CN115366870A - PID (proportion integration differentiation) adjusting method and device for vehicle adaptive transverse control - Google Patents
PID (proportion integration differentiation) adjusting method and device for vehicle adaptive transverse control Download PDFInfo
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Abstract
The invention relates to a PID adjusting method and a device for vehicle self-adaptive transverse control, wherein the method comprises the following steps: acquiring the steering angle of a vehicle steering wheel and the holding torque of a driver in real time, and determining and/or calculating the change rate of dynamic parameters according to the steering angle and the holding torque; calculating a dynamic correction value according to the change rate of the dynamic parameter, and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient; determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; calculating a second correction term of the PID according to the gradient coefficient function; adjusting a lateral control output of the PID based on the plurality of first correction terms and the second correction term. According to the invention, the PID of the transverse control of the vehicle is corrected by the steering wheel angle of the vehicle and the holding torque of the driver and combining the slope smoothing strategy, so that the stability and the adaptability of the vehicle are improved.
Description
Technical Field
The invention belongs to the technical field of vehicle auxiliary driving, and particularly relates to a PID (proportion integration differentiation) adjusting method and device for vehicle self-adaptive transverse control.
Background
In actual driving operation, when a vehicle is in a relatively stable driving state such as high adhesion and low speed, a driver generally maintains the vehicle in the stable driving state mainly by sensing a state variable of the vehicle and adjusting a steering wheel. However, when the vehicle is traveling at an unstable state such as a high speed or a sudden steering, it is difficult for the driver to perform a correct steering adjustment based on the sensed vehicle state variable, which causes a risk. At this time, the vehicle tire slip angle, the yaw velocity, the lateral acceleration, the mass center slip angle and the like are selected as stability control parameters, and the yaw moment is generated through adjustment of vehicle braking, driving and the like, so that stable running of the automobile is guaranteed. The automobile lateral stability control system mainly takes parameters such as yaw velocity, mass center slip angle and the like as control indexes to keep the lateral stability of an automobile. In practice, however, the longitudinal dynamic response and the lateral dynamic response of the vehicle are simultaneously and mutually coupled, the dynamic characteristics are mainly determined by the longitudinal dynamic characteristics and the lateral dynamic characteristics of the tires, and the control effect is mainly realized by the control of the yaw moment generated by the control of the longitudinal force of the wheels.
In the ADAS (Advanced Driving Assistance System) function of the current mass production, the mainstream method is still based on the classical PID (proportional integral, differential, proportional integral and derivative) control, the classical PID control is to determine the proportional term, the integral term and the derivative term coefficient of the PID by means of calibration and table look-up, and then to calculate the sum of the three terms to eliminate the lateral deviation and realize the lateral adjustment.
However, the traditional PID control lateral control is easy to be disturbed by the change of the adjustment parameter to cause the unstable motion of the vehicle; on the other hand, the PID control does not consider the influence of the gradient, and has poor adaptability to the gradient.
Disclosure of Invention
In order to improve the problems of stability and adaptability of the PID lateral control of the vehicle, the invention provides a PID adjusting method of the vehicle adaptive lateral control in a first aspect, which comprises the following steps: acquiring the steering angle of a vehicle steering wheel and the holding torque of a driver in real time, and determining and/or calculating the change rate of dynamic parameters according to the steering angle and the holding torque; calculating a dynamic correction value according to the dynamic parameter change rate, and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient; determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; calculating a second correction term of the PID according to the gradient coefficient function; adjusting a lateral control output of the PID based on the plurality of first correction terms and the second correction term.
In some embodiments of the present invention, said calculating a dynamic correction value based on said dynamic parameter change rate and calculating a dynamic correction factor based thereon comprises: integrating the change rate of the dynamic parameter by the time integral parameter of PID control duration to obtain a dynamic correction value; and calculating a dynamic correction coefficient according to the dynamic correction value and the maximum driving distance within the PID parameter adjustment time.
Further, the dynamic correction coefficient is calculated by the following method:
EffetctiveTuningFactor
＝1/effectiveRange*e log(effectiveRange)*TuningFactor ，
wherein effective range is the maximum driving distance within the parameter adjustment time, and TuningFactor represents the dynamic correction value.
In some embodiments of the invention, the gradient coefficient function is calculated from gradual and abrupt time intervals during which the vehicle experiences a gradient: determining a sudden change time interval of the gradient coefficient function according to a preset tangent function; determining a gradient time interval of a gradient coefficient function according to a preset polynomial; and respectively calculating the numerical value of the gradient coefficient function according to the sudden change time interval and the gradual change time interval of the gradient coefficient function.
Further, the gradient coefficient function is expressed as:
wherein RampOvertime represents gradeDuration of slide treatment, t start Representing a linear processing time, a, b, c, d being the coefficients of a gradual curve of the gradient coefficient function.
In the above embodiment, the obtaining the steering angle of the steering wheel of the vehicle and the holding torque of the driver in real time, and determining and/or calculating the dynamic parameter change rate according to the steering angle and the holding torque of the driver comprises: acquiring the steering wheel angle data of the vehicle, and calculating an activity difference value according to the activity data and a preset target activity; judging whether the driver is in an intervention state according to the holding torque of the driver: if so, determining the dynamic parameter change rate according to the dynamic parameter value of the previous calculation period and a preset maximum dynamic parameter change rate; and if not, determining the dynamic parameter change rate according to the transverse distance deviation and the liveness difference value.
In a second aspect of the present invention, there is provided a PID adjusting apparatus for vehicle adaptive lateral control, comprising: the acquisition module is used for acquiring the steering angle of a vehicle steering wheel and the holding torque of a driver in real time and determining and/or calculating the change rate of the dynamic parameters according to the steering angle and the holding torque; the first correction module is used for calculating a dynamic correction value according to the dynamic parameter change rate and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient; the second correction module is used for determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; and the second correction term output module is used for adjusting the transverse control output of the PID based on the plurality of first correction terms and the second correction term.
Further, the first modification module includes: the integration unit is used for integrating the change rate of the dynamic parameter by the PID control continuous time integration parameter to obtain a dynamic correction value; and the calculating unit is used for calculating the dynamic correction coefficient according to the dynamic correction value and the maximum driving distance in the time adjusted by the PID parameter.
In a third aspect of the present invention, there is provided an electronic device comprising: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the PID adjustment method for vehicle adaptive lateral control of the present invention as provided in the first aspect.
In a fourth aspect of the present invention, there is provided a computer readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the PID adjusting method for vehicle adaptive lateral control provided in the first aspect of the present invention.
The invention has the beneficial effects that:
the disclosure provides a PID adjustment method for vehicle adaptive transverse control, which comprises the following steps: acquiring the steering angle of a vehicle steering wheel and the holding torque of a driver in real time, and determining and/or calculating the change rate of dynamic parameters according to the steering angle and the holding torque; calculating a dynamic correction value according to the change rate of the dynamic parameter, and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient; determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; calculating a second correction term of the PID according to the gradient coefficient function; adjusting a lateral control output of the PID based on the plurality of first correction terms and the second correction term. Therefore, the self-adaptive PID adjusting method is provided on the basis of the existing PID of the vehicle transverse control, and compensation and correction are carried out on the original system. The method comprises the steps of firstly calculating the liveness of a steering wheel of a vehicle, combining the intervention state of a driver and the transverse deviation between the intervention state and a lane line, and calculating the dynamic correction value of an adjustment parameter to obtain the correction coefficient values of proportion, integral and differential of PID. And a gradient smoothing strategy is designed by combining an integral term of the error, and PID control is compensated. The method can solve the problems of disturbance and instability caused by the change of the adjustment parameters in the transverse control, so that the system can quickly and stably reach the target set value while eliminating errors.
Drawings
FIG. 1 is a basic flow diagram of a PID tuning method of vehicle adaptive lateral control in some embodiments of the invention;
FIG. 2 is a detailed flow chart of a PID tuning method of adaptive lateral vehicle control in accordance with some embodiments of the invention;
FIG. 3 is a schematic illustration of slope coefficient function optimization in some embodiments of the invention;
FIG. 4 is a schematic diagram of a PID tuning arrangement for adaptive lateral control of a vehicle in accordance with certain embodiments of the invention;
fig. 5 is a schematic structural diagram of an electronic device in some embodiments of the invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1 or fig. 2, in a first aspect of the present invention, there is provided a PID adjusting method of vehicle adaptive lateral control, including: s100, acquiring the steering angle of a steering wheel of the vehicle and the holding torque of a driver in real time, and determining and/or calculating the change rate of dynamic parameters according to the steering angle and the holding torque; s200, calculating a dynamic correction value according to the dynamic parameter change rate, and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient; s300, determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; calculating a second correction term of the PID according to the gradient coefficient function; and S400, adjusting the transverse control output of the PID based on the plurality of first correction terms and the second correction term.
It will be appreciated that the slope is generally indicated by the letter X in terms of the ratio of the vertical height H and the horizontal width L of the slope surface, otherwise known as the slope ratio. Usually expressed in percentages. Namely: x = H/L × 100; the most common method for gradient, i.e. the percentage of the difference between the height of two points and their distance, is as follows: grade = (elevation difference/course) x100, when expressed in percentage, i.e.: i = h/l × 100%. The slope gradient of 3 percent means that the road rises (falls) 3 meters per 100 meters in the vertical direction; 1% means that the distance rises (falls) 1 meter vertically per 100 meters. The lateral control is mainly used for controlling a steering wheel of a vehicle, and tracking control is mainly performed according to information such as a path and a curvature output by upper-layer motion planning so as to reduce tracking errors. Meanwhile, the stability and the comfort of the vehicle running are ensured. The vehicle model can be classified into two types according to the difference in use of the lateral control, including: a model-free transverse control method is a transverse control method based on a model, and a PID transverse control method in the disclosure belongs to the transverse control method without the model.
In step S200 of some embodiments of the present invention, the calculating a dynamic correction value according to the dynamic parameter change rate and calculating a dynamic correction coefficient according to the dynamic correction value includes: integrating the change rate of the dynamic parameter by the time integral parameter of PID control duration to obtain a dynamic correction value; and calculating a dynamic correction coefficient according to the dynamic correction value and the maximum driving distance within the PID parameter adjustment time.
Further, the calculation is performed according to the dynamic correction coefficient by the following method:
EffetctiveTuningFactor
＝1/effectiveRange*e log(effectiveRange)*TuningFactor ，
wherein effective range is the maximum driving distance within the parameter adjustment time, and TuningFactor represents the dynamic correction value.
The steps only relate to the correction of dynamic coefficients, and in order to improve the adaptability to the gradient, the method designs a gradient smoothing Rampover strategy and performs dynamic proportional coefficient control on an integral term of the PID. In view of this, in step S300 of some embodiments of the invention, a gradient coefficient function is calculated from the gradual change time interval and the abrupt change time interval during which the vehicle experiences a gradient: s301, determining a mutation time interval of a gradient coefficient function according to a preset tangent function; s302, determining a gradient time interval of a gradient coefficient function according to a preset polynomial; and S303, respectively calculating the numerical value of the gradient coefficient function according to the sudden change time interval and the gradual change time interval of the gradient coefficient function.
Specifically, the slope smoothing strategy rampin is a tangent function, and the gain is fixed. The middle process is calculated according to the proportion, and the final rampout (gradual output) section is output according to the integral term. If the slope smoothing time is RampOvertime, the time for starting linear processing is t start . Therefore at t end In, can calculate the gradient systemThe number function is:
wherein, t start ＝0.8×RampOverTime，t end For calibration quantity, k = (f (t) start )-1)/(t start -RampOverTime)，m＝1-k×RampOverTime。
And then optimizing the strategy and performing transition processing on rampout. Assume that the rampout curve is: q (t) = at 3 +bt 2 +ct+d；
According to
The coefficients a, b, c, d of q (t) are calculated, i.e., q (x) is obtained.
The optimized gradient coefficient function is:
referring to fig. 3, if ramplovertime =3s, the starting linear processing time is:
t start =0.8 × ramplovertime =2.4s. Therefore at t end In the area of =5s, a dynamic scale factor graph of slope smoothing processing can be drawn.
Further, the gradient coefficient function is expressed as:
where RampOvertime represents the duration of the slope smoothing process, t start Representing a linear processing time, a, b, c, d being coefficients of a gradient curve of said gradient coefficient function.
It will be appreciated that the gradient coefficient function described above processes the gradient through piecewise functions, each of which is in turn characterized by a different smooth curve (continuous function). Optionally, a Sigmoid function, a tanh function, a Relu function, and a softmax function are used instead of the gradient coefficient function to implement the gradient smoothing strategy.
In step S100 of the foregoing embodiment, the obtaining the steering angle of the steering wheel and the holding torque of the driver in real time, and determining and/or calculating the dynamic parameter change rate according to the steering angle and the holding torque of the driver includes: s101, obtaining vehicle steering wheel corner data, and calculating an activity difference value according to the vehicle steering wheel corner data and a preset target activity; specifically, firstly, the steering wheel angle is processed by a high-pass filter and taking the mean square difference value within a delta t time period, then the dynamic activity steelpactivity of the steering wheel is taken out through table look-up mapping, and the difference with the target activity angleactivity target is obtained to obtain an activity difference value, namely: Δ steelpactivity = AngleActivityTarget-steeActivity, where angleActityTa-target is the normalized quantity.
S102, judging whether the driver is in an intervention state or not according to the holding torque of the driver: if yes, determining the dynamic parameter change rate according to the dynamic parameter value of the previous calculation period and a preset maximum dynamic parameter change rate; and if not, determining the dynamic parameter change rate according to the transverse distance deviation and the liveness difference value.
Specifically, whether the driver is in the intervention state is judged according to whether the hand moment value of the driver is larger than the intervention threshold value or not and continues for a period of time.
When a driver intervenes, fixing a dynamic parameter change rate value, wherein the value is determined according to whether the dynamic parameter value TuningFactorFeedBack of the last calculation period is larger than the maximum dynamic parameter change rate MaxTungrate, and if the TuningFactorFeedBack > MaxTungrate, the current dynamic parameter change rate Tungrate = -MaxTungrate; otherwise, dynamic parameter change rate TuningRate = maxturningrate. Among them, maxTuningRNA is the standard amount.
When the driver does not intervene, it is necessary to perform different processing according to the lateral distance Offset. When | Offset | > OffsetThreshold, the dynamic parameter change rate TuningRate =0.1 | Offset |;
otherwise, the dynamic parameter change rate is: tuningRate = GActivity Δ steeactin.
Based on steps S100-S300 of the above-described embodiments, in step S400 of some embodiments of the invention, the lateral control output of the PID is adjusted based on the plurality of first correction terms and the second correction term. Specifically, the PID parameters before correction are KP, KI, and KD, which are multiplied by the dynamic correction factor respectively, to obtain the corrected PID parameters. The corrected transverse control process is as follows:
A lat = IRamp × IPart + tuning factor × PID controller
Wherein IPart is obtained by one-dimensional table lookup according to the product of the error and the integral term, and the PID controller is a common classic controller. A. The lat Represents the lateral control output of the PID, which may be represented in terms of one or more parameters relating to lateral displacement, velocity, acceleration, torque, etc.
Example 2
Referring to fig. 4, in a second aspect of the present invention, there is provided a PID adjusting apparatus 1 for vehicle adaptive lateral control, comprising: the acquisition module 11 is used for acquiring the steering angle of a vehicle steering wheel and the holding torque of a driver in real time and determining and/or calculating the change rate of the dynamic parameters according to the steering angle and the holding torque; the first correction module 12 is used for calculating a dynamic correction value according to the dynamic parameter change rate and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient; the second correction module 13 is used for determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; and the second correction term output module is used for adjusting the transverse control output of the PID based on the plurality of first correction terms and the second correction term.
Further, the first modification module 12 includes: the integration unit is used for integrating the change rate of the dynamic parameter by the time integration parameter of PID control duration to obtain a dynamic correction value; and the calculating unit is used for calculating the dynamic correction coefficient according to the dynamic correction value and the maximum driving distance within the PID parameter adjusting time.
In some embodiments, any one of the intelligent driving vehicles based on the PID adjusting apparatus for vehicle adaptive lateral control provided by the second aspect of the present invention may include a sensor, an intelligent driving domain controller, an on-board communication device, a high-precision positioning device, a vehicle other controller, and a human-computer interaction system. Wherein the sensor comprises one or more of the following: at least one millimeter wave radar, at least one laser radar, at least one camera. The functions of the above-described modules included in the smart driving vehicle are explained in detail below:
millimeter wave radar: the radar works in millimeter wave band (millimeter wave) for detecting, is used for collecting the transmission time of a light beam reaching an obstacle and the speed of the light beam, and sends the collected data to the intelligent driving area controller; or after acquiring the transmission time of the light beam and the speed of the light beam, calculating data such as the distance and the speed of surrounding obstacles, and sending the calculated data to the intelligent driving area controller.
Laser radar: the radar system detects the position, speed and other characteristic quantities of a target by emitting laser beams. The working principle is to transmit a detection signal (laser beam) to a target, then compare the received signal (target echo) reflected from the target with the transmitted signal, and after appropriate processing, obtain the relevant data of the target, such as target distance, azimuth, height, speed, attitude, even shape and other parameters. In the application, the laser radar is used for collecting a signal reflected from an obstacle and sending the reflected signal and a transmitting signal to the intelligent driving area controller; or after the signal reflected from the obstacle is collected, the signal is compared with the transmitted signal, the data such as the distance, the speed and the like of the surrounding obstacle are obtained through processing, and the data obtained through processing are sent to the intelligent driving area controller.
A camera: the intelligent driving area controller is used for acquiring surrounding images or videos and sending the acquired images or videos to the intelligent driving area controller; when the camera is an intelligent camera, the camera can acquire images or videos, analyze the images or videos to obtain the speed, distance and the like of surrounding obstacles, and send the data obtained through analysis to the intelligent driving area controller.
High accuracy positioning apparatus: the method comprises the steps of collecting accurate position information (the error is less than 20 cm) of a current vehicle and Global Positioning System (GPS) time information corresponding to the accurate position information, and sending the collected information to an intelligent driving area controller. Wherein the high-precision positioning device can be a combined positioning system or a combined positioning module. The high-precision positioning device may include a Global Navigation Satellite System (GNSS), an Inertial Measurement Unit (IMU), and other devices and sensors. The global navigation satellite system can output global positioning information with a certain precision (for example, 5-10 Hz), the frequency of the inertial measurement unit is generally high (for example, 1000 Hz), and the high-precision positioning equipment can output high-frequency precise positioning information (generally requiring more than 200 Hz) by fusing the information of the inertial measurement unit and the global navigation satellite system.
Other controllers of the vehicle: and executing the control command of the intelligent driving area controller, and sending the relevant information of vehicle steering, gear, acceleration, deceleration and the like to the intelligent driving area controller.
A human-computer interaction system: the method provides an audio and video mode for message interaction between the intelligent vehicle and the driver, and can display the track of the vehicle and other vehicles by using the display screen.
Intelligent driving area controller: the intelligent driving area controller may be disposed in the vehicle, and is specifically implemented by a processor, where the processor includes a Central Processing Unit (CPU) or a device or module with a processing function. For example, the intelligent driving domain controller may be a vehicle Mobile Data Center (MDC). When an automatic driving function is executed, namely in an automatic driving mode, the intelligent driving domain controller sends track planning information to the vehicle-mounted communication equipment and sends self position information and predicted tracks of other surrounding vehicles to the human-computer interaction system; when a person drives a vehicle, namely in a manual driving mode, sensor information, the actual track of the vehicle and the predicted track of the person (which are predicted by a neural network or other Artificial Intelligence (AI) algorithms according to the sensor information and information transmitted by other controllers of the vehicle) are transmitted to the vehicle-mounted communication equipment, and the position information of the person and the predicted tracks of other vehicles around the person are transmitted to the man-machine interaction system.
An in-vehicle communication device: the device is communicated with other vehicles, receives other vehicle track prediction information (which can also be described as predicted track, track information and the like) and sends the other vehicle track prediction information to the intelligent driving area controller, and sends the track of the device to other surrounding vehicles; and communicating with the cloud, sending sensor information, positioning information and other controller information on the vehicle to the cloud, and receiving model parameters trained by the cloud. For example, the in-vehicle communication device may be a Telematics BOX (TBOX).
Example 3
Referring to fig. 5, in a third aspect of the present invention, there is provided an electronic apparatus comprising: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the PID adjustment method for vehicle adaptive lateral control of the present invention in the first aspect.
The electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following devices may be connected to the I/O interface 505 in general: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; a storage device 508 including, for example, a hard disk; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 5 may represent one device or may represent multiple devices as desired.
In particular, the processes described above with reference to the flow diagrams may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of embodiments of the present disclosure. It should be noted that the computer readable medium described in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, however, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer-readable medium carries one or more computer programs which, when executed by the electronic device, cause the electronic device to:
computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, python, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A PID adjustment method for vehicle adaptive lateral control, characterized by comprising:
acquiring the steering angle of a vehicle steering wheel and the holding torque of a driver in real time, and determining and/or calculating the change rate of dynamic parameters according to the steering angle and the holding torque;
calculating a dynamic correction value according to the change rate of the dynamic parameter, and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient;
determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; calculating a second correction term of the PID according to the gradient coefficient function;
adjusting a lateral control output of the PID based on the plurality of first correction terms and the second correction term.
2. The PID adjusting method of adaptive lateral control of a vehicle according to claim 1, wherein the calculating a dynamic correction value according to the dynamic parameter change rate and calculating a dynamic correction coefficient according thereto includes:
integrating the change rate of the dynamic parameter by the time integral parameter of PID control duration to obtain a dynamic correction value;
and calculating a dynamic correction coefficient according to the dynamic correction value and the maximum driving distance within the PID parameter adjustment time.
3. The PID adjusting method of vehicle adaptive lateral control according to claim 2, characterized in that the correction coefficient according to the dynamics is calculated by:
EffetctiveTuningFactor
＝1/effectiveRange*e log(effectiveRange)*TuningFactor ，
wherein effective range is the maximum travel distance within the parameter adjustment time, and TuningFactor represents the dynamic correction value.
4. The PID adjustment method of vehicle adaptive lateral control according to claim 1, characterized in that the gradient coefficient function is calculated from gradual and sudden time intervals during which the vehicle experiences a gradient:
determining a sudden change time interval of the gradient coefficient function according to a preset tangent function;
determining a gradient time interval of a gradient coefficient function according to a preset polynomial;
and respectively calculating the numerical value of the gradient coefficient function according to the mutation time interval and the gradual change time interval of the gradient coefficient function.
5. The PID adjustment method of vehicle adaptive lateral control according to claim 4, wherein the gradient coefficient function is expressed as:
where RampOvertime represents the duration of the slope smoothing process, t start Representing linear processing time, a, b, c, d being a function of said gradient coefficientsCoefficient of the gradient curve of (a).
6. The PID adjustment method for vehicle adaptive lateral control according to any one of claims 1 to 5, wherein the obtaining a vehicle steering wheel angle and a driver holding torque in real time and determining and/or calculating a dynamic parameter change rate according thereto comprises:
acquiring vehicle steering wheel corner data, and calculating an activity difference value according to the vehicle steering wheel corner data and a preset target activity;
judging whether the driver is in an intervention state according to the holding torque of the driver: if yes, determining the dynamic parameter change rate according to the dynamic parameter value of the previous calculation period and a preset maximum dynamic parameter change rate; and if not, determining the dynamic parameter change rate according to the transverse distance deviation and the liveness difference value.
7. A PID adjusting apparatus for adaptive lateral control of a vehicle, characterized by comprising:
the acquisition module is used for acquiring the steering angle of a vehicle steering wheel and the holding torque of a driver in real time and determining and/or calculating the change rate of the dynamic parameters according to the steering angle and the holding torque;
the first correction module is used for calculating a dynamic correction value according to the dynamic parameter change rate and calculating a dynamic correction coefficient according to the dynamic correction value; calculating a plurality of first correction terms of the PID according to the dynamic correction coefficient;
the second correction module is used for determining a gradient coefficient function according to a gradual change time interval and a sudden change time interval of the gradient of the vehicle; calculating a second correction term of the PID according to the gradient coefficient function;
an output module to adjust a lateral control output of a PID based on the plurality of first correction terms and the second correction term.
8. The vehicle adaptive lateral control PID tuning device of claim 7, wherein the first modification module comprises:
the integration unit is used for integrating the change rate of the dynamic parameter by the PID control continuous time integration parameter to obtain a dynamic correction value;
and the calculating unit is used for calculating the dynamic correction coefficient according to the dynamic correction value and the maximum driving distance within the PID parameter adjusting time.
9. An electronic device, comprising: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the PID adjustment method of vehicle adaptive lateral control as claimed in any one of claims 1 to 6.
10. A computer-readable medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the PID adjustment method of vehicle adaptive lateral control according to any one of claims 1 to 6.
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| CN202210959395.2A CN115366870A (en) | 2022-08-11 | 2022-08-11 | PID (proportion integration differentiation) adjusting method and device for vehicle adaptive transverse control |
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| CN202210959395.2A CN115366870A (en) | 2022-08-11 | 2022-08-11 | PID (proportion integration differentiation) adjusting method and device for vehicle adaptive transverse control |
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