Vehicle avoidance control method and apparatus, and device and storage medium

Abstract

A vehicle avoidance control method and apparatus, and a device and a storage medium. The method comprises the steps of: on the basis of target vehicle information and lane line information, calculating the distance from edge edge of a target vehicle to the inner edge of a lane line of a host vehicle, and by means of the distance, determining whether the target vehicle needs to be avoided; when it is determined that the target vehicle needs to be avoided, calculating, on the basis of the distance, the height of the target vehicle and the relative speed between the target vehicle and the host vehicle, the timing for the host vehicle to avoid the target vehicle; on the basis of a preset initial avoidance distance, calculating the lateral distance of the host vehicle avoiding the target vehicle; and on the basis of the timing and lateral distance of the host vehicle avoiding the target vehicle, controlling the host vehicle to perform intelligent avoidance.

Description

A control method, device, equipment and storage medium for avoiding vehicles

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Chinese patent application No. 202311277440.7 filed on September 27, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to the field of intelligent driving technology, and in particular to a control method, device, equipment, and storage medium for avoiding a vehicle. Background Art

[0004] When intelligent driving is enabled, the driver feels pressured when overtaking a large vehicle, requiring adaptive lateral shifting to avoid the large vehicle. However, current intelligent driving features on the market suffer from issues such as late avoidance, low avoidance success rates, frequent unnecessary avoidance maneuvers, and frequent driver takeovers.

[0005] Currently, most existing technologies use the lateral distance or relative speed of two vehicles to determine whether a vehicle needs to avoid and the timing of avoidance. The judgment results of this avoidance solution are not accurate, and it is easy to make false avoidances or missed avoidances, causing discomfort to the driver.

[0006] Therefore, how to improve the accuracy of vehicle avoidance is a technical problem that needs to be solved urgently.

[0007] Summary of the Invention

[0008] The main purpose of the present disclosure is to provide a control method, device, equipment and storage medium for avoiding vehicles, which can adapt to different types of large vehicles and different road types, improve the accuracy of avoidance, and also reduce the number of times the driver takes over.

[0009] According to a first aspect of the present disclosure, a method for controlling a vehicle to avoid is provided, comprising: calculating the distance from the edge of a target vehicle to the inner edge of a self-lane line based on target vehicle information and lane line information, and judging whether it is necessary to avoid the target vehicle based on the distance; when it is determined that it is necessary to avoid the target vehicle, calculating the timing for the self-vehicle to avoid the target vehicle based on the distance, the height of the target vehicle, and the relative speed between the target vehicle and the self-vehicle; calculating the lateral distance for the self-vehicle to avoid the target vehicle based on a preset initial avoidance distance; and controlling the self-vehicle to perform intelligent avoidance based on the timing and lateral distance for the self-vehicle to avoid the target vehicle.

[0010] According to the second aspect of the present disclosure, a control device for avoiding a vehicle is provided, including: a decision module, which is used to calculate the distance from the edge of the target vehicle to the inner edge of the own lane line based on the target vehicle information and the lane line information, and judge whether the target vehicle needs to be avoided based on the distance; a calculation module, which is used to calculate the timing for the own vehicle to avoid the target vehicle based on the distance, the height of the target vehicle and the relative speed between the target vehicle and the own vehicle when it is determined that the target vehicle needs to be avoided; based on a preset initial avoidance distance, calculate the lateral distance for the own vehicle to avoid the target vehicle; and a control module, which is used to control the own vehicle to perform intelligent avoidance based on the timing and lateral distance for the own vehicle to avoid the target vehicle.

[0011] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; a memory, wherein computer-readable instructions are stored on the memory, and when the computer-readable instructions are executed by the processor, the processor is prompted to implement the steps of any one of the methods described in the first aspect.

[0012] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, which stores computer program instructions. When the computer program instructions are executed by a computer, the computer is caused to perform the steps of any one of the methods described in the first aspect.

[0013] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0015] FIG1 shows a flow chart of a control method for avoiding a vehicle according to some embodiments of the present disclosure;

[0016] FIG2 shows a schematic diagram of a control device for avoiding a vehicle according to some embodiments of the present disclosure;

[0017] FIG3 shows a schematic diagram of an electronic device according to some embodiments of the present disclosure;

[0018] FIG4 shows a schematic diagram of a computer-readable program medium according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0019] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent the same or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0020] Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the blocks shown in the drawings are functional entities that do not necessarily correspond to physically or logically separate entities.

[0021] The embodiments of the present disclosure provide a control method, device, equipment and storage medium for avoiding vehicles, which can adapt to different types of large vehicles and different types of roads, improve the accuracy of avoidance, and also reduce the number of times the driver takes over.

[0022] To achieve the above technical effects, the general ideas of this disclosure are as follows:

[0023] A method for controlling a vehicle to avoid a collision may include the following steps:

[0024] S101: Calculate the distance from the edge of the target vehicle to the inner edge of the own lane based on the target vehicle information and lane line information, and determine whether to avoid the target vehicle based on the distance;

[0025] S102: When it is determined that the target vehicle needs to be avoided, calculating a timing for the ego vehicle to avoid the target vehicle based on the distance, the height of the target vehicle, and the relative speed between the target vehicle and the ego vehicle;

[0026] S103: Calculating the lateral distance between the vehicle and the target vehicle based on the preset initial avoidance distance; and

[0027] S104: Controlling the ego vehicle to perform intelligent avoidance according to the timing and lateral distance of the ego vehicle avoiding the target vehicle.

[0028] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0029] 1 , which shows a flow chart of a method for controlling a vehicle to avoid a collision according to some embodiments of the present disclosure, as shown in FIG1 , the method may include steps S101 to S104 .

[0030] In step S101, the distance from the edge of the target vehicle to the inner edge of the lane is calculated based on the target vehicle information and the lane line information, and the distance is used to determine whether the target vehicle needs to be avoided.

[0031] During the implementation process, the camera and radar can be used to obtain the target vehicle information of the target vehicles around the vehicle and the lane line information of the lane. In some embodiments, the target vehicle information may include: the width of the target vehicle, the height of the target vehicle, the distance from the center point of the target vehicle to the center point of the vehicle, and the longitudinal distance from the target vehicle to the vehicle; the lane line information may include the lane line equation of the lane, which may include the lane line equation on the left side of the lane: Y L =A 0+ A1x+A2x 2 +A3x 3 , and the lane line equation on the right side of the lane: Y R =A 0+ A1x+A2x 2 +A3x 3 , where Y L Y is the distance from the center point of the front axle to the inner edge of the left lane, R is the distance from the center point of the ego vehicle's front axle to the inner edge of the right lane, x is the longitudinal distance from the target vehicle to the ego vehicle, A0 is the lateral distance from the center point of the ego vehicle's front axle to the lane line on the target vehicle's side, A1 is the angle between the ego vehicle's heading and the lane line on the target vehicle's side, A2 is the curvature of the lane line on the target vehicle's side, and A3 is the rate of change of the lane line curvature.

[0032] In some embodiments, the vehicle avoidance function is triggered only when the distance between the edge of the vehicle and the inner edge of the lane (i.e., the edge of target vehicle A to the inner edge of the lane of ego vehicle B) is L, and 0≤L≤L0. L0 is a set threshold value that can be calibrated based on the height of the target vehicle. The higher the height of the target vehicle, the greater the psychological pressure on the ego vehicle driver when the target vehicle passes. In this case, even if the target vehicle is far away, it is necessary to avoid it. Therefore, the higher the height of the target vehicle, the larger L0 is.

[0033] In order to reduce avoidance judgment errors caused by incorrect vehicle type recognition, the vehicle can be used as a target vehicle only when the vehicle type meets the requirements of being a large vehicle and the width or length of the target vehicle is greater than a certain value.

[0034] It should be noted that when the distance from the edge of the target vehicle to the inner edge of the lane line is greater than the set threshold, it is determined that there is no need to avoid the target vehicle, and when the distance from the edge of the target vehicle to the inner edge of the lane line is less than the set threshold, it is determined that the target vehicle needs to be avoided.

[0035] Before calculating the distance from the edge of the target vehicle to the inner edge of the lane, it is also possible to determine whether the lane is a straight road or a curve.

[0036] If the lane type is a straight road and the target vehicle is in the left lane of the vehicle, the formula can be used: Calculate the horizontal distance L from the edge of the target vehicle to the inner edge of the lane line h , where D is the distance from the center point of the target vehicle to the center point of the vehicle, W is the width of the target vehicle, S is the longitudinal distance from the target vehicle to the vehicle, and Y L It is the distance from the center point of the front axle to the inner edge of the left lane.

[0037] If the lane type is a straight road and the target vehicle is in the right lane of the vehicle, the formula can be used: Calculate the horizontal distance L from the edge of the target vehicle to the inner edge of the lane line h .

[0038] If the lane type is a curve, you can use the formula: Calculate the vertical distance L from the edge of the target vehicle to the inner edge of the lane line v .

[0039] It should be noted that the type of the lane can be determined as a straight road or a curved road based on whether the value of A2 / 2 is greater than or equal to 3000. If the lane type is a straight road, that is, A2 / 2 is greater than or equal to 3000, then L can be simplified to L h If the lane type is a curve, that is, A2 / 2 is less than 3000, then L can be simplified to L v That is, if the lane type is determined to be a straight road, then L = L h If the lane type is determined to be a curve, then L = L v .

[0040] In step S102, when it is determined that the target vehicle needs to be avoided, the timing for the vehicle to avoid the target vehicle is calculated based on the distance, the height of the target vehicle, and the relative speed between the target vehicle and the vehicle.

[0041] In some embodiments, the initial avoidance timing corresponding to the distance from the edge of the target vehicle to the inner edge of the own lane line can be determined by looking up a table, the first correction coefficient for the initial avoidance timing corresponding to the relative speed of the target vehicle and the own vehicle can be determined, and the second correction coefficient for the initial avoidance timing corresponding to the height of the target vehicle can be determined. Based on the initial avoidance timing, the first correction coefficient and the second correction coefficient, the timing for the own vehicle to avoid the target vehicle can be calculated.

[0042] It should be noted that the initial avoidance timing refers to the moment when the longitudinal distance from the target vehicle to the own vehicle is equal to the initially set distance, and the timing for the own vehicle to avoid the target vehicle refers to the moment when the longitudinal distance from the target vehicle to the own vehicle is less than or equal to the target distance, where the target distance is calculated based on the initially set distance.

[0043] The corresponding relationship between the distance L between the edge of the target vehicle and the inner edge of the lane and the initial avoidance timing T can be referred to as shown in the following Table 1:

[0044] Table 1

[0045] Taking the distance L within the range of 0<L≤0.2m and the vehicle speed of 100km / h as an example, the initial set distance is 1.2*100 / 3.6≈33.3, and the initial avoidance timing is when the longitudinal distance between the target vehicle and the vehicle is equal to 33.3m.

[0046] The corresponding relationship between the relative speed V of the target vehicle and the ego vehicle and the first correction coefficient P1 can be referred to as shown in the following Table 2:

[0047] Table 2

[0048] The corresponding relationship between the height H of the target vehicle and the second correction coefficient P2 can be referred to as shown in the following Table 3:

[0049] Table 3

[0050] For the initial avoidance timing corresponding to each distance L, the relative speed and vehicle height are used to make corrections to obtain the final timing for the ego vehicle to avoid the target vehicle.

[0051] For example, when the distance L is within the range of 0 < L ≤ 0.2 m, the ego vehicle's speed is 100 km / h, the relative speed V ≤ 10 km / h, and the vehicle height H < 3 m, a table is used to calculate the initial set distance to be 33.3 m, the first correction coefficient P1 to be 0.8, and the second correction coefficient P2 to be 0.8. The target distance is then calculated to be 33.3 * 0.8 * 0.8 = 21.312 m. Therefore, the moment the longitudinal distance from the target vehicle to the ego vehicle is less than or equal to 21.312 m is the moment when the ego vehicle should avoid the target vehicle.

[0052] In step S103, based on the preset initial avoidance distance, the lateral distance between the ego vehicle and the target vehicle is calculated.

[0053] In some embodiments, a third correction factor for the initial avoidance distance corresponding to the width of the road on which the vehicle is located can be determined by table lookup. A fourth correction factor for the initial avoidance distance corresponding to the speed of the vehicle can also be determined. Furthermore, a fifth correction factor for the initial avoidance distance corresponding to the road curvature radius interval of the road on which the vehicle is located can be determined. A sixth correction factor for the initial avoidance distance can be determined based on whether there is a road edge in the adjacent lane on the avoidance side. A seventh correction factor for the initial avoidance distance can be determined based on whether there is a VRU (Vunerable Road User) or vehicle in the adjacent lane on the avoidance side.

[0054] The lateral distance that the vehicle avoids the target vehicle is calculated based on the product of the preset initial avoidance distance, the third correction coefficient, the fourth correction coefficient, the fifth correction coefficient, the sixth correction coefficient and the seventh correction coefficient.

[0055] For ease of understanding, the following example illustrates how, after determining the timing for the ego vehicle to avoid the target vehicle, an initial avoidance distance can also be determined. This initial avoidance distance can be calibrated based on road conditions, the driver's driving habits, and the stability of the ego vehicle's centering control. In some embodiments, the initial avoidance distance can be Y0 = 30 cm.

[0056] The corresponding relationship between the road width and the third correction coefficient k1 can be referred to as shown in the following Table 4:

[0057] Table 4

[0058] The corresponding relationship between the vehicle speed and the fourth correction coefficient k2 can be referred to as shown in the following Table 5:

[0059] Table 5

[0060] The corresponding relationship between the road curvature radius and the fifth correction coefficient k3 can be referred to as shown in the following Table 6:

[0061] Table 6

[0062] The corresponding relationship between whether there is a road edge in the adjacent lane on the avoidance side and the sixth correction coefficient k4 can be referred to as shown in the following Table 6:

[0063] Table 6

[0064] The corresponding relationship between whether there is a VRU or vehicle in the adjacent lane on the avoidance side and the seventh correction coefficient k5 can be referred to as shown in the following Table 7:

[0065] Table 7

[0066] According to the formula Y1=Y0*k1*k2*k3*k4*k5, the lateral distance Y1 that the vehicle needs to avoid the target vehicle can be calculated.

[0067] Step S104: Control the vehicle to perform intelligent avoidance according to the timing and lateral distance of the vehicle avoiding the target vehicle.

[0068] It is understandable that the vehicle can be controlled to avoid the target vehicle based on the calculated timing and lateral distance of the vehicle.

[0069] In some embodiments, when the time for the ego vehicle to avoid the target vehicle arrives and the distance from the center point of the target vehicle to the center point of the ego vehicle is less than or equal to the calculated lateral distance, the ego vehicle is controlled to avoid the target vehicle.

[0070] In some embodiments, during the process of avoiding a target vehicle, if it is determined that the target vehicle has not been lost, the avoidance is ended when the longitudinal distance from the target vehicle to the own vehicle is greater than a first set distance, or the distance from the center point of the target vehicle to the center point of the own vehicle is greater than a second set distance.

[0071] If it is determined that the target vehicle is lost, the longitudinal distance from the target vehicle to the own vehicle is calculated based on the length of the own vehicle, the speed of the own vehicle, the length of the target vehicle, the average speed of the target vehicle, the average longitudinal distance from the target vehicle to the own vehicle, and the predicted start and end time of the avoidance; if the longitudinal distance from the target vehicle to the own vehicle is greater than or equal to the first set distance, the avoidance is ended; otherwise, the vehicle continues to be controlled to avoid.

[0072] In some embodiments, if the target vehicle is determined to be lost, the formula: Calculate the longitudinal distance S from the target vehicle to the vehicle, where v t is the vehicle speed, v target is the average speed of the target vehicle within the preset time before the target vehicle is lost, T is the predicted avoidance start to end time, s0 is the average longitudinal distance from the target vehicle to the ego vehicle within the preset time before the target vehicle is lost, L target is the length of the target vehicle, L ego The length of your vehicle.

[0073] After the ego vehicle overtakes the target vehicle, there are two ways to end the avoidance.

[0074] In some embodiments, if the system uses a side angle radar or a side view camera, and the side angle radar or the side view camera can operate normally and the target vehicle is not lost during the overtaking process, the avoidance action is canceled after the side angle radar or the side view camera detects that the self-vehicle has overtaken the target vehicle by 15m (that is, the longitudinal distance from the target vehicle to the self-vehicle is greater than 15m), or when it is detected that the target vehicle changes lanes away from the self-vehicle and the distance from the center point of the target vehicle to the center point of the self-vehicle is greater than 5m, the avoidance action is canceled.

[0075] In other embodiments, if the system does not use side angle radar and side view camera, or the side angle radar and side view camera are unavailable, or the target vehicle is lost during the process of overtaking the target vehicle, the system enters predictive control, and the predictive control method is as follows:

[0076] In order to prevent the target vehicle from entering the blind spot or being lost, and thus causing the control time to be too long, the target vehicle's speed and distance recognition errors may be prevented, and the target vehicle's speed v1, v2, v3, v4, v5 and longitudinal distances s1, s2, s3, s4, s5 within five periods (e.g., 250ms) before the target vehicle is lost may be obtained. Then, the minimum and maximum values ​​of the five speeds and five longitudinal distances are removed and the average value is calculated. The corresponding average speed v of the target vehicle within the preset time period before the target vehicle is lost is obtained. target and the average longitudinal distance s0 between the target vehicle and the ego vehicle during the preset time period before the target vehicle is lost.

[0077] According to the formula: The average speed of the target vehicle within a preset time period before the target vehicle is lost can be calculated.

[0078] According to the formula: The average longitudinal distance between the target vehicle and the ego vehicle within a preset time period before the target vehicle is lost can be calculated.

[0079] Assume the length of the vehicle is L ego , the length of the target vehicle is L target , considering that the ego vehicle will accelerate and decelerate during the process of overtaking the target vehicle, it is necessary to calculate the vehicle mileage in real time. Assume that the ego vehicle speed at time t is v t The predicted time from the start to the end of the avoidance is T. The predicted vehicle will cancel the avoidance action after overtaking the target vehicle by 15m. The speed of the target vehicle during the overtaking process is v. target , when the formula satisfies After that, it is considered that the avoidance end time has been reached. If there is no target vehicle in front of the ego vehicle to continue avoiding, the avoidance ends immediately and the ego vehicle returns to the center after the avoidance is completed.

[0080] It is understandable that these two methods can make the judgment of the timing of the vehicle returning to the center more accurate, avoiding the problem of returning to the center too early or too late.

[0081] Referring to Figure 2, Figure 2 shows a schematic diagram of a control device for avoiding a vehicle according to some embodiments of the present disclosure. As shown in Figure 2, the device includes: a decision module 201: which is used to calculate the distance from the edge of the target vehicle to the inner edge of the own lane line based on the target vehicle information and the lane line information, and judge whether it is necessary to avoid the target vehicle based on the distance; a calculation module 202: which is used to calculate the timing for the own vehicle to avoid the target vehicle based on the distance, the height of the target vehicle and the relative speed between the target vehicle and the own vehicle when it is determined that the target vehicle needs to be avoided; based on the preset initial avoidance distance, calculate the lateral distance for the own vehicle to avoid the target vehicle; and a control module 203: which is used to control the own vehicle to perform intelligent avoidance based on the timing and lateral distance for the own vehicle to avoid the target vehicle.

[0082] In some embodiments, the device also includes an acquisition module (not shown), which is used to use a camera and a radar to obtain target vehicle information of target vehicles around the own vehicle and lane line information of the own lane, wherein the target vehicle information includes the width of the target vehicle, the height of the target vehicle, the distance from the center point of the target vehicle to the center point of the own vehicle, and the longitudinal distance from the target vehicle to the own vehicle, and the lane line information includes the lane line equation of the own lane.

[0083] In some embodiments, the calculation module 202 is further configured to determine the type of the lane; when the lane is determined to be a straight road, the calculation module 202 is configured to determine the type of the lane according to the formula: Calculate the horizontal distance from the edge of the target vehicle to the inner edge of the lane line, where L h is the horizontal distance from the edge of the target vehicle to the inner edge of the lane line, D is the distance from the center point of the target vehicle to the center point of the own vehicle, W is the width of the target vehicle, A0 is the lateral distance from the center point of the front axle of the own vehicle to the lane line on the target vehicle side, A1 is the angle between the heading of the own vehicle and the lane line on the target vehicle side, A2 is the curvature of the lane line on the target vehicle side, A3 is the rate of change of the lane line curvature, and S is the longitudinal distance from the target vehicle to the own vehicle; and when the type of the own lane is determined to be a curve, according to the formula: Calculate the vertical distance from the edge of the target vehicle to the inner edge of the lane line, where L v It is the vertical distance from the edge of the target vehicle to the inner edge of the lane line.

[0084] In some embodiments, the calculation module 202 is also used to determine the initial avoidance timing corresponding to the distance from the edge of the target vehicle to the inner edge of the own lane line; determine the first correction coefficient for the initial avoidance timing corresponding to the relative speed of the target vehicle and the own vehicle; determine the second correction coefficient for the initial avoidance timing corresponding to the height of the target vehicle; and calculate the timing for the own vehicle to avoid the target vehicle based on the initial avoidance timing, the first correction coefficient and the second correction coefficient.

[0085] In some embodiments, the calculation module 202 is further used to determine a third correction coefficient for the initial avoidance distance corresponding to the road width of the vehicle; determine a fourth correction coefficient for the initial avoidance distance corresponding to the speed of the vehicle; determine a fifth correction coefficient for the initial avoidance distance corresponding to the road curvature radius of the vehicle; determine a sixth correction coefficient for the initial avoidance distance based on whether there is a road edge in the leading lane on the avoidance side; determine a seventh correction coefficient for the initial avoidance distance based on whether there is a vulnerable traffic participant (VRU) or vehicle in the adjacent lane on the avoidance side; and calculate the lateral distance of the vehicle to avoid the target vehicle based on the product of the preset initial avoidance distance, the third correction coefficient, the fourth correction coefficient, the fifth correction coefficient, the sixth correction coefficient and the seventh correction coefficient.

[0086] In some embodiments, the control module 203 is also used to, during the process of avoiding the target vehicle, if it is determined that the target vehicle has not been lost, end the avoidance when the longitudinal distance from the target vehicle to the own vehicle is greater than a first set distance, or the distance from the center point of the target vehicle to the center point of the own vehicle is greater than a second set distance; if it is determined that the target vehicle is lost, calculate the longitudinal distance from the target vehicle to the own vehicle based on the length of the own vehicle, the speed of the own vehicle, the length of the target vehicle, the average speed of the target vehicle, the average longitudinal distance from the target vehicle to the own vehicle, and the predicted start to end time of the avoidance; and end the avoidance if the longitudinal distance from the target vehicle to the own vehicle is greater than or equal to the first set distance.

[0087] In some embodiments, the calculation module 202 is further configured to calculate the following formula: Calculate the longitudinal distance from the target vehicle to the vehicle, where S is the longitudinal distance from the target vehicle to the vehicle, v t is the vehicle speed, v target is the average speed of the target vehicle within the preset time before the target vehicle is lost, T is the predicted avoidance start to end time, s0 is the average longitudinal distance from the target vehicle to the ego vehicle within the preset time before the target vehicle is lost, L target is the length of the target vehicle, L ego The length of your vehicle.

[0088] The electronic device 300 according to this embodiment of the present disclosure is described below with reference to Figure 3. The electronic device 300 shown in Figure 3 is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0089] As shown in Figure 3, electronic device 300 is implemented as a general-purpose computing device. Components of electronic device 300 may include, but are not limited to, the aforementioned at least one processing unit 310, the aforementioned at least one storage unit 320, and a bus 330 connecting various system components (including storage unit 320 and processing unit 310).

[0090] The storage unit stores program code, which can be executed by the processing unit 310, so that the processing unit 310 performs the steps described in the above "Example Method" section of this specification according to various exemplary embodiments of the present disclosure.

[0091] The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 321 and / or a cache memory unit 322 , and may further include a read-only memory unit (ROM) 323 .

[0092] The storage unit 320 may also include a program / utility 324 having a set (at least one) of program modules 325, such program modules 325 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0093] Bus 330 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0094] The electronic device 300 can also communicate with one or more external devices (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 300, and / or any device that enables the electronic device 300 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 350. Furthermore, the electronic device 300 can also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 360. As shown, the network adapter 360 communicates with other modules of the electronic device 300 via a bus 330. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 300, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0095] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0096] According to the solution of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above-mentioned method of this specification is stored. In some possible implementations, various aspects of the present disclosure can also be implemented in the form of a program product, which includes program code. When the program product is executed on a terminal device, the program code is used to cause the terminal device to perform the steps according to various exemplary embodiments of the present disclosure described in the "Exemplary Methods" section of this specification.

[0097] Referring to FIG4 , a program product 400 for implementing the above-described method according to an embodiment of the present disclosure is described. The program product 400 may be a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0098] The program product may be implemented in any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0099] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0100] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0101] The program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0102] Furthermore, the figures above are merely illustrative of the processes included in the methods according to exemplary embodiments of the present disclosure and are not intended to be limiting. It is readily understood that the processes illustrated in the figures above do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0103] The foregoing description is intended only to provide specific embodiments of the present disclosure, which will enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments shown herein, but rather to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

[0104] The present disclosure provides a vehicle avoidance control method, device, equipment, and storage medium, wherein the method includes the following steps: calculating the distance from the edge of the target vehicle to the inner edge of the own lane based on target vehicle information and lane line information, and determining whether the target vehicle needs to be avoided based on the distance; when it is determined that the target vehicle needs to be avoided, calculating the timing for the own vehicle to avoid the target vehicle based on the distance, the height of the target vehicle, and the relative speed between the target vehicle and the own vehicle; calculating the lateral distance for the own vehicle to avoid the target vehicle based on a preset initial avoidance distance; and controlling the own vehicle to perform intelligent avoidance based on the timing and lateral distance of the self-vehicle avoiding the target vehicle. The present disclosure can adapt to different types of large vehicles and different road types, improves the accuracy of avoidance, and also reduces the number of times the driver takes over.

[0105] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

Claims

1. A control method for avoiding a vehicle, comprising: According to the target vehicle information and lane line information, the distance from the edge of the target vehicle to the inner edge of the lane line is calculated, and the distance is used to determine whether the target vehicle needs to be avoided; When it is determined that the target vehicle needs to be avoided, calculating the timing for the vehicle to avoid the target vehicle according to the distance, the height of the target vehicle and the relative speed between the target vehicle and the vehicle; Based on the preset initial avoidance distance, calculate the lateral distance that the vehicle needs to avoid the target vehicle; as well as According to the timing and lateral distance of the self-vehicle avoiding the target vehicle, the self-vehicle is controlled to perform intelligent avoidance.

2. The method according to claim 1, wherein: Before calculating the distance from the edge of the target vehicle to the inner edge of the lane line according to the target vehicle information and the lane line information, the method further includes: The target vehicle information of the target vehicles around the own vehicle and the lane line information of the own lane are obtained by using the camera and the radar, wherein the target vehicle information includes the width of the target vehicle, the height of the target vehicle, the distance from the center point of the target vehicle to the center point of the own vehicle, and the longitudinal distance from the target vehicle to the own vehicle, and the lane line information includes the lane line equation of the own lane.

3. The method according to claim 2, wherein: The step of calculating the distance from the edge of the target vehicle to the inner edge of the lane line according to the target vehicle information and the lane line information includes: Determine the type of lane; When the type of the lane is determined to be a straight road, according to the formula: Calculate the horizontal distance from the edge of the target vehicle to the inner edge of the lane line, where L h is the horizontal distance from the edge of the target vehicle to the inner edge of the lane line, D is the distance from the center point of the target vehicle to the center point of the own vehicle, W is the width of the target vehicle, A0 is the lateral distance from the center point of the front axle of the own vehicle to the lane line on the target vehicle side, A1 is the angle between the heading of the own vehicle and the lane line on the target vehicle side, A2 is the curvature of the lane line on the target vehicle side, A3 is the rate of change of the curvature of the lane line, and S is the longitudinal distance from the target vehicle to the own vehicle; and When the type of the lane is determined to be a curve, according to the formula: Calculate the vertical distance from the edge of the target vehicle to the inner edge of the lane line, where L v It is the vertical distance from the edge of the target vehicle to the inner edge of the lane line.

4. The method according to claim 1, wherein: The calculating the timing for the vehicle to avoid the target vehicle according to the distance, the height of the target vehicle and the relative speed between the target vehicle and the vehicle includes: Determine the initial avoidance timing corresponding to the distance from the edge of the target vehicle to the inner edge of the lane line; Determining a first correction coefficient for an initial avoidance timing corresponding to a relative speed between the target vehicle and the ego vehicle; Determining a second correction coefficient for the initial avoidance timing corresponding to the height of the target vehicle; and The timing for the ego vehicle to avoid the target vehicle is calculated based on the initial avoidance timing, the first correction coefficient and the second correction coefficient.

5. The method according to claim 1, wherein: The step of calculating the lateral distance of the vehicle to avoid the target vehicle based on the preset initial avoidance distance includes: Determine a third correction coefficient for the initial avoidance distance corresponding to the road width of the road where the vehicle is located; Determining a fourth correction coefficient for the initial avoidance distance corresponding to the vehicle speed; Determine a fifth correction coefficient for the initial avoidance distance corresponding to the road curvature radius of the road where the vehicle is located; determining a sixth correction coefficient for the initial avoidance distance according to whether there is a road edge in the leading lane on the avoidance side; Determining a seventh correction factor for the initial avoidance distance based on whether there is a vulnerable traffic user VRU or vehicle in the adjacent lane on the avoidance side; and The lateral distance that the vehicle avoids the target vehicle is calculated based on the product of the preset initial avoidance distance, the third correction coefficient, the fourth correction coefficient, the fifth correction coefficient, the sixth correction coefficient and the seventh correction coefficient.

6. The method according to claim 1, wherein: After controlling the vehicle to perform intelligent avoidance, the method further includes: In the process of avoiding the target vehicle, if it is determined that the target vehicle is not lost, the avoidance is ended when the longitudinal distance between the target vehicle and the own vehicle is greater than the first set distance, or the distance between the center point of the target vehicle and the center point of the own vehicle is greater than the second set distance; If the target vehicle is determined to be lost, the longitudinal distance from the target vehicle to the own vehicle is calculated based on the own vehicle's length, own vehicle's speed, the length of the target vehicle, the average speed of the target vehicle, the average longitudinal distance from the target vehicle to the own vehicle, and the predicted avoidance start to end time; and If the longitudinal distance from the target vehicle to the own vehicle is greater than or equal to the first set distance, the avoidance is ended.

7. The method according to claim 6, wherein: The longitudinal distance from the target vehicle to the ego vehicle is calculated based on the ego vehicle length, ego vehicle speed, target vehicle length, target vehicle average speed, average longitudinal distance from the target vehicle to the ego vehicle, and predicted avoidance start and end time, including: According to the formula: Calculate the longitudinal distance from the target vehicle to the vehicle, where S is the longitudinal distance from the target vehicle to the vehicle, v t is the vehicle speed, v target is the average speed of the target vehicle within the preset time before the target vehicle is lost, T is the predicted avoidance start to end time, s0 is the average longitudinal distance from the target vehicle to the ego vehicle within the preset time before the target vehicle is lost, L target is the length of the target vehicle, L ego For the captain of your own vehicle.

8. A control device for avoiding a vehicle, comprising: A decision module is used to calculate the distance from the edge of the target vehicle to the inner edge of the lane line according to the target vehicle information and the lane line information, and to determine whether to avoid the target vehicle according to the distance; A calculation module, which is used to calculate the timing for the vehicle to avoid the target vehicle according to the distance, the height of the target vehicle and the relative speed between the target vehicle and the vehicle when it is determined that the target vehicle needs to be avoided; Based on the preset initial avoidance distance, calculate the lateral distance that the vehicle needs to avoid the target vehicle; as well as The control module is used to control the vehicle to perform intelligent avoidance according to the timing and lateral distance of the vehicle avoiding the target vehicle.

9. An electronic device, comprising: processor; as well as A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the processor is prompted to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing computer program instructions, which, when executed by a computer, causes the computer to execute the steps of the method according to any one of claims 1 to 7.

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