CN114954532A - Lane line determination method, device, equipment and storage medium - Google Patents
Lane line determination method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a lane line determining method, a lane line determining device, lane line determining equipment and a storage medium. The method comprises the following steps: acquiring radar detection data of a target vehicle when the target vehicle runs on a target road based on a millimeter wave radar of the target vehicle; determining target key points of guardrails of the target road according to the radar detection data; determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function; and determining a lane line function of the target road according to the target guardrail function, and determining a lane line of the target road according to the lane line function. Therefore, the efficiency and the accuracy of identifying the lane lines in the driving process of the automatic driving vehicle can be improved.
Description
Technical Field
The present invention relates to automatic driving technologies, and in particular, to a lane line determining method, apparatus, device, and storage medium.
Background
In order to ensure that the automatic driving vehicle safely and effectively moves on the road, the automatic driving vehicle always acquires the driving road needing to be sensed to control the vehicle to drive, wherein the lane line is an important marker for restraining the vehicle in the driving process, and the lane line in the road is identified through sensing equipment so as to make a reasonable and safe driving decision.
At present, an automatic driving vehicle can carry out driving control based on a perceived lane line, but due to the fact that the complex situation of road and environmental factors can cause failure of lane line identification or the accuracy rate of lane line identification is low, the performance and stability of a vehicle system are poor, and the requirement of real-time and accurate control of vehicle driving is difficult to meet.
Disclosure of Invention
The invention provides a lane line determining method, a lane line determining device, lane line determining equipment and a storage medium, which are used for improving the efficiency and accuracy of lane line identification in the driving process of an automatic driving vehicle.
According to an aspect of the present invention, there is provided a lane line determination method including:
acquiring radar detection data of a target vehicle when the target vehicle runs on a target road based on a millimeter wave radar of the target vehicle;
determining target key points of guardrails of the target road according to the radar detection data;
determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function;
and determining a lane line function of the target road according to the target guardrail function, and determining a lane line of the target road according to the lane line function.
According to another aspect of the present invention, there is provided a lane line determining apparatus including:
the radar data acquisition module is used for acquiring radar detection data of a target vehicle when the target vehicle runs on a target road based on a millimeter wave radar of the target vehicle;
the key point calculating module is used for determining target key points of guardrails of the target road according to the radar detection data;
the function calculation module is used for determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function;
and the lane line determining module is used for determining a lane line function of the target road according to the target guardrail function and determining a lane line of the target road according to the lane line function.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the lane marking determination method according to any of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the lane line determining method according to any one of the embodiments of the present invention when the computer instructions are executed.
According to the technical scheme of the embodiment of the invention, the millimeter wave radar based on the target vehicle is used for acquiring the radar detection data when the target vehicle runs on the target road, and the target key points of the guardrail of the target road are determined according to the radar detection data, so that only the effective target key points of the guardrail in the running road are acquired, the calculation amount is reduced, and the calculation efficiency of the lane line is improved. The method comprises the steps of determining a target guardrail function of a guardrail according to position information of at least three target key points and a pre-established cubic unitary function, determining a lane line function of a target road according to the target guardrail function, determining a lane line of the target road according to the lane line function, improving the accuracy of the target guardrail function through the cubic unitary function, further improving the accuracy of the determined lane line, solving the technical problem that the lane line identification fails or is low in accuracy of the lane line identification due to the complex conditions of roads and environmental factors, and realizing the efficient and accurate identification of the lane line in the driving process of the automatic driving vehicle.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present invention, nor do they necessarily limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a lane line determining method according to an embodiment of the present invention;
fig. 2 is a flowchart of another lane line determining method according to a second embodiment of the present invention;
fig. 3 is a flowchart of another lane line determining method according to a third embodiment of the present invention;
fig. 4 is a flowchart of another lane line determining method according to an embodiment of the present invention;
fig. 5 is a structural diagram of a lane line determination apparatus according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device that implements the lane line determination method according to the embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Fig. 1 is a flowchart of a lane line determining method according to an embodiment of the present invention, where the embodiment is applicable to an automatic driving situation of an autonomous vehicle, and the method may be implemented by a lane line determining device, which may be implemented in hardware and/or software, and the lane line determining device may be configured in a vehicle. As shown in fig. 1, the method includes:
s110, acquiring radar detection data of the target vehicle when the target vehicle runs on the target road based on the millimeter wave radar of the target vehicle.
The target vehicle is a corresponding vehicle which carries a millimeter wave radar and runs in a target road. The radar detection data may be data of a millimeter wave radar detection target road.
Optionally, the millimeter wave radar may be disposed in a millimeter wave radar sensor of the target vehicle, and the target vehicle may be disposed with a plurality of millimeter wave radars in order to obtain information around the target vehicle during the traveling process.
Optionally, when the target vehicle starts to start, the target vehicle starts all the millimeter wave radars through the millimeter wave radar sensor, in the running process of the target vehicle, the millimeter wave radar detects data in a target road where the target vehicle runs in real time, and the millimeter wave radar sensor sends the data detected in real time to the target vehicle. In the process of driving of a target vehicle on a target road, the target vehicle is used as a reference object, and the target road at least comprises moving objects and static objects, for example, the moving objects comprise: other vehicles, pedestrians, etc., stationary objects include: guardrails, street lamps, signal lamps and the like.
According to the characteristics of the detection data of different objects, the radar detection data obtained during the detection of the millimeter wave radar of the target vehicle can be divided into dynamic data points and static data points in the target road. The dynamic data points may be object data points in which detection data acquired when the millimeter wave radar detects object data corresponds to the motion characteristics of a moving object, and the static data points may be object data points in which detection data acquired when the millimeter wave radar detects object data corresponds to the motion characteristics of a stationary object. Specifically, the detection data acquired when the millimeter wave radar detects the object data may include, but is not limited to, the distance, the azimuth, the angle, the range rate, the radar cross section, and the like of the object.
And S120, determining target key points of guardrails of the target road according to the radar detection data.
The target key points of the guardrail can be object data points which accord with the motion characteristics of the guardrail in radar detection data.
Optionally, after the target vehicle acquires the radar detection data, performing feature analysis on the radar detection data, determining object data points which accord with the guardrail motion characteristics in the radar detection data, and determining the object data points which accord with the guardrail motion characteristics as target key points of the guardrail of the target road.
Optionally, in another embodiment of the present invention, the determining the target key point of the guardrail of the target road according to the radar detection data includes: acquiring static data points in the radar detection data, and determining association information between every two static data points according to the position information of each static data point, wherein the association information comprises at least one of distance change information, angle change information and mahalanobis distance; and if the associated information meets a preset relevant condition, determining two static data points corresponding to the associated information as target key points of the guardrail of the target road.
In the embodiment of the invention, after the target vehicle acquires the static data points in the radar detection data, the position relation of each static data point is determined according to the position information of each static data point, the front and back two adjacent static data points of each static data point are determined, the front and back two adjacent static data points of each static data point are respectively subjected to correlation calculation, and the correlation information between the front and back two adjacent static data points of each static data point is determined. Wherein the association calculation may be at least one of a distance change information calculation, an angle change information calculation, and a mahalanobis distance calculation, and the association information includes at least one of a distance change information, an angle change information, and a mahalanobis distance. The distance change information may be a distance change value or a distance change rate.
For example, the distance change information calculation may be to calculate a distance change between the current static data point and two previous and next static data points, the angle change calculation using the distance change between each two static data points as the distance change information may be to calculate an angle change between the current static data point and two previous and next static data points, and the mahalanobis distance calculation using the angle change between each two static data points as the angle change may be to calculate a covariance distance between the current static data point and two previous and next static data points, and the covariance distance between each two static data points as the mahalanobis distance. The Mahalanobis distance calculation formula of every two static data points is as follows:
sqrt((x-y)'Σ^(-1)(x-y))
wherein sqrt is the root number of the square root calculation; (x-y)' is a transpose of (x-y); Σ is a covariance matrix of multidimensional random variables; x is the first of the two static data points and y is the second of the two static data points.
Further, after obtaining and determining the association information between the two adjacent front and back static data points of each static data point, the target vehicle judges whether the association information meets a preset association condition, and if the association information meets the preset association condition, the two static data points corresponding to the association information are determined as the target key points of the guardrail of the target road.
Optionally, in an optional embodiment of the present invention, if the associated information satisfies a preset relevant condition, determining two static data points corresponding to the associated information as a target key point of a guardrail of the target road includes at least one of the following operations: determining the two static data points as target keypoints of a guardrail of the target roadway if at least one of the following conditions is met: the distance change information between the two static data points does not exceed a preset distance change threshold; the angle change information between the two static data points meets a preset angle change condition; the mahalanobis distance between two static data points does not exceed a preset mahalanobis distance threshold.
For example, after calculating a distance variation between a current static data point and two previous and next static data points, a target vehicle determines whether the distance variation exceeds a preset distance variation threshold, and if the distance variation does not exceed the preset distance variation threshold, determines the two static data points corresponding to the current distance variation as target key points of a guardrail of the target road; after calculating the angle variation between the current static data point and two previous and next static data points, the target vehicle judges whether the angle variation meets a preset angle variation condition, and if the angle variation meets the preset angle variation condition, the two static data points corresponding to the current angle variation are determined as target key points of a guardrail of the target road; after calculating the mahalanobis distance between the current static data point and the two previous and next static data points, the target vehicle judges whether the mahalanobis distance exceeds a preset mahalanobis distance threshold, and if the mahalanobis distance does not exceed the preset mahalanobis distance threshold, the two static data points corresponding to the current mahalanobis distance are determined as the target key points of the guardrail of the target road. And determining the two corresponding static data points as the target key points of the guardrail of the target road as long as any one of the distance variation, the angle variation and the mahalanobis distance between the current static data point and the two previous static data points meets the preset relevant condition.
S130, determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function.
The target guardrail function may be a unitary cubic function generated by calculation according to the position information of the target key point of the guardrail.
In the embodiment of the invention, the position information of at least three target key points can be substituted into a pre-established unitary cubic function, and the target guardrail function of the guardrail is calculated and obtained.
S140, determining a lane line function of the target road according to the target guardrail function, and determining a lane line of the target road according to the lane line function.
The lane line function may be a unitary cubic function generated by calculation according to the target guardrail function.
In the embodiment of the invention, the target vehicle generates the lane line function through the calculation of the target guardrail function according to the incidence relation between the target guardrail function and the lane line function, and then calculates the lane line of the target road according to the lane line function.
Optionally, in another embodiment of the present invention, the determining the lane function of the target road according to the target guardrail function includes: and determining the transverse distance between the guardrail and the lane line of the target road, and moving the target guardrail function based on the transverse distance to obtain the lane line function of the target road.
In the embodiment of the invention, in the target road, the guardrails are usually positioned at the two parallel positions of the lane line, and after the target guardrail function is obtained, the transverse distance between the guardrail of the target road and the lane line is calculated through the millimeter wave radar sensor and the distance sensor, and the lane line function of the target road is calculated based on the transverse distance moving target guardrail function.
According to the technical scheme of the embodiment of the invention, the millimeter wave radar based on the target vehicle is used for acquiring the radar detection data when the target vehicle runs on the target road, and the target key points of the guardrail of the target road are determined according to the radar detection data, so that only the effective target key points of the guardrail in the running road are acquired, the calculation amount is reduced, and the calculation efficiency of the lane line is improved. The method comprises the steps of determining a target guardrail function of a guardrail according to position information of at least three target key points and a pre-established cubic unitary function, determining a lane line function of a target road according to the target guardrail function, determining a lane line of the target road according to the lane line function, improving the accuracy of the target guardrail function through the cubic unitary function, further improving the accuracy of the determined lane line, solving the technical problem that the lane line identification fails or is low in accuracy of the lane line identification due to the complex conditions of roads and environmental factors, and realizing the efficient and accurate identification of the lane line in the driving process of the automatic driving vehicle.
Example two
Fig. 2 is a flowchart of another lane line determining method according to a second embodiment of the present invention, which is based on the above embodiment and further illustrates a calculation process of the target guardrail function. Wherein explanations of the same or corresponding terms as those of the above embodiments are omitted. As shown in fig. 2, the method includes:
s210, radar detection data of the target vehicle during running on the target road are obtained based on the millimeter wave radar of the target vehicle.
And S220, determining target key points of the guardrails of the target road according to the radar detection data.
And S230, determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function.
And S240, if the number of the determined target key points exceeds three, substituting the position information of each three target key points into a pre-established unitary cubic function for solving to obtain at least two reference guardrail functions.
The reference guardrail function can be a guardrail function obtained by substituting position information of three target key points into a pre-established unitary cubic function for solving.
In the embodiment of the invention, in the running process of a target vehicle, radar detection data of the target vehicle running on a target road are obtained through a millimeter wave radar, target key points of a guardrail of the target road are further determined according to the radar detection data, and when the number of the determined target key points of the guardrail of the target road is three, the position information of the three determined target key points is substituted into a pre-established one-dimensional cubic function to solve and obtain a guardrail function; after the guardrail functions are obtained, the target vehicle continues to determine target key points of guardrails of the target road according to the radar detection data, if the number of the determined target key points of the guardrails of the target road exceeds three, the position information of every three target key points is substituted into a pre-established unitary cubic function from the first target key point to be solved, and at least two reference guardrail functions are calculated.
For example, the unitary cubic function solved by substituting the position information of the three target key points into the pre-established unitary cubic function may be represented as follows:
Y＝ax 3 +bx 2 +cx+d
the a, b, c and d are parameters of a unitary cubic function, and the parameter values of the a, b, c and d can be obtained by substituting the position information of the three target key points.
And S250, fitting the obtained reference guardrail functions to obtain the target guardrail functions of the guardrails.
In the embodiment of the invention, the obtained reference guardrail functions are fitted, and the fitted guardrail functions are taken as target guardrail functions. Alternatively, a neural network model may be used to fit each reference barrier function.
For example, fitting a guardrail function by using a neural network model according to a fitting algorithm, wherein the specific training process is as follows: determining activation functions of neurons in a neural network model, further constructing a multilayer neural network, inputting corresponding vertical coordinates of a plurality of points with the same horizontal coordinate in each reference guardrail function into the neural network model, outputting corresponding predicted vertical coordinates, calculating training errors of the predicted vertical coordinates through a loss function, and adjusting and optimizing parameters of the multilayer neural network in the neural network model according to the training errors. And when the convergence of the loss function in the neural network model is detected, the training of the neural network is finished. Wherein the loss function may include, but is not limited to: a mean square error function, a mean absolute value error function, and a cross entropy error function. The fitting algorithm may be, but is not limited to, any one of a least square method, a gradient descent method, and a gauss-newton algorithm.
S260, determining a lane line function of the target road according to the target guardrail function, and determining a lane line of the target road according to the lane line function.
According to the technical scheme of the embodiment of the invention, the target detection data of the target vehicle when the target vehicle runs on the target road is obtained through the millimeter wave radar based on the target vehicle, and the target key points of the guardrail of the target road are determined according to the radar detection data, so that only the effective target key points of the guardrail in the running road are obtained, the calculation amount is reduced, and the calculation efficiency of the lane line is improved. And determining a target guardrail function of the guardrail according to the position information of at least three target key points and the pre-established unitary cubic function, and continuously fitting and correcting the target guardrail function in the driving process, so that the target guardrail function is continuously close to the real road guardrail, and the simulation accuracy of the target guardrail function is further ensured. The lane line function of the target road is determined according to the target guardrail function, the lane line of the target road is determined according to the lane line function, the accuracy of the target guardrail function is improved through the unitary cubic function, the accuracy of the determined lane line is further improved, the technical problem that the lane line identification fails or the lane line identification accuracy is low due to the complex conditions of road and environmental factors is solved, and the efficient and accurate identification of the lane line in the driving process of the automatic driving vehicle is realized.
EXAMPLE III
Fig. 3 is a flowchart of another lane line determining method according to a third embodiment of the present invention, and the third embodiment further illustrates a radar detection data acquiring process based on the foregoing embodiments. Wherein explanations of the same or corresponding terms as those of the above embodiments are omitted. As shown in fig. 3, the method includes:
s310, acquiring radar detection data of the target vehicle when the target vehicle runs on the target road based on the millimeter wave radar of the target vehicle.
S320, obtaining current running information of the target vehicle when the target vehicle runs on the target road, and determining the target running track of the target vehicle according to the current running information.
The current travel information may be vehicle operation information of the target vehicle traveling on the target road, such as a speed, an acceleration, a travel direction, a turning angle, and the like of the vehicle, and the target travel track may be a movement track of the target vehicle traveling on the target road.
Specifically, the acquiring of the current driving information when the target vehicle drives on the target road may be performed by connecting a sensor in the target vehicle through a Controller Area Network (CAN) of the target vehicle, acquiring data of each sensor when the target vehicle drives based on the CAN of the target vehicle, processing the acquired current driving information by the target vehicle, acquiring a driving track point of the target vehicle on the target road, and further connecting the driving track point of the target vehicle on the target road, thereby determining the target driving track of the target vehicle.
Optionally, in another embodiment of the present invention, the determining a target driving track of the target vehicle according to the current driving information includes: determining a transient steering radius of the target vehicle according to the current driving information, wherein the current driving information includes at least one of a steering wheel angle, a wheel track, a vehicle speed, and a yaw rate; and if the transient steering radius meets a preset condition, determining a target running track of the target vehicle according to the transient steering radius and the running track of the target vehicle on the target road.
Specifically, the distance from the steering center to the contact point between the front and outer steering wheels and the ground surface during the traveling of the target vehicle is referred to as a transient steering radius of the target vehicle, and the transient steering radius of the target vehicle may be calculated based on current traveling information of the target vehicle, the current traveling information of the target vehicle including at least one of a steering wheel angle, a wheel track, a vehicle speed, and a yaw rate. Optionally, the transient steering radius calculation methods of the target vehicle at different vehicle speeds are different, if the vehicle speed of the target vehicle is less than the preset speed threshold, the target vehicle is determined to be in a low-speed running state, the steering angle of the front wheel of the current vehicle is calculated through the steering wheel angle in the current running information, and the steering radius of the vehicle can be calculated based on the steering angle of the front wheel and the wheel track of the vehicle in the current running information. The calculation formula for calculating the steering radius of the vehicle based on the front wheel angle and the vehicle track in the current running information is as follows:
R＝L/sin(δf)
wherein R is the transient steering radius of the target vehicle and L is the vehicle track; δ f is the front wheel steering angle.
If the vehicle speed of the target vehicle is greater than the preset speed threshold, the target vehicle is deemed to be in a high-speed driving state, and the turning radius of the vehicle may be calculated based on the current vehicle speed and the yaw rate. The calculation formula for calculating the turning radius of the vehicle based on the current vehicle speed and the yaw rate is as follows:
R＝Vx/ω
wherein R is the transient steering radius of the target vehicle, and Vx is the current vehicle speed of the target vehicle; ω is the yaw rate.
Specifically, the preset speed threshold may be a speed threshold preset when the target vehicle leaves a factory.
Further, after the transient steering radius of the target vehicle is obtained, whether the transient steering radius of the target vehicle meets a preset condition or not is judged, if the transient steering radius of the target vehicle does not meet the preset condition, the target vehicle is judged to be in a straight-line running state, the target running track of the target vehicle does not need to be calculated, and if the transient steering radius of the target vehicle meets the preset condition, the target running track of the target vehicle is determined according to the transient steering radius and the running track of the target vehicle on the target road.
S330, determining a data acquisition area of the target road according to the target running track, and acquiring radar detection data of the data acquisition area based on the millimeter wave radar of the target vehicle.
Wherein, the data acquisition area can be the area detected by the millimeter wave radar. Optionally, a plurality of millimeter wave radars may be installed in four directions of the target vehicle, so as to detect four regions, namely, the front region, the rear region, the left region, the right region, and the left region of the target vehicle.
Specifically, when the target vehicle runs on the target road, the running posture of the target vehicle can be determined through the target running track of the target vehicle, the guardrails are usually on two sides of the road, the relative position relation between the guardrails on two sides of the road and the target vehicle can be determined through the running posture of the target vehicle, and then the millimeter wave radar detection area is determined. Therefore, the area where the guardrail of the target road is located can be judged through the target running track of the target vehicle and the current running information, and the area where the guardrail is located is determined as the data acquisition area of the target road. The data acquisition area of the target road is determined through the target running track, the area of the data acquisition area can be reduced, the data analysis amount of the target vehicle is further reduced, and the calculation efficiency of the target vehicle is improved.
And S340, determining target key points of guardrails of the target road according to the radar detection data.
And S350, determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function.
S360, determining a lane line function of the target road according to the target guardrail function, and determining a lane line of the target road according to the lane line function.
According to the technical scheme of the embodiment of the invention, the target running track of the target vehicle is further determined according to the current running information of the target vehicle running on the target road, the data acquisition area of the target road is determined according to the target running track, and the radar detection data of the target vehicle running on the target road is acquired based on the millimeter wave radar of the target vehicle, so that the area of the data acquisition area can be reduced, the data analysis amount of the target vehicle is further reduced, and the calculation efficiency of the target vehicle is improved. And determining the target key points of the guardrails of the target road according to the radar detection data, so that only the effective target key points of the guardrails in the driving road are obtained, the calculation amount is reduced, and the calculation efficiency of the lane lines is improved. The method comprises the steps of determining a target guardrail function of a guardrail according to position information of at least three target key points and a pre-established cubic unitary function, determining a lane line function of a target road according to the target guardrail function, determining a lane line of the target road according to the lane line function, improving the accuracy of the target guardrail function through the cubic unitary function, further improving the accuracy of the determined lane line, solving the technical problem that the lane line identification fails or is low in accuracy of the lane line identification due to the complex conditions of roads and environmental factors, and realizing the efficient and accurate identification of the lane line in the driving process of the automatic driving vehicle.
Optionally, fig. 4 is a schematic flow chart of another lane line determining method provided by the fourth embodiment of the present invention, as shown in fig. 4, the method includes:
s410, millimeter wave radar data and whole vehicle information are obtained, wherein the whole vehicle information comprises: vehicle speed, yaw rate, steering wheel angle.
And S420, determining the running track of the vehicle based on the whole vehicle information.
And S430, determining the region of interest based on the driving track.
S440, determining target key points of a plurality of guardrails based on the millimeter wave radar data and the region of interest.
S450, based on the plurality of target key points, screening sample points according to the Mahalanobis distance, and fitting a cubic equation to obtain a target guardrail function.
Specifically, the millimeter wave radar data at least comprises point track and track information of a moving object and a static object, wherein the point track information at least comprises the distance, the direction, the distance change rate and the radar scattering cross section of a detection target; the flight path information at least comprises distance, distance change rate, angle and radar scattering cross section. The guardrail can be identified by the millimeter wave radar, the static data points of the guardrail are static and concentrated, the characteristic of similar static points exists in the range for a long time, and the static data points with the guardrail characteristics are identified by the millimeter wave radar data.
The method comprises the steps of determining a running track of a target vehicle based on whole vehicle information, and further determining that an area of interest of the target vehicle is left front side/right front side/left rear side/right rear side, so that a plurality of guardrail sample points of a plurality of static data points with guardrail characteristics are determined through a millimeter wave radar and the area of interest. Wherein, the transient steering radius of the target vehicle can be calculated based on the current running information of the target vehicle during the running of the target vehicle. Optionally, the transient steering radius calculation methods of the target vehicle at different vehicle speeds are different, if the vehicle speed of the target vehicle is less than the preset speed threshold, the target vehicle is determined to be in a low-speed running state, the steering angle of the front wheel of the current vehicle is calculated through the steering wheel angle in the current running information, and the steering radius of the vehicle can be calculated based on the steering angle of the front wheel and the wheel track of the vehicle in the current running information. The calculation formula for calculating the steering radius of the vehicle based on the front wheel angle and the vehicle track in the current running information is as follows:
R＝L/sin(δf)
if the vehicle speed of the target vehicle is greater than the preset speed threshold, the target vehicle is deemed to be in a high-speed driving state, and the turning radius of the vehicle may be calculated based on the current vehicle speed and the yaw rate. The calculation formula for calculating the turning radius of the vehicle based on the current vehicle speed and the yaw rate is as follows:
R＝Vx/ω
after the interesting area of the target vehicle is determined, millimeter wave radar data in the area is selected, the correlation of the millimeter wave radar data is judged by using the Mahalanobis distance, the correlation of a plurality of guardrail sample points in the millimeter wave radar data is further judged, three related guardrail sample points are brought into the unitary cubic equation, the parameters of the unitary cubic equation are solved, and the unitary cubic equation is recalculated to realize the deviation correction of the unitary cubic equation every time one related guardrail sample is added.
Furthermore, in the target road, the guardrails are usually located at the two parallel positions of the lane line, and then after the target guardrail function is obtained, the transverse distance between the guardrail of the target road and the lane line is calculated through the millimeter wave radar sensor and the distance sensor, and the lane line function of the target road is calculated based on the transverse distance moving target guardrail function.
Example four
Fig. 5 is a schematic structural diagram of a lane line determining apparatus according to a fourth embodiment of the present invention. As shown in fig. 5, the apparatus specifically includes: a radar data acquisition module 510, a keypoint computation module 520, a function computation module 530, and a lane line determination module 540. Wherein:
a radar data acquisition module 510, configured to acquire radar detection data of a target vehicle when the target vehicle travels on a target road based on a millimeter wave radar of the target vehicle;
a key point calculation module 520, configured to determine a target key point of a guardrail of the target road according to the radar detection data;
a function calculating module 530, configured to determine a target guardrail function of the guardrail according to the position information of the at least three target key points and a pre-established unitary cubic function;
and a lane line determining module 540, configured to determine a lane line function of the target road according to the target guardrail function, and determine a lane line of the target road according to the lane line function.
According to the technical scheme of the embodiment of the invention, the millimeter wave radar based on the target vehicle is used for acquiring the radar detection data when the target vehicle runs on the target road, and the target key points of the guardrail of the target road are determined according to the radar detection data, so that only the effective target key points of the guardrail in the running road are acquired, the calculation amount is reduced, and the calculation efficiency of the lane line is improved. The method comprises the steps of determining a target guardrail function of a guardrail according to position information of at least three target key points and a pre-established cubic unitary function, determining a lane line function of a target road according to the target guardrail function, determining a lane line of the target road according to the lane line function, improving the accuracy of the target guardrail function through the cubic unitary function, further improving the accuracy of the determined lane line, solving the technical problem that the lane line identification fails or is low in accuracy of the lane line identification due to the complex conditions of roads and environmental factors, and realizing the efficient and accurate identification of the lane line in the driving process of the automatic driving vehicle.
Optionally, the key point calculating module 520 is configured to:
obtaining static data points in the radar detection data, and determining association information between every two static data points according to position information of each static data point, wherein the association information comprises at least one of distance change information, angle change information and Mahalanobis distance;
and if the associated information meets a preset relevant condition, determining two static data points corresponding to the associated information as target key points of the guardrail of the target road.
Optionally, the key point calculating module 520 is further specifically configured to:
determining two static data points corresponding to the associated information as target key points of a guardrail of the target road if the associated information meets a preset relevant condition, wherein the determining comprises at least one of the following operations:
determining the two static data points as target keypoints of a guardrail of the target roadway if at least one of the following conditions is met:
the distance change information between the two static data points does not exceed a preset distance change threshold;
the angle change information between the two static data points meets a preset angle change condition;
the mahalanobis distance between two static data points does not exceed a preset mahalanobis distance threshold.
Optionally, the function calculating module 530 is specifically configured to:
if the number of the determined target key points exceeds three, substituting the position information of every three target key points into a unitary cubic function established in advance to solve to obtain at least two reference guardrail functions;
and fitting each obtained reference guardrail function to obtain a target guardrail function of the guardrail.
Optionally, the lane line determining module 540 is specifically configured to:
and determining the transverse distance between the guardrail and the lane line of the target road, and moving the target guardrail function based on the transverse distance to obtain the lane line function of the target road.
Optionally, the radar data obtaining module 510 is specifically configured to:
acquiring current running information of a target vehicle when the target vehicle runs on a target road, and determining a target running track of the target vehicle according to the current running information;
and determining a data acquisition area of the target road according to the target running track, and acquiring radar detection data of the data acquisition area based on the millimeter wave radar of the target vehicle.
Optionally, the radar data obtaining module 510 is further specifically configured to:
determining a transient steering radius of the target vehicle according to the current driving information, wherein the current driving information includes at least one of a steering wheel angle, a wheel track, a vehicle speed, and a yaw rate;
and if the transient steering radius meets a preset condition, determining a target running track of the target vehicle according to the transient steering radius and the running track of the target vehicle on the target road.
The lane line determination device provided by the embodiment of the invention can execute the lane line determination method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the lane line determination method.
It should be noted that, in the embodiment of the lane line determining apparatus, each included unit and each included module are only divided according to functional logic, but are not limited to the above division as long as the corresponding function can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
EXAMPLE five
FIG. 6 illustrates a schematic structural diagram of an electronic device 10 that may be used to implement an embodiment of the present invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 6, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM)12, a Random Access Memory (RAM)13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM)12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
In some embodiments, the lane line determination method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the lane line determination method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the lane line determination method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired result of the technical solution of the present invention can be achieved.
EXAMPLE five
The present embodiment provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements the steps of a lane marking determination method as provided in any of the embodiments of the present invention, the method comprising:
acquiring radar detection data of a target vehicle when the target vehicle runs on a target road based on a millimeter wave radar of the target vehicle;
determining target key points of guardrails of the target road according to the radar detection data;
determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function;
and determining a lane line function of the target road according to the target guardrail function, and determining a lane line of the target road according to the lane line function.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer-readable storage medium may be, for example but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It will be understood by those skilled in the art that the modules or steps of the invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and optionally they may be implemented by program code executable by a computing device, such that it may be stored in a memory device and executed by a computing device, or it may be separately fabricated into various integrated circuit modules, or it may be fabricated by fabricating a plurality of modules or steps thereof into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A lane line determination method, comprising:
acquiring radar detection data of a target vehicle when the target vehicle runs on a target road based on a millimeter wave radar of the target vehicle;
determining target key points of guardrails of the target road according to the radar detection data;
determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function;
and determining a lane line function of the target road according to the target guardrail function, and determining a lane line of the target road according to the lane line function.
2. The method of claim 1, wherein determining target keypoints for a guardrail of the target roadway from the radar detection data comprises:
acquiring static data points in the radar detection data, and determining association information between every two static data points according to the position information of each static data point, wherein the association information comprises at least one of distance change information, angle change information and mahalanobis distance;
and if the associated information meets a preset relevant condition, determining two static data points corresponding to the associated information as target key points of the guardrail of the target road.
3. The method according to claim 2, wherein the determining two static data points corresponding to the association information as target key points of a guardrail of the target road if the association information satisfies a preset correlation condition comprises at least one of:
determining the two static data points as target keypoints of a guardrail of the target roadway if at least one of the following conditions is met:
the distance change information between the two static data points does not exceed a preset distance change threshold;
the angle change information between the two static data points meets a preset angle change condition;
the mahalanobis distance between two static data points does not exceed a preset mahalanobis distance threshold.
4. The method of claim 1, wherein the determining the target guardrail function of the guardrail according to the position information of the at least three target key points and a pre-established unitary cubic function comprises;
if the number of the determined target key points exceeds three, substituting the position information of every three target key points into a unitary cubic function established in advance to solve to obtain at least two reference guardrail functions;
and fitting each obtained reference guardrail function to obtain a target guardrail function of the guardrail.
5. The method of claim 1, wherein determining the lane line function of the target roadway from the target guardrail function comprises:
and determining the transverse distance between the guardrail and the lane line of the target road, and moving the target guardrail function based on the transverse distance to obtain the lane line function of the target road.
6. The method according to claim 1, wherein the obtaining radar detection data of the target vehicle while traveling on the target road based on the millimeter wave radar of the target vehicle comprises:
acquiring current running information of a target vehicle when the target vehicle runs on a target road, and determining a target running track of the target vehicle according to the current running information;
and determining a data acquisition area of the target road according to the target running track, and acquiring radar detection data of the data acquisition area based on the millimeter wave radar of the target vehicle.
7. The method of claim 6, wherein determining the target travel trajectory of the target vehicle based on the current travel information comprises:
determining a transient steering radius of the target vehicle according to the current driving information, wherein the current driving information includes at least one of a steering wheel angle, a wheel track, a vehicle speed, and a yaw rate;
and if the transient steering radius meets a preset condition, determining a target running track of the target vehicle according to the transient steering radius and the running track of the target vehicle on the target road.
8. A lane line determination apparatus, comprising:
the radar data acquisition module is used for acquiring radar detection data of a target vehicle when the target vehicle runs on a target road based on a millimeter wave radar of the target vehicle;
the key point calculating module is used for determining target key points of guardrails of the target road according to the radar detection data;
the function calculation module is used for determining a target guardrail function of the guardrail according to the position information of at least three target key points and a pre-established unitary cubic function;
and the lane line determining module is used for determining a lane line function of the target road according to the target guardrail function and determining a lane line of the target road according to the lane line function.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the lane line determination method of any one of claims 1-7.
10. A computer-readable storage medium storing computer instructions for causing a processor to perform the lane line determination method of any one of claims 1-7 when executed.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115574805A (en) * | 2022-12-02 | 2023-01-06 | 小米汽车科技有限公司 | Method and device for identifying lane line relationship, vehicle and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115574805A (en) * | 2022-12-02 | 2023-01-06 | 小米汽车科技有限公司 | Method and device for identifying lane line relationship, vehicle and storage medium |
| CN115574805B (en) * | 2022-12-02 | 2023-04-28 | 小米汽车科技有限公司 | Lane line relationship identification method and device, vehicle and storage medium |
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