JP2004069328A - Forward environment recognizing device and forward environment recognizing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a forward environment recognizing device and a forward environment recognizing method for accurately determining whether a toll booth exists forward in the traveling direction of an own vehicle. <P>SOLUTION: This forward environment recognizing device is equipped with a laser radar 11 for detecting reflection points at which laser light is reflected to measure the relative position of each reflection point in relation to the own vehicle. This device is equipped with an object detection part 12 for detecting a forward object by calculating that reflection points close to each other are points on the same object among the reflection points, and an object kind determining part 13 for measuring the number of reflection points included in the forward object to determine the forward object to be a toll booth when the number of relevant reflection points is larger than a reference value. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a forward environment recognizing device and a forward environment recognizing method for determining whether a tollgate is present ahead of a traveling direction of a vehicle.
[0002]
[Prior art]
2. Description of the Related Art Conventionally, as a forward environment recognition device that determines whether or not a tollgate is present ahead of a traveling direction of a vehicle, for example, a technology disclosed in Japanese Patent Application Laid-Open No. 2001-134794 is known.
[0003]
The forward environment recognition device calculates the own vehicle position, acquires map data around the own vehicle position from the map database, and collates the own vehicle position with the map data to thereby charge the vehicle ahead in the traveling direction of the own vehicle. To determine if the location exists.
[0004]
[Problems to be solved by the invention]
However, since a tollgate may be newly constructed, the map database must be frequently updated in order for the forward environment recognition device to make the above-described determination accurately. However, a map database in which tollgates are stored is relatively expensive.
[0005]
For this reason, the forward environment recognition apparatus has a problem that it is relatively expensive to accurately perform the above-described determination.
[0006]
The present invention has been made to solve such a conventional problem, and its main purpose is to determine whether there is a tollgate ahead of the vehicle in the traveling direction without using a map database. It is an object of the present invention to provide a forward environment recognition device and a forward environment recognition method capable of accurately determining the forward environment.
[0007]
[Means for Solving the Problems]
In order to achieve the above-described object, the invention described in the claims of the present application includes: a reflection point detecting unit that detects a reflection point reflecting a detection wave and measures a relative position of the reflection point with respect to the own vehicle; By predicting that the reflection points close to each other among the points are points on the same object, the object detection means for detecting the front object and the number of reflection points included in the front object are measured, and the number of the reflection points is determined. Is larger than the reference value, an object type discriminating means for judging the preceding object as a tollgate is mainly provided.
[0008]
【The invention's effect】
According to the forward environment recognition device described in the claims of the present application, the following effects can be mainly obtained.
[0009]
That is, the number of reflection points detected when scanning a tollgate is much larger than the number of reflection points detected when scanning another forward object.
[0010]
Therefore, by setting the reference value to be larger than the number of reflection points detected when scanning another front object, the front environment recognition device determines that the front object is a toll gate by the above-described determination. Can be determined.
[0011]
In other words, the forward environment recognition device can accurately determine whether a tollgate exists ahead of the own vehicle in the traveling direction without using the map database.
[0012]
BEST MODE FOR CARRYING OUT THE INVENTION
(First embodiment)
Hereinafter, a first embodiment of the present invention (corresponding to the invention described in any one of claims 1, 7 and 12) will be described with reference to the drawings.
[0013]
First, the configuration of the forward environment recognition device 1 according to the present invention will be described with reference to FIGS. 1 to 5 and FIG.
[0014]
Here, FIG. 1 is a block diagram showing a configuration of the forward environment recognition device 1, FIG. 2 is a schematic side view showing an installation position of the laser radar 11, and FIG. FIG.
[0015]
4 and 5 are side views showing a detectable range 11c of the laser radar 11, and FIG. 7 is a schematic plan view showing a reflection point and a position of a front object.
[0016]
The forward environment recognition device 1 is installed in the own vehicle 10 shown in FIG. 2, and as shown in FIG. 1, a scanning laser radar (reflection point detecting means) (hereinafter, referred to as “laser radar”) 11, an object detection (Object detecting means) 12, an object type determining section (object type determining means) 13, and a control section (control content determining means) 14.
[0017]
The laser radar 11 is provided in front of the own vehicle 10 as shown in FIGS. 2 and 3, scans the front of the own vehicle 10 with a laser beam (detection wave) a plurality of times, and reflects the reflected laser. Light (hereinafter, referred to as “reflected light”) is detected.
[0018]
Thereby, the laser radar 11 detects the reflection points that reflect the laser light, the distance from the own vehicle to each reflection point, the azimuth of each reflection point with respect to the own vehicle, and the laser light reflected at each reflection point. (Hereinafter, referred to as “reflection point intensity”).
[0019]
Then, the laser radar 11 creates reflection point information on the detection result and the measurement result and outputs the information to the object detection unit 12.
[0020]
Here, as shown in FIGS. 4, 5 and 7, the laser radar 11 performs scanning by emitting a laser beam a predetermined number of times while shifting its optical axis by a unit angle.
[0021]
In addition, as shown in FIGS. 4 and 5, in each scanning, the angle formed by the laser beam 11a emitted from the top in the side view and the laser beam 11b emitted from the bottom is set in the height direction. The detection angle is set, and its magnitude, that is, the detection angle is set to β.
[0022]
The object detection unit 12 includes a memory 12a and a detection processing unit 12b.
[0023]
The memory 12a stores the reflection point information given from the laser radar 11.
[0024]
The detection processing unit 12b acquires the reflection point information stored in the memory 12a, detects the front objects based on the reflection point information, and detects the size of each detected front object, the relative position with respect to the own vehicle 10, And the relative speed v to the own vehicle 10 is measured.
[0025]
Then, the detection processing unit 12b creates detection result information on the detection result and the measurement result, and stores the information in the memory 13a of the object type determination unit 13.
[0026]
The object type determination unit 13 includes a memory 13a and a determination processing unit 13b.
[0027]
The memory 13a stores the detection result information provided from the detection processing unit 12b.
[0028]
The determination processing unit 13b acquires the detection result information from the memory 13a, and determines the type of the forward object based on the detection result information.
[0029]
Then, the determination processing unit 13b creates determination result information regarding the determination result and the like, and outputs it to the control unit 14.
[0030]
The control unit 14 determines the control content of the own vehicle 10 and the like based on the determination result information provided from the determination processing unit 13b.
[0031]
Next, a procedure of processing by the front environment recognition device 1 will be described with reference to FIGS.
[0032]
Here, FIG. 6 is a flowchart showing a procedure of processing by the front environment recognition device 1, and FIGS. 8 to 9 and FIG. 11 are schematic plan views showing reflection points and positions of front objects. FIG. 10 is an explanatory diagram showing a state ahead of the own vehicle 10 in the traveling direction.
[0033]
First, the procedure of the process performed by the front environment recognition device 1 will be described with reference to an example in which the vehicles 20 to 21, the toll booths 30 to 31, and the delineator 40 exist in the forward direction of the vehicle 10 as shown in FIG. I do.
[0034]
The front environment recognition device 1 can also perform the following processing in other cases.
[0035]
In step S1a (reflection point detection step) shown in FIG. 6, as shown in FIG. 7, the laser radar 11 scans the area in front of the vehicle 10, that is, the detectable range 11c, with a laser beam a plurality of times. A reflection point that reflects the laser light is detected.
[0036]
Here, the vehicle includes a reflex reflector or the like as an object that reflects laser light, and the tollgate includes a reflector or the like as an object that reflects laser light. In addition, road signs such as a delineator and a center pole also include a reflector that reflects laser light.
[0037]
Therefore, the laser radar 11 can detect a reflection point on a vehicle, a tollgate, and a road sign.
[0038]
Next, the laser radar 11 measures the distance from each reflection point to the own vehicle 10, the direction of each reflection point with respect to the own vehicle 10, and the intensity of each reflection point.
[0039]
Next, the laser radar 11 creates reflection point information on the detection result and the measurement result, and stores the information in the memory 12a.
[0040]
Next, in step S2a (object detection step) shown in FIG. 6, the detection processing unit 12b acquires the reflection point information from the memory 12a, and calculates the relative position of each reflection point with respect to the own vehicle 10 as follows.
[0041]
That is, as shown in FIGS. 2 and 3, the detection processing unit 12 b sets the x-axis in a direction parallel to the road surface and perpendicular to the traveling direction of the vehicle 10 with the emission point of the laser beam as the origin. Take. Furthermore, the detection processing unit 12b defines the xyz space by taking the z-axis in the traveling direction of the vehicle 10 and the y-axis in a direction perpendicular to the road surface.
[0042]
Next, the detection processing unit 12b regards each reflection point as a point in the xyz space, calculates coordinates of each reflection point, and sets the coordinates as a relative position of each reflection point with respect to the own vehicle 10.
[0043]
Next, the detection processing unit 12b detects the front objects A1 to E1 as illustrated in FIG. 7 by predicting the reflection points that are close to each other as the reflection points on the same object, and further, detects the size of each front object. And the relative position to the vehicle 10 is measured.
[0044]
Next, the detection processing unit 12b creates detection result information on the detection result and the measurement result and stores the information in the memory 12a.
[0045]
In step S3a, the detection processing unit 12b measures the relative speed v of each forward object and adds the relative speed v to the detection result information, as shown in FIGS.
[0046]
Here, a procedure for measuring the relative speed will be described.
[0047]
First, the forward environment recognition device 1 performs the processing of steps S1a to S2a after a lapse of time Δt after performing the processing of steps S1a to S2a (the time at which the processing is performed is referred to as t−Δt). Do it again.
[0048]
As a result, the detection processing unit 12b detects the front objects A2 to E2 and F1 as shown in FIG. 8, and measures the size and relative position of each detected front object. Further, the detection processing unit 12b stores the detection result information in the memory 12a.
[0049]
Next, the detection processing unit 12b acquires the detection result information at the time t-Δt and the detection result information at the time t from the memory 12a.
[0050]
Next, as illustrated in FIG. 9, the detection processing unit 12b compares the size and relative position of each forward object detected at time t-Δt, and the size and relative position of each forward object detected at time t. , Illuminate.
[0051]
As a result, the detection processing unit 12b regards front objects having substantially the same size and having a relative position at the time t-Δt and a close relative position at the time t as the same front object.
[0052]
Specifically, the detection processing unit 12b regards the front object A1 and the front object A2 as the same front object.
[0053]
Similarly, the detection processing unit 12b regards the front object B1 and the front object B2 as the same and the front object C1 and the front object C2 as the same front object.
[0054]
Similarly, the detection processing unit 12b regards the front object D1 and the front object D2 and the front object E1 and the front object E2 as the same front object.
[0055]
Note that the detection processing unit 12b regards the front object F1 as a front object newly detected at time t because no other front object exists near the front object F1.
[0056]
Next, the detection processing unit 12b measures the relative velocity v of each forward object using the following equation (1).
[0057]
v = (R (t) −R (t−Δt)) / Δt (1)
Here, R (t) is the relative position coordinate of the forward object at time t, and R (t-Δt) is the relative position coordinate of the forward object at time t-Δt.
[0058]
Next, in step S4a (object type determination step), the determination processing unit 13b acquires detection result information from the memory 13a.
[0059]
Next, the determination processing unit 13b determines the type of the forward object based on the detection result information as follows.
[0060]
That is, the determination processing unit 13b measures the number of reflection points included in the front object, and compares the number of the reflection points with a reference value n1 predetermined for the number of the reflection points.
[0061]
Next, when the number of reflection points included in the front object is larger than the reference value n1, the determination processing unit 13b determines the front object (the front objects D1 and E1 in this example) as a toll gate.
[0062]
Here, the reason why the determination is possible will be described.
[0063]
That is, the tollgate is provided with a plurality of objects (for example, a reflector, a toll payment machine, a pole cone, and a lamp) that reflect laser light. For this reason, the number of reflection points detected when scanning a tollgate is significantly larger than the number of reflection points detected when scanning a forward object other than a tollgate.
[0064]
Therefore, by setting the reference value n1 to be very large as compared with the number of reflection points detected when scanning a forward object other than the tollgate, the determination processing unit 13b determines that the number of reflection points is small. A forward object larger than the reference value n1 can be determined as a toll gate.
[0065]
On the other hand, when the number of reflection points included in the front object is smaller than the reference value n1, the determination processing unit 13b determines the type of the front object based on the size, the relative position, and the relative speed v. I do.
[0066]
For example, the discrimination processing unit 13b detects the front objects D1 and E1 determined as tollgates on the traveling direction side of the vehicle 10 and moves the front objects (the front objects that have moved in the past). In this example, the forward objects A1 and B1) are determined to be vehicles.
[0067]
In addition, the determination processing unit 13b determines that the front object (the front object C1 in this example), which is smaller than the vehicle and is stopped, is a road sign.
[0068]
Next, the determination processing unit 13b acquires the distance from the own vehicle 10 to the front object determined as the tollgate, that is, the distance from the own vehicle 10 to the tollgate from the detection result information.
[0069]
Next, the determination processing unit 13b creates determination result information on the size of each forward object, the relative position with respect to the own vehicle 10, the relative speed v, the distance from the own vehicle 10 to the tollgate, and the determination result. The information is stored in the memory 13a shown in FIG.
[0070]
Next, in step S5a shown in FIG. 6, the control unit 14 performs control of the own vehicle 10 and contents of an alarm for an occupant of the own vehicle 10 (hereinafter, “ Control content and alarm content of the vehicle 10).
[0071]
Here, as the control contents, for example, when there is a tollgate, control to reduce the speed of the own vehicle 10, control to stop in the tollgate, and when the own vehicle 10 has an ETC, And control to pass through the tollgate as it is. Further, if the vehicle 10 is equipped with the ACC, there is also a control of stopping the control by the ACC.
[0072]
Further, as the contents of the alarm, for example, when there is a tollgate, there is a notification of information indicating that "the tollgate is approaching".
[0073]
As described above, according to the first embodiment, the forward environment recognition device 1 can accurately determine whether the forward object existing ahead of the own vehicle in the traveling direction is a tollgate.
[0074]
In other words, the forward environment recognition device 1 can accurately determine whether a tollgate exists ahead of the vehicle in the traveling direction without using a map database (corresponding to claim 1 or 7). Effect).
[0075]
Furthermore, the forward environment recognition device 1 can determine the control content and the warning content of the own vehicle 10 according to the result of the determination (an effect corresponding to the seventh aspect of the invention).
[0076]
In particular, the forward environment recognition device 1 can accurately measure the distance from the host vehicle 10 to the tollgate as the distance from the host vehicle 10 to the front object, and the measurement result is included in the above-described determination result. It is.
[0077]
Thereby, the forward environment recognition device 1 can determine the control content regarding the speed of the vehicle 10 and the like according to the distance.
[0078]
Next, in a case other than the example illustrated in FIG. 7, the procedure of the process performed by the front environment recognition device 1 is illustrated in FIG. Is described as an example.
[0079]
In steps S1a to S3a shown in FIG. 6, the forward environment recognition device 1 detects the forward objects A4 to C4 as shown in FIG. 11, and determines the size of each forward object, the relative position to the own vehicle 10, and Measure the relative velocity v. Then, detection result information is created and stored in the memory 13a.
[0080]
Next, in step S4a, the forward environment recognition device 1 determines the type of each forward object.
[0081]
That is, the forward environment recognition device 1 determines that the forward objects A4 to B4 are moving, and as a result, determines that the forward objects A4 to B4 are vehicles.
[0082]
On the other hand, the forward environment recognition device 1 determines that the forward object C4 is smaller than the vehicle and is stopped, and as a result, determines that the forward object C4 is a road sign.
[0083]
Next, the determination processing unit 13b creates determination result information regarding the size of each forward object, the relative position with respect to the own vehicle 10, the relative speed v, and the determination result, and stores the determination result information in the memory 13a illustrated in FIG. And outputs it to the control unit 14.
[0084]
Next, in step S5a, the forward environment recognition device 1 determines the control content and the warning content.
[0085]
(Second embodiment)
Next, a second embodiment according to the present invention (corresponding to any one of claims 2, 7 and 13) will be described with reference to the drawings.
[0086]
As shown in FIG. 1, the forward environment recognition device 2 according to the second embodiment causes the determination processing unit 13 b of the forward environment recognition device 1 to perform the following processing in addition to the above-described processing. It was done.
[0087]
Therefore, in the second embodiment, the description of the configuration of the front environment recognition device 2 is omitted, and the reference numerals of the respective components of the front environment recognition device 2 are replaced with the reference numerals of the respective components of the front environment recognition device 1. And the same as
[0088]
Next, a procedure of processing by the front environment recognition device 2 will be described with reference to FIGS. 1, 6, and 12 to 15. Here, FIG. 12 and FIG. 14 are explanatory views showing a state in front of the own vehicle 10 in the traveling direction, and FIG. 13 and FIG. 15 are schematic plan views showing the positions of the reflection points and the front objects.
[0089]
The process by the front environment recognition device 2 is performed according to the flowchart shown in FIG. 6, but differs from the process by the front environment recognition device 1 only in the process of step S4a. Therefore, in the second embodiment, the different processing will be particularly described.
[0090]
First, as shown in FIG. 12, a case where vehicles 22 to 25 and a tollgate 32 exist in front of the own vehicle 10 in the traveling direction will be described as an example. Note that the front environment recognition device 2 can also perform the following processing in other cases.
[0091]
In steps S1a to S3a, the forward environment recognition device 2 detects the forward objects A3 to E3 as shown in FIG. 13 and determines the size of each forward object, the relative position with respect to the own vehicle 10, and the relative speed v. Measure. Then, detection result information is created and stored in the memory 13a.
[0092]
Next, in step S4a, the determination processing unit 13b determines the type of each forward object by performing the following processing on each forward object.
[0093]
That is, the determination processing unit 13b acquires the detection result information from the memory 13a, measures the number of reflection points included in the front object based on the detection result information, and determines the number of the reflection points and the reference value n1. Compare.
[0094]
Next, when the number of reflection points included in the front object is larger than the reference value n1, the determination processing unit 13b further measures the distance from the reflection point included in the front object to the own vehicle, The variance (distribution) of these distances is calculated.
[0095]
Next, when the variance value is larger than a predetermined reference value n2 for the variance value, the determination processing unit 13b determines that the front object (the front object E3 in this example) is a toll gate. , The reference object is determined to be a large overhead signboard.
[0096]
Here, the reason why the determination is possible will be described.
[0097]
That is, even when the laser radar 11 scans a large overhead signboard, a number of reflection points larger than the reference value n1 may be detected.
[0098]
However, the tollgate has a protruding portion (for example, protruding portions e1 to e6 as shown in FIG. 13) protruding in the traveling direction of the vehicle 10, whereas a large overhead signboard has the protruding portion. It is not provided and has a planar shape. The protruding portion of the tollgate is made up of, for example, a pole cone, a signboard, or the like.
[0099]
For this reason, the variance calculated when the tollgate is scanned is larger than the variance calculated when a large overhead signboard is scanned.
[0100]
Therefore, the above-described determination can be performed by setting the reference value n2 to be larger than the variance value calculated when a large overhead signboard is scanned.
[0101]
On the other hand, when the number of reflection points included in the front object is smaller than the reference value n1, the determination processing unit 13b determines the type of the front object (the front objects A3 to D3 in this example) by the size, The determination is made based on the relative position and the relative speed v.
[0102]
That is, the determination processing unit 13b detects the moving object (the front objects A3 to D3 in this example) detected on the traveling direction side of the own vehicle 10 with respect to the front object E3 determined as the tollgate. Is determined to be a vehicle.
[0103]
Next, the determination processing unit 13b creates determination result information on the distance from the own vehicle 10 to the tollgate, the size of each forward object, the relative position with respect to the own vehicle 10, the relative speed v, and the determination result. The information is stored in the memory 13a shown in FIG.
[0104]
Next, in step S5a, the control unit 14 determines the content of control of the own vehicle 10 and the content of an alarm for an occupant of the own vehicle 10 based on the determination result information.
[0105]
Next, as shown in FIG. 14, a case where the vehicles 28 to 29 and the large overhead sign 50 are present in front of the own vehicle 10 in the traveling direction will be described.
[0106]
In steps S1a to S3a, the forward environment recognition device 2 detects the forward objects A5 to C5, as shown in FIG. 15, and determines the size of each forward object, the relative position with respect to the own vehicle 10, and the relative speed v. Measure. Then, detection result information is created and stored in the memory 13a.
[0107]
Next, in step S4a, the determination processing unit 13b determines the type of each forward object.
[0108]
That is, the determination processing unit 13b determines that the number of reflection points is larger than the reference value n1 but the variance of the distance is smaller than the reference value n2 for the front object C5. Judge as a large overhead sign.
[0109]
On the other hand, the determination processing unit 13b determines that the forward objects A5 to B5 are moving, and as a result, determines that the forward objects A5 to B5 are vehicles.
[0110]
Next, the determination processing unit 13b creates determination result information regarding the size of each forward object, the relative position with respect to the own vehicle 10, the relative speed v, and the determination result, and stores the determination result information in the memory 13a illustrated in FIG. And outputs it to the control unit 14.
[0111]
Next, the control unit 14 determines the control content and the warning content of the own vehicle 10 in step S5a.
[0112]
As described above, according to the second embodiment, the following effects can be obtained in addition to the effects of the first embodiment.
[0113]
That is, when the number of reflection points included in the front object is larger than the reference value n1, the front environment recognition device 2 accurately determines whether the front object is a tollgate or a large overhead signboard. (An effect corresponding to the invention described in claim 2).
[0114]
Further, the forward environment recognition device 2 can determine the control content and the warning content of the own vehicle 10 according to the result of the determination (an effect corresponding to the invention described in claim 7).
[0115]
In the second embodiment, the variance is used as the distance distribution, but the distribution may be, for example, a value obtained by dividing the minimum value from the maximum value of the distance in addition to the variance value. Etc. can be used.
[0116]
(Third embodiment)
Next, a third embodiment (corresponding to the invention of claim 3 or 7) according to the present invention will be described with reference to the drawings.
[0117]
As shown in FIG. 1, the forward environment recognition device 3 according to the third embodiment causes the determination processing unit 13 b of the above-described forward environment recognition device 1 to perform the following processing in addition to the above-described processing. It was done.
[0118]
Therefore, in the third embodiment, the description of the configuration of the front environment recognition device 3 is omitted, and the reference numerals of the respective components of the front environment recognition device 3 are replaced with the reference numerals of the respective components of the front environment recognition device 1. And the same as
[0119]
Next, a procedure of a process performed by the forward environment recognition device 3 will be described with reference to FIGS. 1, 6, and 12 to 15.
[0120]
The processing by the forward environment recognition device 3 is performed according to the flowchart shown in FIG. 6, but differs from the process by the forward environment recognition device 1 only in the process of step S4a. Therefore, in the third embodiment, the different processing will be particularly described.
[0121]
First, as shown in FIG. 12, a case where vehicles 22 to 25 and a tollgate 32 exist in front of the own vehicle 10 in the traveling direction will be described as an example. In addition, it is needless to say that the forward environment recognition device 3 can also perform the following processing in other cases.
[0122]
First, in steps S1a to S3a, the forward environment recognition device 3 detects the forward objects A3 to E3 as shown in FIG. 11, and determines the size of each forward object, the relative position to the own vehicle 10, and the relative speed. Measure v. Then, detection result information is created and stored in the memory 13a.
[0123]
Next, in step S4a, the determination processing unit 13b determines the type of each forward object by performing the following processing on each forward object.
[0124]
That is, the determination processing unit 13b acquires the detection result information from the memory 13a, measures the number of reflection points included in the front object based on the detection result information, and determines the number of the reflection points and the number of the reflection points. The number is compared with a predetermined reference value n1.
[0125]
Next, when the number of reflection points included in the front object is larger than the reference value n1, the determination processing unit 13b performs the following processing.
[0126]
That is, the determination processing unit 13b measures the distances from the reflection points included in the front object to the host vehicle based on the detection result information, and calculates the variance (distribution degree) of these distances.
[0127]
Further, the determination processing unit 13b measures the intensities of the reflection points included in the front object based on the detection result information, and calculates a variance (distribution degree) of these intensities.
[0128]
Next, if the variance value of the distance is greater than the reference value n2 or the variance value of the intensity is greater than the reference value n3 predetermined for the variance value of the intensity, the determination processing unit 13b determines that the forward The object (in this example, the front object E3) is determined to be a tollgate.
[0129]
On the other hand, when the variance of the distance is smaller than the reference value n2 and the variance of the intensity is smaller than the reference value n3, the determination processing unit 13b determines that the front object is a large overhead signboard.
[0130]
Here, the reason why the determination is possible will be described.
[0131]
That is, even when the laser radar 11 scans a large overhead signboard, a number of reflection points larger than the reference value n1 may be detected.
[0132]
However, the tollgate and the large overhead signboard have the following differences in addition to the difference in the variance value (distribution degree) of the distance.
[0133]
That is, the toll booth has a plurality of types of objects that reflect laser light (for example, a reflector, a toll payer, a pole cone, and a lamp). In addition, the portion is oriented in various directions with respect to the vehicle 10.
[0134]
On the other hand, the large overhead signboard is made of substantially the same material, and faces substantially the same direction with respect to the vehicle 10.
[0135]
Therefore, the variance of the intensity calculated when scanning the tollgate is larger than the variance of the intensity calculated when scanning a large overhead signboard.
[0136]
Therefore, the above-described determination can be performed by setting the reference value n3 to be larger than the variance of the intensity calculated when a large overhead signboard is scanned.
[0137]
On the other hand, when the number of reflection points included in the front object is smaller than the reference value n1, the determination processing unit 13b determines the type of the front object (the front objects A3 to D3 in this example) by the size, The determination is made based on the relative position and the relative speed v.
[0138]
For example, the discrimination processing unit 13b is a moving object (in this example, the front objects A3 to D3) that is detected on the traveling direction side of the own vehicle 10 with respect to the front object E3 determined to be a tollgate and is moving. Is determined to be a vehicle.
[0139]
Next, the determination processing unit 13b determines the distance from the host vehicle 10 to the front object determined to be a tollgate, the size of each front object, the relative position to the host vehicle 10, the relative speed v, and the determination result information regarding the determination result. The determination result information is created and stored in the memory 13a shown in FIG.
[0140]
Next, in step S5a, the control unit 14 determines the control content and the warning content of the vehicle 10 based on the determination result information.
[0141]
Next, as shown in FIG. 14, a case where the vehicles 28 to 29 and the large overhead sign 50 are present in front of the own vehicle 10 in the traveling direction will be described.
[0142]
In steps S1a to S3a, the forward environment recognition device 3 detects the forward objects A5 to C5 as shown in FIG. 15 and determines the size of each forward object, the relative position with respect to the own vehicle 10, and the relative speed v. Measure. Then, detection result information is created and stored in the memory 13a.
[0143]
Next, in step S4a, the determination processing unit 13b determines the type of each forward object.
[0144]
That is, for the forward object C5, the number of reflection points is larger than the reference value n1, but the variance value of the distance is smaller than the reference value n2, and the variance value of the intensity is larger than the reference value n3. It is determined to be small, and as a result, the forward object C5 is determined to be a large overhead signboard.
[0145]
On the other hand, the determination processing unit 13b determines that the forward objects A5 to B5 are moving, and as a result, determines that the forward objects A5 to B5 are vehicles.
[0146]
Next, the determination processing unit 13b creates determination result information regarding the determination result, stores the determination result information in the memory 13a, and outputs the determination result information to the control unit 14.
[0147]
Next, in step S5a, the control unit 14 determines the control content and the warning content of the vehicle 10 based on the determination result information.
[0148]
As described above, according to the third embodiment, the following effects can be obtained in addition to the effects of the first embodiment.
[0149]
That is, even if the number of reflection points included in the front object is larger than the reference value n1, the front environment recognition device 3 accurately determines whether the front object is a tollgate or a large overhead signboard. It can be determined (effect corresponding to the invention described in claim 3).
[0150]
Further, the forward environment recognition device 3 can determine the control content and the warning content of the own vehicle 10 according to the result of the determination (an effect corresponding to the seventh aspect of the invention).
[0151]
In the second embodiment, the variance is used as the intensity distribution, but the distribution may be, for example, a value obtained by dividing the minimum value from the maximum value of the intensity in addition to the variance value. Etc. can be used.
[0152]
(Fourth embodiment)
Next, a fourth embodiment (corresponding to the invention described in claim 4 or 7) according to the present invention will be described with reference to the drawings.
[0153]
As shown in FIG. 1, the forward environment recognition device 4 according to the fourth embodiment includes the following processing in addition to the above-described processing in the determination processing unit 13b in any of the above-described forward environment recognition devices 1 to 3. Is performed.
[0154]
Therefore, in the fourth embodiment, the description of the configuration of the front environment recognition device 4 is omitted, and the reference numerals of the respective components of the front environment recognition device 4 are replaced with the reference numerals of the respective components of the front environment recognition device 1. And the same as
[0155]
Next, a procedure of processing by the front environment recognition device 4 will be described with reference to FIGS. 1, 6, and 16 to 18. Here, FIGS. 16 to 18 are schematic plan views showing the positions of the reflection points and the front object.
[0156]
The processing by the front environment recognition device 4 is performed according to the flowchart shown in FIG. 6, but differs from the processing by any of the front environment recognition devices 1 to 3 only in the process of step S4a. Therefore, in the fourth embodiment, the different processing will be particularly described.
[0157]
First, as shown in FIG. 16, a case where vehicles 51 to 52 and a tollgate 33 are present ahead of the own vehicle 10 in the traveling direction will be described as an example. The front environment recognition device 4 can also perform the following processing in other cases.
[0158]
First, in steps S1a to S3a, the forward environment recognition device 4 detects the forward objects A6 to D6, as shown in FIG. 16, and determines the size of each forward object, the relative position with respect to the own vehicle 10, and the relative speed. Measure v. Then, detection result information is created and stored in the memory 13a.
[0159]
Next, in step S4a, the determination processing unit 13b determines the type of each forward object by performing the following processing on each forward object.
[0160]
That is, the determination processing unit 13b acquires the detection result information from the memory 13a, measures the number of reflection points included in the forward object based on the detection result information, and determines the number of the reflection points and the reference value n1. Compare.
[0161]
Next, when the number of reflection points included in the front object is larger than the reference value n1, the determination processing unit 13b further determines whether the front object includes a protruding portion that protrudes in the traveling direction of the host vehicle 10. Judge whether or not.
[0162]
Here, the determination processing unit 13b determines whether or not the projection includes the protruding portion based on the relative position of the reflection point included in the front object.
[0163]
Next, when the forward object includes the protruding portions (in this example, the protruding portions d1 to d3), the determination processing unit 13b determines the forward object (in this example, the front object D6) to be a toll gate. .
[0164]
Here, the reason why the determination is possible will be described.
[0165]
That is, the tollgate has a protruding portion that protrudes in the traveling direction of the vehicle 10, and the protruding portion is formed of an object that reflects laser light (for example, a tollgate pillar, a pole cone, a signboard, and the like). There is a feature that there is.
[0166]
Therefore, when the toll gate is scanned, the protruding portion is detected, so that the above-described determination can be performed.
[0167]
Note that the determination processing unit 13b can determine whether the preceding object is a tollgate by another method. The other method will be described later.
[0168]
On the other hand, when the number of reflection points included in the front object is smaller than the reference value n1, the determination processing unit 13b determines the type of the front object (in this example, the front objects A6 to C6) by its size, The determination is made based on the relative position and the relative speed v.
[0169]
For example, the discrimination processing unit 13b is a moving object (in this example, the front objects A6 to B6 in this example) that is detected on the traveling direction side of the own vehicle 10 with respect to the front object D6 determined to be a tollgate. Is determined to be a vehicle.
[0170]
Further, the determination processing unit 13b determines that the stopped front object (the front object C6 in this example) having a size smaller than that of the vehicle is the delineator.
[0171]
Next, the determination processing unit 13b determines the distance from the host vehicle 10 to the front object determined to be a tollgate, the size of each front object, the relative position to the host vehicle 10, the relative speed v, and the determination result information regarding the determination result. The determination result information is created and stored in the memory 13a shown in FIG.
[0172]
Next, in step S5a, the control unit 14 determines the control content and the warning content of the own vehicle 10 based on the determination result information.
[0173]
Next, as shown in FIG. 17, a case where vehicles 53 to 54 and a tollgate 34 exist ahead of the own vehicle 10 in the traveling direction will be described.
[0174]
First, in steps S1a to S3a, the forward environment recognition device 4 detects the forward objects A7 to C7 as shown in FIG. 17, and determines the size of each forward object, the relative position with respect to the own vehicle 10, and the relative speed. Measure v.
[0175]
Next, in step S4a, the determination processing unit 13b determines the type of each forward object.
[0176]
That is, the determination processing unit 13b determines that the number of reflection points is larger than the reference value n1 and that the front object C7 includes a protruding portion, and as a result, the front object C7 is determined as a tollgate. judge.
[0177]
Here, when another front object is present before the front object C7, all the protruding portions included in the front object C7 may not be detected. FIG. 18 shows an example in this case.
[0178]
That is, FIG. 18 shows that the front objects A8 to C8 (corresponding to the vehicles 55 to 57) exist in front of the front object C7, and the front objects A8 to C8 block the laser light, so that the protruding portions c2 to c3 Is not detected.
[0179]
In this case, the determination processing unit 13b determines whether or not the protruding portions c2 to c3 are not detected because another front object existing in front of the front object C7 blocks the laser beam.
[0180]
As a result, only when the cause that the protruding portions c2 to c3 are not detected is that another front object blocks the laser beam, the determination processing unit 13b regards the protruding portions c2 to c3 as being detected. Then, the type of the forward object C7 is determined.
[0181]
On the other hand, the discrimination processing unit 13b detects the front objects A7 to B7 shown in FIG. 17 on the traveling direction side of the vehicle 10 with respect to the front object C7 determined to be a tollgate, and moves. , The forward objects A7 to B7 are determined as vehicles.
[0182]
Next, the determination processing unit 13b determines the distance from the host vehicle 10 to the front object determined to be a tollgate, the size of each front object, the relative position with respect to the host vehicle 10, the relative speed v, and the determination result information regarding the determination result. The determination result information is created and stored in the memory 13a shown in FIG.
[0183]
Next, in step S5a, the control unit 14 determines the control content and the warning content of the own vehicle 10 based on the determination result information.
[0184]
As described above, according to the fourth embodiment, the following effects can be obtained in addition to the effects of any of the first to third embodiments.
[0185]
That is, the forward environment recognition device 4 can accurately determine whether the forward object is a tollgate (an effect corresponding to the invention described in claim 4).
[0186]
Further, the forward environment recognition device 4 can determine the control content and the warning content of the own vehicle 10 according to the result of the determination (an effect corresponding to the invention described in claim 7).
[0187]
Next, another method for the forward environment recognition device 4 to determine the presence or absence of a tollgate is described in the case where the vehicles 55 to 57 and the tollgate 34 exist in the forward direction of the vehicle 10 as shown in FIG. An example will be described.
[0188]
Here, FIG. 19 is a schematic plan view showing the position of the reflection point and the front object, FIG. 20 is a position distribution graph showing the position distribution of the reflection point, and FIG. 21 is an intensity distribution of the reflection point. 5 is an intensity distribution graph showing.
[0189]
First, in steps S1a to S3a, the forward environment recognition device 4 detects the forward objects A8 to D8 as shown in FIG. 19, and determines the size of each forward object, the relative position to the own vehicle 10, and the relative speed. Measure v. Then, the forward environment recognition device 4 creates detection result information and stores it in the memory 13a.
[0190]
Next, in step S4a illustrated in FIG. 6, the determination processing unit 13b determines the type of each forward object by performing the following processing on each forward object.
[0191]
That is, as shown in FIG. 19, the determination processing unit 13b defines an area F8 including a front object D8 that is considered to constitute a tollgate (that is, a front object whose number of reflection points is larger than the reference value n1).
[0192]
Next, as shown in FIG. 20, the determination processing unit 13b creates a position distribution graph by projecting the reflection points included in the area F8 on the xz plane.
[0193]
In addition, as illustrated in FIG. 21, the determination processing unit 13b creates an intensity distribution graph representing a relationship between the x coordinate of the reflection point included in the area F8 and the intensity of the reflection point.
[0194]
Next, the discrimination processing unit 13b determines whether a peak protruding in the z-axis direction exists at a constant interval along the x-axis direction in the position distribution graph, or a peak protruding in the intensity axis direction in the intensity distribution graph. When there is a certain interval along the x-axis direction, it is determined that the forward object D8 included in the area F8 is a tollgate.
[0195]
Here, these peaks correspond to the protruding portions of the tollgate.
[0196]
Subsequent processing is the same as the above-described processing, and a description thereof will be omitted.
[0197]
(Fifth embodiment)
Next, a fifth embodiment according to the present invention (corresponding to the invention of claim 5 or 7) will be described with reference to the drawings.
[0198]
As shown in FIG. 1, the forward environment recognition device 5 according to the fifth embodiment includes the following processing in addition to the above-described processing in the determination processing unit 13b in any of the above-described forward environment recognition devices 1 to 4. Is performed.
[0199]
Therefore, in the fifth embodiment, the description of the configuration of the front environment recognition device 5 is omitted, and the reference numerals of the respective components of the front environment recognition device 5 are replaced with the reference numerals of the respective components of the front environment recognition device 1. And the same as
[0200]
Next, the procedure of the process by the front environment recognition device 5 will be described based on FIGS. 1, 4 to 6, 12 to 13, and 22. Here, FIG. 22 is a schematic plan view showing the positions of the reflection points and the front object.
[0201]
The processing by the front environment recognition device 5 is performed according to the flowchart shown in FIG. 6, but differs from the processing by any of the front environment recognition devices 1 to 4 only in the process of step S4a. Thus, in the fifth embodiment, step S4a will be particularly described.
[0202]
In the fifth embodiment, as shown in FIG. 12, a case where vehicles 22 to 25 and a tollgate 32 are present in the forward direction of the vehicle 10 will be described as an example of this procedure.
[0203]
The front environment recognition device 5 can also perform the following processing in other cases.
[0204]
First, in steps S1a to S3a, the forward environment recognition device 5 detects the forward objects A3 to E3, as shown in FIG. 13, and determines the size of each forward object, the relative position with respect to the own vehicle 10, and the relative speed. Measure v. Then, the forward environment recognition device 5 creates the detection result information and stores it in the memory 13a.
[0205]
Next, in step S4a, the determination processing unit 13b determines the type of the forward object based on the detection result information acquired from the memory 13a, as in any of the forward environment recognition devices 1 to 4.
[0206]
Thereby, the determination processing unit 13b determines the front objects A3 to D3 as vehicles and determines the front object E3 as a tollgate.
[0207]
Next, the determination processing unit 13b determines the distance from the host vehicle 10 to the front object determined to be a tollgate, the size of each front object, the relative position to the host vehicle 10, the relative speed v, and the determination result information regarding the determination result. The determination result information is created and stored in the memory 13a shown in FIG.
[0208]
Next, in step S5a, the control unit 14 determines the control content and the warning content of the own vehicle 10 based on the determination result information.
[0209]
Thereafter, the forward environment recognition device 5 repeatedly performs the processing of steps S1a to S5a. In step S4a of the repeated processing, the determination processing unit 13b performs the following processing in addition to the above-described processing.
[0210]
That is, before determining the type of the forward object, the determination processing unit 13b acquires the determination result information from the memory 13a and, based on the determination result information and the detection result information, determines the forward object determined to be a tollgate. It is determined whether part of E3 is no longer detected.
[0211]
As a result, when a part of the forward object E3 is no longer detected, the determination processing unit 13b determines that the vehicle 10 has approached the tollgate, and further determines another portion of the forward object as one of the tollgates. Is determined to be a copy.
[0212]
FIG. 22 shows an example of this case. FIG. 22 shows a case where the part e7 of the front object E3 is not detected and the other parts e1 to e6 are detected.
[0213]
Here, the reason why the determination is possible will be described.
[0214]
That is, in the case illustrated in FIG. 13, when the forward environment recognition device 5 repeats the processing of steps S1a to S5a, a part e7 of the forward object E3 is detected at a certain time as illustrated in FIG. 22. May be unable to do so.
[0215]
This is because, as shown in FIG. 4, the detectable range of the laser radar 11 is limited, and as shown in FIG. That is, a part e7 of the forward object E3 comes out of the detectable range of the laser radar 11. Therefore, the determination can be made.
[0216]
Next, the determination processing unit 13b determines the distance from the host vehicle 10 to the front object determined to be a part of the tollgate, the size of each front object, the relative position to the host vehicle 10, the relative speed v, and the determination result. The result information is created, and the determination result information is stored in the memory 13a shown in FIG.
[0217]
Next, the determination processing unit 13b stores the determination result information in the memory 13a and outputs the information to the control unit 14.
[0218]
As described above, according to the fifth embodiment, the following effects can be obtained in addition to the effects of any of the first to fourth embodiments.
[0219]
That is, the forward environment recognition device 5 can determine whether or not the vehicle 10 has approached a tollgate (an effect corresponding to the invention described in claim 5).
[0220]
Further, even when the part e7 of the front object E3 is no longer detected, the forward environment recognition device 5 determines that the other parts, that is, the protruding parts e1 to e6, are part of the tollgate 32. It is possible to prevent the portions e1 to e6 from being determined as a vehicle or the like.
[0221]
Further, the forward environment recognition device 5 can determine the control content and the warning content of the own vehicle 10 according to the result of the determination (an effect corresponding to the invention described in claim 7).
[0222]
When the part e7 of the forward object E3 is no longer detected, the determination processing unit 13b calculates an approximate distance Za from the vehicle 10 to the tollgate using the following equation (1). You can also.
[0223]
Za = H1 / tan (β / 2) (1)
Here, as shown in FIG. 4, H1 is the normal height of the tollgate, and β is the size of the detection angle in the height direction.
[0224]
In this case, the determination processing unit 13b includes the calculated distance Za in the determination result information.
[0225]
Further, the determination processing unit 13b calculates a distance Zb (the distance Zb is calculated by the detection processing unit 12b) from the own vehicle 10 to the forward object determined to be a tollgate, and the following equation (1a). It can also be used to calculate the actual height H2 of the tollgate.
[0226]
H2 = Zb * tan (β / 2) (1a)
In this case, the determination processing unit 13b includes the calculated height H2 in the determination result information.
[0227]
Further, the determination processing unit 13b can also determine whether or not the own vehicle 10 can pass through the tollgate 32 by comparing the height H2 with the height of the own vehicle 10.
[0228]
In this case, the determination processing unit 13b also includes the result of the determination in the determination result information.
[0229]
(Sixth embodiment)
Next, a sixth embodiment according to the present invention (corresponding to the invention of claim 6 or 7) will be described with reference to the drawings.
[0230]
As shown in FIG. 1, the forward environment recognition device 6 according to the sixth embodiment causes the discrimination processing unit 13b of the forward environment recognition device 5 to perform the following processing in addition to the above-described processing. It was done.
[0231]
Therefore, in the sixth embodiment, the description of the configuration of the front environment recognition device 6 is omitted, and the reference numerals of the respective components of the front environment recognition device 6 are replaced with the reference numerals of the respective components of the front environment recognition device 5. And the same as
[0232]
Next, a procedure of processing by the front environment recognition device 6 will be described based on FIGS. 1, 4 to 6, 12 to 13, and 22 to 25. Here, FIG. 23 to FIG. 25 are schematic plan views showing the positions of the reflection points and the front objects when the vehicle 10 approaches the tollgate 32.
[0233]
The processing by the front environment recognition device 6 is performed according to the flowchart shown in FIG. 6, but differs from the processing by the front environment recognition device 5 only in the process of step S4a. Thus, in the sixth embodiment, the processing in step S4a will be particularly described.
[0234]
In the sixth embodiment, a case where the vehicles 22 to 25 and the tollgate 32 exist in the forward direction of the vehicle 10 as shown in FIG. 12 will be described as an example of this procedure.
[0235]
The front environment recognition device 6 can also perform the following processing in other cases.
[0236]
First, in steps S1a to S3a, the forward environment recognition device 6 detects the forward objects A3 to E3, as shown in FIG. 13, and determines the size of each forward object, the relative position to the own vehicle 10, and the relative speed. Measure v. Then, the forward environment recognition device 6 creates detection result information and stores it in the memory 13a.
[0237]
Next, in step S4a, the determination processing unit 13b determines the type of the front object based on the detection result information provided from the detection processing unit 12b, similarly to any of the front environment recognition devices 1 to 4.
[0238]
Thereby, the determination processing unit 13b determines the front objects A3 to D3 as vehicles and determines the front object E3 as a tollgate.
[0239]
Next, the determination processing unit 13b creates determination result information regarding the size of each forward object, the relative position with respect to the own vehicle 10, the relative speed v, and the determination result, and stores the determination result information in the memory 13a illustrated in FIG. And outputs it to the control unit 14.
[0240]
Next, in step S5a, the control unit 14 determines the control content and the warning content of the own vehicle 10 based on the determination result information.
[0241]
Thereafter, the forward environment recognition device 6 repeatedly performs the processing of steps S1a to S5a. In step S4a of the repeated processing, the determination processing unit 13b performs the following processing in addition to the above-described processing.
[0242]
That is, before determining the type of the forward object, the determination processing unit 13b acquires the determination result information from the memory 13a and, based on the determination result information and the detection result information, determines the forward object determined to be a tollgate. It is determined whether part of E3 is no longer detected.
[0243]
As a result, as shown in FIG. 22, when the part e7 of the forward object E3 is no longer detected, the determination processing unit 13b determines that the vehicle 10 has approached the tollgate, and further determines that the own vehicle 10 has approached the tollgate. The other parts, that is, the protruding parts e1 to e6 are determined to be part of the tollgate.
[0244]
Further, the determination processing unit 13b counts the number of the protruding portions. As a result, as shown in FIG. 25, when the number of projecting portions becomes two or less, the determination processing unit 13b determines that the vehicle 10 is approaching the entrance of the tollgate.
[0245]
Further, the determination processing unit 13b measures the distance from the own vehicle 10 to the entrance based on the detection result information as the distance from the own vehicle 10 to the protruding portion of the tollgate.
[0246]
Here, the reason why the determination is possible will be described.
[0247]
That is, first, FIGS. 22 to 25 show a state in which the front environment recognition device 6 detects a front object while the vehicle 10 approaches the tollgate 32.
[0248]
Here, FIG. 22 shows the detection result t1 seconds after the front object E3 is detected, and FIG. 23 shows the detection result t2 seconds after the front object E3 is detected (t1 <t2).
[0249]
FIG. 24 shows the detection result at t3 seconds after the front object E3 is detected, and FIG. 25 shows the detection result at t4 seconds after the front object E3 is detected (t2 <t3 <t4). .
[0250]
As shown in FIGS. 22 to 25, as the vehicle 10 approaches the tollgate 32, the detected protruding portion decreases. If the number of detected protrusions is two or less, it can be said that the vehicle 10 has approached the entrance of the tollgate. Therefore, the determination can be made.
[0251]
Next, the determination processing unit 13b determines the type of another front object (for example, the front object A3) in the same manner as the above-described processing.
[0252]
Next, the determination processing unit 13b determines the distance from the host vehicle 10 to the front object determined to be a part of the tollgate, the size of each front object, the relative position to the host vehicle 10, the relative speed v, and the determination result. The result information is created, and the determination result information is stored in the memory 13a shown in FIG.
[0253]
Next, the determination processing unit 13b stores the determination result information in the memory 13a and outputs the information to the control unit 14.
[0254]
As described above, according to the sixth embodiment, the following effects can be obtained in addition to the effects of the fifth embodiment.
[0255]
That is, the forward environment recognition device 6 can accurately determine whether or not the vehicle 10 has approached the entrance of the tollgate (an effect corresponding to the invention described in claim 6).
[0256]
Further, the forward environment recognition device 6 can determine the optimal control content and the alarm content according to the result of the determination (an effect corresponding to the invention according to claim 7).
[0257]
(Seventh embodiment)
Next, a seventh embodiment according to the present invention (corresponding to the invention of claim 8 or 11) will be described with reference to the drawings.
[0258]
First, the configuration of the front environment recognition device 7 according to the seventh embodiment will be described with reference to FIG. 1 and FIGS. Here, FIG. 26 is a block diagram showing the configuration of the front environment recognition device 7, and FIGS. 27 to 28 are schematic diagrams showing the installation position of the camera 15 and the like.
[0259]
As shown in FIGS. 1 and 26, the forward environment recognition device 7 is obtained by adding the following components to the forward environment recognition device 5 or 6, and changing the processing contents of the determination processing unit 13b and the control unit 14. .
[0260]
Therefore, the description of the configuration of the front environment recognition device 7 will be made only for the added component, the discrimination processing unit 13b, and the control unit 14. The reference numerals of the components common to the front environment recognition device 5 or 6 are the same as those of the components of the front environment recognition device 5 or 6.
[0261]
As shown in FIG. 26, the forward environment recognition device 7 includes a camera (photographing means) 15, an object tracking processing unit (object tracking unit), in addition to the laser radar 11, the object detection unit 12, the object type determination unit 13, and the control unit 14. Processing unit) 16 and an integration processing unit (integration processing unit) 17.
[0262]
The determination processing unit 13b determines the type of the forward object and creates the determination result information, similarly to the forward environment recognition device 5 or 6. Then, the determination processing unit 13b stores the determination result information in the memory 13a and outputs the information to the integration processing unit 17.
[0263]
The control unit 14 determines the control content of the own vehicle 10 based on the integration result information (described later) provided from the integration processing unit 17.
[0264]
As shown in FIGS. 27 to 28, the camera 15 is attached to the front of the own vehicle 10 in the same direction as the laser radar 11. , "Forward video"). Then, the camera 15 outputs the obtained forward video to the object tracking processing unit 16 as video information.
[0265]
The object tracking processing unit 16 includes a memory 16a and a video processing unit 16b.
[0266]
The memory 16a stores the video information provided from the camera 15.
[0267]
The video processing unit 16b acquires the detection result information from the memory 12a, acquires the determination result information from the memory 13a, and further acquires the video information from the memory 16a. Then, the video processing unit 16b performs a template matching process or the like based on the information.
[0268]
Then, the video processing unit 16 b creates tracking result information on the processing result, and outputs the information to the integration processing unit 17.
[0269]
The integration processing unit 17 performs a predetermined determination process based on the determination result information provided from the determination processing unit 13b and the tracking result information provided from the video processing unit 16b.
[0270]
Then, the integration processing unit 17 creates integration result information on the result of the determination and outputs the information to the control unit 14.
[0271]
Next, the procedure of the process performed by the front environment recognition device 7 will be described with reference to FIGS.
[0272]
Here, FIG. 29 is a flowchart showing the procedure of processing by the forward environment recognition device 7, and FIGS. 32 to 33 show the actual width (size) W of the forward object and the width (size) on the forward image. It is explanatory drawing which showed the relationship with A).
[0273]
FIGS. 31, 35, 37, 39, and 41 are explanatory diagrams showing forward images acquired by the camera 15, and FIGS. 30, 34, 36, 38, and 40. FIG. 3 is a schematic plan view showing positions of a reflection point and a front object.
[0274]
The front environment recognition device 7 performs the processing according to the flowchart shown in FIG. 29, and the processing in steps S1b to S4b shown in FIG. 29 is the same as the processing in steps S1a to S4a shown in FIG.
[0275]
Therefore, in the seventh embodiment, processing other than the processing of steps S1b to S4b will be particularly described.
[0276]
Further, in the seventh embodiment, as shown in FIGS. 30 to 41, vehicles 22 to 25 and a tollgate 32 exist in the forward direction of the vehicle 10, and the vehicle 22 and the vehicle 10 are the same. The process when entering the toll gate entrance (hereinafter, referred to as “entrance”) will be described as an example.
[0277]
The front environment recognition device 7 can also perform the following processing in other cases.
[0278]
First, in the state shown in FIG. 30, the front environment recognition device 7 detects the front objects A3 to E3 in steps S1b to S4b shown in FIG.
[0279]
Further, the forward environment recognition device 7 determines the forward objects A3 to D3 as vehicles and determines the forward object E3 as a tollgate. Further, the protruding portions e1 to e6 of the forward object E3 are determined to be a part of the tollgate.
[0280]
As a result, in this example, since there is a tollgate, the forward environment recognition device 7 performs the processing after step S5b. On the other hand, when there is no tollgate, the forward environment recognition device 7 performs the process of step S11b.
[0281]
First, the processing in step S11b will be described.
[0282]
That is, in step S11b, the determination processing unit 13b creates determination result information on the size of each forward object, the relative position with respect to the own vehicle 10, the relative speed v, and the determination result, and stores the determination result information in FIG. The data is stored in the memory 13a shown in FIG.
[0283]
Next, the integration processing unit 17 outputs the determination result information provided from the determination processing unit 13b to the control unit 14.
[0284]
Next, the control unit 14 determines the control content and the warning content of the own vehicle 10 based on the determination result information.
[0285]
Next, processing after step S5b will be described.
[0286]
That is, in step S5b, the determination processing unit 13b determines the distance from the vehicle 10 to the front object determined to be a tollgate, the size of each front object, the relative position to the vehicle 10, the relative speed v, and the determination result. The determination result information is generated, and the determination result information is stored in the memory 13a shown in FIG.
[0287]
Next, in step S6b, the camera 15 captures an image of the front of the vehicle 10 and obtains the front image (the image shown in FIG. 31), that is, the front image, and stores the front image in the memory 16a as image information. save.
[0288]
Next, in step S7b, the video processing unit 16b acquires the detection result information from the memory 12a, acquires the determination result information from the memory 13a, and further acquires the video information from the memory 16a.
[0289]
Next, the video processing unit 16b determines a target forward object based on these pieces of information, and measures a distance Zc from the host vehicle 10 to the target (forward object).
[0290]
In this example, the video processing unit 16b targets the forward object A3 closest to the host vehicle 10, that is, the vehicle 22.
[0291]
Next, the video processing unit 16b creates target distance information regarding the measurement result of the distance Zc, and stores the target distance information in the memory 16a.
[0292]
Next, the video processing unit 16b measures the position of the target on the front video, and further calculates the width (size) A of the target on the front video (see FIG. 32).
[0293]
Here, an example of a method of calculating the target width A will be described below.
[0294]
That is, as shown in FIG. 33, the actual width W of the target, the width A of the target on the front image, the focal length F of the camera 15, and the distance Zc from the host vehicle 10 to the target. Has the relationship shown in the following equation (2).
[0295]
A = W * F / Zc (2)
Here, in this example, since the target is the vehicle 22, the width W is about 2 meters. Further, the focal length F is known, and the distance Zc is measured as described above.
[0296]
Therefore, the video processing unit 16b can calculate the width A by substituting the value of the width W, the value of the focal length F, and the value of the distance Zc into Expression (2).
[0297]
Next, the video processing unit 16b determines whether the calculated width A is larger than a predetermined reference value n4 for the width A.
[0298]
Here, the reference value n4 is determined in consideration of the calculation amount in the template matching process (the calculation amount is reduced when the reference value n4 is small) and the recognition accuracy (the recognition accuracy is improved when the reference value n4 is large). Is determined.
[0299]
As a result, when the width A is smaller than the reference value n4, the front environment recognition device 7 repeats the above-described processing from step S1b.
[0300]
On the other hand, when the width A is larger than the reference value n4, the video processing unit 16b performs the processing after step S8b, that is, the template matching processing and the like.
[0301]
That is, in step S8b, as shown in FIG. 31, the video processing unit 16b sets the target video as the template T1, and stores the template information related to the template T1 in the memory 16a.
[0302]
The template information includes information such as the size of the template. Further, the template may be any part of the target video, but in this example, the video on the entire rear surface of the target is used as the template T1.
[0303]
Next, the forward environment recognition device 7 repeats the processing of the above-described steps S1b to S6b.
[0304]
Next, in the determination processing unit 13b, the video processing unit 16b acquires the detection result information from the memory 12a, acquires the determination result information from the memory 13a, and further acquires the video information from the memory 16a.
[0305]
Next, the video processing unit 16b measures the distance Zc from the vehicle 10 to the target based on the information.
[0306]
Next, the video processing unit 16b enlarges or reduces the template T1 according to the measured distance Zc.
[0307]
Specifically, the video processing unit 16b enlarges the template T1 when the distance Zc is short, and enlarges the template T1 when the distance Zc is long.
[0308]
Here, in the state shown in FIG. 34, FIG. 35 shows a forward image acquired by the camera 15 when the forward environment recognizing device 7 repeatedly performs the processing after step S1b. In this case, since the distance Zc is shorter than the case shown in FIGS. 30 and 31, the template T1 is enlarged.
[0309]
Next, the video processing unit 16b acquires the video information acquired by the repetition processing from the memory 16a, and finds the same target video as the template T1 from the video information.
[0310]
Thereby, the video processing unit 16b measures the position of the target video on the front video. That is, the video processing unit 16b recognizes the trajectory of the target on the front video.
[0311]
Next, the video processing unit 16b acquires the determination result information from the memory 13a, and determines whether the number of entrances into which the vehicle 10 can enter is determined to be one based on the determination result information.
[0312]
Here, the video processing unit 16b determines that the distance from the vehicle 10 to the tollgate is shorter than a predetermined distance or that the vehicle 10 is approaching the entrance of the tollgate. It is determined that the number of entrances into which the vehicle 10 can enter is determined to be one. Here, the predetermined distance is predetermined.
[0313]
As a result, when the number of the entrance is not determined to be one, the front environment recognizing device 7 repeats the above-described processing after step S8b.
[0314]
In this example, until the state shown in FIG. 40 is reached, the forward environment recognition device 7 repeats the processing from step S8b described above.
[0315]
In the state shown in FIGS. 36, 38, and 40, when the front environment recognition device 7 performs the processing after step S8b described above, the images acquired by the camera 15 are shown in FIGS. And FIG. 41.
[0316]
Here, in the repetitive processing, as shown in FIG. 37 and the like, when the distance Zc becomes shorter than the state shown in FIG. 34 and the template T1 becomes larger, the video processing unit 16b The target image is changed to a smaller target image, and the target image is used as a template T2.
[0317]
In this example, as shown in FIG. 37 and the like, the template T2 is a video of the license plate of the vehicle 22.
[0318]
In the repetitive processing, in the case shown in FIG. 40, since the reflection point is not detected from the target vehicle 22, the distance Zc cannot be measured by the above-described method.
[0319]
Such a case may occur, for example, when the reflex reflector of the vehicle 22 is out of the detectable range 11c of the laser radar 11. This is because, depending on the vehicle, a portion other than the reflex reflector may not sufficiently reflect the laser light.
[0320]
In this case, the video processing unit 16b calculates the distance Zc as follows.
[0321]
That is, the video processing unit 16b acquires the target distance information and the template information created in a state where the reflection point is detected from the vehicle 22 (for example, a state illustrated in FIG. 36).
[0322]
Next, based on the target information, the video processing unit 16b recognizes a distance Zc (hereinafter, referred to as “distance Zc1”) measured in a state where the reflection point is detected from the vehicle 22.
[0323]
Next, the video processing unit 16b measures the size of the target license plate video in the state based on the template information. The image processing unit 16b measures the size of the license plate image of the target in the state shown in FIG.
[0324]
Next, the video processing unit 16b calculates the rate of change in the size of the license plate video.
[0325]
Next, the video processing unit 16b calculates the distance Zc using the following equation (3).
[0326]
Zc = Zc1 / (change rate of size of license plate image) (3)
On the other hand, when the number of entrances to which the own vehicle 10 can enter is determined to be one (in this example, the case shown in FIG. 40), the front environment recognition device 7 performs the following processing.
[0327]
That is, in step S9b, the image processing unit 16b determines the size of the target on the front image (the size of the license plate image in this example) in the case shown in FIG. Is compared with a predetermined reference value n5.
[0328]
As a result, when the size is smaller than the reference value n5, the front environment recognition device 7 repeats the processing from step S8b described above.
[0329]
On the other hand, when the size is larger than the reference value n5 (in this example, the case shown in FIG. 40), the video processing unit 16b creates information to that effect and tracking result information on the measured distance Zc. .
[0330]
Next, the video processing unit 16b stores the created follow-up result information in the memory 16a and outputs the information to the integration processing unit 17.
[0331]
Next, in step S10b, when the tracking result information is provided from the video processing unit 16b, the integration processing unit 17 determines the tracking result information based on the tracking result information and the determination result information provided from the determination processing unit 13b. It is determined that the target and the vehicle 10 enter the same entrance.
[0332]
Next, the integration processing unit 17 creates integrated result information relating to the determination result and outputs the integrated result information to the control unit 14. The control unit 14 determines control content and alarm information based on the integrated result information.
[0333]
As described above, according to the seventh embodiment, the following effects can be obtained in addition to the effects of any of the fifth to sixth embodiments.
[0334]
That is, the forward environment recognition device 7 can accurately determine whether the forward object and the own vehicle 10 enter the same entrance (an effect corresponding to the invention according to claim 8).
[0335]
In particular, even when the vehicle 10 approaches the front object and the reflection point from the front object is not detected (see FIG. 40), the front environment recognition device 7 uses the front image to recognize the front object. It is possible to accurately determine whether to enter the same entrance as the vehicle 10 (an effect corresponding to the invention described in claim 8).
[0336]
Further, the forward environment recognition device 7 can determine the control content and the warning content according to the result of the determination (an effect corresponding to the invention according to claim 11).
[0337]
Accordingly, for example, when the own vehicle 10 is equipped with the ETC, the forward environment recognition device 7 prevents the useless brake operation from being performed when no vehicle exists in front of the own vehicle 10 when passing through the gate. Can be prevented.
[0338]
(Eighth embodiment)
Next, an eighth embodiment (corresponding to the invention of claim 9 or 11) according to the present invention will be described with reference to the drawings.
[0339]
As shown in FIG. 1 and FIG. 26, the forward environment recognition device 8 according to the eighth embodiment controls the video processing unit 16b and the integration processing unit 17 of the forward environment recognition device 7 to perform the following processing in addition to the above processing. Is performed.
[0340]
Therefore, in the eighth embodiment, the description of the configuration of the front environment recognition device 8 is omitted, and the reference numerals of the respective components of the front environment recognition device 8 are replaced with the reference numerals of the respective components of the front environment recognition device 7. And the same as
[0341]
Next, the procedure of the process performed by the front environment recognition device 8 will be described with reference to FIG. 29 and FIGS.
[0342]
Here, FIG. 42, FIG. 44, FIG. 46, FIG. 48, and FIG. 50 are schematic plan views showing the positions of the reflection point and the front object, and FIG. 43, FIG. 45, FIG. Reference numeral 51 is an explanatory diagram showing a forward image acquired by the camera 15.
[0343]
The process by the front environment recognition device 8 is the same as the process by the front environment recognition device 7 except that the following processes are added to the above-described processes of steps S9b to S10b.
[0344]
Therefore, in the eighth embodiment, the added processing will be particularly described.
[0345]
That is, when the entrance into which the vehicle 10 can enter is determined to be one by the processing of step S8b, the video processing unit 16b draws a horizontal edge in the forward video acquired by the camera 15 in step S9b. To determine if they have been
[0346]
Next, the video processing unit 16b includes the result of the determination in the tracking result information described above.
[0347]
Here, FIG. 41 shows an example where a horizontal edge is drawn, and FIG. 51 shows an example where a horizontal edge is not drawn. FIG. 41 illustrates a horizontal edge 22 a corresponding to the lower end surface of the vehicle 22. On the other hand, FIG. 51 does not illustrate the horizontal edge.
[0348]
Next, the video processing unit 16b stores the tracking result information in the memory 16a and outputs the tracking result information to the integration processing unit 17.
[0349]
Next, in step S10b, the integration processing unit 17 determines whether or not a vehicle exists in front of the own vehicle 10 based on the tracking result information given from the video processing unit 16b, that is, whether the own vehicle 10 and the vehicle 22 It is determined whether to enter the same entrance.
[0350]
Specifically, as illustrated in FIG. 41, when the horizontal edge 22a is drawn in the forward image, the integration processing unit 17 determines that the vehicle exists in front of the own vehicle 10, that is, the own vehicle 10 and the vehicle Is determined to enter the same entrance.
[0351]
On the other hand, when the horizontal edge is not drawn in the forward image as shown in FIG. 51, the integration processing unit 17 determines that no vehicle exists in front of the own vehicle 10, that is, the own vehicle 10 and the vehicle are at different entrances. It is determined to enter. Since the image of the vehicle always has a horizontal edge, the determination can be made.
[0352]
Next, the integration processing unit 17 creates integrated result information regarding the determination result and outputs the integrated result information to the control unit 14. The control unit 14 determines optimal control contents and alarm information based on the integrated result information.
[0353]
Here, in the case where the horizontal edge is not drawn in the forward image, as shown in FIGS. 42 to 51, the vehicles 22 to 25 and the tollgate 32 exist ahead of the own vehicle 10 in the traveling direction, and the vehicle 22 The case where the vehicle 10 enters a different entrance will be described as an example.
[0354]
In this case, the front environment recognition device 8 first detects the front objects A3 to E3 as shown in FIG. 42 in steps S1b to S4b shown in FIG.
[0355]
Then, the forward environment recognition device 8 determines the forward objects A3 to D3 as vehicles, determines the forward object E3 as a tollgate, and determines the protruding portions e1 to e6 of the forward object E3 as a part of the tollgate.
[0356]
Next, as shown in FIGS. 42, 44, 46, 48, and 50, the front environment recognition device 8 performs the processing of steps S <b> 1 b to S <b> 8 b until the number of entrances to which the vehicle 10 can enter is determined to be one. Is repeated.
[0357]
When the repetition processing is performed in FIGS. 42, 44, 46, 48, and 50, the images acquired by the camera 15 are respectively shown in FIGS. 43, 45, 47, 49, and 49. Shown at 51.
[0358]
Here, as shown in FIGS. 42 to 45, the front environment recognition device 8 performs the template matching process in the state shown in FIGS. 42 and 44 using the entire image of the rear surface of the vehicle 22 as the template T3 in the repeated process. Do.
[0359]
As a result, the video processing unit 16b recognizes that the vehicle 22 is moving to the left with respect to the traveling direction of the vehicle 10.
[0360]
Therefore, as shown in FIGS. 46 to 51, the front environment recognition device 8 converts the image of the right tail lamp of the vehicle 22 into a template in the state shown in FIGS. 46 and 48 (the state in which the own vehicle 10 approaches the vehicle 22). T4.
[0361]
Here, the reason why the right tail lamp is set to the template T4 is that when the vehicle 22 is moving to the left with respect to the traveling direction of the vehicle 10, the camera 15 shoots the right tail lamp for a longer time than other parts. This is because (see FIG. 49).
[0362]
As a result, the video processing unit 16b recognizes that the vehicle 22 moves outside the detectable range 11c of the laser radar 11 and the photographable range of the camera 15 (see FIGS. 49 and 51).
[0363]
As shown in FIG. 48, since the vehicle 22 has moved out of the detectable range 11c of the laser radar 11, new reflection points e31 and e41 are detected by the laser radar 11.
[0364]
Next, as shown in FIG. 50, after the entrance into which the vehicle 10 can enter is determined to be one, as shown in FIG. 50, the image processing unit 16b determines whether or not a horizontal edge is drawn in the forward image in step S9b. Then, follow-up result information on the result of the determination is created.
[0365]
Note that FIG. 50 shows that the tollgate box 32a exists on the right side of the protruding portion e4.
[0366]
In this example, as shown in FIG. 51, the video processing unit 16b creates follow-up result information indicating that no horizontal edge is drawn in the forward video.
[0367]
Next, the video processing unit 16b stores the created follow-up result information in the memory 16a and outputs the information to the integration processing unit 17.
[0368]
Next, in step S10b, the integration processing unit 17 determines that the target and the host vehicle 10 enter different entrances based on the tracking result information provided from the video processing unit 16b.
[0369]
Next, the integration processing unit 17 creates integrated result information relating to the determination result and outputs the integrated result information to the control unit 14. The control unit 14 determines control content and alarm information based on the integrated result information.
[0370]
As described above, according to the eighth embodiment, the following effects can be obtained in addition to the effects of the seventh embodiment.
[0371]
That is, the forward environment recognition device 8 can accurately determine whether the vehicle and the own vehicle 10 have entered the same entrance (an effect corresponding to the ninth aspect of the present invention).
[0372]
Further, the forward environment recognition device 8 can determine the control content and the alarm information according to the result of the determination (an effect corresponding to the invention according to claim 11).
[0373]
In addition, the integration processing unit 17 is only provided when the vehicle 22 moves out of the detectable range 11c of the laser radar 11, and thereafter, a forward object is detected in front of the own vehicle 10 and a horizontal edge is not drawn. It may be determined that there is no vehicle in front of the vehicle 10.
[0374]
In this case, the integration processing unit 17 can more reliably determine whether or not a vehicle exists in front of the vehicle 10.
[0375]
(Ninth embodiment)
Next, a ninth embodiment according to the present invention (corresponding to the invention of claim 10 or 11) will be described with reference to the drawings.
[0376]
As shown in FIG. 1 and FIG. 26, the forward environment recognition device 9 according to the ninth embodiment includes the following Is performed.
[0377]
Therefore, in the ninth embodiment, the description of the configuration of the front environment recognition device 9 is omitted, and the reference numerals of the respective components of the front environment recognition device 9 are replaced with the reference numerals of the respective components of the front environment recognition device 7. And the same as
[0378]
Next, a procedure of processing by the front environment recognition device 9 will be described with reference to FIGS. 29, 40 to 41, and 52 to 54.
[0379]
Here, FIG. 52 and FIG. 54 are schematic plan views showing the positions of the reflection points and the front objects when the vehicle 10 is present near the tollgate. FIG. 53 is the state shown in FIG. FIG. 4 is an explanatory diagram showing a forward image acquired by a camera 15.
[0380]
The process performed by the front environment recognition device 9 is the same as the process performed by the front environment recognition device 8 except that the following process is added to the process of step S10b described above.
[0381]
Thus, in the ninth embodiment, the added processing will be particularly described.
[0382]
That is, in step S10b, the integration processing unit 17 performs the following processing based on the tracking result information provided from the video processing unit 16b.
[0383]
That is, when the horizontal edge is drawn, the integration processing unit 17 predicts that the vehicle G exists in front of the own vehicle 10 as shown in FIG. FIGS. 41 and 53 show examples in which a horizontal edge is drawn.
[0384]
In FIG. 41, a horizontal edge 22a corresponding to the lower end surface of the vehicle 22 is depicted, and in FIG. 53, a horizontal edge 100 corresponding to the road surface is depicted. That is, even when there is no vehicle in front of the own vehicle 10, a horizontal edge may be drawn in the forward image.
[0385]
However, as shown in FIG. 40, in the state shown in FIG. 41, the host vehicle 10 approaches the vehicle 22, and the vehicle 22 blocks the laser beam from the laser radar 11, so that no forward object is detected.
[0386]
On the other hand, as shown in FIG. 54, in the state shown in FIG. 53, the front objects e7 to e8 (corresponding to the pillars of the tollgate) are detected. A toll booth box 32a exists on the right side of the forward object e8.
[0387]
Next, the integration processing unit 17 acquires the reflection point information from the memory 12a, and based on the reflection point information, determines whether the laser radar 11 has detected a reflection point that is not detected when the vehicle G actually exists. Judge whether or not.
[0388]
Next, the integration processing unit 17 determines that the vehicle G does not exist when the laser radar 11 detects the reflection point, and determines that the vehicle G does not exist when the laser radar 11 does not detect the reflection point. It is determined that the vehicle G exists.
[0389]
For example, in the case shown in FIG. 41, as shown in FIG. 40, since the reflection point is not detected, it is determined that the vehicle G exists.
[0390]
On the other hand, in the case shown in FIG. 53, as shown in FIG. 52, a reflection point (a reflection point included in the front objects e7 to e8) is detected. Is a reflection point that is not detected.
[0391]
This is because, as shown in FIG. 52, when the vehicle G is actually present, the vehicle G blocks the laser beam, so that the reflection point is not detected.
[0392]
In this case, since the laser radar 11 detects a reflection point that is not detected when the vehicle G actually exists, the integration processing unit 17 determines that the vehicle G exists.
[0393]
Next, the integration processing unit 17 creates integrated result information relating to the determination result and outputs the integrated result information to the control unit 14. The control unit 14 determines control content and alarm information based on the integrated result information.
[0394]
As described above, according to the ninth embodiment, the following effects can be obtained in addition to the effects of the eighth embodiment.
[0395]
That is, when the horizontal edge corresponding to the road surface is drawn in the front image, the front environment recognition device 9 can reliably prevent the determination that the vehicle is present in front of the host vehicle 10.
[0396]
Therefore, the front environment recognition device 9 can more accurately determine whether the vehicle and the own vehicle 10 have entered the same entrance (an effect corresponding to the invention according to claim 10).
[0397]
Further, the forward environment recognition device 9 can determine the control content and the alarm information according to the result of the determination (an effect corresponding to the invention according to claim 11).
[Brief description of the drawings]
FIG. 1 is a block diagram showing a configuration of a forward environment recognition device.
FIG. 2 is a schematic side view showing an installation position of a laser radar.
FIG. 3 is a schematic plan view showing an installation position of a laser radar.
FIG. 4 is a schematic side view showing a detectable range of the laser radar.
FIG. 5 is a schematic side view showing a detectable range of the laser radar.
FIG. 6 is a flowchart showing a procedure of processing by the forward environment recognition device.
FIG. 7 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 8 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 9 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 10 is an explanatory diagram showing a state in front of the own vehicle.
FIG. 11 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 12 is an explanatory diagram showing a state in front of the own vehicle.
FIG. 13 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 14 is an explanatory diagram showing a state in front of the own vehicle.
FIG. 15 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 16 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 17 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 18 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 19 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 20 is a graph showing a position distribution of a reflection point.
FIG. 21 is a graph showing an intensity distribution of a reflection point.
FIG. 22 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 23 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 24 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 25 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 26 is a block diagram illustrating a configuration of a forward environment recognition device.
FIG. 27 is a schematic side view showing installation positions of a laser radar and a camera.
FIG. 28 is a schematic plan view showing installation positions of a laser radar and a camera.
FIG. 29 is a flowchart showing a procedure of processing by the forward environment recognition device.
FIG. 30 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 31 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 32 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 33 is an explanatory diagram showing a method of calculating the width of a target image.
FIG. 34 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 35 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 36 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 37 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 38 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 39 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 40 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 41 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 42 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 43 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 44 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 45 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 46 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 47 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 48 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 49 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 50 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 51 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 52 is a schematic plan view showing positions of a reflection point and a front object.
FIG. 53 is an explanatory diagram showing a forward image acquired by a camera.
FIG. 54 is a schematic plan view showing positions of a reflection point and a front object.
[Explanation of symbols]
1-9 Forward environment recognition device
10 own car
11 Scanning laser radar (reflection point detection means)
12 Object detection unit (object detection means)
13 Object type discrimination unit (object type discrimination means)
14 control unit (control content determining means)
15 Camera (photographing means)
16 Object tracking processing unit (object tracking processing means)
17 Integrated processing unit (Integrated processing means)
22a, 100 horizontal edge
30-34 Toll gate
50 overhead sign

Claims (13)

A forward environment including a reflection point detecting means for scanning the front of the own vehicle in the traveling direction with a predetermined detection wave, detecting a reflection point reflecting the detection wave, and measuring a relative position of the reflection point with respect to the own vehicle. In the recognition device,
By detecting that reflection points close to each other among the reflection points are points on the same object, an object detection unit that detects a forward object,
The number of reflection points included in the front object is measured. If the number of the reflection points is larger than a predetermined reference value for the number of the reflection points, the type of the object that determines the front object as a toll gate A forward environment recognition device, comprising: a determination unit. The forward environment recognition device according to claim 1,
The object type determination means measures the distance from the reflection point included in the front object to the vehicle, and calculates the distribution of these distances.
The number of reflection points included in the front object is greater than a predetermined reference value for the number of reflection points,
In addition, when the distribution of the distance is larger than a predetermined reference value for the distribution of the distance, the front object is determined to be a tollgate, and the front environment recognition device is characterized in that the preceding environment is determined. The forward environment recognition device according to claim 1,
The object type determination means measures the distance from the reflection point included in the front object to the vehicle, and calculates the distribution of these distances.
Measure the intensity of the detection wave reflected at the reflection point included in the front object, calculate the distribution of these intensities,
The number of reflection points included in the front object is greater than a predetermined reference value for the number of reflection points,
And, if the distribution of the distance is larger than a predetermined reference value for the distribution of the distance, or if the distribution of the intensity is larger than a predetermined reference value for the distribution of the intensity. Is a front environment recognition device, wherein the front object is determined as a toll gate. The forward environment recognition device according to any one of claims 1 to 3,
The object type determining means may be configured such that the number of reflection points included in the front object is larger than a predetermined reference value for the number of reflection points, and the front object protrudes in the traveling direction of the own vehicle. A forward environment recognizing device comprising: determining a forward object as a toll booth when a part is included. The forward environment recognition device according to claim 4,
The object type determining means determines that the own vehicle is approaching the tollgate when a portion other than the protruding portion is not detected for the forward object determined to be a tollgate. Forward environment recognition device. The forward environment recognition device according to claim 5,
The forward environment recognizing device, wherein the object type determining means determines that the own vehicle is approaching the entrance of the tollgate when the number of detected protruding portions is two or less. . The forward environment recognition device according to any one of claims 1 to 6,
A forward environment recognizing device comprising a control content determining means for determining the control content of the own vehicle based on a result of the determination by the object type determining means. The forward environment recognition device according to claim 5 or 6,
Photographing means for photographing the front of the own vehicle in the traveling direction and acquiring an image of the front;
Forward object tracking processing means for measuring the size of the forward object photographed by the image means on the image when it is determined that the vehicle is approaching the tollgate by the object type determination means,
When the size is larger than a reference value predetermined for the size, integrated processing means for determining that the forward object and the vehicle enter the same toll gate entrance are provided. Forward environment recognition device. The forward environment recognition device according to claim 8,
The forward environment recognition device, wherein the integrated processing means determines that a vehicle exists in front of the own vehicle when a horizontal edge is drawn in the image. The forward environment recognition device according to claim 9,
The integration processing means predicts that a vehicle exists in front of the own vehicle when a horizontal edge is drawn in the image,
A forward environment recognition device, wherein the reflection point detecting means determines that no vehicle exists in front of the own vehicle when detecting a reflection point that is not detected when the vehicle actually exists. The forward environment recognition device according to any one of claims 8 to 10,
A forward environment recognizing device comprising a control content determining means for determining the control content of the own vehicle based on a result of the determination by the integration processing means. Scanning the front of the own vehicle in the traveling direction with a predetermined detection wave, detecting a reflection point reflecting the detection wave, and measuring a relative position of the reflection point with respect to the own vehicle, a reflection point detection step,
By predicting that reflection points close to each other among the reflection points are points on the same object, an object detection step of detecting a front forward object,
The number of reflection points included in the front object is measured. If the number of the reflection points is larger than a predetermined reference value for the number of the reflection points, the type of the object that determines the front object as a toll gate And a discriminating step. The forward environment recognition method according to claim 12,
In the object type determination step, the distance from the reflection point included in the front object to the vehicle is measured, and the distribution of these distances is calculated.
The number of reflection points included in the front object is greater than a predetermined reference value for the number of reflection points,
In addition, when the distribution of the distance is larger than a predetermined reference value for the distribution of the distance, the front object is determined to be a tollgate, and a front environment recognition method is provided.

Images