Patent Application
20240012123
The present disclosure relates to an object detection device.
Conventionally, there are techniques for detecting information on an object based on transmission and reception of an ultrasonic wave or the like. Also, in this technique, Constant False Alarm Rate (CFAR) processing is known as processing for reducing noise called clutter caused by reflection from an object that is not a detection target.
According to the CFAR processing, it is possible to acquire a CFAR signal corresponding to a signal acquired by removing clutter from the processing target signal by using a moving average of a value (signal level) of the processing target signal based on the receiving wave. Further, the object can be detected by comparing the CFAR signal with a threshold.
However, in the related art described above, a road surface type cannot be estimated in the CFAR processing when the transmitting wave is transmitted toward the road surface. When the road surface type can be estimated, the accuracy of a setting threshold value and the object detection can be improved, which is significant.
Therefore, one aspect of the present disclosure is to provide an object detection device capable of estimating a road surface type by CFAR processing.
An object detection device as an example of the present disclosure includes: a transmitting unit that transmits a transmitting wave toward a road surface; a receiving unit that receives a reflected wave of the transmitting wave reflected by an object as a receiving wave; a CFAR processing unit that acquires a CFAR signal at a predetermined detection timing by CFAR processing for each of a plurality of the transmitting waves, based on a value of a first processing target signal based on the receiving wave received at the detection timing and an average value of a value of a second processing target signal based on the receiving wave received in a predetermined section before and after the detection timing; and an estimating unit that estimates a road surface type based on an average signal level and a variation degree of a plurality of the CFAR signals.
With such a configuration, in the CFAR processing, the road surface type can be estimated based on the average signal level and the variation degree of the plurality of CFAR signals.
Also, in the above-described object detection device, a plurality of the transmitting units is provided, and each of the plurality of transmitting units simultaneously transmits the transmitting wave toward the road surface.
With such a configuration, by simultaneously transmitting the transmitting waves from the plurality of transmitting units toward the road surface, the road surface type can be estimated with high accuracy even when the vehicle is traveling.
Further, the object detection device described above further includes a threshold processing unit that sets a threshold regarding the CFAR signal in accordance with the road surface type estimated by the estimating unit.
With such a configuration, the threshold regarding the CFAR signal can be set with high accuracy in accordance with the estimated road surface type.
Further, in the above-described object detection device, the object detection device is installed on a vehicle, and the estimating unit transmits information on the estimated road surface type to a brake control unit of the vehicle.
With such a configuration, accurate brake control can be realized in accordance with the estimated road surface type.
Further, in the object detection device described above, the threshold processing unit sets the threshold to be larger as the variation degree corresponding to the road surface type becomes larger.
With such a configuration, a specifically appropriate threshold can be set for each road surface type.
In the object detection device described above, the estimating unit applies the average value and the variation degree of each of the second processing target signals to a map in which a region is defined in advance by a measured value of the average signal level and the variation degree for each road surface type, and estimates a corresponding road surface type.
With such a configuration, the road surface type can be estimated with high accuracy by using the above-described map created in advance.
Hereinafter, embodiments and modifications of the present disclosure will be described based on the drawings. The configurations of the embodiments and modifications described below, as well as the actions and effects brought about by the configurations, are merely examples, and are not limited to the following description.
As described below, the object detection system according to the first embodiment is an in-vehicle sensor system that performs transmission and reception of sound waves (ultrasonic waves) and acquires a time difference between the transmission and reception so as to detect an object including a human existing in the surroundings (for example, an obstacle O shown in
More specifically, as shown in
In the example shown in
Note that in the first embodiment, the hardware configurations and functions of the object detection devices 201 to 204 are the same. Therefore, hereinafter, the object detection devices 201 to 204 may be collectively referred to as the object detection device 200 to simplify the description. Also, in the first embodiment, the number of object detection devices 200 is not limited to four as shown in
As shown in
The input/output device 110 is an interface for realizing transmission and reception of information between the ECU 100 and the outside. For example, in the example shown in
The storage device 120 includes main storage devices such as a read only memory (ROM) and a random access memory (RAM), and/or auxiliary storage devices such as a hard disk drive (HDD) and a solid state drive (SSD).
The processor 130 is in charge of various processes executed in the ECU 100. The processor 130 includes an arithmetic device such as a central processing unit (CPU). The processor 130 reads and executes computer programs stored in the storage device 120 to implement various functions such as autonomous parking.
Further, as shown in
The transducer 210 has an oscillator 211 configured by a piezoelectric element or the like, and transmits/receives an ultrasonic wave using the oscillator 211.
More specifically, the transducer 210 transmits, as a transmitting wave, an ultrasonic wave generated in response to vibration of the oscillator 211, and receives, as a receiving wave, the vibration of the oscillator 211 caused by the ultrasonic wave transmitted as the transmitting wave that has returned by being reflected by an object present outside. In the example shown in
The example shown in
The control unit 220 has a hardware configuration similar to that of a normal computer. More specifically, the control unit 220 includes an input/output device 221, a storage device 222, and a processor 223.
The input/output device 221 is an interface that realizes transmission and reception of information between the control unit 220 and the outside (the ECU 100 and the transducer 210 in the example shown in
The storage device 222 includes main storage devices such as a ROM and a RAM, and/or auxiliary storage devices such as an HDD and an SSD.
The processor 223 is in charge of various processes executed by the control unit 220. The processor 223 includes an arithmetic device such as a CPU, for example. The processor 223 implements various functions by reading and executing computer programs stored in the storage device 333.
Here, the object detection device 200 according to the first embodiment detects a distance to the object by a technique called the time of flight (TOF) method. As will be detailed below, the TOF method is a technique that calculates a distance to an object by taking into consideration a difference between the timing at which a transmitting wave was transmitted (more specifically, the timing at which the transmitting wave began to be transmitted) and the timing at which the receiving wave was received (more specifically, the timing at which the receiving wave began to be received).
More specifically,
In the graph shown in
In the solid line L11, the vibration degree of the oscillator 211 reaches the peak at which the vibration degree of the oscillator 211 exceeds (or becomes equal to or more than) a predetermined threshold Th1 represented by a long dashed short dashed line L21 at a timing t4 at which just a time Tp passes from the timing t0 at which the transmission of the transmitting wave is started. This threshold Th1 is a value that is set beforehand to identify whether the vibration of the oscillator 211 is caused by receiving the receiving wave serving as the transmitting wave that has returned by being reflected by the object (such as the obstacle O shown in
Here, the vibration having a peak exceeding (or equal to or more than) the threshold Th1 can be regarded as being caused by the reception of the receiving wave serving as the transmitting wave that is reflected by the detection target and that is returned. In contrast, the vibration having a peak equal to or less than (or less than) the threshold Th1 can be regarded as being caused by the reception of the receiving wave serving as the transmitting wave that is reflected by an object that is not the detection target and that is returned.
Therefore, from the solid line L11, it can be read that the vibration of the oscillator 211 at the timing t4 was caused by the reception of the receiving wave serving as the transmitting wave that has returned after being reflected back by the detection target.
Note that, in the solid line L11, the vibration of the oscillator 211 is attenuated after the timing t4. Therefore, the timing t4 corresponds to the timing at which the reception of the receiving wave serving as the transmitting wave that has returned after being reflected by the detection target has been completed, in other words, the timing at which the transmitting wave that was last transmitted at the timing t1 returns as the receiving wave.
In the solid line L11, a timing t3 serving as the starting point of the peak at the timing t4 corresponds to the timing at which the reception of the receiving wave serving as the transmitting wave that has returned after being reflected by the detection target starts, in other words, the timing at which the transmitting wave that is transmitted first at the timing t0 returns as the receiving wave. Thus, in the solid line L11, the time ΔT between the timing t3 and the timing t4 is equal to the time Ta serving as the transmission time of the transmitting wave.
Based on the above, in order to acquire the distance to the detection target by the TOF method, it is necessary to acquire a time Tf between the timing t0 at which the transmitting wave starts to be transmitted and the timing t3 at which the receiving wave starts to be received. This time Tf can be acquired by subtracting the time ΔT equal to the time Ta serving as the transmission time of the transmitting wave from the time Tp serving as the difference between the timing t0 and the time t4 at which the signal level of the receiving wave reaches the peak exceeding the threshold Th1.
The timing t0 at which the transmitting wave starts to be transmitted can be easily specified as the timing at which the object detection device 200 starts to operate, and the time Ta serving as the transmission time of the transmitting wave is predetermined by setting or the like. Therefore, in order to acquire the distance to the detection target by the TOF method, it is important to specify the timing t4 at which the signal level of the receiving wave reaches a peak exceeding the threshold Th1. In order to specify the timing t4, it is important to accurately detect the correspondence between the transmitting wave and the receiving wave serving as the transmitting wave that has returned after being reflected by the detection target.
As described above, in the related art, the road surface type cannot be estimated in the CFAR processing when the transmitting wave is transmitted toward the road surface. When the road surface type can be estimated, the accuracy of a setting threshold value and the object detection can be improved, which is significant.
Therefore, in the first embodiment, the road surface type can be estimated by the CFAR processing by configuring the object detection device 200 as described below. A detailed description will be given below.
As shown in
In the first embodiment, at least part of the configuration shown in
First, the configuration on the transmitting side will be described.
The transmitting unit 411 transmits the transmitting wave to the outside including the road surface by causing the above-described oscillator 211 to vibrate at predetermined transmission intervals. The transmission interval is the time interval from when the transmitting wave is transmitted to when the next transmitting wave is transmitted. The transmitting unit 411 is configured to use, for example, a circuit that generates a carrier wave, a circuit that generates a pulse signal corresponding to identification information to be given to the carrier wave, a multiplier that modulates the carrier wave in accordance with the pulse signal, and an amplifier that amplifies the transmission signal output from the multiplier.
The object detection device 200 includes, for example, a plurality of transmitting units 411. For example, since each of the object detection devices 201 to 204 has one transmitting unit 411, four transmitting units 411 can be used. Then, each of the plurality of transmitting units 411 simultaneously transmits the transmitting waves toward the road surface.
Next, the configuration of the receiving side will be described.
The receiving unit 421 receives the reflected wave of the transmitting waves transmitted from the transmitting unit 411 reflected by an object as the receiving wave, until a predetermined measurement time has elapsed after the transmitting wave is transmitted. The measurement time is the waiting time set for receiving the receiving wave serving as the reflected wave of the transmitting wave, after transmission of the transmitting wave.
The preprocessing unit 422 performs preprocessing for converting a received signal corresponding to the receiving wave received by the receiving unit 421 into a processing target signal to be input to the CFAR processing unit 423. The preprocessing includes, for example, an amplification processing for amplifying a received signal corresponding to a receiving wave, a filtering processing for reducing noise contained in the amplified received signal, a correlation processing for acquiring a correlation value indicating the similarity degree of the transmitted signal and the received signal, and an envelope processing for generating a signal based on an envelope of a waveform indicating temporal changes in the correlation value as a processing target signal.
The CFAR processing unit 423 acquires a CFAR signal by performing the CFAR processing on the processing target signal output from the preprocessing unit 422. As described above, the CFAR processing is a process of acquiring the CFAR signal corresponding to a signal from which clutter has been removed from the processing target signal, by using a moving average of values (signal levels) of the processing target signal.
For example, for each of a plurality of transmitting waves, the CFAR processing unit 423 acquires the CFAR signal at the detection timing by the CFAR processing based on a difference between a value of a first processing target signal based on the receiving wave received at a predetermined detection timing, and an average value of a value of a second processing target signal based on the receiving wave received in a predetermined section before and after the detection timing.
Then, the detection processing unit 425 specifies the detection timing at which the CFAR signal value exceeds the threshold, based on the comparison between the CFAR signal value and the threshold set by the threshold processing unit 424. Since the detection timing at which the CFAR signal value exceeds the threshold coincides with the timing at which the signal level of the receiving wave serving as the transmitting wave that has returned by being reflected from the object reaches the peak, when the detection timing at which the value of the CFAR signal exceeds the threshold is specified, it is possible to detect the distance to an object with the TOF method described above.
The estimating unit 426 estimates the road surface type, based on the average signal level of a plurality of the CFAR signals and the variation degree (for example, a standard deviation, a variance, and the like).
Here,
A variation degree B represents the variation degree of the CFAR signals L1 to L4. An average signal level A represents the average signal level of the CFAR signals L1 to L4. In
The variation degree B and the average signal level A differ depending on the road surface type. The reason for these differences is thought to be, for example, that each of the factors such as surface roughness, constituent materials, and colors are different for each road surface type.
Here,
In this table information, six types of road surfaces are stored as examples of road surface types, which are asphalt, concrete, gravel, fresh snow, compacted snow, and ice. For each of the six types of road surfaces, information on the variation degree B and the average signal level A determined by experiments or the like is stored.
Thus, the estimating unit 426, for example, refers to this table information and estimates the road surface type based on the average signal level and the variation degree of the plurality of CFAR signals.
Returning to
The threshold processing unit 424 sets a threshold for the CFAR signal in accordance with the road surface type estimated by the estimating unit 426. For example, the threshold processing unit 424 sets the threshold to be larger when the variation degree corresponding to the road surface type becomes larger.
For example, since asphalt generally has a rougher surface and a greater variation degree than concrete, the threshold processing unit 424 sets the threshold for asphalt to a value greater than the threshold for concrete.
As shown in
Next, in S802, the receiving unit 421 of the object detection device 200 receives the receiving wave corresponding to the transmitting wave transmitted in S801.
Next, in S803, the preprocessing unit 422 of the object detection device 200 performs the preprocessing for the next processing in S804 for the received signal corresponding to the receiving wave received in S802.
Next, in S804, the CFAR processing unit 423 of the object detection device 200 performs the CFAR processing on the processing target signal output from the preprocessing unit 422 through the preprocessing in S803, and generates the CFAR signal.
Next, in S805, the estimating unit 426 estimates the road surface type based on the average signal level and the variation degree of the plurality of the CFAR signals.
Next, in S806, the threshold processing unit 424 of the object detection device 200 sets a threshold for the CFAR signal generated in S804 in accordance with the road surface type estimated in S805.
Next, in S807, the detection processing unit 425 of the object detection device 200 detects the distance to the object based on the comparison between the value of the CFAR signal and the threshold set in S805. Then the process is ended.
As described above, according to the object detection device 200 of the first embodiment, in the CFAR processing, the road surface type can be estimated based on the average signal level and the variation degree of the plurality of CFAR signals. In other words, the road surface type can be estimated with only the information from the ultrasonic sensor.
In addition, by simultaneously transmitting the transmitting waves from the plurality of transmitting units 411 toward the road surface, the road surface type can be estimated with high accuracy even when the vehicle is traveling.
In addition, the threshold for the CFAR signal can be set with high accuracy in accordance with the estimated road surface type.
Further, it is possible to realize accurate brake control in accordance with the estimated road surface type.
In addition, by setting the threshold to be larger as the variation degree corresponding to the road surface type becomes larger, a specifically appropriate threshold can be set for each road surface type.
Next, a second embodiment will be described. Overlapping descriptions of items similar to those of the first embodiment will be omitted as appropriate. In the second embodiment, a case in which the object detection system uses a map to estimate the road surface type ahead and a case in which the object detection system uses a map to estimate the road surface type directly below.
Correspondence with the road surface type for each region in the first map is defined in advance based on measured values of the average signal level and the variation degree regarding the reflected wave from the road surface ahead. Then, the estimating unit 426 refers to the first map, applies the average value and the variation degree of each of the second processing target signals based on the reflected wave from the road surface ahead, and estimates the corresponding road surface type. In this way, the road surface type ahead can be estimated with high accuracy.
Next,
Correspondence with the road surface type for each region in the second map is defined in advance based on measured values of the average signal level and the variation degree regarding the reflected wave from the road surface directly below. Then, the estimating unit 426 refers to the second map, applies the average value and the variation degree of each of the second processing target signals based on the reflected wave from the road surface directly below, and estimates the corresponding road surface type. In this way, the road surface type directly below can be estimated with high accuracy.
<Modification>
In the above-described embodiments, the technique of the present disclosure is applied to a configuration that detects the distance to the object by transmitting and receiving the ultrasonic wave. However, the technique of the present disclosure can also be applied to a configuration that detects a distance to an object by transmitting and receiving a wave other than an ultrasonic wave, such as a sound wave, a millimeter wave, radar, and an electromagnetic wave.
Although the embodiments and modifications of the present disclosure have been described above, the embodiments and modifications described above are merely examples, and are not intended to limit the scope of the invention. The novel embodiments and modifications described above can be implemented in various forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. The embodiments and modifications described above are included in the scope and gist of the invention, and are included in the scope of the invention described in the claims and equivalents thereof
For example, in the above-described embodiment, the transmitting waves are simultaneously transmitted from the plurality of transmitting units 411 toward the road surface. However, the present invention is not limited to this. For example, the road surface type may be estimated based on the plurality of transmitting waves transmitted by a single transmitting unit 411. In particular, when the vehicle is stopped or traveling at a low speed, the road surface type can still be estimated with sufficiently high accuracy.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2021-002369 | Jan 2021 | JP | national |
This application is a National Stage of International Application No. PCT/JP2021/047986 filed Dec. 23, 2021, claiming priority based on Japanese Patent Application No. 2021-002369 filed Jan. 8, 2021, the entire contents of which are incorporated herein by reference.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2021/047986 | 12/23/2021 | WO |
