WO2020008534A1

WO2020008534A1 - Obstacle detection device and driving support device

Info

Publication number: WO2020008534A1
Application number: PCT/JP2018/025254
Authority: WO
Inventors: 聡史上田; 侑己浦川; 裕小野寺; 真一原瀬; 井上　悟; 元気山下; 亘辻田; 努朝比奈
Original assignee: 三菱電機株式会社
Priority date: 2018-07-03
Filing date: 2018-07-03
Publication date: 2020-01-09
Also published as: JPWO2020008534A1; JP7199436B2

Abstract

This obstacle detection device (100) comprises: a feature value extraction unit (12) for extracting feature values for a plurality of reflected waves that have been reflected by an obstacle and received by a distance measurement sensor (2) provided in a vehicle (1); and an obstacle identification unit (13) that determines that the obstacle is higher when the dispersion amount of the feature values is larger than when the dispersion amount of the feature values is smaller and at least identifies whether the obstacle is a traveling obstacle on the basis of the results of clustering first parameter values representing feature value sizes and second parameter values representing dispersion amount sizes.

Description

Obstacle detection device and driving support device

The present invention relates to an obstacle detection device and a driving support device.

2. Description of the Related Art Conventionally, a technology of determining the height of an obstacle around a vehicle using a TOF (Time of Flight) type distance measuring sensor provided in the vehicle has been developed (for example, Patent Document 1 and Patent Document 1). Reference 2).

JP 2010-197351 A JP 2016-80650 A

According to the related art described in Patent Document 1, when the height of the obstacle is low, the vehicle approaches the obstacle and the obstacle moves out of the detection area of the distance measurement sensor (that is, the peak value of the reflected wave decreases). ) Is used to determine the height of the obstacle. For this reason, the prior art described in Patent Literature 1 has a problem in that it is not possible to determine the height of a distant obstacle. Further, the conventional technique described in Patent Document 1 has a problem that when the distance between the vehicle and the obstacle is constant, the height of the obstacle cannot be determined.

The related art described in Patent Document 2 determines the relative height of an obstacle with respect to a predetermined height by comparing the peak value of a reflected wave with a reference value. This utilizes the fact that the peak value differs depending on the height of the obstacle. However, as described in Patent Literature 1, when an obstacle is located far away, the difference in peak value according to the height of the obstacle becomes small. For this reason, the prior art described in Patent Literature 2 has a problem in that the accuracy of determining the height of a distant obstacle is low. Further, in the conventional technology described in Patent Document 2, when an obstacle has a height approximately equal to a predetermined height, an error in determining the height of the obstacle relative to the predetermined height is likely to occur. There was a problem.

The present invention has been made to solve the above-described problem, and has as its object to accurately determine the height of an obstacle using a distance measurement sensor.

An obstacle detection device according to an aspect of the invention includes a feature amount extraction unit that extracts a feature amount related to a plurality of reflected waves when a distance measurement sensor provided in the vehicle receives a plurality of reflected waves due to an obstacle; An obstacle determining unit that determines that the height of the obstacle is higher when the amount of variance is larger than when the amount of variance is smaller, the first parameter value indicating the size of the feature amount, and the size of the amount of variance And an obstacle determining unit that determines whether at least the obstacle is a traveling obstacle based on the result of the clustering of the second parameter value indicating the obstacle.

According to the present invention, since the configuration is as described above, it is possible to accurately determine the height of the obstacle using the distance measuring sensor.

FIG. 2 is a block diagram illustrating a main part of the obstacle detection device according to the first embodiment. FIG. 3 is a block diagram illustrating a main part of an obstacle detection unit in the obstacle detection device according to the first embodiment. FIG. 3A is an explanatory diagram illustrating a hardware configuration of the obstacle detection device according to the first embodiment. FIG. 3B is an explanatory diagram illustrating another hardware configuration of the obstacle detection device according to the first embodiment. 5 is a flowchart illustrating an operation of the obstacle detection device according to the first embodiment. FIG. 5A is an explanatory diagram illustrating an example of a propagation path of a reflected wave by a traveling obstacle. FIG. 5B is an explanatory diagram illustrating an example of a waveform of a transmission signal. FIG. 5C is an explanatory diagram illustrating an example of a waveform of a reception signal corresponding to a reflected wave due to a traveling obstacle. FIG. 5D is an explanatory diagram illustrating another example of the waveform of the received signal corresponding to the reflected wave from the traveling obstacle. FIG. 6A is an explanatory diagram illustrating an example of a propagation path of a reflected wave due to a road obstacle or a road surface obstacle. FIG. 6B is an explanatory diagram illustrating an example of a waveform of a transmission signal. FIG. 6C is an explanatory diagram illustrating an example of a waveform of a received signal corresponding to a reflected wave from a road obstacle. FIG. 6D is an explanatory diagram showing another example of the waveform of the received signal corresponding to the reflected wave from the road obstacle. FIG. 6E is an explanatory diagram illustrating an example of a waveform of a reception signal corresponding to a reflected wave from a road surface obstacle. FIG. 6F is an explanatory diagram illustrating another example of the waveform of the received signal corresponding to the reflected wave due to the road surface obstacle. FIG. 7A is an explanatory diagram illustrating an example of actually measured first parameter values and second parameter values before manufacturing the obstacle detection device according to Embodiment 1. FIG. 7B is an explanatory diagram illustrating an example of the first parameter value and the second parameter value calculated after shipping of the vehicle including the obstacle detection device according to Embodiment 1. FIG. 8A is an explanatory diagram illustrating an example of a wave height, a wave width, and a wave area of a reflected wave. FIG. 8B is an explanatory diagram illustrating an example of a response time of a reflected wave. FIG. 9A is an explanatory diagram showing an example of actual measured values of the first parameter value, the second parameter value, and the third parameter value before manufacturing the obstacle detection device according to Embodiment 1. FIG. 9B is an explanatory diagram illustrating an example of a first parameter value, a second parameter value, and a third parameter value calculated after shipping of the vehicle having the obstacle detection device according to Embodiment 1. FIG. 9 is a block diagram showing a main part of a driving support device according to Embodiment 2. 9 is a flowchart showing the operation of the driving support device according to Embodiment 2. FIG. 12A is an explanatory diagram showing an example of an installation position of a distance measuring sensor in a vehicle, and is an explanatory diagram showing a state viewed from above the vehicle. FIG. 12B is an explanatory diagram illustrating an example of an installation position of the distance measurement sensor in the vehicle, and is an explanatory diagram illustrating a state viewed from a side of the vehicle. FIG. 13A is an explanatory diagram showing an example of an installation position of a distance measurement sensor in a vehicle, and is an explanatory diagram showing a state viewed from above the vehicle. FIG. 13B is an explanatory diagram illustrating an example of an installation position of the distance measurement sensor in the vehicle, and is an explanatory diagram illustrating a state viewed from a side of the vehicle. It is explanatory drawing which shows the example of a facing angle. FIG. 15A is an explanatory diagram illustrating an example of a traveling route when the vehicle approaches an obstacle. FIG. 15B is an explanatory diagram showing an example of a temporal change of the directly facing angle at this time. FIG. 15C is an explanatory diagram illustrating an example of data indicating the feature amount at this time. FIG. 13 is a block diagram illustrating a main part of another driving support device according to Embodiment 2. 9 is a flowchart showing an operation of another driving support device according to Embodiment 2. FIG. 18A is an explanatory diagram illustrating an example of a detection section. FIG. 18B is an explanatory diagram illustrating another example of the detection section. 9 is a flowchart illustrating another operation of the driving support device according to the second embodiment. FIG. 20A is an explanatory diagram illustrating another example of the installation position of the distance measurement sensor in the vehicle, and is an explanatory diagram illustrating a state viewed from above the vehicle. FIG. 20B is an explanatory diagram illustrating another example of the installation position of the distance measurement sensor in the vehicle, and is an explanatory diagram illustrating a state viewed from a side of the vehicle. FIG. 21A is an explanatory diagram illustrating another example of the installation position of the distance measurement sensor in the vehicle, and is an explanatory diagram illustrating a state viewed from above the vehicle. FIG. 21B is an explanatory diagram illustrating another example of the installation position of the distance measurement sensor in the vehicle, and is an explanatory diagram illustrating a state viewed from a side of the vehicle. FIG. 9 is a block diagram showing a main part of a driving support device according to Embodiment 3. 9 is a flowchart showing the operation of the driving support device according to Embodiment 3. FIG. 14 is an explanatory diagram showing an example of a detection result by an obstacle detection unit in the driving support device according to Embodiment 3. It is explanatory drawing which shows the example of a parking position and a guidance route. It is explanatory drawing which shows other examples of a parking position and a guidance route. It is explanatory drawing which shows other examples of a parking position and a guidance route. It is an explanatory view showing an example of a state where there is a wall or a curb on the back side of a parked vehicle and there is a step on the near side of the parked vehicle. FIG. 29A is an explanatory diagram illustrating another example of a detection result by the obstacle detection unit in the driving support device according to Embodiment 3. FIG. 29B is an explanatory diagram illustrating an example of a detection result obtained by the obstacle detection unit in another driving support device according to Embodiment 3. FIG. 14 is an explanatory diagram illustrating another example of a detection result by the obstacle detection unit in another driving support device according to Embodiment 3. FIG. 14 is an explanatory diagram illustrating another example of a detection result by the obstacle detection unit in another driving support device according to Embodiment 3. FIG. 14 is a block diagram showing a main part of a driving support device according to Embodiment 4. FIG. 11 is an explanatory diagram illustrating an example of a state where a marker image is superimposed and displayed on a captured image. 9 is a flowchart showing the operation of the driving support device according to Embodiment 4. FIG. 13 is a block diagram showing a main part of another driving support device according to Embodiment 4.

Hereafter, in order to explain this invention in greater detail, the preferred embodiments of the present invention will be described with reference to the accompanying drawings.

Embodiment 1 FIG.
FIG. 1 is a block diagram illustrating a main part of the obstacle detection device according to the first embodiment. FIG. 2 is a block diagram illustrating a main part of an obstacle detection unit in the obstacle detection device according to the first embodiment. With reference to FIGS. 1 and 2, an obstacle detection device 100 according to the first embodiment will be described.

The obstacle detection device 100 is connected to a computer network (for example, CAN (Controller Area Network)) in the vehicle 1. The obstacle detection device 100 can appropriately acquire various signals from the computer network. These signals include, for example, a signal indicating the traveling speed of the vehicle 1 and a signal indicating the yaw rate or the steering angle of the vehicle 1.

The vehicle 1 has a distance measuring sensor 2. In the example shown in FIG. 1, the distance measuring sensor 2 includes N distance measuring sensors 2 ₁ to 2 _N (N is an arbitrary integer of 2 or more). The N distance measuring sensors 2 ₁ to 2 _N have different installation positions in the vehicle 1 and have the same installation direction in the vehicle 1. Each of the N distance measuring sensors 2 ₁ to 2 _N is constituted by, for example, a sonar, a millimeter wave radar or a laser radar.

Hereinafter, ultrasonic waves, radio waves, light, and the like transmitted and received by the distance measuring sensor 2 are collectively referred to as “search waves”. When the search wave is reflected by an obstacle outside the vehicle 1, the reflected search wave is referred to as a "reflected wave". Further, when one of the distance measurement sensors 2 transmits a search wave and the distance measurement sensor 2 receives a reflected wave, the search wave and the reflected wave are referred to as “direct waves”. When one of the distance measurement sensors 2 transmits a search wave and the other distance measurement sensor 2 receives a reflected wave, the search wave and the reflected wave are referred to as “indirect waves”.

のうち Among obstacles outside the vehicle 1, obstacles having a height high enough to contact the bumper portion of the vehicle 1 are referred to as “running obstacles”. The traveling obstacle is, for example, a wall or another parked vehicle (hereinafter, referred to as “parked vehicle”). In addition, among obstacles outside the vehicle 1, obstacles having a height low enough not to contact the bumper portion of the vehicle 1 and having a height high enough not to be able to get over the vehicle 1 are referred to as “road obstacles”. " The road obstacle is, for example, a curb or a wheelchair. Among obstacles outside the vehicle 1, an obstacle having a height low enough not to contact the bumper portion of the vehicle 1 and having a height low enough to allow the vehicle 1 to get over is referred to as “road obstacle”. That. The road surface obstacle is, for example, a step. That is, the traveling obstacle has a height higher than the road obstacle, and the road obstacle has a height higher than the road obstacle.

The obstacle detection unit 11 detects an obstacle around the vehicle 1 by causing the distance measurement sensor 2 to transmit a search wave. More specifically, the obstacle detection unit 11 determines the position of the obstacle with respect to the vehicle 1 by measuring the distance between the vehicle 1 and the obstacle. The obstacle detection unit 11 includes a transmission signal output unit 21, a reception signal acquisition unit 22, a distance value calculation unit 23, a reflection point position calculation unit 24, a grouping unit 25, a vehicle position calculation unit 26, and a sensor position calculation unit 27. It is configured.

The transmission signal output section 21 outputs a transmission signal to the distance measurement sensor 2 so that the distance measurement sensor 2 transmits a search wave. The reception signal acquisition unit 22 acquires a reception signal from the distance measurement sensor 2 from the distance measurement sensor 2.

The distance value calculation unit 23 determines whether or not the reflected wave is received by the distance measuring sensor 2 by comparing the intensity of the signal received by the distance measuring sensor 2 with a predetermined threshold value. The distance value calculator 23 calculates a distance value by TOF when a reflected wave is received by the distance measuring sensor 2. Since a method of calculating a distance value by TOF is known, detailed description is omitted.

The reflection point position calculation unit 24 calculates the position of the point where the search wave is reflected (hereinafter referred to as “reflection point”) using the distance value calculated by the distance value calculation unit 23. The position of the reflection point is determined by, for example, a first axis (hereinafter referred to as “X axis”) corresponding to the front-rear direction of the vehicle 1 and a second axis (hereinafter referred to as “Y axis”) corresponding to the left / right direction of the vehicle 1. It is represented by coordinate values in a coordinate system in meters (hereinafter referred to as “XY coordinate system”).

Specifically, for example, the reflection point position calculation unit 24 has a start point corresponding to the position of the distance measurement sensor 2 at the transmission timing of the direct wave (or the reception timing of the direct wave), and also measures the distance in the vehicle 1. By calculating a vector having a direction corresponding to the installation direction of the sensor 2 and having a magnitude corresponding to the distance value calculated by the distance value calculation unit 23, the coordinate value of the reflection point in the XY coordinate system is calculated. I do. This vector is a vector in a virtual plane (hereinafter, referred to as “XY plane”) along the X axis and the Y axis.

Or, for example, the reflection point position calculation unit 24 calculates the position of the reflection point by a so-called “two-circle intersection” using a plurality of distance values corresponding to mutually different direct waves. That is, the reflection point position calculation unit 24 calculates the coordinate value of the reflection point in the XY coordinate system by executing the two-circle intersection processing on the XY plane.

情報 Among the information used for calculating the position of the reflection point, the information indicating the position of the distance measuring sensor 2 at the transmission timing of the search wave (or the reception timing of the reflected wave) is output by the sensor position calculation unit 27. Other information (for example, information indicating the installation direction of the distance measurement sensor 2 in the vehicle 1) is stored in the reflection point position calculation unit 24 in advance.

After the positions of the plurality of reflection points are calculated by the reflection point position calculation unit 24, the grouping unit 25 groups the plurality of reflection points to correspond to one or more obstacles in principle one-to-one. One or more reflection point groups (hereinafter, referred to as “groups”) are set. In this grouping, for example, when the distance between two adjacent reflection points is less than a predetermined distance, the two reflection points are included in the same group.

The own vehicle position calculating unit 26 calculates the position of the vehicle 1 at the transmission timing of the search wave (or the reception timing of the reflected wave) (hereinafter, referred to as “own vehicle position”). The sensor position calculator 27 calculates the position of the distance measuring sensor 2 at the timing (hereinafter, referred to as “sensor position”). These positions are represented by coordinate values in an XY coordinate system, for example. The sensor position calculator 27 outputs information indicating the sensor position to the reflection point position calculator 24. The information indicating the sensor position is used by the reflection point position calculation unit 24 to calculate the position of the reflection point.

Various known methods can be used to calculate the vehicle position (for example, autonomous navigation), and a detailed description of these methods will be omitted. Signals used for autonomous navigation (for example, a signal indicating the traveling speed of the vehicle 1 and a signal indicating the yaw rate or the steering angle of the vehicle 1) are appropriately acquired from a computer network in the vehicle 1. Information used for calculating the sensor position (for example, information indicating the installation position of the distance measurement sensor 2 in the vehicle 1) is stored in the sensor position calculation unit 27 in advance.

In the calculation of the distance value by the distance value calculation unit 23 and the calculation of the coordinate value by the reflection point position calculation unit 24, an indirect wave may be used instead of or in addition to the direct wave. By using the indirect wave in addition to the direct wave, the number of reflection points obtained by transmitting the search wave each time can be increased as compared with the case where only the direct wave is used. As a result, the number of reflection points included in each group can be increased.

Each group includes a plurality of reflection points, and the plurality of reflection points correspond to a plurality of reflected waves. The feature amount extraction unit 12 acquires from the obstacle detection unit 11 information indicating the waveform of the received signal corresponding to the plurality of reflected waves. The feature value extraction unit 12 extracts a feature value of the plurality of reflected waves using the acquired information. Details of the feature amount will be described later.

The obstacle determining unit 13 determines, for each group, a value indicating the magnitude of the feature amount extracted by the feature amount extracting unit 12 (hereinafter referred to as a “first parameter value”. For example, an average value of these feature amounts is used. Is calculated). In addition, the obstacle determining unit 13 determines, for each group, a value indicating the magnitude of the variance of the feature amount extracted by the feature amount extracting unit 12 (hereinafter, referred to as a “second parameter value”. Is the variance of the amount.) The obstacle determining unit 13 determines the type of the obstacle corresponding to each group using the calculated first parameter value and the calculated second parameter value. More specifically, the obstacle determining unit 13 determines whether the obstacle corresponding to each group is a road surface obstacle, a road obstacle, or a running obstacle.

Here, the road surface obstacle, the road obstacle, and the traveling obstacle have different heights from each other. Therefore, it is determined whether the obstacle corresponding to each group is a road surface obstacle, a road obstacle, or a running obstacle. It is a judgment as to which height it has. That is, the obstacle determining unit 13 determines the height of the obstacle corresponding to each group by determining the type of the obstacle corresponding to each group. The details of the method of determining the type of the obstacle by the obstacle determination unit 13, that is, the method of determining the height of the obstacle will be described later.

The obstacle detection unit 11, the feature amount extraction unit 12, and the obstacle discrimination unit 13 constitute a main part of the obstacle detection device 100.

Next, the hardware configuration of the main part of the obstacle detection device 100 will be described with reference to FIG.

As shown in FIG. 3A, the obstacle detection device 100 is constituted by a computer, and the computer has a processor 31 and a memory 32. The memory 32 stores a program for causing the computer to function as the obstacle detection unit 11, the feature amount extraction unit 12, and the obstacle determination unit 13. The functions of the obstacle detection unit 11, the feature amount extraction unit 12, and the obstacle determination unit 13 are realized by the processor 31 reading and executing the program stored in the memory 32.

Alternatively, as shown in FIG. 3B, the obstacle detection device 100 may be configured by a processing circuit 33. In this case, the functions of the obstacle detection unit 11, the feature amount extraction unit 12, and the obstacle determination unit 13 may be realized by the processing circuit 33.

Alternatively, the obstacle detection device 100 may include a processor 31, a memory 32, and a processing circuit 33 (not shown). In this case, some of the functions of the obstacle detection unit 11, the feature amount extraction unit 12, and the obstacle determination unit 13 are realized by the processor 31 and the memory 32, and the remaining functions are realized by the processing circuit 33. It may be something.

The processor 31 uses, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a microprocessor, a microcontroller, or a DSP (Digital Signal Processor).

The memory 32 uses a semiconductor memory or a magnetic disk, for example. More specifically, the memory 32 includes a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Memory Only), and an EEPROM (Electrical Memory). State @ Drive) or HDD (Hard @ Disk @ Drive) or the like.

The processing circuit 33 includes, for example, an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), an FPGA (Field-Programmable Gate Array), and a SoC (Sig-Lig- Is used.

Next, the operation of the obstacle detection device 100 will be described with reference to the flowchart of FIG.

First, in step ST1, the obstacle detecting unit 11 detects an obstacle around the vehicle 1 by causing the distance measuring sensor 2 to transmit a search wave. More specifically, the obstacle detection unit 11 determines the position of the obstacle with respect to the vehicle 1 by measuring the distance between the vehicle 1 and the obstacle.

により By the process of step ST1, one or more groups corresponding to one or more obstacles in principle one-to-one are set. Each group includes a plurality of reflection points, and the plurality of reflection points correspond to a plurality of reflected waves. Next, in step ST <b> 2, the feature amount extraction unit 12 acquires from the obstacle detection unit 11 information indicating the waveform of the received signal corresponding to the plurality of reflected waves. The feature amount extraction unit 12 extracts feature amounts related to the plurality of reflected waves using the acquired information. Details of the feature amount will be described later.

Next, in step ST3, the obstacle determining unit 13 calculates a first parameter value and a second parameter value using the feature amount extracted by the feature amount extracting unit 12. The obstacle determining unit 13 determines the type of the obstacle corresponding to each group by using the calculated first parameter value and the second parameter value, thereby obtaining the height of the obstacle corresponding to each group. Judge. The details of the method of determining the type of the obstacle by the obstacle determination unit 13, that is, the method of determining the height of the obstacle will be described later.

Next, the details of the method of determining the type of the obstacle by the obstacle determining unit 13, that is, the method of determining the height of the obstacle will be described with reference to FIGS. Further, details of the feature amount will be described.

FIG. 5A shows an example of the propagation path of the reflected wave RW due to a traveling obstacle (more specifically, a wall). FIG. 5B shows an example of the waveform of the transmission signal TS. FIG. 5C shows an example of the waveform of the reception signal RS corresponding to the reflected wave RW due to the traveling obstacle. FIG. 5D illustrates another example of the waveform of the reception signal RS corresponding to the reflected wave RW due to the traveling obstacle.

FIG. 6A shows an example of a propagation path of the reflected wave RW due to an obstacle on the road (more specifically, a curb) or an obstacle on the road (more specifically, a step). FIG. 6B shows an example of the waveform of the transmission signal TS. FIG. 6C shows an example of the waveform of the reception signal RS corresponding to the reflected wave RW due to the obstacle on the road. FIG. 6D shows another example of the waveform of the received signal RS corresponding to the reflected wave RW due to the obstacle on the road. FIG. 6E shows an example of the waveform of the reception signal RS corresponding to the reflected wave RW due to the road surface obstacle. FIG. 6F shows another example of the waveform of the received signal RS corresponding to the reflected wave RW due to the road surface obstacle.

It is assumed that the transmission signal output unit 21 outputs the transmission signal TS to the distance measurement sensor 2 so that the distance measurement sensor 2 transmits the search wave SW. Usually, since the search wave SW propagates in the air while gradually spreading, the propagation path (so-called “path”) from the transmission of the search wave SW by the distance measuring sensor 2 to the reception of the reflected wave RW by the distance measurement sensor 2. There are a plurality. For example, there is a path that is reflected once by the obstacle O and returns to the distance measurement sensor 2. There is also a path that is reflected once by the road R and then reflected once by the obstacle O and returns to the distance measurement sensor 2. These paths include paths having different path lengths. The reflected wave RW is a composite wave due to interference of a plurality of waves rw corresponding to these paths. The received signal RS is a composite signal of a plurality of signals rs corresponding to the plurality of waves rw.

In addition, since the path changes according to the uneven shape of the road R, the unevenness of the surface of the vehicle 1 that reflects the vibration of the vehicle 1 and the search wave SW on the obstacle O (hereinafter referred to as “reflective surface”), etc. The waveform changes, and the waveform of the received signal RS also changes. For this reason, when a plurality of reflected waves RW due to the same obstacle O are received by the distance measurement sensor 2, the waveforms of the plurality of reflected waves RW have variations, and the plurality of reflected waves RW Also has a variation in the waveform of the received signal RS corresponding to.

Here, when the obstacle O is a traveling obstacle, since the area of the reflection surface portion is larger than when the obstacle O is an on-road obstacle, the reception intensity of the reflected wave RW (that is, the intensity of the reception signal RS). Becomes larger. In addition, since the total number of paths increases and the difference in path length between paths also increases, the variation in the waveform of the reflected wave RW increases, and the variation in the waveform of the reception signal RS also increases.

Similarly, when the obstacle O is an obstacle on the road, the reception surface of the reflected wave RW (that is, the intensity of the reception signal RS) is larger because the area of the reflection surface portion is larger than that when the obstacle O is a road obstacle. Becomes larger. In addition, since the total number of paths increases and the difference in path length between paths also increases, the variation in the waveform of the reflected wave RW increases, and the variation in the waveform of the reception signal RS also increases.

Therefore, when a plurality of reflected waves RW due to the same obstacle O are received by the distance measurement sensor 2, when a feature amount based on the magnitude of these reflected waves RW is extracted, the extracted features are extracted. The amount of dispersion of the amount has a correlation with the height of the obstacle O. For this reason, it is possible to determine the height of the obstacle O based on the amount of dispersion, such as determining that the height of the obstacle O is higher when the amount of dispersion is larger than when the amount of dispersion is smaller. The determination of the height of the obstacle O by the obstacle determination unit 13 is based on this principle.

Based on the above content, the feature amount extraction unit 12 corresponds to each of the plurality of reflected waves RW corresponding to the plurality of reflected points included in each group to the size of each of the plurality of reflected waves RW. Is extracted as a feature value. More specifically, the feature value extraction unit 12 extracts a wave height, a wave width, a waveform area, a response time, or the like of each of the plurality of reflected waves RW as a feature value. These features are extracted from information indicating the waveform of the received signal RS corresponding to the plurality of reflected waves RW.

As a result, not only the average value of these feature values (that is, the first parameter value) has a correlation with the height of the obstacle O, but also the variance value of these feature values (that is, the second parameter value). Value) also has a correlation with the height of the obstacle O. Therefore, the first parameter value and the second parameter value enable clustering according to the height of the obstacle O, that is, clustering according to the type of the obstacle O.

FIG. 7 shows an example of the range A1 including the first parameter value and the second parameter value when the obstacle O is a road surface obstacle, and the first parameter value and the second parameter value when the obstacle O is a road obstacle. An example of a range A2 including a parameter value and an example of a range A3 including a first parameter value and a second parameter value when the obstacle O is a traveling obstacle are shown. In the figure, a dividing line PL1 between the ranges A1 and A2 corresponds to a determination threshold Th1 for determining whether the obstacle O is a road surface obstacle. The dividing line PL2 between the ranges A2 and A3 corresponds to a threshold value Th2 for determining whether or not the obstacle O is a traveling obstacle.

Each circle in FIG. 7A is an actual measurement value of the first parameter value and the second parameter value before the manufacture of the obstacle detection device 100, and is an example of the actual measurement value when the obstacle O is a road surface obstacle. Yes, it is. Each square mark in FIG. 7A is an actual measurement value of the first parameter value and the second parameter value before manufacturing the obstacle detection device 100, and is an example of the actual measurement value when the obstacle O is an on-road obstacle. Yes, it is. Each triangle mark in FIG. 7A is an actual measurement value of the first parameter value and the second parameter value before manufacturing the obstacle detection device 100, and is an example of the actual measurement value when the obstacle O is a traveling obstacle. Yes, it is. The information indicating the ranges A1 to A3 set by the clustering of these actually measured values, more specifically, the information indicating the discrimination thresholds Th1 and Th2 is stored in the obstacle discrimination unit 13 in advance. For the clustering and the setting of the dividing lines PL1 and PL2 (that is, the setting of the discrimination thresholds Th1 and Th2), a machine learning technique such as linear discrimination or pattern recognition is used.

The obstacle determining unit 13 compares the first parameter value and the second parameter value calculated after the manufacture of the vehicle 1 (more specifically, after shipment) with the determination thresholds Th1 and Th2, thereby obtaining the first parameter. It identifies which of the ranges A1 to A3 the value and the second parameter value fall within. Thereby, it is determined whether the obstacle O around the vehicle 1 is a road surface obstacle, a road obstacle, or a traveling obstacle. The crosses in FIG. 7B correspond to examples of the first parameter value and the second parameter value calculated after the shipment of the vehicle 1. In this case, since the first parameter value and the second parameter value are included in the range A3, the obstacle O is determined to be a traveling obstacle.

Next, a specific example of the amount corresponding to the size of each of the plurality of reflected waves RW will be described with reference to FIG.

As described above, the feature amount extraction unit 12 extracts the amount corresponding to the size of each of the plurality of reflected waves RW as the feature amount. FIG. 8 shows an example of the waveform of the reception signal RS corresponding to one of the plurality of reflected waves RW.

{For example, the feature quantity extraction unit 12 extracts the peak of the reflected wave RW based on the peak value PV of the received signal RS (see FIG. 8A). Alternatively, for example, the feature amount extracting unit 12 extracts a time width of a portion of the received signal RS exceeding the threshold Th, that is, a wave width of the reflected wave RW (see FIG. 8A). The threshold Th is a threshold used for determining whether or not the reflected wave RW has been received. Alternatively, for example, the feature amount extraction unit 12 extracts the entire time width of the received signal RS (not illustrated). Alternatively, for example, the feature amount extraction unit 12 extracts the half width of the received signal RS, that is, the half width of the reflected wave RW (not shown). Alternatively, for example, the feature amount extraction unit 12 extracts a waveform area of a portion of the received signal RS exceeding the threshold Th, that is, a waveform area of the reflected wave RW (see FIG. 8A). Alternatively, for example, the feature amount extracting unit 12 extracts the entire waveform area of the received signal RS (not shown). These are all amounts corresponding to the magnitude of the reflected wave RW.

Or, for example, the feature quantity extraction unit 12 extracts the time from when the received signal RS exceeds the peak value PV to when the received signal RS falls below the threshold Th, that is, the response time of the reflected wave RW (see FIG. 8B). Alternatively, for example, the feature amount extraction unit 12 extracts a falling slope in the waveform of the received signal RS, that is, a falling slope in the waveform of the reflected wave RW (not shown). Alternatively, for example, the feature amount extraction unit 12 extracts a time constant in the waveform of the received signal RS, that is, a time constant in the waveform of the reflected wave RW (not shown). These are all amounts corresponding to the magnitude of the reflected wave RW.

Next, another example of the method of determining the type of the obstacle by the obstacle determining unit 13, that is, another example of the method of determining the height of the obstacle will be described with reference to FIG.

The obstacle determining unit 13 acquires, from the obstacle detecting unit 11, information indicating the distance value calculated by the distance value calculating unit 23 or information indicating the coordinate value calculated by the reflection point position calculating unit 24. The obstacle determining unit 13 calculates a value (hereinafter, referred to as a “third parameter value”) corresponding to the distance between the vehicle 1 and the obstacle O using the acquired information. In FIG. 1, connection lines between the obstacle detection unit 11 and the obstacle determination unit 13 are not shown.

FIG. 9 is an example of a range A1 including the first parameter value, the second parameter value, and the third parameter value when the obstacle O is a road surface obstacle, and the first example when the obstacle O is a road obstacle. An example of the range A2 including the parameter value, the second parameter value, and the third parameter value, and the range including the first parameter value, the second parameter value, and the third parameter value when the obstacle O is a traveling obstacle An example of A3 is shown. In the figure, a dividing line PL1 between the ranges A1 and A2 corresponds to a determination threshold Th1 for determining whether the obstacle O is a road surface obstacle. The dividing line PL2 between the ranges A2 and A3 corresponds to a threshold value Th2 for determining whether or not the obstacle O is a traveling obstacle.

9A are actually measured values of the first parameter value, the second parameter value, and the third parameter value before manufacturing the obstacle detection device 100, and indicate the case where the obstacle O is a road surface obstacle. It corresponds to the example of the actual measurement value. 9A are actual measured values of the first parameter value, the second parameter value, and the third parameter value before the manufacture of the obstacle detection device 100, and indicate the case where the obstacle O is a road obstacle. It corresponds to the example of the actual measurement value. 9A are actually measured values of the first parameter value, the second parameter value, and the third parameter value before manufacturing the obstacle detection device 100, and indicate the case where the obstacle O is a traveling obstacle. It corresponds to the example of the actual measurement value. The information indicating the ranges A1 to A3 set by the clustering of these actually measured values, more specifically, the information indicating the discrimination thresholds Th1 and Th2 is stored in the obstacle discrimination unit 13 in advance. For the clustering and the setting of the dividing lines PL1 and PL2 (that is, the setting of the discrimination thresholds Th1 and Th2), a machine learning technique such as linear discrimination or pattern recognition is used.

The obstacle determination unit 13 compares the first parameter value, the second parameter value, and the third parameter value calculated after the manufacture of the vehicle 1 (more specifically, after shipment) with the determination thresholds Th1 and Th2. , The first parameter value, the second parameter value, and the third parameter value are included in any of the ranges A1 to A3. Thereby, it is determined whether the obstacle O around the vehicle 1 is a road surface obstacle, a road obstacle, or a running obstacle. The crosses in FIG. 9B correspond to examples of the first parameter value, the second parameter value, and the third parameter value calculated after the shipment of the vehicle 1. In this case, since the first parameter value, the second parameter value, and the third parameter value are included in the range A3, the obstacle O is determined to be a traveling obstacle.

As described above, by using the third parameter value in addition to the first parameter value and the second parameter value, in the determination of the type of the obstacle (that is, the determination of the height of the obstacle), according to the propagation distance of the search wave. Can be considered. As a result, the accuracy of determining the type of the obstacle, that is, the accuracy of determining the height of the obstacle can be improved. More specifically, it is possible to accurately determine a road surface obstacle or a road obstacle located near the vehicle 1 and a traveling obstacle located far from the vehicle 1.

Next, other modifications of the obstacle detection device 100 will be described.

First, the vehicle position calculating unit 26 may calculate the vehicle position by satellite navigation instead of or in addition to autonomous navigation. In this case, the obstacle detection device 100 may acquire a GNSS signal from a GNSS (Global Navigation Satellite Network) receiver provided in the vehicle 1.

The second parameter value may be any value that indicates the magnitude of the variance of the feature value, and is not limited to the variance value of the feature value. For example, the second parameter value may be a difference value between the maximum value and the minimum value of the feature value, a difference value between the maximum value and the average value of the feature value, or the average value and the minimum value of the feature value. It may be a value difference value.

The obstacle determining unit 13 may determine whether an obstacle corresponding to each group is a traveling obstacle. That is, when it is determined that the obstacle is not a traveling obstacle, the obstacle determination unit 13 may not determine whether the obstacle is a road surface obstacle or a road obstacle. The obstacle determination unit 13 may store information indicating the determination threshold Th2, but may not store information indicating the determination threshold Th1.

Further, the distance measuring sensor 2 may be configured by _one distance measuring sensor 21 instead of the _N distance measuring sensors 2 ₁ to 2 _N. In this case, the plurality of reflection points included in each group may be the one corresponding to the direct wave which is sent multiple times received by one of the distance measuring sensor 2 _1.

That is, the plurality of reflection points to be grouped by the grouping unit 25 correspond to direct waves or indirect waves transmitted and received by the _N distance measuring sensors 2 ₁ to 2 _N whose installation positions in the vehicle 1 are different from each other. may be one, or by one of the distance measuring sensor 2 ₁ may be one corresponding to the direct wave which is transmitted and received at different timings from each other. Alternatively, the plurality of reflection points correspond to direct waves or indirect waves transmitted and received at different timings by _N distance measuring sensors 2 ₁ to 2 _N whose installation positions in the vehicle 1 are different from each other. Is also good.

(4) It is preferable that the transmission signal output unit 21 transmits the modulated wave by the frequency modulation or the phase modulation to the distance measurement sensor 2, rather than transmitting the continuous wave or the burst wave to the distance measurement sensor 2. That is, by using a modulated wave as the search wave, the amplitude and phase of the search wave change with respect to time. As a result, interference of a plurality of search waves passing through different propagation paths (for example, interference of a plurality of waves rw in the examples shown in FIGS. 5 and 6) becomes remarkable. Therefore, it is possible to improve the accuracy of determining the type of the obstacle (that is, the accuracy of determining the height of the obstacle) by the obstacle determining unit 13 as compared with the case where a continuous wave or a burst wave is used as the search wave.

As described above, the obstacle detection device 100 according to the first embodiment uses the feature amount relating to a plurality of reflected waves when the distance measurement sensor 2 provided in the vehicle 1 receives the plurality of reflected waves due to the obstacle. A feature amount extraction unit for extracting, and an obstacle discrimination unit for judging that the height of the obstacle is higher when the variance amount of the feature amount is larger than when the variance amount is smaller. And an obstacle determining unit 13 that determines whether or not the obstacle is a traveling obstacle based on the result of clustering the first parameter value indicating the degree of dispersion and the second parameter value indicating the magnitude of the variance. . By using the second parameter value in addition to the first parameter value, the type of the obstacle can be accurately determined, and the height of the obstacle can be accurately determined. Further, it is possible to determine the height of an obstacle located far from the vehicle 1 (more specifically, at a distance of 5 meters or more).

The obstacle determining unit 13 determines the type of the obstacle by identifying which of the plurality of ranges set by the clustering includes the first parameter value and the second parameter value. . Thus, for example, it is possible to determine whether the obstacle is a road surface obstacle, a road obstacle, or a traveling obstacle.

The clustering is a clustering of a first parameter value, a second parameter value, and a third parameter value corresponding to a distance between the vehicle 1 and an obstacle. By determining which of the ranges includes the first parameter value, the second parameter value, and the third parameter value, the type of the obstacle is determined. By using the third parameter value in addition to the first parameter value and the second parameter value, the type of the obstacle can be determined with higher accuracy, and the height of the obstacle can be determined with higher accuracy.

Embodiment 2 FIG.
FIG. 10 is a block diagram illustrating a main part of the driving support device according to the second embodiment. Referring to FIG. 10, a driving support device 200a according to the second embodiment will be described. In FIG. 10, the same reference numerals are given to the same blocks as the blocks shown in FIG. 1, and the description will be omitted.

In the example shown in FIG. 10, the distance measuring sensor 2 is composed of four distance measuring sensors 2 _{1 to} 2 _4. Four distance measuring sensors 2 _{1 to} 2 _4, the front end of the vehicle 1 is provided on (more specifically, the front bumper unit), and are directed to the front of the vehicle 1.

The obstacle detection unit 11 detects an obstacle in front of the vehicle 1 by causing the distance measurement sensor 2 to transmit a search wave at least once when the vehicle 1 is moving forward. The internal configuration of the obstacle detection unit 11 is the same as that described in Embodiment 1 with reference to FIG.

The facing determination unit 14 determines whether or not the distance measuring sensor 2 faces the obstacle. Details of the determination method by the facing determination unit 14 will be described later.

The obstacle determining unit 13 calculates the first parameter value and the second parameter value using the feature amount in a state in which the distance measurement sensor 2 faces the obstacle (hereinafter, referred to as “facing state”). Has become. More specifically, when the number of accumulated data indicating the feature amount in the directly facing state exceeds a predetermined number, the obstacle determination unit 13 uses the feature amount indicated by these data to determine the first parameter value and the second parameter value. The parameter value is calculated. The obstacle determining unit 13 determines the type of the obstacle using the calculated first parameter value and the calculated second parameter value. That is, the obstacle determining unit 13 determines the type of the obstacle using the feature amount in the directly facing state.

The driving support control unit 15a controls the vehicle according to the determination result of the position of the obstacle by the obstacle detection unit 11 and the determination result of the type of the obstacle by the obstacle determination unit 13 (that is, the determination result of the height of the obstacle). This is to execute control for avoiding a collision between the vehicle 1 and an obstacle.

Specifically, for example, when the obstacle detection unit 11 detects an obstacle in front of the vehicle 1, the obstacle determination unit 13 determines that the obstacle is a traveling obstacle or a road obstacle. Then, the driving support control unit 15a executes control to stop the vehicle 1 by operating the brake of the vehicle 1. On the other hand, in this case, when the obstacle determining unit 13 determines that the obstacle is a road surface obstacle, the driving support control unit 15a cancels the execution of the control.

Here, the driving support control unit 15a may vary the stop position of the vehicle 1 depending on whether the obstacle in front of the vehicle 1 is a traveling obstacle or a road obstacle. More specifically, the driving support control unit 15a stops the vehicle 1 at a position on the near side when the obstacle is a traveling obstacle compared to when the obstacle is a road obstacle. It may be. That is, when the obstacle is a road obstacle, the driving support control unit 15a positions the front bumper of the vehicle 1 above the obstacle and causes the front tire of the vehicle 1 to substantially contact the obstacle. The vehicle 1 may be stopped at the position.

Hereinafter, the control in accordance with the determination result of the position of the obstacle by the obstacle detection unit 11 and the determination result of the type of the obstacle by the obstacle determination unit 13 (that is, the determination result of the height of the obstacle) is referred to as “driving support control”. Collectively.

The obstacle detection unit 11, the feature amount extraction unit 12, the obstacle determination unit 13, and the facing determination unit 14 constitute a main part of the obstacle detection device 100a. The obstacle detection device 100a and the driving support control unit 15a constitute a main part of the driving support device 200a.

ハード The hardware configuration of the main part of the driving support device 200a is the same as that described in Embodiment 1 with reference to FIG. That is, each function of the obstacle detection unit 11, the feature amount extraction unit 12, the obstacle determination unit 13, the facing determination unit 14, and the driving support control unit 15a is realized by the processor 31 and the memory 32. Or may be realized by the processing circuit 33.

Next, the operation of the driving support device 200a will be described with reference to the flowchart of FIG.

First, in step ST11, the obstacle detection unit 11 determines whether the vehicle 1 is moving forward using a signal indicating the traveling speed of the vehicle 1, a signal indicating the shift position of the vehicle 1, and the like. These signals are appropriately obtained from a computer network in the vehicle 1.

If the vehicle 1 is moving forward (“YES” in step ST11), the obstacle detection unit 11 causes the distance measurement sensor 2 to transmit the search wave at least once in step ST12, so that the obstacle detection unit 11 is in front of the vehicle 1. Detect obstacles.

により By the process of step ST12, one or more groups corresponding to one or more obstacles in principle one-to-one are set. Each group includes a plurality of reflection points, and the plurality of reflection points correspond to a plurality of reflected waves. Next, in step ST <b> 13, the feature amount extraction unit 12 acquires from the obstacle detection unit 11 information indicating the waveform of the reception signal corresponding to the plurality of reflected waves. The feature amount extraction unit 12 extracts feature amounts related to the plurality of reflected waves using the acquired information. The feature amount extraction unit 12 outputs data indicating the extracted feature amount to the obstacle determination unit 13.

Next, in step ST14, the facing determination unit 14 determines whether or not the distance measuring sensor 2 faces the obstacle. Details of the determination method by the facing determination unit 14 will be described later.

Next, in step ST15, the obstacle determination unit 13 determines whether the number of accumulated data indicating the feature amount in the directly facing state has exceeded a predetermined number. When the accumulation number of the data indicating the feature amount in the facing state is equal to or smaller than the predetermined number (“NO” in step ST15), the process of the driving support device 200a returns to step ST12, and the search wave is transmitted again. On the other hand, when the number of accumulated data indicating the feature amount in the facing state exceeds the predetermined number (“YES” in step ST15), the process of the driving support device 200a proceeds to step ST16.

Next, in step ST16, the obstacle determining unit 13 calculates a first parameter value and a second parameter value using the feature amount in the directly facing state. The obstacle determining unit 13 determines the type of the obstacle corresponding to each group by using the calculated first parameter value and the second parameter value, thereby obtaining the height of the obstacle corresponding to each group. Judge.

Next, in step ST17, the driving support control unit 15a determines the position of the obstacle by the obstacle detection unit 11 and the determination result of the type of the obstacle by the obstacle determination unit 13 (that is, the determination of the height of the obstacle). According to the result, the control for avoiding the collision between the vehicle 1 and the obstacle is executed. That is, the driving support control unit 15a executes the driving support control.

Next, with reference to FIG. 12 to FIG. 14, the details of the determination method by the facing identification unit 14 will be described.

FIG. 12 and FIG. 13 show examples of the installation positions of the _four distance measurement sensors 2 ₁ to 24 in the vehicle 1. 12 and as shown in FIG. 13, 2, which are arranged more inside the four distance measuring sensors 2 _{1 to} 2 measuring sensor 2 ₁ two more are located outside of the _{_four,} 2 ₄ number of the

distance measuring sensor

2 _2, and 2 _3, the installation position with respect to the vertical direction of the vehicle 1 (that is, the height direction) may be different from each other.

FIG. 12 shows propagation paths PP ₁ to PP of direct waves transmitted and received by the _four distance measurement sensors 2 ₁ to 24 when the obstacle O is a traveling obstacle (more specifically, a wall). _4, an example of reflection points RP ₁ to RP ₄ corresponding to these direct waves, and an example of a group G corresponding to the obstacle O are shown. FIG. 13 shows transmission / reception by the _four distance measuring sensors 2 ₁ to 24 when the obstacle O is a road obstacle (more specifically, a curb) or a road surface obstacle (more specifically, a step). 3 shows examples of direct wave propagation paths PP ₁ to PP ₄ , examples of reflection points RP ₁ to RP ₄ corresponding to these direct waves, and an example of a group G corresponding to an obstacle O.

The confronting discrimination unit 14, the distance measurement sensor 2 ₁ 2 in the vehicle _1, 2 ₄ of installation interval (hereinafter referred to as "sensor pitch".) Information indicating the SP is stored in advance. Confronting discrimination unit 14, the distance measurement sensor _{2 1} information obstacles showing the distance _{D 4} between the information indicating the distance _{D 1} of the between reflection points RP ₁ and ranging sensor _{2 4} and the reflection point RP ₄ detecting section 11 To get from. These distances D ₁ and D ₄ correspond to the distance values calculated by the distance value calculation unit 23 or the coordinate values (more specifically, the X coordinate values) calculated by the reflection point position calculation unit 24. . The facing-facing determining unit 14 calculates the facing angle θ of the obstacle O with respect to the distance measuring sensor 2 by the following equation (1).

θ = tan ⁻¹ {(D ₁ −D ₄ ) / SP} (1)

FIG. 14 shows an example of the sensor pitch SP, the distances D ₁ and D _4, and the directly-facing angle θ. When the facing angle θ is equal to or smaller than the predetermined angle θth, the facing determining unit 14 determines that the distance measurement sensor 2 faces the obstacle O. On the other hand, when the facing angle θ is larger than the predetermined angle θth, the facing determining unit 14 determines that the distance measurement sensor 2 is not directly facing the obstacle O.

Note that the calculation of the confronting angle theta, it is preferred to use a distance measuring sensor 2 _1, 2 _4, which is spaced apart from one another via the other of the distance measuring sensor 2 _2, 2 _3. Thus, as compared with the case of using the distance measuring sensor 2 _2, 2 ₃ are arranged adjacent to each other, it is possible to improve the calculation accuracy of the confronting angle theta.

The facing determination unit 14 may calculate the average value of the facing angles θ in a predetermined section. When the calculated average value is equal to or smaller than the predetermined angle θth, the facing determination unit 14 may determine that the distance measurement sensor 2 faces the obstacle O. Thus, the robustness of the discrimination by the facing discrimination unit 14 can be improved.

The predetermined section may be a time section or a distance section. That is, this average value may be an average value of the facing angle θ calculated while the vehicle 1 moves for a predetermined time, or the average value of the facing angle θ calculated while the vehicle 1 moves for a predetermined distance. The average value may be used.

Next, with reference to FIG. 15, a specific example of the feature amount used for calculating the first parameter value and the second parameter value will be described.

FIG. 15A shows an example of the traveling route TR when the vehicle 1 approaches the obstacle O. FIG. 15B shows an example of a temporal change of the facing angle θ at this time. FIG. 15C shows an example of data indicating the feature amount at this time. That is, each circle in FIG. 15C corresponds to data indicating a feature amount.

により When the vehicle 1 approaches the obstacle O as shown in FIG. 15A, the facing angle θ gradually decreases as shown in FIG. 15B. At time t2, the facing angle θ becomes equal to or smaller than the predetermined angle θth, and at time t3, the number of accumulated data indicating the feature amount in the facing state exceeds the predetermined number. In this case, the obstacle determination unit 13 calculates the first parameter value and the second parameter value using the feature amount in the time section Δt2 from time t2 to t3.

The obstacle determining unit 13 determines the type of the obstacle using the feature amount in the directly facing state, and also determines whether the distance measuring sensor 2 is not directly facing the obstacle O (hereinafter referred to as “non-facing”). The type of the obstacle may be determined using the feature amount in “state”). That is, the obstacle determination unit 13 calculates the first parameter value and the second parameter value using the feature amount in the time section Δt2 between the times t2 and t3, and also calculates the feature in the time section Δt1 between the times t1 and t2. The first parameter value and the second parameter value may be calculated using the amounts.

Further, when the obstacle determination unit 13 determines the type of the obstacle using the feature amount in the non-facing state, the obstacle determination unit 13 may notify the driving support control unit 15a that the reliability of the determination result is low. good. The driving support control unit 15a may vary the content of the driving support control according to the degree of reliability notified by the obstacle determination unit 13.

Next, another example of the feature amount used for calculating the first parameter value and the second parameter value will be described with reference to FIGS.

障害 As shown in FIG. 16, the obstacle detection device 100a may not include the facing determination unit 14. In this case, the obstacle determination unit 13 calculates the first parameter value and the second parameter value using the feature amount in a predetermined section (hereinafter, referred to as a “detection section”) Δ. More specifically, when data indicating the feature amount in the detection section Δ is accumulated, the obstacle determining unit 13 calculates a first parameter value and a second parameter value using the feature amount indicated by the data. .

FIG. 17 shows a flowchart in this case. Subsequent to step ST13, in step ST18, the obstacle determination unit 13 determines whether or not data indicating the feature amount in the detection section Δ has been accumulated. When the data indicating the feature amount in the detection section Δ has not been accumulated (“NO” in step ST18), the process of the driving support device 200a returns to step ST12, and the search wave is transmitted again. On the other hand, when the data indicating the feature amount in the detection section Δ has been accumulated (“YES” in step ST18), the process of the driving support device 200a proceeds to step ST16. In step ST16, the obstacle determining unit 13 calculates a first parameter value and a second parameter value using the feature amounts indicated by these data.

具体 A specific example of the determination method in step ST18 is as follows.

For example, the obstacle determining unit 13 acquires from the obstacle detecting unit 11 information indicating the distance value calculated by the distance value calculating unit 23 or information indicating the coordinate value calculated by the reflection point position calculating unit 24. The obstacle determining unit 13 calculates the amount of change in the distance between the vehicle 1 and the obstacle using the acquired information. The obstacle determining unit 13 determines whether or not the vehicle 1 has traveled in the detection section Δ based on the calculated change amount, so that the data indicating the feature amount in the detection section Δ has been accumulated. It is determined whether or not. In FIG. 16, the connection lines between the obstacle detection unit 11 and the obstacle determination unit 13 are not shown.

Or, for example, the obstacle determining unit 13 acquires information indicating the own vehicle position calculated by the own vehicle position calculating unit 26 from the obstacle detecting unit 11. The obstacle determining unit 13 calculates the moving amount of the vehicle 1 using the obtained information. The obstacle determination unit 13 determines whether or not the vehicle 1 has traveled in the detection section Δ based on the calculated movement amount, so that data indicating the feature amount in the detection section Δ has been accumulated. It is determined whether or not. In FIG. 16, the connection lines between the obstacle detection unit 11 and the obstacle determination unit 13 are not shown.

Or, for example, the obstacle determining unit 13 calculates the accumulation time of the data indicating the feature amount. The threshold value corresponding to the predicted value of the accumulation time of the data indicating the feature amount in the detection section Δ is stored in the obstacle determining unit 13 in advance. The obstacle determination unit 13 compares the calculated accumulation time with the previously stored threshold to determine whether or not the data indicating the feature amount in the detection section Δ has been accumulated.

Or, for example, the obstacle determining unit 13 calculates the number of stored data indicating the feature amount. The threshold value corresponding to the predicted value of the number of accumulated data indicating the feature amount in the detection section Δ is stored in the obstacle determining unit 13 in advance. The obstacle determination unit 13 determines whether or not the data indicating the feature amount in the detection section Δ has been stored by comparing the calculated storage number with the threshold value stored in advance.

Alternatively, for example, the obstacle determining unit 13 determines whether or not the data indicating the feature amount in the detection section Δ has been accumulated by each of two or more of the above four methods. . The obstacle determining unit 13 calculates the logical product of the determination results obtained by these methods. That is, the obstacle determination unit 13 determines the determination result when the determination result indicating that the data indicating the feature amount in the detection section Δ has been accumulated by all of these methods.

As shown in FIG. 18, the detection section Δ may be updated at any time in accordance with the movement of the vehicle 1. In this case, the obstacle determination unit 13 may determine the type of the obstacle using the data indicating the feature amount in the latest detection section Δ in which the vehicle 1 has traveled. Alternatively, when data indicating the feature amount in the first detection section Δ1 is accumulated, the obstacle determination unit 13 determines the type of the obstacle using the feature amount indicated by the data, and then determines the type of the obstacle. When data indicating the feature amount in the detection section Δ2 is accumulated, the type of the obstacle is determined using the feature amount indicated by the data, and finally, the data indicating the feature amount in the n-th detection section Δn is obtained. When the information is accumulated, the type of the obstacle may be determined using the feature amount indicated by the data.

As shown in FIG. 18A, the detection sections Δ1 to Δn may gradually increase as the vehicle 1 moves forward. Alternatively, as shown in FIG. 18B, each of the detection sections Δ1 to Δn may have a certain size.

Next, another example of the feature amount used for calculating the first parameter value and the second parameter value will be described with reference to FIG.

In the configuration in which the obstacle detection device 100a includes the facing identification unit 14 (see FIG. 10), the obstacle determination unit 13 calculates a first parameter value and a second parameter value using a feature amount in a predetermined detection section Δ. It may be something to do. That is, when the number of accumulated data indicating the feature amount in the facing state exceeds the predetermined number and the data indicating the feature amount in the detection section Δ has been accumulated, the obstacle determination unit 13 May be used to calculate the first parameter value and the second parameter value using the characteristic amount indicated by.

FIG. 19 shows a flowchart in this case. If the number of accumulated data indicating the feature amount in the facing state exceeds a predetermined number (“YES” in step ST15), in step ST18, the obstacle determination unit 13 determines that the data indicating the feature amount in the detection section Δ It is determined whether or not the data has been stored. When the data indicating the feature amount in the detection section Δ has not been accumulated (“NO” in step ST18), the process of the driving support device 200a returns to step ST12, and the search wave is transmitted again. On the other hand, when the data indicating the feature amount in the detection section Δ has been accumulated (“YES” in step ST18), the process of the driving support device 200a proceeds to step ST16. In step ST16, the obstacle determining unit 13 calculates a first parameter value and a second parameter value using the feature amounts indicated by these data.

Next, another example of the installation positions of the _four distance measurement sensors 2 ₁ to 24 in the vehicle 1 will be described with reference to FIGS.

FIG. 20 and FIG. 21 show other examples of the installation positions of the _four distance measurement sensors 2 ₁ to 24 in the vehicle 1. As shown in Oyobi diagram 21 in FIG. 20, four distance measuring sensors 2 _{1 to} 2 _4, the installation position may be those equivalent to each other with respect to the vertical direction of the vehicle 1 (i.e. a height direction).

Further, FIG. 20 is transmitting, the obstacle O is traveling obstacle when it is (more specifically on the wall), the distance measurement sensor 2 ₁ propagation of the direct wave to be transmitted and received by the path PP _11, the distance measuring sensor 2 ₁ has been measuring sensor 2 of the indirect waves received by _two propagation paths PP _21, the propagation path of the indirect waves received by the distance measurement sensor 2 ₃ is transmitted by the measuring sensor 2 ₁ PP ₃₁ and distance measuring sensor 2 ₁ shows an example of a propagation path PP ₄₁ of the indirect waves received by the distance measurement sensor 2 ₄ is transmitted by. FIG. 20 shows an example of reflection points RP ₁₁ , RP ₂₁ , RP ₃₁ , RP ₄₁ corresponding to these direct waves and indirect waves, and an example of a group G corresponding to the obstacle O.

Further, FIG. 21 (more specifically, a curb) obstacle O is road obstacle or road obstacle when it is (more specifically, the step), the direct wave transmitted and received by the distance measurement sensor 2 ₁ propagation path _{PP 11,} the distance measurement sensor _{2 1} indirect wave propagation paths _{PP 21} which is received by the distance measurement sensor _{2 2} is transmitted by the propagation path _{PP 33} and ranging of the direct wave transmitted and received by the distance measurement sensor _{2 3} sensor 2 ₃ is transmitted by shows an example of a propagation path PP ₄₃ of the indirect waves received by the distance measuring sensor 2 _4. FIG. 21 shows an example of reflection points RP ₁₁ , RP ₂₁ , RP ₃₃ , RP ₄₃ corresponding to these direct waves and indirect waves, and an example of a group G corresponding to the obstacle O.

That is, as described in the first embodiment, the distance value calculation unit 23 calculates the distance value and the reflection point position calculation unit 24 calculates the coordinate value using the indirect wave instead of or in addition to the direct wave. It may be something. By using the indirect wave in addition to the direct wave, the number of reflection points obtained by transmitting the search wave each time can be increased as compared with the case where only the direct wave is used. Thus, the number of reflection points included in each group can be increased. As a result, it is possible to improve the accuracy of determining the position of the obstacle by the obstacle detection unit 11, and also to determine the accuracy of the type of the obstacle by the obstacle determination unit 13, that is, the determination of the height of the obstacle. Accuracy can be improved.

Next, another modified example of the driving support device 200a will be described.

First, the driving support control by the driving support control unit 15a may be a control for avoiding a collision between the vehicle 1 and an obstacle, and is not limited to a control for operating the brake of the vehicle 1. For example, the driving support control by the driving support control unit 15a determines whether there is a possibility that the vehicle 1 will collide with an obstacle, and if it is determined that there is a possibility, the driver 1 of the vehicle 1 is notified of the possibility. The control may be a warning. The driver of the vehicle 1 may stop the vehicle 1 by operating the brake pedal of the vehicle 1 in response to the warning.

Further, the installation positions of the _four distance measurement sensors 2 ₁ to 24 in the vehicle 1 are not limited to the above example. For example, the four distance measuring sensors 2 _{1 to} 2 more two distance measuring sensors are disposed outside 2 _1, 2 ₄ two distance measuring sensors that are disposed more to the inside and 2 ₂ of the ₄ , and 2 _3, the installation position with respect to the longitudinal direction (i.e. the depth direction) of the vehicle 1 may be different from each other.

Both ends measuring sensor 2 ₁ disposed in _portions, 2 ₄ of the four distance measuring sensors 2 _{1 to} 2 ₄ may be one which is directed obliquely forward of the vehicle 1. For example, the distance measurement sensor 2 ₁ may be those which are directed to the left oblique front of the vehicle 1, the distance measuring sensor 2 ₄ may be one which is directed to the right oblique front of the vehicle 1.

Further, the distance measuring sensor 2 may be provided at a rear end portion (more specifically, a rear bumper portion) of the vehicle 1 and may be directed to the rear of the vehicle 1. In this case, the obstacle detection unit 11 detects an obstacle behind the vehicle 1 by causing the distance measurement sensor 2 to transmit the search wave at least once when the vehicle 1 is moving backward. Is also good. Both ends measuring sensor 2 ₁ disposed in _portions, 2 ₄ of the four distance measuring sensors 2 _{1 to} 2 ₄ may be one which is directed obliquely rearward of the vehicle 1.

Further, the number of the distance measuring sensors 2 may be two or more, and is not limited to four. That is, the distance measuring sensor 2 may be one that is constituted by four instead of distance measuring sensor 2 _{1 ~} 2 ₄ N pieces of distance measuring sensors 2 _{1 ~} 2 _N.

The obstacle detection device 100a can employ various modifications similar to those described in the first embodiment, that is, various modifications similar to the obstacle detection device 100.

As described above, the driving support device 200a according to the second embodiment includes the obstacle detection device 100a and the driving support control unit that performs the driving support control according to the result of the determination of the height of the obstacle by the obstacle determination unit 13. 15a. By using the obstacle detection device 100a, the accuracy of the driving support control can be improved.

運転 Driving support control is control related to collision avoidance. By using the obstacle detection device 100a, it is possible to determine the height of an obstacle located far from the vehicle 1 (more specifically, 5 meters or more). As a result, the necessity of executing the control for operating the brake of the vehicle 1 can be determined at an early stage, so that the time for braking can be secured and the occurrence of sudden braking can be suppressed. Further, when an obstacle in front of or behind the vehicle 1 is a road surface obstacle, occurrence of a false alarm can be suppressed. In addition, since it is possible to eliminate restrictions on the installation position of the distance measuring sensor 2 in the vertical direction (that is, the height direction) of the vehicle 1, the design of the vehicle 1 can be improved, and the degree of freedom in design can be improved. Can be.

In addition, the obstacle detection device 100a includes a facing determination unit 14 that determines whether or not the distance measuring sensor 2 is directly facing an obstacle. The type of the obstacle is determined using the feature amount in the facing state. Thereby, the accuracy of determining the type of the obstacle can be further improved.

{Circle around (2)} The obstacle determining unit 13 calculates the second parameter value using the feature amount in the predetermined detection section Δ. Thereby, the reliability of the determination using the second parameter value can be improved.

Embodiment 3 FIG.
FIG. 22 is a block diagram illustrating a main part of the driving support device according to the third embodiment. Referring to FIG. 22, a driving support device 200b according to the third embodiment will be described. In FIG. 22, the same blocks as those shown in FIG. 1 are denoted by the same reference numerals, and description thereof will be omitted.

In the example shown in FIG. 22, the distance measuring sensor 2 is constituted by a single distance measuring sensor 2 _1. One measuring sensor 2 ₁ is provided on the left side surface portion of the vehicle 1, and is directed to the left side of the vehicle 1.

When the vehicle 1 is traveling at a speed equal to or less than a predetermined speed (for example, 30 kilometers per hour), the obstacle detection unit 11 causes the distance measurement sensor 2 to transmit a search wave a plurality of times at predetermined time intervals. It detects an obstacle on the left side of the vehicle 1. The internal configuration of the obstacle detection unit 11 is the same as that described in Embodiment 1 with reference to FIG.

Here, when the distance measurement sensor 2 transmits the search wave once, for example, a plurality of obstacles reflect the search wave, or a plurality of parts in one obstacle reflect the search wave. By doing so, the distance measuring sensor 2 may receive the reflected wave a plurality of times. Hereinafter, the reflection point based on the distance value corresponding to the first reflected wave in this case is referred to as a “recent reflection point”. In this case, the reflection point based on the distance value corresponding to the second and subsequent reflected waves is referred to as a “non-most recently reflected point”.

In this case, the distance value calculator 23 calculates the distance value corresponding to the first reflected wave, but does not calculate the distance value corresponding to the second and subsequent reflected waves. That is, the reflection point position calculation unit 24 calculates the position of the most recent reflection point, but does not calculate the position of the non-most recently reflection point. In other words, the grouping unit 25 includes the most recently reflected point as a grouping target while excluding the non-mostly reflected point from the grouping targets. Thereby, noise included in the detection result by the obstacle detection unit 11 can be reduced.

The driving support control unit 15b performs a so-called “obstruction” according to the result of the determination of the position of the obstacle by the obstacle detection unit 11 and the result of the classification of the obstacle by the obstacle determination unit 13 (that is, the result of the determination of the height of the obstacle). The control for realizing "automatic parking" is executed.

Specifically, for example, the driving support control unit 15b determines whether or not the vehicle 1 can be parked in a space between two adjacent traveling obstacles (more specifically, a parked vehicle). When it is determined that the vehicle 1 can be parked in the space, the driving support control unit 15b controls the accelerator, brake, steering, and the like of the vehicle 1 to guide the vehicle 1 to the space. At this time, the driving support control unit 15b sets the parking position of the vehicle 1 and the guidance route of the vehicle 1 according to the presence and type of the obstacle located on the back side of the two traveling obstacles. . Specific examples of the parking position and the guidance route will be described later.

The obstacle detection unit 11, the feature amount extraction unit 12, and the obstacle determination unit 13 constitute a main part of the obstacle detection device 100b. The obstacle detection device 100b and the driving support control unit 15b constitute a main part of the driving support device 200b.

ハード The hardware configuration of the main part of the driving support device 200b is the same as that described in the first embodiment with reference to FIG. That is, each function of the obstacle detection unit 11, the feature amount extraction unit 12, the obstacle determination unit 13, and the driving support control unit 15b may be realized by the processor 31 and the memory 32, or the processing circuit 33.

Next, the operation of the driving support device 200b will be described with reference to the flowchart in FIG.

First, in step ST21, the obstacle detection unit 11 determines whether the vehicle 1 is traveling at a speed equal to or lower than a predetermined speed, using a signal indicating the traveling speed of the vehicle 1, and the like. These signals are appropriately obtained from a computer network in the vehicle 1.

When the vehicle 1 is traveling at a speed equal to or lower than the predetermined speed (“YES” in step ST21), in step ST22, the obstacle detection unit 11 transmits a plurality of search waves to the distance measurement sensor 2 at predetermined time intervals. By transmitting twice, an obstacle on the left side of the vehicle 1 is detected.

により By the process of step ST22, one or more groups corresponding to one or more obstacles in principle one-to-one are set. Each group includes a plurality of reflection points, and the plurality of reflection points correspond to a plurality of reflected waves. Next, in step ST <b> 23, the feature amount extraction unit 12 acquires from the obstacle detection unit 11 information indicating the waveform of the reception signal corresponding to the plurality of reflected waves. The feature amount extraction unit 12 extracts feature amounts related to the plurality of reflected waves using the acquired information.

Next, in step ST <b> 24, the obstacle determining unit 13 calculates a first parameter value and a second parameter value using the feature amount extracted by the feature amount extracting unit 12. The obstacle determining unit 13 determines the type of the obstacle corresponding to each group by using the calculated first parameter value and the second parameter value, thereby obtaining the height of the obstacle corresponding to each group. Judge.

Next, in step ST25, the driving support control unit 15b determines the position of the obstacle by the obstacle detection unit 11 and determines the type of the obstacle by the obstacle determination unit 13 (that is, determines the height of the obstacle). According to the result, control for realizing automatic parking of the vehicle 1 is executed. That is, the driving support control unit 15b executes the driving support control.

Next, specific examples of the parking position and the guidance route will be described with reference to FIGS.

FIG. 24 shows an example of a detection result by the obstacle detection unit 11. As shown in FIG. 24, it is assumed that three groups G1 to G3 corresponding to three obstacles O1 to O3 have been set by the grouping unit 25. The group G1 includes seven reflection points RP1, the group G2 includes seven reflection points RP2, and the group G3 includes six reflection points RP3. In the figure, TR indicates a traveling route of the vehicle 1 at a speed equal to or lower than a predetermined speed.

Each of the two obstacles O1 and O2 is a parked vehicle in parallel parking. Therefore, the obstacle determining unit 13 determines that each of the two obstacles O1 and O2 is a running obstacle. The driving support control unit 15b determines whether or not the vehicle 1 can be parked in the space S by comparing the size of the space S between the two obstacles O1 and O2 with the size of the vehicle 1. In the example shown in FIG. 24, since the size of the space S is larger than the size of the vehicle 1, it is determined that the vehicle 1 can be parked in the space S.

Here, the obstacle O3 located on the back side of the two obstacles O1 and O2 is a wall, a curb or a step. When the obstacle O3 is a wall, the obstacle determination unit 13 determines that the obstacle O3 is a traveling obstacle. When the obstacle O3 is a curb, the obstacle determination unit 13 determines that the obstacle O3 is a road obstacle. When the obstacle O is a step, the obstacle determination unit 13 determines that the obstacle O3 is a road surface obstacle.

FIG. 25 illustrates an example of the guidance route GR of the vehicle 1 and the parking position of the vehicle 1 when the obstacle O3 is determined to be a traveling obstacle. When it is determined that the obstacle O3 is a traveling obstacle, the driving support control unit 15b guides the vehicle 1 through a route that does not cause the vehicle 1 to collide with the obstacle O3. The driving support control unit 15b parks the vehicle 1 at a position where a space between the vehicle 1 and the obstacle O3 is secured. This space is a space for passengers to get on and off.

FIG. 26 illustrates an example of the guidance route GR of the vehicle 1 and the parking position of the vehicle 1 when the obstacle O3 is determined to be a road obstacle or a road surface obstacle. When it is determined that the obstacle O3 is a road obstacle or a road surface obstacle, the driving support control unit 15b guides the vehicle 1 through a route such that the rear bumper of the vehicle 1 passes above the obstacle O3. . The driving support control unit 15b parks the vehicle 1 at a position where the left side of the vehicle 1 is along the obstacle O3, more specifically, at a position where the left side of the vehicle 1 is along the reflection point RP3.

FIG. 27 shows an example of the guidance route GR of the vehicle 1 and the parking position of the vehicle 1 when the obstacle O3 does not exist. When the obstacle O3 does not exist, the driving support control unit 15b determines that the position of the left side of the vehicle 1 in the depth direction is aligned with the position of the left side of the parked vehicle, that is, the position of the right side of the vehicle 1 in the depth direction. The vehicle 1 is parked so as to be aligned with the right side of the parked vehicle.

Next, a modified example of the driving support device 200b will be described with reference to FIGS.

In the above example, the reflection point position calculation unit 24 calculates the position of the nearest reflection point, but does not calculate the position of the non-closest reflection point. In other words, the grouping unit 25 includes the most recently reflected point as a grouping target while excluding the non-mostly reflected point from the grouping target.

On the other hand, in the following modified example, the reflection point position calculation unit 24 calculates not only the position of the most recent reflection point but also the position of the non-most recently reflection point. In other words, the grouping unit 25 not only includes the most recently reflected point in the grouping target, but also includes the non-most recently reflected point in the grouping target.

For example, as shown in FIG. 28, there is a wall or a curb (obstacle O3) on the back side of a parked vehicle (obstacle O1, O2) in parallel parking, and a parked vehicle (obstacle O1, O2) in parallel parking. It is assumed that there is a step (obstacle O4) in front of (). That is, it is assumed that there is a step (obstacle O4) between the vehicle 1 and the parked vehicle (obstacles O1, O2). When the reflection point position calculation unit 24 calculates only the position of the latest reflection point, as shown in FIG. 29A, only the position of the reflection point RP4 corresponding to the obstacle O4 is calculated and corresponds to the obstacle O4. Only the group G4 is set. As a result, since other obstacles O1 to O3 are not detected, it is not possible to determine whether the vehicle 1 can be parked in the space S. In addition, the parking position of the vehicle 1 and the guidance route of the vehicle 1 cannot be set. That is, there is an erroneous determination that the vehicle 1 cannot be parked even though there is a space S where the vehicle 1 can be parked.

On the other hand, as shown in FIG. 29B, the positions of the reflection points RP1 to RP4 corresponding to the obstacles O1 to O4 are calculated by the reflection point position calculation unit 24 calculating the positions of the latest reflection point and the non-most recent reflection point. The calculated groups G1 to G4 corresponding to the obstacles O1 to O4 are set. Further, each of the two obstacles O1 and O2 is determined to be a traveling obstacle, the rear obstacle O3 is determined to be a traveling obstacle or a road obstacle, and the front obstacle O4 is determined. Is determined to be a road surface obstacle. Therefore, it is possible to determine whether or not the vehicle 1 can be parked in the space S, and to set the parking position of the vehicle 1 and the guidance route of the vehicle 1. When guiding the vehicle 1, the accelerator, brake, steering, and the like of the vehicle 1 can be controlled so that the vehicle 1 gets over the obstacle O4.

Alternatively, for example, as shown in FIG. 30, there is a curb (obstacle O3) behind the parked vehicle (obstacles O1 and O2) in parallel parking, and the parked vehicle (obstacles O1 and O2) in parallel parking. It is assumed that there is a step (obstacle O4) in front of (). That is, it is assumed that there is a parking space S having a so-called “two-step curb structure”. In this case, the positions of the reflection points RP1 to RP4 corresponding to the obstacles O1 to O4 are calculated by the reflection point position calculation unit 24 calculating the positions of the latest reflection point and the non-closest reflection point, and the obstacles O1 to O4 are calculated. Groups G1 to G4 corresponding to O4 are set. Further, each of the two obstacles O1 and O2 is determined to be a traveling obstacle, the rear obstacle O3 is determined to be a road obstacle, and the front obstacle O4 is determined to be a road obstacle. Is determined. Therefore, it is possible to determine whether or not the vehicle 1 can be parked in the space S, and to set the parking position of the vehicle 1 and the guidance route of the vehicle 1. When guiding the vehicle 1, the accelerator, brake, steering, and the like of the vehicle 1 can be controlled so that the vehicle 1 gets over the obstacle O4.

Alternatively, for example, as shown in FIG. 31, there is a wall (obstacle O3) behind the parked vehicle (obstacles O1 and O2) in parallel parking and the parked vehicle (obstacles O1 and O2) in parallel parking. It is assumed that there is a wheel stop (obstacle O4) in between. In this case, the positions of the reflection points RP1 to RP4 corresponding to the obstacles O1 to O4 are calculated by the reflection point position calculation unit 24 calculating the positions of the latest reflection point and the non-closest reflection point, and the obstacles O1 to O4 are calculated. Groups G1 to G4 corresponding to O4 are set. Further, each of the two obstacles O1 and O2 is determined to be a traveling obstacle, the obstacle O3 on the far side is determined to be a road obstacle, and the distance between the two obstacles O1 and O2 is determined. The obstacle O3 is determined to be a road obstacle. Therefore, it is possible to determine whether or not the vehicle 1 can be parked in the space S, and to set the parking position of the vehicle 1 and the guidance route of the vehicle 1. Further, the vehicle 1 can be parked at a position where the rear bumper portion of the vehicle 1 is located above the obstacle O4 and the rear bumper portion of the vehicle 1 does not collide with the obstacle O3.

Also, by using the height determination results for each of the two groups (for example, groups G3 and G4 in FIG. 31) arranged close to each other, these groups correspond to different obstacles. , Or whether they correspond to the same obstacle. That is, whether the reflection points included in these groups correspond to the reflection waves due to different obstacles or to the reflection points due to the same obstacle (so-called “multiple reflection waves”). Can be identified. The obstacle detection unit 11 may execute the identification using the result of the determination of the height of the obstacle by the obstacle determination unit 13.

Next, another modified example of the driving support device 200b will be described.

First, the driving support control by the driving support control unit 15b may be any control related to the parking support of the vehicle 1, and is not limited to the control for realizing the automatic parking of the vehicle 1. For example, the driving support control by the driving support control unit 15b may be control for setting a parking position of the vehicle 1 and notifying the driver of the vehicle 1 of the set parking position. The driver of the vehicle 1 may park the vehicle 1 by so-called “manual parking” at the notified parking position.

The distance measuring sensor 2 may be provided on the right side of the vehicle 1 and directed to the right of the vehicle 1. In this case, when the vehicle 1 is traveling at a speed equal to or lower than the predetermined speed, the obstacle detection unit 11 causes the distance measurement sensor 2 to transmit the search wave a plurality of times at predetermined time intervals, thereby enabling the vehicle 1 It may detect an obstacle on the right side.

Further, the number of the distance measuring sensors 2 may be one or more, and is not limited to one. That is, the distance measuring sensor 2 may be one that is constituted by one instead of the distance measuring sensor 2 ₁ N pieces of distance measuring sensors 2 _{1 ~} 2 _N.

The obstacle detection device 100b can employ various modifications similar to those described in the first embodiment, that is, various modifications similar to the obstacle detection device 100.

As described above, the driving assistance device 200b according to the third embodiment includes the obstacle detection device 100b and the driving assistance control unit that performs the driving assistance control according to the result of the determination of the height of the obstacle by the obstacle determination unit 13. 15b. By using the obstacle detection device 100b, the accuracy of the driving support control can be improved.

運転 Driving support control is control related to parking support. By using the obstacle detection device 100b, the parking position of the vehicle 1 and the guidance route of the vehicle 1 can be appropriately set according to the position and height of each of the plurality of obstacles. In addition, it is possible to realize parking support corresponding to a parking lot having a two-step curb structure.

In addition, the obstacle detection device 100b includes an obstacle detection unit 11 that determines a position of a plurality of obstacles by grouping a plurality of reflection points corresponding to a plurality of reflected waves. The obstacle determination unit 13 includes a reflection point and a non-closest reflection point, and determines the height of each of the plurality of obstacles. This makes it possible to identify, for a plurality of groups arranged close to each other, whether these groups correspond to different obstacles or to the same obstacle. .

Embodiment 4 FIG.
FIG. 32 is a block diagram showing a main part of the driving support device according to Embodiment 4. With reference to FIG. 32, a driving support device 200c according to the fourth embodiment will be described. In FIG. 32, the same reference numerals are given to the same blocks as the blocks shown in FIG. 1, and the description will be omitted.

The vehicle 1 has a camera 3 for imaging outside the vehicle. The installation direction of the camera 3 in the vehicle 1 is equivalent to the installation direction of the distance measurement sensor 2 in the vehicle 1. Therefore, when an obstacle is detected by the obstacle detection unit 11, the image captured by the camera 3 includes the detected obstacle. The camera 3 is configured by, for example, a visible light camera or an infrared camera.

The driving support control unit 15c acquires image data indicating an image captured by the camera 3 from the camera 3. The driving support control unit 15c executes control for displaying an image indicated by the acquired image data, that is, an image captured by the camera 3 on the display device 4. The display device 4 is provided on, for example, a dashboard of the vehicle 1. The display device 4 is configured by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display.

Here, the driving support control unit 15c determines the area corresponding to the obstacle in the captured image based on the determination result of the position of the obstacle by the obstacle detection unit 11 and the determination result of the height of the obstacle by the obstacle determination unit 13. Is superimposed with a marker image. In addition, the driving support control unit 15c sets the mode (for example, color) of each marker image according to the result of the obstacle type determination performed by the obstacle determination unit 13.

FIG. 33 illustrates an example of a state where the marker images MI1 and MI2 are superimposed and displayed on the captured image CI. In the example illustrated in FIG. 33, the captured image CI includes a wall (obstacle O1) and a curb (obstacle O2). The marker image MI1 is superimposed and displayed on the area corresponding to the obstacle O1 in the captured image CI, and the marker image MI2 is superimposed and displayed on the area corresponding to the obstacle O2 in the captured image CI. The marker images MI1 and MI2 have different colors. In the figure, the hatching of the marker images MI1 and MI2 corresponds to the colors of the marker images MI1 and MI2.

The obstacle detection unit 11, the feature amount extraction unit 12, and the obstacle discrimination unit 13 constitute a main part of the obstacle detection device 100. The main part of the driving support device 200c is configured by the obstacle detection device 100 and the driving support control unit 15c.

ハード The hardware configuration of the main part of the driving support device 200c is the same as that described in the first embodiment with reference to FIG. That is, each function of the obstacle detection unit 11, the feature amount extraction unit 12, the obstacle determination unit 13, and the driving support control unit 15c may be realized by the processor 31 and the memory 32, or the processing circuit 33.

Next, the operation of the driving support device 200c will be described with reference to the flowchart in FIG. In FIG. 34, steps that are the same as the steps shown in FIG. 4 are given the same reference numerals, and descriptions thereof will be omitted.

次いで Subsequent to step ST3, in step ST4, the driving support control unit 15c executes control to display the image captured by the camera 3 on the display device 4. At this time, the driving support control unit 15c superimposes and displays the marker image on a region corresponding to the obstacle in the captured image. That is, the driving support control unit 15c executes the driving support control.

Next, a modified example of the driving support device 200c will be described with reference to FIG.

The driving support control by the driving support control unit 15c is based on the determination result of the position of the obstacle by the obstacle detection unit 11 and the determination result of the height of the obstacle by the obstacle determination unit 13 (that is, the determination result of the type of the obstacle). Any control may be used as long as the information (hereinafter referred to as “result information”) is presented to the occupant of the vehicle 1. The presentation of the result information may be based on the image display as described above, or may be based on the following audio output.

That is, as shown in FIG. 35, the vehicle 1 is provided with the audio output device 5. The audio output device 5 is configured by, for example, a speaker.

The driving support control unit 15c controls the audio output device 5 to output an announcement sound indicating the position of the obstacle determined by the obstacle detection unit 11 and the type of the obstacle determined by the obstacle determination unit 13, for example. Execute. Alternatively, for example, when the obstacle detection unit 11 detects an obstacle, the driving support control unit 15c executes control to cause the audio output device 5 to output a beep sound. At this time, the driving support control unit 15c makes the height of the beep sound correspond to the height of the obstacle determined by the obstacle determination unit 13.

Next, another modified example of the driving support device 200c will be described.

First, the driving support device 200c may have the obstacle detection device 100a instead of the obstacle detection device 100. In this case, in addition to the control for presenting the result information, the driving support control unit 15c may execute control related to collision avoidance (that is, control similar to the driving support control by the driving support control unit 15a). .

運転 Further, the driving support device 200c may include the obstacle detection device 100b instead of the obstacle detection device 100. In this case, in addition to the control for presenting the result information, the driving support control unit 15c may execute control related to parking support (that is, control similar to the driving support control by the driving support control unit 15b). .

As described above, the driving support device 200c according to the fourth embodiment executes the driving support control according to the result of the determination of the height of the obstacle by the

obstacle detection devices

100, 100a, and 100b and the obstacle determination unit 13. And a driving support control unit 15c. By using the

obstacle detection devices

100, 100a, and 100b, the accuracy of the driving support control can be improved.

運転 Driving support control is control related to information display by image display or sound output. By using the

obstacle detection devices

100, 100a, and 100b, highly accurate result information can be presented to the occupants of the vehicle 1.

In the present invention, any combination of the embodiments, a modification of an arbitrary component of each embodiment, or an omission of any component in each embodiment is possible within the scope of the invention. .

The obstacle detection device of the present invention can be applied to, for example, control related to collision avoidance or parking assistance.

1 vehicle, 2 distance measuring sensor, 3 camera, 4 display device, 5 audio output device, 11 obstacle detection unit, 12 feature amount extraction unit, 13 obstacle identification unit, 14 facing identification unit, 15a, 15b, 15c driving Support control unit, 21 transmission signal output unit, 22 reception signal acquisition unit, 23 distance value calculation unit, 24 reflection point position calculation unit, 25 grouping unit, 26 own vehicle position calculation unit, 27 sensor position calculation unit, 31 processor, 32 memory, 33 processing circuit, 100, 100a, 100b obstacle detection device, 200a, 200b, 200c driving support device.

Claims

A feature value extraction unit that extracts a plurality of feature values related to the reflected waves when the distance measurement sensor provided in the vehicle receives a plurality of reflected waves due to the obstacle;
An obstacle determining unit that determines that the height of the obstacle is higher when the variance of the feature amount is larger than when the variance amount is smaller, and a first parameter indicating the magnitude of the feature amount An obstacle determining unit that determines whether at least the obstacle is a running obstacle based on a result of clustering of the second parameter value indicating the value and the magnitude of the variance;
Obstacle detection device comprising:
The feature amount is an amount corresponding to the size of each of the plurality of reflected waves,
The obstacle detection device according to claim 1, wherein the first parameter value is an average value of amounts corresponding to the magnitudes of the plurality of reflected waves.
The obstacle detection device according to claim 1, wherein the characteristic amount is a wave height, a wave width, a waveform area, or a response time of each of the plurality of reflected waves.
The obstacle determining unit identifies the type of the obstacle by identifying which of the plurality of ranges set by the clustering includes the first parameter value and the second parameter value. The obstacle detecting device according to claim 1, wherein the obstacle is detected.
5. The obstacle detection device according to claim 4, wherein the obstacle determination unit determines whether the obstacle is one of a road surface obstacle, a road obstacle, and the traveling obstacle.
An obstacle detection device according to claim 5,
A driving support control unit that performs driving support control according to the result of determining the height of the obstacle by the obstacle determination unit,
A driving assistance device comprising:
7. The driving support device according to claim 6, wherein the driving support control is a control related to parking support.
7. The driving support apparatus according to claim 6, wherein the driving support control is control related to collision avoidance.
7. The driving support device according to claim 6, wherein the driving support control is a control relating to information display by image display or voice output.
The clustering is the clustering of the first parameter value, the second parameter value, and a third parameter value corresponding to a distance between the vehicle and the obstacle,
The obstacle determining unit identifies which of the plurality of ranges set by the clustering includes the first parameter value, the second parameter value, and the third parameter value, The obstacle detection device according to claim 4, wherein a type of the obstacle is determined.
By grouping a plurality of reflection points corresponding to a plurality of the reflected waves, comprising an obstacle detection unit that determines the position of the plurality of obstacles,
The plurality of reflection points include a most recent reflection point and a non-most recently reflection point,
The obstacle detection device according to claim 1, wherein the obstacle determination unit determines a height of each of the plurality of obstacles.
2. The obstacle detection device according to claim 1, wherein the plurality of reflected waves are received by the plurality of distance measurement sensors having different installation positions.
2. The obstacle detecting device according to claim 1, wherein the plurality of reflected waves are received at different timings by a single distance measuring sensor.
2. The obstacle detection device according to claim 1, wherein the plurality of reflected waves are received by the plurality of distance measurement sensors having different installation positions at different timings. 3.
A facing determination unit that determines whether the distance measurement sensor is facing the obstacle,
The obstacle detection device according to claim 1, wherein the obstacle determination unit determines the type of the obstacle using the feature amount in a state where the distance measurement sensor faces the obstacle. .
The facing determination unit calculates a facing angle of the obstacle with respect to the distance measuring sensor, and determines that the distance measuring sensor is facing the obstacle when the facing angle is equal to or less than a predetermined angle. The obstacle detection device according to claim 15, wherein
The facing determination unit calculates the facing angle using the ranging sensors that are spaced apart from each other via another ranging sensor among the plurality of ranging sensors. The obstacle detection device according to claim 16.
The obstacle determining unit is configured to use the feature amount indicated by the data when the accumulated number of data indicating the feature amount in a state where the distance measurement sensor faces the obstacle exceeds a predetermined number. The obstacle detection device according to claim 15, wherein a type of the obstacle is determined.
18. The obstacle detecting device according to claim 17, wherein the facing angle uses an average value in a predetermined section in time or distance.