to the moving direction of the vehicle 1.
　このとき、当該回転の中心には、ＸＹ座標系における任意の点を用いることができる。当該回転の中心は、対応する解析領域ＡＡにおける全ての反射点ＲＰにより共用されるものである。 At this time, any point in the XY coordinate system can be used as the center of the rotation. The center of rotation is shared by all reflection point RPs in the corresponding analysis region AA.
　なお、直線ＳＬの検出には、公知の種々の技術を用いることができる。例えば、補正部４３は、対応する解析領域ＡＡにおける複数個の反射点ＲＰに対して、Ｈｏｕｇｈ変換を用いた直線検出を実行することにより、直線ＳＬを検出するものであっても良い。 Various known techniques can be used to detect the straight line SL. For example, the correction unit 43 may detect the straight line SL by executing the straight line detection using the Hough transform on the plurality of reflection point RPs in the corresponding analysis region AA.
　または、例えば、補正部４３は、ＲＡＮＳＡＣ（Ｒａｎｄｏｍ　Ｓａｍｐｌｅ　Ｃｏｎｓｅｎｓｕｓ）アルゴリズムを用いた直線検出を実行することにより、直線ＳＬを検出するものであっても良い。これにより、広幅障害物と異なる障害物（例えば図３１における障害物Ｏ＿４）に対応する複数個の反射点（例えば図３１における反射点ＲＰ＿４）が含まれる解析領域ＡＡにおいても、直線ＳＬを精度良く検出することができる。 Alternatively, for example, the correction unit 43 may detect the straight line SL by executing the straight line detection using the RANSAC (Random Sample Consensus) algorithm. As a result, even in the analysis region AA including a plurality of reflection points (for example, reflection point RP_4 in FIG. 31) corresponding to an obstacle different from the wide obstacle (for example, obstacle O_4 in FIG. 31), the straight line SL can be accurately performed. Can be detected.
　次に、図３２を参照して、補正部４３による補正方法の第２具体例について説明する。 Next, with reference to FIG. 32, a second specific example of the correction method by the correction unit 43 will be described.
　補正部４３には、Ｍ個の角度φ＿１～φ＿Ｍを示す情報が予め記憶されている。ここで、Ｍは、２以上の任意の整数である。 Information indicating M angles φ_1 to φ_M is stored in advance in the correction unit 43. Here, M is an arbitrary integer of 2 or more.
　補正部４３は、対応する解析領域ＡＡにおける全ての反射点ＲＰの位置を角度φ＿１に応じた回転角度（－φ＿１）にて回転させた状態において、Ｙ座標値Ｃ＿Ｙに対する反射点ＲＰの個数を示す度数分布ＦＤ＿φ＿１を作成する。また、補正部４３は、対応する解析領域ＡＡにおける全ての反射点ＲＰの位置を角度φ＿２に応じた回転角度（－φ＿２）にて回転させた状態において、Ｙ座標値Ｃ＿Ｙに対する反射点ＲＰの個数を示す度数分布ＦＤ＿φ＿２を作成する。以下同様にして、補正部４３は、回転角度（－φ＿３～－φ＿Ｍ）にそれぞれ対応する度数分布ＦＤ＿φ＿３～ＦＤ＿φ＿Ｍを作成する。これにより、Ｍ個の度数分布ＦＤ＿φ＿１～ＦＤ＿φ＿Ｍが作成される。 The correction unit 43 indicates the number of reflection point RPs with respect to the Y coordinate value C_Y in a state where the positions of all reflection point RPs in the corresponding analysis region AA are rotated at a rotation angle (−φ_1) corresponding to the angle φ_1. Create a frequency distribution FD_φ_1. Further, the correction unit 43 has the number of reflection point RPs with respect to the Y coordinate value C_Y in a state where the positions of all reflection point RPs in the corresponding analysis region AA are rotated at a rotation angle (−φ_2) corresponding to the angle φ_2. Create a frequency distribution FD_φ_2 showing. In the same manner below, the correction unit 43 creates frequency distributions FD_φ_3 to FD_φ_M corresponding to the rotation angles (−φ_3 to −φ_M), respectively. As a result, M frequency distributions FD_φ_1 to FD_φ_M are created.
　このとき、当該回転の中心には、ＸＹ座標系における任意の点を用いることができる。当該回転の中心は、対応する解析領域ＡＡにおける全ての反射点ＲＰにより共用されるものである。 At this time, any point in the XY coordinate system can be used as the center of the rotation. The center of rotation is shared by all reflection point RPs in the corresponding analysis region AA.
　次いで、補正部４３は、当該作成された度数分布ＦＤ＿φ＿１～ＦＤ＿φ＿Ｍの各々における最大値Ｆ＿ｍａｘを算出する。これにより、Ｍ個の度数分布ＦＤ＿φ＿１～ＦＤ＿φ＿Ｍと一対一に対応するＭ個の最大値Ｆ＿ｍａｘ＿１～Ｆ＿ｍａｘ＿Ｍが算出される。 Next, the correction unit 43 calculates the maximum value F_max in each of the created frequency distributions FD_φ_1 to FD_φ_M. As a result, M maximum values F_max_1 to F_max_M corresponding to M frequency distributions FD_φ_1 to FD_φ_M on a one-to-one basis are calculated.
　次いで、補正部４３は、Ｍ個の最大値Ｆ＿ｍａｘ＿１～Ｆ＿ｍａｘ＿Ｍのうちの最も大きい値を選択する。補正部４３は、Ｍ個の角度φ＿１～φ＿Ｍのうちの当該選択された値に対応する角度φを選択する。 Next, the correction unit 43 selects the largest value among the M maximum values F_max_1 to F_max_M. The correction unit 43 selects an angle φ corresponding to the selected value among the M angles φ_1 to φ_M.
　次いで、補正部４３は、対応する解析領域ＡＡにおける全ての反射点ＲＰの位置が当該選択された角度φに応じた回転角度（－φ）にて回転するように、上記取得された反射点位置情報に含まれる個々の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙを補正する。当該回転により、反射点配列方向が車両１の移動方向に対して平行な状態を実現することができる。これは、φ＝θであるときＦ＿ｍａｘの値が最大となることを利用したものである。 Next, the correction unit 43 obtains the reflection point positions so that the positions of all the reflection point RPs in the corresponding analysis region AA rotate at a rotation angle (−φ) corresponding to the selected angle φ. The individual reflection point coordinate values C_X and C_Y included in the information are corrected. By the rotation, it is possible to realize a state in which the reflection point arrangement direction is parallel to the moving direction of the vehicle 1. This utilizes the fact that the value of F_max becomes maximum when φ = θ.
　なお、角度φ＿１～φ＿Ｍは、互いに異なる値に設定されたものであれば良い。換言すれば、角度φ＿１～φ＿Ｍの各々は、如何なる値に設定されたものであっても良い。ただし、角度φ＿１～φ＿Ｍは、以下のような値に設定されるのがより好適である。 The angles φ_1 to φ_M may be set to different values. In other words, each of the angles φ_1 to φ_M may be set to any value. However, it is more preferable that the angles φ_1 to φ_M are set to the following values.
　いま、測距センサ２による探査波の送信方向に対応する角度、すなわちＹ方向に対応する角度がθｃであるものとする。また、当該方向に対する送信波の広がりを示す角度がθｗであるものとする。このとき、角度φ＿１～φ＿Ｍは、下限値φ＿ｍｉｎ以上かつ上限値φ＿ｍａｘ以下の角度範囲ΔφをＭ等分してなる値に設定されるのが好適である。ここで、下限値φ＿ｍｉｎは、以下の式（１）に基づく値である。また、上限値φ＿ｍａｘは、以下の式（２）に基づく値である。 Now, it is assumed that the angle corresponding to the transmission direction of the exploration wave by the ranging sensor 2, that is, the angle corresponding to the Y direction is θc. Further, it is assumed that the angle indicating the spread of the transmitted wave with respect to the direction is θw. At this time, the angles φ_1 to φ_M are preferably set to values obtained by dividing the angle range Δφ of the lower limit value φ_min or more and the upper limit value φ_max or less into M equal parts. Here, the lower limit value φ_min is a value based on the following equation (1). The upper limit value φ_max is a value based on the following equation (2).
　φ＿ｍｉｎ＝θｃ－（θｗ／２）　　（１）
　φ＿ｍａｘ＝θｃ＋（θｗ／２）　　（２） φ_min = θc− (θw / 2) (1)
φ_max = θc + (θw / 2) (2)
　すなわち、これは、下限値φ＿ｍｉｎ未満の角度範囲における障害物Ｏには探査波が照射されないことを考慮したものである。また、これは、上限値φ＿ｍａｘを超える角度範囲における障害物Ｏには探査波が照射されないことを考慮したものである。 That is, this is in consideration of not irradiating the obstacle O in the angle range below the lower limit value φ_min with the exploration wave. Further, this is in consideration of not irradiating the obstacle O in the angle range exceeding the upper limit value φ_max with the exploration wave.
　なお、障害物検知装置１００ａは、実施の形態１にて説明したものと同様の種々の変形例を採用することができる。また、駐車支援システム３００ａは、実施の形態１にて説明したものと同様の種々の変形例を採用することができる。 Note that the obstacle detection device 100a can employ various modifications similar to those described in the first embodiment. Further, the parking support system 300a can adopt various modifications similar to those described in the first embodiment.
　以上のように、グループ化部１４ａは、反射点配列方向が車両１の移動方向に対して平行な状態となるように個々の反射点座標値Ｃ＿Ｘ，Ｃ＿Ｙを補正する。これにより、車両１の進路にかかわらず、個々の障害物Ｏに対応する反射点群ＰＧを設定することができる。 As described above, the grouping unit 14a corrects the individual reflection point coordinate values C_X and C_Y so that the reflection point arrangement direction is parallel to the movement direction of the vehicle 1. As a result, the reflection point cloud group PG corresponding to each obstacle O can be set regardless of the course of the vehicle 1.
実施の形態３．
　図３３は、実施の形態３に係る障害物検知装置を含む駐車支援システムの要部を示すブロック図である。図３４は、実施の形態３に係る障害物検知装置における識別部の要部を示すブロック図である。図３３及び図３４を参照して、実施の形態３に係る障害物検知装置について説明する。 Embodiment 3.
FIG. 33 is a block diagram showing a main part of the parking support system including the obstacle detection device according to the third embodiment. FIG. 34 is a block diagram showing a main part of the identification unit in the obstacle detection device according to the third embodiment. The obstacle detection device according to the third embodiment will be described with reference to FIGS. 33 and 34.
　なお、図３３において、図１に示すブロックと同様のブロックには同一符号を付して説明を省略する。また、図３４において、図４に示すブロックと同様のブロックには同一符号を付して説明を省略する。 Note that, in FIG. 33, the same blocks as those shown in FIG. 1 are designated by the same reference numerals, and the description thereof will be omitted. Further, in FIG. 34, the same blocks as those shown in FIG. 4 are designated by the same reference numerals, and the description thereof will be omitted.
　図３３に示す如く、車両１は、測距センサ２、障害物検知装置１００ｂ及び駐車支援装置２００ａを有している。測距センサ２、障害物検知装置１００ｂ及び駐車支援装置２００ａにより、駐車支援システム３００ｂの要部が構成されている。障害物検知装置１００ｂは、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４、識別部１５ａ及び出力部１６を有している。駐車支援装置２００ａは、駐車支援制御部２１ａを有している。図３４に示す如く、識別部１５ａは、幅判断部５１、位置判断部５２、高さ判断部５３及び動き判断部５４を有している。 As shown in FIG. 33, the vehicle 1 has a distance measuring sensor 2, an obstacle detection device 100b, and a parking support device 200a. The distance measuring sensor 2, the obstacle detection device 100b, and the parking support device 200a constitute a main part of the parking support system 300b. The obstacle detection device 100b includes an obstacle detection unit 11, a discontinuous unit detection unit 12, an analysis area extraction unit 13, a grouping unit 14, an identification unit 15a, and an output unit 16. The parking support device 200a has a parking support control unit 21a. As shown in FIG. 34, the identification unit 15a has a width determination unit 51, a position determination unit 52, a height determination unit 53, and a movement determination unit 54.
　動き判断部５４は、識別部１５ａにより取得された反射点情報を用いて、識別部１５ａにより駐車障害物であると識別された個々の障害物Ｏが動的障害物であるか否かを判断するものである。動き判断部５４による判断方法の具体例については後述する。 The motion determination unit 54 determines whether or not each obstacle O identified as a parking obstacle by the identification unit 15a is a dynamic obstacle by using the reflection point information acquired by the identification unit 15a. It is something to do. A specific example of the determination method by the motion determination unit 54 will be described later.
　以下、識別部１５ａにより実行される処理を総称して「識別処理」ということがある。すなわち、識別部１５ａにより実行される識別処理は、識別部１５により実行される識別処理に含まれる処理と同様の処理に加えて、個々の駐車障害物が動的障害物であるか否かを判断する処理などを含むものである。 Hereinafter, the processes executed by the identification unit 15a may be collectively referred to as "identification processing". That is, the identification process executed by the identification unit 15a determines whether or not each parking obstacle is a dynamic obstacle, in addition to the same process as the process included in the identification process executed by the identification unit 15. It includes the process of making a judgment.
　出力部１６は、識別処理の結果を示す信号、すなわち識別結果信号を駐車支援制御部２１ａに出力するものである。ここで、実施の形態３における識別結果信号は、個々の障害物Ｏが縁石であるか否かを示す情報、個々の障害物Ｏが駐車障害物であるか否かを示す情報、及び個々の障害物Ｏの位置を示す情報に加えて、個々の駐車障害物が動的障害物であるか否かを示す情報を含むものである。 The output unit 16 outputs a signal indicating the result of the identification process, that is, the identification result signal to the parking support control unit 21a. Here, the identification result signal in the third embodiment includes information indicating whether or not each obstacle O is a curb, information indicating whether or not each obstacle O is a parking obstacle, and individual obstacles. In addition to the information indicating the position of the obstacle O, the information indicating whether or not each parking obstacle is a dynamic obstacle is included.
　駐車支援制御部２１ａは、駐車支援制御部２１により実行される駐車支援制御と同様の駐車支援制御を実行するものである。すなわち、駐車支援制御部２１ａは、例えば、自動駐車を実現するための制御を実行するものである。 The parking support control unit 21a executes parking support control similar to the parking support control executed by the parking support control unit 21. That is, the parking support control unit 21a executes control for realizing automatic parking, for example.
　ただし、駐車支援制御部２１ａは、側方領域ＬＡに動的障害物が存在する場合、車両１の警笛を鳴らす制御を実行するとともに、動的障害物を自動駐車における回避の対象から除外するようになっている。これは、通常、動的障害物は人間を含むものであるところ、車両１が警笛を鳴らすことにより、動的障害部が車両１を回避するように移動する蓋然性が高いことを利用したものである。これにより、自動駐車において、車両１による不要な回避がなされるのを抑制することができる。 However, when a dynamic obstacle exists in the side area LA, the parking support control unit 21a executes a control for sounding the horn of the vehicle 1 and excludes the dynamic obstacle from the target of avoidance in automatic parking. It has become. This utilizes the fact that the dynamic obstacle usually includes a human being, but when the vehicle 1 sounds a horn, it is highly probable that the dynamic obstacle portion moves so as to avoid the vehicle 1. As a result, it is possible to prevent the vehicle 1 from making unnecessary avoidance in automatic parking.
　障害物検知装置１００ｂの要部のハードウェア構成は、実施の形態１にて図５及び図６を参照して説明したものと同様である。このため、図示及び説明を省略する。すなわち、障害物検知部１１、非連続部検知部１２、解析領域抽出部１３、グループ化部１４、識別部１５ａ及び出力部１６の各々の機能は、プロセッサ６１及びメモリ６２により実現されるものであっても良く、又は専用の処理回路６３により実現されるものであっても良い。 The hardware configuration of the main part of the obstacle detection device 100b is the same as that described with reference to FIGS. 5 and 6 in the first embodiment. Therefore, illustration and description will be omitted. That is, each function of the obstacle detection unit 11, the discontinuous unit detection unit 12, the analysis area extraction unit 13, the grouping unit 14, the identification unit 15a, and the output unit 16 is realized by the processor 61 and the memory 62. It may be present, or it may be realized by a dedicated processing circuit 63.
　駐車支援装置２００ａの要部のハードウェア構成は、実施の形態１にて図７及び図８を参照して説明したものと同様である。このため、図示及び説明を省略する。すなわち、駐車支援制御部２１ａの機能は、プロセッサ７１及びメモリ７２により実現されるものであっても良く、又は専用の処理回路７３により実現されるものであっても良い。 The hardware configuration of the main part of the parking support device 200a is the same as that described with reference to FIGS. 7 and 8 in the first embodiment. Therefore, illustration and description will be omitted. That is, the function of the parking support control unit 21a may be realized by the processor 71 and the memory 72, or may be realized by the dedicated processing circuit 73.
　次に、図３５を参照して、駐車支援システム３００ｂの動作について、障害物検知装置１００ｂ及び駐車支援装置２００ａの動作を中心に説明する。なお、図３５において、図９に示すステップと同様のステップには同一符号を付して説明を省略する。 Next, with reference to FIG. 35, the operation of the parking support system 300b will be described focusing on the operations of the obstacle detection device 100b and the parking support device 200a. In FIG. 35, the same steps as those shown in FIG. 9 are designated by the same reference numerals, and the description thereof will be omitted.
　まず、ステップＳＴ１～ＳＴ４の処理が実行される。次いで、識別部１５ａが識別処理を実行する（ステップＳＴ５ａ）。次いで、ステップＳＴ６の処理が実行される。次いで、駐車支援制御部２１ａが駐車支援制御を実行する（ステップＳＴ７ａ）。 First, the processes of steps ST1 to ST4 are executed. Next, the identification unit 15a executes the identification process (step ST5a). Next, the process of step ST6 is executed. Next, the parking support control unit 21a executes parking support control (step ST7a).
　次に、動き判断部５４による判断方法の第１具体例について説明する。 Next, a first specific example of the determination method by the motion determination unit 54 will be described.
　動き判断部５４は、個々の反射点ＲＰに対応する反射点情報に含まれる波形情報を用いて、個々の反射点ＲＰに対応する受信信号ＲＳの波形に対する周波数分析を実行する。これにより、第１ドップラーシフト量が算出される。次いで、動き判断部５４は、当該算出された第１ドップラーシフト量から車両１の移動による成分を差し引く。これにより、第２ドップラーシフト量が算出される。このとき、車両１の移動による成分は、車両速度情報を用いて算出される。車両速度情報は、例えば、障害物検知装置１００ｂがＣＡＮ通信により取得したものである。 The motion determination unit 54 executes frequency analysis on the waveform of the received signal RS corresponding to each reflection point RP by using the waveform information included in the reflection point information corresponding to each reflection point RP. As a result, the first Doppler shift amount is calculated. Next, the motion determination unit 54 subtracts the component due to the movement of the vehicle 1 from the calculated first Doppler shift amount. As a result, the second Doppler shift amount is calculated. At this time, the component due to the movement of the vehicle 1 is calculated using the vehicle speed information. The vehicle speed information is, for example, acquired by the obstacle detection device 100b by CAN communication.
　すなわち、第１ドップラーシフト量は、対応する障害物Ｏの車両１に対する相対的な移動に基づくドップラーシフト量である。これに対して、第２ドップラーシフト量は、対応する障害物Ｏの絶対的な移動に基づくドップラーシフト量である。 That is, the first Doppler shift amount is the Doppler shift amount based on the relative movement of the corresponding obstacle O with respect to the vehicle 1. On the other hand, the second Doppler shift amount is a Doppler shift amount based on the absolute movement of the corresponding obstacle O.
　次いで、動き判断部５４は、当該算出された第２ドップラーシフト量と対応する反射波が受信された時点における音速とに基づき、対応する障害物Ｏの移動速度を算出する。このとき、当該時点における音速は、当該時点における車外温度を示す情報（以下「温度情報」という。）及び当該時点における車外湿度を示す情報（以下「湿度情報」という。）を用いて算出される。温度情報及び湿度情報は、例えば、障害物検知装置１００ｂがＣＡＮ通信により取得したものである。 Next, the motion determination unit 54 calculates the moving speed of the corresponding obstacle O based on the calculated second Doppler shift amount and the speed of sound at the time when the corresponding reflected wave is received. At this time, the speed of sound at that time is calculated using information indicating the temperature outside the vehicle at that time (hereinafter referred to as "temperature information") and information indicating humidity outside the vehicle at that time (hereinafter referred to as "humidity information"). .. The temperature information and humidity information are, for example, acquired by the obstacle detection device 100b by CAN communication.
　次いで、動き判断部５４は、当該算出された移動速度を所定の閾値と比較する。移動速度が閾値よりも大きい場合、動き判断部５４は、対応する障害物Ｏが動的障害物であると判断する。そうでない場合、動き判断部５４は、対応する障害物Ｏが動的障害物でないと判断する。 Next, the motion determination unit 54 compares the calculated movement speed with a predetermined threshold value. When the movement speed is larger than the threshold value, the movement determination unit 54 determines that the corresponding obstacle O is a dynamic obstacle. If not, the motion determination unit 54 determines that the corresponding obstacle O is not a dynamic obstacle.
　次に、図３６及び図３７を参照して、動き判断部５４による判断方法の第２具体例について説明する。 Next, a second specific example of the determination method by the motion determination unit 54 will be described with reference to FIGS. 36 and 37.
　通常、動的障害物（例えば歩行者）の表面形状は、静的障害物（例えば電柱、ポール又は看板）の表面形状に比して複雑である。このため、動的障害物に対応する受信信号波形は、所定の幅ｗを有する判断用の時間窓（以下「判断窓」という。）ＪＷ内に複数個のピーク部Ｐを有するものとなる。すなわち、動的障害物に対応する受信信号波形は、略林状のピーク部Ｐを有するものとなる。図３６は、判断窓ＪＷ内に３個のピーク部Ｐ＿１，Ｐ＿２，Ｐ＿３を有する受信信号波形の例を示している。幅ｗは、例えば、狭幅障害物に係る識別用の閾値Ｗ＿ｔｈ＿１に対応する値に設定されている。 Normally, the surface shape of a dynamic obstacle (for example, a pedestrian) is more complicated than the surface shape of a static obstacle (for example, a utility pole, pole or signboard). Therefore, the received signal waveform corresponding to the dynamic obstacle has a plurality of peak portions P in the judgment time window (hereinafter referred to as “judgment window”) JW having a predetermined width w. That is, the received signal waveform corresponding to the dynamic obstacle has a substantially forest-like peak portion P. FIG. 36 shows an example of a received signal waveform having three peak portions P_1, P_2, and P_3 in the determination window JW. The width w is set to a value corresponding to, for example, the threshold value W_th_1 for identification of a narrow obstacle.
　他方、静的障害物（例えば電柱、ポール又は看板）の表面形状は、動的障害物（例えば歩行者）の表面形状に比して単純である。このため、静的障害物に対応する受信信号波形は、判断窓ＪＷ内に１個のピーク部Ｐを有するものとなる。すなわち、静的障害物に対応する受信信号波形は、略板状のピーク部Ｐを有するものとなる。図３７は、判断窓ＪＷ内に１個のピーク部Ｐを有する受信信号波形の例を示している。 On the other hand, the surface shape of a static obstacle (for example, a utility pole, pole or signboard) is simpler than the surface shape of a dynamic obstacle (for example, a pedestrian). Therefore, the received signal waveform corresponding to the static obstacle has one peak portion P in the determination window JW. That is, the received signal waveform corresponding to the static obstacle has a substantially plate-shaped peak portion P. FIG. 37 shows an example of a received signal waveform having one peak portion P in the determination window JW.
　そこで、動き判断部５４は、個々の反射点ＲＰに対応する反射点情報に含まれる波形情報を用いて、個々の反射点ＥＰに対応する受信信号波形における判断窓ＪＷ内のピーク部Ｐの個数を算出する。当該算出された個数が所定数（例えば２個）以上である場合、動き判断部５４は、対応する障害物Ｏが動的障害物であると判断する。そうでない場合、動き判断部５４は、対応する障害物Ｏが動的障害物でないと判断する。 Therefore, the motion determination unit 54 uses the waveform information included in the reflection point information corresponding to each reflection point RP, and the number of peak portions P in the determination window JW in the received signal waveform corresponding to each reflection point EP. Is calculated. When the calculated number is a predetermined number (for example, two) or more, the motion determination unit 54 determines that the corresponding obstacle O is a dynamic obstacle. If not, the motion determination unit 54 determines that the corresponding obstacle O is not a dynamic obstacle.
　なお、障害物検知装置１００ｂは、実施の形態１にて説明したものと同様の種々の変形例を採用することができる。また、駐車支援システム３００ｂは、実施の形態１にて説明したものと同様の種々の変形例を採用することができる。 Note that the obstacle detection device 100b can employ various modifications similar to those described in the first embodiment. Further, the parking support system 300b can adopt various modifications similar to those described in the first embodiment.
　また、障害物検知装置１００ｂは、グループ化部１４に代えてグループ化部１４ａを有するものであっても良い。この場合、障害物検知装置１００ｂは、実施の形態２にて説明したものと同様の種々の変形例を採用することができる。 Further, the obstacle detection device 100b may have a grouping unit 14a instead of the grouping unit 14. In this case, the obstacle detection device 100b can employ various modifications similar to those described in the second embodiment.
　以上のように、識別部１５ａは、駐車障害物が動的障害物であるか否かを判断する。これにより、駐車障害物が動的障害物であるか否かの判断結果を駐車支援制御に用いることができる。この結果、より適切な駐車支援制御を実現することができる。 As described above, the identification unit 15a determines whether or not the parking obstacle is a dynamic obstacle. Thereby, the determination result of whether or not the parking obstacle is a dynamic obstacle can be used for the parking support control. As a result, more appropriate parking support control can be realized.
　なお、本願発明はその発明の範囲内において、各実施の形態の自由な組み合わせ、あるいは各実施の形態の任意の構成要素の変形、もしくは各実施の形態において任意の構成要素の省略が可能である。 In the present invention, within the scope of the invention, it is possible to freely combine each embodiment, modify any component of each embodiment, or omit any component in each embodiment. ..
　本発明の障害物検知装置は、駐車支援システムに用いることができる。 The obstacle detection device of the present invention can be used in a parking support system.
　１　車両、２　測距センサ、１１　障害物検知部、１２　非連続部検知部、１３　解析領域抽出部、１４，１４ａ　グループ化部、１５，１５ａ　識別部、１６　出力部、２１，２１ａ　駐車支援制御部、３１　送信信号出力部、３２　受信信号取得部、３３　測距値算出部、３４　座標値算出部、４１　第１解析部、４２　第２解析部、４３　補正部、５１　幅判断部、５２　位置判断部、５３　高さ判断部、５４　動き判断部、６１　プロセッサ、６２　メモリ、６３　処理回路、７１　プロセッサ、７２　メモリ、７３　処理回路、１００，１００ａ，１００ｂ　障害物検知装置、２００，２００ａ　駐車支援装置、３００，３００ａ，３００ｂ　駐車支援システム。 1 vehicle, 2 ranging sensor, 11 obstacle detection unit, 12 discontinuous part detection unit, 13 analysis area extraction unit, 14,14a grouping unit, 15,15a identification unit, 16 output unit, 21,21a parking support control Unit, 31 Transmission signal output unit, 32 Received signal acquisition unit, 33 Distance measurement value calculation unit, 34 Coordinate value calculation unit, 41 First analysis unit, 42 Second analysis unit, 43 Correction unit, 51 Width determination unit, 52 Position Judgment unit, 53 height judgment unit, 54 movement judgment unit, 61 processor, 62 memory, 63 processing circuit, 71 processor, 72 memory, 73 processing circuit, 100, 100a, 100b obstacle detection device, 200, 200a parking support device , 300, 300a, 300b Parking support system.

Claims (11)

  1. 　車両に設けられた測距センサを用いて、移動中の前記車両に対する側方領域における障害物群を検知する障害物検知部と、
    　前記障害物群における非連続部を検知する非連続部検知部と、
    　前記非連続部に基づく解析領域を抽出する解析領域抽出部と、
    　前記解析領域における複数個の反射点に係る度数分布を解析することにより、前記障害物群に含まれる複数個の障害物に対応する複数個の反射点群を設定するグループ化部と、
    　前記複数個の障害物の各々が縁石であるか否かを識別するとともに、前記複数個の障害物の各々が駐車障害物であるか否かを識別する識別部と、
    　前記縁石と前記駐車障害物間の距離が所定距離以下であるとき、少なくとも前記駐車障害物の位置を示す信号を出力する出力部と、
    　を備える障害物検知装置。     An obstacle detection unit that detects a group of obstacles in a lateral region with respect to the moving vehicle using a distance measuring sensor provided on the vehicle.
    A discontinuous portion detecting unit that detects a discontinuous portion in the obstacle group, and a discontinuous portion detecting unit.
    An analysis area extraction unit that extracts an analysis area based on the discontinuous part, and an analysis area extraction unit.
    By analyzing the frequency distribution related to the plurality of reflection points in the analysis region, a grouping unit for setting a plurality of reflection point groups corresponding to the plurality of obstacles included in the obstacle group, and a grouping unit.
    An identification unit that identifies whether or not each of the plurality of obstacles is a curb, and also identifies whether or not each of the plurality of obstacles is a parking obstacle.
    When the distance between the curb and the parking obstacle is less than or equal to a predetermined distance, at least an output unit that outputs a signal indicating the position of the parking obstacle, and
    Obstacle detection device equipped with.
  2. 　前記非連続部検知部は、第１条件が満たされたとき前記非連続部を検知するものであり、
    　前記第１条件は、第ｎ波に対応する複数個の反射点における反射点間距離が算出される場合において、当該算出された反射点間距離が閾値を超えるという条件である
    　ことを特徴とする請求項１記載の障害物検知装置。     The discontinuous portion detecting unit detects the discontinuous portion when the first condition is satisfied.
    The first condition is a condition that the calculated distance between reflection points exceeds a threshold value when the distances between reflection points at a plurality of reflection points corresponding to the nth wave are calculated. The obstacle detection device according to claim 1.
  3. 　前記非連続部検知部は、第２条件が満たされたとき前記非連続部を検知するものであり、
    　前記第２条件は、各回の送信波に対応する１個以上の測距値における分散値が算出される場合において、当該算出された分散値の変化量が算出されるとき、当該算出された変化量が閾値を超えるという条件である
    　ことを特徴とする請求項１記載の障害物検知装置。     The discontinuous portion detecting unit detects the discontinuous portion when the second condition is satisfied.
    The second condition is that when the variance value in one or more ranging values corresponding to each transmitted wave is calculated and the amount of change in the calculated variance value is calculated, the calculated change. The obstacle detection device according to claim 1, wherein the amount exceeds a threshold value.
  4. 　前記非連続部検知部は、第３条件が満たされたとき前記非連続部を検知するものであり、
    　前記第３条件は、算出済みの複数組の反射点座標値における連続性に基づき未算出の少なくとも１組の反射点座標値の予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である
    　ことを特徴とする請求項１記載の障害物検知装置。     The discontinuous portion detecting unit detects the discontinuous portion when the third condition is satisfied.
    The third condition relates to the calculated predicted value when the predicted value of at least one set of uncalculated reflection point coordinate values is calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values. The obstacle detection device according to claim 1, wherein when the residual value is calculated, the calculated residual value exceeds a threshold value.
  5. 　前記非連続部検知部は、第１条件及び第２条件のうちの少なくとも一方が満たされたとき前記非連続部を検知するものであり、
    　前記第１条件は、第ｎ波に対応する複数個の反射点における反射点間距離が算出される場合において、当該算出された反射点間距離が閾値を超えるという条件であり、
    　前記第２条件は、各回の送信波に対応する１個以上の測距値における分散値が算出される場合において、当該算出された分散値の変化量が算出されるとき、当該算出された変化量が閾値を超えるという条件である
    　ことを特徴とする請求項１記載の障害物検知装置。     The discontinuous portion detecting unit detects the discontinuous portion when at least one of the first condition and the second condition is satisfied.
    The first condition is a condition that the calculated distance between reflection points exceeds a threshold value when the distances between reflection points at a plurality of reflection points corresponding to the nth wave are calculated.
    The second condition is that when the variance value in one or more distance measurement values corresponding to each transmitted wave is calculated and the amount of change in the calculated variance value is calculated, the calculated change. The obstacle detection device according to claim 1, wherein the amount exceeds a threshold value.
  6. 　前記非連続部検知部は、第１条件及び第３条件のうちの少なくとも一方が満たされたとき前記非連続部を検知するものであり、
    　前記第１条件は、第ｎ波に対応する複数個の反射点における反射点間距離が算出される場合において、当該算出された反射点間距離が閾値を超えるという条件であり、
    　前記第３条件は、算出済みの複数組の反射点座標値における連続性に基づき未算出の少なくとも１組の反射点座標値の予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である
    　ことを特徴とする請求項１記載の障害物検知装置。     The discontinuous portion detecting unit detects the discontinuous portion when at least one of the first condition and the third condition is satisfied.
    The first condition is a condition that the calculated distance between reflection points exceeds a threshold value when the distances between reflection points at a plurality of reflection points corresponding to the nth wave are calculated.
    The third condition relates to the calculated predicted value when the predicted value of at least one set of uncalculated reflection point coordinate values is calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values. The obstacle detection device according to claim 1, wherein when the residual value is calculated, the calculated residual value exceeds a threshold value.
  7. 　前記非連続部検知部は、第２条件及び第３条件のうちの少なくとも一方が満たされたとき前記非連続部を検知するものであり、
    　前記第２条件は、各回の送信波に対応する１個以上の測距値における分散値が算出される場合において、当該算出された分散値の変化量が算出されるとき、当該算出された変化量が閾値を超えるという条件であり、
    　前記第３条件は、算出済みの複数組の反射点座標値における連続性に基づき未算出の少なくとも１組の反射点座標値の予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である
    　ことを特徴とする請求項１記載の障害物検知装置。     The discontinuous portion detecting unit detects the discontinuous portion when at least one of the second condition and the third condition is satisfied.
    The second condition is that when the variance value in one or more distance measurement values corresponding to each transmitted wave is calculated and the amount of change in the calculated variance value is calculated, the calculated change. The condition is that the amount exceeds the threshold.
    The third condition relates to the calculated predicted value when the predicted value of at least one set of uncalculated reflection point coordinate values is calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values. The obstacle detection device according to claim 1, wherein when the residual value is calculated, the calculated residual value exceeds a threshold value.
  8. 　前記非連続部検知部は、第１条件、第２条件及び第３条件のうちの少なくとも一つが満たされたとき前記非連続部を検知するものであり、
    　前記第１条件は、第ｎ波に対応する複数個の反射点における反射点間距離が算出される場合において、当該算出された反射点間距離が閾値を超えるという条件であり、
    　前記第２条件は、各回の送信波に対応する１個以上の測距値における分散値が算出される場合において、当該算出された分散値の変化量が算出されるとき、当該算出された変化量が閾値を超えるという条件であり、
    　前記第３条件は、算出済みの複数組の反射点座標値における連続性に基づき未算出の少なくとも１組の反射点座標値の予測値が算出される場合において、当該算出された予測値に係る残差値が算出されるとき、当該算出された残差値が閾値を超えるという条件である
    　ことを特徴とする請求項１記載の障害物検知装置。     The discontinuous portion detecting unit detects the discontinuous portion when at least one of the first condition, the second condition, and the third condition is satisfied.
    The first condition is a condition that the calculated distance between reflection points exceeds a threshold value when the distances between reflection points at a plurality of reflection points corresponding to the nth wave are calculated.
    The second condition is that when the variance value in one or more distance measurement values corresponding to each transmitted wave is calculated and the amount of change in the calculated variance value is calculated, the calculated change. The condition is that the amount exceeds the threshold.
    The third condition relates to the calculated predicted value when the predicted value of at least one set of uncalculated reflection point coordinate values is calculated based on the continuity of the calculated plurality of sets of reflection point coordinate values. The obstacle detection device according to claim 1, wherein when the residual value is calculated, the calculated residual value exceeds a threshold value.
  9. 　前記解析領域抽出部は、前記解析領域に対応する測距値の算出数が所定数を超えたとき、前記解析領域を複数個の解析領域に分割することを特徴とする請求項１記載の障害物検知装置。 The obstacle according to claim 1, wherein the analysis area extraction unit divides the analysis area into a plurality of analysis areas when the number of calculated distance measurement values corresponding to the analysis area exceeds a predetermined number. Object detection device.
  10. 　前記グループ化部は、反射点配列方向が前記車両の移動方向に対して平行な状態となるように個々の反射点座標値を補正することを特徴とする請求項１記載の障害物検知装置。 The obstacle detection device according to claim 1, wherein the grouping unit corrects individual reflection point coordinate values so that the reflection point arrangement direction is parallel to the moving direction of the vehicle.
  11. 　前記識別部は、前記駐車障害物が動的障害物であるか否かを判断することを特徴とする請求項１記載の障害物検知装置。 The obstacle detection device according to claim 1, wherein the identification unit determines whether or not the parking obstacle is a dynamic obstacle.
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