JP7152848B2 - External environment recognition device - Google Patents

Description

The present invention relates to an external environment recognition device that uses radar to recognize vehicles and the like around the vehicle.

In recent years, in vehicles, various driving control devices have been developed that enable autonomous driving by recognizing the driving environment, detecting the driving information of the own vehicle, and executing steering control and acceleration/deceleration control in cooperation with each other. techniques have been proposed and put into practical use.

In the vehicle external environment recognition device used in such a travel control device, a technique for detecting various objects (three-dimensional objects) including a preceding vehicle, a parallel running vehicle, and a following vehicle using a plurality of radars is known. ing. In such object detection using a plurality of radars, for example, Patent Document 1 describes a technique for improving the accuracy of determining the same object in an overlapping area where the scanning areas of two radars overlap and acquiring position information. , based on the position of the object (the position of the representative point of the object) detected by one of the two radars whose scanning areas partially overlap, a range is set for the course of the object, and the other radar is set within the range. A technique is disclosed for determining that an object detected by one radar and an object detected by the other radar are the same object when the position of an object detected by radar is included.

JP 2007-232594 A

However, in end regions in the scanning direction within the scanning region of the radar, the detection positions of the reflection points from the object tend to vary. Therefore, when object detection is performed using the reflection points detected by each radar as is, as in the technique disclosed in the above-mentioned Patent Document 1, a three-dimensional object existing in the overlapping area where the edge areas of the two radars overlap. can be difficult to detect accurately.

SUMMARY OF THE INVENTION It is an object of the present invention to provide an external environment recognition system capable of accurately detecting three-dimensional objects existing in an area where two radar scanning areas overlap.

A vehicle exterior environment recognition apparatus according to an aspect of the present invention scans a preset first scanning region in a horizontal direction with a first radar wave, and the first radar wave reflects off a three-dimensional object. first radar means for receiving reflected waves and detecting a plurality of first reflection points on the three-dimensional object; A second radar wave is horizontally scanned within a second scanning region preset so that the regions overlap each other, and the second radar wave receives a second reflected wave reflected by a three-dimensional object to receive the second radar means for detecting a plurality of second reflection points on a three-dimensional object, and in an overlapping area where the first scanning area and the second scanning area overlap, the first radar means An edge area in the scanning direction of the first radar wave in which detection accuracy of the first reflection point is lower than that of other areas in the first scanning area, and the first scanning area. a first reflection point exclusion means for excluding the first reflection points existing in a first exclusion area set on the one end side of the second radar means in the overlapping area; 2 scanning regions, the second scanning region is an end region in the scanning direction of the second radar wave in which the detection accuracy of the second reflection point is lower than that of the other regions , and second reflection point exclusion means for excluding the second reflection points existing in a second exclusion area set on the other end side; a plurality of the first reflection points not excluded and a plurality of the reflection points and representative point calculation means for forming a reflection point group consisting of a series of reflection points adjacent to each other based on the second reflection points, and calculating a representative point of the three-dimensional object for each reflection point group. is.

According to the vehicle exterior environment recognition device of the present invention, it is possible to accurately detect a three-dimensional object existing in an area where the scanning areas of two radars overlap.

Configuration diagram of vehicle driving support device Explanatory diagram showing the scanning area of the vehicle-mounted camera and each radar Explanatory diagram showing reflection points detected within the scanning area of the right front side radar Explanatory diagram showing reflection points detected within the scanning area of the right rear side radar Flowchart showing a three-dimensional object recognition routine using two radars (Part 1) Flowchart showing a three-dimensional object recognition routine using two radars (Part 2) Explanatory diagram showing reflection points of a passenger car detected in the overlapping area Explanatory drawing showing reflection point cloud of passenger car after selection of reflection points in superimposed area Explanatory diagram showing reflection points of a large trailer detected in two radar scanning areas including an overlapping area Explanatory drawing showing reflection point cloud of large trailer after selection of reflection points in superimposed area Carrier car side view Explanatory diagram showing reflection points of carrier cars detected in two radar scanning areas including an overlapping area Explanatory drawing showing the reflection point group of the carrier car after selecting the reflection points of the superimposed area

Hereinafter, embodiments of the present invention will be described with reference to the drawings. The drawings relate to one embodiment of the present invention, FIG. 1 is a configuration diagram of a vehicle driving support system, FIG. 2 is an explanatory diagram showing the scanning area of an on-vehicle camera and each radar, and FIG. Fig. 4 is an explanatory diagram showing reflection points detected in the scanning area of the right rear side radar, Figs. 5 and 6 show a three-dimensional object recognition routine using two radars 7 is an explanatory diagram showing the reflection points of the passenger car detected in the overlapping area, FIG. 8 is an explanatory diagram showing the group of reflection points of the passenger car after selecting the reflection points in the overlapping area, and FIG. FIG. 10 is an explanatory diagram showing the reflection points of the large trailer detected in the two radar scanning areas, FIG. 12 is an explanatory diagram showing the reflection points of the carrier car detected in the two radar scanning areas including the overlapping area, and FIG. 13 is the reflection point group of the carrier car after selecting the reflection points in the overlapping area. It is an explanatory view showing .

A vehicle driving support device 2 shown in FIG. 1 is mounted in a vehicle (self-vehicle) 1 (see FIG. 2) such as an automobile. This vehicle driving support device 2 includes a driving support control unit 11, an engine control unit (hereinafter referred to as "E/G_ECU") 12, a power steering control unit (hereinafter referred to as "PS_ECU") 13, a brake control unit (hereinafter referred to as " BK_ECU”) 14, etc. These control units 11 to 14 are connected through an in-vehicle communication line 15 such as a CAN (Controller Area Network). Each of the units 11 to 14 is composed of a microcomputer having a CPU, ROM, RAM, etc. The ROM stores a control program for realizing operations set for each system.

An input side of the driving support control unit 11 is connected to an arithmetic unit 31 of an external environment recognition device 30, which will be described later. The arithmetic unit 31, as the information about the environment outside the vehicle, for example, the lane in which the own vehicle 1 travels (traveling lane), the lane adjacent to the traveling lane (adjacent lane), and the preceding vehicle traveling in the traveling lane and the adjacent lane. It recognizes various kinds of information including information about a parallel running vehicle, etc., and outputs this recognition information to the driving support control unit 11 .

Further, on the input side of the driving support control unit 11, there are a vehicle speed sensor 35 for detecting the vehicle speed (own vehicle speed) V of the own vehicle 1, a yaw rate sensor 36 for detecting the yaw rate γ acting on the own vehicle 1, and an automatic operation switch. Various sensors and switches such as 21 are connected. Furthermore, a notification means 22 is connected to the output side of the driving support control unit 11 .

The automatic operation switch 21 is provided at a position that can be operated by the driver, such as the instrument panel or the steering wheel. It is possible to set the set vehicle speed at the time and set the driving mode during automatic driving to either the follow-up control mode or the overtaking control mode.

Then, when the follow-up control mode is selected as the operation mode in automatic driving, the driving support control unit 11 performs follow-up control through control of the E/G_ECU 12, PS_ECU 13, and BK_ECU 14. That is, when there is no preceding vehicle in the driving lane, the driving support control unit 11 performs constant speed control to maintain the vehicle speed V at the set vehicle speed and drive in the driving lane. Further, when there is a preceding vehicle ahead of the driving lane, the driving support control unit 11 performs follow-up control to keep the vehicle-to-vehicle distance at a predetermined distance and follow the preceding vehicle. In this case, even if the vehicle speed of the preceding vehicle is equal to or lower than the set vehicle speed of the own vehicle 1, the driving support control unit 11 continues follow-up control without overtaking the preceding vehicle.

On the other hand, when the overtaking control mode is selected, the driving support control unit 11 basically performs the above-described constant speed control or following control, and the vehicle speed of the preceding vehicle is slower than the set vehicle speed of the host vehicle 1 by a predetermined amount. In this case, overtaking control is executed to maintain the set vehicle speed of the own vehicle 1 .

However, even if the vehicle speed of the preceding vehicle is slower than the set vehicle speed of the own vehicle 1, if there is a parallel running vehicle or the like in the adjacent lane, or if there is a lane further adjacent to the adjacent lane to the adjacent lane. If there is a vehicle or the like to be changed, the driving support control unit 11 cancels the overtaking control. Alternatively, when the vehicle speed of the preceding vehicle is slower than the set vehicle speed of the own vehicle 1 and there is a parallel running vehicle or the like in the adjacent lane, or when the lane is changed from the lane further adjacent to the adjacent lane to the adjacent lane. If there is a vehicle or the like on the other side, the driving support control unit 11 temporarily decelerates the own vehicle speed, waits for the parallel running vehicle or the like to move a predetermined distance ahead, and then executes overtaking control.

The notification means 22 notifies the driver of the start or suspension of automatic driving by flashing display, character display, sound, etc., and is composed of a display lamp, a display, a speaker, and the like.

A throttle actuator 17 is connected to the output side of the E/G_ECU 12 . The throttle actuator 17 opens and closes the throttle valve of an electronically controlled throttle provided in the throttle body of the engine, and adjusts the intake air flow rate by opening and closing the throttle valve according to a drive signal from the E/G_ECU 12. By doing so, a desired engine output is generated.

An electric power steering motor 18 is connected to the output side of the PS_ECU 13 . This electric power steering motor 18 applies a steering torque to the steering mechanism by the rotational force of the motor. and lane change control (lane change control for overtaking control, etc.) for moving the host vehicle 1 to the adjacent lane.

A brake actuator 19 is connected to the output side of the BK_ECU 14 . The brake actuator 19 adjusts the brake hydraulic pressure supplied to the brake wheel cylinder provided for each wheel. A braking force is generated against the vehicle, forcing deceleration.

Next, the configuration of the vehicle exterior environment recognition device 30 will be specifically described.

The external environment recognition device 30 includes an on-vehicle camera 32, a navigation device 33, and a plurality of radars 34 (a left front side radar 34lf, a right front side radar 34rf, a left rear side radar 34rf, and a left rear side radar 34rf). A radar 34lr, a right rear side radar 34rr), a vehicle speed sensor 35, and a yaw rate sensor 36 are connected to form a main part.

The vehicle-mounted camera 32 is, for example, a stereo camera having a main camera 32a and a sub-camera 32b. These main camera 32a and sub-camera 32b are, for example, fixed in the front part of the cabin of the vehicle 1 with a predetermined interval in the vehicle width direction (left-right direction), and cover a predetermined area A1 (see FIG. 2) ahead in the traveling direction. Stereo imaging is possible from different left and right viewpoints.

The left and right image data captured by the in-vehicle camera 32 are processed, for example, as follows. That is, the arithmetic unit 31 first obtains distance information from the displacement amount of the corresponding positions for a pair of images taken by the main camera 32a and the sub camera 32b in the traveling direction of the own vehicle, and generates a distance image. . Then, based on the generated distance image, etc., the arithmetic unit 31 detects side walls such as white lines, guardrails along the road, curbs, etc., and three-dimensional objects (type, distance, speed, relative speed to the own vehicle, preceding vehicle information, etc.), etc., and outputs these recognition data to the driving support control unit 11. FIG.

In recognizing a white line, the arithmetic unit 31 evaluates the brightness change of pixels in the width direction of the road based on the knowledge that the white line has a higher brightness than the road surface, and calculates the left and right white line candidate points in the image plane. is located on the image plane. The position (x, y, z) of this white line candidate point on the real space is obtained by a known It is calculated by a coordinate conversion formula. The real space coordinate system set based on the position of the own vehicle has, for example, the road surface directly below the center of the main camera 32a as the origin O, the vehicle width direction as the X axis, the vehicle height direction as the Y axis, and the vehicle length direction. is defined as the Z-axis. Then, each white line candidate point converted into the coordinate system of the real space is grouped by, for example, a series of points that are close to each other, and approximated to a quadratic curve (white line approximation line) using the least squares method or the like. Here, in this embodiment, if there are adjacent lanes adjacent to the driving lane of the host vehicle 1, lanes further adjacent to the adjacent lanes, and oncoming lanes (hereinafter referred to as adjacent lanes, etc.), the arithmetic unit 31 Also recognize the white lines that separate the adjacent lanes. That is, in the left and right white line recognition of the present embodiment, not only the white lines that separate the driving lanes of the vehicle, but also the white lines that separate adjacent lanes and the like are separately recognized.

In recognizing side walls and three-dimensional objects, the arithmetic unit 31 compares the data on the distance image with pre-stored three-dimensional side wall data, three-dimensional object data, and other frames (windows) to determine the road surface. Along with extracting side wall data such as guardrails and curbs extending along the road, three-dimensional objects are extracted by classifying them into other three-dimensional objects such as automobiles, two-wheeled vehicles, pedestrians, and utility poles. In extracting the three-dimensional object data, the arithmetic unit 31 calculates the relative speed with respect to the own vehicle from the rate of temporal change in the distance (relative distance) from each own vehicle, and adds this relative speed and the own vehicle speed V. By doing so, the velocity of each three-dimensional object is calculated. At this time, in particular, three-dimensional objects classified as vehicles, based on their speed, assume that the forward direction of the own vehicle is positive. , the vehicle closest to the own vehicle is classified as a preceding vehicle, and a vehicle with a negative speed (a vehicle approaching the own vehicle) is classified and recognized as an oncoming vehicle.

The navigation device 33 includes a map database that stores map information (supplier data and predetermined updated data), and a navigation ECU that generates route information for realizing a navigation function. (none shown).

The map database stores information necessary for constructing a road map, such as node data and facility data. The node data relates to the position and shape of the roads that make up the map image. latitude, longitude), the direction and type of the road that includes the node point (for example, information such as highway, arterial road, city road), the type of road at the node point (straight section, arc section (arc curve section), Clothoid curve section (segmentation curve portion)) and curve curvature (or radius) data are included.

Then, the navigation ECU, for example, receives radio signals from GPS (Global Positioning System) satellites and acquires the position information (latitude and longitude) of the own vehicle 1, the own vehicle speed V acquired from the vehicle speed sensor 35, and the geomagnetism Identifying the position of the vehicle 1 on the map data based on the moving direction information of the vehicle 1 obtained from a sensor or a gyro sensor, etc., and recognizing various information such as the driving lane of the vehicle 1 and adjacent lanes. is possible.

The left front side radar 34lf and the right front side radar 34rf are millimeter wave radars, for example, and are arranged on the left and right sides of the front bumper, respectively. The front left side radar 34lf and the front right side radar 34rf scan areas (scanning areas Alf, Arf (see FIG. 2 ))).

The left rear side radar 34lr and the right rear side radar 34rr are millimeter wave radars, for example, and are arranged on the left and right sides of the rear bumper, respectively. These left rear side radar 34lr and right rear side radar 34rr scan an area (scanning area Alr , Arr (see FIG. 2)).

That is, each of the radars 3434lf, 34rf, 34lr, and 34rr scans the radar wave in the horizontal direction, and receives the reflected wave of the radar wave reflected by the object, thereby detecting a three-dimensional object such as a parallel running vehicle or a following vehicle. is detected as a radar object (radar OBJ).

In this case, for example, in order to continuously detect the reflection point R of a three-dimensional object such as a parallel running vehicle, the left rear side radar 34lr and the left front side radar 34lf are positioned at one end side (tip side) of the scanning area Alr. The partial area and the partial area on the other end side (rear end side) of the scanning area Alf are set to overlap each other to form an overlapping area Asl. Similarly, the right rear side radar 34rr and the right front side radar 34rf are divided into a partial area on one end side (front end side) of the scanning area Arr and a partial area on the other end side (rear end side) of the scanning area Arf. are set so as to form an overlapping region Asr in which are overlapped with each other.

When a plurality of reflection points R detected by each radar 34 are input, the arithmetic unit 31 calculates the distribution of the reflection points R based on preset conditions. Each reflection point R having a high probability is grouped. That is, the arithmetic unit 31 groups the point sequences of the reflection points R that are close to each other as a reflection point group. Then, the arithmetic unit 31 detects the radar OBJ for each group of grouped reflection points, calculates the representative point (representative point of the three-dimensional object) P of the detected radar OBJ, and , the amount of movement of the representative point P (amount of change in position with respect to the ground), and the acceleration of the representative point P are calculated as three-dimensional object information such as vehicles running in parallel and following vehicles.

In this case, for example, as shown in FIGS. 3 and 4, the plurality of reflection points R detected by each radar 34 are basically detected along a three-dimensional object surface such as a vehicle body surface. However, the detection position tends to vary in the end regions in the scanning direction within the scanning region A, and the reflection point R tends to be detected at a position different from the actual three-dimensional object surface. Therefore, the arithmetic unit 31 removes the reflection point R detected in the edge area of each radar 34 in the overlapping area As including such an edge area, and then extracts the representative point P of the three-dimensional object. calculate.

Hereinafter, the right rear side radar 34rr will be referred to as the first radar means, the right front side radar 34rf will be referred to as the second radar means, and the scanning area Arr of the right rear side radar 34rr will be referred to as the first scanning area. A case where the scanning area Arf of the radar 34rf is set as the second scanning area will be described as an example.

In this case, for example, in the overlapping region Asr of the scanning region Arr of the right rear side radar 34rr and the right front side radar 34rf, a partial region on the tip side (one end side) is detected by the right rear side radar 34rr. The reflection point R (reflection point Rrr) is set as a first exclusion area Ae1 for excluding the reflection point R (reflection point Rrr) detected by the right front side radar 34rf. It is set as a second exclusion area Ae2 for excluding (reflection point Rrf). Then, the arithmetic unit 31 excludes the reflection points Rrr that exist within the first exclusion area Ae1, excludes the reflection points Rrf that exist within the second exclusion area Ae2, and removes the reflection points Rrr and A representative point P of the three-dimensional object (radar OBJ) is calculated based on the reflection point Rrf.

Furthermore, when the behavior of the representative points P of two radar OBJs detected at distant positions matches, the arithmetic unit 31 determines that these radar OBJs represent the same three-dimensional object, and determines that the representative points P By integrating P, the representative point P of the final radar OBJ is set.

Here, by adjusting the mounting positions and scanning angles of the right rear side radar 34rr and the right front side radar 34rf, the first exclusion area Ae1 and the second exclusion area Ae2 divide the overlapping area Asr substantially equally. It should be set so that

Thus, in this embodiment, the arithmetic unit 31 implements the functions of first reflection point exclusion means, second reflection point exclusion means, and representative point calculation means.

Next, three-dimensional object recognition processing based on the reflection points Rrr and Rrf detected by the right rear side radar 34rr and the right front side radar 34rf will be described with reference to the flowchart of the three-dimensional object recognition routine shown in FIGS.

This routine is repeatedly executed in the arithmetic unit 31 at set time intervals. When the routine starts, the arithmetic unit 31 is first detected by the right rear side radar 34rr and the right front side radar 34rf in step S101. Among the reflection points R (reflection points Rrr and Rrf), the point sequences of the reflection points R that are close to each other are grouped as a reflection point group. As a result, for example, in the example shown in FIG. 7, a reflection point group including reflection points Rrr and reflection points Rrf is formed for a three-dimensional object (vehicle) existing within the overlapping area Asr, and only within the scanning area Arr. A reflection point group consisting of only reflection points Rrr is formed for an existing three-dimensional object (vehicle).

When the process proceeds from step S101 to step S102, the arithmetic unit 31 determines whether or not there is an unprocessed reflection point group for which the representative point P calculation processing has not been performed among the reflection point groups grouped in step S101. investigate.

Then, when it is determined in step S102 that there is no unprocessed reflection point group, the arithmetic unit 31 proceeds to step S110.

On the other hand, if it is determined in step S102 that there is an unprocessed reflection point group, the arithmetic unit 31 proceeds to step S103, extracts a new reflection point group from the unprocessed reflection point group, The process proceeds to step S104.

When proceeding from step S103 to step S104, the arithmetic unit 31 checks whether or not the currently extracted reflection point group exists in an area including the overlapping area Asr.

Then, when it is determined in step S104 that the reflection point group does not exist in the region including the overlapping region Asr, the arithmetic unit 31 proceeds to step S106.

On the other hand, if it is determined in step S104 that the group of reflection points exists in the region including the overlapping region Asr, the arithmetic unit 31 proceeds to step S105 and performs exclusion processing of the reflection point R.

That is, when the reflection point Rrr exists in the first exclusion area Ae1, the arithmetic unit 31 excludes the reflection point Rrr from the reflection point group as a reflection point with low detection accuracy. Further, when the reflection point Rrf exists in the second exclusion area Ae2, the calculation unit 31 excludes the reflection point Rrf from the reflection point group as a reflection point with low detection accuracy.

As a result, the reflection point Rrr detected in the end region on the one end side in the scanning region Arr of the right rear lateral radar 34rr is excluded, and the other end in the scanning region Arf of the right front lateral radar 34rf is excluded. Reflection points Rrf detected in partial regions are excluded.

Even when the reflection point Rrr in the first exclusion area Ae1 is excluded in this way, if a three-dimensional object exists in the first exclusion area Ae1, the right front side radar 34rf detects the same Since the reflection point Rrf of the three-dimensional object is detected with high accuracy, the continuity of the reflection point R is not interrupted within the region. Similarly, even if the reflection point Rrf within the second exclusion area Ae2 is excluded, if a three-dimensional object exists within the second exclusion area Ae2, the right rear side radar 34rr detects the same three-dimensional object. Since the reflection point Rrr of the object is detected with high accuracy, the continuity of the reflection point R is not interrupted within the region.

When proceeding from step S104 or step S105 to step S106, the arithmetic unit 31 linearly approximates the currently selected reflection point group. That is, the arithmetic unit 31 obtains a straight line that approximates the reflecting surface of the three-dimensional object by performing a well-known Hough transform or the like on the reflecting point group.

When proceeding from step S106 to step S107, the arithmetic unit 31 calculates a representative point P of the reflecting surface of the linearly approximated three-dimensional object. In this case, the arithmetic unit 31 sets, for example, the point on the approximate straight line that is closest to the origin O (the road surface just below the center of the main camera 32a) set on the host vehicle 1 as the representative point P (see FIG. 8). ).

When the process proceeds from step S107 to step S108, the arithmetic unit 31 determines whether or not the representative point corresponding to the representative point P calculated this time was also calculated in the previous process, i.e., the same radar OBJ as the radar OBJ detected this time. is also detected last time.

Then, when it is determined in step S108 that the representative point corresponding to the representative point P calculated this time has not been calculated last time, the arithmetic unit 31 returns to step S102.

On the other hand, if it is determined in step S108 that the representative point corresponding to the representative point P calculated this time has been calculated last time, the arithmetic unit 31 proceeds to step S109 to After calculating the relative speed between the own vehicle 1 and the three-dimensional object (representative point P), the amount of ground movement of the three-dimensional object (representative point P), the acceleration of the three-dimensional object (representative point P), etc. based on the amount, etc., step S102 back to

When proceeding from step S102 to step S110, the arithmetic unit 31 checks whether or not a plurality of representative points P have been calculated this time.

Then, when it is determined in step S110 that a plurality of representative points P have not been calculated, the arithmetic unit 31 exits the routine as it is.

On the other hand, if it is determined in step S110 that a plurality of representative points P have been calculated, the arithmetic unit 31 proceeds to step S111 to create a representative point set pattern paired with each representative point P detected this time. Among them, it is checked whether or not there is an unprocessed representative point set that has not been subjected to match determination, which will be described later.

Then, if it is determined in step S111 that there is no unprocessed representative point set, the arithmetic unit 31 exits the routine as it is.

On the other hand, if it is determined in step S111 that there is an unprocessed representative point set, the arithmetic unit 31 extracts a new set of representative point sets from the unprocessed representative point sets, and then proceeds to step S113. .

When proceeding from step S112 to step S113, the arithmetic unit 31 checks whether or not the relative velocities of the two representative points P forming the representative point set with respect to the host vehicle 1 match.

If it is determined in step S113 that the relative velocities of the two representative points P do not match, the arithmetic unit 31 determines that the three-dimensional objects related to the two representative points P are highly likely to be different three-dimensional objects. Then, the process returns to step S111.

On the other hand, if it is determined in step S113 that the relative velocities of the two representative points P match, the arithmetic unit 31 proceeds to step S114 to check whether the movement amounts of the two representative points P match.

If it is determined in step S114 that the movement amounts of the two representative points P do not match, the arithmetic unit 31 determines that the three-dimensional objects related to the two representative points P are highly likely to be different three-dimensional objects. Then, the process returns to step S111.

On the other hand, if it is determined in step S114 that the movement amounts of the two representative points P match, the arithmetic unit 31 proceeds to step S115 to check whether the accelerations of the two representative points match.

Then, when it is determined in step S115 that the accelerations of the two representative points P do not match, the arithmetic unit 31 determines that the three-dimensional objects (radar OBJ) related to the two representative points are highly likely to be different three-dimensional objects. Then, the process returns to step S111.

On the other hand, if it is determined in step S115 that the accelerations of the two representative points P match, the arithmetic unit 31 determines that the three-dimensional objects related to the two representative points are the same three-dimensional object, and proceeds to step S116. , two representative points P are integrated as a new representative point P, and then the process returns to step S111.

Although a detailed description is omitted, the left rear side radar 34lr is the first radar means, the left front side radar 34lf is the second radar means, and the scanning area Alr of the left rear side radar 34lr is The same processing can be performed when the first scanning area and the scanning area Alf of the left front side radar 34lf are used as the second scanning area.

According to this embodiment, the first radar set on one end side (front end side) in the overlapping region Asr where the scanning region Arr of the right rear lateral radar 34rr and the scanning region Arf of the right front lateral radar 34rf overlap each other while excluding the reflection point Rrr existing within the exclusion area Ae1 of and excluding the reflection point Rrf existing within the second exclusion area Ae2 set on the other end side (base end side) of the overlapping area Asr, By calculating the representative point P of the three-dimensional object (radar object) based on the non-excluded reflection point Rrr and reflection point Rrf, the three-dimensional object present in the area where the two radar scanning areas overlap can also be accurately detected. be able to.

That is, the first exclusion area Ae1 corresponding to the edge area of the scanning area Arr and the second exclusion area Ae2 corresponding to the edge area of the scanning area Arf are arranged in the overlapping area Asr without overlapping each other. By setting the right rear side radar 34rr and the right front side radar 34rf as follows to exclude the reflection point Rrr in the first exclusion area Ae1 and the reflection point Rrf in the second exclusion area Ae2, Even when a three-dimensional object exists within the superimposed region Asr, the reflection points R with low reliability can be accurately excluded without impairing the continuity of the reflection points R (reflection points Rrr and Rrf). Therefore, it is possible to accurately detect a three-dimensional object existing within the scanning area Arr of the right rear side radar 34rr and the right front side radar 34rf and the overlapping area Asr of the scanning area Arf.

In this case, for example, not only a three-dimensional object such as a passenger car shown in FIGS. 7 and 8 but also a large three-dimensional object such as a large trailer shown in FIGS. Therefore, accurate recognition can be performed.

On the other hand, for example, as shown in FIG. 11, in a carrier car or the like, it is difficult for the frame portion of the carrier to reflect the radar, and since the reflective range exists separately in the front and rear of the vehicle body, the reflection point groups are formed separately. Although there are cases (see FIG. 12), even in such a case, by integrating the representative points P of the three-dimensional objects calculated individually (the representative points after integration are shown as “P′” in FIG. 13) , can be accurately recognized as one three-dimensional object.

In this case, for example, when the following vehicle of the two vehicles is following the preceding vehicle by auto-cruising or the like in an adjacent lane, the relative speeds of the own vehicle 1 and each representative point P are compared. , and the match determination based only on the comparison of the amount of ground movement of each representative point P, it may be difficult to determine whether or not the three-dimensional object related to the two representative points P is the same three-dimensional object. By adding matching judgment by comparing the acceleration of the point P, it is possible to accurately judge whether or not the three-dimensional objects related to the two representative points P are the same three-dimensional object. In other words, even if the following vehicle is following the preceding vehicle, the following vehicle waits for the behavior of the preceding vehicle and responds, so there is always a gap in the timing of changes in acceleration between the preceding and following vehicles. By focusing on and adding matching determination by comparing the acceleration of each representative point P, it is possible to accurately determine whether or not the three-dimensional object related to two representative points P is the same three-dimensional object.

The present invention is not limited to the embodiments described above, and various modifications and changes are possible, which are also within the technical scope of the present invention.

For example, in the above-described embodiment, an example of a configuration in which the mounting positions and scanning angles of the respective radars are set so that the first exclusion area and the second exclusion area equally divide the overlapping area has been described. The invention is not limited to this. For example, the proportions of the first and second exclusion areas within the overlapping area are set unequal according to the type of radar used, vehicle conditions, objects to be detected, etc. is also possible.

1 … vehicle (own vehicle)
2 ... vehicle driving support device 11 ... driving support control unit 12 ... engine control unit 13 ... power steering control unit 14 ... brake control unit 15 ... in-vehicle communication line 17 ... throttle actuator 18 ... electric power steering motor 19 ... brake actuator 21 ... automatic Operation switch 22... Notifying means 30... External environment recognition device 31... Calculation unit (first reflection point exclusion means, second reflection point exclusion means, representative point calculation means)
32... In-vehicle camera 32a... Main camera 32b... Sub camera 33... Navigation device 34lf... Left front side radar 34lr... Left rear side radar 34rf... Right front side radar (second radar means)
34rr ... right rear side radar (first radar means)
35... Vehicle speed sensor 36... Yaw rate sensor Ae1... First exclusion area Ae2... Second exclusion area Alf... Scanning area Alr... Scanning area Arf... Scanning area Arr... Scanning area As (Asl, Asr)... Superimposed area P... Representative Point R (Rlf, Rrf, Rlr, Rrr) … Reflection point

Claims (2)

A preset first scanning area is horizontally scanned with a first radar wave, and a first reflected wave reflected by the three-dimensional object is received by the first radar wave. first radar means for detecting a first reflection point of
horizontally scanning a second radar wave in a second scanning region preset so that a partial region on the other end side overlaps a partial region on the one end side of the first scanning region; second radar means for receiving a second reflected wave of the second radar wave reflected by a three-dimensional object and detecting a plurality of second reflection points on the three-dimensional object;
In an overlapping area where the first scanning area and the second scanning area overlap, the detection accuracy of the first reflection point in the first scanning area by the first radar means is a different area. The first edge region in the scanning direction of the first radar wave that is lower than the a first reflection point exclusion means for excluding reflection points;
Within the superimposed area, an end portion in the scanning direction of the second radar wave where detection accuracy of the second reflection point in the second scanning area by the second radar means is lower than in other areas . a second reflection point exclusion means for excluding the second reflection points existing within a second exclusion area set on the other end side of the second scanning area;
Based on the plurality of the first reflection points and the plurality of the second reflection points that are not excluded , a reflection point group composed of a series of reflection points that are adjacent to each other is formed, and the three-dimensional object is formed for each of the reflection point groups . and a representative point calculation means for calculating a representative point of the vehicle exterior environment recognition device. 3. The representative point calculation means integrates the combination of the representative points when there are a plurality of the representative points and when there is a combination of the representative points with matching behavior. 1. The vehicle exterior environment recognition device according to 1.

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