TW202122294A - Vehicle control method and vehicle control system - Google Patents

Abstract

A vehicle control method and a vehicle control system are provided. The method is adapted to the vehicle control system mounted on a vehicle. A video stream including a plurality of road images are captured toward the front of the vehicle. A free space of each road image is detected. Each road image is divided into a plurality of vertical bar segmentations, and a plurality of boundary values of the free space respectively corresponding to the vertical bar segmentations are obtained, wherein the road images includes a current road image and at least one previous road images. A plurality of region boundary variety parameters respectively corresponding to the vertical bar segmentations are obtained according to the boundary values of the current road image and the boundary values of the previous road image. A driving status of the vehicle is controlled according to the region boundary variety parameters.

Description

Vehicle control method and vehicle control system

The present invention relates to a driving assistance technology, and particularly relates to a vehicle control method and a vehicle control system.

With the continuous investment in research on autonomous vehicles in recent years, the research and development and technology of autonomous vehicles have also been rapidly developed. Under the current technology, many related technologies, such as sensing technology, object recognition technology, and positioning technology, have been developed to basically meet the needs of autonomous vehicles. The ideal automatic driving system can correctly detect the drivable area of the road surface to avoid dangerous situations such as vehicle collision or vehicle departure from the road. Current research has proposed many methods to detect the drivable area for various driving situations, such as taking images of the road conditions in front of the vehicle and analyzing the road conditions images to detect the drivable area on the road surface. For example, the disparity map generated by the dual-lens camera device can effectively detect the drivable area, or the use of other object recognition technology and deep learning architecture can also effectively detect the drivable area. However, how to use the information of the drivable area to improve driving safety and stability is also a topic of concern to those skilled in the art.

In view of this, the present invention proposes a vehicle control method and a vehicle control system, which can control the vehicle according to the change trend of the boundary of the drivable area, thereby improving the safety and stability of the automatic driving system and the driving assistance system.

An embodiment of the present invention provides a vehicle control method, which is suitable for a vehicle control system on a vehicle, and includes the following steps: capturing a video stream including multiple road condition images toward the front of the vehicle; detecting the drivability in each road condition image Area; each road condition image is divided into a plurality of vertical strip-shaped parts, and multiple boundary values of the drivable area relative to the vertical strip-shaped parts are obtained, wherein the road condition image includes the current road condition image and at least one previous road condition image; According to the boundary value of the current road condition image and the boundary value of the at least one previous road condition image, obtain a plurality of area boundary change parameters respectively relative to the vertical strip portion; and control the driving state of the vehicle according to the area boundary change parameter.

The embodiment of the present invention provides a vehicle control system, which is suitable for a vehicle and includes a vehicle control device, a camera device, a storage device, and a controller. The camera device captures a video stream including multiple road condition images toward the front of the vehicle. The controller is coupled to the vehicle control device, the camera device and the storage device, and is configured to execute the instructions in the storage device to: detect the drivable area in each road condition image; divide each road condition image into a plurality of vertical strip-shaped parts, And obtain a plurality of boundary values of the drivable area with respect to the vertical strip portion, wherein the road condition image includes the current road condition image and at least one previous road condition image; according to the boundary value of the current road condition image and the boundary value of the at least one previous road condition image, Obtain a plurality of regional boundary change parameters relative to the vertical strip part; and control the driving state of the vehicle according to the regional boundary change parameters.

Based on the above, in the embodiment of the present invention, after detecting the drivable area in the road condition image, the boundary value of the drivable area relative to each vertical strip portion will be obtained. Then, the regional boundary change parameters of each vertical strip portion can be obtained by comparing the boundary value of the current road condition image with the corresponding boundary value of at least one previous road condition image. In this way, the vehicle control system can estimate the change trend of the usable area according to the change parameters of the area boundary, and control the driving state of the vehicle accordingly, so as to avoid the collision of the vehicle with obstacles and improve the safety of the vehicle.

In order to make the above-mentioned features and advantages of the present invention more comprehensible, the following specific embodiments are described in detail in conjunction with the accompanying drawings.

Part of the embodiments of the present invention will be described in detail in conjunction with the accompanying drawings. The reference symbols in the following description will be regarded as the same or similar elements when the same symbol appears in different drawings. These embodiments are only a part of the present invention, and do not disclose all the possible implementation modes of the present invention. More precisely, these embodiments are just examples of methods and systems within the scope of the patent application of the present invention.

Fig. 1 is a schematic diagram of a vehicle control system according to an embodiment of the present invention. Please refer to FIG. 1, the vehicle control system 10 includes a vehicle control device 110, a storage device 120, a camera device 130, and a controller 140. In one embodiment, the vehicle control system 10 can be configured in various types of vehicles, such as passenger cars, buses, golf carts, guided vehicles, trucks, or trucks. The present invention does not limit the type of vehicle equipped with the vehicle control system 10.

The vehicle control device 110 is, for example, a steering device, a brake device, a throttle device, a navigation device, or other vehicle components that can be used to control the driving state of the vehicle. The driving state is, for example, vehicle speed, braking state, driving direction or route planning and so on.

The storage device 120 is, for example, any type of fixed or removable random access memory (Random Access Memory, RAM), read-only memory (Read-Only Memory, ROM), flash memory (Flash memory), hard disk A disk or other similar devices or a combination of these devices are used to store data, program codes, images, etc. that may be used in the operation of the driving control system 10. That is, the storage device 120 is further used to record multiple instructions that can be executed by the processor 130.

The camera 130 is installed on the vehicle and used for shooting a video stream including multiple images toward the front of the vehicle. The imaging device 130 may include an imaging lens having a lens and a photosensitive element. The photosensitive element is used to sense the intensity of light entering the lens to generate an image. The photosensitive element may be, for example, a charge coupled device (CCD), a complementary metal-oxide semiconductor (CMOS) element or other elements, and the present invention is not limited here.

The controller 140 is coupled to the vehicle control device 110, the camera device 130 and the storage device 120 to control the overall operation of the vehicle control system 10. In this embodiment, the controller 140 is, for example, a central processing unit (Central Processing Unit, CPU), or other programmable microprocessor (Microprocessor), digital signal processor (Digital Signal Processor, DSP), programmable Controllers, Application Specific Integrated Circuits (ASIC), Programmable Logic Device (PLD), or other hardware devices with computing capabilities, but this disclosure is not limited to this.

Fig. 2 is a schematic diagram of a vehicle control system and a vehicle according to an embodiment of the present invention. Referring to FIG. 2, if the vehicle control system 10 is applied to the driving environment of the vehicle V1, the camera device 130 can be installed inside or outside the vehicle V1. However, FIG. 2 is only an exemplary illustration, and the present invention does not limit the number and actual positions of the camera 130, which can be designed according to actual application conditions. In an embodiment, the camera 130 may be installed on the front glass of the vehicle V1.

Fig. 3 is a flowchart of a rear-view mirror control method according to an embodiment of the present invention. Please refer to FIG. 3, the method of this embodiment is applicable to the vehicle control system 10 in the above-mentioned embodiment. The following is a description of the components of the vehicle control system 10 in this embodiment to control the vehicle according to the change trend of the drivable area detailed steps.

In step S301, the camera device 130 captures a video stream including multiple road condition images toward the front of the vehicle. Specifically, the camera 130 can continuously capture multiple road condition images at fixed time intervals, and the video stream is composed of these road condition images corresponding to different shooting time points. The aforementioned time interval is the reciprocal of the frame rate of the video stream. For example, assuming that the frame rate of the video stream is 60 fps, which means that the camera 130 captures 60 road condition images per second, the time interval between the road condition images is 1/60 second.

In step S302, the controller 140 detects the drivable area in each road condition image. Here, the drivable area is the range of the area in the road condition image that is determined as the vehicle drivable, and the present invention does not limit the method for detecting the drivable area. For example, the Republic of China Patent Publication No. 201913557 discloses a deep learning model that can detect drivable areas. The Republic of China Patent Publication No. 201327473 also discloses a method for detecting a drivable area using a disparity map. The non-patent document "Dan Levi et al.: "StixelNet: A Deep Convolutional Network for Obstacle Detection and Road Segmentation." BMVC 2015" also discloses a driving area detection method that combines object recognition, image cutting and deep learning models. It should be noted that the drivable area in the road condition image can be expressed based on the image coordinates, that is, the boundary of the drivable area can be expressed by the image coordinates.

In step S303, the controller 140 divides each road condition image into a plurality of vertical strip-shaped parts, and obtains a plurality of boundary values of the drivable area with respect to the vertical strip-shaped parts, respectively. In one embodiment, the road condition image includes a current road condition image and at least one previous road condition image. Specifically, these road condition images can be divided into multiple vertical strip-shaped parts, but the present invention does not limit the number and width of the vertical strip-shaped parts, which can be set according to actual needs. In addition, the controller 140 will generate the boundary of the drivable area corresponding to the boundary value of each vertical strip portion.

In one embodiment, when the drivable area is generated based on the columnar pixels (Sixel), such as the method for detecting drivable area in the aforementioned non-patent document, the road condition image has been detected during the process of detecting the boundary of the drivable area. It is divided into a plurality of vertical strip-shaped parts, and the estimation result of the boundary of the drivable area is also expressed as a plurality of boundary values respectively relative to the vertical strip-shaped part. In another embodiment, the boundary of the drivable area may change continuously from pixel to pixel, and the controller 140 may calculate each vertical strip after dividing each road condition image into a plurality of vertical strips. Obtain a plurality of boundary values relative to the vertical strip part by using the average value of the boundary of the drivable area in the section.

For example, FIG. 6 is a schematic diagram of the boundary value relative to each vertical strip portion according to an embodiment of the present invention. Please refer to FIG. 6, in this example, the drivable area is an area generated by removing obstacles such as other vehicles from the lane area. The road condition image Img1 is divided into N vertical strip-shaped parts, for example, 50 vertical strip-shaped parts. These vertical strips respectively have independent boundary values of the drivable area, and these boundary values can be represented by Y-axis pixel coordinates. For example, the vertical strip portion B4 corresponds to the boundary value Y4 of the drivable area, and the vertical strip portion B12 corresponds to the boundary value Y12 of the drivable area. Furthermore, these boundary values of the drivable area in the road condition image Img1 can be expressed as (n _bar , y), where n _bar represents the number index of the vertical bar, and y represents the Y axis where the boundary value is located. Pixel coordinates.

In step S304, the controller 140 obtains a plurality of regional boundary change parameters respectively relative to the vertical strip portion according to the boundary value of the current road condition image and the boundary value of at least one previous road condition image. In one embodiment, by comparing the boundary value of the current road condition image with the boundary value of the same vertical stripe in the previous road condition image one to one, the controller 140 can obtain the area corresponding to each vertical stripe. Boundary change parameters to know the change trend of the drivable area. In one embodiment, these regional boundary change parameters may include multiple boundary change trend parameters and/or multiple boundary change amplitude parameters respectively relative to the vertical strip portion. Here, the boundary change trend parameter is the boundary value change speed, and the boundary change amplitude parameter is the boundary value change acceleration. The boundary change trend parameter can be used to represent the expansion speed and the reduction speed of the driving area, and the boundary change amplitude parameter can be used to represent the expansion acceleration and the reduction acceleration of the travelable area.

In detail, FIG. 4 is a schematic diagram of a vehicle control method according to an embodiment of the present invention. 4, it should be noted that, in this example, the camera device 130 captures the previous road condition image Img_t0 after capturing the previous road condition image Img_t1, and after capturing the previous road condition image Img_t1, the current road condition image Img_t2 is captured. The controller 140 can use the drivable area detection model to obtain the current road condition image Img_t2, the previous road condition image Img_t1, and the previous road condition image Img_t0 respectively.

In the example of FIG. 4, the controller 140 can obtain the boundary change trend parameter P2 between the current road condition image Img_t2 and the previous road condition image Img_t1 according to the current road condition image Img_t2 and the previous road condition image Img_t1 (ie, the first previous road condition image). Specifically, the controller 140 subtracts the multiple boundary values B3 of the current road condition image Img_t2 from the multiple boundary values B2 of the previous road condition image Img_t1 to obtain multiple first boundary difference values respectively relative to the vertical strip portion. For example, the controller 140 subtracts the boundary value of the first vertical strip part in the current road condition image Img_t2 (n _bar =1, y) from the boundary value of the first vertical strip part in the previous road condition image Img_t1 (n _bar =1, y) to obtain the first boundary difference relative to the first vertical bar. Then, the controller 140 divides the first boundary difference relative to the vertical strip portion by the time interval Δt to obtain the boundary change trend parameter P2 between the current road condition image Img_t2 and the previous road condition image Img_t1. Assuming there are 50 vertical strip parts, the controller can obtain 50 boundary change trend parameters P2.

Similarly, the controller 140 can obtain the boundary change trend parameter between the previous road condition image Img_t1 and the previous road condition image Img_t0 according to the previous road condition image Img_t1 (ie, the first previous road condition image) and the previous road condition image Img_t0 (ie, the second previous road condition image). P1. Specifically, the controller 140 subtracts the multiple boundary values B1 of the previous road condition image Img_t0 from the multiple boundary values B2 of the previous road condition image Img_t1 to obtain multiple second boundary difference values with respect to the vertical strip portion, respectively. Then, the controller 140 divides the second boundary difference relative to the vertical strip portion by the time interval Δt to obtain the boundary change trend parameter P1 between the previous road condition image Img_t1 and the previous road condition image Img_t0. Assuming there are 50 vertical strip parts, the controller can obtain 50 boundary change trend parameters P1.

In addition, the controller 140 may subtract the result of the boundary change trend parameter P2 between the current road condition image Img_t2 and the previous road condition image Img_t1 and the multiple boundary change trend parameters P1 between the previous road condition image Img_t1 and the previous road condition image Img_t0. Divide by the time interval Δt to obtain the boundary change amplitude parameter P3. Assuming that there are 50 vertical strip parts, the controller can obtain 50 boundary variation range parameters P3.

Returning to the steps in FIG. 3, after acquiring a plurality of area boundary change parameters respectively relative to the vertical strip-shaped portion, in step S305, the controller 140 controls the driving state of the vehicle according to the area boundary change parameters. Specifically, after acquiring a plurality of regional boundary change parameters relative to the vertical strip portion, the controller 140 can estimate the boundary change trend of the drivable area, and control the driving of the vehicle according to the boundary change trend of the drivable area Status, such as decelerating, accelerating, braking, providing warnings, changing driving directions, prompting driving directions, planning driving paths, etc.

In one embodiment, at least part of the boundary change trend parameter between the current road condition image and the previous road condition image meets the positive change condition, which represents that the boundary of the drivable area moves away from the vehicle, and the controller 140 can control The vehicle control device 110 increases the vehicle speed. On the other hand, at least part of the boundary change trend parameter between the current road condition image and the previous road condition image meets the negative change condition, which represents that the boundary of the drivable area moves toward the direction of the vehicle, and the controller 140 can control the vehicle control device 110 and lower the speed. Specifically, the controller 140 can determine whether a positive change condition or a negative change condition is met based on the positive or negative of at least part of the boundary change trend parameters.

In one embodiment, when the boundary change trend parameter is positive, it represents that the boundary change trend parameter meets the positive change condition. When the boundary change trend parameter is negative, it represents that the boundary change trend parameter meets the negative change condition. However, the positive change condition or the negative change condition needs to be designed according to the preset position of the origin of the image coordinate. Those with ordinary knowledge in the field of the invention should change the design according to actual needs. In addition, in an embodiment, the controller 140 may take a part of the boundary change trend parameter directly in front of the vehicle driving route to make a judgment. For example, the controller 140 may take the boundary change trend parameters from the 15th vertical strip portion to the 35th vertical strip portion to determine the vehicle deceleration or vehicle acceleration.

In addition, in an embodiment, the controller 140 may further determine the vehicle speed acceleration of the vehicle according to at least some of the boundary change amplitude parameters. Alternatively, the controller 140 may further determine the speed check speed of the vehicle according to at least part of the boundary change range parameter. In detail, after knowing that the boundary of the drivable area is close to the vehicle or far from the vehicle according to the boundary change trend parameter, the controller 140 can estimate the acceleration of the drivable area close to the vehicle or the drivable area according to the boundary change amplitude parameter The acceleration of the boundary away from the vehicle. In this way, the controller 140 can determine the vehicle speed acceleration or vehicle deceleration according to the boundary change range parameter.

For example, FIG. 5 is a flowchart of a vehicle control method according to an embodiment of the present invention. Referring to FIG. 5, in step S501, the controller 140 determines whether the boundary change trend parameter in the area boundary change parameter is greater than zero. If the determination in step S501 is yes, it means that the drivable area in front of the vehicle is being expanded. Therefore, in step S502, the controller 140 decides to maintain the vehicle speed or increase the vehicle speed, and determines the vehicle speed acceleration according to the boundary change amplitude parameter in the area boundary change parameter. For example, the controller 140 may control the throttle according to the regional boundary change parameter after deciding to increase the vehicle speed.

On the other hand, if the determination in step S501 is no, it means that the drivable area in front of the vehicle is being reduced. Therefore, in step S503, the controller 140 determines the vehicle speed deceleration according to the boundary change magnitude parameter in the area boundary change parameter. For example, the controller 140 may control the braking force according to the boundary variation parameter after deciding to reduce the vehicle speed. In other words, the controller 140 can control the vehicle speed acceleration and the vehicle speed deceleration by controlling the braking force or the throttle level, and the throttle level and the braking force can be adjusted adaptively based on the boundary variation parameter.

In summary, in the embodiment of the present invention, the boundary change trend of the drivable area can be obtained by comparing the boundary values of the drivable area in successive road condition images, so as to control the vehicle according to the boundary change trend of the drivable area In order to avoid collisions between vehicles and obstacles and improve safety. In addition, the regional boundary change parameters used to indicate the trend of the boundary change of the drivable area can also be used to help the automatic vehicle decision-making system and the advanced driving assistance system provide more accurate judgments and real-time warnings, thereby improving the safety and stability of the vehicle. .

Although the present invention has been disclosed in the above embodiments, it is not intended to limit the present invention. Anyone with ordinary knowledge in the relevant technical field can make some changes and modifications without departing from the spirit and scope of the present invention. The protection scope of the present invention shall be subject to those defined by the attached patent application scope.

10: Vehicle control system 110: Vehicle control device 120: storage device 130: camera device 140: Controller V1: Vehicle P1, P2: boundary change trend parameters P3: Boundary change amplitude parameter B1~B3: boundary value Img_t0, Img_t1: images of previous road conditions Img_t2: current road condition image B4, B12: vertical strip part Img1: road condition image S301～S305, S501～S503: steps

Fig. 1 is a schematic diagram of a vehicle control system according to an embodiment of the present invention. Fig. 2 is a schematic diagram of a vehicle control system and a vehicle according to an embodiment of the present invention. Fig. 3 is a flowchart of a vehicle control method according to an embodiment of the present invention. Fig. 4 is a schematic diagram of a vehicle control method according to an embodiment of the present invention. Fig. 5 is a flowchart of a vehicle control method according to an embodiment of the present invention. FIG. 6 is a schematic diagram of the boundary value relative to each vertical strip portion according to an embodiment of the present invention.

S301~S305: steps

Claims (10)

A vehicle control method suitable for a vehicle control system on a vehicle, the method comprising: Capture a video stream including multiple road condition images towards the front of the vehicle; Detecting a drivable area in each of the road condition images; Divide each of the road condition images into a plurality of vertical strip-shaped parts, and obtain multiple boundary values of the drivable area with respect to the vertical strip-shaped parts, wherein the road condition images include the current road condition image and at least An image of previous road conditions; According to the boundary values of the current road condition image and the boundary values of the at least one previous road condition image, obtain a plurality of region boundary change parameters respectively relative to the vertical strip-shaped parts; and The driving state of the vehicle is controlled according to the change parameters of the regional boundaries. For the vehicle control method described in claim 1, wherein the regional boundary change parameters include a plurality of boundary change trend parameters relative to the vertical strip portions, and the at least one previous road condition image includes the first previous According to the road condition image, the step of obtaining the boundary change parameters of the regions respectively relative to the vertical strip-shaped parts according to the boundary values of the current road condition image and the boundary values of the at least one previous road condition image includes: Subtracting the boundary values of the first previous road condition image from the boundary values of the current road condition image to obtain a plurality of first boundary difference values respectively relative to the vertical strip-shaped parts; and The first boundary differences relative to the vertical strip parts are divided by a time interval to obtain the boundary change trend parameters between the current road condition image and the first previous road condition image. For the vehicle control method described in item 2 of the scope of patent application, the regional boundary change parameters include a plurality of boundary change amplitude parameters respectively relative to the vertical strip portions, and the at least one previous road condition image further includes a second According to the previous road condition image, the step of obtaining the boundary change parameters of the regions relative to the vertical strip portions according to the boundary values of the current road condition image and the boundary values of the at least one previous road condition image includes: Subtracting the boundary values of the second previous road condition image from the boundary values of the first previous road condition image to obtain a plurality of second boundary difference values respectively relative to the vertical strip-shaped parts; Dividing the second boundary differences relative to the vertical strip-shaped parts by the time interval to obtain the boundary change trend parameters between the first previous road condition image and the second previous road condition image; and Subtraction result between the boundary change trend parameters between the current road condition image and the first previous road condition image and the boundary change trend parameters between the first previous road condition image and the second previous road condition image Divide by the time interval to obtain the boundary change amplitude parameters. For the vehicle control method described in item 3 of the scope of patent application, the step of controlling the driving state of the vehicle according to the regional boundary change parameters includes: Responding to that at least part of the boundary change trend parameters between the current road condition image and the first previous road condition image meet the positive change condition, controlling a vehicle control device to increase the vehicle speed; and It is reflected that at least part of the boundary change trend parameters between the current road condition image and the first previous road condition image meet the negative change condition, and the vehicle control device is controlled to reduce the vehicle speed. For the vehicle control method described in item 4 of the scope of patent application, the step of controlling the vehicle control device to increase the vehicle speed includes: Determine the speed acceleration of the vehicle according to at least part of the boundary change range parameters, The steps of controlling the vehicle control device to reduce the vehicle speed include: Deceleration of the vehicle speed is determined according to at least part of the boundary change range parameters. A vehicle control system for a vehicle, including: A vehicle control device; A storage device that stores multiple commands; A camera device that captures a video stream including multiple road condition images toward the front of the vehicle; and A processor, coupled to the vehicle control device, the camera device, and the storage device, and configured to execute the instructions to: Detecting a drivable area in each of the road condition images; Divide each of the road condition images into a plurality of vertical strip-shaped parts, and obtain multiple boundary values of the drivable area with respect to the vertical strip-shaped parts, wherein the road condition images include current road condition images and at least An image of previous road conditions; According to the boundary values of the current road condition image and the boundary values of the at least one previous road condition image, obtain a plurality of regional boundary change parameters respectively relative to the vertical strip-shaped parts; and The vehicle control device is controlled according to the regional boundary change parameters to control the driving state of the vehicle. For the vehicle control system described in item 6 of the scope of patent application, the regional boundary change parameters include a plurality of boundary change trend parameters respectively relative to the vertical strip portions, and the at least one previous road condition image includes the first For the previous road condition images, the processor is further configured to: Subtracting the boundary values of the first previous road condition image from the boundary values of the current road condition image to obtain a plurality of first boundary difference values respectively relative to the vertical strip-shaped parts; and The first boundary differences relative to the vertical strip parts are divided by a time interval to obtain the boundary change trend parameters between the current road condition image and the first previous road condition image. For example, in the vehicle control system described in item 6 of the scope of patent application, the regional boundary change parameters include a plurality of boundary change amplitude parameters relative to the vertical strip portions, and the at least one previous road condition image further includes the first 2. The previous road condition image, the processor is further configured to: Subtracting the boundary values of the second previous road condition image from the boundary values of the first previous road condition image to obtain a plurality of second boundary difference values respectively relative to the vertical strip-shaped parts; Dividing the second boundary differences relative to the vertical strip-shaped parts by the time interval to obtain the boundary change trend parameters between the first previous road condition image and the second previous road condition image; and Subtraction result between the boundary change trend parameters between the current road condition image and the first previous road condition image and the boundary change trend parameters between the first previous road condition image and the second previous road condition image Divide by the time interval to obtain the boundary change amplitude parameters The vehicle control system according to the eighth scope of the patent application, wherein the processor is further configured to: Responding to that at least part of the boundary change trend parameters between the current road condition image and the first previous road condition image meet the positive change condition, controlling a vehicle control device to increase the vehicle speed; and It is reflected that at least part of the boundary change trend parameters between the current road condition image and the first previous road condition image meet the negative change condition, and the vehicle control device is controlled to reduce the vehicle speed. The vehicle control system according to the 9th scope of the patent application, wherein the processor is further configured to: The vehicle speed deceleration is determined according to at least part of the boundary change amplitude parameters, or the vehicle speed acceleration of the vehicle is determined according to at least part of the boundary change amplitude parameters.

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