JP6820958B2 - Vehicle control device and control method - Google Patents

Description

The present invention relates to a vehicle control device and a control method.

Conventionally, when it is determined that the object in front of the own vehicle detected from the own vehicle side is a stationary object, and it is determined that another vehicle traveling in front of the own vehicle can straddle the stationary object. A technique for excluding a stationary object from the target of emergency automatic braking on the own vehicle side has been proposed (see, for example, Patent Document 1). Specifically, the object in front of the own vehicle is detected by the in-vehicle radar mounted on the own vehicle. The stationary object means an object in a state of being stationary on the road, and specific examples of the stationary object include a manhole cover on the road, a falling object that has fallen on the road, and the like.

Japanese Patent No. 4210640

Here, the in-vehicle radar as described above may erroneously detect an object continuously in time even though the object does not actually exist in the detection area. Hereinafter, an object that is falsely detected even though the object does not actually exist in the detection area is referred to as a "false positive object".

As described above, when the in-vehicle radar erroneously detects an object continuously in time, the erroneous detection object is approaching the own vehicle when viewed from the own vehicle. In this case, the own vehicle may determine that the false positive object is an obstacle even though it does not actually exist and is a non-obstacle. The non-obstacle means an object that does not hinder the running of the own vehicle, and the obstacle means an object that does not hinder the running of the own vehicle. When the own vehicle determines that the false detection object is an obstacle, for example, it is conceivable that the false detection object is targeted for emergency automatic braking and the false detection object is erroneously applied.

Considering the above, when an object detected from the vehicle side corresponds to the above-mentioned false detection object, a new technique for appropriately determining that such an object is a non-obstacle is required.

The present invention has been made to solve the above problems, and provides a vehicle control device and a control method capable of determining whether or not an object detected from the vehicle side is a non-obstacle. The purpose is to get.

The vehicle control device of the present invention is an object by clustering a reflection point detection unit that detects a reflection point that reflects a detection wave transmitted from the vehicle side to an object and a reflection point detected by the reflection point detection unit. An object corresponding to the non-judgment cluster based on the clustering unit that generates the corresponding cluster for each and the reflection points in the non-judgment cluster that is the cluster in which the number of reflection points is equal to or greater than the threshold value generated by the clustering unit. A characteristic line calculation unit that calculates a characteristic line of a non-judgment target, a reflection point recording unit that records reflection points in a judgment cluster that is a cluster in which the number of reflection points is less than the threshold value, and a reflection point recording unit generated by the clustering unit. Calculated by the movement locus calculation unit and the characteristic line calculation unit that calculate the movement locus of the judgment target that is the object corresponding to the judgment cluster based on the time series data of the reflection points in the judgment cluster recorded by the reflection point recording unit. Based on the characteristic line to be determined and the movement locus calculated by the movement locus calculation unit, the determination unit that determines whether or not the determination target is a non-obstacle, and the reflection point in the non-judgment cluster, It includes an object width calculation unit that calculates the width of the non-judgment target, and the determination unit calculates the intersection point where the characteristic line calculated by the characteristic line calculation unit and the movement locus calculated by the movement locus calculation unit intersect. Then, based on the calculated intersection, it is determined whether or not the determination target is a non-obstacle, and the determination unit determines when the intersection on the characteristic line is located within the width calculated by the object width calculation unit. , It is determined that the determination target is a non-obstacle .

In the vehicle control method of the present invention, a step of detecting a reflection point that reflects a detection wave sent from the vehicle side to an object and a clustering of the detected reflection points generate a corresponding cluster for each object. A step and a step of calculating a characteristic line of a non-judgment target, which is an object corresponding to the non-judgment cluster, based on the generated reflection points in the non-judgment cluster which is a cluster in which the number of reflection points is equal to or more than the threshold value. Corresponds to the judgment cluster based on the step of recording the reflection points in the judgment cluster, which is a cluster in which the number of reflection points is less than the threshold, and the time-series data of the reflection points in the recorded judgment cluster. A step of calculating the movement locus of a determination target that is an object to be determined, a step of determining whether or not the determination target is a non-obstacle based on the calculated characteristic line and the calculated movement locus, and a non- A step of calculating the width of the non-judgment target based on the reflection point in the judgment cluster is provided , and in the judgment step, the characteristic line calculated by the step of calculating the characteristic line and the step of calculating the movement locus are provided. In the step of calculating the intersection with the movement locus calculated by the above, determining whether or not the determination target is a non-obstacle based on the calculated intersection, and determining, the intersection on the characteristic line is the width. If it is located within the width calculated by the step of calculating, it is determined that the determination target is a non-obstacle .

According to the present invention, it is possible to obtain a vehicle control device and a control method capable of determining whether or not an object detected from the vehicle side is a non-obstacle.

It is a block diagram which shows the own vehicle provided with the control device of the vehicle in Embodiment 1 of this invention. It is a block diagram which shows the control device of the vehicle in Embodiment 1 of this invention. It is explanatory drawing which shows the specific example of the reflection point detection processing executed by the reflection point detection unit of FIG. It is explanatory drawing which shows the specific example of the clustering process executed by the clustering part of FIG. It is explanatory drawing which shows the specific example of the representative point calculation process executed by the representative point calculation part of FIG. It is explanatory drawing which shows the specific example of the object width calculation process executed by the object width calculation part of FIG. It is explanatory drawing which shows the specific example of the characteristic line calculation process executed by the characteristic line calculation part of FIG. It is explanatory drawing which shows the specific example of the reflection point recording processing and the movement locus calculation processing executed by the reflection point recording unit and the movement locus calculation unit of FIG. 2, respectively. It is explanatory drawing which shows the specific example of the intersection calculation process executed by the intersection calculation part of the determination part of FIG. It is explanatory drawing which shows the 1st specific example of the non-obstacle determination process executed by the non-obstacle determination part of the determination part of FIG. It is explanatory drawing which shows the 2nd specific example of the non-obstacle determination processing executed by the non-obstacle determination part of the determination part of FIG. It is explanatory drawing which shows the specific example of the exclusion process executed by the exclusion part of FIG. It is a flowchart which shows the series of processing executed by the control device of the vehicle in Embodiment 1 of this invention. It is a block diagram which shows the control device of the vehicle in Embodiment 2 of this invention. It is explanatory drawing which shows the specific example of the process executed by the operation control part of FIG. It is a flowchart which shows the series of processing executed by the control device of the vehicle in Embodiment 2 of this invention.

Hereinafter, the vehicle control device and the control method according to the present invention will be described with reference to the drawings according to preferred embodiments. In the description of the drawings, the same parts or corresponding parts are designated by the same reference numerals, and duplicate description will be omitted.

Embodiment 1.
FIG. 1 is a configuration diagram showing an own vehicle 1 provided with a vehicle control device 20 according to the first embodiment of the present invention. As shown in FIG. 1, the own vehicle 1 is equipped with a radar 10 and a control device 20.

The radar 10 sends a detection wave toward the detection area 11 in front of the own vehicle 1. Specifically, the radar 10 reflects the radio wave by transmitting the radio wave as the detection wave from the own vehicle 1 side and receiving the radio wave reflected at the reflection point position on the object in the detection area 11. Get the reflection point. The radar 10 gives information about the acquired reflection point to the control device 20.

FIG. 1 illustrates a case where the object in the detection area 11 of the radar 10 is another vehicle 2 traveling in front of the own vehicle 1. In this case, the radar 10 acquires the reflection point derived from the other vehicle 2.

In the first embodiment, as a specific example of a sensor that acquires a reflection point that reflects a detection wave transmitted from the own vehicle 1 side to an object, a case where a radar 10 that transmits a radio wave as a detection wave is used is exemplified. However, it is not limited to this. For example, a sensor in the form of transmitting ultrasonic waves, light, or the like as a detection wave may be used instead of the radar 10. Specific examples of such a sensor include an ultrasonic sensor, an infrared sensor, an optical camera, and the like.

Next, the configuration of the control device 20 according to the first embodiment will be described with reference to FIG. FIG. 2 is a configuration diagram showing a vehicle control device 20 according to the first embodiment of the present invention.

As shown in FIG. 2, the control device 20 includes a reflection point detection unit 21, a clustering unit 22, a representative point calculation unit 23, an object width calculation unit 24, a characteristic line calculation unit 25, a reflection point recording unit 26, and a movement locus calculation unit. 27, a determination unit 28 and an exclusion unit 29 are provided. Hereinafter, each of these components of the control device 20 will be described.

<Reflection point detection unit 21>
The reflection point detection unit 21 detects the reflection point by receiving the reflection point that reflects the detection wave transmitted from the own vehicle 1 side to the object from the radar 10 as the reflection point detection process.

Here, an example of the reflection point detection process executed by the reflection point detection unit 21 will be described with reference to FIG. FIG. 3 is an explanatory diagram showing a specific example of the reflection point detection process executed by the reflection point detection unit 21 of FIG. Note that FIG. 3 illustrates a case where the objects detected by the radar 10 are an object corresponding to the reflection points A1 to A5 and an object corresponding to the reflection point B1.

In the situation shown in FIG. 3, the reflection point detection unit 21 detects the reflection points A1 to A5 and the reflection point B1. The objects corresponding to the reflection points A1 to A5 are other vehicles 2 traveling in front of the own vehicle 1. Further, as the object corresponding to the reflection point B1, the above-mentioned stationary object, the above-mentioned false positive object, and the like can be considered. In the first embodiment, as a specific example, the object corresponding to the reflection point B1 is assumed to be a stationary object.

<Clustering unit 22>
As a clustering process, the clustering unit 22 clusters the reflection points detected by the reflection point detection unit 21 to generate a cluster corresponding to each object. Specifically, the clustering unit 22 clusters, for example, the physical quantities of each reflection point detected by the reflection point detection unit 21, for example, reflection points having similar relative velocities, positions, and the like are derived from the same object.

Here, an example of the clustering process executed by the clustering unit 22 will be described with reference to FIG. FIG. 4 is an explanatory diagram showing a specific example of the clustering process executed by the clustering unit 22 of FIG.

As shown in FIG. 4, the clustering unit 22 clusters the reflection points A1 to A5 and the reflection points B1 detected by the reflection point detection unit 21. As a result, the clustering unit 22 generates a cluster C (A) including the reflection points A1 to A5 and a cluster C (B) including the reflection points B1.

Hereinafter, a cluster in which the number of reflection points is equal to or greater than the threshold value TH is referred to as a “non-judgment cluster”, and an object corresponding to the non-judgment cluster is referred to as a “non-judgment target”. Further, a cluster in which the number of reflection points is less than the threshold value TH is referred to as a "judgment cluster", and an object corresponding to the judgment cluster is referred to as a "judgment target". The threshold TH is, for example, preset and set to be an integer of 2 or more.

For example, when the threshold TH is set to be "3", in the situation shown in FIG. 4, the cluster C (A) having 5 reflection points is a non-determination cluster and the number of reflection points is large. Cluster C (B), which is 1, is a determination cluster. In this case, the object corresponding to the cluster C (A) corresponding to the non-judgment cluster, that is, the other vehicle 2, is the non-judgment target, and the object corresponding to the cluster C (B) corresponding to the judgment cluster, that is, the stationary object is , Is the subject of judgment.

<Representative point calculation unit 23>
As the representative point calculation process, the representative point calculation unit 23 calculates the representative points representing the reflection points in the non-determination cluster based on the reflection points in the non-determination cluster generated by the clustering unit 22. Further, the representative point calculation unit 23 calculates a representative point representing the reflection point in the determination cluster based on the reflection point in the determination cluster generated by the clustering unit 22. Specifically, the representative point calculation unit 23 calculates a representative point representing the reflection point in the cluster based on the reflection point included in the cluster.

Here, an example of the representative point calculation process executed by the representative point calculation unit 23 will be described with reference to FIG. FIG. 5 is an explanatory diagram showing a specific example of the representative point calculation process executed by the representative point calculation unit 23 of FIG.

As shown in FIG. 5, the representative point calculation unit 23 is a representative representative of the reflection points in the cluster C (A) based on the reflection points A1 to A5 in the cluster C (A) generated by the clustering unit 22. Calculate the points. Specifically, as shown in FIG. 5, the representative point calculation unit 23 calculates the reflection point A3 located at the center of the reflection points A1 to A5 in the cluster C (A) as a representative point. ..

Further, the representative point calculation unit 23 calculates a representative point representing the reflection point B1 in the cluster C (B) based on the reflection point B1 in the cluster C (B) generated by the clustering unit 22. Specifically, as shown in FIG. 5, the representative point calculation unit 23 calculates the reflection point B1 in the cluster C (B) as a representative point.

<Object width calculation unit 24>
The object width calculation unit 24 calculates the width W of the non-determination target based on the reflection points in the non-determination cluster as the object width calculation process. Specifically, the object width calculation unit 24 calculates the width W from, for example, the two most distant reflection points among the reflection points in the non-determination cluster.

Here, an example of the object width calculation process executed by the object width calculation unit 24 will be described with reference to FIG. FIG. 6 is an explanatory diagram showing a specific example of the object width calculation process executed by the object width calculation unit 24 of FIG.

As shown in FIG. 6, the object width calculation unit 24 calculates the width W of the other vehicle 2 corresponding to the non-determination target based on the reflection points A1 to A5 in the cluster C (A) corresponding to the non-determination cluster. To do. Specifically, as shown in FIG. 6, the object width calculation unit 24 calculates the width W from the two most distant reflection points A1 and A5 among the reflection points A1 to A5 in the cluster C (A). To do.

The representative point calculation unit 23 may be configured to change the representative point calculated by the above-mentioned representative point calculation process by using the width W calculated by the object width calculation unit 24. In this case, the representative point calculation unit 23 calculates the center point of the width W from the width W calculated by the object width calculation unit 24. The representative point calculation unit 23 compares the deviation between the representative point calculated by the representative point calculation process and the center point thereof and the preset threshold value. As a result of the comparison, if the deviation is equal to or greater than the threshold value, the representative point calculation unit 23 replaces the representative point calculated by the representative point calculation process with the center point, and sets the center point as the representative point.

<Characteristic line calculation unit 25>
The characteristic line calculation unit 25 calculates the characteristic line L to be non-determined based on the reflection points in the non-determination cluster generated by the clustering unit 22 as the characteristic line calculation process.

As an example, the characteristic line calculation unit 25 obtains an approximate line that approximates the reflection point in the non-determination cluster, and calculates the obtained approximate line as the characteristic line L. Any method may be used as an approximation method for approximating the reflection points in the non-determination cluster. For example, if linear approximation is used as the approximation method, the approximation line becomes a straight line, and if polynomial approximation is used as the approximation method, the approximation line becomes a curve.

Here, an example of the characteristic line calculation process executed by the characteristic line calculation unit 25 will be described with reference to FIG. 7. FIG. 7 is an explanatory diagram showing a specific example of the characteristic line calculation process executed by the characteristic line calculation unit 25 of FIG.

As shown in FIG. 7, the characteristic line calculation unit 25 obtains an approximate line that approximates the reflection points A1 to A5 in the cluster C (A) corresponding to the non-determination cluster, and uses the obtained approximate line as the characteristic line L. calculate. Note that FIG. 7 illustrates a case where linear approximation is used as an approximation method for approximating the reflection points A1 to A5 in the cluster C (A). In this case, the characteristic line L is a straight line.

<Reflection point recording unit 26 and movement locus calculation unit 27>
As the reflection point recording process, the reflection point recording unit 26 records the reflection points generated by the clustering unit 22 in the determination cluster in association with time. The reflection point recorded by the reflection point recording unit 26 may be the reflection point itself in the determination cluster, or may be a representative point representing the reflection point in the determination cluster. By repeating such reflection point recording processing with the passage of time, time-series data of reflection points in the determination cluster can be obtained.

As the movement locus calculation process, the movement locus calculation unit 27 calculates the movement locus M of the determination target based on the time series data of the reflection points in the determination cluster recorded by the reflection point recording unit 26.

Specifically, the movement locus calculation unit 27 obtains an approximate line that approximates the time series data of the reflection points in the determination cluster, and calculates the obtained approximate line as the movement locus M. Any method may be used as an approximation method for approximating the time series data of the reflection points in the determination cluster. For example, if linear approximation is used as the approximation method, the approximation line becomes a straight line, and if polynomial approximation is used as the approximation method, the approximation line becomes a curve.

Here, an example of the reflection point recording process and the movement locus calculation process executed by the reflection point recording unit 26 and the movement locus calculation unit 27, respectively, will be described with reference to FIG. FIG. 8 is an explanatory diagram showing specific examples of the reflection point recording process and the movement locus calculation process executed by the reflection point recording unit 26 and the movement locus calculation unit 27 of FIG. 2, respectively.

As shown in FIG. 8, the reflection point recording unit 26 records the reflection point B1 in the cluster C (B) corresponding to the determination cluster. In the situation shown in FIG. 8, the determination target is a stationary object, and the own vehicle 1 is traveling toward the determination target. Therefore, the reflection point B1 in the cluster C (B) changes in the direction of approaching the own vehicle 1 with the passage of time when viewed from the own vehicle 1. The reflection point recording unit 26 obtains time-series data of the reflection point B1 by recording the reflection point B1 that changes with time in this way over time.

As shown in FIG. 8, the movement locus calculation unit 27 obtains an approximate line that approximates the time series data of the reflection point B1 in the cluster C (B) corresponding to the determination cluster, and obtains the approximate line for the movement locus M. Calculate as. Note that FIG. 8 illustrates a case where polynomial approximation is used as an approximation method for approximating the time series data of the reflection point B1 in the cluster C (B). In this case, the movement locus M is a curved line.

<Judgment unit 28>
The determination unit 28 determines whether or not the determination target is a non-obstacle based on the characteristic line L calculated by the characteristic line calculation unit 25 and the movement locus M calculated by the movement locus calculation unit 27. .. The determination unit 28 includes an intersection calculation unit 281 and a non-obstacle determination unit 282 as specific configurations.

As the intersection calculation process, the intersection calculation unit 281 calculates an intersection P at which the characteristic line L calculated by the characteristic line calculation unit 25 and the movement locus M calculated by the movement locus calculation unit 27 intersect.

The non-obstacle determination unit 282 determines whether or not the determination target is a non-obstacle based on the intersection P calculated by the intersection calculation unit 281 as the non-obstacle determination process. Specifically, in the non-obstacle determination unit 282, when the intersection P on the characteristic line L is located within the width W calculated by the object width calculation unit 24, the determination target is a non-obstacle. Judge that there is. On the other hand, the non-obstacle determination unit 282 determines that the determination target is not a non-obstacle when the intersection P on the characteristic line L is not located within the width W, that is, the determination target is an obstacle. Is determined to be.

Here, an example of the intersection calculation process executed by the intersection calculation unit 281 will be described with reference to FIG. FIG. 9 is an explanatory diagram showing a specific example of the intersection calculation process executed by the intersection calculation unit 281 of the determination unit 28 of FIG.

As shown in FIG. 9, the intersection calculation unit 281 calculates the intersection P at which the characteristic line L calculated by the characteristic line calculation unit 25 and the movement locus M calculated by the movement locus calculation unit 27 intersect. In FIG. 9, when the y-axis is defined as the horizontal distance and the x-axis is defined as the vertical distance, the movement locus M is represented by x = ay ³ + by ² + cy + d, and the characteristic line L is x =. The case represented by ey is illustrated. However, a, b, c, d and e are constants.

Subsequently, an example of the non-obstacle determination process executed by the non-obstacle determination unit 282 will be described with reference to FIGS. 10 and 11. FIG. 10 is an explanatory diagram showing a first specific example of the non-obstacle determination process executed by the non-obstacle determination unit 282 of the determination unit 28 of FIG.

As shown in FIG. 10, the intersection P on the characteristic line L is located within the width W of the other vehicle 2. In this case, it is considered that the other vehicle 2 corresponding to the non-judgment target passes over the judgment target. That is, in this case, it is considered that the other vehicle 2 can straddle the determination target. Therefore, in such a case, the non-obstacle determination unit 282 determines that the determination target is a non-obstacle.

FIG. 11 is an explanatory diagram showing a second specific example of the non-obstacle determination process executed by the non-obstacle determination unit 282 of the determination unit 28 of FIG.

As shown in FIG. 11, the intersection P on the characteristic line L is located outside the width W of the other vehicle 2. In this case, it is considered that the other vehicle 2 corresponding to the non-judgment target does not pass over the judgment target. That is, in this case, it is considered that the other vehicle 2 cannot straddle the determination target. Therefore, in such a case, the non-obstacle determination unit 282 determines that the determination target is not a non-obstacle.

<Exclusion part 29>
As an exclusion process, the exclusion unit 29 excludes the determination target determined to be a non-obstacle by the non-obstacle determination unit 282 from the detection target that reflects the detection wave transmitted from the own vehicle 1 side. In the first embodiment, such a detection target exemplifies a case where an object existing in the detection area 11 of the radar 10, that is, a detection target of the radar 10.

Here, an example of the exclusion process executed by the exclusion unit 29 will be described with reference to FIG. FIG. 12 is an explanatory diagram showing a specific example of the exclusion process executed by the exclusion unit 29 of FIG.

As shown in FIG. 12, the exclusion unit 29 is non-obstructed by the non-obstacle determination unit 282 from the detection target of the radar 10, that is, the other vehicle 2 corresponding to the non-determination target and the stationary object corresponding to the determination target. Exclude stationary objects that correspond to the determination target determined to be an object.

Next, a series of processes of the control device 20 according to the first embodiment will be described with reference to FIG. FIG. 13 is a flowchart showing a series of processes executed by the vehicle control device 20 according to the first embodiment of the present invention. The control device 20 repeatedly performs a series of processes shown in FIG. 13 at a certain operation cycle, for example.

In step S101, the reflection point detection unit 21 executes the reflection point detection process. After that, the process proceeds to step S102.

When such step S101 is executed, the reflection point detection unit 21 detects the reflection points A1 to A5 and the reflection points B1 as illustrated in FIG. 3 above.

In step S102, the clustering unit 22 executes the clustering process using the result of the reflection point detection process executed in step S101. After that, the process proceeds to step S103.

When such step S102 is executed, the clustering unit 22 includes the cluster C (A) including the reflection points A1 to A5 and the cluster C (B) including the reflection points B1 as illustrated in FIG. And generate.

In step S103, the representative point calculation unit 23 executes the representative point calculation process using the result of the clustering process executed in step S102. After that, the process proceeds to step S104.

When such step S103 is executed, the representative point calculation unit 23 determines the reflection point A3 as a representative point representing the reflection points A1 to A5 in the cluster C (A), as illustrated in FIG. Is calculated. Further, the representative point calculation unit 23 calculates the reflection point B1 as a representative point representing the reflection point B1 in the cluster C (B).

In step S104, the control device 20 uses the result of the clustering process executed in step S102 to determine whether or not the number of reflection points in the cluster is equal to or greater than the threshold value TH for each cluster. As a result of the determination, the control device 20 executes the processes of steps S105 and S106 for the cluster in which the number of reflection points is equal to or greater than the threshold value TH, that is, the non-determination cluster. On the other hand, the control device 20 executes the processes of steps S107 and S108 for the cluster in which the number of reflection points is less than the threshold value TH as a result of the determination, that is, the determination cluster.

In step S105, the object width calculation unit 24 executes the object width calculation process for the reflection points in the non-determination cluster. After that, the process proceeds to step S106.

When such step S105 is executed, the object width calculation unit 24 determines, as illustrated in FIG. 6, based on the reflection points A1 to A5 in the cluster C (A) corresponding to the non-determination cluster. The width W of the other vehicle 2 corresponding to the non-judgment target is calculated.

In step S106, the characteristic line calculation unit 25 executes the characteristic line calculation process for the reflection points in the non-determination cluster. After that, the process proceeds to step S109.

When such step S106 is executed, the characteristic line calculation unit 25 bases on the reflection points A1 to A5 in the cluster C (A) corresponding to the non-determination cluster, as illustrated in FIG. The characteristic line L of the non-determination target is calculated.

In step S107, the reflection point recording unit 26 executes the reflection point recording process for the reflection points in the determination cluster. After that, the process proceeds to step S108.

In step S108, the movement locus calculation unit 27 executes the movement locus calculation process for the time series data of the reflection points in the determination cluster. After that, the process proceeds to step S109.

When such steps S107 and S108 are executed, the movement locus calculation unit 27 increases the time series data of the reflection point B1 in the cluster C (B) corresponding to the determination cluster, as illustrated in FIG. The movement locus M of the determination target is calculated based on.

In step S109, the intersection calculation unit 281 executes the intersection calculation process by using the result of the characteristic line calculation process executed in step S106 and the result of the movement locus calculation process executed in step S108. After that, the process proceeds to step S110.

When such step S109 is executed, the intersection calculation unit 281 calculates an intersection P where the characteristic line L of the non-determination target and the movement locus M of the determination target intersect, as illustrated in FIG. To do.

In step S110, the non-obstacle determination unit 282 uses the result of the object width calculation process executed in step S105 and the result of the intersection calculation process executed in step S109 to determine the intersection point P on the characteristic line L. It is determined whether or not the non-determination target is located within the width W.

If it is determined that the intersection P on the characteristic line L is located within the width W of the non-determination target, the process proceeds to step S111. On the other hand, if it is determined that the intersection P on the characteristic line L is not located within the width W of the non-determination target, the process proceeds to step S113.

When such step S110 is executed, in the situation illustrated in FIG. 10 above, the non-obstacle determination unit 282 is within the width W of the other vehicle 2 whose intersection P on the characteristic line L corresponds to the non-determination target. Judge that it is located in. Further, in the situation illustrated in FIG. 11 above, the non-obstacle determination unit 282 determines that the intersection P on the characteristic line L is not located within the width W of the other vehicle 2 corresponding to the non-determination target.

In step S111, the non-obstacle determination unit 282 determines that the determination target is the “non-obstacle”. After that, the process proceeds to step S112.

In step S112, the exclusion unit 29 excludes the determination target determined to be "non-obstacle" in step S111 from the detection targets of the radar 10. After that, the process ends.

When such step S112 is executed, the exclusion unit 29 corresponds to the determination target determined to be a “non-obstacle” from the detection targets of the radar 10 as illustrated in FIG. Exclude stationary objects.

In step S113, the non-obstacle determination unit 282 determines that the determination target is an “obstacle”. After that, the process ends.

As described above, according to the first embodiment, the vehicle control device 20 detects the reflection points that reflect the detection wave transmitted from the own vehicle 1 side to the object, and clusters the detected reflection points. It is configured to generate a corresponding cluster for each object. Further, the control device 20 calculates the characteristic line L of the non-determination target based on the generated reflection points in the non-determination cluster, and the movement locus M of the determination target based on the time series data of the reflection points in the determination cluster. Is configured to calculate. Further, the control device 20 is configured to determine whether or not the determination target is a non-obstacle based on the calculated characteristic line L and the calculated movement locus M.

As a result, even when the object detected from the own vehicle 1 side is a stationary object, a false detection object, or the like, it is possible to determine whether or not the object is a non-obstacle object. Further, the non-obstacle is excluded from the detection target by configuring the control device 20 further provided with a configuration for excluding the object determined to be a non-obstacle from the detection target with respect to the above configuration. Is possible.

Embodiment 2.
In the second embodiment of the present invention, the control device 20 having a configuration different from that of the first embodiment will be described. In the second embodiment, the description of the same points as in the first embodiment will be omitted, and the points different from the first embodiment will be mainly described.

FIG. 14 is a configuration diagram showing a vehicle control device 20 according to a second embodiment of the present invention. As shown in FIG. 14, the control device 20 is communicably connected to the operation control unit 30. Further, the control device 20 includes a reflection point detection unit 21, a clustering unit 22, a representative point calculation unit 23, an object width calculation unit 24, a characteristic line calculation unit 25, a reflection point recording unit 26, a movement locus calculation unit 27, and a determination unit 28. To be equipped.

The determination unit 28 includes an intersection calculation unit 281 and a non-obstacle determination unit 282. The non-obstacle determination unit 282 notifies the operation control unit 30 of the determination result of the non-obstacle determination process described in the first embodiment.

The driving control unit 30 controls the driving of the own vehicle 1 based on the detection target detected by the radar 10. In the second embodiment, the operation control unit 30 is a brake ECU (Electronic Control Unit) configured to apply the automatic brake when it is determined that the detection target of the radar 10 is the target to apply the automatic brake. Illustrate the case.

When the determination unit 28 notifies the determination result of whether or not the determination target is a non-obstacle, the operation control unit 30 controls the operation of the own vehicle 1 based on the determination result. Specifically, when the determination unit 28 notifies that the determination target is a non-obstacle, the operation control unit 30 excludes the determination target from the automatic braking targets.

Here, an example of the process executed by the operation control unit 30 will be described with reference to FIG. FIG. 15 is an explanatory diagram showing a specific example of the process executed by the operation control unit 30 of FIG. Note that FIG. 15 illustrates a case where the process is executed for a situation in which the determination target is determined to be a non-obstacle in the non-obstacle determination process described in the first embodiment.

As shown in FIG. 15, the operation control unit 30 excludes the determination target notified by the non-obstacle determination unit 282 that it is a non-obstacle from the targets of the automatic braking.

Next, a series of processes of the control device 20 according to the second embodiment will be described with reference to FIG. FIG. 16 is a flowchart showing a series of processes executed by the vehicle control device 20 according to the second embodiment of the present invention.

Steps S101 to S110 shown in FIG. 16 are the same as steps S101 to S110 shown in FIG. 13 described in the first embodiment.

In step S111, similarly to step S111 shown in FIG. 13, the non-obstacle determination unit 282 determines that the determination target is the “non-obstacle”. After that, the process proceeds to step S114.

In step S114, the non-obstacle determination unit 282 notifies the operation control unit 30 of the determination result in step S111, that is, that the determination target is a non-obstacle. In this case, the operation control unit 30 excludes the determination target notified that it is a non-obstacle from the targets of the automatic braking. After that, the process ends.

In step S113, similarly to step S113 shown in FIG. 13, the non-obstacle determination unit 282 determines that the determination target is an “obstacle”. After that, the process ends.

As described above, according to the second embodiment, the vehicle control device 20 is configured to notify the driving control unit 30 of the determination result of the non-obstacle determination process described in the first embodiment. .. As a result, the operation control unit 30 can perform appropriate operation control by using the notified determination result. In particular, when the operation control unit 30 is a brake ECU, it is possible to prevent the operation control unit 30 from accidentally applying the automatic brake by targeting an object notified as a non-obstacle to the emergency automatic braking. Can be done.

Each function of the control device 20 in the above-described first and second embodiments is realized by a processing circuit. The processing circuit may be dedicated hardware or a processor that executes a program stored in memory.

When the processing circuit is dedicated hardware, the processing circuit may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array). , Or a combination of these.

On the other hand, when the processing circuit is a processor, each function of the control device 20 is realized by software, firmware, or a combination of software and firmware. Software and firmware are written as programs and stored in memory. The processor realizes each of the above-mentioned functions by reading and executing the program stored in the memory.

It should be noted that some of the above-mentioned functions may be realized by dedicated hardware and some may be realized by software or firmware.

In this way, the processing circuit can realize each of the above-mentioned functions by hardware, software, firmware, or a combination thereof.

Although the first and second embodiments have been described as examples of the present invention, the present invention is not limited to the configurations of the first and second embodiments, and is carried out within a range not deviating from the gist of the present invention. It is possible to appropriately combine each of the configurations 1 and 2 of the above, add some modifications to each configuration, and partially omit each configuration.

1 own vehicle, 2 other vehicles, 10 radar, 11 detection area, 20 control device, 21 reflection point detection unit, 22 clustering unit, 23 representative point calculation unit, 24 object width calculation unit, 25 characteristic line calculation unit, 26 reflection point Recording unit, 27 movement locus calculation unit, 28 judgment unit, 281 intersection calculation unit, 282 non-obstacle determination unit, 29 exclusion unit, 30 operation control unit.

Claims (8)

A reflection point detector that detects a reflection point that reflects the detection wave sent from the vehicle side to the object,
A clustering unit that generates a cluster corresponding to each object by clustering the reflection points detected by the reflection point detection unit.
Based on the reflection points in the non-determination cluster, which is a cluster in which the number of reflection points is equal to or greater than the threshold value, the characteristic line of the non-determination target, which is an object corresponding to the non-determination cluster, is generated by the clustering unit. The characteristic line calculation unit to be calculated and
A reflection point recording unit that records the reflection points in the determination cluster, which is a cluster in which the number of reflection points is less than the threshold value, generated by the clustering unit.
A movement locus calculation unit that calculates a movement locus of a determination target that is an object corresponding to the determination cluster based on the time series data of the reflection points in the determination cluster recorded by the reflection point recording unit.
A determination unit that determines whether or not the determination target is a non-obstacle based on the characteristic line calculated by the characteristic line calculation unit and the movement locus calculated by the movement locus calculation unit.
An object width calculation unit that calculates the width of the non-judgment target based on the reflection point in the non-judgment cluster, and
Equipped with a,
The determination unit
The intersection of the characteristic line calculated by the characteristic line calculation unit and the movement locus calculated by the movement locus calculation unit is calculated, and the determination target is the non-obstacle based on the calculated intersection. Judge whether it is a thing or not,
The determination unit
When the intersection on the characteristic line is located within the width calculated by the object width calculation unit, it is determined that the determination target is the non-obstacle.
Vehicle control device. The characteristic line calculation unit
Wherein said calculated approximation line that approximates the reflection point in the non-determination cluster, the approximate line obtained, the control apparatus for a vehicle according to claim 1 which is calculated as the characteristic line. The movement locus calculation unit
The invention according to claim 1 or 2 , wherein an approximate line that approximates the time series data of the reflection point in the determination cluster recorded by the reflection point recording unit is obtained, and the obtained approximate line is calculated as the movement locus. Vehicle control device. Claims 1 to 3 further include an exclusion unit that excludes the determination target determined to be a non-obstacle by the determination unit from the detection target that reflects the detection wave transmitted from the vehicle side. The vehicle control device according to any one of the following items. Any one of claims 1 to 3 , wherein the determination unit notifies the operation control unit that controls the operation of the vehicle based on the determination result as to whether or not the determination target is the non-obstacle. The vehicle control device according to item 1. The vehicle control device according to any one of claims 1 to 5 , wherein the detection wave is transmitted by a radar mounted on the vehicle. A reflection point detector that detects the reflection point that reflects the detection wave sent to the object,
A clustering unit that generates a cluster by clustering the reflection points detected by the reflection point detection unit, and a clustering unit.
Based on the reflection points in the non-determination cluster, which is a cluster in which the number of reflection points is equal to or greater than the threshold value, the characteristic line of the non-determination target, which is an object corresponding to the non-determination cluster, is generated by the clustering unit. Characteristic line calculation unit to calculate and
Movement of a determination target that is an object corresponding to the determination cluster based on the time series data of the reflection points in the determination cluster that is a cluster in which the number of reflection points is less than the threshold value generated by the clustering unit. A movement locus calculation unit that calculates the locus and
A determination unit that determines whether or not the determination target is a non-obstacle based on the characteristic line calculated by the characteristic line calculation unit and the movement locus calculated by the movement locus calculation unit.
An object width calculation unit that calculates the width of the non-judgment target based on the reflection point in the non-judgment cluster, and
Equipped with a,
The determination unit
The intersection of the characteristic line calculated by the characteristic line calculation unit and the movement locus calculated by the movement locus calculation unit is calculated, and the determination target is the non-obstacle based on the calculated intersection. Judge whether it is a thing or not,
The determination unit
When the intersection on the characteristic line is located within the width calculated by the object width calculation unit, it is determined that the determination target is the non-obstacle.
Vehicle control device. The step of detecting the reflection point that reflects the detection wave sent from the vehicle side to the object,
A step of generating a corresponding cluster for each object by clustering the detected reflection points, and
A step of calculating the characteristic line of the non-judgment target, which is an object corresponding to the non-judgment cluster, based on the generated reflection points in the non-judgment cluster which is a cluster in which the number of the reflection points is equal to or more than the threshold value. ,
A step of recording the reflection points in the determination cluster, which is a cluster in which the number of reflection points is less than the threshold value, is generated.
Based on the recorded time-series data of the reflection points in the determination cluster, a step of calculating the movement locus of the determination target, which is an object corresponding to the determination cluster, and
A step of determining whether or not the determination target is a non-obstacle based on the calculated characteristic line and the calculated movement locus.
A step of calculating the width of the non-determination target based on the reflection point in the non-determination cluster, and
Equipped with a,
In the determination step,
The intersection of the characteristic line calculated by the step of calculating the characteristic line and the movement locus calculated by the step of calculating the movement locus is calculated, and the determination target is based on the calculated intersection. Determines whether or not is the non-obstacle
In the determination step,
When the intersection on the characteristic line is located within the width calculated by the step of calculating the width, it is determined that the determination target is the non-obstacle.
How to control the vehicle.

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