CN118082772A - Automatic emergency braking target obstacle screening method, device, equipment and medium - Google Patents
Automatic emergency braking target obstacle screening method, device, equipment and medium Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a medium for screening an automatic emergency braking target obstacle, which relate to the technical field of automatic driving and comprise the following steps: the method comprises the steps of carrying out sectional processing on a self-lane and a left lane and a right lane adjacent to the self-lane according to lane change trend to obtain a plurality of lane segments; obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment; fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment; calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane central line of each lane segment and the target lane line parameters of each lane segment; and determining the target obstacle from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane. The application improves the screening accuracy of the target obstacle.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to a method, a device, equipment and a medium for screening an automatic emergency braking target obstacle.
Background
Screening of automatic emergency braking (AEB, autonomous Emergency Braking) target obstacles is a key whether AEB functions can be stably and accurately triggered, and the current screening method of AEB target obstacles mainly comprises the following steps: 1. selecting a target in front of a self-lane as a target obstacle according to a lane line of a road surface; 2. according to the relative speeds of the vehicle and the obstacle, a safe distance is calculated, and a target obstacle is selected in a certain safe range area. In the scheme 1, lane line parameters cannot be output or the output parameters have no great reference value in the scenes of congestion of roads, abrasion of lane lines, loss of single-side lane lines, rolling of lane lines by vehicles in adjacent lanes, no lane lines in underground parking lots and the like; scheme 2 is easy to misselect a target of an adjacent outer lane as a target obstacle on a curve, or to identify a vehicle parked in a curve as a target obstacle.
The false selection of the AEB target obstacle brings bad experience to passengers, and the dangerous situations such as rear-end collision, even tail flick and the like can be caused when the situation is serious.
For this reason, how to improve the accuracy of automatic emergency braking target obstacle screening is a problem to be solved urgently by those skilled in the art.
Disclosure of Invention
In view of the above, the present invention aims to provide a method, a device and a medium for screening an automatic emergency braking target obstacle, which can improve the accuracy of screening the automatic emergency braking target obstacle, and the specific scheme is as follows:
in a first aspect, the application discloses a method for screening an automatic emergency braking target obstacle, which comprises the following steps:
Carrying out sectional processing on at least one lane according to the lane change trend to obtain a plurality of lane segments;
Obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment;
Fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment;
Calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane central line of each lane segment and the target lane line parameters of each lane segment;
and determining a target obstacle from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane.
Optionally, the processing of segmenting at least one lane according to the lane change trend to obtain a plurality of lane segments includes:
determining a curvature change rate of the at least one lane, and determining at least one curvature change rate critical point from the curvature change rate;
The at least one lane is segmented according to the curvature change rate critical point, so that a plurality of lane segments are obtained; wherein the curvature change rates at the two sides of the curvature change rate critical point correspond to different lane change trends.
Optionally, the fusing of the lane center line of each lane segment and the track line of the own vehicle in each lane segment to obtain the target lane center line of each lane segment includes:
Acquiring a plurality of sampling points in a target sampling mode, and determining longitudinal coordinates of the sampling points;
determining first transverse coordinates of the plurality of sampling points according to the lane center line of each lane segment and the longitudinal coordinates of the plurality of sampling points;
Determining second transverse coordinates of the plurality of sampling points according to the track line of the self-vehicle in each lane section and the longitudinal coordinates of the plurality of sampling points;
and screening target sampling points from the plurality of sampling points by using the first transverse coordinates and the second transverse coordinates, and obtaining the target lane center line of each lane segment by using the target sampling points in a fusion way.
Optionally, the screening the target sampling point from the plurality of sampling points by using the first lateral coordinate and the second lateral coordinate includes:
Judging whether the absolute value of the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is not larger than a first preset threshold value or not according to any sampling point in the plurality of sampling points;
if the absolute value of the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is not greater than the first preset threshold value, determining any sampling point as the target sampling point;
And if the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is larger than the first preset threshold value, eliminating any sampling point.
Optionally, the calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane center line of each lane segment and the target lane line parameter of each lane segment includes:
determining a target lane segment corresponding to each obstacle according to the position coordinates of each obstacle and the target lane line parameters of each lane segment;
Calculating lateral offsets corresponding to the respective obstacles using the position coordinates of the respective obstacles and the target lane center line of the target lane segment;
Calculating the probability of each obstacle in each lane through the lateral offset corresponding to each obstacle and a target calculation model;
Wherein the target calculation model includes:
；
Wherein, Representing the probability of each obstacle in each lane,/>Representing the lateral coordinates of the position coordinates of the respective obstacle,/>Representing the lateral offset corresponding to the respective obstacle,/>Representing the standard deviation of the lateral coordinates of the respective obstacle,/>And/>And respectively representing the abscissa of the right boundary of the lane and the abscissa of the left boundary of the lane in the target lane line parameters.
Optionally, before determining the target obstacle from the obstacles according to the overlapping rate of the obstacles and the own vehicle and the probability of the obstacles in each lane, the method further includes:
and calculating the overlapping rate of each obstacle and the own vehicle according to the transverse distance between each obstacle and the own vehicle, the width of each obstacle and the width of the own vehicle.
Optionally, the determining, according to the overlapping ratio of the respective obstacle and the own vehicle and the probability of the respective obstacle in each lane, the target obstacle from the respective obstacles includes:
determining a candidate obstacle with the largest probability of a self-lane according to the probability of each obstacle in each lane, and determining the candidate obstacle with the overlapping rate with the self-vehicle larger than a second preset threshold value as the target obstacle; the lane of the vehicle is the lane where the vehicle is located.
In a second aspect, the present application discloses an automatic emergency braking target obstacle screening device, comprising:
the lane dividing module is used for carrying out sectional processing on at least one lane according to lane change trend to obtain a plurality of lane segments;
the lane center line fusion module is used for obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment;
the lane line fusion module is used for fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment;
The probability determining module is used for calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane center line of each lane segment and the target lane line parameters of each lane segment;
and the target obstacle determining module is used for determining target obstacles from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane.
In a third aspect, the present application discloses an electronic device, comprising:
A memory for storing a computer program;
And a processor for executing the computer program to implement the automatic emergency braking target obstacle screening method disclosed above.
In a fourth aspect, the present application discloses a computer readable storage medium for storing a computer program; wherein the computer program when executed by the processor implements the automatic emergency braking target obstacle screening method disclosed previously.
The application provides an automatic emergency braking target obstacle screening method, which comprises the following steps: carrying out sectional processing on at least one lane according to the lane change trend to obtain a plurality of lane segments; obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment; fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment; calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane central line of each lane segment and the target lane line parameters of each lane segment; and determining a target obstacle from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane. In summary, according to the first aspect, the lane is segmented according to the lane change trend to obtain a plurality of lane segments, and the target lane center line and the target lane line parameters of each lane segment are determined, so that the more accurate target lane center line and the target lane center line parameters can be fitted by means of the change of the lane curvature, namely the lane change trend, thereby improving the recognition accuracy of the relative positions of each obstacle from the lane, further reducing the probability of the false allocation of the lanes to which the subsequent obstacle belongs, and solving the problem that the targets of the adjacent outer lanes are easily selected as target obstacles or the vehicles parked in the curve are recognized as target obstacles in the conventional technology. According to the method, the target lane line parameters of each lane segment are obtained through fusion of the lane line parameters of each lane segment and the preset lane line parameters, so that even if the situation that the lane line parameters under visual perception do not have reference significance due to abrasion of the lane line and loss of the lane line occurs, the target lane line parameters can be generated based on the preset lane line parameters, the lane distribution of subsequent obstacles is ensured, and the accuracy of screening the automatic emergency braking target obstacles is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for screening an automatic emergency braking target obstacle;
FIG. 2 is a schematic illustration of a lane division according to the present disclosure;
FIG. 3 is a schematic diagram of an automatic emergency braking target obstacle screening method according to the present disclosure;
FIG. 4 is a schematic diagram of a screening device for automatically and emergently braking a target obstacle according to the present application;
fig. 5 is a block diagram of an electronic device according to the present disclosure.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The current screening method of AEB target barriers mainly comprises the following steps: 1. selecting a target in front of a self-lane as a target obstacle according to a lane line of a road surface; 2. and calculating a safety distance according to the relative speeds of the vehicle and the road sign, and selecting a target obstacle in a certain safety range area. In the scheme 1, lane line parameters cannot be output or the output parameters have no great reference value in the scenes of congestion of roads, abrasion of lane lines, loss of single-side lane lines, rolling of lane lines by vehicles in adjacent lanes, no lane lines in underground parking lots and the like; scheme 2 is easy to misselect a target of an adjacent outer lane as a target obstacle on a curve, or to identify a vehicle parked in a curve as a target obstacle.
Therefore, the embodiment of the application provides an automatic emergency braking target obstacle screening scheme which can improve the accuracy of screening the automatic emergency braking target obstacle.
The embodiment of the application discloses a screening method of an automatic emergency braking target obstacle, which is shown in fig. 1 and comprises the following steps:
step S11: and carrying out segmentation processing on at least one lane according to the lane change trend to obtain a plurality of lane segments.
In this embodiment, at least one lane is processed in a segmented manner according to a lane change trend, so as to obtain a plurality of lane segments. In a specific embodiment, determining a curvature change rate of at least one lane, determining at least one curvature change rate critical point from the curvature change rates, and then carrying out segmentation processing on the at least one lane according to the curvature change rate critical point to obtain a plurality of lane segments; the curvature change rates at two sides of the curvature change rate critical point correspond to different lane change trends. Specifically, taking a curvature change rate critical point as an example, the curvature change rate of the curvature change rate critical point is 0, in a vehicle coordinate system (the specified direction is that the left is positive direction and the right is negative direction), the curvature change rate is greater than 0, the corresponding lane segment is changed leftwards, the curvature change rate is smaller than 0, the corresponding lane segment is changed rightwards, further, the lane segment changed leftwards is divided into one lane segment, the lane segment changed rightwards is divided into a plurality of lane segments, and the lane shown in fig. 2 is divided based on the fact that three lane segments are arranged between ① and ②, namely, a first lane segment of lane 0, a first lane segment of lane 1 and a first lane segment of lane 2, and three lane segments are arranged between ② and ③, namely, a second lane segment of lane 0, a second lane segment of lane 1 and a second lane segment of lane 2, and so on, and in a specific embodiment, the lane 0 is a lane segment adjacent to the left lane 1 and the lane 2 is a lane segment adjacent to the right.
Step S12: and obtaining the target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment.
In this embodiment, firstly, a lane center line equation of each lane segment under visual perception is obtained, and specifically, the lane center line equation is: ; wherein/> Representing the rate of change of curvature of the lane centerline of each lane segment when the host vehicle is traveling along the lane centerline (i.e., ideal trajectory)/>Representing the curvature of the lane center line of each lane segment when the vehicle runs along the lane center line,/>Representing the included angle between the self-vehicle and the lane center line of each lane section when the self-vehicle runs according to the lane center line,/>Representing the transverse distance of the self-vehicle from the lane center line of each lane segment when the self-vehicle runs along the lane center line,/>And/>The position coordinates of the points on the lane line obtained by taking a certain position on the own vehicle as an origin when the own vehicle runs along the lane center line are respectively obtained, and in a specific embodiment, the rear axle center of the own vehicle is taken as the origin.
In this embodiment, the trajectory equation of the own vehicle in each lane segment is further obtained, specifically,Wherein/>Representing the rate of change of the curvature of the lane center line of each lane segment when the own vehicle is traveling along the actual track,/>Representing the curvature of the lane center line of each lane segment when the vehicle runs along the actual track,/>Representing the included angle between the self-vehicle and the lane center line of each lane segment when the self-vehicle runs along the actual track,/>Represents the lateral distance of the self-vehicle from the lane center line of each lane segment when the self-vehicle runs along the actual track,/>And/>The coordinates of the position of the point on the lane line obtained by taking a certain position on the own vehicle as the origin when the own vehicle is actually running are respectively obtained.
Further, in this embodiment, a plurality of sampling points are obtained by a target sampling manner, and longitudinal coordinates of the plurality of sampling points are determined, then a first transverse coordinate of the plurality of sampling points is determined according to the lane center line equation of each lane segment under visual perception and the longitudinal coordinates of the plurality of sampling points, and a second transverse coordinate of the plurality of sampling points is determined according to the trajectory line equation of the own vehicle in each lane segment and the longitudinal coordinates of the plurality of sampling points. And finally, screening out target sampling points from the plurality of sampling points by using the first transverse coordinates and the second transverse coordinates, and obtaining the target lane center line equation of each lane segment by utilizing the fusion of the target sampling points so as to obtain the target lane center line of each lane segment.
In a specific embodiment, the screening the target sampling point from the plurality of sampling points by using the first transverse coordinate and the second transverse coordinate specifically includes: and determining any sampling point as the target sampling point by aiming at any sampling point in the plurality of sampling points, judging whether the absolute value of the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is not larger than a first preset threshold value, if the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is not larger than the first preset threshold value, eliminating any sampling point if the absolute value of the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is larger than the first preset threshold value.
For example, assuming that the lane length is 150m, in this embodiment, by using a forward sampling manner, one sampling point is taken every 2m in the forward 150m to obtain 75 sampling points, and it can be understood that each sampling point of the 75 sampling points corresponds to a position coordinate, in this embodiment, the longitudinal coordinate of each sampling point is substituted into the lane centerline equation and the trajectory equation, so as to obtain the first transverse coordinate and the second transverse coordinate of each sampling point, respectively. Further, the present embodiment determines whether the difference between the first transverse coordinate and the second transverse coordinate of each sampling point is not greater than a first preset threshold, if yes, the corresponding sampling point is determined to be a target sampling point, and if not, the sampling point is removed, so that the present embodiment obtains a plurality of target sampling points, further, the present embodiment obtains a target lane center line equation according to the fusion of the target sampling points, and it can be understood that the first preset threshold can be set by itself according to the actual situation, and the present embodiment is not limited herein.
Step S13: and fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment.
In this embodiment, lane line parameters of each lane segment under visual perception are first obtained, where the lane line parameters include a lane boundary of each lane segment (the lane boundary may reflect a lane width) and an upper limit value and a lower limit value of each lane segment (which lane segment an obstacle is located in may be determined according to the upper limit value and the lower limit value). Further, in this embodiment, the lane boundary of each lane segment is preset, and in a specific embodiment, the lane width may be preset to 3m. Finally, the embodiment fuses the lane line parameters of each lane segment under visual perception with the preset lane line parameters of each lane segment to obtain the target lane line parameters of each lane segment.
For example, assuming that the lane width under visual perception is greater than 4.5m, and the lane width does not conform to the lane width under the actual scene, the embodiment eliminates the lane width, and obtains the lane width after final fusion through the preset lane width, and further, if the lane line is worn or lost, and thus the complete lane line cannot be identified under visual perception, for example, the target lane line parameter after final fusion is obtained based on the preset lane line parameter.
Step S14: and calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane central line of each lane section and the target lane line parameters of each lane section.
In this embodiment, it is known from statistical knowledge that the choice of which lane the vehicle on the road is traveling on is a random event, but the position of the vehicle with respect to the own vehicle at a certain time is determined, and the distribution at a certain lane at the present time can be regarded as a normal distribution. Therefore, the present embodiment solves the probability that an obstacle exists in each lane (left lane, own lane, right lane) at a certain time by using a probability density function of normal distribution.
Referring to FIG. 3, the random variable x (lateral coordinates of the obstacle) obeys the mathematical expectation μ (lateral offset of the obstacle, i.e., lateral distance of the obstacle from the lane centerline), standard deviationIs noted as: x.sub.N (μ, σ,) then its probability density function is:
；
Thus, the probability of the presence of an obstacle in each lane, i.e., the integral of the probability density of the obstacle at one lane boundary, can be expressed as:
；
Wherein, Representing the probability of each obstacle in each lane,/>Representing the lateral coordinates of the position coordinates of the respective obstacle,/>Representing the lateral offset corresponding to the respective obstacle,/>Representing the standard deviation of the lateral coordinates of the respective obstacle,/>And/>And respectively representing the abscissa of the right boundary of the lane and the abscissa of the left boundary of the lane in the target lane line parameters.
The integration of the probability density is described in detail below: it is to be understood that, since the target lane line parameter includes the lane boundary of each lane segment and the upper and lower limit values of each lane segment, the present embodiment can determine the target lane segment to which each obstacle belongs according to the position coordinates of the respective obstacle. Further, in this embodiment, a target lane center line equation corresponding to each obstacle is determined according to a target lane segment to which each obstacle belongs, and a longitudinal coordinate in a position coordinate of each obstacle is substituted into the corresponding target lane center line equation to obtain a lateral offset corresponding to each obstacle, and further, in this embodiment, the probability of each obstacle in each lane is calculated through the lateral offset corresponding to each obstacle and a target calculation model (that is, the integral formula of the probability density).
Step S15: and determining a target obstacle from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane.
In this embodiment, the overlapping rate of each obstacle and the own vehicle is calculated according to the lateral distance between each obstacle and the own vehicle, the width of each obstacle, and the width of the own vehicle.
Specifically, the overlapping rate of each obstacle and the own vehicle may be expressed as:
；
Wherein, Represents the lateral distance between the center of the obstacle and the center of the vehicle,/>Representing width of own vehicle,/>Representing the width of the obstacle.
Further, in this embodiment, a candidate obstacle with the largest probability of being in a self-lane is determined according to the probability of each obstacle being in each lane, and the candidate obstacle with the overlapping rate with the self-vehicle being greater than a second preset threshold value is determined as the target obstacle; the lane of the vehicle is the lane where the vehicle is located.
That is, the present embodiment selects an obstacle having a maximum probability of self-lane and an overlap ratio greater than a certain value as a target obstacle for automatic emergency braking.
The application provides an automatic emergency braking target obstacle screening method, which comprises the following steps: carrying out sectional processing on at least one lane according to the lane change trend to obtain a plurality of lane segments; obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment; fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment; calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane central line of each lane segment and the target lane line parameters of each lane segment; and determining a target obstacle from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane. In summary, according to the first aspect, the lane is segmented according to the lane change trend to obtain a plurality of lane segments, and the target lane center line and the target lane line parameters of each lane segment are determined, so that the more accurate target lane center line and the target lane center line parameters can be fitted by means of the change rate of the lane curvature, namely the lane change trend, thereby improving the recognition accuracy of the relative positions of each obstacle from the lane, further reducing the probability of the false allocation of the lanes to which the subsequent obstacles belong, and solving the problem that the targets of the adjacent outer lanes are easily selected as target obstacles on the curve or the vehicles parked in the curve are recognized as target obstacles in the prior art. According to the method, the target lane line parameters of each lane segment are obtained through fusion of the lane line parameters of each lane segment and the preset lane line parameters, so that even if the situation that the lane line parameters under visual perception do not have reference significance due to abrasion of the lane line and loss of the lane line occurs, the target lane line parameters can be generated based on the preset lane line parameters, the lane distribution of subsequent obstacles is ensured, and the accuracy of screening the automatic emergency braking target obstacles is improved.
Correspondingly, the embodiment of the application also discloses an automatic emergency braking target obstacle screening device, which is shown in fig. 4 and comprises the following steps:
the lane dividing module 11 is used for carrying out sectional processing on at least one lane according to lane change trend to obtain a plurality of lane segments;
the lane center line fusion module 12 is configured to obtain a target lane center line of each lane segment based on fusion of a lane center line of each lane segment and a track line of a vehicle in the each lane segment;
The lane line fusion module 13 is configured to fuse the lane line parameter of each lane segment with a preset lane line parameter to obtain a target lane line parameter of each lane segment;
A probability determining module 14, configured to calculate a probability of each obstacle in each lane according to a position coordinate of each obstacle, the target lane center line of each lane segment, and the target lane line parameter of each lane segment;
and a target obstacle determining module 15, configured to determine a target obstacle from the respective obstacles according to the overlapping rate of the respective obstacles and the own vehicle and the probability of the respective obstacles in each lane.
The more specific working process of each module may refer to the corresponding content disclosed in the foregoing embodiment, and will not be described herein.
The application provides an automatic emergency braking target obstacle screening method, which comprises the following steps: carrying out sectional processing on at least one lane according to the lane change trend to obtain a plurality of lane segments; obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment; fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment; calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane central line of each lane segment and the target lane line parameters of each lane segment; and determining a target obstacle from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane. In summary, according to the first aspect, the lane is segmented according to the lane change trend to obtain a plurality of lane segments, and the target lane center line and the target lane line parameters of each lane segment are determined, so that the more accurate target lane center line and the target lane center line parameters can be fitted by means of the change rate of the lane curvature, namely the lane change trend, thereby improving the recognition accuracy of the relative positions of each obstacle from the lane, further reducing the probability of the false allocation of the lanes to which the subsequent obstacles belong, and solving the problem that the targets of the adjacent outer lanes are easily selected as target obstacles on the curve or the vehicles parked in the curve are recognized as target obstacles in the prior art. According to the method, the target lane line parameters of each lane segment are obtained through fusion of the lane line parameters of each lane segment and the preset lane line parameters, so that even if the situation that the lane line parameters under visual perception do not have reference significance due to abrasion of the lane line and loss of the lane line occurs, the target lane line parameters can be generated based on the preset lane line parameters, the lane distribution of subsequent obstacles is ensured, and the accuracy of screening the automatic emergency braking target obstacles is improved.
Further, the embodiment of the application also provides electronic equipment. Fig. 5 is a block diagram of an electronic device 20, according to an exemplary embodiment, and is not intended to limit the scope of use of the present application in any way.
Fig. 5 is a schematic structural diagram of an electronic device 20 according to an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a display screen 23, an input output interface 24, a communication interface 25, a power supply 26, and a communication bus 27. Wherein the memory 22 is configured to store a computer program that is loaded and executed by the processor 21 to implement the relevant steps in the automatic emergency braking target obstacle screening method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in the present embodiment may be specifically an electronic computer.
In this embodiment, the power supply 26 is used to provide an operating voltage for each hardware device on the electronic device 20; the communication interface 25 can create a data transmission channel between the electronic device 20 and an external device, and the communication protocol to be followed is any communication protocol applicable to the technical solution of the present application, which is not specifically limited herein; the input/output interface 24 is used for obtaining external input data or outputting external output data, and the specific interface type thereof may be selected according to the specific application needs, which is not limited herein.
The memory 22 may be a read-only memory, a random access memory, a magnetic disk, an optical disk, or the like, and the resources stored thereon may include the computer program 221, which may be stored in a temporary or permanent manner. The computer program 221 may further include a computer program that can be used to perform other specific tasks in addition to the computer program that can be used to perform the automatic emergency braking target obstacle screening method performed by the electronic device 20 disclosed in any of the foregoing embodiments.
Further, the embodiment of the application also discloses a computer readable storage medium for storing a computer program; wherein the computer program when executed by the processor implements the automatic emergency braking target obstacle screening method disclosed previously.
For specific steps of the method, reference may be made to the corresponding contents disclosed in the foregoing embodiments, and no further description is given here.
In the present disclosure, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and the same or similar parts between the embodiments refer to each other, that is, for the device disclosed in the embodiments, since the device corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description of the method, the device, the equipment and the storage medium for screening the automatic emergency braking target obstacle provided by the application applies specific examples to illustrate the principle and the implementation of the application, and the description of the above examples is only used for helping to understand the method and the core idea of the application; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (10)
1. An automatic emergency braking target obstacle screening method, comprising:
Carrying out sectional processing on at least one lane according to the lane change trend to obtain a plurality of lane segments;
Obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment;
Fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment;
Calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane central line of each lane segment and the target lane line parameters of each lane segment;
and determining a target obstacle from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane.
2. The method for screening the automatic emergency braking target obstacle according to claim 1, wherein the step of performing the segmentation processing on at least one lane according to the lane change trend to obtain a plurality of lane segments comprises:
determining a curvature change rate of the at least one lane, and determining at least one curvature change rate critical point from the curvature change rate;
The at least one lane is segmented according to the curvature change rate critical point, so that a plurality of lane segments are obtained; wherein the curvature change rates at the two sides of the curvature change rate critical point correspond to different lane change trends.
3. The automatic emergency braking target obstacle screening method according to claim 1, wherein the fusing of the lane center line of each lane segment with the track line of the own vehicle in each lane segment to obtain the target lane center line of each lane segment includes:
Acquiring a plurality of sampling points in a target sampling mode, and determining longitudinal coordinates of the sampling points;
determining first transverse coordinates of the plurality of sampling points according to the lane center line of each lane segment and the longitudinal coordinates of the plurality of sampling points;
Determining second transverse coordinates of the plurality of sampling points according to the track line of the self-vehicle in each lane section and the longitudinal coordinates of the plurality of sampling points;
and screening target sampling points from the plurality of sampling points by using the first transverse coordinates and the second transverse coordinates, and obtaining the target lane center line of each lane segment by using the target sampling points in a fusion way.
4. The automatic emergency braking target obstacle screening method according to claim 3, wherein the screening the target sampling points from the plurality of sampling points using the first lateral coordinates and the second lateral coordinates includes:
Judging whether the absolute value of the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is not larger than a first preset threshold value or not according to any sampling point in the plurality of sampling points;
if the absolute value of the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is not greater than the first preset threshold value, determining any sampling point as the target sampling point;
and if the absolute value of the difference value between the first transverse coordinate and the second transverse coordinate of any sampling point is larger than the first preset threshold value, eliminating any sampling point.
5. The automatic emergency braking target obstacle screening method according to any one of claims 1 to 4, wherein said calculating the probability of each obstacle in each lane from the position coordinates of each obstacle, the target lane center line of each lane segment, and the target lane line parameters of each lane segment includes:
determining a target lane segment corresponding to each obstacle according to the position coordinates of each obstacle and the target lane line parameters of each lane segment;
Calculating lateral offsets corresponding to the respective obstacles using the position coordinates of the respective obstacles and the target lane center line of the target lane segment;
Calculating the probability of each obstacle in each lane through the lateral offset corresponding to each obstacle and a target calculation model;
Wherein the target calculation model includes:
；
Wherein, Representing the probability of each obstacle in each lane,/>Representing the lateral coordinates of the position coordinates of the respective obstacle,/>Representing the lateral offset corresponding to the respective obstacle,/>Representing the standard deviation of the lateral coordinates of the respective obstacle,/>And/>And respectively representing the abscissa of the right boundary of the lane and the abscissa of the left boundary of the lane in the target lane line parameters.
6. The automatic emergency braking target obstacle screening method according to any one of claims 1 to 4, wherein the method further comprises, before determining a target obstacle from the respective obstacles according to the overlapping ratio of the respective obstacles to the own vehicle and the probability of the respective obstacles in the each lane:
and calculating the overlapping rate of each obstacle and the own vehicle according to the transverse distance between each obstacle and the own vehicle, the width of each obstacle and the width of the own vehicle.
7. The automatic emergency braking target obstacle screening method according to claim 6, wherein the determining a target obstacle from the respective obstacles according to the overlapping ratio of the respective obstacles to the own vehicle and the probability of the respective obstacles in the each lane comprises:
determining a candidate obstacle with the largest probability of a self-lane according to the probability of each obstacle in each lane, and determining the candidate obstacle with the overlapping rate with the self-vehicle larger than a second preset threshold value as the target obstacle; the lane of the vehicle is the lane where the vehicle is located.
8. An automatic emergency braking target obstacle screening device, comprising:
the lane dividing module is used for carrying out sectional processing on at least one lane according to lane change trend to obtain a plurality of lane segments;
the lane center line fusion module is used for obtaining a target lane center line of each lane segment based on the fusion of the lane center line of each lane segment and the track line of the own vehicle in each lane segment;
the lane line fusion module is used for fusing the lane line parameters of each lane segment with preset lane line parameters to obtain target lane line parameters of each lane segment;
The probability determining module is used for calculating the probability of each obstacle in each lane according to the position coordinates of each obstacle, the target lane center line of each lane segment and the target lane line parameters of each lane segment;
and the target obstacle determining module is used for determining target obstacles from the obstacles according to the overlapping rate of the obstacles and the vehicle and the probability of the obstacles in each lane.
9. An electronic device, comprising:
A memory for storing a computer program;
A processor for executing the computer program to implement the automatic emergency braking target obstacle screening method according to any one of claims 1 to 7.
10. A computer-readable storage medium for storing a computer program; wherein the computer program, when executed by a processor, implements the automatic emergency braking target obstacle screening method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410499681.4A CN118082772B (en) | 2024-04-24 | Automatic emergency braking target obstacle screening method, device, equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410499681.4A CN118082772B (en) | 2024-04-24 | Automatic emergency braking target obstacle screening method, device, equipment and medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118082772A true CN118082772A (en) | 2024-05-28 |
| CN118082772B CN118082772B (en) | 2024-08-02 |
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