CN118068729A - Method, device, equipment and medium for updating and adjusting transverse and longitudinal control parameters in vehicle parking process - Google Patents

Method, device, equipment and medium for updating and adjusting transverse and longitudinal control parameters in vehicle parking process Download PDF

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Publication number
CN118068729A
CN118068729A CN202410202195.1A CN202410202195A CN118068729A CN 118068729 A CN118068729 A CN 118068729A CN 202410202195 A CN202410202195 A CN 202410202195A CN 118068729 A CN118068729 A CN 118068729A
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vehicle
steering wheel
wheel angle
speed
simulated
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余忠伟
张绪胜
利航
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Huizhou Desay SV Intelligent Transport Technology Research Institute Co Ltd
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Huizhou Desay SV Intelligent Transport Technology Research Institute Co Ltd
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Priority to CN202410202195.1A priority Critical patent/CN118068729A/en
Publication of CN118068729A publication Critical patent/CN118068729A/en
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The invention discloses a method, a device, equipment and a medium for updating and adjusting transverse and longitudinal control parameters in a vehicle parking process. The method comprises the following steps: determining a speed command signal and a steering wheel angle command signal of a desired given vehicle based on the data deviation between the acquired planning state data and simulation state data; determining a target steering wheel angle and a target vehicle speed of the vehicle based on the gaussian regression fit model, the simulation state data, the speed command signal and the steering wheel angle command signal; and determining the pedal depth and steering wheel angle in the dynamics simulation software to be input next time according to the preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle so as to adjust the transverse and longitudinal control parameters of the vehicle parking. According to the embodiment of the invention, through the technical scheme, the dynamic real response simulation of the actual vehicle can be realized, the dependence on actual vehicle resources is reduced, the waste of resources and time cost is avoided, and the parking control is more accurate.

Description

Method, device, equipment and medium for updating and adjusting transverse and longitudinal control parameters in vehicle parking process
Technical Field
The invention relates to the technical field of vehicle driving safety, in particular to a method for updating and adjusting transverse and longitudinal control parameters in a vehicle parking process.
Background
The control of the intelligent vehicle parking transverse and longitudinal directions depends on control methods MPC, LQR, PID and the like, key parameters in the methods greatly influence the vehicle control effect, so that the updating and adjustment of the key parameters of the control methods are important for intelligent vehicle parking development; in the prior art, the update adjustment of the key parameters of the intelligent vehicle parking transverse and longitudinal control is usually two ways, the first way is that engineering personnel continuously update and adjust the key parameters directly on an actual vehicle according to the control effect and is seriously dependent on a large number of actual vehicle resources, the second way is that complex parameters (such as cornering stiffness, steering system characteristic parameters, driving system characteristic parameters and the like) of the actual vehicle are obtained through a large number of third-party tests, then a simulation dynamics model of the actual vehicle is established according to the parameters, simulation tests are carried out on the basis of the simulation dynamics model, and then the vehicle control parameters are updated and adjusted.
Disclosure of Invention
In view of the above, the invention provides a method, a device, equipment and a medium for updating and adjusting transverse and longitudinal control parameters in the vehicle parking process, which can realize the dynamic real response simulation of an actual vehicle, enable multiple engineering personnel to complete the updating and adjustment of the vehicle control parameters at the PC end at the same time, obtain approximate vehicle control parameters, reduce the dependence of actual vehicle resources, avoid wasting human resources and time cost, and enable parking control to be more accurate.
According to an aspect of the present invention, an embodiment of the present invention provides a method for updating and adjusting a transverse and longitudinal control parameter in a vehicle parking process, where the method includes:
Acquiring simulation state data of a vehicle and planning state data of the vehicle;
Determining a speed command signal and a steering wheel angle command signal corresponding to the vehicle which are required to be given based on the data deviation between the planning state data and the simulation state data;
Determining a target steering wheel angle and a target vehicle speed of the vehicle based on a pre-trained gaussian regression fit model, the simulation state data, the speed command signal and the steering wheel angle command signal;
And determining the pedal depth and steering wheel angle in the dynamics simulation software to be input next time according to a preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulated state data so as to adjust transverse and longitudinal control parameters of vehicle parking.
According to another aspect of the present invention, an embodiment of the present invention further provides a device for updating and adjusting a transverse and longitudinal control parameter in a vehicle parking process, where the device includes:
the data acquisition module is used for acquiring simulation state data of the vehicle and planning state data of the vehicle;
The signal determining module is used for determining a speed command signal and a steering wheel angle command signal corresponding to the vehicle which are required to be given on the basis of the data deviation between the planning state data and the simulation state data;
The target information determining module is used for determining a target steering wheel angle and a target vehicle speed of the vehicle based on a pre-trained Gaussian regression fitting model, the simulation state data, the speed command signal and the steering wheel angle command signal;
And the adjusting module is used for determining the pedal depth and the steering wheel angle in the simulation of the dynamics simulation software to be input next time according to a preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulation state data so as to adjust the transverse and longitudinal control parameters of the vehicle parking.
According to another aspect of the present invention, an embodiment of the present invention further provides an electronic device, including:
at least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the method for updating and adjusting the longitudinal and transverse control parameters during the parking of the vehicle according to any of the embodiments of the present invention.
According to another aspect of the present invention, an embodiment of the present invention further provides a computer readable storage medium, where the computer readable storage medium stores computer instructions, where the computer instructions are configured to enable a processor to implement the method for updating and adjusting a transverse and longitudinal control parameter in a vehicle parking process according to any one of the embodiments of the present invention when the processor executes the method.
According to the technical scheme, the speed command signal and the steering wheel angle command signal of the vehicle are determined according to the simulation state data of the vehicle and the data deviation between the planning state data of the vehicle; then determining a target steering wheel angle and a target vehicle speed of the vehicle based on the Gaussian regression fit model, the simulation state data, the speed command signal and the steering wheel angle command signal; the pedal depth and steering wheel angle in the next input dynamics simulation software simulation are determined according to the preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle so as to adjust the transverse and longitudinal control parameters of vehicle parking, realize the dynamics real response simulation of the actual vehicle, reduce the dependence of actual vehicle resources, avoid wasting human resources and time cost, and enable parking control to be more accurate.
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 or to delineate 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 flowchart of a method for updating and adjusting parameters of a horizontal/vertical control in a parking process of a vehicle according to an embodiment of the present invention;
FIG. 2 is a flowchart of another method for updating and adjusting parameters of lateral and longitudinal control during parking of a vehicle according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a method for updating and adjusting parameters of a horizontal/vertical control during parking of a vehicle according to another embodiment of the present invention;
FIG. 4 is a block diagram illustrating a device for updating and adjusting parameters of a vehicle in a horizontal/vertical direction during parking according to an embodiment of the present invention;
Fig. 5 is a schematic structural diagram of an electronic device 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. 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.
In an embodiment, fig. 1 is a flowchart of a method for updating and adjusting a transverse and longitudinal control parameter in a vehicle parking process according to an embodiment of the present invention, where the method may be performed by a transverse and longitudinal control parameter updating and adjusting device in a vehicle parking process, where the transverse and longitudinal control parameter updating and adjusting device in a vehicle parking process may be implemented in hardware and/or software, and where the transverse and longitudinal control parameter updating and adjusting device in a vehicle parking process may be configured in an electronic device.
As shown in fig. 1, in the embodiment, a method for updating and adjusting a transverse and longitudinal control parameter in a vehicle parking process includes the following specific steps:
S110, acquiring simulation state data of the vehicle and planning state data of the vehicle.
The simulation state data may be understood as vehicle simulation data obtained by a dynamic simulation of an actual vehicle, which simulation state data may characterize the actual state data of the vehicle. The planning state data refers to planning data which is planned and generated by information data collected by the vehicle in the early stage.
In some embodiments, the simulated state data of the vehicle may include, but is not limited to, simulated vehicle positioning, simulated vehicle speed, simulated acceleration and deceleration strength, and simulated vehicle steering wheel angle; the vehicle's planned state data may include, but is not limited to, vehicle planned trajectory, vehicle planned speed, and vehicle planned steering wheel angle.
In this embodiment, the simulation may be performed by the dynamics simulation software to obtain a simulated vehicle positioning, a simulated vehicle speed, a simulated acceleration/deceleration strength, and a simulated vehicle steering wheel angle of the vehicle, and a vehicle planning track, a vehicle planning speed, and a vehicle planning steering wheel angle of the vehicle may be obtained by a planning module in the vehicle, which is not limited herein. The dynamics simulation software in this embodiment may include, but is not limited to, carsim, carmaker, etc. simulation software.
S120, determining a speed command signal and a steering wheel angle command signal corresponding to the given vehicle based on the data deviation between the planning state data and the simulation state data.
Wherein the speed command signal may be understood as requiring a given speed value. The steering wheel angle command signal may be understood as requiring a given steering wheel angle value.
In this embodiment, the speed command signal and the steering wheel angle command signal corresponding to the vehicle required by the user may be determined by the data deviation between the planning state data and the simulation state data; specifically, the deviation between the simulated vehicle positioning, the simulated vehicle speed, the simulated acceleration and deceleration strength and the simulated vehicle steering wheel angle in the simulated state data and the vehicle planning track, the vehicle planning speed and the vehicle planning steering wheel angle in the planning state data can be determined by a method in the prior art, and the given speed command signal and the steering wheel angle command signal are determined based on the data deviations; in some embodiments, the speed command signal and the steering wheel angle command signal that are required in this embodiment may be determined in other manners, and this embodiment is not limited herein; the data bias in this embodiment at least includes: vehicle position deviation, vehicle speed deviation, and steering wheel angle deviation.
S130, determining a target steering wheel angle and a target vehicle speed of the vehicle based on a pre-trained Gaussian regression fit model, simulation state data, a speed command signal and a steering wheel angle command signal.
The target steering wheel angle can be understood as the steering wheel angle which needs to be input into the PID controller next time; the target vehicle speed may be understood as the vehicle speed that needs to be input to the PID controller next time.
In this embodiment, the pre-trained gaussian regression fit model includes: a first pre-trained gaussian regression fit model and a second pre-trained gaussian regression fit model; in one embodiment, the training of the first gaussian regression fit model includes: obtaining a first training sample set, wherein the first training sample set comprises: real vehicle data of different vehicle speeds and a given speed command signal; and inputting the vehicle age speed and a given speed command signal in the real vehicle data into a first Gaussian regression fit model to perform first fitting, and recognizing that the fitting is optimal under the condition that the deviation of the first fitting is smaller than a first preset deviation threshold value, so as to obtain a trained first Gaussian regression model.
In one embodiment, the training of the second gaussian regression fit model includes: obtaining a second training sample set, wherein the second training sample set comprises: real vehicle data of different steering wheel angles and given steering wheel angle command signals; and inputting the steering wheel angle in the real vehicle data and the given steering wheel angle instruction signal into the second Gaussian regression fit model to perform second fit, and recognizing that the fit is optimal under the condition that the second fit reaches a deviation smaller than a second preset deviation threshold value, so as to obtain a trained second Gaussian regression model.
In this embodiment, the first training sample set is obtained, where the first training sample set includes: real vehicle data of different vehicle speeds and a given speed command signal; inputting the vehicle age speed in the real vehicle data and a given speed command signal into a first Gaussian regression fit model to perform first fitting, and recognizing that the fitting is optimal under the condition that the deviation of the first fitting is smaller than a first preset deviation threshold value so as to obtain a trained first Gaussian regression model; and by obtaining a second training sample set, wherein the second training sample set comprises: real vehicle data of different steering wheel angles and given steering wheel angle command signals; and inputting steering wheel angles and given steering wheel angle instruction signals in the real vehicle data into a second Gaussian regression fitting model to carry out second fitting, and recognizing that the fitting is optimal under the condition that the deviation of the second fitting is smaller than a second preset deviation threshold value so as to obtain a trained second Gaussian regression model. Illustratively, the gaussian process regression fit model is built dependent on a certain amount of real vehicle data. And collecting the time T1 consumed by the speed change unit value of the vehicle under the condition that the vehicle speed (0, 1,2, 3, 4,5 km/h), the steering wheel rotation angle (-450, -440 …, …, 450 degrees) and the speed command signals (0, 1,2, 3, 4,5 km/h) are determined and combined one by one. And collecting the time T2 consumed by the steering wheel angle change unit value under the condition that the vehicle speeds (0, 1,2, 3, 4 and 5 km/h), the steering wheel angles (-450, -440 …, …, 450 degrees) and the steering wheel angle command signals (-450, -440 …, 0 …, 440, 450 degrees) are determined and combined one by one.
In this embodiment, the gaussian process regression fit model is trained with a real vehicle speed, a steering wheel angle, and a speed command as input, with a speed change time consumption gaussian model with a speed change unit consumption time as output, with a real vehicle speed, a steering wheel angle, and a steering wheel angle command as input, and with a speed change unit consumption time as output.
In the embodiment, the target speed of the vehicle can be determined by a pre-trained gaussian regression fit model and a simulated vehicle speed and speed command signal in simulated state data, and the target steering wheel angle of the vehicle can be determined by a pre-trained gaussian regression fit model and a simulated vehicle steering wheel angle and steering wheel angle command signal in simulated state data; specifically, the required given speed command signal and the simulated vehicle speed in the simulated state data can be input into a first Gaussian regression fit model trained in advance to obtain the speed change unit consumption time; inputting the required given steering wheel angle instruction signal and the simulated vehicle steering wheel angle in the simulated state data into a pre-trained Gaussian regression fitting model to obtain the steering wheel angle change unit quantity consumption time; on the basis, the speed change unit consumption time and the steering wheel angle change unit consumption time pass, the target speed of the vehicle is determined according to the comparison of the simulated vehicle speed and the speed command signal, and the target steering wheel angle of the vehicle is determined according to the comparison of the simulated vehicle steering wheel angle and the steering wheel angle command signal.
And S140, determining the pedal depth and the steering wheel angle in the simulation of the dynamics simulation software to be input next time according to the preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulation state data, so as to adjust the transverse and longitudinal control parameters of the vehicle parking.
The preset PID controller is a PID controller in the prior art. The pedal depth may be indicative of the input vehicle speed.
In this embodiment, the speed deviation between the target speed and the simulated vehicle speed of the vehicle and the angle deviation between the target steering wheel angle and the simulated steering wheel angle of the vehicle may be determined by presetting the PID controller, and the pedal depth and the steering wheel angle in the simulation of the dynamics simulation software are determined based on the speed deviation and the angle deviation, so that the simulated vehicle speed in the simulated vehicle state data is closer to the target speed, and the simulated steering wheel angle and the target angle in the simulated vehicle state data are closer to each other, so as to realize adjustment of the transverse and longitudinal control parameters of the vehicle parking. It can be understood that the PID method is used for outputting the opening degree of an acceleration pedal and the opening degree of a brake pedal, and the steering wheel turns to dynamics simulation software, so that the real vehicle determines a speed value after the vehicle speed in the dynamics simulation software is followed by the T1 time in real time, and the real vehicle steering wheel turns value after the T2 time in the dynamics simulation software is followed by the vehicle turning in real time, thereby realizing the completion of the effective response characteristic to the real vehicle dynamics at the PC end Simulation .
According to the technical scheme, the speed command signal and the steering wheel angle command signal of the vehicle are determined according to the simulation state data of the vehicle and the data deviation between the planning state data of the vehicle; then determining a target steering wheel angle and a target vehicle speed of the vehicle based on the Gaussian regression fit model, the simulation state data, the speed command signal and the steering wheel angle command signal; the pedal depth and steering wheel angle in the next input dynamics simulation software simulation are determined according to the preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle so as to adjust the transverse and longitudinal control parameters of the vehicle parking, and the dynamics real response simulation of the actual vehicle can be realized, so that multiple engineering personnel can finish the updating and adjustment of the vehicle control parameters at the PC end at the same time to obtain approximate vehicle control parameters, thereby reducing the dependence of actual vehicle resources, avoiding wasting human resources and time cost, and enabling the parking control to be more accurate.
In an embodiment, fig. 2 is a flowchart of another method for updating and adjusting a transverse and longitudinal control parameter in a parking process of a vehicle according to an embodiment of the present invention, where the method is based on the above embodiments, and the method includes obtaining simulation state data of the vehicle and planning state data of the vehicle; determining a speed command signal and a steering wheel angle command signal corresponding to a given vehicle based on the data deviation between the planning state data and the simulation state data; determining a target steering wheel angle and a target vehicle speed of the vehicle based on a pre-trained Gaussian regression fit model, simulation state data, a speed command signal and a steering wheel angle command signal, and determining the pedal depth and the steering wheel angle in the simulation of the dynamics simulation software to be further refined according to a preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulation state data.
As shown in fig. 2, the method for updating and adjusting the transverse and longitudinal control parameters in the vehicle parking process in this embodiment may specifically include the following steps:
S210, acquiring simulation state data of the vehicle obtained through simulation by using dynamics simulation software, and receiving planning state data of a planning module of the vehicle on the vehicle.
In the embodiment, the dynamics simulation software is used for simulating the related data generated by simulating the actual state of the vehicle so as to acquire the simulation state data of the vehicle simulated by the dynamics simulation software and receive the planning state data of the vehicle transmitted by the planning unit of the vehicle; wherein the simulated state data characterizes actual state data of the vehicle; the simulation state data includes: simulated vehicle positioning, simulated vehicle speed, simulated acceleration and deceleration strength and simulated vehicle steering wheel angle; the planning state data includes: vehicle planned trajectory, vehicle planned speed, and vehicle planned steering wheel angle.
S220, determining data deviation between planning state data and simulation state data according to a preset parking horizontal and vertical control algorithm; wherein, the data deviation at least comprises: vehicle position deviation, vehicle speed deviation, and steering wheel angle deviation.
The preset parking horizontal and vertical control algorithm is one control algorithm in the prior art, and the control algorithm may include, but is not limited to, model predictive control (Model Predictive Control, MPC) or linear quadratic regulator (linear quadratic regulator, LQR) or PID control algorithm or pure tracking algorithm.
In one embodiment, the data bias between the planning state data and the simulation state data may be determined according to any control algorithm in the prior art; wherein, the data deviation at least comprises: vehicle position deviation, vehicle speed deviation, and steering wheel angle deviation. It can be understood that the data included in the planning state data and the simulation state data are compared to obtain corresponding vehicle position deviation, vehicle speed deviation and steering wheel angle deviation.
S230, determining a required given speed command signal and a steering wheel angle command signal according to the data deviation.
In this embodiment, the speed command signal and the steering wheel angle command signal that need to be given may be determined according to the vehicle position deviation, the vehicle speed deviation, and the steering wheel angle deviation, which may be understood as values corresponding to the speed command signal and the steering wheel angle command signal that need to be input by the user are determined according to the data deviation.
S240, inputting the required given speed command signal and the simulated vehicle speed in the simulated state data into a first Gaussian regression fit model trained in advance to obtain a speed change unit consumption time T1, and taking the speed change unit consumption time T1 as a next speed delay time T1.
In this embodiment, the pre-trained gaussian regression fit model includes: a first pre-trained gaussian regression fit model and a second pre-trained gaussian regression fit model.
In this embodiment, the required given speed command signal and the simulated vehicle speed in the simulated state data may be input into a first gaussian regression fit model trained in advance to obtain a speed change unit consumption time T1, and the speed change unit consumption time T1 is taken as the next speed delay time T1.
S250, inputting the required given steering wheel angle instruction signal and the simulated vehicle steering wheel angle in the simulated state data into a pre-trained second Gaussian regression fit model to obtain steering wheel angle change unit quantity consumed time T2, and taking the steering wheel angle change unit quantity consumed time T2 as the next steering wheel angle delay time T2.
In this embodiment, the required given steering wheel angle command signal and the simulated vehicle steering wheel angle in the simulated state data may be input into a second gaussian regression fit model trained in advance, to obtain the steering wheel angle change unit consumption time T2, and the steering wheel angle change unit consumption time T2 is used as the next steering wheel angle delay time T2.
S260, delaying the next speed by a delay time T1, and determining the target speed of the vehicle according to the first comparison of the simulated vehicle speed and the speed command signal in the simulated state data.
In this embodiment, after the next speed delay time T1 is obtained, the next speed delay time T1 is delayed, and the target speed of the vehicle is determined according to the first comparison between the simulated vehicle speed and the speed command signal in the simulated state data, which can be understood that the gaussian regression model receives the speed command and the simulated speed of the vehicle dynamics simulation software, calculates the time T1 (e.g. 0.1 km/h) required by the speed command to change the unit value under the control of the speed command, and delays the time T1, thereby sending the target speed. Specifically, under the condition of delaying the next speed delay time T1, the target speed of the vehicle can be determined according to the comparison result of the simulated vehicle speed in the simulated state data and the speed command signal.
In one embodiment, delaying the next speed delay time T1 and determining the target speed of the vehicle based on a first comparison of the simulated vehicle speed and the speed command signal in the simulated status data includes:
in the case of the delay time T1 of the next speed, if the simulated vehicle speed in the simulated state data is smaller than the speed instruction signal, the target vehicle speed of the vehicle is: simulating the sum of the vehicle speed and the vehicle speed change unit value under the next speed delay time T1;
If the simulated vehicle speed in the simulated state data is greater than or equal to the speed command signal, the target vehicle speed of the vehicle is: the difference between the vehicle speed and the vehicle speed variation unit value at the next speed delay time T1 is simulated.
In the present embodiment, in the case of delaying the next speed delay time T1, if the simulated vehicle speed in the simulated state data is smaller than the speed instruction signal, the target vehicle speed of the vehicle is: simulating the sum of the vehicle speed and the vehicle speed change unit value under the next speed delay time T1; if the simulated vehicle speed in the simulated state data is greater than or equal to the speed command signal, the target vehicle speed of the vehicle is: the difference between the vehicle speed and the vehicle speed variation unit value at the next speed delay time T1 is simulated. It can be understood that if the current actual vehicle speed < speed command, the result of the current actual vehicle speed + the vehicle speed change unit value is the target vehicle speed; and if the current actual vehicle speed is greater than the speed command, the result of the current actual vehicle speed-vehicle speed change unit value is the target vehicle speed.
S270, delaying the next steering wheel angle delay time T2, and determining the target steering wheel angle of the vehicle according to the second comparison of the simulated vehicle steering wheel angle and the steering wheel angle command signal in the simulated state data of the vehicle.
In this embodiment, the next steering wheel angle delay time T2 is delayed, and the target steering wheel angle of the vehicle is determined according to the second comparison of the simulated vehicle steering wheel angle and the steering wheel angle command signal in the simulated state data of the vehicle, specifically, the target steering wheel angle of the vehicle can be determined by the comparison of the simulated vehicle steering wheel angle and the steering wheel angle command signal in the simulated state data.
In one embodiment, delaying the next steering wheel angle delay time T2 and determining the target steering wheel angle of the vehicle based on a second comparison of the simulated vehicle steering wheel angle and the steering wheel angle command signal in the simulated state data of the vehicle comprises:
under the condition of delaying the next steering wheel angle delay time T2, if the simulated vehicle steering wheel angle in the simulated state data is smaller than the steering wheel angle command signal, the target steering wheel angle of the vehicle is: simulating the sum of the steering wheel angle change unit value of the steering wheel angle of the vehicle and the steering wheel angle change unit value of the next steering wheel angle delay time T2;
If the simulated vehicle steering wheel angle in the simulated state data is greater than or equal to the steering wheel angle command signal, the target steering wheel angle of the vehicle is: the difference between the steering wheel angle of the simulated vehicle and the steering wheel angle change unit value of the next steering wheel angle delay time T2.
In this embodiment, in the case of delaying the next steering wheel angle delay time T2, if the simulated vehicle steering wheel angle in the simulated state data is smaller than the steering wheel angle command signal, the target steering wheel angle of the vehicle is: simulating the sum of the steering wheel angle change unit value of the steering wheel angle of the vehicle and the steering wheel angle change unit value of the next steering wheel angle delay time T2; if the simulated vehicle steering wheel angle in the simulated state data is greater than or equal to the steering wheel angle command signal, the target steering wheel angle of the vehicle is: the difference between the steering wheel angle of the simulated vehicle and the steering wheel angle change unit value of the next steering wheel angle delay time T2. It can be understood that, if the steering wheel angle < steering wheel angle command in the actual state data of the vehicle passes through the next steering wheel angle delay, the result of the steering wheel angle + steering wheel angle change unit value in the actual state data of the vehicle is the target steering wheel angle; if the steering wheel angle in the actual state data of the vehicle is > steering wheel angle command, the result of the steering wheel angle-steering wheel angle change unit value in the actual state data of the vehicle is the target steering wheel angle.
S280, inputting the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulated state data into a preset PID controller to obtain the vehicle speed deviation between the target vehicle speed and the simulated vehicle speed and the angle deviation between the target steering wheel angle and the simulated vehicle steering wheel angle.
In the embodiment, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulated state data are input into a preset PID controller, and the vehicle speed deviation between the target vehicle speed and the simulated vehicle speed and the steering angle deviation between the target steering wheel angle and the simulated vehicle steering wheel angle are obtained.
S290, determining the pedal depth and steering wheel angle in the simulation of the dynamics simulation software according to the vehicle speed deviation and the angle deviation, so that the simulated vehicle speed in the vehicle simulation state data is closer to the target vehicle speed, and the simulated vehicle steering wheel angle in the vehicle simulation state data is closer to the target angle, so as to adjust the transverse and longitudinal control parameters of vehicle parking.
In this embodiment, the pedal depth and steering wheel angle in the simulation of the dynamics simulation software are determined according to the vehicle speed deviation and the angle deviation, so that the simulated vehicle speed in the vehicle simulation state data is closer to the target vehicle speed, the simulated vehicle steering wheel angle in the vehicle simulation state data is closer to the target angle, and it can be understood that the actual vehicle determination speed value after the time of T1 is followed by the vehicle speed in the dynamics simulation software, and the actual vehicle steering wheel angle value after the time of T2 is followed by the vehicle angle in the dynamics simulation software.
According to the technical scheme of the embodiment of the invention, the required given speed command signal and the simulated vehicle speed in the simulated state data are input into a pre-trained first Gaussian regression fit model to obtain the speed change unit consumption time T1, the speed change unit consumption time T1 is taken as the next speed delay time T1, the required given steering wheel angle command signal and the simulated vehicle steering wheel angle in the simulated state data are input into a pre-trained second Gaussian regression fit model to obtain the steering wheel angle change unit consumption time T2, the steering wheel angle change unit consumption time T2 is taken as the next steering wheel angle delay time T2, the next speed delay time T1 is delayed, the target speed of the vehicle is determined according to the first comparison of the simulated vehicle speed and the speed command signal in the simulated state data, delaying the next steering wheel angle delay time T2, determining the target steering wheel angle of the vehicle according to the second comparison of the simulated vehicle steering wheel angle and the steering wheel angle command signal in the simulated state data of the vehicle, inputting the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulated state data into a preset PID controller to obtain the vehicle speed deviation between the target vehicle speed and the simulated vehicle speed and the steering wheel angle deviation between the target steering wheel angle and the simulated vehicle steering wheel angle, determining the pedal depth and the steering wheel angle in the simulation software of the next input dynamics according to the vehicle speed deviation and the steering wheel angle deviation so as to enable the simulated vehicle speed in the simulated state data of the vehicle to be closer to the target vehicle speed and the simulated vehicle steering wheel angle in the simulated state data of the vehicle to be closer to the target vehicle speed, the dynamic real response simulation of the actual vehicle can be realized at the PC end without a large amount of power system parameters of the actual vehicle and a large amount of actual vehicle resources, and the dynamic real response simulation of the actual vehicle is further realized, so that multiple engineering personnel can finish updating and adjusting the vehicle control parameters at the PC end at the same time to obtain approximate vehicle control parameters, thereby reducing the dependence of the actual vehicle resources, avoiding wasting human resources and time cost, and ensuring more accurate parking control.
In an embodiment, in order to better understand the method for updating and adjusting the transverse and longitudinal control parameters during the parking of the vehicle, fig. 3 is a schematic diagram of another method for updating and adjusting the transverse and longitudinal control parameters during the parking of the vehicle according to an embodiment of the present invention, and the specific steps include:
a1, starting parking, feeding back a vehicle state to a parking transverse and longitudinal control algorithm by vehicle dynamics simulation software, and receiving a planned path result;
a2, calculating the transverse deviation, the course deviation and the speed deviation of control points on a planned path according to the vehicle state, and calculating a speed instruction and a steering wheel angle instruction according to a corresponding control algorithm;
a3, the first Gaussian regression model receives a speed command and the simulation speed of vehicle dynamics simulation software, calculates the time T1 (such as 0.1 km/h) required by a speed change unit value under the control of the speed command under the current actual speed, delays the time T1, and sends out a target speed; if the current actual vehicle speed is less than the speed command, the result of the current actual vehicle speed plus the vehicle speed change unit value is the target vehicle speed; if the current actual vehicle speed is greater than the speed command, the result of the current actual vehicle speed-vehicle speed change unit value is the target vehicle speed;
The second Gaussian regression model receives a steering wheel angle instruction and a simulated steering wheel angle of vehicle dynamics simulation software, calculates the time T1 (such as 0.1 km/h) required by a steering wheel angle change unit value under the control of the steering wheel angle instruction under the current actual steering wheel angle, delays the time T1, and sends out a target steering wheel angle; if the current actual steering wheel angle is less than the steering wheel angle instruction, the current actual steering wheel angle plus the result of the steering wheel angle change unit value is the target steering wheel angle; if the current actual steering wheel angle is greater than the steering wheel angle instruction, the current actual steering wheel angle-steering wheel angle change unit value is the target steering wheel angle;
a4, after the target vehicle speed is sent out, the target vehicle speed and the actual vehicle speed (namely the simulation software vehicle speed) are converted into the opening degree of an accelerator brake pedal through PID operation, and the vehicle is controlled to track the target vehicle speed relatively perfectly; after the target steering wheel angle is sent out, the target steering wheel angle and the actual steering wheel angle (namely the steering wheel angle of simulation software) are converted into the opening degree of an accelerator brake pedal through PID operation, and the vehicle is controlled to relatively perfectly track the upper target steering wheel angle so as to adjust the transverse and longitudinal control parameters of the parking of the vehicle.
In the embodiment, a model containing the dynamic response characteristics of the real vehicle is established, and is embedded between a control algorithm and dynamic simulation software, so that the vehicle control parameters are updated and adjusted in the Matlab at the PC end rapidly, and the vehicle resource requirements are reduced. The real vehicle dynamic response characteristic model is realized by using a Gaussian model, specifically, a Gaussian process regression fitting model is used for calculating time T1 consumed by a vehicle speed change unit value and time T2 consumed by the steering wheel angle change unit value under the conditions of determining the vehicle speed, determining the steering wheel angle, determining a speed command signal and the steering wheel angle command signal, namely, the real vehicle speed becomes a determinable value after the time T1 at the current moment and the real vehicle steering wheel angle also becomes a determinable value after the time T2 at the current moment. Meanwhile, the PID method is used for outputting the opening degree of an acceleration pedal and the opening degree of a brake pedal in Matlab, the steering wheel turns to dynamics simulation software, the vehicle speed in the dynamics simulation software is enabled to follow the actual vehicle to determine the speed value after T1 time in real time, the vehicle turning in the dynamics simulation software is enabled to follow the actual vehicle steering wheel turning value after T2 time in real time, effective simulation of the dynamics response characteristic of the actual vehicle is achieved at the PC end, the pedal depth and the steering wheel turning in the dynamics simulation software are determined next time according to a preset PID controller, a target vehicle speed, the target steering wheel turning, the simulated vehicle speed and the simulated vehicle steering wheel angle, so that transverse and longitudinal control parameters of vehicle parking are adjusted, the resource dependence of multi-user multifunctional multi-parameter adjustment on a large number of actual vehicles is reduced, and rapid iteration of multiple users on the control parameters at the PC end is achieved.
In an embodiment, fig. 4 is a block diagram of a device for updating and adjusting a transverse and longitudinal control parameter in a vehicle parking process according to an embodiment of the present invention, where the device is applicable to a situation when the transverse and longitudinal control parameter is updated and adjusted in the vehicle parking process, and the device may be implemented by hardware/software. The method can be configured in the electronic equipment to realize the updating and adjusting method of the transverse and longitudinal control parameters in the vehicle parking process.
As shown in fig. 4, the apparatus includes: a data acquisition module 410, a signal determination module 420, a target information determination module 430, and an adjustment module 440.
The data acquisition module 410 is configured to acquire simulation state data of a vehicle and planning state data of the vehicle;
A signal determining module 420, configured to determine a speed command signal and a steering wheel angle command signal corresponding to the vehicle that need to be given, based on a data deviation between the planning state data and the simulation state data;
A target information determination module 430 for determining a target steering wheel angle and a target vehicle speed of the vehicle based on a pre-trained gaussian regression fit model, the simulation state data, the speed command signal, and the steering wheel angle command signal;
The adjusting module 440 is configured to determine a pedal depth and a steering wheel angle in the simulation of the dynamics simulation software to adjust the transverse and longitudinal control parameters of the vehicle parking according to the preset PID controller, the target vehicle speed, the target steering wheel angle, and the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulation state data.
According to the embodiment of the invention, the signal determining module determines a speed command signal and a steering wheel angle command signal of a vehicle to be given through data deviation between simulation state data of the vehicle and planning state data of the vehicle; the target information determining module is used for determining a target steering wheel angle and a target vehicle speed of the vehicle based on the Gaussian regression fitting model, the simulation state data, the speed command signal and the steering wheel angle command signal; the adjusting module is used for determining the pedal depth and steering wheel angle in the next input dynamics simulation software simulation according to the preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle so as to adjust the transverse and longitudinal control parameters of the vehicle parking, so that the dynamics real response simulation of the actual vehicle can be realized, multiple engineering personnel can finish the updating and adjustment of the vehicle control parameters at the PC end at the same time, the rough vehicle control parameters are obtained, the dependence of actual vehicle resources is reduced, the waste of human resources and time cost is avoided, and the parking control is more accurate.
In one embodiment, the data acquisition module 410 includes:
The data acquisition unit is used for acquiring simulation state data of the vehicle, which is obtained through simulation by using dynamics simulation software, and receiving planning state data of the vehicle by the planning module of the vehicle;
wherein the simulated state data characterizes actual state data of the vehicle; the simulation state data includes: simulated vehicle positioning, simulated vehicle speed, simulated acceleration and deceleration strength and simulated vehicle steering wheel angle;
The planning state data includes: vehicle planned trajectory, vehicle planned speed, and vehicle planned steering wheel angle.
In one embodiment, the signal determination module 420 includes:
The deviation determining unit is used for determining data deviation between the planning state data and the simulation state data according to a preset parking horizontal and vertical control algorithm; wherein the data bias comprises at least: vehicle position deviation, vehicle speed deviation and steering wheel angle deviation;
and the signal determining unit is used for determining a required given speed command signal and a steering wheel angle command signal according to the data deviation.
In one embodiment, the pre-trained gaussian regression fit model comprises: a first pre-trained gaussian regression fit model and a second pre-trained gaussian regression fit model;
Accordingly, the target information determining module 430 includes:
The speed delay determining unit is used for inputting the speed command signal required to be given and the simulated vehicle speed in the simulated state data into the first Gaussian regression fit model trained in advance to obtain speed change unit quantity consumption time T1, and taking the speed change unit quantity consumption time T1 as next speed delay time T1;
The steering wheel angle delay determining unit is used for inputting the required given steering wheel angle instruction signal and the simulated vehicle steering wheel angle in the simulated state data into the pre-trained second Gaussian regression fit model to obtain steering wheel steering angle change unit quantity consumption time T2, and taking the steering wheel steering angle change unit quantity consumption time T2 as next steering wheel steering angle delay time T2;
A target vehicle speed determining unit, configured to delay the next speed by a delay time T1, and determine a target vehicle speed of the vehicle according to a first comparison between the simulated vehicle speed in the simulated state data and the speed command signal;
And the target steering angle determining unit is used for delaying the next steering wheel angle delay time T2 and determining the target steering wheel angle of the vehicle according to the second comparison of the simulated vehicle steering wheel angle in the simulated state data of the vehicle and the steering wheel angle command signal.
In one embodiment, a target vehicle speed determination unit includes:
A first speed determining unit, configured to, in a case where the next speed delay time T1 is delayed, if the simulated vehicle speed in the simulated state data is less than the speed command signal, set a target vehicle speed of the vehicle to be: the sum of the simulated vehicle speed and the vehicle speed change unit value under the next speed delay time T1;
A second speed determining unit configured to, if the simulated vehicle speed in the simulated state data is greater than or equal to the speed instruction signal, target vehicle speed of the vehicle is: the difference between the simulated vehicle speed and the vehicle speed variation unit value at the next speed delay time T1.
In an embodiment, the target rotation angle determination unit includes:
A first steering angle determining unit, configured to, in a case of delaying the next steering wheel angle delay time T2, if the simulated vehicle steering wheel angle in the simulated state data is smaller than the steering wheel angle command signal, target steering wheel angle of the vehicle is: the sum of the steering wheel angle change unit value of the simulated vehicle steering wheel angle and the steering wheel angle change unit value of the next steering wheel angle delay time T2;
A second steering angle determining unit, configured to, if the simulated vehicle steering angle in the simulated state data is greater than or equal to the steering angle command signal, target steering angle of the vehicle is: and the difference between the simulated vehicle steering wheel angle and the steering wheel angle change unit value of the next steering wheel angle delay time T2.
In one embodiment, the adjustment module 440 includes:
The deviation determining unit is used for inputting the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulated state data into a preset PID controller to obtain the vehicle speed deviation between the target vehicle speed and the simulated vehicle speed and the angle deviation between the target steering wheel angle and the simulated vehicle steering wheel angle;
And the adjusting unit is used for determining the pedal depth and the steering wheel angle in the next simulation of the input dynamics simulation software according to the vehicle speed deviation and the angle deviation so as to enable the simulated vehicle speed in the vehicle simulation state data to be closer to the target vehicle speed, and the simulated vehicle steering wheel angle in the vehicle simulation state data to be closer to the target angle.
In an embodiment, the training of the first gaussian regression fit model includes:
obtaining a first training sample set, wherein the first training sample set comprises: real vehicle data of different vehicle speeds and a given speed command signal;
and inputting the vehicle age speed in the real vehicle data and the given speed command signal into the first Gaussian regression fit model to perform first fitting, and recognizing that the fitting is optimal under the condition that the deviation of the first fitting is smaller than a first preset deviation threshold value, so as to obtain a trained first Gaussian regression model.
In an embodiment, the training of the second gaussian regression fit model includes:
obtaining a second training sample set, wherein the second training sample set comprises: real vehicle data of different steering wheel angles and given steering wheel angle command signals;
And inputting the steering wheel angle in the real vehicle data and the given steering wheel angle instruction signal into the second Gaussian regression fit model to perform second fit, and recognizing that the fit is optimal under the condition that the second fit reaches a deviation smaller than a second preset deviation threshold value, so as to obtain a trained second Gaussian regression model.
The device for updating and adjusting the transverse and longitudinal control parameters in the vehicle parking process provided by the embodiment of the invention can execute the method for updating and adjusting the transverse and longitudinal control parameters in the vehicle parking process provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the executing method.
In an embodiment, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. The electronic device 10 is 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. 5, 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 method of updating and adjusting the lateral-longitudinal control parameters during vehicle parking.
In some embodiments, the method of updating and adjusting the lateral-longitudinal control parameter during vehicle parking 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 the RAM 13 and executed by the processor 11, one or more steps of the above-described transverse-longitudinal control parameter update adjustment method during parking of the vehicle may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the lateral-longitudinal control parameter update adjustment method during vehicle parking in any other suitable manner (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 general purpose computer, special purpose computer, or other programmable vehicle processor of a cross-machine direction control parameter update adjustment device during parking, such that the computer programs, when executed by the processor, cause the functions/operations specified in the flowchart and/or block diagram to be performed. 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 (12)

1. A method for updating and adjusting transverse and longitudinal control parameters in a vehicle parking process is characterized by comprising the following steps:
Acquiring simulation state data of a vehicle and planning state data of the vehicle;
Determining a speed command signal and a steering wheel angle command signal corresponding to the vehicle which are required to be given based on the data deviation between the planning state data and the simulation state data;
Determining a target steering wheel angle and a target vehicle speed of the vehicle based on a pre-trained gaussian regression fit model, the simulation state data, the speed command signal and the steering wheel angle command signal;
And determining the pedal depth and steering wheel angle in the dynamics simulation software to be input next time according to a preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulated state data so as to adjust transverse and longitudinal control parameters of vehicle parking.
2. The method of claim 1, wherein the obtaining simulation state data of a vehicle and planning state data of the vehicle comprises:
The simulation state data of the vehicle, which are obtained through simulation by using dynamics simulation software, are obtained, and the planning state data of the vehicle, which is obtained through simulation by using dynamics simulation software, are received by a planning module of the vehicle;
wherein the simulated state data characterizes actual state data of the vehicle; the simulation state data includes: simulated vehicle positioning, simulated vehicle speed, simulated acceleration and deceleration strength and simulated vehicle steering wheel angle;
The planning state data includes: vehicle planned trajectory, vehicle planned speed, and vehicle planned steering wheel angle.
3. The method of claim 1, wherein said determining a desired given speed command signal and steering wheel angle command signal for the vehicle based on a data deviation between the planning state data and the simulation state data comprises:
Determining data deviation between the planning state data and the simulation state data according to a preset parking horizontal and vertical control algorithm; wherein the data bias comprises at least: vehicle position deviation, vehicle speed deviation and steering wheel angle deviation;
And determining a required given speed command signal and a steering wheel angle command signal according to the data deviation.
4. The method of claim 1, wherein the pre-trained gaussian regression fit model comprises: a first pre-trained gaussian regression fit model and a second pre-trained gaussian regression fit model;
Accordingly, the determining the target steering wheel angle and the target vehicle speed of the vehicle based on the pre-trained gaussian regression fit model, the simulation state data, the speed command signal and the steering wheel angle command signal includes:
inputting the required given speed command signal and the simulated vehicle speed in the simulated state data into the pre-trained first Gaussian regression fit model to obtain speed change unit consumption time T1, and taking the speed change unit consumption time T1 as next speed delay time T1;
Inputting the required given steering wheel angle instruction signal and the simulated vehicle steering wheel angle in the simulated state data into the pre-trained second Gaussian regression fit model to obtain steering wheel angle change unit consumption time T2, and taking the steering wheel angle change unit consumption time T2 as next steering wheel angle delay time T2;
Delaying the next speed delay time T1, and determining a target speed of the vehicle according to first comparison of the simulated vehicle speed in the simulated state data and the speed command signal;
And delaying the next steering wheel angle delay time T2, and determining the target steering wheel angle of the vehicle according to the second comparison of the simulated vehicle steering wheel angle in the simulated state data of the vehicle and the steering wheel angle command signal.
5. The method of claim 4, wherein said delaying said next speed delay time T1 and determining a target vehicle speed of said vehicle based on a first comparison of a simulated vehicle speed in said simulated status data and said speed command signal comprises:
In the case of delaying the next speed delay time T1, if the simulated vehicle speed in the simulated state data is smaller than the speed command signal, the target vehicle speed of the vehicle is: the sum of the simulated vehicle speed and the vehicle speed change unit value under the next speed delay time T1;
If the simulated vehicle speed in the simulated state data is greater than or equal to the speed command signal, the target vehicle speed of the vehicle is: the difference between the simulated vehicle speed and the vehicle speed variation unit value at the next speed delay time T1.
6. The method of claim 4, wherein delaying the next steering wheel angle delay time T2 and determining the target steering wheel angle of the vehicle based on a second comparison of the simulated vehicle steering wheel angle and the steering wheel angle command signal in the simulated state data of the vehicle comprises:
Under the condition of delaying the next steering wheel angle delay time T2, if the simulated vehicle steering wheel angle in the simulated state data is smaller than the steering wheel angle command signal, the target steering wheel angle of the vehicle is: the sum of the steering wheel angle change unit value of the simulated vehicle steering wheel angle and the steering wheel angle change unit value of the next steering wheel angle delay time T2;
if the simulated vehicle steering wheel angle in the simulated state data is greater than or equal to the steering wheel angle command signal, the target steering wheel angle of the vehicle is: and the difference between the simulated vehicle steering wheel angle and the steering wheel angle change unit value of the next steering wheel angle delay time T2.
7. The method of claim 1, wherein determining the pedal depth and steering wheel angle for the next input into the dynamics simulation software based on a preset PID controller, the target vehicle speed, the target steering wheel angle, and a simulated vehicle speed and simulated vehicle steering wheel angle in the simulated state data, comprises:
inputting the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulated state data into a preset PID controller to obtain a vehicle speed deviation between the target vehicle speed and the simulated vehicle speed and a steering angle deviation between the target steering wheel angle and the simulated vehicle steering wheel angle;
And determining the pedal depth and the steering wheel angle in the simulation of the dynamics simulation software to be input next time according to the vehicle speed deviation and the angle deviation, so that the simulated vehicle speed in the vehicle simulation state data is closer to the target vehicle speed, and the simulated vehicle steering wheel angle in the vehicle simulation state data is closer to the target angle.
8. The method of claim 4, wherein the training of the first gaussian regression fit model comprises:
obtaining a first training sample set, wherein the first training sample set comprises: real vehicle data of different vehicle speeds and a given speed command signal;
and inputting the vehicle age speed in the real vehicle data and the given speed command signal into the first Gaussian regression fit model to perform first fitting, and recognizing that the fitting is optimal under the condition that the deviation of the first fitting is smaller than a first preset deviation threshold value, so as to obtain a trained first Gaussian regression model.
9. The method of claim 4, wherein the training of the second gaussian regression fit model comprises:
obtaining a second training sample set, wherein the second training sample set comprises: real vehicle data of different steering wheel angles and given steering wheel angle command signals;
And inputting the steering wheel angle in the real vehicle data and the given steering wheel angle instruction signal into the second Gaussian regression fit model to perform second fit, and recognizing that the fit is optimal under the condition that the second fit reaches a deviation smaller than a second preset deviation threshold value, so as to obtain a trained second Gaussian regression model.
10. A device for updating and adjusting transverse and longitudinal control parameters in a vehicle parking process, the device comprising:
the data acquisition module is used for acquiring simulation state data of the vehicle and planning state data of the vehicle;
The signal determining module is used for determining a speed command signal and a steering wheel angle command signal corresponding to the vehicle which are required to be given on the basis of the data deviation between the planning state data and the simulation state data;
The target information determining module is used for determining a target steering wheel angle and a target vehicle speed of the vehicle based on a pre-trained Gaussian regression fitting model, the simulation state data, the speed command signal and the steering wheel angle command signal;
And the adjusting module is used for determining the pedal depth and the steering wheel angle in the dynamics simulation software to be input next time according to a preset PID controller, the target vehicle speed, the target steering wheel angle, the simulated vehicle speed and the simulated vehicle steering wheel angle in the simulation state data so as to adjust the transverse and longitudinal control parameters of the vehicle parking.
11. An electronic device, the 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 enable the at least one processor to perform the method of updating and adjusting the lateral-longitudinal control parameter during parking of the vehicle of any one of claims 1-9.
12. A computer readable storage medium, characterized in that the computer readable storage medium stores computer instructions for causing a processor to implement the method for updating and adjusting a transverse and longitudinal control parameter during parking of a vehicle according to any one of claims 1 to 9 when executed.
CN202410202195.1A 2024-02-23 2024-02-23 Method, device, equipment and medium for updating and adjusting transverse and longitudinal control parameters in vehicle parking process Pending CN118068729A (en)

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