CN112364561B - Vehicle control action correction method and device, electronic equipment and storage medium - Google Patents

Vehicle control action correction method and device, electronic equipment and storage medium Download PDF

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CN112364561B
CN112364561B CN202011156742.5A CN202011156742A CN112364561B CN 112364561 B CN112364561 B CN 112364561B CN 202011156742 A CN202011156742 A CN 202011156742A CN 112364561 B CN112364561 B CN 112364561B
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曹春耕
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Shanghai Gantan Information Technology Co ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60—VEHICLES IN GENERAL
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Abstract

The invention relates to the field of vehicle control, and provides a method, a device, electronic equipment and a storage medium for correcting vehicle control actions, wherein the method comprises the following steps: acquiring vehicle operation information, vehicle basic information, vehicle control information and corresponding environment information which are output by multiple observation angle sensors, and feedback information of processes of controlling the vehicle and the environment; calculating a coupling parameter by using vehicle operation information, vehicle basic information, vehicle control information, corresponding environment information and feedback information; and adjusting the historical vehicle control action information based on the coupling parameters to correct the vehicle control action of the vehicle. The method realizes the continuous and fine holography and optimization of the dynamic simulation model based on the mutual cooperation of the sensing data stream to the vehicle and the road, realizes the continuous approximation of the mathematical model to the practical similarity through the closed-loop sensing information system, and realizes the self-learning of the machine through the dynamic modification of the dynamic simulation model, thereby modifying and outputting more accurate and efficient vehicle control actions.

Description

Vehicle control action correction method and device, electronic equipment and storage medium
Technical Field
The present invention relates to the field of vehicle control, and in particular, to a method and an apparatus for correcting a vehicle control action, an electronic device, and a storage medium.
Background
The intelligent highway traffic construction relates to the construction of equipment and facilities such as automobiles, roads, pavements, roadside traffic facilities, networks, edge side equipment, cloud equipment and the like, and the vehicle operation needs to be simulated.
In the real world, the driving environment of a vehicle is unrealistic, and the situation varies from vehicle to vehicle. When the simulation is performed through the mathematical model, the mechanical structures of various vehicles need to be simulated, that is, mathematical models corresponding to various vehicles are respectively established according to the structures and characteristics of various vehicles, and one mathematical model corresponds to one vehicle. And, various parameters are set and debugged for various mathematical models.
In the prior art, it is time consuming and difficult to collect and maintain mechanical configuration and characterization data for various vehicles. Therefore, the existing dynamic simulation method for the automatic driving vehicle has the defects of low efficiency and reliability, and cannot efficiently simulate the dynamic condition of the vehicle moving in different environments.
Disclosure of Invention
The invention aims to provide a method and a device for correcting vehicle control action, electronic equipment and a storage medium, and realize high-efficiency utilization
The technical scheme provided by the invention is as follows:
a vehicle control action correction method comprises the following steps:
acquiring vehicle operation information, vehicle basic information, vehicle control information and corresponding environment information which are output by multiple observation angle sensing, and feedback information of a process of controlling the vehicle and the environment;
calculating a coupling parameter using the vehicle operation information, the vehicle basic information, the vehicle control information, and corresponding environment information, and the feedback information;
and adjusting historical vehicle control action information based on the coupling parameters to correct the vehicle control action of the vehicle.
Further preferably, the step of obtaining the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information output by the multi-angle sensing comprises the steps of:
obtaining first vehicle operation information by wheel rotating speed ranging, satellite positioning ranging, wireless network base station positioning ranging and radar ranging methods;
and acquiring second vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information by vehicle-mounted sensing, axle load sensing and time position sensing methods.
Further preferably, the calculating the coupling parameter by using the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information comprises the steps of:
setting an algorithm of the vehicle control action model as f' (t) × (AomebB) 0 )；
Coupling the vehicle operation information, vehicle base information, vehicle control information, and feedback information to obtain a corrected coupling parameter:
Figure GDA0003605631630000021
circularly correcting an algorithm of the vehicle control action model by using the coupling parameters;
wherein the algorithm of the modified vehicle control action model is f (t) n-1 )×(A∪B n-1 ) The derived parameter is Bn; a is the vehicle running information, the vehicle basic information, the vehicle control information and the inverseFeeding information; when n approaches infinity, { B n It converges on | | λ |, λ being the true value.
Further preferably, the step of coupling the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information to obtain the corrected coupling parameter comprises the steps of:
and coupling the first vehicle running information acquired by the wheel rotating speed ranging method, the satellite positioning ranging method, the wireless network base station positioning ranging method and the radar ranging method.
Further preferably, the step of coupling the first vehicle operation information obtained by the methods of wheel speed ranging, satellite positioning ranging, wireless network base station positioning ranging and radar ranging includes the steps of:
if the vehicle speed is v, the displacement is s, the time is t, and the speed is v, then:
{v n }＝{ds n }/{dt n }；
{ds n }＝(ds 1 ,ds 2 ,…ds n )，{dt n }＝(dt 1 ,dt 2 ,…dt n )；
wherein when ds is v/dt, Δ t >0, Δ s > 0;
Δt gps >Δt net ；Δt net >Δt rada ；Δt rada >Δt rps ；Δt rps >0
wherein, Δ t gps Delta t, Delta t for satellite positioning ranging net Δ t, Δ Δ t for positioning and ranging of wireless network base stations rada Locating Δ t, Δ t for radar rps Delta t for wheel speed ranging;
Δs gps >Δs net ；Δs net >Δs rada ；Δs rada >Δs rps ；Δs rps >0；
wherein, Δ s gps Delta s, Delta s for satellite positioning ranging net Delta s, Delta s for positioning and ranging of wireless network base station rada Δ s, Δ s for radar location ranging rps Δ s for wheel speed ranging;
assuming that the acceleration of the vehicle is a and the speed change of the vehicle is Δ v, then:
{Δv}＝{a}·Δt；
wherein, Δ t is a time period; when { Δ t } gps }≈{Δt m }≈{Δt rps In time:
Figure GDA0003605631630000031
Figure GDA0003605631630000032
V gps is equivalent to v net Is equivalent to v rada Is equivalent to v rps ；
Wherein v is gps V, v for satellite positioning ranging net V, v for positioning and ranging wireless network base station rada V, v for radar location ranging rps And v is the distance measurement of the wheel speed.
Further preferably, the coupling the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information to obtain the corrected coupling parameter includes:
coupling the first vehicle operation information, second vehicle operation information, the vehicle basis information, the vehicle control information, and the feedback information.
Further preferably, the coupling the first vehicle operation information, the second vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information comprises:
based on the vehicle control action information in the vehicle control information, the vehicle control action feedback information in the feedback information and the time position relation feedback information, calculating a control action factor and a feedback factor, wherein the calculation formula is as follows:
F(t)＝[P control +P feedback +P couple ]×η×ρ；
η＝F”(t)·{B}·P step ，ρ＝F”′(t)·{B}·γ；
wherein F is the acting force between the vehicle and the ground; p is control Information of vehicle control actions; p is feedback Feeding back information for controlling the vehicle; p is couple The time position relation feedback information is obtained, eta represents a vehicle control action factor, and rho represents a feedback correction factor;
wherein, P step To control the minimum step size, γ is the correction period:
Figure GDA0003605631630000041
further preferably, the calculating of the control action factor and the feedback factor comprises the steps of:
when the control action factor and the feedback factor are not calculated according to the data resolution and the control minimum step size, then:
η＝F”(t)·{B}·P step and ρ ═ F' "(t) · { B }. γ.
Further preferably, the calculating the control action factor and the feedback factor includes the steps of:
when the control action factor and the feedback factor are calculated from the data resolution and the control minimum step size, then:
Figure GDA0003605631630000051
wherein the content of the first and second substances,
Figure GDA0003605631630000052
is a parametric probabilistic wave function smaller than the data resolution.
Further preferably, before the coupling the first vehicle operation information, the second vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information, the method further comprises:
acquiring the vehicle basic information and the environment information, wherein the vehicle basic information comprises the mass and the acceleration of the vehicle and the positive pressure between the vehicle and the road surface, and the environment information comprises the road surface gradient, the slope speed coefficient and the dynamic friction coefficient;
using acceleration information a in the second vehicle operation information n And calculating the acting force of the vehicle and the ground, and the ratio of the friction force to the acting force of the vehicle and the road surface is as follows:
{F n }＝{a n m, and
Figure GDA0003605631630000053
{N n }＝{G×m×cosθ}·{k n }；
wherein, F n The acting force of the vehicle and the road surface is m, the mass of the vehicle is a, the acceleration of the vehicle is a, the positive pressure of the vehicle and the road surface is N, cos theta is the gradient of the road surface, k is the coefficient of slope speed, mu is the coefficient of dynamic friction, and G is the acceleration of gravity.
On the other hand, the invention also provides a vehicle control action correcting device, which comprises:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring vehicle operation information, vehicle basic information, vehicle control information and corresponding environment information which are output by multiple observation angle sensing, and feedback information of a process of controlling the vehicle and the environment;
the calculation module is used for calculating coupling parameters by utilizing the vehicle running information, the vehicle basic information, the vehicle control information and the corresponding environment information, and the feedback information;
and the correction module is used for adjusting historical vehicle control action information based on the coupling parameters so as to correct the vehicle control action of the vehicle.
The invention also provides an electronic device, which comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the processor is used for executing the computer program stored in the memory and realizing the operation executed by the vehicle control action correcting method.
The invention also provides a storage medium, wherein at least one instruction is stored in the storage medium, and the instruction is loaded and executed by the processor to realize the operation executed by the vehicle control action correction method.
The method and the device for correcting the vehicle control action, the electronic equipment and the storage medium provided by the invention at least have the following beneficial effects:
1) the model corrector is arranged in the scheme, so that the similarity of the sensing data to the model is continuously refined and optimized; in particular to a method for realizing machine self-learning through model correction, thereby realizing the improvement of 'holography' and 'confidence' of a process of approximating a real object by a model.
2) By the method and the device, the vehicle control action instruction information and the vehicle control action feedback information can be acquired so as to correct the vehicle control action, realize vehicle-vehicle linkage and ensure the running safety of the vehicle.
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The above features, technical features, advantages and implementations of a method, apparatus, electronic device and storage medium for correcting a vehicle control operation will be further described in the following detailed description of preferred embodiments with reference to the accompanying drawings.
FIG. 1 is a flow of closed loop control information in the present invention;
FIG. 2 is a static "event-time-information" logic diagram in accordance with the present invention;
FIG. 3 is a waveform visualization diagram in the present invention;
FIG. 4 is a visualization of a formula in the present invention;
FIG. 5 is a graph of efficiency visualization in the present invention;
FIG. 6 is a dynamic "event-time-information" logic diagram of the present invention
FIG. 7 is a graph comparing efficiency in the present invention;
FIG. 8 is a schematic structural diagram of an embodiment of the apparatus for correcting the behavior of the console of the present invention;
FIG. 9 is a schematic block diagram of an embodiment of an electronic device in accordance with the present invention;
fig. 10 is a speed measuring chart of the vehicle running with the variable speed motion in the invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
For the sake of simplicity, only the parts relevant to the present invention are schematically shown in the drawings, and they do not represent the actual structure as a product. Moreover, in the interest of brevity and understanding, only one of the components having the same structure or function is illustrated schematically or designated in some of the drawings. In this document, "one" means not only "only one" but also a case of "more than one".
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
In addition, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not intended to indicate or imply relative importance.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
One embodiment of the present invention, as shown in fig. 1, is a method for correcting a vehicle control action, including:
the method comprises the steps of obtaining vehicle running information, vehicle basic information, vehicle control information and corresponding environment information which are output by multiple observation angle sensing, and feedback information of a process of controlling the vehicle and controlling the environment.
Specifically, the multi-angle sensing means: 1) the method comprises the following steps of (1) wheel rotating speed ranging, 2) satellite positioning ranging, 3) wireless network base station positioning ranging, 4) radar ranging, 5) time position sensing and other sensing methods, wherein the five positioning ranging methods respectively have obvious advantages; the wireless network base station displacement ranging can measure the identity information of the automobile, radar ranging has the advantage of high-speed response time, and time position sensing can provide the advantages of accurate road position and time for the automobile to pass through the position. The sensing devices with different observation angles can realize complementary advantages by being coupled together.
And acquiring multi-parameter data, namely historical measurement parameters, through the multi-angle sensing, and correcting the vehicle control action model by taking the multi-parameter data of the vehicle as a training sample.
Illustratively, in this embodiment, by setting a multi-parameter sensor, real object parameter changes are obtained by the sensor, and the parameters that change in real time are imported into an equation, i.e., a model.
In addition, the embodiment realizes that the similarity of the sensing data to the simulation model is continuously refined and optimized, and particularly realizes machine self-learning through model correction, so that the improvement of the 'holographic degree' and 'confidence' of the simulation model to the real object approximation process is realized.
Meanwhile, a unified clock module is arranged on the sensing side, correlation coupling is carried out on multiple parameters based on the unified clock, and data coupling unification is realized according to the audit relationship among the multiple parameters.
For example, since the multi-parameter data of the vehicle is changed in real time, the trained vehicle operation dynamic mirror simulation model can obtain the real-time coupling data of the vehicle according to the real-time multi-parameter data of the vehicle.
And calculating a coupling parameter by using the vehicle operation information, the vehicle basic information, the vehicle control information and the corresponding environment information, and the feedback information.
And adjusting historical vehicle control action information based on the coupling parameters to correct the vehicle control action of the vehicle.
Exemplarily, historical measurement parameters corresponding to wheel rotation speed ranging, satellite positioning ranging, wireless network base station positioning ranging, radar ranging and time position sensing methods are compared, resolution scales are adjusted according to resolution differences of the historical measurement parameters, and errors of calibration parameters are corrected.
Meanwhile, before the correction, firstly establishing a vehicle control action model, then training the vehicle control action model, and when training the vehicle control action model, specifically comprising the following steps:
and importing historical measurement parameters to an edge calculation unit simulator.
Wherein the historical measurement parameters comprise satellite positioning sensing data D 1 And wireless base station positioning sensing data D 2 Radar ranging data D 3 Axle weight data D 4 And vehicle time position information D 5 Weather sensing data D 6 Accumulated water and road surface humidity sensing data D 7 And vehicle data D uploaded to the edge computing unit simulator 8 、D 9 、……D N ；
And (3) leading the parameter to be { A } by the sensor side, namely obtaining the historical measurement parameter to be { A } by the model:
Figure GDA0003605631630000091
setting an arithmetic unit f (t) of the simulator to derive an indirect parameter B 0 Error E 0 The true value is lambda; coupling the historical measurement parameters through the edge calculation unit simulator, wherein a coupling formula is as follows:
Figure GDA0003605631630000092
deriving the coupling parameter { B } from the above formula, where the coupling parameter is:
Figure GDA0003605631630000093
the observation method comprises wheel rotating speed ranging, satellite positioning ranging, wireless network base station positioning ranging, radar ranging parameters and time position sensing ranging.
Meanwhile, if | | | λ | | = { B | |) 0 }+E 0 And | | | λ | - { B 0 }|≤|||λ||-{A}。
In this embodiment, the model is modified by a model modifier
Figure GDA0003605631630000101
Then, the parameters are derived after correction:
Figure GDA0003605631630000102
the algorithm of the modified simulator is f) t 1 )×(A∪B 1 ) Derived parameters are B 2 (ii) a Continuing the loop correction, … … the algorithm of the corrected simulator is f (t) n-1 )×(A∪B n-1 ) Derived parameters are B n (ii) a When n approaches infinity, { B n It converges to lambda.
For example, in this embodiment, a dynamic simulation model with a unified vehicle-road cooperation is first constructed; acquiring vehicle and road operation information, vehicle and road foundation information and vehicle and road control action information process result feedback information which are output by multiple observation angles in a sensing way; automatically associating and coupling multi-source information in a dynamic simulation model by utilizing the vehicle-road running information, the vehicle-road foundation information, the vehicle-road control action information and the vehicle control and road control effect feedback information to realize closed loop of the information; and further optimizing background information based on the parameter coupling process of the dynamic simulation model, namely correcting the expectation of the vehicle control action and further optimizing the control effect, and outputting the vehicle control action based on the optimized background information.
Wherein, the closed loop system related to realizing the closed loop of the information is the basic information flow of the wisdom. The large closed loop is internally provided with a small closed loop, and the long period closed loop is internally provided with a short period closed loop.
In addition, the multi-source information means that mutual independence of data information sources is guaranteed. For example, the sensed data is considered to be one of the sources. The sensors are independent local, fractional sampling information, with data from the field energy transmission. The sensing data is generally classified into a load class, a constraint class and a feedback class. Of course, a simulation model with only sensory data is not sufficient.
Background information is one of the most basic concepts of information. Without background information, all information is unacceptable to the recipient of the information. For example, the following steps are carried out: a sentence is spoken by uttering a sound, but the sound itself is not the meaning of the message. The ability to receive information depends on the context of the information recipient.
The control action expectation refers to the control action expectation executed based on pattern recognition. Pattern recognition may in turn be understood as machine autonomous decision making.
It should be noted that the background information is historical information including artificial teaching and self-learning, and the historical information includes data and logic. The vehicle control action correction is to execute the output of vehicle control action information (what is, how much is done) by pre-judging the output need of the vehicle control in a real-time closed-loop information interval. After the output information drives the execution action, the actual output execution action effects are monitored through sensing, and the feedback information is compared with the initial 'output need of the pre-judging control vehicle', so that the next upcoming pre-judgment is corrected.
To enhance understanding, for example, the humidity of the road surface changes with the weather, multiple vehicles are driven over the same road surface. In this modification to the immediacy anticipation, the resulting information is public information. If the preceding vehicle correction information is for the following vehicle, it is background information (common information) for the following vehicle; if the vehicle-controlled system is used for further adjusting the vehicle-controlled system in real time to be further accurate, action correction (personal information) is carried out.
In this embodiment, a specific single parameter sensor is used as a basis for multi-angle sensing, and specifically includes:
a satellite positioning system: a GPS/BD positioning satellite, a road side ground differential station and a vehicle-mounted terminal; the system realizes positioning of vehicle-mounted terminals distributed in a wide area of a city among a plurality of satellites and terminals, and is one of the traditional positioning methods. Particularly, the distributed differential station is necessarily established on the ground, and the positioning accuracy (millimeter level), the signal stability and the time coordinate accuracy are improved. However, the system cannot completely meet the requirement of measurement and control of a high-speed moving automobile because the positioning period is about 1 second.
Wireless communication positioning: a road side wireless network base station and a vehicle-mounted wireless terminal; the system realizes positioning of vehicle-mounted terminals distributed in a range of 1 kilometer of the base stations among a plurality of base stations and terminals, and is one of the traditional positioning methods. Compared with satellite positioning, the method has the advantage of short positioning period, and can determine the identity of the vehicle; however, for positioning a moving automobile, the positioning time is delayed, the network reliability causes possible delay, and the measurement and control requirements of the high-speed moving automobile cannot be completely met.
Fixed position radar ranging and speed measuring: a roadside radar distance and speed measurement sensing device; the radar distance and speed measuring sensing device is fixedly positioned on a road, so that the distance and speed measurement of a moving automobile within the range of about 40 meters of distributed measuring points can be realized, and the radar distance and speed measuring sensing device is one of the traditional distance and speed measuring methods. Compared with satellite positioning and wireless positioning, the radar ranging and speed measuring device has the advantages of high measuring speed and high precision; however, the detection distance of the distribution points is only about 40 meters, and the speed measurement is indirectly obtained through two-point distance measurement and time measurement calculation, so that the holography cannot completely meet the requirement of measurement and control of a high-speed moving automobile for an automobile which possibly has variable-speed movement. Moreover, the cost for realizing continuous coverage of the distributed radar measuring points is too high, and the distributed radar measuring points can only be used as effective supplement for satellite positioning and wireless positioning.
Vehicle-mounted rotating speed measurement vehicle speed: a vehicle-side vehicle-mounted tachometer; the vehicle-mounted rotating speed measurement and speed measurement is one of the traditional positioning methods; the device is connected with a road side calculation unit through an OBD vehicle-mounted module and is used as a part of a real-time dynamic road unit (local road section). However, the disadvantage is that the dynamic speed (differential speed) accumulates errors, such as: the inflation state of the tire influences the coefficient A of the rotating speed and the vehicle speed, and the tread and road surface state influences the coefficient B of the rotating speed and the vehicle speed. The disadvantage is that the three positioning and speed measuring methods of the satellite positioning system, wireless communication positioning, fixed-position radar distance and speed measurement are coupled (model correction), and then the complementarity is very strong.
Measuring the axle weight and the fixed time position: a road side axle weight sensing device and a ground sensing monitoring device; the device is used for measuring time position information of a vehicle passing a determined position at a determined moment, and is an effective supplement to the four types of measured vehicle speed and positioning information. In the three positioning and speed measuring methods of the satellite positioning system, the wireless communication positioning, the fixed-position radar distance measurement and speed measurement and the like, in the measurement of the moving vehicle, one positioning point is determined based on a certain integral quantity, and the average speed is obtained through the distance and time calculation of two continuous positioning points; and the vehicle speed measured by the vehicle-mounted rotating speed has no time position relation with the road side. The axle weight measurement is to measure the weight of a single axle of an automobile (the pressure generated by two parallel tires on a road surface, and at least two axles of an automobile), and under the same meteorological conditions, the coefficient B of the tire tread and the road surface state, which influences the rotating speed and the vehicle speed, forms a causal relationship with the axle weight.
Measuring six meteorological elements, road surface humidity and road surface accumulated water liquid level: the road side weather sensing device comprises a roadside weather six-element sensing device, a road surface humidity sensing device and a liquid level sensing device; the device is used for measuring the corresponding change of the road surface along with the meteorological change, and is a necessary parameter for correcting a coefficient A of the inflation state of the tire, which influences the rotating speed and the vehicle speed, and a coefficient B of the tread and the road surface state, which influences the rotating speed and the vehicle speed. And is also an important component of vehicle control parameters.
Controlling vehicle action and effect feedback: a vehicle side control vehicle action measuring device and a vehicle control effect feedback device (comprising acceleration, a gyroscope and power); the device is connected with a road side calculation unit by an OBD vehicle-mounted module and is used as a part of a real-time dynamic road unit (local road section); the coupling coefficient among various parameters can be corrected in real time through feedback information. The key of vehicle-vehicle connection is to know the current information of the opposite vehicle, the information of the vehicle control action command which is not to be done and the feedback information of the vehicle control action.
And (3) measuring the relative position and the relative speed of the vehicle: a vehicle side range radar; the relation between time, position and speed between the front and the rear vehicles on the same lane is the key for improving the utilization efficiency of traffic resources of the vehicles and the roads. Specifically, the following description is provided: the kinetic energy of rear-end collision of the automobile comes from the speed difference between two automobiles, and the kinetic energy of the speed difference is released at the moment of collision; the safe distance between the front vehicle and the rear vehicle in the traditional driving process provides driving response time, and also provides speed difference generation time of the two vehicles. Reducing the safety distance as much as possible reduces the kinetic energy of collision, but requires a faster reaction. The response speed of the machine is faster than that of a human, and the vehicle-to-vehicle connection is characterized by knowing the current information of the vehicle of the opposite side, the information of the vehicle control action command which is not to be done and the feedback information of the vehicle control action.
In this embodiment, because the simulation model may have an error, the model is corrected by setting the model corrector, so that the prediction and judgment of the model are more accurate.
Example two
Based on the above embodiment, in this embodiment, the obtaining of the vehicle operation information, the vehicle basic information, the vehicle control information, and the feedback information output by the multi-angle sensor includes:
and obtaining the first vehicle running information by wheel rotating speed ranging, satellite positioning ranging, wireless network base station positioning ranging and radar ranging methods.
The first vehicle operation information may include a vehicle operation displacement and speed information calculated according to the displacement.
Specifically, comparison: 1) wheel rotating speed ranging, 2) satellite positioning ranging, 3) wireless network base station positioning ranging, 4) radar ranging, 5) time position sensing and the like, wherein the five positioning ranging methods comprise:
first, the wheels measure the vehicle displacement, as follows:
Figure GDA0003605631630000131
wherein S represents displacement, ω represents rotational speed, t represents time, and R represents tire radius;
let, the error of rotation speed omega E Time error t E Radius error of tire R E (ii) a The displacement accumulated error S E wheel Comprises the following steps:
Figure GDA0003605631630000141
secondly, the satellite measures the moving distance of the vehicle, as follows:
ΔS(t n ，t 0 )＝P n -P 0 ；
wherein Δ S represents a displacement, P n Representing the coordinates of the end point, P 0 Denotes the coordinates of the origin, t 0 Denotes the time of origin, t n Represents the endpoint time;
setting and end point positioning error P En Starting point positioning error P E0 Time error of origin t E0 End point time error t En (ii) a The displacement accumulates the total error S E satellite Comprises the following steps:
S E (t E0 ，t En )＝P En -P E0 。
in the two measurement methods, the vehicle runs in variable speed motion, and the speed measurement is as shown in fig. 10, wherein the time t required by a single measurement period is t satellite > t wheel; for variable speed vehicle motion, the time required for a single measurement cycle is the resolution of the speed change, which is a resolution scaling error. Because the wheel method is realized by multiple continuous real-time distance measurement, single measurement error can be accumulated; and the satellite positioning only has two errors generated by the positioning of the starting point and the end point.
The two speed measuring methods are compared to obtain the following results:
when the displacement is larger, the error of the satellite displacement distance measurement is smaller than the wheel displacement distance measurement: i.e. satellite E S <Wheel E S ；
When the displacement is smaller, the error of the satellite displacement distance measurement is larger than the wheel displacement distance measurement: i.e. satellite E S >Wheel E S ；
The mutual correction between the two observation angles can be realized by utilizing the respective advantages of two different speed measuring methods; two different observation angles of the same object can mutually compensate resolution scale errors in the data coupling process, and can also correct errors of calibration parameters, for example, when a vehicle runs in a relatively uniform speed state, the satellite speed measurement utilizes the advantage that the satellite ES < the wheel ES, so that a correction basis is provided for the wheel speed measurement.
It should be noted that the second vehicle operation information, the vehicle basic information, the vehicle control information, and the feedback information may also be obtained by vehicle-mounted sensing, axle load sensing, and time-position sensing methods.
Preferably, the calculating the coupling parameter by using the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information comprises the steps of:
setting an algorithm of the vehicle control action model as f' (t) × (AomebB) 0 )；
Coupling the vehicle operation information, vehicle base information, vehicle control information and feedback information to obtain a corrected coupling parameter:
Figure GDA0003605631630000151
circularly correcting an algorithm of the vehicle control action model by using the coupling parameters;
wherein the algorithm of the modified vehicle control action model is f (t) n-1 )×(A∪B n-1 ) The derived parameter is Bn; a is the vehicle running information, the vehicle basic information, the vehicle control information and the feedback information; when n approaches infinity, { B n It converges on | | λ |, λ being the true value.
Preferably, the step of coupling the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information to obtain the corrected coupling parameter comprises the steps of:
and coupling the first vehicle running information acquired by the wheel rotating speed ranging method, the satellite positioning ranging method, the wireless network base station positioning ranging method and the radar ranging method.
Preferably, the step of coupling the first vehicle operation information obtained by the methods of wheel speed ranging, satellite positioning ranging, wireless network base station positioning ranging and radar ranging comprises the steps of:
setting the speed of a vehicle as v, the displacement as s, the time as t and the speed as v (wherein s and v are vectors respectively); wherein ds, dt are obtained by sensor measurements:
{v n }＝{ds n }/{dt n }；
{ds n }＝(dS 1 ,ds 2 ,…ds n )，{dt n }＝(dt 1 ,dt 2 ,…dt n )；
wherein Δ s >0 when ds ═ v/dt, Δ t > 0;
Δt gps >Δt net ；Δt net >Δt rada ；Δt rada >Δt rps ；Δt rps >0
wherein, Δ t gps Delta t for satellite positioning ranging net Δ t, Δ t for positioning ranging of wireless network base stations rada Locating Δ t, Δ t for radar rps Delta t for wheel speed ranging;
Δs gps >Δs net ；Δs net >Δs rada ；Δs rada >Δs rps ；Δs rps >0；
wherein, Δ s gps Delta s for satellite positioning ranging net Delta s, Delta s for positioning and ranging of wireless network base station rada Δ s, Δ s for radar location ranging rps Δ s for wheel speed ranging;
assuming that the acceleration of the vehicle is a and the speed change of the vehicle is Δ v, then:
{Δv}＝{a}·Δt；
wherein, Δ t is a time period; when { Δ t } gps }≈{Δt m }≈{Δt rps When the position is right:
Figure GDA0003605631630000161
at the same time, the user can select the desired position,
Figure GDA0003605631630000162
V gps is equivalent to v net Is equivalent to v rada Is equivalent to v rps ；
Wherein v is gps V, v for satellite positioning ranging net Positioning ranging v, v for wireless network base station ra da is v, v of radar positioning and ranging rps V, which is the distance measurement of the wheel speed.
Preferably, the step of coupling the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information to obtain the corrected coupling parameter comprises the steps of:
coupling the first vehicle operation information, second vehicle operation information, the vehicle grounding information, the vehicle control information, and the feedback information.
Preferably, said coupling said first vehicle operation information, second vehicle operation information, said vehicle basis information, said vehicle control information and said feedback information comprises the steps of:
based on the vehicle control action information in the vehicle control information, the vehicle control action feedback information in the feedback information and the time position relation feedback information, calculating a control action factor and a feedback factor, wherein the calculation formula is as follows:
F(t)＝[P control +P feedback +P couple ]×η×ρ；
η＝F”(t)·{B}·P step ，ρ＝F”′(t)·{B}·γ；
wherein F is the acting force of the vehicle and the ground; p is control The information is the vehicle control action information; p feedback Feeding back information for vehicle control actions; p couple The time position relation feedback information is obtained, eta represents a vehicle control action factor, and rho represents a feedback correction factor;
wherein, P step To control the minimum step size, γ is the correction period:
Figure GDA0003605631630000171
preferably, the calculating of the control action factor and the feedback factor comprises the steps of:
when the control action factor and the feedback factor are not calculated according to the data resolution and the control minimum step size, then:
η＝F”(t)·{B}·P step and ρ ═ F' "(t) · { B }. γ.
Preferably, the calculating the control action factor and the feedback factor comprises the steps of:
when the control action factor and the feedback factor are calculated according to the data resolution and the control minimum step size, then:
Figure GDA0003605631630000172
wherein the content of the first and second substances,
Figure GDA0003605631630000173
is a parametric probabilistic wavefunction that is less than the data resolution.
Preferably, before the coupling the first vehicle operation information, the second vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information, further comprising:
using acceleration information a in the second vehicle operation information n And calculating the acting force of the vehicle and the ground:
{F n }＝{a n m, and
Figure GDA0003605631630000174
specifically, in this embodiment, the parameter coupling relationship in this embodiment includes other related sensing parameter couplings besides the multi-angle velocity measurement coupling.
Setting the vehicle speed as v, the displacement as s, the time as t and the speed as v (wherein s and v are vectors respectively); wherein ds, dt are obtained by sensor measurements.
{v n }＝{ds n }/{dt n }
Wherein, { ds n }＝(ds 1 ,ds 2 ,…ds n )，{dt n }＝(dt 1 ,dt 2 ,…dt n )。
And because ds is v/dt, limited by the actual sensing measurement sampling, Δ t > 0; therefore, Δ s > 0.
For the above positioning methods, Δ t of satellite positioning gps is greater than Δ t of wireless network base station positioning, Δ t of wireless network base station positioning is greater than Δ t of radar positioning, Δ t of radar positioning is greater than Δ t of wheel rotation speed:
Δt gps >Δt net ；Δt net >Δt rada ；Δt rada >Δt rps ；Δt rps >0
therefore, Δ s of satellite positioning gps is greater than Δ s of wireless network base station positioning, Δ s of wireless network base station positioning is greater than Δ s of radar positioning, Δ s of radar positioning is greater than Δ s of wheel rotation speed:
Δs gps >Δs net ；Δs net >Δs rada ；Δs rada >Δs rps ；Δs rps >0
assuming that the acceleration of the vehicle is a and the speed change is Δ v, then:
{Δv}＝{a}·Δtt
wherein a is measured by a sensor and Δ t is measured by a sensor; when { Δ t } gps }≈{Δt m }≈{Δt rps In time:
Figure GDA0003605631630000181
simultaneously:
Figure GDA0003605631630000182
therefore, according to the same principle, the following can be obtained:
v gps is equivalent to v net Is equivalent to v rada Is equivalent to v rps
F represents the comprehensive acting force of the ground and the vehicle platform surface, m represents the vehicle mass, a represents the acceleration, N represents the positive pressure of the vehicle and the road surface, cos theta represents the road surface gradient, k represents the gradient speed coefficient, and mu represents the dynamic friction coefficient; (wherein F, a, N, G are vectors, respectively); wherein m is obtained by the measurement of an axle weight sensor; a is obtained through calculation, cos theta is a determination constant, G is gravity acceleration, m is obtained through measurement of an axle load sensor, k is obtained through speed correlation calculation, and N represents vehicle and road surface positive pressure.
Then:
{F n }＝{a n m, and
Figure GDA0003605631630000191
where δ n represents the coefficient of application of friction, i.e. the ratio between the maximum available force and the actual force generated.
Simultaneously:
{N n }＝{G×m×cosθ}·{k n }
vehicle control action data P obtained by vehicle-mounted sensing control (ii) a Meanwhile, vehicle control action feedback data P can be obtained by vehicle-mounted sensing feedback (ii) a Meanwhile, time position relation feedback data P is obtained by the road side couple 。
F(t)＝[P control +P feedback +P couple ]Xeta. rho … … … … (formula 2)
Wherein eta represents a vehicle control action factor, and rho represents a feedback correction factor.
Let, control the minimum P of step length step (ii) a CorrectionThe period is gamma;
Figure GDA0003605631630000192
assuming, regardless of the data resolution, and regardless of the control minimum step size, then:
η＝F”(t)·{B}·P step and ρ ═ F' "(t) · { B }. γ
And because all sensory data comes from the past and all interventions occur in the future, as shown in the static "event-time-information" logic diagram of fig. 2.
Therefore, { A } and { B } are formed in the past in (formula 1); where { A } is sampled in the past and { B } is an estimate of the value of { lambda } that will occur in the future.
Thus, in the case where (equation 2) is a future intervention, the basis is from past samples that have occurred and forms the background of the information in the face of the future.
Therefore, intervention accuracy depends on two aspects: first, the holographic resolution; and secondly, controlling the action resolution.
Setting parameters less than resolution to conform to probabilistic wave functions
Figure GDA0003605631630000201
So, considering the data resolution, and considering the control minimum step size, then:
Figure GDA0003605631630000202
and is provided with
Figure GDA0003605631630000205
Because, in the mathematical model, there are measurement errors, insufficient conditions, empirical assumptions, there are control errors, output errors, fitting errors in the vehicle control action output, and:
F(t)＞f(t)
therefore, as shown in fig. 3, the output of the vehicle control action is completed by pattern recognition with the data derived from the mathematical model as a criterion; namely:
f (t.).. decision
f (t)
Wherein:
single＝∑ Δt [P step ]
when the minimum resolution of f (t) is less than the minimum resolution of f (t), then:
f(t)∈F(t)；
conversely, as shown in fig. 4, there are:
F(t)∈f(t)；
as shown in fig. 5, the realistic efficiency achieves:
Figure GDA0003605631630000204
and (4) conclusion: the dynamic event-time-information logic is derived from the static event-time-information logic, such as the dynamic event-time-information logic diagram shown in fig. 6.
Therefore, the utilization efficiency of the real resources depends on two aspects of measurement accuracy and control accuracy, and the smaller the phi is, the highest real output efficiency is; and the worst outcome occurs between the two and reality.
Meanwhile, cycle → Min, i.e. the smaller Δ t, the highest realistic yield efficiency.
Therefore, the accuracy of both measurement and control should be within a reasonable and uniform interval, as shown in fig. 7.
On the other hand, as shown in fig. 8, the present invention also provides a vehicle control action correcting device, including:
the acquisition module 801 is used for acquiring vehicle operation information, vehicle basic information, vehicle control information and feedback information which are output by multi-angle sensing;
a calculating module 802, configured to calculate a coupling parameter using the vehicle operation information, the vehicle basic information, the vehicle control information, and the feedback information;
and a correcting module 803, configured to correct the vehicle control action output by the vehicle control action model based on the coupling parameter.
Specifically, in the present embodiment, the following measurement is performed by the single parameter sensor:
a satellite positioning system: a GPS/BD positioning satellite, a road side ground differential station and a vehicle-mounted terminal; the system realizes positioning of vehicle-mounted terminals distributed in a wide area of a city among a plurality of satellites and terminals, and is one of the traditional positioning methods. Particularly, the distributed differential station is necessarily established on the ground, and the positioning precision (millimeter level), the signal stability and the time coordinate precision are improved. However, the system can not completely meet the requirement of measurement and control of the high-speed moving automobile because the positioning period is about 1 second.
Wireless communication positioning: a road side wireless network base station and a vehicle-mounted wireless terminal; the system realizes positioning of vehicle-mounted terminals distributed in a range of 1 kilometer of the base stations among a plurality of base stations and terminals, and is one of the traditional positioning methods. Compared with satellite positioning, the method has the advantage of short positioning period, and can determine the identity of the vehicle; however, for the positioning of the moving automobiles, the positioning time is delayed, the network reliability causes delay possibly, and the measurement and control requirements of the high-speed moving automobiles cannot be completely met.
Fixed position radar ranging and speed measuring: a roadside radar distance and speed measurement sensing device; the radar distance and speed measuring sensing device is fixedly arranged on a road, so that the distance and speed measurement of a moving automobile within the range of about 40 meters of distributed measuring points can be realized, and the radar distance and speed measuring sensing device is one of the traditional distance and speed measuring methods. Compared with satellite positioning and wireless positioning, the radar ranging and speed measuring device has the advantages of high measuring speed and high precision; however, the detection distance of the distribution points is only about 40 meters, and the speed measurement is indirectly obtained through two-point distance measurement and time measurement calculation, so that the holography cannot completely meet the requirement of measurement and control of a high-speed moving automobile for an automobile which possibly has variable-speed movement. And the cost for realizing the continuous coverage of the distributed radar measuring points is too high, and the distributed radar measuring points can only be used as effective supplement for satellite positioning and wireless positioning.
Vehicle-mounted rotating speed measurement vehicle speed: a vehicle-side vehicle-mounted tachometer; vehicle-mounted rotating speed measurement and speed measurement are one of the traditional positioning methods; the device is connected with a road side calculation unit by an OBD vehicle-mounted module and is used as a part of a real-time dynamic road unit (local road section). However, the disadvantage is that the dynamic speed (differential speed) accumulates errors, such as: the inflation state of the tire influences the coefficient A of the rotating speed and the vehicle speed, and the tread and road surface state influences the coefficient B of the rotating speed and the vehicle speed. The disadvantage is that the three positioning and speed measuring methods of the satellite positioning system, wireless communication positioning, fixed-position radar distance and speed measurement are coupled (model correction), and then the complementarity is very strong.
Measuring the axle weight and the fixed time position: the road side axle load sensing device and the ground sensing monitoring device; the device is used for measuring time position information of a vehicle passing a determined position at a determined time, and is an effective supplement to the four types of measured vehicle speed and positioning information. In the three positioning and speed measuring methods of the satellite positioning system, the wireless communication positioning, the fixed-position radar distance measurement and speed measurement and the like, in the measurement of the moving vehicle, one positioning point is determined based on a certain integral quantity, and the average speed is obtained through the distance and time calculation of two continuous positioning points; and the vehicle speed measured by the vehicle-mounted rotating speed has no time position relation with the road side. The axle weight measurement is to measure the weight of a single axle of an automobile (the pressure generated by two parallel tires on a road surface, and at least two axles of an automobile), and under the same meteorological conditions, the coefficient B of the tire tread and the road surface state, which influences the rotating speed and the vehicle speed, forms a causal relationship with the axle weight.
Measuring six meteorological factors, road surface humidity and road surface accumulated water liquid level: the system comprises a roadside meteorological six-element sensing device, a road surface humidity sensing device and a liquid level sensing device; the device is used for measuring the corresponding change of the road surface along with the meteorological change, and is a necessary parameter for correcting a coefficient A of the inflation state of the tire, which influences the rotating speed and the vehicle speed, and a coefficient B of the tread and the road surface state, which influences the rotating speed and the vehicle speed. And is also an important component of vehicle control parameters.
Controlling vehicle action and effect feedback: a vehicle side control vehicle action measuring device and a vehicle control effect feedback device (comprising acceleration, a gyroscope and power); the device is connected with a roadside computing unit by an OBD vehicle-mounted module and is used as a part of a real-time dynamic road unit (local road section); the coupling coefficient among various parameters can be corrected in real time through feedback information. The key of vehicle-vehicle connection is to know the current information of the opposite vehicle, the information of the vehicle control action command which is not to be done and the feedback information of the vehicle control action.
And (3) measuring the relative position and the relative speed of the vehicle: a vehicle side range radar; the relation of time, position and speed between the front and the rear vehicles on the same lane is the key for improving the utilization efficiency of traffic resources of vehicles and roads.
Specifically, the following description is provided: the kinetic energy of the automobile in rear-end collision comes from the speed difference between two automobiles, and the kinetic energy of the speed difference is released at the moment of collision.
The safe distance between the front vehicle and the rear vehicle in the traditional driving process provides driving reaction time and also provides speed difference generation time of the two vehicles. Reducing the safety distance as much as possible reduces the kinetic energy of collision, but requires a faster reaction. The response speed of the machine is faster than that of a human, and the vehicle-to-vehicle connection is characterized by knowing the current information of the vehicle of the opposite side, the information of the vehicle control action command which is not to be done and the feedback information of the vehicle control action.
The invention can acquire the vehicle control action instruction information and the vehicle control action feedback information to correct the vehicle control action.
EXAMPLE five
One embodiment of the present invention, as shown in fig. 9, an electronic device 100, includes a processor 110, a memory 120, wherein the memory 120 is used for storing a computer program 121; the processor 110 is configured to execute the computer program 121 stored in the memory 120 to implement the method in the above embodiments.
The electronic device 100 may be a desktop computer, a notebook computer, a palm computer, a tablet computer, a mobile phone, a human-computer interaction screen, or the like. The apparatus 100 may include, but is not limited to, a processor 110, a memory 120. Those skilled in the art will appreciate that fig. 9 is merely an example of the electronic device 100, and does not constitute a limitation of the electronic device 100, and may include more or fewer components than illustrated, or some of the components may be combined, or different components, as illustrated by the example: electronic device 100 may also include input/output interfaces, display devices, network access devices, communication buses, communication interfaces, and the like. A communication interface and a communication bus, and may further include an input/output interface, wherein the processor 110, the memory 120, the input/output interface and the communication interface complete communication with each other through the communication bus. The memory 120 stores a computer program 121, and the processor 110 is configured to execute the computer program 121 stored in the memory 120 to implement the method in the above embodiment.
The Processor 110 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 120 may be an internal storage unit of the electronic device 100, for example: hard disk or memory of the device. The memory may also be an external storage device of the device, for example: the equipment comprises a plug-in hard disk, an intelligent memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) and the like. Further, the memory 120 may also include both an internal storage unit and an external storage device of the electronic device 100. The memory 120 is used for storing the computer program 121 and other programs and data required by the electronic device 100. The memory may also be used to temporarily store data that has been output or is to be output.
A communication bus is a circuit that connects the described elements and enables transmission between the elements. Illustratively, the processor 110 receives commands from other elements through the communication bus, decrypts the received commands, and performs calculations or data processing according to the decrypted commands. Memory 120 may include program modules, illustratively, a kernel (kernel), middleware (middleware), an Application Programming Interface (API), and applications. The program modules may be comprised of software, firmware or hardware, or at least two of the same. The input/output interface forwards commands or data input by a user via the input/output interface (e.g., sensor, keypad, touch screen). The communication interface connects the electronic device 100 with other network devices, user devices, networks. For example, the communication interface may be connected to the network by wire or wirelessly to connect to other external network devices or user devices. The wireless communication may include at least one of: wireless fidelity (WiFi), Bluetooth (BT), near field communication technology (NFC), Global Positioning Satellite (GPS) and cellular communications, among others. The wired communication may include at least one of: universal Serial Bus (USB), high-definition multimedia interface (HDMI), asynchronous transfer standard interface (RS-232), and the like. The network may be a telecommunications network and a communications network. The communication network may be a computer network, the internet of things, a telephone network. The electronic device 100 may be connected to the network through a communication interface, and a protocol by which the electronic device 100 communicates with other network devices may be supported by at least one of an application, an Application Programming Interface (API), middleware, a kernel, and a communication interface.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/device and method may be implemented in other ways. The above-described apparatus/device embodiments are merely exemplary, and the division of the modules or units is merely an example of a logical functional division, and there may be other divisions in actual implementation, and as an example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units may be stored in a storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow in the method according to the above embodiments may also be implemented by sending instructions to relevant hardware by the computer program 121, where the computer program 121 may be stored in a medium, and when being executed by a processor, the computer program 121 may implement the steps of the above embodiments of the method. The computer program 121 may be in a source code form, an object code form, an executable file or some intermediate form, etc. The medium may include: any entity or device capable of carrying the computer program 121, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content contained in the medium can be increased or decreased as appropriate according to the requirements of legislation and patent practice in the jurisdiction, and the following are exemplary: in some jurisdictions, in accordance with legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunications signals. It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of program modules is illustrated, and in practical applications, the above-described distribution of functions may be performed by different program modules, that is, the internal structure of the apparatus may be divided into different program units or modules to perform all or part of the above-described functions. Each program module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one processing unit, and the integrated unit may be implemented in a form of hardware, or may be implemented in a form of software program unit. In addition, the specific names of the program modules are only used for distinguishing one program module from another, and are not used for limiting the protection scope of the application.
A storage medium having at least one instruction stored therein, the instruction being loaded and executed by a processor to implement the operation performed by the method for correcting vehicle control action.
In the foregoing embodiments, the descriptions of the respective embodiments have their respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or recited in detail in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

Claims (11)

1. A vehicle control action correction method is characterized by comprising the following steps:
acquiring vehicle operation information, vehicle basic information, vehicle control information and corresponding environment information which are output by multiple observation angle sensing, and feedback information of a process of controlling the vehicle and controlling the environment; the method comprises the following steps:
obtaining first vehicle operation information by wheel rotating speed ranging, satellite positioning ranging, wireless network base station positioning ranging and radar ranging methods; acquiring second vehicle running information, the vehicle basic information, the vehicle control information and the feedback information by a vehicle-mounted sensing method, an axle load sensing method and a time position sensing method;
calculating a coupling parameter using the vehicle operation information, the vehicle basic information, the vehicle control information, and corresponding environment information, and the feedback information; the method comprises the following steps:
setting an algorithm of the vehicle control action model as f' (t) × (AomebB) 0 )；
Coupling the vehicle operation information, vehicle base information, vehicle control information and feedback information to obtain a corrected coupling parameter:
Figure FDA0003605631620000011
circularly correcting an algorithm of the vehicle control action model by using the coupling parameters;
wherein f (t) is an algorithm of a simulator, B 0 To derive indirect parameters; u is a union set; the algorithm of the modified vehicle control action model is f (t) n-1 )×(A∪B n-1 ) The derived parameter is Bn; a is the vehicle running information, the vehicle basic information, the vehicle control information and the feedback information; when n approaches infinity, { B n The } converges on | | λ |, λ is the true value;
adjusting historical vehicle control action information based on the coupling parameters to correct the vehicle control action of the vehicle;
wherein the vehicle operation information includes the first vehicle operation information and the second vehicle operation information; the multi-observation angle sensing is to output parameters through various sensors; the first vehicle running information may include vehicle running displacement and speed information calculated according to the displacement; the second vehicle operation information includes acceleration information.
2. The vehicle control action correcting method according to claim 1, wherein the step of coupling the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information to obtain the corrected coupling parameter comprises the steps of:
and coupling the first vehicle running information obtained by the wheel rotating speed ranging method, the satellite positioning ranging method, the wireless network base station positioning ranging method and the radar ranging method.
3. The method for correcting vehicle control operation according to claim 2, wherein the step of coupling the first vehicle operation information obtained by the wheel speed ranging method, the satellite positioning ranging method, the wireless network base station positioning ranging method and the radar ranging method comprises the steps of:
if the vehicle speed is v, the displacement is s, the time is t, and the speed is v, then:
{v n }＝{ds n }/{dt n }；
{ds n }＝(ds 1 ,dS 2 ,…ds n )，{dt n }＝(dt 1 ,dt 2 ,…dt n )；
wherein Δ s >0 when ds ═ v/dt, Δ t > 0;
Δt gps >Δt net ；Δt net >Δt rada ；Δt rada >Δt rps ；Δt rps >0
wherein, Δ t gps Delta t, Delta t for satellite positioning ranging net Δ t, Δ t for positioning ranging of wireless network base stations rada Locating Δ t, Δ t for radar rps Delta t for wheel speed ranging;
Δs gps >Δs net ；Δs net >Δs rada ；Δs rada >Δs rps ；Δs rps >0；
wherein, Δ s gps Delta s for satellite positioning ranging net Delta s, Delta s for positioning and ranging of wireless network base station rada Δ s, Δ s for radar location ranging rps Δ s for wheel speed ranging;
assuming that the acceleration of the vehicle is a and the speed change of the vehicle is Δ v, then:
{Δv}＝{a}·Δt；
wherein, Δ t is a time period;when { Δ t } gps }≈{Δt m }≈{Δt rps In time:
Figure FDA0003605631620000021
Figure FDA0003605631620000031
v gps is equivalent to v net Is equivalent to v rada Is equivalent to v rps ；
Wherein v is gps V, v for satellite positioning ranging net Positioning ranging v, v for wireless network base station rada V, v for radar location ranging rps And v is the distance measurement of the wheel speed.
4. The vehicle control action correcting method according to claim 3, wherein the step of coupling the vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information to obtain the corrected coupling parameter comprises the steps of:
coupling the first vehicle operation information, second vehicle operation information, the vehicle basis information, the vehicle control information, and the feedback information.
5. The vehicle control action correction method according to claim 4, wherein the coupling of the first vehicle operation information, the second vehicle operation information, the vehicle basic information, the vehicle control information and the feedback information comprises the steps of:
based on the vehicle control action information in the vehicle control information, the vehicle control action feedback information and the time position relation feedback information in the feedback information, calculating a control action factor and a feedback factor, wherein the calculation formula is as follows:
F(t)＝[P control +P feedback +P couple ]×η×ρ；
η＝F″(t)·{B}·P step ，ρ＝F″′(t)·{B}·γ；
wherein F is the acting force between the vehicle and the ground; p is control Information of vehicle control actions; p feedback Feeding back information for controlling the vehicle; p couple The time position relation feedback information is obtained, eta represents a vehicle control action factor, and rho represents a feedback correction factor; the time position relation refers to the relation between time and displacement;
wherein, P step To control the minimum step size, γ is the correction period:
Figure FDA0003605631620000041
6. the vehicle control action correction method according to claim 5, wherein the calculating of the control action factor and the feedback factor comprises the steps of:
when the control action factor and the feedback factor are not calculated according to the data resolution and the control minimum step size, then:
Figure FDA0003605631620000042
and ρ ═ F' "(t) · { B }. γ.
7. The vehicle control action correction method according to claim 6, wherein the calculating of the control action factor and the feedback factor comprises the steps of:
when the control action factor and the feedback factor are calculated according to the data resolution and the control minimum step size, then:
Figure FDA0003605631620000043
wherein the content of the first and second substances,
Figure FDA0003605631620000044
is less thanParametric probabilistic wave function of data resolution.
8. The vehicle control action correction method according to claim 7, further comprising, before the coupling the first vehicle operation information, the second vehicle operation information, the vehicle basic information, the vehicle control information, and the feedback information:
acquiring the vehicle basic information and the environment information, wherein the vehicle basic information comprises the mass and the acceleration of the vehicle and the positive pressure between the vehicle and the road surface, and the environment information comprises the road surface gradient, the slope speed coefficient and the dynamic friction coefficient;
using acceleration information a in the second vehicle operation information n And calculating the acting force of the vehicle and the ground, and the ratio of the friction force to the acting force of the vehicle and the road surface as follows:
{F n }＝{a n m, and
Figure FDA0003605631620000051
{N n }＝{G×m×cosθ}·{k n }；
wherein, F n The acting force of the vehicle and the road surface is m, the mass of the vehicle is a, the acceleration of the vehicle is a, the positive pressure of the vehicle and the road surface is N, cos theta is the gradient of the road surface, k is the coefficient of slope speed, mu is the coefficient of dynamic friction, and G is the acceleration of gravity.
9. A car control action correcting device is characterized by comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring vehicle operation information, vehicle basic information, vehicle control information and corresponding environment information which are output by multiple observation angle sensing, and feedback information of a process of controlling the vehicle and the environment; the method is specifically used for:
obtaining first vehicle operation information by wheel rotating speed ranging, satellite positioning ranging, wireless network base station positioning ranging and radar ranging methods; acquiring second vehicle running information, the vehicle basic information, the vehicle control information and the feedback information by a vehicle-mounted sensing method, an axle load sensing method and a time position sensing method;
the calculation module is used for calculating coupling parameters by utilizing the vehicle running information, the vehicle basic information, the vehicle control information and the corresponding environment information, and the feedback information; the method is specifically used for:
setting an algorithm of the vehicle control action model as f' (t) × (AomebB) 0 )；
Coupling the vehicle operation information, vehicle base information, vehicle control information and feedback information to obtain a corrected coupling parameter:
Figure FDA0003605631620000052
circularly correcting the algorithm of the vehicle control action model by using the coupling parameters;
wherein the algorithm of the modified vehicle control action model is f (t) n-1 )×(A∪B n-1 ) The derived parameter is Bn; a is the vehicle running information, the vehicle basic information, the vehicle control information and the feedback information; when n approaches infinity, { B n The convergence is on lambda, which is the true value;
the correction module is used for adjusting historical vehicle control action information based on the coupling parameters so as to correct the vehicle control action of the vehicle;
the vehicle operation information includes the first vehicle operation information and the second vehicle operation information; .
10. An electronic device, comprising a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the processor is configured to execute the computer program stored in the memory to realize the operations performed by the method for correcting a controlling action according to any one of claims 1 to 8.
11. A storage medium, wherein at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement the operation performed by the method for correcting vehicle control action according to any one of claims 1 to 8.
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