CN117289686B - Parameter calibration method and device, electronic equipment and storage medium - Google Patents
Parameter calibration method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a parameter calibration method, a parameter calibration device, electronic equipment and a storage medium. The method comprises the following steps: acquiring acquired driving data acquired in a driving process of a target vehicle, and determining a target control mode of the target vehicle; determining a preset upper bound, a preset lower bound and preset identification precision, which correspond to the vehicle type of the target vehicle, of the control parameters aiming at the control parameters to be calibrated of the target control mode; and determining a target calibration result aiming at the control parameter based on the preset upper limit, the preset lower limit, the preset identification precision and the acquired driving data. According to the technical scheme provided by the embodiment of the invention, the cost for calibrating the control parameters can be reduced.
Description
Technical Field
The embodiment of the invention relates to the technical field of vehicle control parameter calibration, in particular to a parameter calibration method, a device, electronic equipment and a storage medium.
Background
The existing vehicle transverse control methods all need to calibrate control parameters, but the current calibration of the control parameters needs to be carried out by professional technicians to adjust and calibrate the control parameters of the vehicle through professional equipment.
Therefore, the current calibration of the control parameters depends on professional equipment and manual debugging, and the calibration cost is high.
Disclosure of Invention
The embodiment of the invention provides a parameter calibration method, a parameter calibration device, electronic equipment and a storage medium, so as to reduce the cost of calibrating control parameters.
According to an aspect of the present invention, there is provided a parameter calibration method, which may include:
acquiring acquired driving data acquired in the driving process of a target vehicle, and determining a target control mode of the target vehicle;
determining a preset upper limit, a preset lower limit and preset identification precision which are respectively corresponding to the control parameters aiming at the vehicle type of the target vehicle aiming at the control parameters to be calibrated of the target control mode;
and determining a target calibration result aiming at the control parameter based on the preset upper limit, the preset lower limit, the preset identification precision and the acquired driving data.
According to another aspect of the present invention, there is provided a parameter calibration device, which may include:
the target control mode determining module is used for acquiring acquired driving data acquired in the driving process of the target vehicle and determining a target control mode of the target vehicle;
the preset identification precision determining module is used for determining a control parameter to be calibrated aiming at a target control mode, wherein the control parameter corresponds to a preset upper limit, a preset lower limit and preset identification precision of a vehicle type of a target vehicle respectively;
The target calibration result determining module is used for determining a target calibration result aiming at the control parameter based on a preset upper limit, a preset lower limit, a preset identification precision and collected driving data.
According to another aspect of the present invention, there is provided an electronic device, which may include:
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 cause the at least one processor to perform the parameter calibration method provided by any embodiment of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium having stored thereon computer instructions for causing a processor to perform the parameter calibration method provided by any of the embodiments of the present invention.
According to the technical scheme, acquired driving data acquired in the driving process of the target vehicle is acquired, and a target control mode of the target vehicle is determined; determining a preset upper limit, a preset lower limit and preset identification precision which are respectively corresponding to the control parameters aiming at the vehicle type of the target vehicle aiming at the control parameters to be calibrated of the target control mode; and determining a target calibration result aiming at the control parameter based on the preset upper limit, the preset lower limit, the preset identification precision and the acquired driving data. According to the technical scheme, the calibration of the control parameters can be achieved without depending on professional equipment and manual debugging by acquiring the driving data based on the driving process of the target vehicle and respectively corresponding preset upper bound, preset lower bound and preset identification precision of the control parameters to the vehicle type of the target vehicle, so that the calibration effect is good, and the cost of the calibration of the control parameters is reduced.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention, nor is it intended to be used to limit the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a parameter calibration method provided according to an embodiment of the present invention;
FIG. 2 is a flow chart of another parameter calibration method provided in accordance with an embodiment of the present invention;
FIG. 3 is a flow chart of yet another parameter calibration method provided in accordance with an embodiment of the present invention;
FIG. 4 is a flowchart of an alternative example of a parameter calibration method according to an embodiment of the present invention;
FIG. 5 is a block diagram of a parameter calibration device according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device implementing a parameter calibration method according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. The cases of "target", "original", etc. are similar and will not be described in detail herein. 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.
Fig. 1 is a flowchart of a parameter calibration method provided in an embodiment of the present invention. The embodiment is applicable to parameter calibration, in particular to transverse control parameter calibration. The method can be implemented by the parameter calibration device provided by the embodiment of the invention, the device can be realized by software and/or hardware, and the device can be integrated on electronic equipment, and the electronic equipment can be various user terminals or servers.
Referring to fig. 1, the method of the embodiment of the present invention specifically includes the following steps:
s110, acquiring acquired driving data acquired in the driving process of the target vehicle, and determining a target control mode of the target vehicle.
The target vehicle is a vehicle for calibrating control parameters of a control method adopted when the target vehicle is required to be controlled. The collected driving data is data collected for the driving process of the target vehicle. The target control mode is a control mode adopted by a control target vehicle with a control parameter calibration requirement; the target control method may be a lateral control method of the target vehicle, and the target control method may be at least one of a proportional-integral-derivative (Proportional Integral Derivative, PID), a linear quadratic form (Linear Quadratic Regulator, LQR), a model predictive control (Model Predictive Control, MPC), and the like; the number of target control modes may be one or a plurality of. The control parameters are parameters in a target control mode to be calibrated.
In the embodiment of the invention, a driver can drive a target vehicle, and the acquired driving data is acquired aiming at the process of driving the target vehicle by the driver; the control mode with the control parameter calibration requirement is taken as the target control mode in the control modes of the target vehicle.
In an embodiment of the present invention, the collected driving data may include vehicle body information and/or vehicle surrounding information. The body information may include at least one of a vehicle speed, a steering wheel angle, a wheelbase, a turning radius, an acceleration, a jerk, a planned driving trajectory, an actual driving trajectory, and the like of the target vehicle. The vehicle surroundings information may include at least one of a position error of the planned driving trajectory and the actual driving trajectory, a position error change rate, a direction error of the planned driving trajectory and the actual driving trajectory, a direction error change rate, and the like. In the embodiment of the invention, specific data content of the vehicle body information and/or the vehicle surrounding environment information is not specifically limited. The planned driving track is a track obtained by planning the driving track of the driving process of the target vehicle before the driving data is acquired for the driving process of the target vehicle.
S120, determining a preset upper limit, a preset lower limit and a preset identification precision, which correspond to the vehicle type of the target vehicle, of the control parameters aiming at the control parameters to be calibrated of the target control mode.
In the embodiment of the invention, the parameters to be calibrated in the target control mode can be determined as the control parameters, and the control parameters can be all parameters in the target control mode and can also be part of parameters required to be calibrated in the target control method; the number of control parameters may be one or a plurality. The preset upper bound is a preset maximum value of the control parameter, which can be calibrated. The preset lower limit is a minimum value which can be calibrated for a preset control parameter. The preset identification accuracy is the identification accuracy of the preset control parameters.
It can be understood that the calibration of the control parameters by the vehicles of different vehicle types is also different due to the different performance aspects and the like; the same vehicle type has the same calibration of control parameters due to the same performance and other aspects; therefore, in the embodiment of the invention, different preset upper bounds, different preset lower bounds and different preset identification accuracies can be respectively set for different vehicle types and control parameters.
In the embodiment of the invention, for each control parameter, a preset upper bound, a preset lower bound and a preset identification precision, which correspond to the vehicle type of the target vehicle, of the control parameter can be determined. Exemplary, if the control parameters includeAnd->The preset upper and lower bounds of the control parameter can be set to +.>、/>、/>、/>And->I.e. ] a +>And->Respectively->And->Is a preset upper bound of->And->Respectively->And->Is defined by a predetermined lower bound; can be provided withAnd->The identification precision of the number is i; for example, in->In the case where i is 5, then +.>The preset upper limit of (2) is 0, the preset lower limit is 100, and the preset identification accuracy is 5, namely +.>Values of 0, 5, 10, 15, …, 100 can be taken.
In the embodiment of the present invention, the preset upper bound, the preset lower bound and the preset identification precision may be set by the user according to experience, or may be set by other modes, which is not particularly limited.
S130, determining a target calibration result aiming at the control parameter based on a preset upper limit, a preset lower limit, a preset identification precision and collected driving data.
In the embodiment of the invention, the target calibration result for the control parameter can be determined based on the preset upper bound, the preset lower bound, the preset identification precision and the acquired driving data, the target calibration result is the calibration result obtained by calibrating the control parameter, for example, the optimal calibration result obtained by calculating the acquired driving data in the possible calibration result of at least one control parameter obtained according to the preset identification precision in the preset upper bound and the preset lower bound range can be determined based on the preset upper bound, the preset lower bound, the preset identification precision and the acquired driving data, and the optimal calibration result is used as the target calibration result, so that the control parameter can be calibrated in a self-adaptive manner through off-line acquisition of the driving data without depending on professional equipment and manual debugging.
In the embodiment of the invention, the mode of determining the target calibration result for the control parameter based on the preset upper limit, the preset lower limit, the preset identification precision and the collected driving data is not particularly limited.
According to the technical scheme, acquired driving data acquired in the driving process of the target vehicle is acquired, and a target control mode of the target vehicle is determined; determining a preset upper limit, a preset lower limit and preset identification precision which are respectively corresponding to the control parameters aiming at the vehicle type of the target vehicle aiming at the control parameters to be calibrated of the target control mode; and determining a target calibration result aiming at the control parameter based on the preset upper limit, the preset lower limit, the preset identification precision and the acquired driving data. According to the technical scheme, the calibration of the control parameters can be achieved without depending on professional equipment and manual debugging by acquiring the driving data based on the driving process of the target vehicle and respectively corresponding preset upper bound, preset lower bound and preset identification precision of the control parameters to the vehicle type of the target vehicle, so that the calibration effect is good, and the cost of the calibration of the control parameters is reduced.
An optional technical scheme, before determining a target calibration result for the control parameter based on a preset upper bound, a preset lower bound, a preset identification precision and collected driving data, the parameter calibration method further comprises: performing data cleaning operation on the collected driving data according to at least one of a preset steering wheel angle threshold value, an acceleration threshold value, a jerk threshold value, a track deviation distance threshold value, a track deviation direction threshold value and a turning radius jump threshold value; and updating and collecting driving data according to the obtained data cleaning result.
The steering wheel angle threshold is a threshold set for a steering wheel angle in the collected driving data, and may be, for example, a maximum angle value set for the steering wheel angle. The acceleration threshold is a threshold set for acceleration in collecting driving data, and may be, for example, a maximum acceleration value set for acceleration. The jerk threshold is a threshold set for jerk in the collected driving data, and may be, for example, a maximum jerk value set for jerk. The trajectory deviation distance threshold is a threshold set for a position error of the planned driving trajectory and the actual driving trajectory in the collected driving data, and may be, for example, a maximum error value set for a position error of the planned driving trajectory and the actual driving trajectory. The trajectory deviation direction threshold is a threshold set for a direction error of the planned driving trajectory and the actual driving trajectory in the collected driving data, and may be, for example, a maximum error value set for the direction error of the planned driving trajectory and the actual driving trajectory. The turning radius jump threshold is a threshold set for the jump size between turning radii corresponding to adjacent frames in the collected driving data, and the turning radius jump threshold may be, for example, a maximum jump value set for the jump size between turning radii corresponding to adjacent frames.
It should be noted that, in the embodiment of the present invention, each frame may be a one-to-one correspondence to a time when a set of data is acquired each time in the process of acquiring the acquired driving data.
For example, according to the acquired driving data, a group of acquired data corresponding to frames, in which the steering angle is greater than the steering angle threshold, the acceleration is greater than the acceleration threshold, the jerk is greater than the jerk threshold, the position error of the planned driving track and the actual driving track is greater than the track deviation distance threshold, the direction error of the planned driving track and the actual driving track is greater than the track deviation direction threshold, and the jump size between the current frame and the turning radius corresponding to the adjacent frame is greater than at least one of the turning radius jump thresholds, may be satisfied, and the data cleaning operation may be performed on the acquired driving data, for example, a group of acquired data corresponding to frames, in which at least one of the conditions is satisfied, in the acquired driving data may be deleted from the acquired driving data, and then, for example, a group of acquired data corresponding to frames, in which at least one of the conditions is satisfied, in the front and back of the frames, is preset, may be deleted from the acquired driving data.
In the embodiment of the invention, the data cleaning operation can be performed on the collected driving data according to the frame corresponding to the data, in which the current frame and the corresponding adjacent frame have a larger error, namely the data exceeding the preset threshold corresponding to the data, in the collected driving data.
In the embodiment of the invention, the setting of the steering wheel angle threshold, the acceleration threshold, the jerk threshold, the track deviation distance threshold, the track deviation direction threshold and/or the turning radius jump threshold can be determined according to at least one of the target vehicle, the vehicle type of the target vehicle, the working condition of the target vehicle and the like.
In the embodiment of the invention, before a target calibration result for control parameters is determined based on a preset upper bound, a preset lower bound, preset identification precision and collected driving data, data cleaning operation can be performed on the collected driving data according to at least one of a preset steering wheel angle threshold, an acceleration threshold, a jerk threshold, a track deviation distance threshold, a track deviation direction threshold and a turning radius jump threshold; and updating and collecting driving data according to the obtained data cleaning result. According to the technical scheme, the data which are wrong, redundant, missing, inconsistent, abnormal, low in riding comfort and do not meet the requirement of self-calibration calculation on the data in the acquired driving data can be subjected to cleaning processing through the data cleaning operation, so that the accuracy, the completeness and the consistency of the acquired driving data are ensured, and the accuracy of calibrating the control parameters can be improved.
FIG. 2 is a flow chart of another parameter calibration method provided in an embodiment of the present invention. The present embodiment is optimized based on the above technical solutions. In this embodiment, optionally, determining the target calibration result for the control parameter based on the preset upper bound, the preset lower bound, the preset identification precision, and the collected driving data includes: determining at least one reference calibration result of the control parameter according to a preset upper limit, a preset lower limit and a preset identification precision; determining a cost function value according to the reference calibration result and the acquired driving data aiming at each reference calibration result in the at least one reference calibration result; and determining a target calibration result aiming at the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result. Wherein, the explanation of the same or corresponding terms as the above embodiments is not repeated herein.
Referring to fig. 2, the method of this embodiment may specifically include the following steps:
s210, acquiring acquired driving data acquired in the driving process of the target vehicle, and determining a target control mode of the target vehicle.
S220, determining a preset upper limit, a preset lower limit and a preset identification precision, which correspond to the vehicle type of the target vehicle, of the control parameters aiming at the control parameters to be calibrated of the target control mode.
S230, determining at least one reference calibration result of the control parameter according to the preset upper limit, the preset lower limit and the preset identification precision.
Wherein the reference calibration result is a calibration result that may be a calibration result of the control parameter.
Exemplary, if two control parameters A and B are present, inAndIn the case that the preset recognition accuracy of the control parameters A and B is 1, thenPossible values of 0 and 1, and possible values of B of 0, 1 and 2, thenThere can be six reference calibration results, the six reference calibration results being 0 for A and 0 for B, 0 for A and 1 for B, 0 for A and 2 for B, 1 for A and 0 for B, 1 for A and 1 for B, 1 for A and 2 for B, respectively.
S240, determining a cost function value according to the reference calibration result and the collected driving data aiming at each reference calibration result in the at least one reference calibration result.
In the embodiment of the invention, for each reference calibration result in at least one reference calibration result, the cost function value can be determined according to the reference calibration result and the acquired driving data through the cost function.
It should be noted that, the target control modes are different, and when the corresponding control parameters are calibrated, the collected driving data used for determining the cost function value needs may also be different, so according to the reference calibration result and the collected driving data, determining the cost function value may include: according to the target control mode, determining target driving data corresponding to the target control mode from the collected driving data, and determining a cost function value according to the target driving data and a reference calibration result, for example, in the case that the target control mode is LQR, determining the speed, steering wheel angle and wheelbase of the target vehicle, the position error and the position error change rate of a planned driving track and an actual driving track, and the direction error change rate of the planned driving track and the actual driving track from the collected driving data as the target driving data, and determining the cost function value according to the target driving data and the reference calibration result.
In the embodiment of the invention, since the target control modes are different, the mode of determining the cost function value according to the reference calibration result and the collected driving data is also different according to the target control mode for each reference calibration result in the at least one reference calibration result, and therefore, the mode of determining the cost function value according to the reference calibration result and the collected driving data is determined according to the target control mode for each reference calibration result in the at least one reference calibration result.
S250, determining a target calibration result aiming at the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result.
In the embodiment of the present invention, the manner of determining the target calibration result for the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result is not specifically limited, for example, the reference calibration result corresponding to the minimum cost function value in the cost function values respectively corresponding to the at least one reference calibration result may be used as the target calibration result for the control parameter.
In the embodiment of the invention, the process of determining the target calibration result for the control parameters can be realized in a for-loop mode, for example, under the condition that the control parameters required to be calibrated are 5, the reference corner data of each frame of data in the collected driving data can be calculated in the range of a preset upper bound and a preset lower bound through 5 layers of for-loop, the squares of errors of the reference corner data and the steering wheel corner under all the collected driving data are calculated in an accumulated mode, and finally, the reference calibration result corresponding to the minimum cost function value is used as the target calibration result for the control parameters. The step size of the for cycle may be a preset recognition accuracy.
According to the technical scheme, at least one reference calibration result of the control parameters is determined according to a preset upper limit, a preset lower limit and preset identification accuracy; determining a cost function value according to the reference calibration result and the acquired driving data aiming at each reference calibration result in the at least one reference calibration result; and determining a target calibration result aiming at the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result. In the embodiment of the invention, the target calibration result for the control parameter can be determined based on the cost function values respectively corresponding to the at least one reference calibration result, so that the accuracy of the determined target calibration result for the control parameter is improved.
An optional technical solution, determining a cost function value according to a reference calibration result and collected driving data, includes: determining reference rotation angle data according to the reference calibration result and the acquired driving data; and determining the cost function value according to the reference rotation angle data and the acquired driving data.
In the embodiment of the invention, for a group of data corresponding to each frame in the acquired driving data, determining the reference corner data corresponding to the frame according to the group of data and the reference calibration result, wherein the reference corner data is the steering wheel corner which can be calculated when the reference calibration result is adopted as the calibration result of the control data; the formula can be used: And determining the square of the difference between the reference steering angle data and the steering wheel steering angle in the group of data in the acquired driving data, namely determining the square of the difference between the actual steering wheel steering angle and the steering wheel steering angle obtained when the reference calibration result is used as the calibration result of the control data, and carrying out cumulative calculation on the square of the difference obtained by respectively determining according to the group of data corresponding to at least one frame in the acquired driving data to obtain the cost function value. Where Cost is the Cost function value; />Representing +.>A frame; />For the acquisition of the +.>A frame, i.e., the largest frame used when the control data is calibrated;collecting steering wheel rotation angles in driving data; />Is the reference rotation angle data.
In the embodiment of the invention, the mode of determining the reference rotation angle data according to the reference calibration result and the collected driving data can be determined according to the target control modes, namely different target control modes, and the mode of determining the reference rotation angle data according to the reference calibration result and the collected driving data can be different.
For example, in the case where the target control mode is LQR, the LQR may use a vehicle kinematic model to satisfy the formula The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>；/>；/>The method comprises the steps of carrying out a first treatment on the surface of the k represents the time instant, i.e. the frame; />Is a control period; u (k) is the steering wheel angle; />；/>The vehicle speed is the vehicle speed; />Is the steering wheel angle; />Is the wheelbase; the position error between the planned driving track and the actual driving track is +.>The method comprises the steps of carrying out a first treatment on the surface of the The change rate of the position error is +.>The method comprises the steps of carrying out a first treatment on the surface of the The direction error of the planned driving track and the actual driving track is +.>The method comprises the steps of carrying out a first treatment on the surface of the The change rate of the direction error is +.>；
The optimal problem in LQR is: for this controlled system of the vehicle, an optimal solution for the feedback control law U is determined such that the following performance indicators are minimized:the method comprises the steps of carrying out a first treatment on the surface of the The state feedback quantity in the optimal feedback control law isThe method comprises the steps of carrying out a first treatment on the surface of the P may be determined by solving the algebraic Li-Carl equation (Riccati equation)Obtaining; therefore, the key of the design of the optimal controller is to select a proper weighting matrix Q and a proper coefficient R, calculate P in an algebraic equation of a Li Kadi matrix and calculate a feedback gain K; wherein:；/>and->Is a control coefficient to be calibrated; the reference calibration result can be substitutedAnd->Substituting the related data in the collected driving data into the formula to obtain reference rotation angle data, namely the U (k).
In the embodiment of the invention, the reference corner data can be determined according to the reference calibration result and the acquired driving data; and determining the cost function value according to the reference rotation angle data and the acquired driving data. According to the technical scheme, the cost function value with higher accuracy can be determined based on the reference rotation angle data, so that the accuracy of the determined target calibration result aiming at the control parameter is further improved.
FIG. 3 is a flow chart of yet another parameter calibration method provided in an embodiment of the present invention. The present embodiment is optimized based on the above technical solutions. In this embodiment, optionally, determining the target calibration result for the control parameter based on the cost function value corresponding to the at least one reference calibration result includes: determining at least one reference calibration result to respectively correspond to the minimum cost function value in the cost function values; and determining a target calibration result aiming at the control parameter based on the reference calibration result corresponding to the minimum cost function value. Wherein, the explanation of the same or corresponding terms as the above embodiments is not repeated herein.
Referring to fig. 3, the method of this embodiment may specifically include the following steps:
s310, acquiring acquired driving data acquired in the driving process of the target vehicle, and determining a target control mode of the target vehicle.
S320, determining a preset upper limit, a preset lower limit and a preset identification precision, which correspond to the vehicle type of the target vehicle, of the control parameters aiming at the control parameters to be calibrated of the target control mode.
S330, determining at least one reference calibration result of the control parameter according to the preset upper limit, the preset lower limit and the preset identification precision.
S340, determining a cost function value according to the reference calibration result and the collected driving data aiming at each reference calibration result in the at least one reference calibration result.
S350, determining that at least one reference calibration result corresponds to the minimum cost function value in the cost function values respectively.
The minimum cost function value is the minimum cost function value in the cost function values corresponding to at least one reference calibration result respectively.
S360, determining a target calibration result aiming at the control parameter based on a reference calibration result corresponding to the minimum cost function value.
It may be appreciated that the at least one reference calibration result corresponding to the minimum cost function value is closest to the steering wheel angle in the collected driving data, and therefore, the target calibration result for the control parameter may be determined based on the reference calibration result corresponding to the minimum cost function value.
In the embodiment of the present invention, the manner of determining the target calibration result for the control parameter based on the reference calibration result corresponding to the minimum cost function value is not particularly limited.
According to the technical scheme, at least one reference calibration result is determined to correspond to the minimum cost function value in the cost function values respectively; and determining a target calibration result aiming at the control parameter based on the reference calibration result corresponding to the minimum cost function value. According to the technical scheme, the target calibration result for the control parameter is determined based on the reference calibration result corresponding to the minimum cost function value, so that the accuracy of the determined target calibration result for the control parameter can be further improved.
An optional technical solution, determining a target calibration result for the control parameter based on a reference calibration result corresponding to the minimum cost function value, includes: determining an upper target boundary, a lower target boundary and target identification precision based on a reference calibration result corresponding to the minimum cost function value; and determining a target calibration result aiming at the control parameter based on the target upper limit, the target lower limit, the target identification precision and the collected driving data.
It can be understood that, in order to ensure the calibration efficiency of the control parameter, the accuracy value of the preset identification accuracy may be larger, so that the number of the obtained reference calibration results is relatively smaller; however, in order to ensure the calibration efficiency of the control parameter and also ensure the accuracy of the target calibration result for the control parameter, in the embodiment of the present invention, the target upper boundary, the target lower boundary and the target identification accuracy are determined based on the reference calibration result corresponding to the minimum cost function value, for example, the reference calibration result adjacent to the reference calibration result corresponding to the minimum cost function value may be determined according to the reference calibration result corresponding to the minimum cost function value, and the target upper boundary, the target lower boundary and the target identification accuracy are determined according to the adjacent reference calibration result; and determining a target calibration result aiming at the control parameter based on the target upper limit, the target lower limit, the target identification precision and the collected driving data.
In the embodiment of the present invention, the manner of determining the target calibration result for the control parameter based on the target upper boundary, the target lower boundary, the target identification precision and the collected driving data may be the same as the manner of determining the target calibration result for the control parameter based on the preset upper boundary, the preset lower boundary, the preset identification precision and the collected driving data, for example, at least one target calibration result for the control parameter may be determined according to the target upper boundary, the target lower boundary and the target identification precision, each target calibration result in the at least one target calibration result may be determined, the target cost function value may be determined according to the target calibration result and the collected driving data, the minimum target cost function value in the cost function values may be respectively corresponding to the at least one target calibration result, and the target calibration result corresponding to the minimum target cost function value may be used as the target calibration result for the control parameter.
It should be noted that the target recognition accuracy is smaller than the preset recognition accuracy.
Exemplary, if control parameter C is present, inUnder the condition that the preset recognition accuracy of the control parameter C is 5, if the reference calibration result corresponding to the minimum cost function value is 25, the target upper bound is 20, the target lower bound is 30 and the target recognition accuracy is 1.
In the embodiment of the invention, the upper boundary of the target, the lower boundary of the target and the identification precision of the target can be determined based on the reference calibration result corresponding to the minimum cost function value; and determining a target calibration result aiming at the control parameter based on the target upper limit, the target lower limit, the target identification precision and the collected driving data. According to the technical scheme, the target calibration result of the control parameter can be determined to be secondarily calibrated based on the target upper bound, the target lower bound, the target identification precision and the acquired driving data, so that the calculation speed is high, the calculation force required by operation is small, the execution is convenient, and the actual application is good, and therefore the accuracy of the target calibration result of the control parameter can be guaranteed while the calibration efficiency of the control parameter is guaranteed.
For better understanding of the technical solution of the embodiment of the present invention described above, an alternative example is provided herein. For example, referring to fig. 4, acquired driving data acquired for a driving course of a target vehicle may be acquired, and the acquired driving data may include vehicle body information and vehicle surrounding information; performing data cleaning operation on the collected driving data, and updating the collected driving data according to the obtained data cleaning result; determining a preset upper bound, a preset lower bound and preset identification precision of control parameters corresponding to the vehicle type of the target vehicle respectively; and performing self-calibration calculation on the control parameters based on a preset upper limit, a preset lower limit, a preset identification precision and the acquired driving data to obtain a target calibration result aiming at the control parameters.
In another alternative solution, determining a target calibration result for the control parameter based on a reference calibration result corresponding to the minimum cost function value includes: and taking the reference calibration result corresponding to the minimum cost function value as a target calibration result aiming at the control parameter.
In the embodiment of the invention, the reference calibration result corresponding to the minimum cost function value can be directly used as the target calibration result for the control parameter, so that the calibration efficiency for the control parameter can be ensured.
FIG. 5 is a block diagram of a parameter calibration apparatus according to an embodiment of the present invention, where the apparatus is configured to execute the parameter calibration method according to any of the foregoing embodiments. The device and the parameter calibration method of each embodiment belong to the same invention conception, and the details of the embodiment of the parameter calibration device, which are not described in detail, can be referred to the embodiment of the parameter calibration method. Referring to fig. 5, the apparatus may specifically include: the target control mode determining module 410, the preset identification accuracy determining module 420 and the target calibration result determining module 430.
The target control mode determining module 410 is configured to acquire acquired driving data acquired in a driving process of the target vehicle, and determine a target control mode of the target vehicle;
The preset identification precision determining module 420 is configured to determine, for a control parameter to be calibrated of a target control manner, a preset upper bound, a preset lower bound and a preset identification precision, which correspond to a vehicle type of a target vehicle, respectively;
the target calibration result determining module 430 is configured to determine a target calibration result for the control parameter based on the preset upper bound, the preset lower bound, the preset identification accuracy, and the collected driving data.
Optionally, the target calibration result determining module 430 may include:
the reference calibration result determining unit is used for determining at least one reference calibration result of the control parameter according to a preset upper limit, a preset lower limit and a preset identification precision;
a cost function value determining unit, configured to determine a cost function value for each of the at least one reference calibration result according to the reference calibration result and the collected driving data;
and the target calibration result determining unit is used for determining a target calibration result aiming at the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result.
Optionally, on the basis of the above device, the target calibration result determining unit may include:
A minimum cost function value determining subunit, configured to determine at least one reference calibration result respectively corresponding to a minimum cost function value of the cost function values;
and the target calibration result determining subunit is used for determining a target calibration result aiming at the control parameter based on the reference calibration result corresponding to the minimum cost function value.
Optionally, on the basis of the above device, the target calibration result determining subunit may specifically be configured to:
determining an upper target boundary, a lower target boundary and target identification precision based on a reference calibration result corresponding to the minimum cost function value;
and determining a target calibration result aiming at the control parameter based on the target upper limit, the target lower limit, the target identification precision and the collected driving data.
Optionally, on the basis of the above device, the target calibration result determining subunit may specifically be configured to:
and taking the reference calibration result corresponding to the minimum cost function value as a target calibration result aiming at the control parameter.
Alternatively, on the basis of the above apparatus, the cost function value determining unit may include:
the reference rotation angle data determining subunit is used for determining reference rotation angle data according to a reference calibration result and acquired driving data;
And the cost function value determining subunit is used for determining the cost function value according to the reference rotation angle data and the collected driving data.
Optionally, on the basis of the above device, the device may further include:
the data cleaning module is used for performing data cleaning operation on the collected driving data according to at least one of a preset steering wheel angle threshold value, an acceleration threshold value, a jerk threshold value, a track deviation distance threshold value, a track deviation direction threshold value and a turning radius jump threshold value before determining a target calibration result for control parameters based on a preset upper limit, a preset lower limit, a preset identification precision and the collected driving data;
and the collected driving data updating module is used for updating the collected driving data according to the obtained data cleaning result.
According to the parameter calibration device provided by the embodiment of the invention, the collected driving data collected in the driving process of the target vehicle is obtained through the target control mode determining module, and the target control mode of the target vehicle is determined; determining, by a preset identification accuracy determining module, a preset upper bound, a preset lower bound and a preset identification accuracy, which correspond to a vehicle type of a target vehicle, of control parameters aiming at control parameters to be calibrated of a target control mode; and determining a target calibration result aiming at the control parameter based on the preset upper limit, the preset lower limit, the preset identification precision and the acquired driving data by a target calibration result determining module. According to the device, the calibration of the control parameters can be realized without depending on professional equipment and manual debugging by acquiring the driving data based on the driving process of the target vehicle and respectively corresponding preset upper bound, preset lower bound and preset identification precision of the control parameters for the vehicle type of the target vehicle, so that the calibration effect is good, and the cost of the calibration of the control parameters is reduced.
The parameter calibration device provided by the embodiment of the invention can execute the parameter calibration method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
It should be noted that, in the embodiment of the parameter calibration device, each unit and module included are only divided according to the functional logic, but not limited to the above division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Fig. 6 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the 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. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, 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, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may 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.
Various 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, etc.; 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.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the parameter calibration method.
In some embodiments, the parameter calibration method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the 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 of the steps of the parameter calibration method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the parameter calibration method in any other suitable way (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On 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, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out 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 implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the 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. The 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) through 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 may 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 input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background 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 background, 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. The client and server are typically 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 hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (9)
1. The parameter calibration method is characterized by comprising the following steps of:
acquiring acquired driving data acquired in a driving process of a target vehicle, and determining a target control mode of the target vehicle;
determining a preset upper bound, a preset lower bound and preset identification precision, which correspond to the vehicle type of the target vehicle, of the control parameters aiming at the control parameters to be calibrated of the target control mode;
Determining a target calibration result for the control parameter based on the preset upper bound, the preset lower bound, the preset identification precision and the acquired driving data;
the determining a target calibration result for the control parameter based on the preset upper bound, the preset lower bound, the preset identification precision and the collected driving data includes:
determining at least one reference calibration result of the control parameter according to the preset upper bound, the preset lower bound and the preset identification precision;
determining a cost function value according to the reference calibration result and the collected driving data for each reference calibration result in the at least one reference calibration result;
determining a target calibration result for the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result;
and determining a cost function value according to the reference calibration result and the acquired driving data.
2. The method according to claim 1, wherein the determining a target calibration result for the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result comprises:
Determining the minimum cost function value in the cost function values respectively corresponding to the at least one reference calibration result;
and determining a target calibration result aiming at the control parameter based on the reference calibration result corresponding to the minimum cost function value.
3. The method of claim 2, wherein the determining a target calibration result for the control parameter based on the reference calibration result corresponding to the minimum cost function value comprises:
determining an upper target boundary, a lower target boundary and target identification precision based on a reference calibration result corresponding to the minimum cost function value;
and determining a target calibration result for the control parameter based on the target upper bound, the target lower bound, the target identification precision and the acquired driving data.
4. The method of claim 2, wherein the determining a target calibration result for the control parameter based on the reference calibration result corresponding to the minimum cost function value comprises:
and taking the reference calibration result corresponding to the minimum cost function value as a target calibration result aiming at the control parameter.
5. The method of claim 1, wherein said determining a cost function value from said reference calibration result and said collected driving data comprises:
Determining reference rotation angle data according to the reference calibration result and the acquired driving data;
and determining a cost function value according to the reference rotation angle data and the acquired driving data.
6. The method of claim 1, further comprising, prior to the determining a target calibration result for the control parameter based on the preset upper bound, the preset lower bound, the preset recognition accuracy, and the collected driving data:
performing data cleaning operation on the collected driving data according to at least one of a preset steering wheel angle threshold value, an acceleration threshold value, a jerk threshold value, a track deviation distance threshold value, a track deviation direction threshold value and a turning radius jump threshold value;
and updating the collected driving data according to the obtained data cleaning result.
7. A parameter calibration device, comprising:
the target control mode determining module is used for acquiring acquired driving data acquired in the driving process of the target vehicle and determining a target control mode of the target vehicle;
the preset identification precision determining module is used for determining a preset upper limit, a preset lower limit and preset identification precision which are respectively corresponding to the vehicle type of the target vehicle according to the control parameters to be calibrated of the target control mode;
The target calibration result determining module is used for determining a target calibration result aiming at the control parameter based on the preset upper limit, the preset lower limit, the preset identification precision and the acquired driving data;
the target calibration result determining module comprises:
the reference calibration result determining unit is used for determining at least one reference calibration result of the control parameter according to a preset upper limit, a preset lower limit and a preset identification precision;
a cost function value determining unit, configured to determine a cost function value for each of the at least one reference calibration result according to the reference calibration result and the collected driving data;
the target calibration result determining unit is used for determining a target calibration result aiming at the control parameter based on the cost function values respectively corresponding to the at least one reference calibration result;
and determining a cost function value according to the reference calibration result and the acquired driving data.
8. An electronic device, comprising:
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 cause the at least one processor to perform the parameter calibration method of any one of claims 1-6.
9. A computer readable storage medium storing computer instructions for causing a processor to perform the parameter calibration method according to any one of claims 1-6.
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