CN116069041B - Track planning method, device, vehicle and medium - Google Patents

Track planning method, device, vehicle and medium Download PDF

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CN116069041B
CN116069041B CN202310272415.3A CN202310272415A CN116069041B CN 116069041 B CN116069041 B CN 116069041B CN 202310272415 A CN202310272415 A CN 202310272415A CN 116069041 B CN116069041 B CN 116069041B
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parameter
path
target
speed
value
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CN116069041A (en
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周荣宽
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Beijing Jidu Technology Co Ltd
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Beijing Jidu Technology Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0219—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory ensuring the processing of the whole working surface
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The embodiment of the application provides a track planning method, a track planning device, a vehicle and a medium, and relates to the technical field of vehicle control. The method comprises the following steps: taking the path parameter value and the speed parameter value as input data of a prediction model to obtain a path parameter predicted value and a speed parameter predicted value corresponding to a preset track point; obtaining a path target parameter value and a speed target parameter value according to the path parameter predicted value and the path expected parameter value; thereby obtaining target track planning information; and sending the target track planning information to a control unit so that the control unit can execute track control on the vehicle according to the target track control information. According to the embodiment of the application, the path parameter value and the speed parameter value are used as input data of the prediction model so as to obtain the path target parameter value and the speed target parameter value, so that the target track information is obtained based on coupling of the path target parameter value and the speed target parameter value, and efficient track control is realized.

Description

Track planning method, device, vehicle and medium
Technical Field
The present disclosure relates to the field of vehicle control technologies, and in particular, to a track planning method, a device, a vehicle, and a medium.
Background
Vehicle intellectualization is one of the main development directions of the current vehicle technology, and automatic driving technology is a key technology in the vehicle intellectualization process. In the automatic driving technology, the track planning technology can enable the vehicle to avoid obstacles and stably run. The track planning technology can be realized by planning a safe and efficient running track according to the current surrounding environment, and providing the running track for various actuators for controlling the movement of the vehicle to perform corresponding steering and acceleration and deceleration control.
The inventor finds out in the process of realizing the invention that the track control involves path control and speed control, how to efficiently obtain corresponding control parameter values, and further realize efficient track control, and the invention becomes a technical problem to be solved.
Disclosure of Invention
The embodiment of the application provides a track planning method, a track planning device, a vehicle and a medium, which are used for realizing a scheme of efficient track control.
In a first aspect, an embodiment of the present application provides a track planning method, including:
acquiring a path parameter value, a speed parameter value and a control parameter value corresponding to a current track point of a vehicle;
taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to a preset track point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value;
Obtaining target track planning information based on path target parameter values and the speed target parameter values respectively corresponding to a plurality of preset track points;
and sending the target track planning information to a control unit so that the control unit can execute track control on the vehicle according to the target track control information.
In a second aspect, an embodiment of the present application provides a trajectory planning device, including:
the acquisition module is used for acquiring a path parameter value, a speed parameter value and a control parameter value corresponding to the current track point of the vehicle; taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to a preset track point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value; obtaining target track planning information based on path target parameter values and speed target parameter values respectively corresponding to a plurality of preset track points;
the generation module is used for generating target difference information according to the first difference information of the path parameter predicted value and the path expected parameter value and the second difference information of the speed parameter predicted value and the speed expected parameter value;
The adjusting module is used for adjusting the path parameter predicted value and the speed parameter predicted value to obtain a path target parameter value and a speed target parameter value by taking the target difference information accords with an optimization condition as an optimization target;
and the sending module is used for sending the target track planning information to a control unit so that the control unit can execute track control on the vehicle according to the target track control information.
In a third aspect, embodiments of the present application provide a vehicle, including: a vehicle body and a display device;
the vehicle body is provided with a memory, a processor and a sensor;
the memory is used for storing one or more computer instructions;
the processor is configured to execute the one or more computer instructions for performing the first aspect.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program, where the computer program is capable of implementing the steps of the method according to the first aspect when executed.
In the track planning method, device, apparatus and medium provided in the embodiments of the present application, the method includes: acquiring a path parameter value, a speed parameter value and a control parameter value corresponding to a current track point of a vehicle; taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to a preset track point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value; and sending the target track planning information to a control unit so that the control unit can execute track control on the vehicle according to the target track control information. According to the embodiment of the application, the path parameter value and the speed parameter value are used as input data of the prediction model so as to obtain the path target parameter value and the speed target parameter value, so that the target track information is obtained based on coupling of the path target parameter value and the speed target parameter value, and efficient track control is realized.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 shows a schematic flow chart of a track planning method provided in the present application;
FIG. 2 is a flow chart of another trajectory planning method provided herein;
fig. 3 is a schematic structural diagram of a track planning apparatus according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application.
Detailed Description
In order to enable those skilled in the art to better understand the present invention, the following description will make clear and complete descriptions of the technical solutions according to the embodiments of the present invention with reference to the accompanying drawings.
In some of the flows described in the description of the invention, the claims, and the figures described above, a number of operations occurring in a particular order are included, and the operations may be performed out of order or concurrently with respect to the order in which they occur. The sequence numbers of operations such as 101, 102, etc. are merely used to distinguish between the various operations, and the sequence numbers themselves do not represent any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.
For easy understanding, the technical scheme of the present application will be described below in connection with specific embodiments. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
Fig. 1 shows a flow chart of a track planning method provided in the present application, where the track planning method may be applied to a path algorithm unit of a vehicle-mounted system, and the vehicle-mounted system is mounted on a vehicle, as shown in fig. 1, and the method includes:
101. and obtaining a path parameter value, a speed parameter value and a control parameter value corresponding to the current track point of the vehicle.
102. And taking the path parameter value, the speed parameter value and the control parameter value as input data of the first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to the preset track point obtained by the first prediction model to obtain the path target parameter value and the speed target parameter value.
103. And obtaining target track planning information based on the path target parameter values and the speed target parameter values respectively corresponding to the plurality of preset track points.
104. The target trajectory planning information is sent to the control unit so that the control unit performs trajectory control of the vehicle in accordance with the target trajectory control information.
The path parameter value corresponding to the current track point can comprise at least one of a current track transverse deviation, a track course angle deviation and a front wheel corner of the vehicle, and the speed parameter value corresponding to the current track point can comprise at least one of a current speed and an acceleration of the vehicle.
Optionally, a sensor may be installed in the vehicle, for acquiring a path parameter value, a speed parameter value, and a control parameter value corresponding to a current track point of the vehicle.
In addition, the control parameter value corresponding to the current track point may be a future input parameter value as a prediction model, for example, the sensor has an intersection after the control parameter value currently detected is 30 meters and needs to turn, and then the prediction model may influence the path parameter predicted value and the speed parameter predicted value corresponding to the current track point based on the control parameter value, and may be represented as steering ahead, braking ahead, and the like.
The first prediction model may be (Model Predictive Control, abbreviated as MPC) model, and the corresponding path parameter predicted value and the corresponding speed parameter predicted value may be obtained based on the input path parameter value, the speed parameter value and the control parameter value.
The path expected parameter value and the speed expected parameter value may be obtained in advance, so that the path parameter predicted value and the speed parameter predicted value may be compared with the path expected parameter value and the speed expected parameter value, and the target difference information may be generated based on the first difference information of the path parameter predicted value and the path expected parameter value and the second difference information of the speed parameter predicted value and the speed expected parameter value.
It can be understood that the smaller the difference value represented by the target difference information, the smaller the difference between the parameter predicted value and the parameter expected value, the more the parameter predicted value of the preset track point accords with the expectation, so that the optimization condition can gradually adjust each parameter predicted value by taking the difference value represented by the target difference information as the optimization target when the difference value represented by the target difference information is minimum, so that the target difference information accords with the optimization condition.
And optimizing each parameter predicted value corresponding to the preset track points according to the optimization method to obtain corresponding path target parameter values and speed target parameter values.
Further, the target trajectory planning information may be transmitted to the control unit so that the control unit performs trajectory control of the vehicle in accordance with the target trajectory control information.
The track planning method provided by the embodiment of the application. According to the embodiment of the application, the path parameter value and the speed parameter value are used as input data of the prediction model so as to obtain the path target parameter value and the speed target parameter value, so that the target track information is obtained based on coupling of the path target parameter value and the speed target parameter value, and efficient track control is realized.
To describe in detail a specific process of obtaining the path target parameter value and the speed target parameter value, fig. 2 shows a flow chart of another track planning method provided in the present application, where the track planning method may be applied to a path algorithm unit of a vehicle system, and the vehicle system is installed on a vehicle, as shown in fig. 2, and the method includes:
201. and obtaining a path parameter value, a speed parameter value and a control parameter value corresponding to the current track point of the vehicle.
202. And taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, so as to obtain a path parameter predicted value and a speed parameter predicted value corresponding to a preset track point by using the first prediction model.
203. And generating target difference information according to the first difference information of the path parameter predicted value and the path expected parameter value and the second difference information of the speed parameter predicted value and the speed expected parameter value.
204. And taking the target difference information meeting the optimization condition as an optimization target, and adjusting the path parameter predicted value and the speed parameter predicted value to obtain a path target parameter value and a speed target parameter value.
The path expected parameter value and the speed expected parameter value may be obtained in advance, so that the path parameter predicted value and the speed parameter predicted value may be compared with the path expected parameter value and the speed expected parameter value, and the target difference information may be generated based on the first difference information of the path parameter predicted value and the path expected parameter value and the second difference information of the speed parameter predicted value and the speed expected parameter value.
It can be understood that the smaller the difference value represented by the target difference information, the smaller the difference between the parameter predicted value and the parameter expected value, the more the parameter predicted value of the preset track point accords with the expectation, so that the optimization condition can gradually adjust each parameter predicted value by taking the difference value represented by the target difference information as the optimization target when the difference value represented by the target difference information is minimum, so that the target difference information accords with the optimization condition.
205. And obtaining target track planning information based on the path target parameter values and the speed target parameter values respectively corresponding to the plurality of preset track points.
206. The target trajectory planning information is sent to the control unit so that the control unit performs trajectory control of the vehicle in accordance with the target trajectory control information.
In some embodiments, adjusting the path parameter predicted value and the speed parameter predicted value to obtain the path target parameter value and the speed target parameter value with the target difference information meeting the optimization condition as the optimization target includes: taking the minimum value of the target difference information as an optimization target, and adjusting a path parameter predicted value and a speed parameter predicted value; when the target difference information reaches the minimum value, the path parameter predicted value after adjustment is taken as the path target parameter value and the speed parameter predicted value after adjustment is taken as the speed target parameter value.
As described above, the smaller the difference value represented by the target difference information, the smaller the difference between the parameter predicted value and the parameter expected value, the more the parameter predicted value of the preset track point meets the expectation, so that the optimization condition can gradually adjust each parameter predicted value by taking the difference value represented by the target difference information as the optimization target when the difference value represented by the target difference information is minimum, so that the target difference information meets the optimization condition.
In some embodiments, the path parameter values comprise at least one path sub-parameter value; the speed parameter values include at least one speed sub-parameter value; the path parameter values comprise at least one path sub-parameter value; the path parameter predictor includes at least one path subparameter predictor, generating target difference information according to first difference information of the path parameter predictor and a path parameter expected value and second difference information of the speed parameter predictor and the speed parameter expected value includes: calculating first difference information of at least one path sub-parameter predicted value and each path sub-parameter expected value by using an objective function corresponding to the at least one path sub-parameter value respectively; calculating second difference information of at least one speed subparameter predicted value and each speed subparameter expected value by utilizing the corresponding objective function of at least one speed subparameter; and summing the at least one first difference information and the at least one second difference information to obtain target difference information.
As can be seen from the above, the path parameter value corresponding to the current track point may include at least one of a current track lateral deviation, a track course angle deviation and a front wheel corner of the vehicle, the speed parameter value corresponding to the current track point may include at least one of a current speed and an acceleration of the vehicle, and the corresponding at least one speed sub-parameter value may include at least one of a speed and an acceleration, and the at least one path sub-parameter value may include at least one of a track lateral deviation, a track course angle deviation and a front wheel corner of the vehicle.
In addition, each sub-parameter predicted value is respectively corresponding to an objective function, and the objective function is used for representing the difference between the sub-parameter predicted value and the expected predicted value, so that the objective functions respectively corresponding to the sub-parameter predicted values can be summed to obtain final objective difference information, and when the objective difference information is minimum, the corresponding parameter predicted value is the parameter objective value.
In some embodiments, each piece of difference information has a corresponding weight coefficient, and summing the at least one piece of first difference information and the at least one piece of second difference information to obtain the target difference information may be implemented as: determining weight coefficients corresponding to the at least one first difference information and the at least one second difference information respectively; adjusting at least one first difference information and at least one second difference information based on the weight coefficient; and summing the adjusted at least one first difference information and the at least one second difference information to obtain target difference information.
The weight coefficient is related to the importance degree of the sub-parameter, and the more important the sub-parameter is, the larger the corresponding weight coefficient is, wherein the weight coefficient may be obtained by receiving the weight coefficient corresponding to each sub-parameter input by the user, so as to determine the weight coefficient corresponding to each sub-parameter.
Further, each sub-parameter predicted value is adjusted to take the path parameter predicted value when the target difference information is minimum as the path target parameter value and take the adjusted speed parameter predicted value as the speed target parameter value.
In addition, there may be other objective functions corresponding to other parameters, such as a distance between the objective vehicle and the objective function, a difference value between the objective function and a track lateral deviation between the objective vehicle, and the like, and the corresponding objective function may be flexibly set according to specific situations.
In some embodiments, the vehicle-mounted system further includes a control unit, and according to the target track information, performing track control on the vehicle may be implemented as follows: the method comprises the steps of sending a path target parameter value and a speed target parameter value to an instruction generation unit, wherein the instruction generation unit is used for generating a corresponding control instruction based on the path target parameter value and the speed target parameter value, and sending the control instruction to a control unit, and the control unit is used for controlling the vehicle to perform corresponding track movement based on the control instruction.
In some scenes, the vehicle-mounted system is provided with an instruction generating unit, so as to simplify the algorithm complexity of the track planning, a MPC model can be utilized to obtain corresponding path target parameter values and speed target parameter values, wherein the path target parameter values and the speed target parameter values can comprise track transverse deviations corresponding to each track planning point
Figure SMS_1
Track course angle deviation->
Figure SMS_2
Front wheel corner of vehicle>
Figure SMS_3
It will be appreciated that, in general, the track points are generally represented by x-coordinates, y-coordinates, angles, curvatures, curvature change rates, arc lengths, time periods, and the like, so that the command generating unit may convert the path target parameter values and the speed target parameter values into track data of the x-coordinates, y-coordinates, angles, curvatures, curvature change rates, arc lengths, time periods, and the like, so as to generate corresponding control commands based on the converted data, and send the control commands to the control unit, so that the control unit controls the vehicle to perform corresponding running according to the control commands.
It should be noted that, the instruction generating unit may only output the track data corresponding to the first preset track point to the control unit, and after the control unit executes the control action of the track data element corresponding to the first preset track point, the path algorithm unit has already generated the path target parameter values and the speed target parameter values corresponding to the plurality of preset track points in the next period, that is, the instruction generating unit has already generated the track data corresponding to the plurality of preset track points in the next later period. Therefore, after the control unit executes the control action corresponding to the first preset track point in the present period, the control action corresponding to the first preset track point in the next period can be executed, thereby completing the roll-off type finite time domain optimization strategy
As another alternative embodiment, the vehicle system itself is not provided with an instruction generating unit, and the MPC model is required to output the corresponding control variable or the variation of the corresponding control variable. In some embodiments, the path parameter value, the speed parameter value, and the control parameter value are used as input data of the second prediction model, so that a corresponding path parameter predicted value, a speed expected parameter value, and a control parameter predicted value can be obtained, and thus the path parameter predicted value, the speed parameter predicted value, and the control parameter predicted value can be adjusted, so as to obtain a control planning target parameter value, and the method further includes: taking the path parameter value, the speed parameter value and the control parameter value as input data of a second prediction model, so as to obtain motion control parameter predicted values respectively corresponding to a plurality of preset track points by using the second prediction model; generating target difference information according to the first difference information of the path parameter predicted value and the path expected parameter value, the second difference information of the speed parameter predicted value and the speed expected parameter value and the third difference information of the control parameter predicted value and the control path expected parameter value aiming at any preset track point; taking the target difference information meeting the optimization condition as an optimization target, and adjusting the path parameter predicted value, the speed parameter predicted value and the control parameter predicted value to obtain a control planning target parameter value; obtaining target track control information based on control planning target parameter values corresponding to a plurality of preset track points; and performing track control on the vehicle according to the target track control information.
The control parameter value and the control parameter predicted value may be any one of a steering wheel change rate and an acceleration change rate. The second predictive model may be an MPC model and may be based on the input path parameter values and the speed parameter values and the corresponding path parameter predictors, speed parameter predictors, and control parameter predictors.
It may be appreciated that in some scenarios, the vehicle-to-machine system is not provided with a control unit, and therefore, the second prediction model may obtain the corresponding path parameter predicted value, the speed parameter predicted value, and the control parameter predicted value based on the input path parameter value, the speed parameter value, and the control parameter value, so as to optimize the path parameter predicted value, the speed parameter predicted value, and the control parameter predicted value, and obtain the corresponding path parameter predicted value, the speed parameter predicted value, and the control parameter predicted value.
It should be noted that, the transfer function in the MPC model may be adjusted accordingly based on the configuration of the vehicle system, if the vehicle system is configured with the control unit, the MPC model may obtain the corresponding path parameter predicted value and the speed parameter predicted value based on the path parameter value, the speed parameter value and the control parameter value, and if the vehicle system is not configured with the control unit, the MPC model may obtain the corresponding path parameter predicted value, the speed parameter predicted value and the motion control parameter predicted value based on the path parameter value, the speed parameter value and the control parameter value, or obtain the corresponding path parameter predicted value and the speed parameter predicted value based on the path parameter value, the speed parameter value and the control parameter value. Therefore, the corresponding prediction model can be flexibly set based on the configuration of the vehicle-to-machine system
Taking an MPC model as an example, the process of trajectory planning can be described in detail by obtaining a path parameter predicted value, a speed parameter predicted value, and a motion control parameter predicted value based on the path parameter value, the speed parameter value, and the control parameter value.
The corresponding path parameter value of a certain vehicle is the track lateral deviation
Figure SMS_4
Track course angle deviation->
Figure SMS_5
Front wheel corner of vehicle>
Figure SMS_6
The speed parameter value speed v, acceleration a and control parameters are as follows: wheel front wheel angle change rate u->
Figure SMS_7
Acceleration ofRate of change->
Figure SMS_8
Time t.
And respectively differentiating the path parameter value and the speed parameter value in space to obtain a differential equation as follows:
Figure SMS_9
Figure SMS_10
Figure SMS_11
Figure SMS_12
Figure SMS_13
Figure SMS_14
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_26
for the length of travel along the reference line, +.>
Figure SMS_15
For reference line curvature->
Figure SMS_22
For the current vehicle speed>
Figure SMS_24
For the vehicle centroid side deviation angle +.>
Figure SMS_28
For track lateral deviation +.>
Figure SMS_30
For track course angle deviation +.>
Figure SMS_31
For the front wheel corner of the vehicle->
Figure SMS_23
For track speed +.>
Figure SMS_27
For track acceleration +.>
Figure SMS_17
For time (I)>
Figure SMS_19
For the distance of the rear axle of the vehicle to the centre of mass +.>
Figure SMS_18
Is the wheelbase of the vehicle. The model considers both the transverse planning and motion control of the vehicle track and the longitudinal planning and motion control of the vehicle track, thereby being a transverse-longitudinal coupled track planning and vehicle control model. Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_21
，/>
Figure SMS_25
，/>
Figure SMS_29
Three items corresponding to path parameter values, < ->
Figure SMS_16
And->
Figure SMS_20
Corresponding to the speed parameter value.
Further, the path parameter predicted value, the speed parameter predicted value and the motion control parameter predicted value corresponding to each preset track point can be determined based on the position information of each preset track point and the differential equation.
Further, the boundary constraints of each path parameter predicted value, speed parameter predicted value and motion control parameter predicted value are determined according to specific situations. The boundary constraint is used for limiting the space range of the optimization solution when the MPC optimization solution is carried out. Other expressions may be used instead of the boundary constraints described above, and other boundary constraints to be considered may be added.
The boundary constraints may be determined based on attributes of the vehicle itself and other constraints. For example, certain parameter values may be determined based on navigation information, such as track speed
Figure SMS_32
Not exceeding 120 km per hour and not below 60 km per hour, some parameters may be based on properties of the vehicle itself, such as +.>
Figure SMS_33
Is the front wheel angle of the vehicle and generally the front wheel angle of the vehicle is not more than 60 degrees at maximum, if the direction is added, then +. >
Figure SMS_34
Not exceeding 60 degrees and not falling below 0 degrees. If the direction is not added, then
Figure SMS_35
Not exceeding 60 degrees and not below-60 degrees.
Further, selecting several important parameters to establish an objective function, determining corresponding important parameters according to the current environment of the vehicle, for example, if a target vehicle exists in front of the current vehicle, then the objective function can be based on
Figure SMS_36
、/>
Figure SMS_37
、
Figure SMS_38
、/>
Figure SMS_39
And establishing a corresponding objective function:
Figure SMS_40
Figure SMS_41
Figure SMS_42
Figure SMS_43
Figure SMS_44
wherein the method comprises the steps of
Figure SMS_46
For the driving distance corresponding to the current track point, +.>
Figure SMS_48
For the variation of the track lateral deviation of the current track point, < >>
Figure SMS_51
For the difference between the current track point vehicle speed and the desired vehicle speed, +.>
Figure SMS_47
For a desired speed of the vehicle>
Figure SMS_49
Is the difference between the distance from the current track point to the target vehicle and the expected distance from the target vehicle to the vehicle>
Figure SMS_52
For the distance to the target vehicle when following a car, +.>
Figure SMS_53
For a desired distance from the target vehicle while following the vehicle. />
Figure SMS_45
For the current track point, the variation of the front wheel angle of the vehicle, < > is>
Figure SMS_50
Is the variation of the acceleration of the current track point. J-band different subscripts represent the corresponding objective functions of the different parameters. The function of the optimization objective function is to make the value of the objective function reach the extreme value of the needed solution as much as possible when performing MPC optimization solution, namely the so-called optimization objective. Other expression modes can be used for replacing the optimization objective function, and other optimization objective functions which need to be considered and correspond to parameters can be added, for example, the objective function which corresponds to the acceleration a can be added. Or the objective function of avoiding the obstacle is increased, namely, the closer the distance from the vehicle to the obstacle is, the larger the corresponding objective function value is, and other modes can be adopted for specific design calculation of the objective function of avoiding the obstacle. Compared with the horizontal-longitudinal split planning, the horizontal-longitudinal coupling planning is mainly different in that the optimization can be performed on the aspect of horizontal and longitudinal superposition two-dimensional space, the track of the obstacle avoidance can be better calculated, and the obstacle avoidance result of one of the horizontal dimension or the longitudinal dimension can be planned at one time only unlike the split planning.
In addition, each objective function has a corresponding weight coefficient, and the weight coefficient corresponding to each objective function may be the same or different, if added with weight, and the final overall objective function may be expressed as:
Figure SMS_54
w with different subscripts indicating different objective function weights,
Figure SMS_56
is->
Figure SMS_62
Weight of->
Figure SMS_66
Is that
Figure SMS_58
Weight of->
Figure SMS_59
Is->
Figure SMS_63
Weight of->
Figure SMS_67
Is->
Figure SMS_55
Weight of->
Figure SMS_60
Is->
Figure SMS_64
Is a weight of (2). The MPC solution needs to set the number of predicted steps, that is, the number of corresponding preset track points, for example, the number of predicted steps k=25 set in this example, and because the vehicle-machine system in this example is not provided with an instruction generating unit, the constructed model is utilized to perform optimization solution, so as to obtain a control target parameter value of 25 steps. In this example, the front wheel angle change rate +.>
Figure SMS_68
And vehicle acceleration change rate->
Figure SMS_57
Can also be converted after appropriate conversion, for example into front wheel corner +.>
Figure SMS_61
And acceleration of the vehicle->
Figure SMS_65
And then sent to the control unit.
It should be noted that, only the control target parameter value corresponding to the first preset track point may be output to the control unit, and after the control action of the control target parameter value corresponding to the first preset track point is executed, the path algorithm unit has already generated the control target parameter values corresponding to the plurality of preset track points in the next period, so that after the control unit executes the control action corresponding to the first preset track point in the present period, the control action corresponding to the first preset track point in the next period may be executed, thereby completing the rolling-type finite time domain optimization strategy.
Of course, when the vehicle-mounted system is provided with the control unit, the model constructed by the MPC may be used to perform optimization solution to obtain a 25-step speed target parameter value and a path target parameter value. The speed target parameter value and the path target parameter value are further sent to the control unit.
The control unit can convert the speed target parameter value and the path target parameter value corresponding to each preset track point into main information such as x coordinate, y coordinate, angle, curvature change rate, arc length, time and the like, and the main information can be obtained from the predicted state variable result through calculation and conversion, so that complete track information containing 26 track points can be finally obtained and is output to the control unit as a track planning result for track following and vehicle control.
In addition, in some special situations, other input parameters may occur, for example, the speed of the current road section may be limited by using speed limit signs on a foggy road section or some special road sections, so an image acquisition unit may be further disposed on the vehicle system, the image acquisition unit may perform an image of the vicinity of the vehicle during the running process according to a preset acquisition mode, and send the acquired image to the vehicle system, and the vehicle system identifies the object in the image in real time, where the preset acquisition mode may be to acquire the image once every preset time period, and the driving system determines the image including the speed limit signs as an acquired image. Therefore, the speed limit sign in the collected image can be identified, and the maximum speed per hour of the speed limit road section can be identified. And also identifies the distance between the speed limit sign and the current vehicle.
Further, a path parameter value, a speed parameter value, a control parameter value, a maximum speed per hour of a speed limit road section and a distance between a speed limit sign and a current vehicle corresponding to the current track point of the vehicle can be input into the vehicle-to-machine system.
In some embodiments, the path parameter value, the speed parameter value and the control parameter value are used as input data of a prediction model to obtain a path parameter predicted value and a speed parameter predicted value corresponding to each preset track point, at this time, the vehicle-to-machine system determines a first track point located in a speed-limiting road section based on the distance between the speed-limiting sign and the current vehicle and the position information of each preset track point, and obtains the speed corresponding to the track point, if the speed corresponding to the track point is greater than the maximum speed per hour of the speed-limiting road section, the speed corresponding to the track point is reduced, so that the vehicle can travel on the speed-limiting road section at the speed per hour meeting the requirement.
It will be appreciated that if deceleration is initiated only for the first track point on the speed-limiting road section, the acceleration of that track point will be too much, and the vehicle will be in a state of rapid deceleration, giving the driver a poor experience. Therefore, alternatively, the track point at which deceleration is started may be determined based on the speed corresponding to the track point and the maximum speed of the speed-limit road section, for example, a difference between the speed corresponding to the track point and the maximum speed of the speed-limit road section is 20km/h, and deceleration is started from the track point immediately before the track point, so that the vehicle speed at the track point may be reduced below the maximum speed by a relatively smooth deceleration process so that the vehicle may travel on the speed-limit road section at a speed-up speed that meets the requirements.
The embodiment of the application also provides a track control device. FIG. 3 is a schematic diagram of an embodiment of a document labeling apparatus according to the embodiments of the present application. As shown in fig. 3, the apparatus includes: an acquisition module 301 and a transmission module 302.
An obtaining module 301, configured to obtain a path parameter value, a speed parameter value, and a control parameter value corresponding to a current track point of a vehicle; taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to a preset track point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value; and obtaining target track planning information based on the path target parameter values and the speed target parameter values respectively corresponding to the plurality of preset track points.
And a sending module 302, configured to send the target track planning information to a control unit, so that the control unit performs track control on the vehicle according to the target track control information.
In some embodiments, the obtaining module 301 is specifically configured to use the path parameter value, the speed parameter value, and the control parameter value as input data of a first prediction model, so as to obtain a path parameter predicted value and a speed parameter predicted value corresponding to a preset track point by using the first prediction model;
Generating target difference information according to the first difference information of the path parameter predicted value and the path expected parameter value and the second difference information of the speed parameter predicted value and the speed expected parameter value;
taking the target difference information meeting the optimization condition as an optimization target, and adjusting the path parameter predicted value and the speed parameter predicted value to obtain a path target parameter value and a speed target parameter value
In some embodiments of the present invention,
the obtaining module 301 is further configured to use the path parameter value, the speed parameter value, and the control parameter value as input data of a second prediction model, so as to obtain a path parameter predicted value, a speed parameter predicted value, and a motion control parameter predicted value that respectively correspond to a plurality of preset track points by using the second prediction model;
the obtaining module 301 is further configured to generate, for any one of preset track points, target difference information according to the first difference information of the path parameter predicted value and the path expected parameter value, the second difference information of the speed parameter predicted value and the speed expected parameter value, and the third difference information of the control parameter predicted value and the control expected parameter value;
the obtaining module 301 is further configured to adjust the path parameter predicted value, the speed parameter predicted value, and the control parameter predicted value with the target difference information meeting an optimization condition as an optimization target, so as to obtain a control target parameter value;
The obtaining module 301 is further configured to obtain target track control information based on control target parameter values corresponding to a plurality of preset track points;
and the execution module is used for executing track control on the vehicle according to the target track control information.
In some embodiments, the obtaining module 301 is specifically configured to send the path target parameter value and the speed target parameter value to an instruction generating unit, where the instruction generating unit is configured to generate target trajectory planning information based on the path target parameter value and the speed target parameter value; and generating a corresponding control instruction based on the target track information, and sending the control instruction to a control unit, wherein the control unit is used for controlling the vehicle to perform corresponding track movement based on the control instruction.
In some embodiments, the obtaining module 301 is specifically configured to: taking the minimum value of the target difference information as an optimization target, and adjusting the path parameter predicted value and the speed parameter predicted value; and taking the path parameter predicted value after adjustment as a path target parameter value and taking the speed parameter predicted value after adjustment as a speed target parameter value when the target difference information reaches the minimum value.
In some embodiments, the path parameter values comprise at least one path sub-parameter value; the speed parameter values include at least one speed sub-parameter value; the path parameter predicted value comprises at least one path subparameter predicted value; the path parameter predicted value includes at least one path subparameter predicted value, and the obtaining module 301 is specifically configured to: calculating first difference information of the at least one path sub-parameter predicted value and the respective path sub-parameter expected value by using the objective function respectively corresponding to the at least one path sub-parameter value; calculating second difference information of the at least one speed subparameter predicted value and the respective speed subparameter expected value by utilizing the objective function respectively corresponding to the at least one speed subparameter; and summing the at least one first difference information and the at least one second difference information to obtain target difference information.
In some embodiments, the obtaining module 301 is further specifically configured to sum the at least one first difference information and the at least one second difference information to obtain the target difference information.
In some embodiments, the obtaining module 301 is further specifically configured to:
determining weight coefficients corresponding to the at least one first difference information and the at least one second difference information respectively;
Adjusting the at least one first difference information and the at least one second difference information based on a weight coefficient;
and summing the adjusted at least one first difference information and the at least one second difference information to obtain target difference information.
The track control device shown in fig. 3 may perform the track control method shown in the embodiment shown in fig. 1, and its implementation principle and technical effects are not repeated. The specific manner in which the respective modules and units of the track control device in the above embodiment perform operations has been described in detail in the embodiments related to the method, and will not be described in detail here.
Fig. 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application, where, as shown in fig. 4, a vehicle device is configured on the vehicle, and the vehicle device includes: a memory 401 and a controller 402.
The memory 401 is used for storing a computer program and may be configured to store other various data to support operations on the vehicle device. Examples of such data include instructions for any application or method operating on the vehicular device, contact data, phonebook data, messages, pictures, videos, and the like.
The Memory 401 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random-Access Memory (SRAM), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read Only Memory, EEPROM), erasable programmable Read-Only Memory (Electrical Programmable Read Only Memory, EPROM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
The vehicle apparatus further includes: and a display device 403. A controller 402 coupled with the memory 401 for executing a computer program in the memory 401 for:
acquiring a path parameter value, a speed parameter value and a control parameter value corresponding to a current track point of a vehicle;
taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to a preset track point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value;
obtaining target track planning information based on path target parameter values and the speed target parameter values respectively corresponding to a plurality of preset track points;
and sending the target track planning information to a control unit so that the control unit can execute track control on the vehicle according to the target track control information.
The display device 403 in fig. 4 described above includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation.
The audio component 404 of fig. 4 above may be configured to output and/or input audio signals. For example, the audio component includes a Microphone (MIC) configured to receive external audio signals when the device in which the audio component is located is in an operational mode, such as a call mode, a recording mode, and a speech recognition mode. The received audio signal may be further stored in a memory or transmitted via a communication component. In some embodiments, the audio assembly further comprises a speaker for outputting audio signals.
Further, as shown in fig. 4, the vehicle apparatus further includes: communication component 405, power supply component 406, and the like. Only some of the components are schematically shown in fig. 4, which does not mean that the vehicle device only comprises the components shown in fig. 4.
The communication component 405 of fig. 4 described above is configured to facilitate wired or wireless communication between the device in which the communication component is located and other devices. The device in which the communication component is located may access a wireless network based on a communication standard, such as WiFi,2G, 3G, 4G, or 5G, or a combination thereof. In one exemplary embodiment, the communication component may be implemented based on near field communication (Near Field Communication, NFC) technology, radio frequency identification (Radio Frequency Identification, RFID) technology, infrared data association (Infrared Data Association, irDA) technology, ultra Wideband (UWB) technology, bluetooth technology, and other technologies.
Wherein the power supply assembly 406 provides power to various components of the device in which the power supply assembly is located. The power components may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the devices in which the power components are located.
Accordingly, the present application further provides a computer readable storage medium storing a computer program, where the computer program is capable of implementing the steps in the method embodiment of fig. 1.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims (10)

1. A track control method, characterized by comprising:
obtaining a path parameter value, a speed parameter value and a control parameter value corresponding to a current track point of a vehicle, wherein the path parameter value comprises at least one of a track transverse deviation, a track course angle deviation and a wheel front wheel corner, the speed parameter value comprises at least one of current speed and acceleration, and the control parameter comprises any one of a steering wheel change rate and an acceleration change rate;
taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to a preset track point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value, wherein the path target parameter value and the speed target parameter value are respectively an adjusted path parameter predicted value and a speed parameter predicted value when difference information between the path expected parameter value and the speed expected parameter value accords with an optimization condition;
obtaining target track planning information based on path target parameter values and the speed target parameter values respectively corresponding to a plurality of preset track points;
And sending the target track planning information to a control unit so that the control unit can execute track control on the vehicle according to the target track control information.
2. The method according to claim 1, wherein the step of using the path parameter value, the speed parameter value, and the control parameter value as input data of a first prediction model to adjust a path parameter predicted value and a speed parameter predicted value corresponding to a preset trajectory point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value includes:
taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, so as to obtain a path parameter predicted value and a speed parameter predicted value corresponding to a preset track point by using the first prediction model;
generating target difference information according to the first difference information of the path parameter predicted value and the path expected parameter value and the second difference information of the speed parameter predicted value and the speed expected parameter value;
and taking the target difference information meeting the optimization condition as an optimization target, and adjusting the path parameter predicted value and the speed parameter predicted value to obtain a path target parameter value and a speed target parameter value.
3. The method according to claim 1, wherein the method further comprises:
taking the path parameter value, the speed parameter value and the control parameter value as input data of a second prediction model, so as to obtain path parameter predicted values, speed parameter predicted values and motion control parameter predicted values respectively corresponding to a plurality of preset track points by using the second prediction model;
generating target difference information according to the first difference information of the path parameter predicted value and the path expected parameter value, the second difference information of the speed parameter predicted value and the speed expected parameter value and the third difference information of the control parameter predicted value and the control expected parameter value aiming at any preset track point;
taking the target difference information meeting an optimization condition as an optimization target, and adjusting the path parameter predicted value, the speed parameter predicted value and the control parameter predicted value to obtain a control target parameter value;
obtaining target track control information based on control target parameter values corresponding to a plurality of preset track points;
and executing track control on the vehicle according to the target track control information.
4. The method according to claim 1, wherein the obtaining the target trajectory planning information based on the path target parameter values and the speed target parameter values respectively corresponding to the plurality of preset trajectory points includes:
Transmitting the path target parameter value and the speed target parameter value to an instruction generating unit, wherein the instruction generating unit is used for generating target track planning information based on the path target parameter value and the speed target parameter value; and generating a corresponding control instruction based on the target track information, and sending the control instruction to a control unit, wherein the control unit is used for controlling the vehicle to perform corresponding track movement based on the control instruction.
5. The method of claim 2, wherein adjusting the path parameter predictor and the speed parameter predictor to obtain a path target parameter value and a speed target parameter value with the target difference information meeting an optimization condition as an optimization target comprises:
taking the minimum value of the target difference information as an optimization target, and adjusting the path parameter predicted value and the speed parameter predicted value;
and taking the path parameter predicted value after adjustment as a path target parameter value and taking the speed parameter predicted value after adjustment as a speed target parameter value when the target difference information reaches the minimum value.
6. The method of claim 2, wherein the path parameter values comprise at least one path sub-parameter value; the speed parameter values include at least one speed sub-parameter value; the path parameter predicted value comprises at least one path subparameter predicted value; the path parameter predicted value includes at least one path subparameter predicted value, and generating the target difference information according to the first difference information of the path parameter predicted value and the path parameter expected value and the second difference information of the speed parameter predicted value and the speed parameter expected value includes:
Calculating first difference information of the at least one path sub-parameter predicted value and the respective path sub-parameter expected value by using the objective function respectively corresponding to the at least one path sub-parameter value;
calculating second difference information of the at least one speed subparameter predicted value and the respective speed subparameter expected value by utilizing the objective function respectively corresponding to the at least one speed subparameter;
and summing the at least one first difference information and the at least one second difference information to obtain target difference information.
7. The method of claim 6, wherein summing the at least one first difference information with the at least one second difference information to obtain the target difference information comprises:
determining weight coefficients corresponding to the at least one first difference information and the at least one second difference information respectively;
adjusting the at least one first difference information and the at least one second difference information based on the weight coefficient;
and summing the adjusted at least one first difference information and the at least one second difference information to obtain target difference information.
8. A trajectory planning device, the device comprising:
The acquisition module is used for acquiring a path parameter value, a speed parameter value and a control parameter value corresponding to the current track point of the vehicle; taking the path parameter value, the speed parameter value and the control parameter value as input data of a first prediction model, and adjusting the path parameter predicted value and the speed parameter predicted value corresponding to a preset track point obtained by the first prediction model to obtain a path target parameter value and a speed target parameter value; obtaining target track planning information based on path target parameter values and speed target parameter values respectively corresponding to a plurality of preset track points, wherein the path parameter values comprise at least one of track transverse deviation, track course angle deviation and wheel front wheel rotation angle, the speed parameter values comprise at least one of current speed and acceleration, the control parameters comprise any one of steering wheel change rate and acceleration change rate, and the path target parameter values and the speed target parameter values are respectively adjusted path parameter predicted values and speed parameter predicted values when difference information between path expected parameter values and speed expected parameter values accords with optimization conditions;
and the sending module is used for sending the target track planning information to the control unit so that the control unit can execute track control on the vehicle according to the target track control information.
9. A vehicle, characterized by comprising: a trajectory planning device as claimed in claim 8.
10. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed, is capable of realizing the steps in the trajectory control method as claimed in any one of claims 1 to 7.
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