Object detection device

Abstract

To provide an object detection device capable of suppressing the overlook of an obstacle and improving the accuracy of obstacle detection.SOLUTION: An object detection device detects an obstacle present in the vicinity of a moving body based on time-series changes in the intensity of a reflected wave generated when a transmission wave transmitted from the moving body is reflected by an object. The object detection device includes a threshold calculation unit that calculates a variable threshold that varies in accordance with the movement of the moving body based on a moving average value of the intensity of the reflected wave, and a determination unit that determines the presence or absence of an obstacle based on whether the intensity of the reflected wave is greater than the variable threshold. The threshold calculation unit calculates a smoothed moving average value by smoothing the current moving average value based on at least one past moving average value, and calculates the variable threshold based on the smoothed moving average value.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to an object detection device. [Background technology]

[0002] In moving bodies such as vehicles, object detection devices are used to detect obstacles present around the moving bodies based on information such as TOF (Time Of Flight) and Doppler shift obtained by transmitting and receiving ultrasonic waves, etc. In such object detection devices, CFAR (Constant False Alarm Rate) processing is used as a technique for suppressing the influence of noise caused by reflected waves from objects that are not the detection target (e.g., road surfaces, etc.). According to CFAR processing, a threshold value for determining whether an object that reflects a reflected wave is an obstacle or not is optimized according to the condition of the road surface, etc., based on a moving average value of the intensity of the reflected wave that changes over time. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2016-206011 A Summary of the Invention [Problem to be solved by the invention]

[0004] Although the above-mentioned CFAR processing can basically reduce the influence of noise and improve the accuracy of obstacle detection, the detection accuracy may decrease depending on the situation. For example, when an obstacle is present within the detection range, the moving average value of the strength of the reflected wave increases, so the threshold value set by the CFAR processing becomes higher, and the possibility of overlooking the obstacle increases.

[0005] The present invention has been made in view of the above, and provides an object detection device that can suppress overlooking of an obstacle and improve the accuracy of obstacle detection. [Means for solving the problem]

[0006] One aspect of the present invention is an object detection device that detects obstacles present in the vicinity of a moving body based on time-series changes in the intensity of a reflected wave generated when a transmission wave transmitted from the moving body is reflected by an object, and includes a threshold calculation unit that calculates a variable threshold that varies in accordance with the movement of the moving body based on a moving average value of the intensity of the reflected wave, and a judgment unit that judges the presence or absence of an obstacle based on whether the intensity of the reflected wave is greater than the variable threshold, and the threshold calculation unit calculates a smoothed moving average value by smoothing the current moving average value based on at least one past moving average value, and calculates the variable threshold value based on the smoothed moving average value. Effect of the Invention

[0007] According to the present invention, it is possible to provide an object detection device that is capable of suppressing overlooking of an obstacle and improving the accuracy of obstacle detection. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a vehicle according to the first embodiment. [Diagram 2] FIG. 2 is a diagram showing an example of the configuration of the vehicle control system according to the first embodiment. [Diagram 3] FIG. 3 is a diagram showing an example of a distance calculation method using the TOF method according to the first embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a functional configuration of the object detection device according to the first embodiment. [Diagram 5] FIG. 5 is a diagram illustrating an example of a functional configuration included in the threshold calculation unit according to the first embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a process for calculating a CFAR threshold value according to the first embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of a relationship between a current moving average value and a past moving average value according to the first embodiment. [Figure 8]FIG. 8 is a diagram illustrating an example of a CFAR threshold value based on a current moving average value according to the first embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a CFAR threshold value based on a smooth moving average value according to the first embodiment. [Figure 10] FIG. 10 is a flowchart showing an example of processing in the object detection device of the first embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of the relationship between the CFAR threshold based on the current moving average value and the fixed threshold according to the first embodiment. [Figure 12] FIG. 12 is a flowchart showing an example of processing in the object detection device according to the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. The configuration of the embodiment described below and the actions and effects brought about by the configuration are merely examples, and the present invention is not limited to the following description.

[0010] (First embodiment) 1 is a diagram showing an example of the configuration of a vehicle 1 according to the first embodiment. The vehicle 1 is an example of a moving body on which an object detection device according to the present embodiment is mounted. The object detection device according to the present embodiment is a device that detects obstacles present around the vehicle 1 based on information such as TOF (Time Of Flight) and Doppler shift acquired by transmitting and receiving ultrasonic waves.

[0011] The object detection device according to this embodiment includes a plurality of transceivers 21A-21L. Hereinafter, when there is no need to distinguish between the plurality of transceivers 21A-21L, they may be referred to as transceivers 21. Each transceiver 21 is installed on a vehicle body 2 serving as the exterior of a vehicle 1, transmits ultrasonic waves toward the outside of the vehicle body 2, and receives ultrasonic waves generated when the ultrasonic waves are reflected by an object present outside the vehicle body 2. Hereinafter, ultrasonic waves transmitted from the transceiver 21 may be referred to as a transmission wave, and ultrasonic waves generated when the transmission wave is reflected by an object may be referred to as a reflected wave.

[0012] 1, four transceivers 21A-21D are arranged at the front end of the vehicle body 2, four transceivers 21E-21H are arranged at the rear end, two transceivers 21I, 21J are arranged on the right side, and two transceivers 21K, 21L are arranged on the left side. Note that the number and installation positions of the transceivers 21 are not limited to this example.

[0013] 2 is a diagram showing an example of the configuration of the vehicle control system 10 according to the first embodiment. The vehicle control system 10 performs processing for controlling the vehicle 1 based on information output from an object detection device 11. The vehicle control system 10 according to this embodiment includes the object detection device 11 and an ECU 12.

[0014] The object detection device 11 includes a plurality of transmitting / receiving units 21 and a control unit 22. Each transmitting / receiving unit 21 includes a transducer 31 configured using a piezoelectric element or the like, an amplifier, etc., and realizes transmission and reception of ultrasonic waves by the vibration of the transducer 31. Specifically, each transmitting / receiving unit 21 transmits ultrasonic waves generated in response to the vibration of the transducer 31 as a transmission wave, and detects the vibration of the transducer 31 caused by the reflected wave of the transmission wave reflected by an object such as an obstacle O or a road surface G. The obstacle O is an object to be detected among objects present around the vehicle 1, and may be, for example, another vehicle, a road accessory, a wall, a person, a curb, a car stop, etc. The vibration of the transducer 31 is converted into an electric signal, and based on the electric signal, a TOF corresponding to the distance from the transmitting / receiving unit 21 to the obstacle O, a Doppler shift corresponding to the relative speed between the vehicle 1 and the obstacle O, etc. can be obtained.

[0015] 2, a configuration is illustrated in which both transmission of the transmission wave and reception of the reflected wave are performed using a single transducer 31, but the configuration of the transceiver unit 21 is not limited to this. For example, the transmission side and the reception side may be separated, such as a configuration in which a transducer for transmitting the transmission wave and a transducer for receiving the reflected wave are separately provided.

[0016] The control unit 22 includes an input / output device 41, a storage device 42, and a processor 43. The input / output device 41 is an interface device that enables transmission and reception of information between the control unit 22 and external devices (the transmission / reception unit 21, the ECU 12, etc.). The storage device 42 includes a main storage device such as a read only memory (ROM) and a random access memory (RAM), and an auxiliary storage device such as a hard disk drive (HDD) and a solid state drive (SSD). The processor 43 is an integrated circuit that executes various processes for realizing the functions of the control unit 22, and may be configured using, for example, a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), etc. that operate according to a program. The processor 43 executes various arithmetic processes and control processes by reading and executing the programs stored in the storage device 42.

[0017] The ECU 12 is a unit that executes various processes for controlling the vehicle 1 based on information acquired from the object detection device 11 and the like. The ECU 12 has an input / output device 51, a storage device 52, and a processor 53. The input / output device 51 is an interface device that enables transmission and reception of information between the ECU 12 and external mechanisms (such as the object detection device 11, the drive mechanism, the braking mechanism, the steering mechanism, the transmission mechanism, the in-vehicle display, the speaker, and various sensors). The storage device 52 includes a main storage device such as a ROM or RAM, and an auxiliary storage device such as an HDD or SSD. The processor 53 is an integrated circuit that executes various processes for realizing the functions of the ECU 12, and may be configured using, for example, a CPU, an ASIC, an FPGA, or the like. The processor 53 reads out a program stored in the storage device 52 and executes various arithmetic processes and control processes.

[0018] Fig. 3 is a diagram showing an example of a method for calculating distance using the TOF method according to the first embodiment. Fig. 3 illustrates an envelope curve L indicating a change over time in the intensity (signal level) of ultrasonic waves transmitted and received by the transmitting and receiving unit 21. In the graph shown in Fig. 3, the horizontal axis corresponds to time (TOF), and the vertical axis corresponds to the intensity of ultrasonic waves transmitted and received by the transmitting and receiving unit 21 (the magnitude of vibration of the transducer 31).

[0019] The envelope curve L indicates the change over time in the strength indicating the magnitude of the vibration of the oscillator 31. From the envelope curve L illustrated in Fig. 3, it can be seen that the oscillator 31 is driven to vibrate for a period of time Ta from timing t0, and the transmission of the transmission wave is completed at timing t1, and then the vibration of the oscillator 31 due to inertia continues while attenuating for a period of time Tb until timing t2. Therefore, in the graph shown in Fig. 3, the period of time Tb corresponds to the so-called reverberation time.

[0020] The envelope L reaches a peak at a time t4, which is a time Tp after the time t0 when the transmission of the transmission wave starts, at which the magnitude of the vibration of the vibrator 31 reaches or exceeds a threshold value Th. This threshold value Th is a value that is set to distinguish whether the vibration of the vibrator 31 is caused by the reception of a reflected wave from the obstacle O or the reception of a reflected wave from an object other than the obstacle O (e.g., the road surface G, etc.). Note that although the threshold value Th is shown here as a constant value, the threshold value Th may be a variable value that changes depending on the situation. Vibrations having a peak equal to or greater than the threshold value Th can be considered to be caused by the reception of a reflected wave from the obstacle O.

[0021] In this example, the envelope curve L indicates that the vibration of the transducer 31 is attenuated after the timing t4. Therefore, the timing t4 corresponds to the timing at which the reception of the reflected wave from the obstacle O is completed, in other words, the timing at which the transmission wave finally transmitted at the timing t1 returns as a reflected wave.

[0022] Furthermore, in the envelope L, timing t3 as the start point of the peak at timing t4 corresponds to the timing at which reception of the reflected wave from the obstacle O begins, in other words, the timing at which the transmission wave first transmitted at timing t0 returns as a reflected wave. Therefore, the time ΔT between timing t3 and timing t4 is equal to the time Ta as the transmission time of the transmission wave.

[0023] From the above, in order to use TOF to find the distance from the transmitting / receiving unit 21, which is the source of transmitting and receiving ultrasonic waves, to the obstacle O, it is necessary to find the time Tf between the timing t0 when the transmission of the transmitted wave begins and the timing t3 when the reflected wave begins to be received. This time Tf can be found by subtracting the time ΔT, which is equal to the time Ta as the transmission time of the transmitted wave, from the time Tp, which is the difference between the timing t0 and the timing t4 when the intensity of the reflected wave reaches a peak by exceeding the threshold value Th.

[0024] The timing t0 when the transmission wave starts to be transmitted can be easily identified as the timing when the object detection device 200 starts to operate, and the time Ta as the transmission time of the transmission wave is determined in advance by settings, etc. Therefore, by identifying the timing t4 when the intensity of the reflected wave reaches a peak and exceeds the threshold value Th, the distance from the vehicle 1 (the transceiver unit 21 which is the source of transmission and reception of the ultrasonic waves) to the obstacle O can be obtained. Note that the above calculation method is merely an example, and the distance from the vehicle 1 to the obstacle O may be calculated by appropriately using a known or new method.

[0025] Fig. 4 is a diagram showing an example of the functional configuration of the object detection device 11 according to the first embodiment. The object detection device 11 (control unit 22) according to this embodiment includes an echo information generation unit 101, a threshold calculation unit 102, a determination unit 103, and an output unit 104. These functional units can be realized, for example, by cooperation between hardware and software (programs, etc.) of the object detection device 11 as shown in Fig. 2. Furthermore, at least a part of these functional units may be realized by dedicated hardware (circuits).

[0026] The echo information generating unit 101 generates echo information indicating a time-series change in the intensity of the reflected wave based on information acquired from the transmitting / receiving unit 21. The echo information may include, for example, data of an envelope L as illustrated in FIG.

[0027] The threshold calculation unit 102 performs CFAR processing on the echo information to calculate a CFAR threshold (an example of a variable threshold) that varies in accordance with the movement of the vehicle 1. The threshold calculation unit 102 calculates a moving average value of the intensity of the reflected wave based on the echo information, and calculates a CFAR threshold value based on the moving average value. The method of calculating the CFAR threshold value will be described later.

[0028] The determination unit 103 determines whether or not an obstacle exists around the vehicle 1 based on the echo information and the CFAR threshold calculated by the threshold calculation unit 102. In this embodiment, the determination unit 103 determines that an obstacle exists when the intensity of the reflected wave is greater than the CFAR threshold. When the determination unit 103 determines that an obstacle exists, it generates obstacle information related to the obstacle. The obstacle information may include, for example, the distance from the vehicle 1 (transmission / reception unit 21) to the obstacle, the relative speed of the obstacle, and the like.

[0029] The output unit 104 outputs the obstacle information generated by the determination unit 103 to a predetermined mechanism (eg, the ECU 12, etc.).

[0030] The threshold calculation unit 102 of this embodiment calculates a smoothed moving average value by smoothing the current moving average value based on at least one past moving average value, and calculates a CFAR threshold value based on the smoothed moving average value.

[0031] 5 is a diagram showing an example of a functional configuration included in the threshold calculation unit 102 according to the first embodiment. The threshold calculation unit 102 according to the present embodiment includes a moving average calculation unit 201, a storage unit 202, a smoothing processing unit 203, and an adjustment processing unit 204.

[0032] The moving average calculation unit 201 calculates a moving average value of the intensity of the reflected wave based on echo information indicating a time series change in the intensity of the reflected wave. The moving average calculation unit 201 calculates the moving average value, for example, for each predetermined detection cycle. The detection cycle is a period from when a transmission wave is transmitted once to when a reflected wave of the transmission wave is awaited to be received.

[0033] The storage unit 202 stores the moving average value calculated by the moving average calculation unit 201 for each detection period. That is, the storage unit 202 stores a plurality of past moving average values ​​in chronological order.

[0034] The smoothing processing unit 203 executes a smoothing process for smoothing the current moving average value calculated by the moving average calculation unit 201, based on at least one past moving average value stored in the storage unit 202. The specific method of the smoothing process should be appropriately determined depending on the usage situation, etc., but may be, for example, a process for calculating the average value of the current moving average value and at least one past moving average value as a smoothed moving average value.

[0035] The adjustment processing unit 204 calculates a CFAR threshold by performing a predetermined adjustment process on the smoothed moving average value calculated by the smoothing processing unit 203. The adjustment process can be, for example, a multiplication process or an addition process. The integration process is a process of integrating a predetermined constant with respect to the moving average value (the smoothed moving average value in this embodiment). The addition process is a process of adding a predetermined constant with respect to the moving average value.

[0036] FIG. 6 is a diagram showing an example of a process for calculating a CFAR threshold value according to the first embodiment. In the process illustrated here, first, a received signal indicating the intensity of a reflected wave is sampled at a predetermined time interval. Then, a first sum Σ1 is calculated, which is a sum of the intensity values ​​of the reflected wave received in a first period Δt1 before a certain detection timing t for a number N of samples. Also, a second sum Σ2 is calculated, which is a sum of the intensity values ​​of the reflected wave received in a second period Δt2 after the detection timing t for a number N of samples. Then, the sum Σ of the first sum Σ1 and the second sum Σ2 is divided by 2N, which is the sum of the number N of samples in the first period Δt1 and the number N of samples in the second period Δt2, to calculate a current moving average value (moving average value corresponding to the detection timing t).

[0037] Then, a smoothed moving average value is calculated by smoothing the current moving average value based on the current moving average value and at least one past moving average value (a moving average value corresponding to a detection timing prior to the detection timing t). The smoothed moving average value may be, for example, an average value of the current moving average value and the past moving average value. A CFAR threshold value is then calculated by performing a predetermined integration process, addition process, or the like on the smoothed moving average value. Then, based on a difference signal indicating the difference between the CFAR threshold value and the intensity value I of the reflected wave corresponding to the detection timing t, it is determined whether or not an obstacle is present at the distance corresponding to the detection timing t.

[0038] The current method of calculating the moving average value is not limited to the above. For example, in the above description, the CA (Cell Averaging)-CFAR process is described in which the average value of all intensity values ​​corresponding to periods Δt1 and Δt2 before and after the detection timing t is used as the moving average value, but the CFAR threshold Thc may be calculated by GO (Greatest Of)-CFAR process, SO (Smallest Of)-CFAR process, or the like. The GO-CFAR process is a process in which the moving average value is calculated using the larger value of the first sum Σ1 and the second sum Σ2. The SO-CFAR process is a process in which the moving average value is calculated using the smaller value of the first sum Σ1 and the second sum Σ2.

[0039] Fig. 7 is a diagram showing an example of the relationship between the current moving average value Ac and past moving average values ​​Ap1, Ap2 according to the first embodiment. Fig. 7 illustrates the current moving average value Ac, the previous moving average value Ap1 (an example of the past moving average value), and the moving average value before last Ap2 (an example of the past moving average value).

[0040] The current moving average value Ac is the moving average value (moving average line) of the envelope Lc corresponding to the current detection cycle. The previous moving average value Ap1 is the moving average value of the envelope Lp1 corresponding to the detection cycle prior to the current detection cycle (e.g., one cycle prior). The moving average value before previous Ap2 is the moving average value of the envelope Lp2 corresponding to the detection cycle prior to the detection cycle corresponding to the previous moving average value Ap1 (e.g., two cycles prior to the current detection cycle). Note that, although an example is shown here in which two moving average values ​​are used as the past moving average values, three or more past moving average values ​​may be used.

[0041] In FIG. 7, the peak Pc in the current envelope Lc, the peak Pp1 in the previous envelope Lp1, and the peak Pp2 in the envelope Lp2 before last are caused by the same obstacle. That is, it is shown that the obstacle was at a distance Dp2 in the detection cycle before last, at a distance Dp1 in the previous detection cycle, and at a distance Dc in the current detection cycle (Dc <Dp1<Dp2)。

[0042] In such a case, as shown in Fig. 7, the height (intensity) of each of the peaks Pc, Pp1, and Pp2 caused by the obstacle increases as the distance from the vehicle 1 to the obstacle decreases. Therefore, the influence of the reflected wave from the obstacle on the current moving average value Ac is greater than the influence of the past moving average values ​​Ap1 and Ap2. Therefore, when an obstacle is present, the current moving average value Ac is likely to be higher than the past moving average values ​​Ap1 and Ap2 due to the influence of the reflected wave from the obstacle.

[0043] Fig. 8 is a diagram showing an example of a CFAR threshold Th based on the current moving average value Ac according to the first embodiment. As shown in Fig. 8, the CFAR threshold Th based on the current moving average value Ac that has not been subjected to smoothing processing is set high due to being strongly affected by the reflected wave from an obstacle. In such a case, a peak Pc appearing in the envelope curve Lc due to an obstacle is unlikely to exceed the CFAR threshold Th, so that the obstacle is more likely not to be detected.

[0044] Therefore, in this embodiment, a smoothed moving average value is calculated by smoothing the current moving average value Ac based on the past moving average values ​​Ap1 and Ap2, and a CFAR threshold value is calculated based on the smoothed moving average value.

[0045] 9 is a diagram showing an example of a CFAR threshold value Ths based on a smoothed moving average value As according to the first embodiment. The smoothed moving average value As illustrated here is an average value of the current moving average value Ac, the previous moving average value Ap1, and the moving average value Ap2 before the previous one illustrated in FIG.

[0046] As shown in Fig. 9, the smoothed moving average value As is smoothed more than the current moving average value Ac (see Fig. 8) by reducing the influence of peaks Pc that appear in the envelope Lc due to obstacles. This makes it possible to avoid setting the CFAR threshold value Ths calculated based on the smoothed moving average value As excessively high, thereby reducing the possibility of overlooking an obstacle.

[0047] 10 is a flowchart showing an example of processing in the object detection device 11 of the first embodiment. In step S101, the transmitter / receiver 21 starts transmitting and receiving ultrasonic waves, and in step S102, the echo information generator 101 generates echo information indicating a time-series change in intensity of a reflected wave from an object present around the vehicle 1.

[0048] In step S103, the threshold calculation unit 102 calculates the current moving average value Ac based on the echo information. In step S104, the threshold calculation unit 102 calculates a smoothed moving average value As based on the current moving average value Ac and the past moving average values ​​Ap1 and Ap2. In step S105, the threshold calculation unit 102 calculates a CFAR threshold value Ths based on the smoothed moving average value As.

[0049] In step S106, the determination unit 103 determines whether the current strength of the reflected wave is equal to or greater than the CFAR threshold Ths. In step S106, if the strength of the reflected wave is not equal to or greater than the CFAR threshold Ths (S106: No), the determination unit 103 determines that no obstacle is present, and this routine ends. In step S106, if the strength of the reflected wave is equal to or greater than the CFAR threshold Ths (S106: Yes), the determination unit 103 determines that an obstacle is present and generates obstacle information related to the obstacle, and in step S207, the output unit 104 outputs the obstacle information to a mechanism such as the ECU 12.

[0050] As described above, according to this embodiment, the CFAR threshold Ths is set based on the smoothed moving average value As smoothed using the past moving average values ​​Ap1 and Ap2, so it is possible to avoid setting the CFAR threshold too high due to the influence of reflected waves from obstacles, etc. This makes it possible to suppress overlooking of obstacles and improve the accuracy of obstacle detection.

[0051] Other embodiments will be described below with reference to the drawings, but descriptions of parts that are the same as or similar to the first embodiment will be omitted as appropriate.

[0052] Second embodiment The object detection device 11 according to the second embodiment differs from the first embodiment in that when the CFAR threshold Th based on the current moving average value Ac is greater than a predetermined fixed threshold, the object detection device 11 calculates a smoothed moving average value Ths based on at least one of the past moving average values ​​Ap1, Ap2 without using the current moving average value Ac.

[0053] FIG. 11 is a diagram showing an example of the relationship between the CFAR threshold value Th based on the current moving average value Ac according to the first embodiment and the fixed threshold value Th0. The fixed threshold value Th0 illustrated here is a fixed value uniquely determined for the distance from the vehicle 1. The fixed threshold value Th0 may be stored in advance in an appropriate storage device (e.g., the storage device 42, etc.) mounted on the vehicle 1. A specific setting method for the fixed threshold value Th0 should be appropriately determined according to the specifications of the vehicle 1 and the performance of the transceiver unit 21, etc., but the fixed threshold value Th0 may be set, for example, based on a statistical value (e.g., a lower limit value, an average value, etc.) of the intensity of the reflected wave from an obstacle for each distance. Since the intensity of the reflected wave from an obstacle decreases as the distance from the vehicle 1 increases, the fixed threshold value Th0 is usually set to decrease as the distance from the vehicle 1 increases. Note that, although the fixed threshold value Th0 that decreases linearly as the distance increases is illustrated here, the form of the fixed threshold value Th0 is not limited thereto.

[0054] 11 illustrates a state in which a part of the CFAR threshold value Th based on the current moving average value Ac is larger than the fixed threshold value Th0. In such a case, in this embodiment, the smoothed moving average value Ths (see FIG. 9) is calculated based on at least one past moving average value without using the current moving average value Ac. A specific calculation method of the smoothed moving average value Ths in this case may be appropriately determined according to the usage situation, etc., and for example, the average value of a plurality of past moving average values ​​(for example, past moving average values ​​Ap1, Ap2, etc. illustrated in FIG. 7) may be set as the smoothed moving average value Ths, or one past moving average value selected from a plurality of past moving average values ​​may be set as the smoothed moving average value Ths.

[0055] 12 is a flowchart showing an example of processing in the object detection device 11 according to the second embodiment. In step S201, the transmitter / receiver 21 starts transmitting and receiving ultrasonic waves, and in step S202, the echo information generator 101 generates echo information indicating a time-series change in intensity of a reflected wave from an object present around the vehicle 1.

[0056] In step S203, the threshold calculation unit 102 calculates the current moving average value Ac based on the echo information. In step S204, the threshold calculation unit 102 calculates the CFAR threshold value Th based on the current moving average value Ac. In step S205, the threshold calculation unit 102 determines whether the CFAR threshold value Th based on the current moving average value Ac is greater than a fixed threshold value Th0.

[0057] In step S205, if the CFAR threshold Th based on the current moving average value Ac is not greater than the fixed threshold value Th0 (S205: No), in step S206, the threshold calculation unit 102 calculates the smoothed moving average value As based on the current moving average value Ac and the past moving average values ​​Ap1 and Ap2.

[0058] In step S205, if the CFAR threshold Th based on the current moving average value Ac is greater than the fixed threshold value Th0 (S205: Yes), in step S207, the threshold calculation unit 102 calculates the smoothed moving average value As based on the past moving average values ​​Ap1 and Ap2 without using the current moving average value Ac. The method of calculating the smoothed moving average value As based on the past moving average values ​​Ap1 and Ap2 may be appropriately determined depending on the usage situation, etc., and for example, the average value of multiple past moving average values ​​Ap1 and Ap2 may be used as the smoothed moving average value As, or one past moving average value selected from multiple past moving average values ​​(for example, either one of the past moving average values ​​Ap1 or Ap2) may be used as the smoothed moving average value As.

[0059] In step S208, the threshold calculation unit 102 calculates a smoothed CFAR threshold Ths based on the smoothed moving average value As calculated in step S206 or step S207. In step S209, the judgment unit 103 judges whether or not the current intensity of the reflected wave is equal to or greater than the smoothed CFAR threshold Ths. In step S209, if the intensity of the reflected wave is not equal to or greater than the smoothed CFAR threshold Ths (S209: No), the judgment unit 103 judges that no obstacle is present, and this routine ends. In step S209, if the intensity of the reflected wave is equal to or greater than the smoothed CFAR threshold Ths (S209: Yes), in step S210, the judgment unit 103 judges that an obstacle is present and generates obstacle information related to the obstacle, and the output unit 104 outputs the obstacle information to a mechanism such as the ECU 12.

[0060] As described above, according to this embodiment, when the CFAR threshold Th based on the current moving average value Ac is greater than the predetermined fixed threshold value Th0, the smoothed moving average value As is calculated based on at least one of the past moving average values ​​Ap1, Ap2 without using the current moving average value Ac. Then, the presence or absence of an obstacle is determined based on the CFAR threshold value Ths calculated based on the smoothed moving average value As. This makes it possible to exclude the current moving average value Ac, which is strongly influenced by the reflected waves from the obstacle, from the elements for calculating the smoothed moving average value As, and to more appropriately set the CFAR threshold value Ths.

[0061] (Modification) In the above-described embodiment, an example has been given of a configuration in which ultrasonic waves are used as the waves transmitted and received to detect an obstacle, but the configuration of the object detection device is not limited to this. For example, a millimeter wave radar, a LiDAR (Light Detection And Ranging) sensor, or the like may be used.

[0062] Furthermore, the threshold calculation unit 102 (smoothing processing unit 203) may limit the past moving average value used in the calculation of the smoothed moving average value to the past moving average value corresponding to the detection period in which it was determined that no obstacle was present. With this configuration, it is possible to more effectively prevent the CFAR threshold value from being set excessively high due to the influence of the reflected wave from the obstacle.

[0063] Furthermore, the threshold calculation unit 102 (smoothing processing unit 203) may change the number of past moving average values ​​used in the calculation of the smoothed moving average value according to the distance of an obstacle determined to exist by the determination unit 103. The relationship between the distance of an obstacle and the number of past moving average values ​​should be appropriately determined according to the usage situation, etc., but for example, the number of past moving average values ​​used in the calculation of the smoothed moving average value may be increased as the distance from the vehicle 1 to the obstacle becomes closer. This is because the influence of the reflected wave from the obstacle becomes greater as the distance from the vehicle 1 to the obstacle becomes closer. With this configuration, the CFAR threshold can be more appropriately set according to the distance from the vehicle 1 to the obstacle.

[0064] The program for causing a computer (such as the processor 43) to execute the process for realizing the functions of the object detection device described above can be provided by recording it in an installable or executable file format on a computer-readable recording medium such as a CD (Compact Disc)-ROM, a flexible disk (FD), a CD-R (Recordable), a DVD (Digital Versatile Disk), etc. The program may also be provided or distributed via a network such as the Internet.

[0065] Although the embodiment of the present invention has been described above, the above-mentioned embodiment and its modifications are merely examples and are not intended to limit the scope of the invention. The above-mentioned novel embodiment and modifications can be implemented in various forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. The above-mentioned embodiment and modifications are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0066] 1...vehicle (moving object), 11...object detection device, 21, 21A to 21L...transmitter / receiver, 102...threshold calculation unit, 103...determination unit, Ac...current moving average value, Ap1, Ap2...past moving average values, As...smoothed moving average value, Th...(before smoothing) CFAR threshold (variation threshold value), Ths...(after smoothing) CFAR threshold (variation threshold value), Th0...fixed threshold value

Claims

1. 1. An object detection device that detects an obstacle present around a moving body based on a time series change in intensity of a reflected wave generated when a transmission wave transmitted from the moving body is reflected by an object, comprising: a threshold calculation unit that calculates a variable threshold that varies in accordance with the movement of the moving object based on a moving average value of the intensity of the reflected wave; a determination unit that determines whether or not the obstacle is present based on whether or not the intensity of the reflected wave is greater than the fluctuation threshold; Equipped with the threshold calculation unit calculates a smoothed moving average value by smoothing a current moving average value based on at least one past moving average value, and calculates the fluctuation threshold value based on the smoothed moving average value; Object detection device.

2. when the fluctuation threshold based on the current moving average value is greater than a predetermined fixed threshold value, the threshold calculation unit calculates the smooth moving average value based on at least one of the past moving average values ​​without using the current moving average value; The object detection device according to claim 1 .

3. the threshold calculation unit limits the past moving average value used in the calculation of the smooth moving average value to the past moving average value corresponding to a detection period in which it is determined that the obstacle does not exist; The object detection device according to claim 1 or 2.

4. the threshold calculation unit changes the number of the past moving average values ​​used for calculating the smooth moving average value in accordance with the distance of the obstacle determined to be present by the determination unit. The object detection device according to claim 1 or 2.

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