WO2020070908A1 - Detection device, moving body system, and detection method - Google Patents

Detection device, moving body system, and detection method

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Publication number
WO2020070908A1
WO2020070908A1 PCT/JP2019/009926 JP2019009926W WO2020070908A1 WO 2020070908 A1 WO2020070908 A1 WO 2020070908A1 JP 2019009926 W JP2019009926 W JP 2019009926W WO 2020070908 A1 WO2020070908 A1 WO 2020070908A1
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WO
WIPO (PCT)
Prior art keywords
blind spot
detection
control unit
risk
detection device
Prior art date
Application number
PCT/JP2019/009926
Other languages
French (fr)
Japanese (ja)
Inventor
圭記 松浦
宜崇 鶴亀
直毅 吉武
Original Assignee
オムロン株式会社
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.)
Filing date
Publication date
Application filed by オムロン株式会社 filed Critical オムロン株式会社
Publication of WO2020070908A1 publication Critical patent/WO2020070908A1/en

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Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60RVEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R21/00Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/16Anti-collision systems

Definitions

  • the present disclosure relates to a detection device that detects a nearby object from a moving object, a moving object system including the detection device, and a detection method.
  • Patent Documents 1 and 2 A technology has been proposed that is mounted on a mobile object such as an automobile or an AGV (automatic guided vehicle) and monitors the periphery of the mobile object (for example, Patent Documents 1 and 2).
  • Patent Document 1 discloses a driving assistance device including an obstacle recognition device that recognizes an obstacle in front of a host vehicle.
  • the obstacle recognition device of Patent Literature 1 detects a blind spot area with respect to the own vehicle in order to recognize an obstacle that appears from a blind spot with respect to the own vehicle.
  • the driving support device estimates the danger to the obstacle based on the detection result of the obstacle recognition device, and notifies a warning or the like for guiding the user to avoid the obstacle when the danger to the obstacle is lower than a predetermined value. When the degree of danger is higher than a predetermined value, control is performed such that the own vehicle runs automatically.
  • Patent Document 2 discloses a vehicle environment estimating apparatus for accurately estimating a traveling environment around a host vehicle.
  • the vehicle environment estimating device of Patent Literature 2 detects the behavior of another vehicle in the vicinity of the own vehicle, and estimates the presence of another vehicle traveling in a blind spot area from the own vehicle based on the behavior of the vehicle. .
  • the driving control of the own vehicle is performed by using the estimation result of such a blind spot area, for example, for predicting the vehicle speed of another vehicle preceding the own vehicle.
  • Patent Document 1 various controls for driving assistance are performed by determining whether the risk estimated based on the detection result of the blind spot area is higher or lower than a predetermined value.
  • the criterion for determining the degree of danger is a predetermined value regardless of the surrounding environment outside the blind spot, and in the related art, even in a situation of the surrounding environment where it is considered that the object in the blind spot is unlikely to hinder the traveling of the own vehicle, This has led to erroneous determination of the risk of causing excessive operation control.
  • An object of the present disclosure is a detection device, a detection method, and a mobile body system that can suppress excessive erroneous determination of a risk level when detecting an object with respect to a blind spot in a surrounding environment of the mobile body and determining the risk level. Is to provide.
  • a detection device is a device that detects an object in a surrounding environment including a path of a moving object.
  • the detection device includes a detection unit and a control unit.
  • the detection unit detects distance information indicating a distance from the moving body to a surrounding environment.
  • the control unit controls the detection unit.
  • the control unit detects a blind spot area indicating a blind spot in the surrounding environment based on the detection result of the detection unit, and determines the degree of risk related to the blind spot area based on the detection result of the blind spot area.
  • the control unit relaxes the risk criterion when an object is present at a junction where the detected blind spot area and the path of the moving body merge.
  • a mobile body system includes the above-described detection device, and a control device mounted on the mobile body and performing an operation according to a result of the determination of the degree of risk by the detection device.
  • the detection method is a method of detecting an object in a surrounding environment including a path of a moving object.
  • the detecting unit detects distance information indicating a distance from the moving body to the surrounding environment
  • the control unit detects a blind spot area indicating a blind spot in the surrounding environment based on a detection result of the detecting unit.
  • the method includes a step of, when an object is present at a merging point where the blind spot area and the path of the moving body merge, the control unit relaxes the criterion for determining the degree of risk.
  • the detection device the mobile body system, and the detection method according to the present disclosure, it is possible to suppress an erroneous determination of an excessive risk when detecting an object with respect to a blind spot in a surrounding environment of the mobile and determining the risk. Can be.
  • FIG. 1 is a block diagram illustrating a configuration of a mobile system according to a first embodiment of the present disclosure.
  • FIG. 4 is a diagram for explaining the operation of the detection device according to the first embodiment.
  • FIG. 8 illustrates a case where there is a blind spot object in the experiment of FIG. 8.
  • FIG. 4 is a flowchart illustrating a blind spot object detection process performed by the detection device
  • the flowchart which illustrates the judgment process of the danger degree by a detection apparatus
  • the figure for explaining the judgment processing of the degree of danger by the detection device Diagram for explaining a modification of the operation of the detection device
  • Flowchart for explaining a modification of the operation of the detection device
  • FIG. 1 is a diagram for describing an application example of the detection device 1 according to the present disclosure.
  • FIG. 2 is a diagram illustrating a case where an object is present at a merging point in this application example.
  • the detection device 1 is applicable to, for example, in-vehicle use, and constitutes a mobile body system in a mobile body such as an automobile.
  • FIG. 1 illustrates a running state of a vehicle 2 on which the detection device 1 is mounted.
  • the mobile system according to the application example monitors, for example, the surrounding environment that changes around the own vehicle 2 that is traveling using the detection device 1.
  • the surrounding environment includes, for example, structures such as buildings and electric poles existing around the vehicle 2 and various objects such as moving objects such as pedestrians and other vehicles.
  • the range that can be monitored from the host vehicle 2 is blocked by the wall 31 of the structure near the intersection 3, and a blind spot occurs.
  • the blind spot indicates a location that cannot be directly viewed geometrically from a moving object such as the host vehicle 2 in accordance with the surrounding environment.
  • another vehicle 4 approaching the intersection 3 from a side road exists in a blind spot region R1 which is a blind spot from the own vehicle 2.
  • the vehicle 4 and the host vehicle 2 from the blind spot may collide with each other at the intersection.
  • the detection device 1 of the present embodiment executes detection of an object (hereinafter, sometimes referred to as “blind spot object”) existing in the blind spot region R1 such as the vehicle 4, and based on the detection result of the blind spot object 4.
  • Determine the degree of risk The risk relates to, for example, the possibility that the host vehicle 2 and the blind spot object 4 may collide.
  • the detection device 1 can perform various types of control of driving support or driving control for warning to avoid a collision at an intersection based on the determination result of the degree of danger.
  • FIG. 2 illustrates a case where the preceding vehicle 5 exists in the same surrounding environment as in FIG.
  • the front vehicle 5 travels ahead of the host vehicle 2 on the path where the host vehicle 2 travels, and is located at the intersection 3.
  • the side road including the blind spot area R1 joins the course of the host vehicle 2, and the position of the preceding vehicle 5 is right beside the blind spot area R1.
  • the intersection 3 is an example of a merging point
  • the preceding vehicle 5 is an example of an object existing at the same point.
  • the preceding vehicle 5 as described above alerts the blind spot object (vehicle) 4 as a result of being visually recognized by the driver of the vehicle 4 in the blind spot area R1, for example. From this, the risk of collision of the encounter between the own vehicle 2 and the blind spot object 4 or the possibility that the blind spot object 4 becomes an obstacle to the running of the own vehicle is higher than the case where there is no preceding vehicle 5 (see FIG. 1). It is considered low. In such a case, using the same criterion for determining the degree of danger as in the case where there is no preceding vehicle 5 causes an excessive warning or the like such that the above control is performed even in a situation where a warning is not actually required. Can be considered.
  • the detection device 1 of the present embodiment relaxes the risk criterion when there is an object such as the preceding vehicle 5 located at the intersection 3 where the blind spot region R1 and the host vehicle 2 meet. I do. Thereby, erroneous determination of the degree of danger can be suppressed according to the situation of the surrounding environment of the own vehicle 2, an excessive warning or the like can be avoided, and the driving of the own vehicle 2 can be performed smoothly.
  • FIG. 3 is a block diagram illustrating the configuration of the present system.
  • the detection device 1 of the present embodiment includes a radar 11, a camera 12, and a control unit 13. Further, for example, the detection device 1 includes a storage unit 14, a navigation device 15, and an in-vehicle sensor 16.
  • the vehicle control device 20 includes various in-vehicle devices mounted on the host vehicle 2, and is used for, for example, driving assistance or automatic driving.
  • the radar 11 and the camera 12 are each an example of a detection unit that detects distance information.
  • the radar 11 includes, for example, a transmitter 11a, a receiver 11b, and a radar control circuit 11c.
  • the radar 11 is installed on, for example, a front grill or a windshield of the host vehicle 2 so as to transmit and receive signals forward (see FIG. 1) in the traveling direction of the host vehicle 2.
  • the transmitter 11a includes, for example, an antenna having a variable directivity (a phased array antenna or the like), a transmission circuit that causes the antenna to externally transmit the physical signal Sa, and the like.
  • the physical signal Sa includes, for example, at least one of a millimeter wave, a microwave, a radio wave, and a terahertz wave.
  • the receiver 11b includes, for example, an antenna having variable directivity, and a receiving circuit that receives the wave signal Sb from outside using the antenna.
  • the wave signal Sb is set in the same wavelength band as the physical signal Sa so as to include the reflected wave of the physical signal Sa.
  • the transmitter 11a and the receiver 11b may use a common antenna, for example, or may be configured integrally.
  • the radar control circuit 11c controls transmission and reception of signals by the transmitter 11a and the receiver 11b.
  • the radar control circuit 11c starts transmission and reception of signals by the radar 11 and controls the direction in which the physical signal Sa is emitted from the transmitter 11a, for example, by a control signal from the control unit 13. Further, the radar control circuit 11c causes the transmitter 11a to emit a physical signal Sa to the surrounding environment, and detects a wave signal Sb indicating a reflected wave of the physical signal Sa in the reception result of the receiver 11b.
  • the radar 11 operates according to a modulation method such as a CW (continuous wave) method or a pulse method, and measures the distance, azimuth, speed, and the like of an external object.
  • the CW method includes a two-wave CW method, an FM-CW method, a spread spectrum method, and the like.
  • the pulse method may be a pulse Doppler method, or pulse compression of a chirp signal or pulse compression of a PN sequence may be used.
  • the radar 11 uses, for example, coherent phase information control.
  • the radar 11 may use an incoherent method.
  • the camera 12 is installed at a position where, for example, the range in which the physical signal Sa can be radiated from the radar 11 in the own vehicle 2 can be imaged.
  • the camera 12 is installed on a windshield or the like of the host vehicle 2 toward the front of the host vehicle 2 (see FIG. 1), for example.
  • the blind spot in the detection device 1 may be based on the installation position of the camera 12 as a geometric reference or based on the installation position of the radar 11.
  • the camera 12 captures an external image from the installation position and generates a captured image.
  • the camera 12 outputs image data indicating the captured image to the control unit 13.
  • the camera 12 is, for example, an RGB-D camera, a stereo camera, or a range image sensor.
  • the camera 12 is an example of a distance measuring unit (or a monitoring unit) in the present embodiment.
  • the control unit 13 includes a CPU, a RAM, a ROM, and the like, and controls each component according to information processing.
  • the control unit 13 is configured by, for example, an ECU (electronic control unit).
  • the control unit 13 expands the program stored in the storage unit 14 on the RAM, and interprets and executes the program expanded on the RAM by the CPU.
  • the control unit 13 implements a blind spot estimation unit 131, a blind spot object measurement unit 132, and a risk determination unit 133. Each of the units 131 to 133 will be described later.
  • the storage unit 14 stores programs executed by the control unit 13, various data, and the like.
  • the storage unit 14 stores structure information D1 described below.
  • the storage unit 14 includes, for example, a hard disk drive or a solid state drive. Further, the RAM and the ROM may be included in the storage unit 14.
  • the above-mentioned programs and the like may be stored in a portable storage medium.
  • the storage medium stores the information such as the program by an electrical, magnetic, optical, mechanical or chemical action so that the computer or the like can read the information such as the recorded program by a machine or the like.
  • the detection device 1 may acquire a program or the like from the storage medium.
  • the navigation device 15 is an example of a distance measuring unit (monitoring unit) including a memory for storing map information and a GPS receiver, for example.
  • the in-vehicle sensors 16 are various sensors mounted on the host vehicle 2, and include, for example, a vehicle speed sensor, an acceleration sensor, a gyro sensor, and the like.
  • the on-vehicle sensor 16 detects the speed, acceleration, angular velocity, and the like of the vehicle 2.
  • the detection device 1 is not limited to the above configuration.
  • the detection device 1 may not include the navigation device 15 and the vehicle-mounted sensor 16.
  • the control unit 13 of the detection device 1 may be configured by a plurality of hardware resources that execute the units 131 to 133 separately.
  • the control unit 13 may be configured by various semiconductor integrated circuits such as a CPU, an MPU, a GPU, a microcomputer, a DSP, an FPGA, and an ASIC.
  • the vehicle control device 20 is an example of a control device of the mobile system according to the present embodiment.
  • the vehicle control device 20 includes, for example, a vehicle drive unit 21 and an alarm 22.
  • the vehicle drive unit 21 is configured by, for example, an ECU, and controls driving of each unit of the host vehicle 2.
  • the vehicle drive unit 21 controls the brake of the own vehicle 2 to realize automatic braking.
  • the notifier 22 notifies the user of various kinds of information by images or sounds.
  • the alarm 22 is a display device such as a liquid crystal panel or an organic EL panel mounted on the vehicle 2.
  • the alarm 22 may be an audio output device that outputs an alarm or the like by audio.
  • the mobile system operates the detection device 1 so as to monitor the surrounding environment, for example, while the own vehicle 2 is operating.
  • the vehicle control device 20 of the present system performs various controls for driving support of the own vehicle 2 or automatic driving based on the detection result by the detection device 1.
  • the detection device 1 of the present embodiment captures an image around the own vehicle 2 with the camera 12, for example, and monitors the surrounding environment of the own vehicle 2.
  • the blind spot estimation unit 131 of the detection device 1 sequentially detects, for example, the presence or absence of an area where a blind spot is estimated in the current surrounding environment, based on distance information indicating various distances in the monitoring result.
  • the blind spot object measurement unit 132 uses the radar 11 to measure the internal state of the blind spot region R1. Since the physical signal Sa radiated from the radar 11 of the own vehicle 2 has a wave-like property, the physical signal Sa causes multiple reflections or diffractions to reach the blind spot object 4 in the blind spot area R1, and furthermore, the physical signal Sa is transmitted to the own vehicle 2. It is thought that the propagation of returning to may occur.
  • the detection method of the present embodiment detects the blind spot object 4 by utilizing the wave propagating as described above.
  • the risk determining unit 133 of the present embodiment determines the risk of the blind spot object 4 that can be included in the blind spot area R1 based on the measurement result of the blind spot object measuring unit 132.
  • the risk determination unit 133 can dynamically change a threshold value that is a reference for determining the risk.
  • the degree of danger indicates, for example, the degree to which a possibility of a collision between the blind spot object 4 and the host vehicle 2 is considered.
  • the present system when the detection device 1 determines the degree of danger that requires a warning, the present system notifies the driver or the like by the annunciator 22 or increases the safety of the automatic braking or the like by the vehicle drive unit 21. Or vehicle control of the vehicle. Details of the operation of the detection device 1 in the present system will be described below.
  • FIG. 4 is a flowchart for explaining the operation of the detection device 1 according to the present embodiment. Each process shown in the flowchart of FIG. 4 is executed by the control unit 13 of the detection device 1. This flowchart is started at a predetermined cycle while the vehicle 2 is operating, for example.
  • the control unit 13 acquires one or more frames of captured images from the camera 12 (S1).
  • the control unit 13 may acquire a distance image as a captured image, or may generate a distance image based on the acquired captured image.
  • the distance image is an example of distance information indicating various distances for monitoring the surrounding environment.
  • control unit 13 performs image analysis on the acquired captured image (S2), and generates structural information D1 relating to the current surrounding environment of the own vehicle 2.
  • the structure information D1 is information indicating various object structures in the surrounding environment, and includes, for example, distances to various structures.
  • the control unit 13 also operates as the blind spot estimation unit 131 in step S2, and performs image analysis for detecting a blind spot in the acquired captured image.
  • FIG. 5 illustrates an image to be analyzed in step S2.
  • FIG. 5 is, for example, an image taken from the host vehicle 2 as a distance image (S1), and shows walls 31 and 32 of a plurality of structures near the intersection 3.
  • a blind spot region R1 is present behind the wall 31 due to the shielding of the wall 31 near the host vehicle 2.
  • a wall 32 on the back side of the blind spot area R1 faces the host vehicle 2.
  • the wall 31 is referred to as a “shielding wall”, and the wall 32 is referred to as an “opposing wall”.
  • a boundary between the blind spot region R1 and the outside is formed between the shielding wall 31 and the opposing wall 32 (see FIG. 1).
  • step S ⁇ b> 2 the control unit 13 extracts the distance values of the various walls 31 and 32 in the distance image for each pixel as the structure information D ⁇ b> 1 and stores the extracted values in the storage unit 14.
  • the distance value in the case of FIG. 5 changes discontinuously from the end of the shielding wall 31 to the opposing wall 32 while continuously changing from the own vehicle 2 side by the shielding wall 31 along the direction d1. Will be done.
  • the control unit 13 analyzes the change in the distance value as described above, and can estimate the existence of the blind spot region R1.
  • control unit 13 as the blind spot estimation unit 131 determines whether or not the blind spot region R1 is detected in the current surrounding environment of the own vehicle 2 according to an estimation result by image analysis, for example (S3).
  • image analysis for example (S3)
  • the control unit 13 determines that the blind spot area R1 has not been detected (NO in S3), the processing of steps S1 to S3 is periodically repeated, for example.
  • the control unit 13 determines that the blind spot area R1 has been detected (YES in S3), the control unit 13 executes the processing as the blind spot object measurement unit 132 (S4 to S6).
  • the processing as the blind spot object measurement unit 132 S4 to S6.
  • a processing example of the blind spot object measurement unit 132 that measures the blind spot object 4 in the blind spot region R1 by utilizing the multiple reflected waves in the wave signal Sb of the radar 11 will be described below.
  • the control unit 13 as the blind spot object measurement unit 132 controls the radar 11 so as to emit the physical signal Sa toward the blind spot area R1 (S4).
  • FIGS. 6A and 6B illustrate the propagation path of the physical signal Sa in step S4 when there is no blind spot object 4 and when there is a blind spot object 4, respectively.
  • step S4 the control unit 13 causes the radar 11 to emit the physical signal Sa from the radar 11 to the opposing wall 32 near the boundary of the blind spot region R1, based on the analysis result in FIG.
  • the physical signal Sa from the radar 11 of the host vehicle 2 is repeatedly reflected between the opposed wall 32 and the opposite wall 35 via the blind spot region R1 on the side road, and a multiple reflected wave is formed. Propagating as In the example of FIG. 6A, the multiple reflected wave does not come toward the own vehicle 2 in response to the absence of the blind spot object 4.
  • the physical signal Sa from the radar 11 is reflected not only on the walls 32 and 33 but also on the blind spot object 4 and is reflected on the host vehicle 2. It can be a forward reflected multiple reflected wave Rb1. Therefore, the wave signal Sb received by the radar 11 includes the signal component of the multiple reflection wave Rb1 having information on the blind spot object 4.
  • step S4 the radar 11 emits the physical signal Sa and receives the wave signal Sb, and performs various measurements based on the reflected wave of the physical signal Sa.
  • the control unit 13 acquires a measurement result from the radar 11 (S5).
  • the controller 13 performs a blind spot object detection process based on the measurement result of the radar 11 (S6).
  • the signal component of the multiple reflected wave Rb1 (FIG. 6B) has information corresponding to the speed of the reflection-source blind spot object 4 and the length of the propagation path by Doppler shift, phase, and propagation time.
  • the blind spot object detection process (S6), the speed and position of the blind spot object 4 that has reflected the multiple reflected wave Rb1 are detected by analyzing such signal components. Details of the process in step S6 will be described later.
  • control unit 13 operates as the risk determination unit 133, and performs a risk determination process based on the detection result of the blind spot object 4 (S6) (S7).
  • a risk is determined based on the detected position, speed, and the like, for determining whether a warning is required for the blind spot object 4 approaching the vehicle 2.
  • the threshold value used for the determination is dynamically adjusted so as to relax the risk determination criterion when, for example, the preceding vehicle 5 is present (FIG. 2). I do.
  • the risk may be determined using the information in step S7. Details of the processing in step S7 will be described later.
  • control unit 13 outputs various control signals to the vehicle control device 20 according to the determination result of the degree of risk (S7) (S8). For example, when it is determined in step S7 that a warning is required, the control unit 13 generates a control signal for causing the alarm unit 22 to notify the warning and controlling the vehicle driving unit 21.
  • the detection device 1 monitors the surroundings of the own vehicle 2 (S1 to S3), and if a blind spot is found (YES in S3), determines the degree of danger of the blind spot object 4 (S7). And various actions can be performed (S8).
  • the camera 12 is used for monitoring the periphery, but the navigation device 15 may be used.
  • This modification is shown in FIG.
  • the navigation device 15 calculates various distances to the host vehicle 2 in the map information D2 of the surrounding environment of the host vehicle 2, and monitors the current position of the host vehicle 2.
  • the control unit 13 can use the monitoring result of the navigation device 15 as described above for various processes in FIG.
  • the control unit 13 can acquire the structural information D1 or detect the blind spot region R1 based on the monitoring result of the navigation device 15, for example, based on the structure 30 in the map information D2 (S2). Further, the control unit 13 may use the detection result of the vehicle-mounted sensor 16 as appropriate in the processing of FIG.
  • FIG. 8 is a diagram for describing an experiment of a blind spot object detection process.
  • FIG. 8A shows the structure information D1 of the experiment environment of this experiment.
  • FIG. 8B shows a measurement result of the radar 11 when there is no blind spot object 4.
  • FIG. 9 is a diagram illustrating a case where there is a blind spot object in the experiment of FIG.
  • FIG. 9A shows a measurement result of the radar 11 when the blind spot object 4 is present.
  • FIG. 9B illustrates a propagation path of a multiple reflection wave estimated from the blind spot object 4.
  • a strong peak P4 appeared near 7 m farther than the opposing wall 32.
  • the azimuth of the peak P4 is seen from the radar 11 to the far side of the opposing wall 32. From the above distance and direction, it can be seen that the peak P4 is mainly a component reflected from the blind spot object 4 through reflection by the opposing wall 32 (see FIG. 9B). That is, it was confirmed that the peak P4 having the blind spot object 4 as a wave source can be detected based on the distance and the azimuth to the peak P4 in the measurement result of the radar 11.
  • the presence / absence, position, and the like of the blind spot object 4 can be detected more accurately by using the structural information of the surrounding environment.
  • an example of a blind spot object detection process according to the present embodiment will be described with reference to FIG.
  • FIG. 10 is a flowchart illustrating a blind spot object detection process according to the present embodiment. The process according to the flowchart in FIG. 10 is executed by the control unit 13 operating as the blind spot object measurement unit 132 in step S6 in FIG.
  • control unit 13 extracts an environmental component indicating a reflected wave from the surrounding environment from the signal of the measurement result of the radar 11 acquired in step S5 of FIG. It is removed (S11).
  • the process in step S11 is performed using, for example, the structure information acquired in step S2.
  • each of the peaks P1, P2, and P3 in the example of FIG. 8B is an environment component indicating a reflected wave from the corresponding wall 31, 32, or 33 in the passage structure information D1 (FIG. 8B).
  • the control unit 13 predicts reflected waves from various structures with reference to the structure information D1, and subtracts the environmental component of the prediction result from the measurement result (for example, FIG. 9A) of the radar 11 (S11).
  • FIG. 9A the radar 11
  • control unit 13 performs signal analysis for detecting the blind spot object 4 based on the signal component obtained by removing the environmental component (S12).
  • the signal analysis in step S12 may include various types of analysis such as frequency analysis, analysis on the time axis, spatial distribution, and signal strength.
  • the control unit 13 determines whether a wave source is observed, for example, beyond the blind spot facing the opposite wall 32 based on the analysis result of the signal analysis (S13), and thereby detects the presence or absence of the blind spot object 4. .
  • the peak P4 has a wave source located on the far side of the passage than the facing wall 32 and is located at a position that is not predicted as an environmental component from the structure of the passage. From this, it can be presumed that the peak P4 is caused by multiple reflection of a wave whose source is inside the blind spot. That is, when the reflected wave is observed at a distance exceeding the facing wall 32 in the direction of the detected blind spot, the control unit 13 can determine that the blind spot object 4 is present (YES in step S13).
  • the control unit 13 determines that the wave source is observed beyond the opposite wall 32 in the blind spot (YES in S13), the distance to the blind spot object 4 and the distance to the blind spot object 4 are determined according to the propagation path in which the bending due to the multiple reflection is estimated.
  • Various state variables such as speed are measured (S14).
  • the control unit 13 uses the information indicating the road width of the blind spot portion (the width of the blind spot area R1) in the structural information D1, and thereby, for example, as shown in FIG. By correcting the path length so as to be folded, the position of the blind spot object 4 closer to the actual position can be calculated.
  • step S6 in FIG. 4 ends. After that, the control unit 13 executes a risk determination process (S7 in FIG. 4) for the detected blind spot object 4.
  • control unit 13 determines that the wave source is not observed beyond the opposite wall 32 in the blind spot (NO in S13), the control unit 13 ends this processing without performing any surveying. In this case, the control unit 13 may omit the processing after step S7 in FIG.
  • the blind spot object 4 can be detected using the signal component generated inside the blind spot area R1 based on the property of the multiple reflection in the physical signal Sa of the radar 11.
  • the signal component having information on the blind spot object 4 is weak, and it is detected in the presence of a reflected wave from a visible object outside the blind spot. Therefore, it is considered that detection and estimation are difficult.
  • the actual distance to the blind spot object 4 is different from the length of the signal propagation path, it may be difficult to estimate the actual distance.
  • the structure information D1 of the surrounding environment it is possible to narrow down the preconditions for analyzing the received wave (S11) and to improve the estimation accuracy (S14).
  • the control unit 13 refers to the distance to the intersection near the blind spot in the structure information D1, and removes the signal component of the received wave obtained within a round trip propagation time of the signal with respect to the linear distance to the intersection. .
  • a received wave is a directly reflected wave (ie, a single reflected wave) and does not include information on the blind spot object 4, and thus can be excluded from the analysis target.
  • the control unit 13 can also separate the reflected wave coming from the blind spot from the reflected wave coming from another angle based on the azimuth angle of the blind spot viewed from the host vehicle 2.
  • step S11 does not necessarily need to use the structure information D1 of the surrounding environment.
  • the control unit 13 may limit the analysis target to a moving object by subtracting the position change of the own vehicle 2 from the signal obtained along the time axis. This processing may be performed in the signal analysis of step S12.
  • the control unit 13 determines whether the signal component to be analyzed has a feature that appears due to the behavior of a specific object, such as Doppler shift due to reflection on a moving object, or fluctuation of a behavior peculiar to a human or a bicycle. Whether or not it may be analyzed. In addition, the control unit 13 determines whether the spatially distributed surface measurement signal distribution has a characteristic distribution of an automobile, a bicycle, a human, or the like, or includes a reflection from a metal object of an automobile size depending on the reflection intensity. Or the like may be analyzed. The above analysis may be performed in combination as appropriate, or may be analyzed as a multidimensional feature using machine learning instead of explicitly analyzing each.
  • the risk of the blind spot object 4 is determined by detecting the blind spot object 4 based on the detection result of the blind spot region R1. judge. At this time, the threshold value of the degree of danger is dynamically adjusted according to the situation of the surrounding environment such as the preceding vehicle 5 (FIG. 2). Details of the processing in step S7 will be described with reference to FIGS.
  • FIG. 11 is a flowchart illustrating an example of a risk determination process.
  • FIG. 12 is a diagram for explaining the risk determination processing. The process according to the flowchart in FIG. 11 is executed by the control unit 13 operating as the risk determination unit 133 in step S7 in FIG.
  • the control unit 13 calculates the risk index D based on the detection result of the blind spot object 4 in step S6 (S21).
  • the risk index D indicates an index for determining the risk of a collision between the detected blind spot object 4 and the host vehicle 2. For example, as shown in FIG. 12, the speed v 1 of blind spot object 4 approaches the own vehicle 2 can be set to risk index D.
  • the control unit 13 determines whether or not an object exists at the junction where the blind spot region R1 joins in the surrounding environment of the vehicle 2 (S22).
  • the process in step S22 is performed based on, for example, the analysis result in step S2 in FIG.
  • the control unit 13 specifies the junction such as the intersection 3 in the distance image or the structure information D1, and determines whether or not the moving object is located at the specified junction, thereby performing the determination in step S22.
  • the control unit 13 determines that there is no object at the junction of the blind spots (NO in S22).
  • the control unit 13 determines that an object exists at the junction of the blind spots (S22). YES).
  • control unit 13 determines that there is no object at the junction of the blind spots (NO in S22), it sets the threshold value Va for determining the degree of danger to a normal level (S23).
  • the normal level of the threshold value Va is set in consideration of, for example, the magnitude of the risk index D for which a warning is required for the blind spot object 4 in a normal state where no attention is specifically given.
  • the control unit 13 determines that the risk index D exceeds the threshold value Va (YES in S25)
  • the control unit 13 sets, for example, a warning flag to “ON” as a risk determination result (S26).
  • the warning flag is a flag that manages the presence / absence of a warning regarding the blind spot object 4 by “ON / OFF”, and is stored in the storage unit 14.
  • the control unit 13 sets the warning flag to “OFF” (S27).
  • the control unit 13 determines that an object is present at the junction of the blind spots (YES in S22), it sets the threshold value Va to a relaxation level instead of a normal level (S24). Since the blind spot object 4 is in a state of being alerted, the mitigation level of the threshold value Va is, for example, a level at which a criterion that requires a warning regarding the blind spot object 4 is relaxed from the normal level.
  • the mitigation level of the threshold Va is set to a value larger than the normal level of the threshold Va.
  • the control unit 13 the speed v 1 of the blind spot object 4, to determine the degree of risk depending on whether exceeds the larger threshold Va than the normal level (S25), a warning flag "ON” or It is set to "OFF" (S26, S27).
  • control unit 13 ends the risk determination process (S7 in FIG. 4) and proceeds to the process of step S8.
  • the risk of the blind spot object 4 approaching the own vehicle 2 or the intersection 3 is determined according to the corresponding risk index D. For example, a binary determination according to the warning flag is performed.
  • the control unit 13 can cause the alarm 22 to warn or cause the vehicle drive unit 21 to perform specific control (S8 in FIG. 4).
  • the threshold value Va is changed from the normal level to the mitigation level (S22 to S24). Accordingly, in consideration of the effect that the blind spot object 4 is alerted by the forward vehicle 5 or the like, no warning is given when the speed of the blind spot object 4 is higher than the normal level but lower than the relaxation level. Can be tolerated. Note that the execution time of the processing of steps S22 to S24 is not particularly limited, and for example, steps S22 to S24 may be performed before step S21.
  • the risk determination process is not limited to the binary determination.
  • a ternary determination for determining whether or not a warning is issued when a warning is unnecessary may be performed.
  • the control unit 13 may determine whether or not D> Vb when proceeding to “NO” in step S25. .
  • risk index D is not limited to the speed v 1, can be set by various state variables related to the blind spot object 4, for example, instead of the velocity v 1 may be set to the acceleration dv 1 / dt.
  • the relaxation level of the threshold value Va is set to, for example, a value smaller than the normal level. Accordingly, in consideration of the effect of alerting the blind spot object 4 when the forward vehicle 5 or the like exists, the distance L to the blind spot object 4 within the range larger than the mitigation level is smaller than the normal level. A smaller case can be tolerated, and a warning or the like can be omitted.
  • the risk index D may be set by a combination of various state variables.
  • An example of such a risk index D is shown in the following equation (1).
  • D
  • L 1 is the distance from the reference position P0 to the blind spot object 4 ( Figure 12).
  • the reference position P0 is set to a position where a collision between the blind spot object 4 and the vehicle 2 is assumed, such as the center of an intersection.
  • ⁇ t is a predetermined time width, and is set, for example, in the vicinity of a time width expected to take until the host vehicle 2 reaches the reference position P0.
  • L 0 is the distance from the reference position P 0 to the host vehicle 2.
  • v 0 is the speed of the vehicle 2 and can be obtained from the on-board sensor 16 or the like.
  • the risk index D in the above equation (1) is the sum of the distance between the blind spot object 4 and the reference position P0 and the distance between the reference position P0 and the host vehicle 2, which are estimated after the elapse of the time width ⁇ t ( (FIG. 12).
  • the control unit 13 determines “ The process may proceed to “YES” and proceed to “NO” when the value does not fall.
  • the risk index D may be set as in the following Expression (2) or Expression (2 ′).
  • D L 1 ⁇ v 1 ⁇ t (2)
  • D
  • ⁇ t L 0 / v 0 is set.
  • the time width ⁇ t may be set within an allowable range in consideration of a change in the speed v 0 of the host vehicle 2 or an estimation error of the reference position P0.
  • the control unit 13 determines the degree of risk in the same manner as in the case of Expression (1) using the risk index D of Expression (2) or Expression (2 ′). Can be.
  • the mitigation level and the normal level of the threshold value Va may be dynamically changed according to, for example, the states of the host vehicle 2 and the blind spot object 4. For example, small or is L 0 as described above, large or the dv 0 / dt or dv 1 / dt, or if the blind spot object 4 is presumed to humans, is considered to be a determination of the risk more strictly. Therefore, when such a case is detected, the control unit 13 may increase the threshold value Va with respect to the risk index D of the above equation (1), for example.
  • the detection device 1 detects an object in a surrounding environment of the own vehicle 2 which is an example of a moving object.
  • the detection device 1 includes a radar 11 and a camera 12 as detection units, and a control unit 13.
  • the detection units 11 and 12 detect distance information indicating the distance from the vehicle 2 to the surrounding environment.
  • the control unit 13 controls the detection units 11 and 12 to analyze the detection result.
  • the control unit 13 detects a blind spot region R1 indicating a blind spot in the surrounding environment based on the detection results of the detection units 11 and 12, and determines a risk degree regarding the blind spot region R1 based on the detection result of the blind spot region R1 ( S7).
  • the control unit 13 relaxes the criterion for determining the degree of danger ( S24).
  • the detection device 1 described above when an object is present at the junction of blind spots, the risk criterion is relaxed, thereby detecting the object with respect to the blind spot in the surrounding environment of the own vehicle 2 to reduce the risk. It is possible to suppress erroneous determination of an excessive degree of risk when making a determination.
  • the control unit 13 detects an object in the blind spot area R1 based on the detection result of the detection unit (S6), and determines the detection result of the blind spot object 4 in the blind spot area R1. Accordingly, the degree of danger is determined (S7). Thereby, the degree of danger according to the blind spot object 4 can be determined.
  • the radar 11 emits a physical signal Sa having wave characteristics from the own vehicle 2 to the surrounding environment, and detects distance information according to a reflected wave of the emitted physical signal Sa. .
  • the control unit 13 detects the blind spot object 4 based on the wave signal Sb including the component of the wave arriving from the blind spot area R1 in the detection result of the radar 11.
  • Waves to be used are not limited to multiple reflection waves, and may include diffracted waves or transmitted waves.
  • the control unit 13 controls the radar 11 to emit the physical signal Sa toward the detected blind spot region R1 (S4).
  • the physical signal Sa from the radar 11 does not necessarily need to be concentrated in the blind spot area Ra.
  • the physical signal Sa may be radiated as appropriate within a range that the radar 11 can detect.
  • the detection device 1 of the present embodiment further includes a storage unit 14 that stores structure information D1 indicating the object structure of the surrounding environment.
  • the control unit 13 detects the blind spot object 4 by analyzing the wave signal including the component of the wave arriving from the blind spot region R1 in the detection result of the radar 11 with reference to the structure information D1 (S6). By using the structure information D1, the detection of the blind spot object 4 can be performed with high accuracy.
  • the control unit 13 generates the structure information D1 based on the detection result of the camera 12, and stores it in the storage unit 14 (S2).
  • the blind spot object 4 can be accurately detected by sequentially generating the structure information D1.
  • the control unit 13 calculates a risk index D corresponding to the risk based on the detection result of the blind spot object 4 (S21), and calculates the calculated risk index D and the threshold Va. And the risk is determined (S25).
  • the control unit 13 adjusts the threshold value Va so as to ease the risk criterion (S22, S24). By adjusting the threshold value Va, erroneous determination of an excessive degree of risk can be easily suppressed.
  • the control unit 13 determines whether or not an object exists at the junction based on the detection result of the detection unit (S22), and determines that the object exists at the junction. (YES in S22), the risk criterion is relaxed (S24). By this determination, an erroneous determination of an excessive degree of risk can be appropriately suppressed.
  • the detection unit includes at least one of the camera 12, the radar 11, and the navigation device 15.
  • the distance information can be detected by the various detection units, and the periphery of the vehicle 2 can be monitored.
  • the mobile system includes the detection device 1 and the vehicle control device 20.
  • the vehicle control device 20 is mounted on the host vehicle 2 and executes an operation according to the result of the determination of the degree of danger by the detection device 1.
  • the detection device 1 can suppress an erroneous determination of an excessive risk when detecting an object with respect to a blind spot in a surrounding environment of the own vehicle 2 and determining the risk.
  • the detection method is a method for detecting an object in a surrounding environment including a path of a moving body such as the host vehicle 2.
  • the method includes steps S1 and S2 in which the detection unit detects distance information indicating a distance from the moving body to the surrounding environment.
  • the method includes steps S3 to S6 in which the control unit 13 detects a blind spot region R1 indicating a blind spot in the surrounding environment based on the detection result of the detection unit, and the control unit 13 relates to the blind spot region R1 based on the detection result of the blind spot region R1.
  • Step S7 for determining the degree of danger.
  • the method includes a step S24 in which, when an object is present at a junction where the blind spot region R1 and the path of the mobile unit merge, the control unit 13 relaxes the risk criterion.
  • a program for causing the control unit 13 to execute the above detection method is provided. According to the detection method of the present embodiment, it is possible to suppress an erroneous determination of an excessive risk when detecting an object with respect to a blind spot in a surrounding environment of a moving object such as the host vehicle 2 and determining a risk.
  • the multiple reflected waves are used for detecting the blind spot object 4.
  • the present invention is not limited to the multiple reflected waves, and for example, a diffracted wave may be used. This modification will be described with reference to FIG.
  • the physical signal Sa from the radar 11 is diffracted on the shielding wall 31 and reaches the blind spot object 4.
  • the reflected wave from the blind spot object 4 is diffracted on the shielding wall 31 and returns to the host vehicle 2 as a diffracted wave Sb2.
  • the control unit 13 of the present embodiment controls the wavelength and the azimuth of the physical signal Sa radiated from the radar 11 so that the shielding wall 31 wraps around in Step S4 of FIG.
  • the signal can reach even a region that cannot be reached geometrically with visible light or the like having high linearity due to the presence of various shields. .
  • the signal is transmitted not only in a completely reflective path but also in a direction in which the radiated own vehicle 2 exists. reflect. Such a reflected wave causes the diffraction phenomenon to propagate to the shielding wall 31, so that the radar 11 can receive the diffracted wave Sb ⁇ b> 2 as a signal component to be analyzed.
  • the signal component of the diffracted wave Sb2 has information on the propagation path to the blind spot object 4 and Doppler information according to the moving speed. Therefore, by analyzing the signal components, the position and velocity of the blind spot object 4 can be measured from the information on the propagation time, phase, and frequency of the signal components, as in the first embodiment. At this time, the propagation path of the diffracted wave Sb2 can also be estimated from the distance to the shielding wall 31 or various types of structural information D1. Further, a propagation path in which multiple reflection and diffraction are combined can be appropriately estimated, and a signal component of such a wave may be analyzed.
  • FIG. 14 is a flowchart for explaining a modification of the detection device 1.
  • the detection device 1 according to the first embodiment monitors the periphery using the camera 12 (S1 to S3 in FIG. 4).
  • the detection device 1 of the present modified example performs the same peripheral monitoring by the radar 11 as in S1 to S3 of FIG. 4 (S1A to S3A).
  • the control unit 13 performs switching control of, for example, the band of the radar 11, and uses a band that easily turns around at the blind spot (S4A). In this case, a signal analysis utilizing the diffracted wave is performed in step S6.
  • steps S1A to S3A the resolution in monitoring the periphery of the radar 11 can be improved by using a band having high linearity.
  • the radar 11, the camera 12, and the navigation device 15 have been described as examples of the detection unit.
  • the detection unit of the present embodiment is not limited to these, and may be, for example, LIDAR.
  • the physical signal Sa emitted from the detection unit may be, for example, infrared light.
  • the detection unit may be a sonar, and may emit an ultrasonic wave as the physical signal Sa. In these cases, the wave signal Sb received by the detection unit is set in the same manner as the corresponding physical signal Sa.
  • the example in which the radar 11 and the camera 12 are installed toward the front of the vehicle 2 has been described, but the installation positions of the radar 11 and the like are not particularly limited.
  • the radar 11 and the like may be arranged toward the rear of the vehicle 2 and, for example, the mobile system may be used for parking assistance.
  • the detection device 1 detects the blind spot object 4 by utilizing the characteristics of the wave based on the physical signal Sa from the detection unit.
  • the method of detecting the blind spot object 4 is not limited to the above method, and various methods may be adopted.
  • the object 4 in the blind spot area R1 may be estimated based on various information. Even in this case, it is possible to perform the risk determination process on the estimation result in the same manner as in each of the above embodiments.
  • the detection device 1 has detected the blind spot object 4.
  • the detection device 1 of the present embodiment may determine the degree of danger related to the blind spot without detecting the blind spot object 4.
  • the risk determination process may be performed using the detection result of the blind spot region R1, and the risk index D is appropriately determined based on various information such as the size, shape, or positional relationship of the detected blind spot region R1. It may be calculated. Even in this case, erroneous determination of the degree of risk can be suppressed by relaxing the criteria for determining the degree of risk according to the presence of an object at the junction of the blind spots. For example, even if there is a blind spot object 4 that has not been particularly detected, an excessive warning or the like can be avoided by reflecting a state alerted by the preceding vehicle 5 or the like as a result.
  • the moving body on which the detection device 1 is mounted is not particularly limited to an automobile, and may be, for example, an AGV.
  • the detection device 1 may monitor the periphery when the AGV automatically travels, and may detect an object in a blind spot.
  • a first aspect according to the present disclosure is a detection device that detects an object in a surrounding environment including a path of a moving object (2).
  • the detection device includes a detection unit (11, 12) and a control unit (13).
  • the detecting unit detects distance information indicating a distance from the moving body to the surrounding environment.
  • the control unit controls the detection unit.
  • the control unit detects a blind spot area indicating a blind spot in the surrounding environment based on the detection result of the detection unit (S3), and determines a degree of risk related to the blind spot area based on the detection result of the blind spot area. (S7).
  • the control unit relaxes the risk criterion when an object is present at a junction where the detected blind spot area and the path of the moving body merge (S24).
  • the control unit detects an object in the blind spot area based on a detection result of the detection unit (S6), and detects the object in the blind spot area.
  • the risk is determined according to the detection result of the object (S7).
  • the detection unit emits a physical signal having wave characteristics from the moving body to the surrounding environment, and responds to a reflected wave of the emitted physical signal. To detect the distance information.
  • the control unit detects an object in the blind spot area based on a wave signal including a wave component arriving from the blind spot area in the detection result of the detection unit.
  • control unit is configured to, when detecting the blind spot area in the surrounding environment, emit the physical signal toward the detected blind spot area.
  • the section is controlled (S4).
  • the detection device further includes a storage unit (14) that stores structure information (D1) indicating an object structure of the surrounding environment.
  • the control unit refers to the structure information, analyzes a wave signal including a wave component arriving from the blind spot area in a detection result of the detection unit, and detects an object in the blind spot area (S6). .
  • the control unit is configured to determine a risk index corresponding to the risk based on a detection result of an object in the blind spot area ( D) is calculated (S21), and the calculated risk index is compared with a threshold to determine the risk (S25).
  • the control unit adjusts the threshold so as to ease the risk criterion (S22, S24).
  • the control unit determines whether an object is present at the junction based on a detection result of the detection unit. When it is determined that an object is present at the junction, the criterion for determining the degree of risk is relaxed.
  • the detection unit includes at least one of a camera, a radar, a LIDAR, and a navigation device.
  • 9A ninth aspect is a mobile system including the detection device according to any one of the first to eighth aspects, and a control device (20).
  • the control device is mounted on the moving body and performs an operation according to a result of the determination of the degree of risk by the detection device.
  • the 10A tenth aspect is a detection method for detecting an object in a surrounding environment including a path of a moving object (2).
  • the method includes a step of detecting distance information indicating a distance from the moving object to the surrounding environment (S1, S2).
  • a control unit (13) detects a blind spot region (R1) indicating a blind spot in the surrounding environment based on a detection result of the detection unit (S3), and based on the detection result of the blind spot region. (S7) determining the degree of risk related to the blind spot area.
  • the method includes a step (S24) of relaxing the risk criterion when an object is present at a junction where the blind spot area and the path of the mobile unit merge.
  • An eleventh aspect is a program for causing a control unit to execute the detection method according to the tenth aspect.

Abstract

A detection device (1) detects an object in a surrounding environment including a route of a moving body (2). The detection device is provided with detection units (11, 12) and a control unit (13). The detection units detect distance information representing the distance from the moving body to the surrounding environment. The control unit controls the detection units. The control unit detects a blind spot region representing a blind spot in the surrounding environment on the basis of the results of the detection by the detection units, and determines a degree of risk associated with the blind spot region on the basis of the result of the detection of the blind spot region (S7). If the object is located at the connection point where the route of the moving body connects to the detected blind spot region, then the control unit eases the criteria for determining the degree of risk (S24).

Description

検知装置、移動体システム、及び検知方法Detecting device, moving body system, and detecting method
 本開示は、移動体から周辺の物体を検知する検知装置、検知装置を備えた移動体システム、及び検知方法に関する。 The present disclosure relates to a detection device that detects a nearby object from a moving object, a moving object system including the detection device, and a detection method.
 自動車又はAGV(自動搬送車)などの移動体に搭載され、移動体の周辺を監視する技術が提案されている(例えば特許文献1,2)。 技術 A technology has been proposed that is mounted on a mobile object such as an automobile or an AGV (automatic guided vehicle) and monitors the periphery of the mobile object (for example, Patent Documents 1 and 2).
 特許文献1は、自車両前方の障害物を認識する障害物認識装置を含んだ運転支援装置を開示している。特許文献1の障害物認識装置は、自車両に対する死角から出現する障害物を認識するために、自車両に対する死角領域を検出している。運転支援装置は、障害物認識装置の検出結果に基づき障害物に対する危険度を推定し、障害物に対する危険度が所定値よりも低いときは、障害物を回避誘導するための警告等を通知し、危険度が所定値よりも高いときは自車両を自動走行させるといった制御を行っている。 Patent Document 1 discloses a driving assistance device including an obstacle recognition device that recognizes an obstacle in front of a host vehicle. The obstacle recognition device of Patent Literature 1 detects a blind spot area with respect to the own vehicle in order to recognize an obstacle that appears from a blind spot with respect to the own vehicle. The driving support device estimates the danger to the obstacle based on the detection result of the obstacle recognition device, and notifies a warning or the like for guiding the user to avoid the obstacle when the danger to the obstacle is lower than a predetermined value. When the degree of danger is higher than a predetermined value, control is performed such that the own vehicle runs automatically.
 特許文献2は、自車両周辺の走行環境を的確に推定することを目的とした車両環境推定装置を開示している。特許文献2の車両環境推定装置は、自車両の周辺の他車両の挙動を検出し、当該車両の挙動に基づいて、自車両からの死角領域を走行する別の車両の存在を推定している。このような死角領域についての推定結果を、例えば自車両から先行する他車両の車速等の予測に用いることにより、自車両の運転制御が行われている。 Patent Document 2 discloses a vehicle environment estimating apparatus for accurately estimating a traveling environment around a host vehicle. The vehicle environment estimating device of Patent Literature 2 detects the behavior of another vehicle in the vicinity of the own vehicle, and estimates the presence of another vehicle traveling in a blind spot area from the own vehicle based on the behavior of the vehicle. . The driving control of the own vehicle is performed by using the estimation result of such a blind spot area, for example, for predicting the vehicle speed of another vehicle preceding the own vehicle.
特開2011-242860号公報JP 2011-242860 A 特開2010-267211号公報JP 2010-267211 A
 特許文献1では、死角領域の検出結果に基づき推定された危険度が、所定値よりも高いか低いかの判定によって、運転支援の各種制御が行われている。危険度を判定する基準が死角外の周辺環境に拘わらず所定値であり、従来技術では、死角中の物体が自車両の走行の障害となり難いと考えられる周辺環境の状況下であっても、過剰な運転制御を生じる危険度の誤判定を招来していた。 In Patent Document 1, various controls for driving assistance are performed by determining whether the risk estimated based on the detection result of the blind spot area is higher or lower than a predetermined value. The criterion for determining the degree of danger is a predetermined value regardless of the surrounding environment outside the blind spot, and in the related art, even in a situation of the surrounding environment where it is considered that the object in the blind spot is unlikely to hinder the traveling of the own vehicle, This has led to erroneous determination of the risk of causing excessive operation control.
 本開示の目的は、移動体の周辺環境における死角に対して物体を検知して危険度を判定する際に過剰な危険度の誤判定を抑制することができる検知装置、検知方法及び移動体システムを提供することにある。 An object of the present disclosure is a detection device, a detection method, and a mobile body system that can suppress excessive erroneous determination of a risk level when detecting an object with respect to a blind spot in a surrounding environment of the mobile body and determining the risk level. Is to provide.
 本開示の一態様に係る検知装置は、移動体の進路を含む周辺環境における物体を検知する装置である。検知装置は、検出部と、制御部とを備える。検出部は、移動体から周辺環境までの距離を示す距離情報を検出する。制御部は、検出部を制御する。制御部は、検出部の検出結果に基づいて、周辺環境における死角を示す死角領域を検知し、死角領域の検知結果に基づいて、死角領域に関する危険度を判定する。制御部は、検知された死角領域と移動体の進路とが合流する合流地点に物体が存在する場合、危険度の判定基準を緩和する。 検 知 A detection device according to an aspect of the present disclosure is a device that detects an object in a surrounding environment including a path of a moving object. The detection device includes a detection unit and a control unit. The detection unit detects distance information indicating a distance from the moving body to a surrounding environment. The control unit controls the detection unit. The control unit detects a blind spot area indicating a blind spot in the surrounding environment based on the detection result of the detection unit, and determines the degree of risk related to the blind spot area based on the detection result of the blind spot area. The control unit relaxes the risk criterion when an object is present at a junction where the detected blind spot area and the path of the moving body merge.
 本開示の一態様に係る移動体システムは、上記の検知装置と、移動体に搭載され、検知装置による危険度の判定結果に応じた動作を実行する制御装置とを備える。 移動 A mobile body system according to an aspect of the present disclosure includes the above-described detection device, and a control device mounted on the mobile body and performing an operation according to a result of the determination of the degree of risk by the detection device.
 本開示の一態様に係る検知方法は、移動体の進路を含む周辺環境における物体を検知する方法である。本方法は、検出部が、移動体から周辺環境までの距離を示す距離情報を検出するステップと、制御部が、検出部の検出結果に基づき、周辺環境における死角を示す死角領域を検知するステップと、制御部が、死角領域の検知結果に基づいて、死角領域に関する危険度を判定するステップとを含む。さらに、本方法は、死角領域と移動体の進路とが合流する合流地点に物体が存在する場合、制御部は、危険度の判定基準を緩和するステップを含む。 検 知 The detection method according to an aspect of the present disclosure is a method of detecting an object in a surrounding environment including a path of a moving object. In the method, the detecting unit detects distance information indicating a distance from the moving body to the surrounding environment, and the control unit detects a blind spot area indicating a blind spot in the surrounding environment based on a detection result of the detecting unit. And a step in which the control unit determines the degree of risk related to the blind spot area based on the detection result of the blind spot area. Further, the method includes a step of, when an object is present at a merging point where the blind spot area and the path of the moving body merge, the control unit relaxes the criterion for determining the degree of risk.
 本開示に係る検知装置、移動体システム、及び検知方法によると、移動体の周辺環境における死角に対して物体を検知して危険度を判定する際に過剰な危険度の誤判定を抑制することができる。 According to the detection device, the mobile body system, and the detection method according to the present disclosure, it is possible to suppress an erroneous determination of an excessive risk when detecting an object with respect to a blind spot in a surrounding environment of the mobile and determining the risk. Can be.
本開示に係る検知装置の適用例を説明するための図Diagram for explaining an application example of the detection device according to the present disclosure 検知装置の適用例における合流地点に物体が存在する場合を例示する図The figure which illustrates the case where an object is present at the junction in the application example of the detection device. 本開示の実施形態1に係る移動体システムの構成を例示するブロック図1 is a block diagram illustrating a configuration of a mobile system according to a first embodiment of the present disclosure. 実施形態1に係る検知装置の動作を説明するためのフローチャートFlowchart for explaining the operation of the detection device according to the first embodiment 検知装置における距離情報の一例を説明するための図Diagram for explaining an example of distance information in the detection device 実施形態1に係る検知装置の動作を説明するための図FIG. 4 is a diagram for explaining the operation of the detection device according to the first embodiment. 検知装置における距離情報の変形例を説明するための図The figure for explaining the modification of distance information in a detecting device 死角物体の検知処理の実験を説明するための図Diagram for explaining an experiment of blind spot object detection processing 図8の実験において死角物体がある場合を例示する図FIG. 8 illustrates a case where there is a blind spot object in the experiment of FIG. 8. 検知装置による死角物体の検知処理を例示するフローチャート4 is a flowchart illustrating a blind spot object detection process performed by the detection device 検知装置による危険度の判定処理を例示するフローチャートThe flowchart which illustrates the judgment process of the danger degree by a detection apparatus 検知装置による危険度の判定処理を説明するための図The figure for explaining the judgment processing of the degree of danger by the detection device 検知装置の動作の変形例を説明するための図Diagram for explaining a modification of the operation of the detection device 検知装置の動作の変形例を説明するためのフローチャートFlowchart for explaining a modification of the operation of the detection device
 以下、添付の図面を参照して本開示に係る検知装置及び方法、並びに移動体システムの実施の形態を説明する。なお、以下の各実施形態において、同様の構成要素については同一の符号を付している。 Hereinafter, embodiments of a detection device and a method and a mobile system according to the present disclosure will be described with reference to the accompanying drawings. In the following embodiments, the same components are denoted by the same reference numerals.
(適用例)
 本開示に係る検知装置及び方法、並びに移動体システムが適用可能な一例について、図1,2を用いて説明する。図1は、本開示に係る検知装置1の適用例を説明するための図である。図2は、本適用例における合流地点に物体が存在する場合を例示する図である。
(Application example)
An example to which the detection device and method according to the present disclosure and the mobile body system can be applied will be described with reference to FIGS. FIG. 1 is a diagram for describing an application example of the detection device 1 according to the present disclosure. FIG. 2 is a diagram illustrating a case where an object is present at a merging point in this application example.
 本開示に係る検知装置1は、例えば車載用途に適用可能であり、自動車等の移動体において移動体システムを構成する。図1では、検知装置1が搭載された車両2の走行状態を例示している。本適用例に係る移動体システムは、例えば、検知装置1を用いて走行中の自車両2の周りで移り変わる周辺環境を監視する。周辺環境は、例えば自車両2周辺に存在する建物及び電柱などの構造物、並びに歩行者及び他車両などの動体といった各種物体を含む。 検 知 The detection device 1 according to the present disclosure is applicable to, for example, in-vehicle use, and constitutes a mobile body system in a mobile body such as an automobile. FIG. 1 illustrates a running state of a vehicle 2 on which the detection device 1 is mounted. The mobile system according to the application example monitors, for example, the surrounding environment that changes around the own vehicle 2 that is traveling using the detection device 1. The surrounding environment includes, for example, structures such as buildings and electric poles existing around the vehicle 2 and various objects such as moving objects such as pedestrians and other vehicles.
 図1の例では、交差点3近傍における構造物の壁31によって、自車両2から監視可能な範囲が遮られ、死角が生じている。死角は、自車両2等の移動体から、周辺環境に応じて幾何学的に直接視できない場所を示す。本例において、自車両2から死角となる領域である死角領域R1には、横道から交差点3に接近する別の車両4が存在している。上記のような場合、死角からの車両4と自車両2とが、出会い頭に衝突するような事態が懸念される。 In the example of FIG. 1, the range that can be monitored from the host vehicle 2 is blocked by the wall 31 of the structure near the intersection 3, and a blind spot occurs. The blind spot indicates a location that cannot be directly viewed geometrically from a moving object such as the host vehicle 2 in accordance with the surrounding environment. In this example, another vehicle 4 approaching the intersection 3 from a side road exists in a blind spot region R1 which is a blind spot from the own vehicle 2. In the above case, there is a concern that the vehicle 4 and the host vehicle 2 from the blind spot may collide with each other at the intersection.
 そこで、本実施形態の検知装置1は、例えば車両4のように死角領域R1に内在する物体(以下「死角物体」という場合がある)の検知を実行して、死角物体4の検知結果に基づき危険度を判定する。危険度は、例えば自車両2と死角物体4とが衝突を起こす可能性に関する。検知装置1は、危険度の判定結果に基づいて、出会い頭の衝突等を回避させる警告のための運転支援或いは運転制御の各種制御を行うことができる。 Thus, the detection device 1 of the present embodiment executes detection of an object (hereinafter, sometimes referred to as “blind spot object”) existing in the blind spot region R1 such as the vehicle 4, and based on the detection result of the blind spot object 4. Determine the degree of risk. The risk relates to, for example, the possibility that the host vehicle 2 and the blind spot object 4 may collide. The detection device 1 can perform various types of control of driving support or driving control for warning to avoid a collision at an intersection based on the determination result of the degree of danger.
 図2は、図1と同様の周辺環境において前方車両5が存在する場合を例示している。前方車両5は、自車両2が進行する進路において、自車両2よりも前方を走行し、交差点3に位置している。交差点3においては、死角領域R1を含む横道が自車両2の進路に合流し、前方車両5の位置は、死角領域R1の真横になっている。本適用例において、交差点3は合流地点の一例であり、前方車両5は同地点に存在する物体の一例である。 FIG. 2 illustrates a case where the preceding vehicle 5 exists in the same surrounding environment as in FIG. The front vehicle 5 travels ahead of the host vehicle 2 on the path where the host vehicle 2 travels, and is located at the intersection 3. At the intersection 3, the side road including the blind spot area R1 joins the course of the host vehicle 2, and the position of the preceding vehicle 5 is right beside the blind spot area R1. In this application example, the intersection 3 is an example of a merging point, and the preceding vehicle 5 is an example of an object existing at the same point.
 以上のような前方車両5は、例えば死角領域R1中の車両4の運転者に視認される結果として、死角物体(車両)4に注意喚起を促すこととなる。このことから、自車両2と死角物体4との出会い頭の衝突する危険度、或いは死角物体4が自車両の走行の障害になる可能性は、前方車両5がない場合(図1参照)よりも低いと考えられる。このような場合に前方車両5がない場合と同様の危険度の判定基準を用いると、実際には警告が不要な状況であっても上記制御が為されるといった、過剰な警告等を招来してしまうことが考えられる。 前方 The preceding vehicle 5 as described above alerts the blind spot object (vehicle) 4 as a result of being visually recognized by the driver of the vehicle 4 in the blind spot area R1, for example. From this, the risk of collision of the encounter between the own vehicle 2 and the blind spot object 4 or the possibility that the blind spot object 4 becomes an obstacle to the running of the own vehicle is higher than the case where there is no preceding vehicle 5 (see FIG. 1). It is considered low. In such a case, using the same criterion for determining the degree of danger as in the case where there is no preceding vehicle 5 causes an excessive warning or the like such that the above control is performed even in a situation where a warning is not actually required. Can be considered.
 そこで、本実施形態の検知装置1は、前方車両5のように、死角領域R1と自車両2との合流地点である交差点3に位置する物体が存在する場合に、危険度の判定基準を緩和する。これにより、自車両2の周辺環境の状況に応じて危険度の誤判定を抑制して、過剰な警告等を回避でき、自車両2の運転を円滑にすることができる。 Therefore, the detection device 1 of the present embodiment relaxes the risk criterion when there is an object such as the preceding vehicle 5 located at the intersection 3 where the blind spot region R1 and the host vehicle 2 meet. I do. Thereby, erroneous determination of the degree of danger can be suppressed according to the situation of the surrounding environment of the own vehicle 2, an excessive warning or the like can be avoided, and the driving of the own vehicle 2 can be performed smoothly.
(構成例)
 以下、検知装置1を備えた移動体システムの構成例としての実施形態を説明する。
(Configuration example)
Hereinafter, an embodiment as a configuration example of a mobile system including the detection device 1 will be described.
(実施形態1)
 実施形態1に係る移動体システムの構成および動作について、以下説明する。
(Embodiment 1)
The configuration and operation of the mobile system according to the first embodiment will be described below.
1.構成
 本実施形態に係る移動体システムの構成を、図3を用いて説明する。図3は、本システムの構成を例示するブロック図である。
1. Configuration The configuration of the mobile system according to the present embodiment will be described with reference to FIG. FIG. 3 is a block diagram illustrating the configuration of the present system.
 本システムは、図3に例示するように、検知装置1と、車両制御装置20とを備える。本実施形態の検知装置1は、レーダ11と、カメラ12と、制御部13とを備える。また、例えば検知装置1は、記憶部14と、ナビゲーション機器15と、車載センサ16とを備える。車両制御装置20は、自車両2に搭載された各種の車載機器を含み、例えば運転支援又は自動運転に用いられる。本実施形態において、レーダ11及びカメラ12は、それぞれ距離情報を検出する検出部の一例である。 This system includes the detection device 1 and the vehicle control device 20 as illustrated in FIG. The detection device 1 of the present embodiment includes a radar 11, a camera 12, and a control unit 13. Further, for example, the detection device 1 includes a storage unit 14, a navigation device 15, and an in-vehicle sensor 16. The vehicle control device 20 includes various in-vehicle devices mounted on the host vehicle 2, and is used for, for example, driving assistance or automatic driving. In the present embodiment, the radar 11 and the camera 12 are each an example of a detection unit that detects distance information.
 検知装置1において、レーダ11は、例えば、送信機11aと、受信機11bと、レーダ制御回路11cとを備える。レーダ11は、例えば自車両2の走行方向における前方(図1参照)に向けて信号の送受信を行うように、自車両2のフロントグリル又はフロントガラス等に設置される。 In the detection device 1, the radar 11 includes, for example, a transmitter 11a, a receiver 11b, and a radar control circuit 11c. The radar 11 is installed on, for example, a front grill or a windshield of the host vehicle 2 so as to transmit and receive signals forward (see FIG. 1) in the traveling direction of the host vehicle 2.
 送信機11aは、例えば可変指向性を有するアンテナ(フェイズドアレイアンテナ等)、及び当該アンテナに物理信号Saを外部送信させる送信回路などを含む。物理信号Saは、例えばミリ波、マイクロ波、ラジオ波、及びテラヘルツ波のうちの少なくとも1つを含む。 The transmitter 11a includes, for example, an antenna having a variable directivity (a phased array antenna or the like), a transmission circuit that causes the antenna to externally transmit the physical signal Sa, and the like. The physical signal Sa includes, for example, at least one of a millimeter wave, a microwave, a radio wave, and a terahertz wave.
 受信機11bは、例えば可変指向性を有するアンテナ、及び当該アンテナにより外部から波動信号Sbを受信する受信回路などを含む。波動信号Sbは、物理信号Saの反射波を含むように、物理信号Saと同様の波長帯に設定される。なお、送信機11aと受信機11bとは、例えば共用のアンテナを用いてもよく、一体的に構成されてもよい。 The receiver 11b includes, for example, an antenna having variable directivity, and a receiving circuit that receives the wave signal Sb from outside using the antenna. The wave signal Sb is set in the same wavelength band as the physical signal Sa so as to include the reflected wave of the physical signal Sa. The transmitter 11a and the receiver 11b may use a common antenna, for example, or may be configured integrally.
 レーダ制御回路11cは、送信機11a及び受信機11bによる信号の送受信を制御する。レーダ制御回路11cは、例えば制御部13からの制御信号により、レーダ11による信号の送受信を開始したり、送信機11aから物理信号Saを放射する方向を制御したりする。また、レーダ制御回路11cは、送信機11aから周辺環境に物理信号Saを放射させ、受信機11bの受信結果において、物理信号Saの反射波を示す波動信号Sbを検出する。 The radar control circuit 11c controls transmission and reception of signals by the transmitter 11a and the receiver 11b. The radar control circuit 11c starts transmission and reception of signals by the radar 11 and controls the direction in which the physical signal Sa is emitted from the transmitter 11a, for example, by a control signal from the control unit 13. Further, the radar control circuit 11c causes the transmitter 11a to emit a physical signal Sa to the surrounding environment, and detects a wave signal Sb indicating a reflected wave of the physical signal Sa in the reception result of the receiver 11b.
 レーダ11は、例えばCW(連続波)方式またはパルス方式などの変調方式に従って動作し、外部の物体の距離、方位および速度等の計測を行う。CW方式は、2波CW方式、FM-CW方式及びスペクトル拡散方式などを含む。パルス方式は、パルスドップラー方式であってもよいし、チャープ信号のパルス圧縮或いはPN系列のパルス圧縮を用いてもよい。レーダ11は、例えばコヒーレントな位相情報制御を用いる。レーダ11は、インコヒーレントな方式を用いてもよい。 The radar 11 operates according to a modulation method such as a CW (continuous wave) method or a pulse method, and measures the distance, azimuth, speed, and the like of an external object. The CW method includes a two-wave CW method, an FM-CW method, a spread spectrum method, and the like. The pulse method may be a pulse Doppler method, or pulse compression of a chirp signal or pulse compression of a PN sequence may be used. The radar 11 uses, for example, coherent phase information control. The radar 11 may use an incoherent method.
 カメラ12は、例えば自車両2においてレーダ11から物理信号Saを放射可能な範囲と重畳する範囲を撮像可能な位置に設置される。例えば、カメラ12は、例えば自車両2前方(図1参照)に向けて、自車両2フロントガラス等に設置される。検知装置1における死角は、カメラ12の設置位置を幾何学的な基準としてもよいし、レーダ11の設置位置を基準としてもよい。 The camera 12 is installed at a position where, for example, the range in which the physical signal Sa can be radiated from the radar 11 in the own vehicle 2 can be imaged. For example, the camera 12 is installed on a windshield or the like of the host vehicle 2 toward the front of the host vehicle 2 (see FIG. 1), for example. The blind spot in the detection device 1 may be based on the installation position of the camera 12 as a geometric reference or based on the installation position of the radar 11.
 カメラ12は、設置位置から外部の画像を撮像して、撮像画像を生成する。カメラ12は、撮像画像を示す画像データを制御部13に出力する。カメラ12は、例えばRGB-Dカメラ、ステレオカメラ、又は距離画像センサである。カメラ12は、本実施形態における測距部(或いは監視部)の一例である。 The camera 12 captures an external image from the installation position and generates a captured image. The camera 12 outputs image data indicating the captured image to the control unit 13. The camera 12 is, for example, an RGB-D camera, a stereo camera, or a range image sensor. The camera 12 is an example of a distance measuring unit (or a monitoring unit) in the present embodiment.
 制御部13は、CPU、RAM及びROM等を含み、情報処理に応じて各構成要素の制御を行う。制御部13は、例えば、ECU(電子制御ユニット)により構成される。制御部13は、記憶部14に格納されたプログラムをRAMに展開し、RAMに展開されたプログラムをCPUにより解釈及び実行する。このように実現されるソフトウェアモジュールとして、例えば、制御部13は、死角推定部131、死角物体計測部132および危険度判定部133を実現する。各部131~133については後述する。 The control unit 13 includes a CPU, a RAM, a ROM, and the like, and controls each component according to information processing. The control unit 13 is configured by, for example, an ECU (electronic control unit). The control unit 13 expands the program stored in the storage unit 14 on the RAM, and interprets and executes the program expanded on the RAM by the CPU. As software modules implemented in this way, for example, the control unit 13 implements a blind spot estimation unit 131, a blind spot object measurement unit 132, and a risk determination unit 133. Each of the units 131 to 133 will be described later.
 記憶部14は、制御部13で実行されるプログラム、及び各種のデータ等を記憶する。例えば、記憶部14は、後述する構造情報D1を記憶する。記憶部14は、例えば、ハードディスクドライブ又はソリッドステートドライブを含む。また、RAM及びROMは、記憶部14に含まれてもよい。 The storage unit 14 stores programs executed by the control unit 13, various data, and the like. For example, the storage unit 14 stores structure information D1 described below. The storage unit 14 includes, for example, a hard disk drive or a solid state drive. Further, the RAM and the ROM may be included in the storage unit 14.
 上記のプログラム等は、可搬性を有する記憶媒体に格納されてもよい。記憶媒体は、コンピュータその他装置、機械等が記録されたプログラム等の情報を読み取り可能なように、当該プログラム等の情報を、電気的、磁気的、光学的、機械的又は化学的作用によって蓄積する媒体である。検知装置1は、当該記憶媒体からプログラム等を取得してもよい。 プ ロ グ ラ ム The above-mentioned programs and the like may be stored in a portable storage medium. The storage medium stores the information such as the program by an electrical, magnetic, optical, mechanical or chemical action so that the computer or the like can read the information such as the recorded program by a machine or the like. Medium. The detection device 1 may acquire a program or the like from the storage medium.
 ナビゲーション機器15は、例えば地図情報を格納するメモリ、及びGPS受信機を含む測距部(監視部)の一例である。車載センサ16は、自車両2に搭載された各種センサであり、例えば車速センサ、加速度センサ、及びジャイロセンサなどを含む。車載センサ16は、自車両2の速度、加速度および角速度などを検出する。 The navigation device 15 is an example of a distance measuring unit (monitoring unit) including a memory for storing map information and a GPS receiver, for example. The in-vehicle sensors 16 are various sensors mounted on the host vehicle 2, and include, for example, a vehicle speed sensor, an acceleration sensor, a gyro sensor, and the like. The on-vehicle sensor 16 detects the speed, acceleration, angular velocity, and the like of the vehicle 2.
 以上のような構成は一例であり、検知装置1は上記の構成に限られない。例えば、検知装置1は、ナビゲーション機器15及び車載センサ16を備えなくてもよい。また、検知装置1の制御部13は、上記各部131~133を別体で実行する複数のハードウェア資源で構成されてもよい。制御部13は、CPU、MPU、GPU、マイコン、DSP、FPGA、ASIC等の種々の半導体集積回路で構成されてもよい。 The above configuration is an example, and the detection device 1 is not limited to the above configuration. For example, the detection device 1 may not include the navigation device 15 and the vehicle-mounted sensor 16. Further, the control unit 13 of the detection device 1 may be configured by a plurality of hardware resources that execute the units 131 to 133 separately. The control unit 13 may be configured by various semiconductor integrated circuits such as a CPU, an MPU, a GPU, a microcomputer, a DSP, an FPGA, and an ASIC.
 車両制御装置20は、本実施形態における移動体システムの制御装置の一例である。車両制御装置20は、例えば、車両駆動部21、及び報知器22を含む。車両駆動部21は、例えばECUで構成され、自車両2の各部を駆動制御する。例えば、車両駆動部21は、自車両2のブレーキを制御し、自動ブレーキを実現する。 The vehicle control device 20 is an example of a control device of the mobile system according to the present embodiment. The vehicle control device 20 includes, for example, a vehicle drive unit 21 and an alarm 22. The vehicle drive unit 21 is configured by, for example, an ECU, and controls driving of each unit of the host vehicle 2. For example, the vehicle drive unit 21 controls the brake of the own vehicle 2 to realize automatic braking.
 報知器22は、画像又は音などにより、ユーザに各種情報を報知する。報知器22は、例えば自車両2に搭載された液晶パネル又は有機ELパネルなどの表示装置である。報知器22は、警報等を音声出力する音声出力装置であってもよい。 The notifier 22 notifies the user of various kinds of information by images or sounds. The alarm 22 is a display device such as a liquid crystal panel or an organic EL panel mounted on the vehicle 2. The alarm 22 may be an audio output device that outputs an alarm or the like by audio.
2.動作
 以上のように構成される移動体システム及び検知装置1の動作について、以下説明する。
2. Operation The operation of the moving object system and the detection device 1 configured as described above will be described below.
 本実施形態に係る移動体システムは、例えば自車両2の運転中に、周辺環境を監視するように、検知装置1を動作させる。本システムの車両制御装置20は、検知装置1による検知結果に基づき、自車両2の運転支援又は自動運転等のための各種制御を行う。 移動 The mobile system according to the present embodiment operates the detection device 1 so as to monitor the surrounding environment, for example, while the own vehicle 2 is operating. The vehicle control device 20 of the present system performs various controls for driving support of the own vehicle 2 or automatic driving based on the detection result by the detection device 1.
 本実施形態の検知装置1は、例えばカメラ12において自車両2周辺の画像を撮像して、自車両2の周辺環境を監視する。検知装置1の死角推定部131は、例えば監視結果の各種距離を示す距離情報などに基づき、現在の周辺環境において死角が推定される領域の有無を逐次、検知する。 検 知 The detection device 1 of the present embodiment captures an image around the own vehicle 2 with the camera 12, for example, and monitors the surrounding environment of the own vehicle 2. The blind spot estimation unit 131 of the detection device 1 sequentially detects, for example, the presence or absence of an area where a blind spot is estimated in the current surrounding environment, based on distance information indicating various distances in the monitoring result.
 検知装置1において、死角推定部131により死角が発見されると、死角物体計測部132は、レーダ11を用いて死角領域R1の内部状態を計測する。自車両2のレーダ11から放射される物理信号Saは、波動的な性質を有することから、多重の反射或いは回折等を起こして死角領域R1中の死角物体4に到り、さらに自車両2にまで戻って来るという伝搬を生じ得ると考えられる。本実施形態の検知方法は、上記のように伝搬する波を活用して、死角物体4を検知する。 In the detection device 1, when a blind spot is found by the blind spot estimation unit 131, the blind spot object measurement unit 132 uses the radar 11 to measure the internal state of the blind spot region R1. Since the physical signal Sa radiated from the radar 11 of the own vehicle 2 has a wave-like property, the physical signal Sa causes multiple reflections or diffractions to reach the blind spot object 4 in the blind spot area R1, and furthermore, the physical signal Sa is transmitted to the own vehicle 2. It is thought that the propagation of returning to may occur. The detection method of the present embodiment detects the blind spot object 4 by utilizing the wave propagating as described above.
 本実施形態の危険度判定部133は、死角物体計測部132の計測結果に基づいて、死角領域R1に内在し得る死角物体4についての危険度を判定する。危険度判定部133は、危険度の判定基準となるしきい値を動的に変更可能である。危険度は、例えば死角物体4と自車両2間の衝突等の可能性が考えられる程度を示す。 The risk determining unit 133 of the present embodiment determines the risk of the blind spot object 4 that can be included in the blind spot area R1 based on the measurement result of the blind spot object measuring unit 132. The risk determination unit 133 can dynamically change a threshold value that is a reference for determining the risk. The degree of danger indicates, for example, the degree to which a possibility of a collision between the blind spot object 4 and the host vehicle 2 is considered.
 例えば、警告を要すると考えられる危険度が検知装置1において判定されると、本システムは、報知器22によって運転者等に報知したり、車両駆動部21によって自動ブレーキ等の安全性を高めるための車両制御を実行したりすることができる。本システムにおける検知装置1の動作の詳細を、以下説明する。 For example, when the detection device 1 determines the degree of danger that requires a warning, the present system notifies the driver or the like by the annunciator 22 or increases the safety of the automatic braking or the like by the vehicle drive unit 21. Or vehicle control of the vehicle. Details of the operation of the detection device 1 in the present system will be described below.
2-1.検知装置の動作
 本実施形態に係る検知装置1の動作について、図4~7を用いて説明する。
2-1. Operation of Detecting Device The operation of the detecting device 1 according to the present embodiment will be described with reference to FIGS.
 図4は、本実施形態に係る検知装置1の動作を説明するためのフローチャートである。図4のフローチャートに示す各処理は、検知装置1の制御部13によって実行される。本フローチャートは、例えば車両2の運転中に、所定の周期で開始される。 FIG. 4 is a flowchart for explaining the operation of the detection device 1 according to the present embodiment. Each process shown in the flowchart of FIG. 4 is executed by the control unit 13 of the detection device 1. This flowchart is started at a predetermined cycle while the vehicle 2 is operating, for example.
 まず、制御部13は、カメラ12から1又は複数フレームの撮像画像を取得する(S1)。ステップS1において、制御部13は、撮像画像として距離画像を取得してもよいし、取得した撮像画像に基づき距離画像を生成してもよい。距離画像は、周辺環境を監視するための各種距離を示す距離情報の一例である。 First, the control unit 13 acquires one or more frames of captured images from the camera 12 (S1). In step S1, the control unit 13 may acquire a distance image as a captured image, or may generate a distance image based on the acquired captured image. The distance image is an example of distance information indicating various distances for monitoring the surrounding environment.
 次に、制御部13は、取得した撮像画像に画像解析を行って(S2)、現在の自車両2の周辺環境に関する構造情報D1を生成する。構造情報D1は、周辺環境における種々の物体構造を示す情報であり、例えば、各種構造物までの距離を含む。また、制御部13は、ステップS2において死角推定部131としても動作し、取得した撮像画像において死角を検知するための画像解析も行う。図5に、ステップS2の解析対象の画像を例示する。 Next, the control unit 13 performs image analysis on the acquired captured image (S2), and generates structural information D1 relating to the current surrounding environment of the own vehicle 2. The structure information D1 is information indicating various object structures in the surrounding environment, and includes, for example, distances to various structures. The control unit 13 also operates as the blind spot estimation unit 131 in step S2, and performs image analysis for detecting a blind spot in the acquired captured image. FIG. 5 illustrates an image to be analyzed in step S2.
 図5は、例えば距離画像として自車両2から撮像されており(S1)、交差点3近傍で複数の構造物による壁31,32を映している。本例では、自車両2近傍の壁31の遮蔽により、当該壁31よりも奥側に死角領域R1が存在している。また、死角領域R1よりも奥側の壁32が、自車両2に対向している。以下、壁31を「遮蔽壁」といい、壁32を「対向壁」という。遮蔽壁31と対向壁32との間には、死角領域R1と外部との境界が形成される(図1参照)。 FIG. 5 is, for example, an image taken from the host vehicle 2 as a distance image (S1), and shows walls 31 and 32 of a plurality of structures near the intersection 3. In the present example, a blind spot region R1 is present behind the wall 31 due to the shielding of the wall 31 near the host vehicle 2. Further, a wall 32 on the back side of the blind spot area R1 faces the host vehicle 2. Hereinafter, the wall 31 is referred to as a “shielding wall”, and the wall 32 is referred to as an “opposing wall”. A boundary between the blind spot region R1 and the outside is formed between the shielding wall 31 and the opposing wall 32 (see FIG. 1).
 ステップS2において、制御部13は、例えば構造情報D1として距離画像における各種壁31,32の距離値を画素毎に抽出し、記憶部14に保持する。図5の場合の距離値は、方向d1に沿って自車両2側から遮蔽壁31の分、連続的に変化しながら、遮蔽壁31の端部から対向壁32に到ると不連続に変化することとなる。制御部13は、上記のような距離値の変化を解析して、死角領域R1の存在を推定できる。 In step S <b> 2, the control unit 13 extracts the distance values of the various walls 31 and 32 in the distance image for each pixel as the structure information D <b> 1 and stores the extracted values in the storage unit 14. The distance value in the case of FIG. 5 changes discontinuously from the end of the shielding wall 31 to the opposing wall 32 while continuously changing from the own vehicle 2 side by the shielding wall 31 along the direction d1. Will be done. The control unit 13 analyzes the change in the distance value as described above, and can estimate the existence of the blind spot region R1.
 図4に戻り、死角推定部131としての制御部13は、例えば画像解析による推定結果に従って、現在の自車両2の周辺環境に、死角領域R1が検知されたか否かを判断する(S3)。制御部13は、死角領域R1が検知されなかったと判断すると(S3でNO)、例えば周期的にステップS1~S3の処理を繰り返す。 Returning to FIG. 4, the control unit 13 as the blind spot estimation unit 131 determines whether or not the blind spot region R1 is detected in the current surrounding environment of the own vehicle 2 according to an estimation result by image analysis, for example (S3). When the control unit 13 determines that the blind spot area R1 has not been detected (NO in S3), the processing of steps S1 to S3 is periodically repeated, for example.
 制御部13は、死角領域R1が検知されたと判断すると(S3でYES)、死角物体計測部132としての処理を実行する(S4~S6)。本実施形態では、レーダ11の波動信号Sbにおける多重反射波を活用して、死角領域R1中の死角物体4を計測する死角物体計測部132の処理例を以下、説明する。 When the control unit 13 determines that the blind spot area R1 has been detected (YES in S3), the control unit 13 executes the processing as the blind spot object measurement unit 132 (S4 to S6). In the present embodiment, a processing example of the blind spot object measurement unit 132 that measures the blind spot object 4 in the blind spot region R1 by utilizing the multiple reflected waves in the wave signal Sb of the radar 11 will be described below.
 死角物体計測部132としての制御部13は、まず、死角領域R1に向けて物理信号Saを放射するように、レーダ11を制御する(S4)。図6(a),(b)に、それぞれ死角物体4がない場合とある場合におけるステップS4の物理信号Saの伝搬経路を例示する。 First, the control unit 13 as the blind spot object measurement unit 132 controls the radar 11 so as to emit the physical signal Sa toward the blind spot area R1 (S4). FIGS. 6A and 6B illustrate the propagation path of the physical signal Sa in step S4 when there is no blind spot object 4 and when there is a blind spot object 4, respectively.
 ステップS4において、制御部13は、例えば図5の解析結果に基づいて、レーダ11から死角領域R1の境界近傍の対向壁32に物理信号Saを放射させる。図6(a)の例において、自車両2のレーダ11からの物理信号Saは、横道の死角領域R1を介して対向壁32と反対側の壁35との間で反射を繰り返し、多重反射波として伝搬している。図6(a)の例では、死角物体4がないことに対応して、多重反射波は自車両2に向かって来ない。 In step S4, the control unit 13 causes the radar 11 to emit the physical signal Sa from the radar 11 to the opposing wall 32 near the boundary of the blind spot region R1, based on the analysis result in FIG. In the example of FIG. 6A, the physical signal Sa from the radar 11 of the host vehicle 2 is repeatedly reflected between the opposed wall 32 and the opposite wall 35 via the blind spot region R1 on the side road, and a multiple reflected wave is formed. Propagating as In the example of FIG. 6A, the multiple reflected wave does not come toward the own vehicle 2 in response to the absence of the blind spot object 4.
 一方、図6(b)の例では、死角物体4が存在することから、レーダ11からの物理信号Saは、各々の壁32,33に加えて死角物体4でも反射して、自車両2に向かう多重反射波Rb1となり得る。よって、レーダ11で受信される波動信号Sbには、死角物体4の情報を有する多重反射波Rb1の信号成分が含まれることとなる。 On the other hand, in the example of FIG. 6B, since the blind spot object 4 exists, the physical signal Sa from the radar 11 is reflected not only on the walls 32 and 33 but also on the blind spot object 4 and is reflected on the host vehicle 2. It can be a forward reflected multiple reflected wave Rb1. Therefore, the wave signal Sb received by the radar 11 includes the signal component of the multiple reflection wave Rb1 having information on the blind spot object 4.
 ステップS4において、レーダ11は、物理信号Saを放射すると共に波動信号Sbを受信して、物理信号Saの反射波に基づく各種計測を行う。制御部13は、レーダ11から計測結果を取得する(S5)。 In step S4, the radar 11 emits the physical signal Sa and receives the wave signal Sb, and performs various measurements based on the reflected wave of the physical signal Sa. The control unit 13 acquires a measurement result from the radar 11 (S5).
 制御部13は、レーダ11の計測結果に基づいて、死角物体の検知処理を行う(S6)。多重反射波Rb1(図6(b))の信号成分は、ドップラーシフト、位相及び伝搬時間により、反射元の死角物体4の速度および伝搬経路の長さに応じた情報を有している。死角物体の検知処理(S6)は、このような信号成分を解析することにより、多重反射波Rb1を反射した死角物体4の速度及び位置等を検知する。ステップS6の処理の詳細については後述する。 The controller 13 performs a blind spot object detection process based on the measurement result of the radar 11 (S6). The signal component of the multiple reflected wave Rb1 (FIG. 6B) has information corresponding to the speed of the reflection-source blind spot object 4 and the length of the propagation path by Doppler shift, phase, and propagation time. In the blind spot object detection process (S6), the speed and position of the blind spot object 4 that has reflected the multiple reflected wave Rb1 are detected by analyzing such signal components. Details of the process in step S6 will be described later.
 次に、制御部13は危険度判定部133として動作し、死角物体4の検知結果(S6)に基づいて危険度の判定処理を行う(S7)。危険度の判定処理は、例えば、検知された位置及び速度等から死角物体4が自車両2に接近することに対する警告の要否を決定するための危険度を判定する。 Next, the control unit 13 operates as the risk determination unit 133, and performs a risk determination process based on the detection result of the blind spot object 4 (S6) (S7). In the risk determination process, for example, a risk is determined based on the detected position, speed, and the like, for determining whether a warning is required for the blind spot object 4 approaching the vehicle 2.
 本実施形態における危険度の判定処理(S7)は、例えば前方車両5が存在する場合(図2)には危険度の判定基準を緩和するように、判定に用いるしきい値を動的に調整する。ステップS6において死角物体4の動き、距離、種類及び形状等の情報が検知される場合、ステップS7ではこれらの情報を用いて危険度が判定されてもよい。ステップS7の処理の詳細については後述する。 In the risk determination process (S7) in the present embodiment, the threshold value used for the determination is dynamically adjusted so as to relax the risk determination criterion when, for example, the preceding vehicle 5 is present (FIG. 2). I do. When information such as the movement, distance, type, and shape of the blind spot object 4 is detected in step S6, the risk may be determined using the information in step S7. Details of the processing in step S7 will be described later.
 次に、制御部13は、危険度の判定結果(S7)に応じて、車両制御装置20に各種の制御信号を出力する(S8)。例えば、ステップS7において警告を要すると判定された場合、制御部13は、報知器22に警告を報知させたり、車両駆動部21を制御したりするための制御信号を生成する。 Next, the control unit 13 outputs various control signals to the vehicle control device 20 according to the determination result of the degree of risk (S7) (S8). For example, when it is determined in step S7 that a warning is required, the control unit 13 generates a control signal for causing the alarm unit 22 to notify the warning and controlling the vehicle driving unit 21.
 制御部13は、例えば制御信号を出力する(S8)と、図4のフローチャートに示す処理を終了する。 (4) When the control unit 13 outputs, for example, a control signal (S8), the processing shown in the flowchart of FIG.
 以上の処理によると、検知装置1は自車両2の周辺監視を行いながら(S1~S3)、死角が発見されると(S3でYES)、死角物体4についての危険度を判定し(S7)、各種のアクションを行うことができる(S8)。 According to the above processing, the detection device 1 monitors the surroundings of the own vehicle 2 (S1 to S3), and if a blind spot is found (YES in S3), determines the degree of danger of the blind spot object 4 (S7). And various actions can be performed (S8).
 以上の処理では、周辺監視にカメラ12を用いたが、ナビゲーション機器15を用いてもよい。本変形例を図7に示す。ナビゲーション機器15は、例えば図7に示すように、自車両2の周辺環境の地図情報D2において、自車両2までの各種距離を計算し、自車両2の現在位置を監視する。制御部13は、以上のようなナビゲーション機器15の監視結果を、図4の各種処理に用いることができる。制御部13は、ナビゲーション機器15の監視結果に基づいて、例えば地図情報D2中の構造物30に基づき、構造情報D1を取得したり、死角領域R1を検知したりすることができる(S2)。また、制御部13は、図4の処理において適宜、車載センサ16の検出結果を用いてもよい。 In the above processing, the camera 12 is used for monitoring the periphery, but the navigation device 15 may be used. This modification is shown in FIG. For example, as shown in FIG. 7, the navigation device 15 calculates various distances to the host vehicle 2 in the map information D2 of the surrounding environment of the host vehicle 2, and monitors the current position of the host vehicle 2. The control unit 13 can use the monitoring result of the navigation device 15 as described above for various processes in FIG. The control unit 13 can acquire the structural information D1 or detect the blind spot region R1 based on the monitoring result of the navigation device 15, for example, based on the structure 30 in the map information D2 (S2). Further, the control unit 13 may use the detection result of the vehicle-mounted sensor 16 as appropriate in the processing of FIG.
2-2.死角物体の検知処理
 死角物体の検知処理(図4のS6)について、図8~10を用いて説明する。
2-2. Blind Spot Object Detection Process The blind spot object detection process (S6 in FIG. 4) will be described with reference to FIGS.
 図8は、死角物体の検知処理の実験を説明するための図である。図8(a)は、本実験の実験環境の構造情報D1を示す。図8(b)は、死角物体4がない場合のレーダ11の計測結果を示す。図9は、図8の実験において死角物体がある場合を例示する図である。図9(a)は、死角物体4がある場合のレーダ11の計測結果を示す。図9(b)は、死角物体4から推定される多重反射波の伝搬経路を例示する。 FIG. 8 is a diagram for describing an experiment of a blind spot object detection process. FIG. 8A shows the structure information D1 of the experiment environment of this experiment. FIG. 8B shows a measurement result of the radar 11 when there is no blind spot object 4. FIG. 9 is a diagram illustrating a case where there is a blind spot object in the experiment of FIG. FIG. 9A shows a measurement result of the radar 11 when the blind spot object 4 is present. FIG. 9B illustrates a propagation path of a multiple reflection wave estimated from the blind spot object 4.
 本実験は、図8(a)に示すように、交差点を有する通路において行われた。図8(b),9(a)における濃淡は、淡いほどレーダ11で得られた信号強度が強いことを示している。 実 験 This experiment was performed in a passage having an intersection as shown in FIG. 8 (b) and 9 (a) indicate that the lighter the lighter, the stronger the signal intensity obtained by the radar 11.
 本実験においては、死角物体4がない状態では、図8(b)に示すように、4m付近に強いピークP1が確認された。ピークP1は、レーダ11に対向する対向壁P1からの反射波を示している。また、図8(b)では、その他各壁32,33からの反射波によるピークP2,P3がそれぞれ確認できる。 実 験 In this experiment, when there was no blind spot object 4, as shown in FIG. 8B, a strong peak P1 was observed around 4 m. The peak P1 indicates a reflected wave from the facing wall P1 facing the radar 11. Further, in FIG. 8B, peaks P2 and P3 due to reflected waves from the other walls 32 and 33 can be respectively confirmed.
 一方、死角物体4を置いた状態では、図9(a)に示すように、対向壁32よりも遠い7m付近に、強いピークP4が現れた。同ピークP4の方位は、レーダ11から対向壁32の奥側に見える。以上の距離と方位から、当該ピークP4が、対向壁32による反射を経て死角物体4から反射した成分が主となっていることが分かる(図9(b)参照)。即ち、レーダ11の計測結果におけるピークP4までの距離と方位に基づいて、死角物体4を波源とするピークP4を検知できることが確認された。 On the other hand, when the blind spot object 4 was placed, as shown in FIG. 9A, a strong peak P4 appeared near 7 m farther than the opposing wall 32. The azimuth of the peak P4 is seen from the radar 11 to the far side of the opposing wall 32. From the above distance and direction, it can be seen that the peak P4 is mainly a component reflected from the blind spot object 4 through reflection by the opposing wall 32 (see FIG. 9B). That is, it was confirmed that the peak P4 having the blind spot object 4 as a wave source can be detected based on the distance and the azimuth to the peak P4 in the measurement result of the radar 11.
 以上のような死角物体4の信号成分の解析は、周辺環境の構造情報を用いることにより、死角物体4の有無及び位置等をより精度良く検知できる。以下、本実施形態における死角物体の検知処理の一例を、図10を用いて説明する。 In the analysis of the signal component of the blind spot object 4 as described above, the presence / absence, position, and the like of the blind spot object 4 can be detected more accurately by using the structural information of the surrounding environment. Hereinafter, an example of a blind spot object detection process according to the present embodiment will be described with reference to FIG.
 図10は、本実施形態における死角物体の検知処理を例示するフローチャートである。図10のフローチャートによる処理は、図4のステップS6において、死角物体計測部132として動作する制御部13によって実行される。 FIG. 10 is a flowchart illustrating a blind spot object detection process according to the present embodiment. The process according to the flowchart in FIG. 10 is executed by the control unit 13 operating as the blind spot object measurement unit 132 in step S6 in FIG.
 まず、制御部13は、図4のステップS5において取得したレーダ11の計測結果の信号から、死角物体の解析対象とする信号成分を抽出するために、周辺環境からの反射波を示す環境成分を除去する(S11)。ステップS11の処理は、例えばステップS2で取得された構造情報を用いて行われる。 First, the control unit 13 extracts an environmental component indicating a reflected wave from the surrounding environment from the signal of the measurement result of the radar 11 acquired in step S5 of FIG. It is removed (S11). The process in step S11 is performed using, for example, the structure information acquired in step S2.
 例えば、図8(b)の例の各ピークP1,P2,P3は、通路の構造情報D1(図8(b))において各々対応する壁31,32,33からの反射波を示す環境成分として、予め推定可能である。制御部13は、構造情報D1を参照して各種構造物での反射波を予測して、レーダ11の計測結果(例えば図9(a))から予測結果の環境成分を差し引く(S11)。これにより、通路等の環境下の構造物による反射波の影響を低減し、死角の物体の信号成分のみを強調し易くできる。 For example, each of the peaks P1, P2, and P3 in the example of FIG. 8B is an environment component indicating a reflected wave from the corresponding wall 31, 32, or 33 in the passage structure information D1 (FIG. 8B). , Can be estimated in advance. The control unit 13 predicts reflected waves from various structures with reference to the structure information D1, and subtracts the environmental component of the prediction result from the measurement result (for example, FIG. 9A) of the radar 11 (S11). As a result, it is possible to reduce the influence of a reflected wave due to a structure in an environment such as a passage, and to easily emphasize only signal components of a blind spot object.
 次に、制御部13は、環境成分の除去により得られた信号成分に基づいて、死角物体4を検知するための信号解析を行う(S12)。ステップS12の信号解析は、周波数解析、時間軸上の解析、空間分布および信号強度等の各種の解析を含んでもよい。 Next, the control unit 13 performs signal analysis for detecting the blind spot object 4 based on the signal component obtained by removing the environmental component (S12). The signal analysis in step S12 may include various types of analysis such as frequency analysis, analysis on the time axis, spatial distribution, and signal strength.
 制御部13は、信号解析の解析結果に基づいて、例えば死角の対向壁32の向こう側に波源が観測されるか否かを判断し(S13)、これによって、死角物体4の有無を検知する。例えば、図9(a)の例においてピークP4は、対向壁32よりも通路の奥側を波源としており、通路の構造から環境成分として予測されない位置にある。このことから、当該ピークP4は、死角内を波源とする波が、多重反射したことに起因すると推定できる。つまり、制御部13は、検知済みの死角の方位に、対向壁32を超える距離で反射波が観測される場合、死角物体4があると判定できる(ステップS13でYES)。 The control unit 13 determines whether a wave source is observed, for example, beyond the blind spot facing the opposite wall 32 based on the analysis result of the signal analysis (S13), and thereby detects the presence or absence of the blind spot object 4. . For example, in the example of FIG. 9A, the peak P4 has a wave source located on the far side of the passage than the facing wall 32 and is located at a position that is not predicted as an environmental component from the structure of the passage. From this, it can be presumed that the peak P4 is caused by multiple reflection of a wave whose source is inside the blind spot. That is, when the reflected wave is observed at a distance exceeding the facing wall 32 in the direction of the detected blind spot, the control unit 13 can determine that the blind spot object 4 is present (YES in step S13).
 制御部13は、死角の対向壁32の向こう側に波源が観測されると判断した場合(S13でYES)、多重反射による屈曲が推定される伝搬経路に応じて、死角物体4までの距離および速度といった各種の状態変数を計測する(S14)。例えば、制御部13は、構造情報D1において死角部分の道幅(死角領域R1の幅)を示す情報を用いることによって、例えば図9(b)に示すように、信号成分から分かる死角物体4までの経路長を折り返すように補正して、より実際の位置に近い死角物体4の位置を算出することができる。 When the control unit 13 determines that the wave source is observed beyond the opposite wall 32 in the blind spot (YES in S13), the distance to the blind spot object 4 and the distance to the blind spot object 4 are determined according to the propagation path in which the bending due to the multiple reflection is estimated. Various state variables such as speed are measured (S14). For example, the control unit 13 uses the information indicating the road width of the blind spot portion (the width of the blind spot area R1) in the structural information D1, and thereby, for example, as shown in FIG. By correcting the path length so as to be folded, the position of the blind spot object 4 closer to the actual position can be calculated.
 制御部13は、死角物体4の測量を行うと(S14)、図4のステップS6の処理を終了する。その後、制御部13は、検知された死角物体4についての危険度の判定処理(図4のS7)を実行する。 When the control unit 13 measures the blind spot object 4 (S14), the process of step S6 in FIG. 4 ends. After that, the control unit 13 executes a risk determination process (S7 in FIG. 4) for the detected blind spot object 4.
 また、制御部13は、死角の対向壁32の向こう側に波源が観測されないと判断した場合(S13でNO)、特に測量を行わずに、本処理を終了する。この場合、制御部13は、図4のステップS7以降の処理を省略してもよい。 If the control unit 13 determines that the wave source is not observed beyond the opposite wall 32 in the blind spot (NO in S13), the control unit 13 ends this processing without performing any surveying. In this case, the control unit 13 may omit the processing after step S7 in FIG.
 以上の処理によると、レーダ11の物理信号Saにおける多重反射の性質に基づき死角領域R1内部で生じた信号成分を利用して、死角物体4を検知することができる。 According to the above processing, the blind spot object 4 can be detected using the signal component generated inside the blind spot area R1 based on the property of the multiple reflection in the physical signal Sa of the radar 11.
 ここで、死角物体4の情報を有する信号成分は微弱であり、死角外の見えている物体からの反射波も存在する中で検出することとなるため、検出及び推定が難しいと考えられる。また、死角物体4までの実際の距離と信号の伝搬経路の長さが異なるため、実際の距離を推定し難いとも考えられる。これに対して、周辺環境の構造情報D1を用いることにより、受信波を解析する前提条件を絞り込んだり(S11)、推定精度を高めたりすることができる(S14)。 Here, the signal component having information on the blind spot object 4 is weak, and it is detected in the presence of a reflected wave from a visible object outside the blind spot. Therefore, it is considered that detection and estimation are difficult. In addition, since the actual distance to the blind spot object 4 is different from the length of the signal propagation path, it may be difficult to estimate the actual distance. On the other hand, by using the structure information D1 of the surrounding environment, it is possible to narrow down the preconditions for analyzing the received wave (S11) and to improve the estimation accuracy (S14).
 例えば、ステップS11において、制御部13は、構造情報D1における死角近傍の交差点までの距離を参照して、交差点との直線距離に対する信号の往復伝搬時間以下で得られる受信波の信号成分を除去する。このような受信波は直接反射波(即ち反射1回の波)であり、死角物体4の情報を含まないことから、解析対象から除外することができる。また、制御部13は、自車両2から見た死角の方位角に基づいて、死角から到来する反射波と他の角度から到来する反射波とを分離することもできる。 For example, in step S11, the control unit 13 refers to the distance to the intersection near the blind spot in the structure information D1, and removes the signal component of the received wave obtained within a round trip propagation time of the signal with respect to the linear distance to the intersection. . Such a received wave is a directly reflected wave (ie, a single reflected wave) and does not include information on the blind spot object 4, and thus can be excluded from the analysis target. The control unit 13 can also separate the reflected wave coming from the blind spot from the reflected wave coming from another angle based on the azimuth angle of the blind spot viewed from the host vehicle 2.
 ステップS11の処理は、必ずしも周辺環境の構造情報D1を用いなくてもよい。例えば、制御部13は、時間軸に沿って得た信号から、自車両2の位置変化を差し引いて、解析対象を動体に制限してもよい。本処理は、ステップS12の信号解析において行われてもよい。 処理 The processing in step S11 does not necessarily need to use the structure information D1 of the surrounding environment. For example, the control unit 13 may limit the analysis target to a moving object by subtracting the position change of the own vehicle 2 from the signal obtained along the time axis. This processing may be performed in the signal analysis of step S12.
 以上のステップS12において、制御部13は、解析対象の信号成分において、動体に反射したことによるドップラーシフト、或いは人間や自転車など特有の所作の揺らぎといった、特定の物体の所作により現れる特徴があるか否かを解析してもよい。また、制御部13は、空間的に広がりを持った面計測の信号分布が、自動車、自転車、人間などの特有の分布を持っているか、或いは反射強度により自動車大の金属体による反射が含まれるか等を解析してもよい。以上のような解析は、適宜組み合わせて行われてもよいし、個々を明示的に解析する代わりに、機械学習を用いて多次元の特徴量として解析されてもよい。 In the above step S12, the control unit 13 determines whether the signal component to be analyzed has a feature that appears due to the behavior of a specific object, such as Doppler shift due to reflection on a moving object, or fluctuation of a behavior peculiar to a human or a bicycle. Whether or not it may be analyzed. In addition, the control unit 13 determines whether the spatially distributed surface measurement signal distribution has a characteristic distribution of an automobile, a bicycle, a human, or the like, or includes a reflection from a metal object of an automobile size depending on the reflection intensity. Or the like may be analyzed. The above analysis may be performed in combination as appropriate, or may be analyzed as a multidimensional feature using machine learning instead of explicitly analyzing each.
2-3.危険度の判定処理
 本実施形態における危険度の判定処理(図4のS7)は、死角領域R1の検出結果に基づいて、死角物体4が検知されることにより、死角物体4についての危険度を判定する。この際、前方車両5(図2)等の周辺環境の状況に応じて、危険度のしきい値が動的に調整される。ステップS7の処理の詳細を、図11~12を用いて説明する。
2-3. Risk Determination Process In the risk determination process (S7 in FIG. 4) in the present embodiment, the risk of the blind spot object 4 is determined by detecting the blind spot object 4 based on the detection result of the blind spot region R1. judge. At this time, the threshold value of the degree of danger is dynamically adjusted according to the situation of the surrounding environment such as the preceding vehicle 5 (FIG. 2). Details of the processing in step S7 will be described with reference to FIGS.
 図11は、危険度の判定処理を例示するフローチャートである。図12は、危険度の判定処理を説明するための図である。図11のフローチャートによる処理は、図4のステップS7において、危険度判定部133として動作する制御部13によって実行される。 FIG. 11 is a flowchart illustrating an example of a risk determination process. FIG. 12 is a diagram for explaining the risk determination processing. The process according to the flowchart in FIG. 11 is executed by the control unit 13 operating as the risk determination unit 133 in step S7 in FIG.
 まず、制御部13は、ステップS6における死角物体4の検知結果に基づいて、危険度指数Dを算出する(S21)。危険度指数Dは、検知された死角物体4と自車両2との間の衝突に関する危険度を判定するための指標を示す。例えば図12に示すように、死角物体4が自車両2に近付く速度vが、危険度指数Dに設定できる。 First, the control unit 13 calculates the risk index D based on the detection result of the blind spot object 4 in step S6 (S21). The risk index D indicates an index for determining the risk of a collision between the detected blind spot object 4 and the host vehicle 2. For example, as shown in FIG. 12, the speed v 1 of blind spot object 4 approaches the own vehicle 2 can be set to risk index D.
 また、制御部13は、自車両2の周辺環境において死角領域R1が合流する合流地点に、物体が存在するか否かを判断する(S22)。ステップS22の処理は、例えば図4のステップS2の解析結果に基づき行われる。例えば、制御部13は、距離画像あるいは構造情報D1において交差点3等の合流地点を特定し、特定した合流地点に動体が位置するか否かを検知することにより、ステップS22の判断を行う。 {Circle around (1)} The control unit 13 determines whether or not an object exists at the junction where the blind spot region R1 joins in the surrounding environment of the vehicle 2 (S22). The process in step S22 is performed based on, for example, the analysis result in step S2 in FIG. For example, the control unit 13 specifies the junction such as the intersection 3 in the distance image or the structure information D1, and determines whether or not the moving object is located at the specified junction, thereby performing the determination in step S22.
 例えば、図1に例示する状況では、自車両2の進路と死角領域R1との合流地点である交差点3に、前方車両5のような他の車両等は特に存在していない(図2参照)。このような状況では、制御部13は、死角の合流地点に物体が存在しないと判断する(S22でNO)。一方、図2に例示する状況では、死角の合流地点である交差点3に、前方車両5が位置していることから、制御部13は、死角の合流地点に物体が存在すると判断する(S22でYES)。 For example, in the situation illustrated in FIG. 1, there is no other vehicle such as the preceding vehicle 5 at the intersection 3 that is the junction of the path of the host vehicle 2 and the blind spot region R1 (see FIG. 2). . In such a situation, the control unit 13 determines that there is no object at the junction of the blind spots (NO in S22). On the other hand, in the situation illustrated in FIG. 2, since the preceding vehicle 5 is located at the intersection 3 that is the junction of the blind spots, the control unit 13 determines that an object exists at the junction of the blind spots (S22). YES).
 制御部13は、死角の合流地点に物体が存在しないと判断すると(S22でNO)、危険度を判定するためのしきい値Vaを、通常レベルに設定する(S23)。しきい値Vaの通常レベルは、例えば注意喚起が特に為されていない通常の状態の死角物体4に関して警告が必要となる危険度指数Dの大きさを考慮して設定される。 When the control unit 13 determines that there is no object at the junction of the blind spots (NO in S22), it sets the threshold value Va for determining the degree of danger to a normal level (S23). The normal level of the threshold value Va is set in consideration of, for example, the magnitude of the risk index D for which a warning is required for the blind spot object 4 in a normal state where no attention is specifically given.
 制御部13は、算出した危険度指数Dが、設定したしきい値Vaを超えるか否かを判断する(S25)。例えば、D=vの場合に危険度指数Dがしきい値Vaを上回ると、制御部13は、ステップS25で「YES」に進む。 The control unit 13 determines whether or not the calculated risk index D exceeds the set threshold value Va (S25). For example, when the risk index D in the case of D = v 1 exceeds the threshold value Va, the control unit 13 proceeds to "YES" in step S25.
 制御部13は、危険度指数Dがしきい値Vaを超えると判断したとき(S25でYES)、危険度の判定結果として、例えば警告フラグを「ON」に設定する(S26)。警告フラグは、死角物体4に関する警告の有無を「ON/OFF」で管理するフラグであり、記憶部14に記憶される。 When the control unit 13 determines that the risk index D exceeds the threshold value Va (YES in S25), the control unit 13 sets, for example, a warning flag to “ON” as a risk determination result (S26). The warning flag is a flag that manages the presence / absence of a warning regarding the blind spot object 4 by “ON / OFF”, and is stored in the storage unit 14.
 一方、制御部13は、危険度指数Dがしきい値Vaを超えないと判断したとき(S25でNO)、警告フラグを「OFF」に設定する(S27)。 On the other hand, when determining that the risk index D does not exceed the threshold value Va (NO in S25), the control unit 13 sets the warning flag to “OFF” (S27).
 また、制御部13は、死角の合流地点に物体が存在すると判断すると(S22でYES)、しきい値Vaを、通常レベルではなく緩和レベルに設定する(S24)。しきい値Vaの緩和レベルは、死角物体4が注意喚起された状態であることから、例えば死角物体4に関する警告が必要となる判定基準を、通常レベルよりも緩和するレベルである。 When the control unit 13 determines that an object is present at the junction of the blind spots (YES in S22), it sets the threshold value Va to a relaxation level instead of a normal level (S24). Since the blind spot object 4 is in a state of being alerted, the mitigation level of the threshold value Va is, for example, a level at which a criterion that requires a warning regarding the blind spot object 4 is relaxed from the normal level.
 例えばD=vの場合、しきい値Vaの緩和レベルは、しきい値Vaの通常レベルよりも大きい値に設定される。この場合、制御部13は、死角物体4の速度vが、通常レベルよりも大きいしきい値Vaを上回るか否かに応じて危険度を判定し(S25)、警告フラグを「ON」又は「OFF」に設定する(S26,S27)。 For example, in the case of D = v 1, the mitigation level of the threshold Va is set to a value larger than the normal level of the threshold Va. In this case, the control unit 13, the speed v 1 of the blind spot object 4, to determine the degree of risk depending on whether exceeds the larger threshold Va than the normal level (S25), a warning flag "ON" or It is set to "OFF" (S26, S27).
 制御部13は、以上のように警告フラグを設定すると(S26,S27)、危険度の判定処理(図4のS7)を終了して、ステップS8の処理に進む。 When the warning flag is set as described above (S26, S27), the control unit 13 ends the risk determination process (S7 in FIG. 4) and proceeds to the process of step S8.
 以上の処理によると、死角物体4が自車両2或いは交差点3に近付く危険度が、対応する危険度指数Dに応じて判定される。例えば、警告フラグに応じた2値判定が行われる。警告フラグが「ON」のとき、制御部13は、報知器22に警告させたり、車両駆動部21に特定の制御を行わせたりすることができる(図4のS8)。 According to the above processing, the risk of the blind spot object 4 approaching the own vehicle 2 or the intersection 3 is determined according to the corresponding risk index D. For example, a binary determination according to the warning flag is performed. When the warning flag is “ON”, the control unit 13 can cause the alarm 22 to warn or cause the vehicle drive unit 21 to perform specific control (S8 in FIG. 4).
 この際、前方車両5のように死角の合流地点に物体が存在する状況になると、しきい値Vaが通常レベルから緩和レベルに変更される(S22~S24)。これにより、前方車両5等によって死角物体4には注意喚起が為されている影響を考慮して、死角物体4の速度が通常レベルよりも大きくても緩和レベルよりも小さい場合を、警告せずに許容することができる。なお、ステップS22~S24の処理の実行時は特に限定されず、例えばステップS21以前にステップS22~S24が行われてもよい。 At this time, if an object is present at the junction of the blind spots, such as the preceding vehicle 5, the threshold value Va is changed from the normal level to the mitigation level (S22 to S24). Accordingly, in consideration of the effect that the blind spot object 4 is alerted by the forward vehicle 5 or the like, no warning is given when the speed of the blind spot object 4 is higher than the normal level but lower than the relaxation level. Can be tolerated. Note that the execution time of the processing of steps S22 to S24 is not particularly limited, and for example, steps S22 to S24 may be performed before step S21.
 また、危険度の判定処理は2値判定に限らず、例えば警告の不要時に注意喚起の有無を判定する3値判定が行われてもよい。例えば、自車両2に対する注意喚起用のしきい値Vb(<Va)を用いて、制御部13が、ステップS25で「NO」に進んだときにD>Vbか否かを判断してもよい。 The risk determination process is not limited to the binary determination. For example, a ternary determination for determining whether or not a warning is issued when a warning is unnecessary may be performed. For example, using the threshold value Vb (<Va) for alerting the host vehicle 2, the control unit 13 may determine whether or not D> Vb when proceeding to “NO” in step S25. .
 以上の処理において、危険度指数Dは速度vに限らず、死角物体4に関する種々の状態変数により設定可能であり、例えば速度vの代わりに加速度dv/dtに設定されてもよい。 In the above processing, risk index D is not limited to the speed v 1, can be set by various state variables related to the blind spot object 4, for example, instead of the velocity v 1 may be set to the acceleration dv 1 / dt.
 また、危険度指数Dは、自車両2と死角物体4との間の距離Lに設定されてもよい。距離Lは、小さいほど自車両2と死角物体4間の衝突に関する危険度が高いと考えられる。そこで、例えばステップS25において、制御部13は、危険度指数D(=L)がしきい値Vaを下回るときに「YES」に進み、下回らないときには「NO」に進んでもよい。 The risk index D may be set to the distance L between the vehicle 2 and the blind spot object 4. It is considered that the smaller the distance L is, the higher the risk of collision between the host vehicle 2 and the blind spot object 4 is. Thus, for example, in step S25, the control unit 13 may proceed to “YES” when the risk index D (= L) falls below the threshold value Va, and may proceed to “NO” when it does not fall below the threshold value Va.
 上記の場合、しきい値Vaの緩和レベルは、例えば通常レベルよりも小さい値に設定される。これにより、前方車両5等が存在する場合に死角物体4には注意喚起が為されている影響を考慮して、緩和レベルよりも大きい範囲内で死角物体4までの距離Lが通常レベルよりも小さい場合を許容でき、警告等を省略することができる。 In the above case, the relaxation level of the threshold value Va is set to, for example, a value smaller than the normal level. Accordingly, in consideration of the effect of alerting the blind spot object 4 when the forward vehicle 5 or the like exists, the distance L to the blind spot object 4 within the range larger than the mitigation level is smaller than the normal level. A smaller case can be tolerated, and a warning or the like can be omitted.
 また、危険度指数Dは、各種の状態変数の組み合わせによって設定されてもよい。このような一例の危険度指数Dを次式(1)に示す。
D=|(L-vΔt)+(L-vΔt)| …(1)
 上式(1)において、Lは、基準位置P0から死角物体4までの距離である(図12)。基準位置P0は、例えば交差点の中心など、死角物体4と自車両2との衝突が想定される位置に設定される。Δtは、所定の時間幅であり、例えば自車両2が基準位置P0に到達するまでにかかることが予測される時間幅の近傍に設定される。Lは、基準位置P0から自車両2までの距離である。vは、自車両2の速度であり、車載センサ16等から取得可能である。
Further, the risk index D may be set by a combination of various state variables. An example of such a risk index D is shown in the following equation (1).
D = | (L 1 −v 1 Δt) + (L 0 −v 0 Δt) | (1)
In the above formula (1), L 1 is the distance from the reference position P0 to the blind spot object 4 (Figure 12). The reference position P0 is set to a position where a collision between the blind spot object 4 and the vehicle 2 is assumed, such as the center of an intersection. Δt is a predetermined time width, and is set, for example, in the vicinity of a time width expected to take until the host vehicle 2 reaches the reference position P0. L 0 is the distance from the reference position P 0 to the host vehicle 2. v 0 is the speed of the vehicle 2 and can be obtained from the on-board sensor 16 or the like.
 上式(1)の危険度指数Dは、時間幅Δtの経過後に推定される、死角物体4と基準位置P0間の距離と、基準位置P0と自車両2間の距離との総和である(図12)。上式(1)によると、危険度指数Dが所定値よりも小さくなると、自車両2と死角物体4とが同時に基準位置P0に到達する可能性が充分に高いといった推定が行える。このような推定に対応する危険度の判定として、上式(1)の場合、制御部13はD=Lの場合と同様に、危険度指数Dがしきい値Vaを下回るときステップS25で「YES」に進み、下回らないとき「NO」に進んでもよい。このような危険度指数Dに対してしきい値Vaを動的に調整することにより、危険度の判定を精度良くすることができる。 The risk index D in the above equation (1) is the sum of the distance between the blind spot object 4 and the reference position P0 and the distance between the reference position P0 and the host vehicle 2, which are estimated after the elapse of the time width Δt ( (FIG. 12). According to the above equation (1), when the risk index D becomes smaller than a predetermined value, it can be estimated that the possibility that the own vehicle 2 and the blind spot object 4 will simultaneously reach the reference position P0 is sufficiently high. As the determination of the risk corresponding to such estimation, in the case of the above equation (1), as in the case of D = L, when the risk index D falls below the threshold Va, the control unit 13 determines “ The process may proceed to “YES” and proceed to “NO” when the value does not fall. By dynamically adjusting the threshold value Va with respect to such a risk index D, it is possible to accurately determine the risk.
 また、危険度指数Dは、以下の式(2)又は式(2’)のように設定されてもよい。
D=L-vΔt              …(2)
D=|L-vΔt|            …(2’)
 上記の各式(2),(2’)では、例えばΔt=L/vに設定される。時間幅Δtは、自車両2の速度vの変動或いは基準位置P0の見積誤差などを考慮した許容範囲内で設定されてもよい。
Further, the risk index D may be set as in the following Expression (2) or Expression (2 ′).
D = L 1 −v 1 Δt (2)
D = | L 1 −v 1 Δt | (2 ′)
In the above equations (2) and (2 ′), for example, Δt = L 0 / v 0 is set. The time width Δt may be set within an allowable range in consideration of a change in the speed v 0 of the host vehicle 2 or an estimation error of the reference position P0.
 式(2)の危険度指数Dが所定値よりも小さいとき(負値を含む)、自車両2が基準位置P0に到達する前に死角物体4が自車両2前方を横切る可能性が充分に高いと推定できる。また、式(2’)の危険度指数D(式(2)の場合の絶対値)が所定値よりも小さいとき、自車両2と死角物体4とが同時に基準位置P0に存在する可能性が充分に高いと推定できる。以上のような推定に対応して、制御部13は、式(2)又は式(2’)の危険度指数Dを用いて、式(1)の場合と同様に危険度の判定を行うことができる。 When the risk index D in Expression (2) is smaller than a predetermined value (including a negative value), there is a sufficient possibility that the blind spot object 4 will cross the front of the host vehicle 2 before the host vehicle 2 reaches the reference position P0. It can be estimated that it is high. When the risk index D (absolute value in the case of the equation (2)) of the equation (2 ′) is smaller than a predetermined value, there is a possibility that the own vehicle 2 and the blind spot object 4 are simultaneously present at the reference position P0. It can be estimated that it is sufficiently high. In response to the above estimation, the control unit 13 determines the degree of risk in the same manner as in the case of Expression (1) using the risk index D of Expression (2) or Expression (2 ′). Can be.
 また、以上のような危険度の判定処理において、しきい値Vaの緩和レベル及び通常レベルは、例えば自車両2及び死角物体4の状態に応じて、動的に変更されてもよい。例えば、上述したLが小さかったり、dv/dt又はdv/dtが大きかったり、或いは死角物体4が人間と推定される場合、危険度の判定をより厳格に行うべきと考えられる。そこで、このような場合が検知されると、制御部13は、例えば上式(1)の危険度指数Dに対して、しきい値Vaを大きくしてもよい。 In the risk determination processing as described above, the mitigation level and the normal level of the threshold value Va may be dynamically changed according to, for example, the states of the host vehicle 2 and the blind spot object 4. For example, small or is L 0 as described above, large or the dv 0 / dt or dv 1 / dt, or if the blind spot object 4 is presumed to humans, is considered to be a determination of the risk more strictly. Therefore, when such a case is detected, the control unit 13 may increase the threshold value Va with respect to the risk index D of the above equation (1), for example.
3.まとめ
 以上のように、本実施形態に係る検知装置1は、移動体の一例である自車両2の周辺環境における物体を検知する。検知装置1は、検出部としてのレーダ11及びカメラ12と、制御部13とを備える。検出部11,12は、自車両2から周辺環境までの距離を示す距離情報を検出する。制御部13は、検出部11,12を制御して、検出結果を解析する。制御部13は、検出部11,12の検出結果に基づいて、周辺環境における死角を示す死角領域R1を検知し、死角領域R1の検知結果に基づいて、死角領域R1に関する危険度を判定する(S7)。制御部13は、検知された死角領域R1と自車両2の進路とが合流する合流地点(例えば交差点3)に物体(例えば前方車両5)が存在する場合、危険度の判定基準を緩和する(S24)。
3. Conclusion As described above, the detection device 1 according to the present embodiment detects an object in a surrounding environment of the own vehicle 2 which is an example of a moving object. The detection device 1 includes a radar 11 and a camera 12 as detection units, and a control unit 13. The detection units 11 and 12 detect distance information indicating the distance from the vehicle 2 to the surrounding environment. The control unit 13 controls the detection units 11 and 12 to analyze the detection result. The control unit 13 detects a blind spot region R1 indicating a blind spot in the surrounding environment based on the detection results of the detection units 11 and 12, and determines a risk degree regarding the blind spot region R1 based on the detection result of the blind spot region R1 ( S7). When an object (for example, the preceding vehicle 5) exists at a junction (for example, the intersection 3) where the detected blind spot region R1 and the path of the vehicle 2 merge, the control unit 13 relaxes the criterion for determining the degree of danger ( S24).
 以上の検知装置1によると、死角の合流地点に物体が存在する場合には危険度の判定基準を緩和することにより、自車両2の周辺環境における死角に対して物体を検知して危険度を判定する際に過剰な危険度の誤判定を抑制することができる。 According to the detection device 1 described above, when an object is present at the junction of blind spots, the risk criterion is relaxed, thereby detecting the object with respect to the blind spot in the surrounding environment of the own vehicle 2 to reduce the risk. It is possible to suppress erroneous determination of an excessive degree of risk when making a determination.
 本実施形態の検知装置1において、制御部13は、検出部の検出結果に基づいて、死角領域R1の中の物体を検知し(S6)、死角領域R1の中の死角物体4の検知結果に応じて、危険度を判定する(S7)。これにより、死角物体4に応じた危険度を判定することができる。 In the detection device 1 of the present embodiment, the control unit 13 detects an object in the blind spot area R1 based on the detection result of the detection unit (S6), and determines the detection result of the blind spot object 4 in the blind spot area R1. Accordingly, the degree of danger is determined (S7). Thereby, the degree of danger according to the blind spot object 4 can be determined.
 本実施形態の検知装置1において、レーダ11は、自車両2から周辺環境に、波の特性を有する物理信号Saを放射して、放射した物理信号Saの反射波に応じて距離情報を検出する。制御部13は、レーダ11の検出結果において、死角領域R1から到達する波の成分を含んだ波動信号Sbに基づいて、死角物体4を検知する。これにより、レーダ11からの物理信号Saにおける波の特性を活用して、自車両2から周辺環境における死角の中に存在する物体を検知することができる。活用する波は多重反射波に限らず、回折波或いは透過波を含んでもよい。 In the detection device 1 of the present embodiment, the radar 11 emits a physical signal Sa having wave characteristics from the own vehicle 2 to the surrounding environment, and detects distance information according to a reflected wave of the emitted physical signal Sa. . The control unit 13 detects the blind spot object 4 based on the wave signal Sb including the component of the wave arriving from the blind spot area R1 in the detection result of the radar 11. Thus, an object existing in the blind spot in the surrounding environment from the host vehicle 2 can be detected by utilizing the characteristics of the wave in the physical signal Sa from the radar 11. Waves to be used are not limited to multiple reflection waves, and may include diffracted waves or transmitted waves.
 本実施形態の検知装置1において、制御部13は、周辺環境において死角領域R1を検知したとき、検知した死角領域R1に向けて物理信号Saを放射するように、レーダ11を制御する(S4)。これにより、死角領域R1近傍に物理信号Saを集中させ、死角領域R1の中の死角物体4から多重反射波Rb1等を得やすくすることができる。なお、レーダ11からの物理信号Saは必ずしも死角領域Raに集中させなくてもよく、例えば、レーダ11が検出可能な範囲に適時、物理信号Saを放射してもよい。 In the detection device 1 of the present embodiment, when detecting the blind spot region R1 in the surrounding environment, the control unit 13 controls the radar 11 to emit the physical signal Sa toward the detected blind spot region R1 (S4). . This makes it possible to concentrate the physical signal Sa in the vicinity of the blind spot area R1, and to easily obtain the multiple reflected waves Rb1 and the like from the blind spot object 4 in the blind spot area R1. The physical signal Sa from the radar 11 does not necessarily need to be concentrated in the blind spot area Ra. For example, the physical signal Sa may be radiated as appropriate within a range that the radar 11 can detect.
 本実施形態の検知装置1は、周辺環境の物体構造を示す構造情報D1を記憶する記憶部14をさらに備える。制御部13は、構造情報D1を参照し、レーダ11の検出結果において死角領域R1から到達する波の成分を含んだ波動信号を解析して、死角物体4を検知する(S6)。構造情報D1を用いることにより、死角物体4の検知を精度良くすることができる。 The detection device 1 of the present embodiment further includes a storage unit 14 that stores structure information D1 indicating the object structure of the surrounding environment. The control unit 13 detects the blind spot object 4 by analyzing the wave signal including the component of the wave arriving from the blind spot region R1 in the detection result of the radar 11 with reference to the structure information D1 (S6). By using the structure information D1, the detection of the blind spot object 4 can be performed with high accuracy.
 本実施形態の検知装置1において、制御部13は、カメラ12の検出結果に基づき構造情報D1を生成して、記憶部14に保持する(S2)。構造情報D1を逐次、生成して、死角物体4を精度良く検知することができる。 In the detection device 1 of the present embodiment, the control unit 13 generates the structure information D1 based on the detection result of the camera 12, and stores it in the storage unit 14 (S2). The blind spot object 4 can be accurately detected by sequentially generating the structure information D1.
 本実施形態の検知装置1において、制御部13は、死角物体4の検知結果に基づいて、危険度に対応する危険度指数Dを算出し(S21)、算出した危険度指数Dとしきい値Vaとを比較して、危険度を判定する(S25)。制御部13は、交差点3等の合流地点に物体が存在する場合、危険度の判定基準を緩和するようにしきい値Vaを調整する(S22,S24)。しきい値Vaの調整により、過剰な危険度の誤判定を簡単に抑制できる。 In the detection device 1 of the present embodiment, the control unit 13 calculates a risk index D corresponding to the risk based on the detection result of the blind spot object 4 (S21), and calculates the calculated risk index D and the threshold Va. And the risk is determined (S25). When an object is present at a junction such as the intersection 3 or the like, the control unit 13 adjusts the threshold value Va so as to ease the risk criterion (S22, S24). By adjusting the threshold value Va, erroneous determination of an excessive degree of risk can be easily suppressed.
 本実施形態の検知装置1において、制御部13は、検出部の検出結果に基づいて、合流地点に物体が存在するか否かを判断し(S22)、合流地点に物体が存在すると判断したとき(S22でYES)、危険度の判定基準を緩和する(S24)。当該判断により、過剰な危険度の誤判定を適確に抑制できる。 In the detection device 1 of the present embodiment, the control unit 13 determines whether or not an object exists at the junction based on the detection result of the detection unit (S22), and determines that the object exists at the junction. (YES in S22), the risk criterion is relaxed (S24). By this determination, an erroneous determination of an excessive degree of risk can be appropriately suppressed.
 本実施形態の検知装置1において、検出部は、カメラ12、レーダ11、及びナビゲーション機器15のうちの少なくとも一つを含む。各種検出部によって距離情報を検出し、自車両2の周辺監視を行うことができる。 In the detection device 1 according to the present embodiment, the detection unit includes at least one of the camera 12, the radar 11, and the navigation device 15. The distance information can be detected by the various detection units, and the periphery of the vehicle 2 can be monitored.
 本実施形態に係る移動体システムは、検知装置1と、車両制御装置20とを備える。車両制御装置20は、自車両2に搭載され、検知装置1による危険度の判定結果に応じた動作を実行する。移動体システムは、検知装置1により、自車両2の周辺環境における死角に対して物体を検知して危険度を判定する際に過剰な危険度の誤判定を抑制することができる。 移動 The mobile system according to the present embodiment includes the detection device 1 and the vehicle control device 20. The vehicle control device 20 is mounted on the host vehicle 2 and executes an operation according to the result of the determination of the degree of danger by the detection device 1. In the mobile system, the detection device 1 can suppress an erroneous determination of an excessive risk when detecting an object with respect to a blind spot in a surrounding environment of the own vehicle 2 and determining the risk.
 本実施形態に係る検知方法は、自車両2等の移動体の進路を含む周辺環境における物体を検知する方法である。本方法は、検出部が、移動体から周辺環境までの距離を示す距離情報を検出するステップS1,S2を含む。本方法は、制御部13が、検出部の検出結果に基づいて、周辺環境における死角を示す死角領域R1を検知するステップS3~S6と、死角領域R1の検知結果に基づいて、死角領域R1に関する危険度を判定するステップS7とを含む。さらに、本方法は、死角領域R1と移動体の進路とが合流する合流地点に物体が存在する場合、制御部13は、危険度の判定基準を緩和するステップS24を含む。 検 知 The detection method according to the present embodiment is a method for detecting an object in a surrounding environment including a path of a moving body such as the host vehicle 2. The method includes steps S1 and S2 in which the detection unit detects distance information indicating a distance from the moving body to the surrounding environment. The method includes steps S3 to S6 in which the control unit 13 detects a blind spot region R1 indicating a blind spot in the surrounding environment based on the detection result of the detection unit, and the control unit 13 relates to the blind spot region R1 based on the detection result of the blind spot region R1. Step S7 for determining the degree of danger. Further, the method includes a step S24 in which, when an object is present at a junction where the blind spot region R1 and the path of the mobile unit merge, the control unit 13 relaxes the risk criterion.
 本実施形態において、以上の検知方法を制御部13に実行させるためのプログラムが提供される。本実施形態の検知方法によると、自車両2等の移動体の周辺環境における死角に対して物体を検知して危険度を判定する際に過剰な危険度の誤判定を抑制することができる。 In the present embodiment, a program for causing the control unit 13 to execute the above detection method is provided. According to the detection method of the present embodiment, it is possible to suppress an erroneous determination of an excessive risk when detecting an object with respect to a blind spot in a surrounding environment of a moving object such as the host vehicle 2 and determining a risk.
(他の実施形態)
 上記の実施形態1では、死角物体4の検知に多重反射波を活用したが、多重反射波に限らず、例えば回折波が活用されてもよい。本変形例について、図13を用いて説明する。
(Other embodiments)
In the first embodiment, the multiple reflected waves are used for detecting the blind spot object 4. However, the present invention is not limited to the multiple reflected waves, and for example, a diffracted wave may be used. This modification will be described with reference to FIG.
 図13では、レーダ11からの物理信号Saが遮蔽壁31において回折し、死角物体4に到達している。また、死角物体4における反射波は、遮蔽壁31において回折し、回折波Sb2として自車両2に戻って来ている。例えば、本実施形態の制御部13は、図4のステップS4において、遮蔽壁31で回り込みを生じるように、レーダ11からの放射する物理信号Saの波長および方位を制御する。 In FIG. 13, the physical signal Sa from the radar 11 is diffracted on the shielding wall 31 and reaches the blind spot object 4. The reflected wave from the blind spot object 4 is diffracted on the shielding wall 31 and returns to the host vehicle 2 as a diffracted wave Sb2. For example, the control unit 13 of the present embodiment controls the wavelength and the azimuth of the physical signal Sa radiated from the radar 11 so that the shielding wall 31 wraps around in Step S4 of FIG.
 例えば可視光よりも波長が大きい物理信号Saを用いることによって、直進性の高い可視光等では各種の遮蔽物の存在により幾何学的に到達し得ない領域にも、信号を到達させることができる。また、死角物体4となり得る車両や人間などは通常丸みを帯びた形状をしていること等から、当該信号は完全反射的な経路だけではなく、放射された自車両2が存在する方向へも反射する。このような反射波が遮蔽壁31に対して回折現象を起こして伝搬することにより、解析対象の信号成分として回折波Sb2をレーダ11に受信させることができる。 For example, by using the physical signal Sa having a wavelength larger than that of visible light, the signal can reach even a region that cannot be reached geometrically with visible light or the like having high linearity due to the presence of various shields. . Further, since a vehicle or a person that can be the blind spot object 4 usually has a rounded shape, the signal is transmitted not only in a completely reflective path but also in a direction in which the radiated own vehicle 2 exists. reflect. Such a reflected wave causes the diffraction phenomenon to propagate to the shielding wall 31, so that the radar 11 can receive the diffracted wave Sb <b> 2 as a signal component to be analyzed.
 回折波Sb2の信号成分は死角物体4までの伝搬経路の情報と移動速度に応じたドップラー情報を有している。よって、同信号成分を信号解析することにより、実施形態1と同様に、信号成分の伝搬時間、位相及び周波数の情報から死角物体4の位置及び速度を計測可能である。この際、回折波Sb2の伝搬経路も、遮蔽壁31までの距離或いは各種の構造情報D1により、推定可能である。また、多重反射と回折が組み合わされた伝搬経路も適宜、推定でき、このような波の信号成分が解析されてもよい。 The signal component of the diffracted wave Sb2 has information on the propagation path to the blind spot object 4 and Doppler information according to the moving speed. Therefore, by analyzing the signal components, the position and velocity of the blind spot object 4 can be measured from the information on the propagation time, phase, and frequency of the signal components, as in the first embodiment. At this time, the propagation path of the diffracted wave Sb2 can also be estimated from the distance to the shielding wall 31 or various types of structural information D1. Further, a propagation path in which multiple reflection and diffraction are combined can be appropriately estimated, and a signal component of such a wave may be analyzed.
 上記の各実施形態では、レーダ11とカメラ12等とにより検出部及び測距部が別体で構成される例を説明したが、検出部及び測距部は、一体的に構成されてもよい。本変形例について、図14を用いて説明する。 In each of the above embodiments, an example has been described in which the detection unit and the distance measurement unit are separately configured by the radar 11 and the camera 12 and the like, but the detection unit and the distance measurement unit may be integrally configured. . This modification will be described with reference to FIG.
 図14は、検知装置1の変形例を説明するためのフローチャートである。実施形態1の検知装置1は、カメラ12により周辺監視を行った(図4のS1~S3)。本変形例の検知装置1は、レーダ11によって、図4のS1~S3と同様の周辺監視を行う(S1A~S3A)。 FIG. 14 is a flowchart for explaining a modification of the detection device 1. The detection device 1 according to the first embodiment monitors the periphery using the camera 12 (S1 to S3 in FIG. 4). The detection device 1 of the present modified example performs the same peripheral monitoring by the radar 11 as in S1 to S3 of FIG. 4 (S1A to S3A).
 また、本変形例において死角が発見されると(S3AでYES)、制御部13は、例えばレーダ11の帯域を切替え制御し、死角で回り込みし易い帯域を用いる(S4A)。この場合、ステップS6では回折波を活用した信号解析が行われる。一方、ステップS1A~S3Aでは、直線性が高い帯域を用いて、レーダ11の周辺監視における解像度を良くすることができる。 If a blind spot is found in the present modified example (YES in S3A), the control unit 13 performs switching control of, for example, the band of the radar 11, and uses a band that easily turns around at the blind spot (S4A). In this case, a signal analysis utilizing the diffracted wave is performed in step S6. On the other hand, in steps S1A to S3A, the resolution in monitoring the periphery of the radar 11 can be improved by using a band having high linearity.
 また、上記の各実施形態では、検出部の一例としてレーダ11、カメラ12及びナビゲーション機器15を説明した。本実施形態の検出部はこれらに限らず、例えばLIDARであってもよい。検出部から放射する物理信号Saは、例えば赤外線であってもよい。また、検出部は、ソナーであってもよく、物理信号Saとして超音波を放射してもよい。これらの場合、検出部が受信する波動信号Sbは、対応する物理信号Saと同様に設定される。 In each of the above embodiments, the radar 11, the camera 12, and the navigation device 15 have been described as examples of the detection unit. The detection unit of the present embodiment is not limited to these, and may be, for example, LIDAR. The physical signal Sa emitted from the detection unit may be, for example, infrared light. Further, the detection unit may be a sonar, and may emit an ultrasonic wave as the physical signal Sa. In these cases, the wave signal Sb received by the detection unit is set in the same manner as the corresponding physical signal Sa.
 また、上記の各実施形態では、レーダ11及びカメラ12が自車両2前方に向けて設置される例を説明したが、レーダ11等の設置位置は特に限定されない。例えば、レーダ11等は、自車両2後方に向けて配置されてもよく、例えば移動体システムは駐車支援に用いられてもよい。 In each of the above embodiments, the example in which the radar 11 and the camera 12 are installed toward the front of the vehicle 2 has been described, but the installation positions of the radar 11 and the like are not particularly limited. For example, the radar 11 and the like may be arranged toward the rear of the vehicle 2 and, for example, the mobile system may be used for parking assistance.
 また、上記の各実施形態において、検知装置1は、検出部からの物理信号Saによる波の特性を活用して、死角物体4の検知を行った。本実施形態において、死角物体4を検知する方法は、必ずしも上記の方法に限らず、各種の方法を採用してもよい。死角領域R1の中の物体4が各種の情報に基づき推定されてもよい。この場合であっても、推定結果に対して危険度の判定処理を、上記各実施形態と同様に行うことができる。 In addition, in each of the above-described embodiments, the detection device 1 detects the blind spot object 4 by utilizing the characteristics of the wave based on the physical signal Sa from the detection unit. In the present embodiment, the method of detecting the blind spot object 4 is not limited to the above method, and various methods may be adopted. The object 4 in the blind spot area R1 may be estimated based on various information. Even in this case, it is possible to perform the risk determination process on the estimation result in the same manner as in each of the above embodiments.
 また、上記の各実施形態において、検知装置1は、死角物体4の検知を行った。本実施形態の検知装置1は、死角物体4の検知を行わずに、死角に関する危険度の判定を行ってもよい。例えば、危険度の判定処理は、死角領域R1の検出結果を用いて行われてもよく、検出された死角領域R1のサイズ、形状あるいは位置関係などの各種情報に基づき適宜、危険度指数Dが算出されてもよい。この場合であっても、死角の合流地点における物体の存在に応じて危険度の判定基準を緩和することにより、危険度の誤判定を抑制できる。例えば、特に検知されていない死角物体4が仮に存在したとしても、前方車両5等により注意喚起された状態を結果的に反映して、過剰な警告等を回避できる。 In each of the above embodiments, the detection device 1 has detected the blind spot object 4. The detection device 1 of the present embodiment may determine the degree of danger related to the blind spot without detecting the blind spot object 4. For example, the risk determination process may be performed using the detection result of the blind spot region R1, and the risk index D is appropriately determined based on various information such as the size, shape, or positional relationship of the detected blind spot region R1. It may be calculated. Even in this case, erroneous determination of the degree of risk can be suppressed by relaxing the criteria for determining the degree of risk according to the presence of an object at the junction of the blind spots. For example, even if there is a blind spot object 4 that has not been particularly detected, an excessive warning or the like can be avoided by reflecting a state alerted by the preceding vehicle 5 or the like as a result.
 また、上記の各実施形態では、移動体の一例として自動車を例示した。検知装置1が搭載される移動体は、特に自動車に限定されず、例えばAGVであってもよい。例えば、検知装置1は、AGVの自動走行時に周辺監視を行い、死角中の物体を検知してもよい。 In each of the above embodiments, an automobile has been described as an example of the moving object. The moving body on which the detection device 1 is mounted is not particularly limited to an automobile, and may be, for example, an AGV. For example, the detection device 1 may monitor the periphery when the AGV automatically travels, and may detect an object in a blind spot.
(付記)
 以上のように、本開示の各種実施形態について説明したが、本開示は上記の内容に限定されるものではなく、技術的思想が実質的に同一の範囲内で種々の変更を行うことができる。以下、本開示に係る各種態様を付記する。
(Note)
As described above, various embodiments of the present disclosure have been described. However, the present disclosure is not limited to the above description, and various changes can be made within a technical idea that is substantially the same. . Hereinafter, various aspects according to the present disclosure will be additionally described.
 本開示に係る第1の態様は、移動体(2)の進路を含む周辺環境における物体を検知する検知装置である。前記検知装置は、検出部(11,12)と、制御部(13)とを備える。前記検出部は、前記移動体から前記周辺環境までの距離を示す距離情報を検出する。前記制御部は、前記検出部を制御する。前記制御部は、前記検出部の検出結果に基づいて、前記周辺環境における死角を示す死角領域を検知し(S3)、前記死角領域の検知結果に基づいて、前記死角領域に関する危険度を判定する(S7)。前記制御部は、検知された死角領域と前記移動体の進路とが合流する合流地点に物体が存在する場合、前記危険度の判定基準を緩和する(S24)。 第 A first aspect according to the present disclosure is a detection device that detects an object in a surrounding environment including a path of a moving object (2). The detection device includes a detection unit (11, 12) and a control unit (13). The detecting unit detects distance information indicating a distance from the moving body to the surrounding environment. The control unit controls the detection unit. The control unit detects a blind spot area indicating a blind spot in the surrounding environment based on the detection result of the detection unit (S3), and determines a degree of risk related to the blind spot area based on the detection result of the blind spot area. (S7). The control unit relaxes the risk criterion when an object is present at a junction where the detected blind spot area and the path of the moving body merge (S24).
 第2の態様では、第1の態様の検知装置において、前記制御部は、前記検出部の検出結果に基づいて、前記死角領域の中の物体を検知し(S6)、前記死角領域の中の物体の検知結果に応じて、前記危険度を判定する(S7)。 In a second aspect, in the detection device according to the first aspect, the control unit detects an object in the blind spot area based on a detection result of the detection unit (S6), and detects the object in the blind spot area. The risk is determined according to the detection result of the object (S7).
 第3の態様では、第2の態様の検知装置において、前記検出部は、前記移動体から前記周辺環境に、波の特性を有する物理信号を放射して、放射した物理信号の反射波に応じて前記距離情報を検出する。前記制御部は、前記検出部の検出結果において、前記死角領域から到達する波の成分を含んだ波動信号に基づいて、前記死角領域の中の物体を検知する。 In a third aspect, in the detection device according to the second aspect, the detection unit emits a physical signal having wave characteristics from the moving body to the surrounding environment, and responds to a reflected wave of the emitted physical signal. To detect the distance information. The control unit detects an object in the blind spot area based on a wave signal including a wave component arriving from the blind spot area in the detection result of the detection unit.
 第4の態様では、第3の態様の検知装置において、前記制御部は、前記周辺環境において前記死角領域を検知したとき、検知した死角領域に向けて前記物理信号を放射するように、前記検出部を制御する(S4)。 In a fourth aspect, in the detection device according to the third aspect, the control unit is configured to, when detecting the blind spot area in the surrounding environment, emit the physical signal toward the detected blind spot area. The section is controlled (S4).
 第5の態様では、第3又は第4の態様の検知装置において、前記周辺環境の物体構造を示す構造情報(D1)を記憶する記憶部(14)をさらに備える。前記制御部は、前記構造情報を参照し、前記検出部の検出結果において前記死角領域から到達する波の成分を含んだ波動信号を解析して、前記死角領域中の物体を検知する(S6)。 In a fifth aspect, the detection device according to the third or fourth aspect further includes a storage unit (14) that stores structure information (D1) indicating an object structure of the surrounding environment. The control unit refers to the structure information, analyzes a wave signal including a wave component arriving from the blind spot area in a detection result of the detection unit, and detects an object in the blind spot area (S6). .
 第6の態様では、第2~第5のいずれかの態様の検知装置において、前記制御部は、前記死角領域の中の物体の検知結果に基づいて、前記危険度に対応する危険度指数(D)を算出し(S21)、算出した危険度指数としきい値とを比較して、前記危険度を判定する(S25)。前記制御部は、前記合流地点に物体が存在する場合、前記危険度の判定基準を緩和するように前記しきい値を調整する(S22,S24)。 In a sixth aspect, in the detection device according to any one of the second to fifth aspects, the control unit is configured to determine a risk index corresponding to the risk based on a detection result of an object in the blind spot area ( D) is calculated (S21), and the calculated risk index is compared with a threshold to determine the risk (S25). When an object is present at the junction, the control unit adjusts the threshold so as to ease the risk criterion (S22, S24).
 第7の態様では、第1~第6のいずれかの態様の検知装置において、前記制御部は、前記検出部の検出結果に基づいて、前記合流地点に物体が存在するか否かを判断し、前記合流地点に物体が存在すると判断したとき、前記危険度の判定基準を緩和する。 In a seventh aspect, in the detection device according to any one of the first to sixth aspects, the control unit determines whether an object is present at the junction based on a detection result of the detection unit. When it is determined that an object is present at the junction, the criterion for determining the degree of risk is relaxed.
 第8の態様では、第1~第7のいずれかの態様の検知装置において、前記検出部は、カメラ、レーダ、LIDAR、及びナビゲーション機器のうちの少なくとも一つを含む。 In an eighth aspect, in the detection device according to any one of the first to seventh aspects, the detection unit includes at least one of a camera, a radar, a LIDAR, and a navigation device.
 第9の態様は、第1~第8のいずれかの態様の検知装置と、制御装置(20)とを備える移動体システムである。前記制御装置は、前記移動体に搭載され、前記検知装置による前記危険度の判定結果に応じた動作を実行する。 9A ninth aspect is a mobile system including the detection device according to any one of the first to eighth aspects, and a control device (20). The control device is mounted on the moving body and performs an operation according to a result of the determination of the degree of risk by the detection device.
 第10の態様は、移動体(2)の進路を含む周辺環境における物体を検知する検知方法である。本方法は、検出部が、前記移動体から前記周辺環境までの距離を示す距離情報を検出するステップ(S1,S2)を含む。本方法は、制御部(13)が、前記検出部の検出結果に基づいて、前記周辺環境における死角を示す死角領域(R1)を検知するステップ(S3)と、前記死角領域の検知結果に基づいて、前記死角領域に関する危険度を判定するステップ(S7)とを含む。さらに、本方法は、前記死角領域と前記移動体の進路とが合流する合流地点に物体が存在する場合、前記制御部は、前記危険度の判定基準を緩和するステップ(S24)を含む。 10A tenth aspect is a detection method for detecting an object in a surrounding environment including a path of a moving object (2). The method includes a step of detecting distance information indicating a distance from the moving object to the surrounding environment (S1, S2). In the method, a control unit (13) detects a blind spot region (R1) indicating a blind spot in the surrounding environment based on a detection result of the detection unit (S3), and based on the detection result of the blind spot region. (S7) determining the degree of risk related to the blind spot area. Further, the method includes a step (S24) of relaxing the risk criterion when an object is present at a junction where the blind spot area and the path of the mobile unit merge.
 第11の態様は、第10の態様の検知方法を制御部に実行させるためのプログラムである。 An eleventh aspect is a program for causing a control unit to execute the detection method according to the tenth aspect.
  1  検知装置
  11  レーダ
  12  カメラ
  13  制御部
  14  記憶部
  15  ナビゲーション機器
  2  自車両
  20  車両制御装置
Reference Signs List 1 detection device 11 radar 12 camera 13 control unit 14 storage unit 15 navigation device 2 own vehicle 20 vehicle control device

Claims (11)

  1.  移動体の進路を含む周辺環境における物体を検知する検知装置であって、
     前記移動体から前記周辺環境までの距離を示す距離情報を検出する検出部と、
     前記検出部を制御する制御部とを備え、
     前記制御部は、
      前記検出部の検出結果に基づいて、前記周辺環境における死角を示す死角領域を検知し、
      前記死角領域の検知結果に基づいて、前記死角領域に関する危険度を判定し、
     前記制御部は、検知された死角領域と前記移動体の進路とが合流する合流地点に物体が存在する場合、前記危険度の判定基準を緩和する
    検知装置。
    A detection device for detecting an object in a surrounding environment including a path of a moving body,
    A detection unit that detects distance information indicating a distance from the moving body to the surrounding environment,
    A control unit for controlling the detection unit,
    The control unit includes:
    Based on the detection result of the detection unit, detects a blind spot area indicating a blind spot in the surrounding environment,
    Based on the detection result of the blind spot area, determine the degree of risk related to the blind spot area,
    The detection device, wherein the control unit relaxes the risk criterion when an object is present at a junction where the detected blind spot area and the path of the moving body merge.
  2.  前記制御部は、
     前記検出部の検出結果に基づいて、前記死角領域の中の物体を検知し、
     前記死角領域の中の物体の検知結果に応じて、前記危険度を判定する
    請求項1に記載の検知装置。
    The control unit includes:
    Based on the detection result of the detection unit, detects an object in the blind spot area,
    The detection device according to claim 1, wherein the degree of danger is determined based on a detection result of an object in the blind spot area.
  3.  前記検出部は、前記移動体から前記周辺環境に、波の特性を有する物理信号を放射して、放射した物理信号の反射波に応じて前記距離情報を検出し、
     前記制御部は、前記検出部の検出結果において、前記死角領域から到達する波の成分を含んだ波動信号に基づいて、前記死角領域の中の物体を検知する
    請求項2に記載の検知装置。
    The detection unit emits a physical signal having wave characteristics from the moving body to the surrounding environment, and detects the distance information according to a reflected wave of the emitted physical signal,
    The detection device according to claim 2, wherein the control unit detects an object in the blind spot area based on a wave signal including a component of a wave arriving from the blind spot area in a detection result of the detection unit.
  4.  前記制御部は、前記周辺環境において前記死角領域を検知したとき、検知した死角領域に向けて前記物理信号を放射するように、前記検出部を制御する
    請求項3に記載の検知装置。
    4. The detection device according to claim 3, wherein when detecting the blind spot area in the surrounding environment, the control unit controls the detection unit to emit the physical signal toward the detected blind spot area. 5.
  5.  前記周辺環境の物体構造を示す構造情報を記憶する記憶部をさらに備え、
     前記制御部は、前記構造情報を参照し、前記検出部の検出結果において前記死角領域から到達する波の成分を含んだ波動信号を解析して、前記死角領域中の物体を検知する
    請求項3又は4に記載の検知装置。
    Further comprising a storage unit that stores structure information indicating the object structure of the surrounding environment,
    The said control part detects the object in the said blind spot area | region by analyzing the wave signal containing the component of the wave which arrives from the said blind spot area | region in the detection result of the said detection part with reference to the said structure information. Or the detection device according to 4.
  6.  前記制御部は、
     前記死角領域の中の物体の検知結果に基づいて、前記危険度に対応する危険度指数を算出し、
     算出した危険度指数としきい値とを比較して、前記危険度を判定し、
     前記制御部は、前記合流地点に物体が存在する場合、前記危険度の判定基準を緩和するように前記しきい値を調整する
    請求項2~5のいずれか1項に記載の検知装置。
    The control unit includes:
    Based on the detection result of the object in the blind spot area, calculate a risk index corresponding to the risk,
    By comparing the calculated risk index and the threshold, the risk is determined,
    The detection device according to any one of claims 2 to 5, wherein the control unit adjusts the threshold value so as to ease the risk criterion when an object is present at the junction.
  7.  前記制御部は、前記検出部の検出結果に基づいて、前記合流地点に物体が存在するか否かを判断し、
     前記合流地点に物体が存在すると判断したとき、前記危険度の判定基準を緩和する
    請求項1~6のいずれか1項に記載の検知装置。
    The control unit determines whether an object is present at the junction based on a detection result of the detection unit,
    The detection device according to any one of claims 1 to 6, wherein when it is determined that an object is present at the junction, the criterion for determining the degree of risk is relaxed.
  8.  前記検出部は、レーダ、LIDAR、カメラ及びナビゲーション機器のうちの少なくとも一つを含む
    請求項1~7のいずれか1項に記載の検知装置。
    The detection device according to any one of claims 1 to 7, wherein the detection unit includes at least one of a radar, a LIDAR, a camera, and a navigation device.
  9.  請求項1~8のいずれか1項に記載の検知装置と、
     前記移動体に搭載され、前記検知装置による前記危険度の判定結果に応じた動作を実行する制御装置と
    を備える移動体システム。
    A detection device according to any one of claims 1 to 8,
    And a control device mounted on the moving body and performing an operation according to a result of the determination of the degree of risk by the detection device.
  10.  移動体の進路を含む周辺環境における物体を検知する検知方法であって、
     検出部が、前記移動体から前記周辺環境までの距離を示す距離情報を検出するステップと、
     制御部が、前記検出部の検出結果に基づき、前記周辺環境における死角を示す死角領域を検知するステップと、
     前記制御部が、前記死角領域の検知結果に基づいて、前記死角領域に関する危険度を判定するステップとを含み、さらに
     前記死角領域と前記移動体の進路とが合流する合流地点に物体が存在する場合、前記制御部は、前記危険度の判定基準を緩和するステップを含む
    検知方法。
    A detection method for detecting an object in a surrounding environment including a path of a moving object,
    Detecting a distance information indicating a distance from the moving body to the surrounding environment,
    A control unit that detects a blind spot area indicating a blind spot in the surrounding environment based on a detection result of the detection unit;
    The control unit determines a degree of risk related to the blind spot area based on the detection result of the blind spot area, and furthermore, an object is present at a junction where the blind spot area and the path of the moving body join. In this case, the control unit includes a step of relaxing the risk criterion.
  11.  請求項10に記載の検知方法を制御部に実行させるためのプログラム。 A program for causing a control unit to execute the detection method according to claim 10.
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