Control method and device for emergency braking of a vehicle and vehicle

Abstract

The application discloses a control method and device for emergency braking of a vehicle and the vehicle. The method comprises the following steps: obtaining driving data of a vehicle driving in front of a target vehicle; determining an expected displacement of a brake lever in the target vehicle at a current time based on the driving data; determining control data of the target vehicle at a future time based on the expected displacement and an actual displacement of the brake lever at the current time; and controlling the target vehicle to drive at the future time based on the control data. The application solves the technical problem of poor control effect of emergency braking of the vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent auxiliary driving of vehicles, in particular to a control method and device of emergency braking of a vehicle and the vehicle. BACKGROUND

[0002] At present, the emergency braking system of a vehicle generally uses a vehicle-mounted sensor (such as a millimeter wave radar, a vehicle-mounted camera, etc.) to perceive the motion state of other positional driving obstacles (such as pedestrians, various vehicles, etc.), generally reminds the driver to brake in a pre-warning manner, and in the case that the pre-warning is invalid or in an emergency, the system automatically and forcibly brakes to enable the vehicle to realize autonomous avoidance of collision with the obstacles.

[0003] In the prior art, the emergency braking system only considers emergency braking when the vehicle detects that the distance between the vehicle and the obstacles reaches a certain limit, and ignores the determination of the longitudinal displacement of the brake lever for controlling the braking of the vehicle through the current vehicle speed and other information, and therefore, there is the technical problem of poor control effect of the emergency braking of the vehicle. SUMMARY

[0004] The embodiments of the present application provide a control method and device of emergency braking of a vehicle and the vehicle to at least solve the technical problem of poor control effect of the emergency control of the vehicle.

[0005] According to an aspect of the embodiments of the present application, a control method of emergency braking of a vehicle is provided, including: obtaining driving data of a vehicle driving in front of a target vehicle; determining an expected displacement of a brake lever in the target vehicle at a current time based on the driving data; determining control data of the target vehicle at a future time based on the expected displacement and an actual displacement of the brake lever at the current time; and controlling the target vehicle to drive at the future time based on the control data.

[0006] Optionally, the determination of the control data of the target vehicle at the future time based on the expected displacement and the actual displacement of the brake lever at the current time includes: determining difference data between the expected displacement and the actual displacement based on the obtained expected displacement and actual displacement, wherein the difference data is used to represent the difference degree between the expected displacement and the actual displacement; and determining the control data based on the difference data and the expected displacement.

[0007] Optionally, the determination of the control data based on the difference data and the expected displacement includes: obtaining state data of an electric cylinder in the target vehicle, wherein the state data is used to represent the working state of the electric cylinder in the target vehicle; and determining the control data based on the state data, the difference data and the expected displacement.

[0008] Optionally, the control data is determined based on the state data, the difference data and the expected displacement, including: in response to the state data indicating that the electric cylinder is in a normal working state, and the difference data being greater than or equal to a difference threshold, and the expected displacement being greater than or equal to a displacement threshold, the control data is determined based on an output displacement of the electric cylinder at the current time.

[0009] Optionally, the control data is determined based on the output displacement of the electric cylinder at the current time, including: polynomial fitting is performed on historical output displacements of the electric cylinder and historical longitudinal displacements of the brake lever, to obtain first fitting coefficients; and the output displacement of the electric cylinder at the current time is fitted according to the first fitting coefficients, to obtain the control data.

[0010] Optionally, the control data is determined based on the state data, the difference data and the expected displacement, including: in response to the state data indicating that the electric cylinder is in an abnormal working state, and the difference data being greater than or equal to a difference threshold, and the expected displacement being greater than or equal to a displacement threshold, the control data is determined based on an output angle of the electric motor in the target vehicle at the current time.

[0011] Optionally, the control data is determined based on the output angle of the electric motor in the target vehicle at the current time, including: polynomial fitting is performed on historical output angles of the electric motor and historical longitudinal displacements of the brake lever, to obtain second fitting coefficients; and the output angle of the electric motor at the current time is fitted according to the second fitting coefficients, to obtain the control data.

[0012] Optionally, historical driving data of a vehicle driving in front of the target vehicle and historical longitudinal displacements of the brake lever of the target vehicle in multiple traffic scenarios are obtained; and the historical driving data and the historical longitudinal displacements of the brake lever are used as training data to train a target model, where the target model is used to process the driving data to obtain the expected displacement.

[0013] According to another aspect of the embodiment of the present application, a control device for vehicle emergency braking is also provided, including: an obtaining unit configured to obtain driving data of a vehicle driving in front of a target vehicle; a first determining unit configured to determine control data of the target vehicle at a future time based on an expected displacement and an actual displacement of a brake lever at the current time; and a control unit configured to control the target vehicle to drive at the future time based on the control data.

[0014] According to another aspect of the embodiment of the present application, a computer readable storage medium is also provided. The computer readable storage medium includes a stored program, where the program, when executed, controls a device in which the computer readable storage medium is located to perform the control method for vehicle emergency braking of the embodiment of the present application.

[0015] According to another aspect of the embodiments of the present application, a processor is also provided. The processor is configured to run a program, wherein the program is configured to perform the method for controlling vehicle emergency braking according to the embodiments of the present application.

[0016] According to another aspect of the embodiments of the present application, a vehicle is also provided. The vehicle is configured to perform the method for controlling vehicle emergency braking according to the embodiments of the present application.

[0017] In the embodiments of the present application, the driving data of the vehicle driving in front of the target vehicle is acquired; the expected displacement of the brake lever in the target vehicle at the current time is determined based on the driving data; the control data of the target vehicle at the future time is determined based on the expected displacement and the actual displacement of the brake lever at the current time; and the target vehicle is controlled to drive at the future time based on the control data. That is, the embodiments of the present application determine the expected displacement by the driving data of the vehicle driving in front of the target vehicle, acquire the actual displacement of the brake lever of the target vehicle at the current time, determine the gap between the expected displacement and the actual displacement of the target vehicle, and determine the control data of the target vehicle. Since the driving data of the vehicle is converted into the longitudinal displacement of the brake lever of the vehicle, the technical problem of poor control effect of vehicle emergency braking is solved, and the technical effect of improving the control effect of vehicle emergency braking is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and serve to explain the present application. In the drawings:

[0019] Figure 1 is a flowchart of a method for controlling vehicle emergency braking according to an embodiment of the present application;

[0020] Figure 2 is a schematic diagram of a circuit connection of a vehicle dual-redundant auxiliary braking device according to an embodiment of the present application;

[0021] Figure 3 is a schematic diagram of an internal structure of a vehicle dual-redundant auxiliary braking device according to an embodiment of the present application;

[0022] Figure 4 is a schematic diagram of an external overall structure of a vehicle dual-redundant auxiliary braking device according to an embodiment of the present application;

[0023] Figure 5 is a flowchart of a method for controlling vehicle dual-redundant auxiliary braking according to an embodiment of the present application;

[0024] Figure 6 is a schematic diagram of a control device for vehicle emergency braking according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to better understand the technical scheme of the present application, the technical scheme in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of the present application.

[0026] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described accompanying drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0027] Embodiment 1

[0028] According to the embodiments of the present application, an embodiment of a control method for vehicle emergency braking is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that herein.

[0029] Figure 1 is a flowchart of a control method for vehicle emergency braking according to an embodiment of the present application, as shown in Figure 1 The method can include the following steps:

[0030] Step S102, obtaining driving data of a vehicle driving in front of a target vehicle.

[0031] In the technical scheme provided by step S102 of the present application, during driving of the target vehicle, driving data of a vehicle driving in front of the target vehicle is obtained, wherein the vehicle driving in front of the target vehicle can be a vehicle in the same lane in front of the target vehicle, and the driving data can be used to represent the driving state of the vehicle, such as including the distance between the front vehicle and the target vehicle, the speed and the acceleration, etc. It should be noted that this is only an example and the driving data is not specifically limited.

[0032] For example, the position information of the target vehicle and the vehicle in front of the target vehicle can be acquired to determine the lanes in which the target vehicle and the vehicle in front of the target vehicle are located, and further to determine whether the vehicle in front of the target vehicle is in the same lane as the target vehicle. If yes, the driving data of the vehicle in front of the target vehicle can be further detected; if no, the detection of the vehicle in front of the target vehicle can be abandoned, and the position information of other vehicles can be detected.

[0033] For another example, the driving data of the vehicle in front of the target vehicle during the driving of the target vehicle can be detected by the sensors installed on the target vehicle.

[0034] In step S104, the expected displacement of the brake lever in the target vehicle at the current time is determined based on the driving data.

[0035] In the technical solution provided in step S104, the driving data of the target vehicle and the vehicle in front of the target vehicle can be acquired to determine the relative driving data of the two vehicles. Based on the relative driving data of the two vehicles, the expected displacement of the brake lever in the target vehicle at the current time can be determined, wherein the expected displacement can be the ideal longitudinal displacement of the brake lever in the target vehicle at the current time.

[0036] For example, the speed and acceleration of the target vehicle, the speed and acceleration of the vehicle in front of the target vehicle, and the distance between the two vehicles can be acquired to determine the relative speed and relative acceleration of the two vehicles. Further, the expected displacement of the brake lever in the target vehicle at the current time can be determined based on the relative speed, the relative acceleration, and the distance between the two vehicles. It should be noted that the prediction method or data of the expected displacement is only for illustration, and the determination method based on the driving data should be within the protection scope of the embodiments of the present application, and is not specifically limited herein.

[0037] When the driver drives the target vehicle, the force required to press the brake pedal is different based on different traffic scenarios and driving data, and thus different longitudinal displacements of the brake lever are required. In the embodiments of the present application, the driving data of the target vehicle and the vehicle in front of the target vehicle in different traffic scenarios is acquired, and the longitudinal displacement of the brake lever when the driver drives the target vehicle in the traffic scenario and the relative driving data of the two vehicles is taken as the expected displacement of the brake lever in the target vehicle at the current time, so as to improve the control effect of the vehicle emergency braking.

[0038] In step S106, the control data of the target vehicle at the future time is determined based on the expected displacement and the actual displacement of the brake lever at the current time.

[0039] In the technical solution provided in the step S106 of the present application, the actual displacement of the target vehicle at the current time and the ideal expected displacement of the brake lever are obtained, and based on the actual displacement and the expected displacement, the control data of the target vehicle at the future time can be determined, wherein the actual displacement can be the displacement of the brake lever caused by the driver stepping on the brake pedal at the current time, and the control data can be used to control the target vehicle to travel, for example, to control the change amount of the longitudinal displacement of the brake lever, and the like, which is not limited here.

[0040] Optionally, the expected displacement is compared with the actual displacement of the brake lever at the current time, and based on the comparison result, the control data of the target vehicle at the future time can be determined.

[0041] In the technical solution provided in the step S108 of the present application, the control data can be determined based on the expected displacement and the actual displacement of the brake lever at the current time, and the target vehicle can be controlled to travel at the future time based on the control data.

[0042] In the technical solution provided in the step S108 of the present application, the control data can be determined based on the expected displacement and the actual displacement of the brake lever at the current time, and the target vehicle can be controlled to travel at the future time based on the control data.

[0043] For example, the longitudinal movement displacement of the brake lever of the target vehicle can be controlled based on the control data, so as to control the braking of the target vehicle at the future time.

[0044] In the embodiment of the present application, the travel data of the vehicle traveling in front of the target vehicle is obtained, the expected displacement of the brake lever of the target vehicle at the current time is determined based on the travel data, the control data of the target vehicle at the future time is determined based on the expected displacement and the actual displacement of the brake lever at the current time, and the target vehicle is controlled to travel at the future time based on the control data. That is, in the embodiment of the present application, the expected displacement is determined based on the travel data of the vehicle traveling in front of the target vehicle, the actual displacement of the brake lever of the target vehicle at the current time is obtained, the difference between the expected displacement and the actual displacement of the target vehicle is determined, and the control data of the target vehicle can be determined. Since the travel data of the vehicle is converted into the longitudinal displacement of the brake lever of the vehicle, the technical problem of poor control effect of vehicle emergency braking is solved, and the technical effect of improving the control effect of vehicle emergency braking is achieved.

[0045] The above method of the embodiment will be further introduced below.

[0046] As an optional embodiment, in step S102, the historical travel data of the vehicle traveling in front of the target vehicle and the corresponding historical longitudinal displacement of the brake lever of the target vehicle under multiple traffic scenarios are obtained, and the historical travel data and the historical longitudinal displacement of the brake lever are used as training data to train a target model, wherein the target model is used to process the travel data to obtain the expected displacement.

[0047] In this embodiment, when the target vehicle drives in different traffic scenarios, the historical driving data of the vehicle in front of the target vehicle and the historical displacement of the brake lever of the target vehicle can be obtained, the historical driving data and the historical displacement of the brake lever are used as input data of the model to train the model, and a target model is obtained, wherein the target model can be used to process the driving data to obtain the expected displacement, and the target model can be a neural network model. It should be noted that the target model can also include a mapping relationship between the driving data and the longitudinal displacement of the brake lever to achieve the purpose of determining the expected displacement based on the target model. As long as the processing method for operating the driving data to obtain the expected displacement of the brake lever is within the protection scope of the present application.

[0048] When the driver drives the target vehicle, even if the historical driving data of the vehicle in front of the target vehicle obtained in different traffic scenarios is the same, the historical displacement of the brake lever will be different because the driving risk is different in different traffic scenarios. In the embodiment of the present application, the required displacement of the brake lever in different traffic scenarios is determined by classifying the traffic scenarios, thereby improving the control effect of the vehicle emergency braking.

[0049] Optionally, the historical driving data of the target vehicle and the vehicle driving in front of the target vehicle can be obtained, and the current traffic scenario of the target vehicle can be collected, and the historical displacement of the brake lever obtained by the driver operating the brake pedal can be obtained. The relative historical driving data of the two vehicles can be determined, and the historical relative driving data and the historical displacement of the brake lever can be used as training data to train the target model, wherein the traffic scenario can include road conditions and weather conditions, etc. For example, the road conditions can be smooth, slow and congested; the weather conditions can be sunny, foggy, rainy and snowy, etc. It should be noted that this is only an example and the traffic scenario is not limited.

[0050] For example, the historical driving data and the historical longitudinal displacement of the brake lever of the target vehicle driven by the driver in different traffic scenarios can be collected, and a table can be used for recording, and the historical relative driving data and the historical longitudinal displacement of the brake lever can be used as input data of the model to train the model to obtain the target model.

[0051] For another example, the trained neural network model can be divided into three layers, such as an input layer, a hidden layer and an output layer, wherein the input layer is the input relative driving data of the target vehicle and the vehicle driving in front of the target vehicle, the output layer is the output longitudinal displacement of the brake lever of the target vehicle, and the hidden layer is a transition layer between the input layer and the output layer. The value of the hidden layer can be calculated by the following formula:

[0052]

[0053] Hk For the output of the hidden layer, ω ik x represents the weights between the input layer and the hidden layer. i For the input data of the neural network model, a j is the threshold of the j-th hidden layer neuron.

[0054] Furthermore, Therefore, the output layer value can be calculated using the following formula:

[0055]

[0056] Among them, O j For the output of the output layer, H k For the output of the hidden layer, ω kj b represents the weights between the hidden layer and the input layer. k is the threshold of the k-th output layer neuron.

[0057] As an optional embodiment, step S106, based on the expected displacement and the actual displacement of the brake lever at the current moment, determines the control data of the target vehicle at a future moment, including: determining the difference data between the expected displacement and the actual displacement based on the acquired expected displacement and the actual displacement; and determining the control data based on the difference data and the expected displacement.

[0058] In this embodiment, by obtaining the expected displacement and the actual displacement, the difference data between the two can be determined. Based on the difference data and the expected displacement, control data can be determined. The actual displacement can be the longitudinal displacement of the brake lever generated when the driver depresses the brake pedal at the current moment. The difference data is used to characterize the degree of difference between the expected displacement and the actual displacement.

[0059] Optionally, based on the obtained expected displacement and the actual displacement of the brake lever at the current moment, the difference data can be calculated using the following formula:

[0060]

[0061] Where k represents the difference data, p p p is the desired displacement of the brake lever. a This represents the actual displacement of the brake lever.

[0062] As an optional embodiment, step S106, determining control data based on difference data and desired displacement, includes: acquiring state data of the electric cylinder in the target vehicle, wherein the state data is used to characterize the working state of the electric cylinder in the target vehicle; and determining control data based on the state data, difference data, and desired displacement.

[0063] In this embodiment, the state data of the electric cylinder in the target vehicle is acquired, and based on the state data, the difference data and the expected displacement, the control data can be determined, wherein the state data is used to represent the working state of the electric cylinder in the target vehicle, such as the electric cylinder speed, load, thrust and maximum acceleration data, and it should be noted that this is only an example and the state data is not limited.

[0064] Optionally, the state data interval of the working state set by the electric cylinder when it is factory is acquired, and by detecting the state data of the electric cylinder in real time, it is determined whether the state data is within the state data interval of the normal state, if yes, it is determined that the working state of the electric cylinder is normal, and further, the control data can be determined by the state data of the electric cylinder at this time, the difference data and the expected displacement; if not, it is determined that the working state of the electric cylinder is abnormal, and the backup electric motor can be used for work, the state data of the electric motor at this time is detected, and further, the control data can be determined by the state data of the electric motor at this time, the difference data and the expected displacement.

[0065] For example, the speed range of the electric cylinder in the normal state is between 0.1-2m / s, and if the speed of the electric cylinder detected at this time is 1m / s, it is determined that the speed is within the speed range of the normal state, and it is determined that the working state of the electric cylinder at this time is normal, and further, the control data can be determined.

[0066] As an optional embodiment, in step S106, based on the state data, the difference data and the expected displacement, the control data is determined, including: in response to the state data representing that the electric cylinder is in a normal working state, and the difference data is greater than or equal to the difference threshold value, and the expected displacement is greater than or equal to the displacement threshold value, the control data is determined based on the output displacement of the electric cylinder at the current time.

[0067] In this embodiment, when the working state of the electric cylinder is normal, and the difference data is greater than or equal to the difference threshold value, and the expected displacement is greater than or equal to the displacement threshold value, the output displacement of the electric cylinder at the current time is acquired, and the control data can be determined based on the output displacement of the electric cylinder at the current time, the difference data and the expected displacement, wherein the displacement threshold value is related to the maximum value of the longitudinal displacement of the brake lever of the target vehicle, and can be half of the maximum value of the longitudinal displacement of the brake lever (i.e. half of the position corresponding to the maximum braking force of the brake lever), the maximum value of the longitudinal displacement of the brake lever is related to the length of the brake lever made when the target vehicle is factory, and the difference threshold value can be a value preset according to actual needs, and the difference data can be a difference coefficient.

[0068] For example, the difference threshold can be 0.2. If the maximum longitudinal displacement of the target vehicle's brake lever is 20cm, then the displacement threshold is 10cm. When the electric cylinder is in normal working condition, and the difference data is greater than or equal to 0.2, and the expected displacement is greater than or equal to 10cm, then the control data can be determined based on the output displacement of the electric cylinder, the difference data, and the expected displacement. It should be noted that this is only an example and no specific restrictions are placed on the difference threshold and the maximum value of the brake lever's longitudinal displacement.

[0069] As an optional embodiment, step S106, determining control data based on the output displacement of the electric cylinder at the current moment, includes: performing polynomial fitting on the historical output displacement of the electric cylinder and the historical longitudinal displacement of the brake lever to obtain a first fitting coefficient; and fitting the output displacement of the electric cylinder at the current moment according to the first fitting coefficient to obtain control data.

[0070] In this embodiment, the historical output displacement of the electric cylinder and the historical longitudinal displacement of the brake lever under different traffic scenarios are obtained. Polynomial fitting can be performed on the two to obtain the first fitting coefficient, and then the first fitting equation is obtained. The current output displacement and the expected displacement of the electric cylinder are input into the first fitting equation to determine the control data. The historical output displacement of the electric cylinder and the historical longitudinal displacement of the brake lever correspond one-to-one.

[0071] For example, the output displacement of the electric cylinder and the longitudinal displacement of the brake lever can be collected under different traffic scenarios and recorded in a table. The first fitting coefficient can be obtained by inputting the following language in the software matrix laboratory (MATLAB):

[0072] T = [t1, t2, ..., t g ];

[0073] Q1 = [q 11 ,q 12 ,……,q 1g ];

[0074] K1 = polyfit(T,Q,3);

[0075] Where T represents the set of historical output displacements of the electric cylinder, and t1~t g Let q represent the historical output displacements of the electric cylinders under g different traffic scenarios, and let Q1 represent the set of historical longitudinal displacements of the brake lever, where q 11 ~q 1g Let g be the historical longitudinal displacements of the brake levers under different scenarios, and K1 represent the first fitting coefficient. The polyfit function is a polynomial fitting function. Furthermore, we can obtain the first fitting coefficient K1 = [k 10 ,k11 ,k 12 ,k 13 ]。

[0076] It should be noted that this is only an example, and no specific restriction is made on how to determine the first fitting coefficient.

[0077] For example, based on the determined first fitting coefficient, the first fitting equation shown below can be obtained, based on the first fitting equation, the output displacement of the corresponding electric cylinder and the expected displacement can be input to determine the control data:

[0078] Q=k 10 +k 11 T+k 12 T 2 +k 13 T 3

[0079] Wherein, Q represents the control data based on the electric cylinder, T represents the set of output displacement of the electric cylinder.

[0080] As an optional embodiment, step S106, based on the state data, the difference data and the expected data, determining the control data, comprising: in response to the state data for characterizing the electric cylinder in the working state is an abnormal working state, and the difference data is greater than or equal to the difference threshold value, the expected displacement is greater than or equal to the displacement threshold value, based on the output angle of the electric motor in the target vehicle at the current time to determine the control data.

[0081] In this embodiment, when the working state of the electric cylinder is an abnormal state, it can be determined that the electric cylinder is currently invalid, in order to ensure the normal operation of the automatic emergency braking function of the target vehicle, the next work can be carried out by the backup electric motor, when the difference data is greater than or equal to the difference threshold value, and the expected displacement is greater than or equal to the displacement threshold value, the control data can be determined based on the output angle of the electric motor at the current time and the expected displacement.

[0082] Because there is a possibility of failure of some components (such as the failure of the electric cylinder), but the related art does not consider the influence of the failure of some components on vehicle control, there is a technical problem of low safety of vehicle emergency braking, and the embodiment of the application proposes backup redundancy, that is, when the electric cylinder fails, the backup electric motor can replace the electric cylinder to work for vehicle emergency braking, so as to ensure the safe driving of the target vehicle.

[0083] For example, the difference threshold can be 0.3, the maximum value of the longitudinal displacement of the target vehicle brake lever is 20 cm, and the displacement threshold can be 12 cm. When the electric cylinder is in an abnormal state, the following work is performed by the electric motor: when the difference data is greater than or equal to 0.3 and the expected displacement is greater than or equal to 12 cm, the output angle of the electric motor can be obtained, and the control data is determined based on the output angle of the electric motor and the expected displacement. It should be noted that this is only an example and does not limit the difference threshold and the maximum value of the longitudinal displacement of the brake lever.

[0084] As an optional embodiment, in step S106, the control data is determined based on the output angle of the electric motor in the target vehicle at the current time, including: performing polynomial fitting on the historical output angle of the electric motor and the historical longitudinal displacement of the brake lever to obtain a second fitting coefficient; fitting the output angle of the electric motor at the current time according to the second fitting coefficient to obtain the control data.

[0085] In this embodiment, when the working state of the electric cylinder is an abnormal state, the backup electric motor is started to work, the historical output angle of the electric motor and the historical longitudinal displacement of the brake lever under different traffic scenarios are obtained, and the two can be polynomial fitted to obtain a second fitting coefficient, a second fitting equation is further obtained, and the output displacement of the electric motor at the current time, the difference data and the expected displacement are input into the second fitting equation to determine the control data, wherein the historical output angle of the electric motor and the historical longitudinal displacement of the brake lever correspond one by one.

[0086] For example, the output angle of the electric motor and the longitudinal displacement of the brake lever under different traffic scenarios are collected, and a table can be used for recording. The following language is input into matlab to obtain the second fitting coefficient:

[0087]

[0088] Q2=[q 21 ,q 22 ,……,q 2g ];

[0089]

[0090] wherein, represents a set of output angles of the electric motor, wherein is the historical output angle of the electric motor under g different traffic scenarios, Q2 represents a set of longitudinal displacements of the brake lever, wherein q 21 ~ q 2g is the longitudinal displacement of the brake lever under g different scenarios, K2 represents the second fitting coefficient, and further, the second fitting coefficient K2=[k 20 ,k 21,k 22 ,k 23 ]。

[0091] It should be noted that this is only an example, and no specific restrictions are made on how to determine the second fitting coefficient.

[0092] For example, based on the determined second fitting coefficient, the second fitting equation shown below can be obtained, based on the second fitting equation, the output angle of the corresponding motor, the difference data and the expected displacement can be input to determine the control data:

[0093]

[0094] wherein, represents the control data based on the motor, T represents the set of output displacements of the motor, k 20 ~k 23 is the second fitting coefficient.

[0095] In the embodiment of the application, the driving data of the vehicle driving in front of the target vehicle is obtained; the expected displacement of the brake lever in the target vehicle at the current time is determined based on the driving data; the control data of the target vehicle at the future time is determined based on the expected displacement and the actual displacement of the brake lever at the current time; and the target vehicle is controlled to drive at the future time based on the control data. That is, the embodiment of the application determines the expected displacement by the driving data of the vehicle driving in front of the target vehicle, obtains the actual displacement of the brake lever of the target vehicle at the current time, determines the gap between the expected displacement and the actual displacement of the target vehicle, and can determine the control data of the target vehicle. Since the driving data of the vehicle is converted into the longitudinal displacement of the brake lever of the vehicle, the technical problem of poor control effect of vehicle emergency braking is solved, and the technical effect of improving the control effect of vehicle emergency braking is achieved.

[0096] Embodiment 2

[0097] The technical solutions of the embodiments of the application will be illustrated below in combination with preferred embodiments.

[0098] During vehicle driving, there are many situations of vehicle collision with other obstacles. The function of the automatic emergency braking system aims to solve the collision risk when the driver does not perform emergency braking during vehicle driving.

[0099] The automatic emergency braking system in the related art does not consider converting the driving data of the vehicle into the longitudinal displacement of the brake lever of the vehicle, and therefore can only perform urgent emergency braking of the vehicle and cannot achieve the effect of gentle braking of the vehicle within the braking safety distance. Therefore, there is still the technical problem of poor effect of automatic emergency braking of the vehicle.

[0100] In a related technology, a vehicle automatic braking method is disclosed, which obtains a position relationship of a front vehicle relative to a host vehicle, and judges a lane in which the front vehicle is located, when judging that the front vehicle is moving to a lane adjacent to the lane of the host vehicle, calculates a lateral distance of the front vehicle relative to the host vehicle and a heading angle of the front vehicle according to the position relationship, and judges whether the front vehicle has a tendency to merge into the lane of the host vehicle according to the heading angle and the lateral distance, when judging that the front vehicle has the tendency to merge into the lane of the host vehicle, inputs current motion parameters to a pre-trained first safety distance model to obtain a first safety distance parameter, wherein the motion parameters include a current estimated road adhesion coefficient, and controls the front vehicle to brake according to the first safety distance parameter and an actual longitudinal distance between the two vehicles.

[0101] In another related technology, a linear control system and control method with a backup braking system are disclosed, which comprises a brake pedal module, a control module, a wheel module and a brake module; the brake pedal module comprises a brake pedal, a pedal rotation shaft, a connecting rod, a push rod and a pedal simulator; the wheel module comprises a left front wheel, a left rear wheel, a right front wheel and a right rear wheel; the brake module comprises a motor, a transmission device and a brake installed on each wheel; and the control module comprises an electronic control unit, a pedal displacement sensor, a pedal speed sensor and a current regulating module, to realize a vehicle automatic emergency braking system with a backup function.

[0102] However, the above methods do not consider converting the driving data of the vehicle into the longitudinal displacement of the brake lever of the vehicle, and thus there is still the technical problem of poor control effect of the vehicle automatic emergency braking system.

[0103] Based on the above problems, the embodiment of the present application proposes a vehicle automatic emergency braking system, which collects the actual displacement of the brake lever at the current time and the driving data of the vehicle in front of the vehicle during the driving of the vehicle, analyzes the collected driving data of the vehicle in front of the vehicle to determine the expected displacement of the brake lever of the vehicle at the current time, determines the control data required for braking of the vehicle at a future time through the expected displacement and the actual displacement of the brake lever at the current time, and controls the vehicle to drive based on the control data. Since the driving data of the vehicle is converted into the longitudinal displacement of the brake lever of the vehicle, the technical problem of poor braking effect of the vehicle emergency braking is solved.

[0104] Next, the data processing method of the vehicle of the embodiment of the present application is further introduced.

[0105] Figure 2 is a schematic diagram of a vehicle dual-redundant auxiliary braking device circuit connection according to the embodiment of the present application, like Figure 2As shown, the schematic diagram of the device circuit connection can include: intelligent camera 1, signal line 2, first processor 3, second processor 4, electric cylinder controller 5, electric motor controller 3 and vehicle controller 3, wherein the intelligent camera 1 is connected with the first processor 3 and the second processor 4 through the signal line 2 respectively, the first processor 3 is connected with the electric cylinder controller 5 through the signal line 2, the second processor 4 is connected with the electric motor controller 6 through the signal line 2, and the first processor 3 and the second processor 4 are connected with the vehicle controller 33 through the signal line 2 respectively.

[0106] Figure 3 is a schematic diagram of the internal structure of a vehicle dual-redundancy auxiliary braking device according to an embodiment of the application, as shown in the figure, Figure 3 The internal structure of the device can include: brake pedal 7, brake lever 8, fitting box 9, hinged shaft 11, square hole 12, rear fixed plate 13, front fixed plate 14, left fixed bolt 15, right fixed bolt 16, action amplification arm 17, bearing sleeve 18, fixed rotating shaft 19, sleeve ring 20, action lever 21, electric cylinder 22, electric cylinder bottom plate 23, action lever 24, long rack 25, second cylindrical gear 26, support shaft 27, support plate 28, first cylindrical gear 29, output shaft 30, electric motor 31 and electric motor bottom plate 32.

[0107] Figure 4 is a schematic diagram of the external overall structure of a vehicle dual-redundancy auxiliary braking device according to an embodiment of the application, as shown in the figure, Figure 4 The external structure of the device can include: brake pedal 7, brake lever 8, fitting box 9, cover plate 10 and hinged shaft 11.

[0108] Optionally, the connection mode and position relationship between the internal and external components of the device are as follows: the left part of the front side of the assembly box 9 is provided with a hinge shaft 11, the right part of the hinge shaft 11 is connected with the left part of the cover plate 10, the cover plate 10 can rotate around the hinge shaft 11, the lower side of the assembly box 9 is provided with a square hole 12, the bottom end of the brake lever 8 extends from the square hole 12, the top end of the brake lever 8 is fixed with a brake pedal 7, the brake pedal 7 and the brake lever 8 can be directly realized by using the original response assembly on the vehicle, the middle part of the rear side of the brake lever 8 is in contact with the rear fixed plate 13, the middle part of the front side of the brake lever 8 is in contact with the front fixed plate 14, the left and right ends of the front fixed plate 14 are fixedly connected with the rear fixed plate 13 through the left fixed bolt 15 and the right fixed bolt 16 respectively, the right part of the upper side of the rear fixed plate 13 is in contact with the left part of the lower side of the action amplification arm 17, the right end of the action amplification arm 17 is fixed with a bearing sleeve 18, the inner periphery of the bearing sleeve 18 is in contact with the outer periphery of the fixed rotating shaft 19, the rear end of the fixed rotating shaft 19 is fixedly connected with the internal rear side of the assembly box 9, the bearing sleeve 18 can rotate around the fixed rotating shaft 19, the right part of the outer periphery of the action amplification arm 17 is in contact with the inner periphery of the sleeve 20, the outer periphery of the top end of the sleeve 20 is fixedly connected with the bottom end of the action lever 21, the action lever 21 is arranged at the lower power output end of the electric cylinder 22, the upper side of the electric cylinder 22 is fixed with an electric cylinder bottom plate 23, the rear end of the electric cylinder bottom plate 23 is fixedly connected with the internal rear side of the assembly box 9.

[0109] Optionally, the connection mode and position relationship of the motor part inside the device are as follows: the left part of the upper side of the rear fixed plate 13 is in contact with the right part of the lower side of the action lever 24, the left part of the lower side of the action lever 24 is fixedly connected with the top end of the long rack 25, the front part of the long rack 25 is in contact with the rear periphery of the left part of the second cylindrical gear 26, the right end side of the second cylindrical gear 26 is fixedly connected with the support shaft 27, the right end of the support shaft 27 is in contact with the support plate 28, the rear end of the support plate 28 is fixedly connected with the internal rear side of the assembly box 9, the support shaft 27 can rotate relative to the support plate 28, the lower periphery of the right part of the second cylindrical gear 26 is in contact with the upper periphery of the first cylindrical gear 29, the right side of the first cylindrical gear 29 is fixedly connected with the left end of the output shaft 30, the output shaft 30 is arranged at the left power output end of the electric motor 31, the right side of the electric motor 31 is provided with an electric motor bottom plate 32, the rear end of the electric motor bottom plate 32 is fixedly connected with the internal rear side of the assembly box 9.

[0110] Figure 5 is a flow chart of a vehicle dual-redundancy auxiliary braking method according to an embodiment of the application, as shown in Figure 5 , the method can include the following steps:

[0111] Step S502, extract the brake displacement under different scenes.

[0112] In the technical solution provided in the step S502 of the present application, the intelligent camera 1 is fixed at a suitable position of the vehicle and connected with the signal line 2, when the target vehicle is driving, the intelligent camera 1 can collect the driving data of the vehicle in front of the target vehicle, and transmit the driving data to the first processor 3 and the second processor 4 through the signal line 2.

[0113] For example, the intelligent camera is fixedly installed inside the front windshield of the vehicle and connected with the signal line, which is only an example and does not limit the position of the intelligent camera.

[0114] Optionally, if the double-redundant auxiliary braking system shown in Figure 2 With Figure 3 Before the double-redundant auxiliary braking system shown in the prior art, the natural driving data collection work can be performed, the driving data of the vehicle in front of the target vehicle and the longitudinal displacement data of the brake lever 8 in the manual driving condition are collected and recorded, and a data set table 1 can be formed. The data set table 1 is collected in the manual driving condition according to an embodiment of the present application, as shown in table 1, serial numbers 1-g are used to represent different traffic scenes in the driving process of the target vehicle, d1-d g are used to represent the distance between the target vehicle and the vehicle in front of it under different traffic scenes, v1-v g are used to represent the relative speed between the target vehicle and the vehicle in front of it under different traffic scenes, a1-a g are used to represent the relative acceleration between the target vehicle and the vehicle in front of it under different traffic scenes, p1-p g are used to represent the longitudinal displacement of the brake lever of the target vehicle under different traffic scenes.

[0115] Table 1 is a data set collected in the manual driving condition according to an embodiment of the present application

[0116] Serial number 1 2 ... g Front vehicle distance d d1 [d2] ... d g ]]> Front vehicle relative speed v <![CDATA[v2]]> <![CDATA[v2]]> ... v g ]]> Front vehicle relative acceleration a [a1] [a2] ... a g ]]> Brake lever longitudinal displacement p [p2] [p2] ... p g ]]>

[0117] Optionally, based on the data in the above table 1, considering that different traffic scenes will produce different front vehicle distances d, front vehicle relative speeds v and front vehicle relative accelerations a, and then the driver can step on the brake pedal to different degrees according to the different degrees of danger, thereby producing different degrees of brake lever longitudinal displacement corresponding to different brake lever longitudinal displacement p.

[0118] Optionally, by obtaining the data collected in the manual driving condition in table 1, a network model training can be performed, and the network model input x i may include: front vehicle distance d, front vehicle relative speed v and front vehicle relative acceleration a), and then output the brake lever longitudinal displacement p, so as to determine the mapping relationship between the above three driving data and the brake lever longitudinal displacement data.

[0119] Optionally, the process of training the network model can include the following five steps:

[0120] Step 1, by setting the number of nodes of the network input layer, hidden layer and output layer as n=3, m=5 and p=1 respectively, the weight matrix ω ik and ω kj between the layers of the network are initialized, the threshold values of the hidden layer and the output layer are set as vectors a and b respectively, the weight matrix ω ik and ω kj and the vectors a and b are initialized using normal distribution, with mean value set to 0 and variance set to 0.1, through the above steps, the network initialization can be performed, wherein ω ik is used to represent the weight between the i-th input layer neuron and the k-th hidden layer neuron, ω kj is used to represent the weight between the k-th hidden layer neuron and the j-th output layer neuron, in the vector a, a i is used to identify the threshold value of the i-th hidden layer neuron, in the vector b, b j is used to identify the threshold value of the j-th output layer neuron.

[0121] Step 2, the output of the hidden layer can be calculated by the following formula:

[0122]

[0123] wherein, H k is the output of the hidden layer, ω ik is the weight between the input layer and the hidden layer, x i is the input data of the neural network model, q j is the threshold value of the j-th hidden layer neuron.

[0124] Further, the output of the output layer can be calculated by the following formula:

[0125]

[0126] wherein, O j is the output of the output layer, H k is the output of the hidden layer, ω kj is the weight between the hidden layer and the input layer, b k is the threshold value of the k-th output layer neuron.

[0127] Step 3, the network error at each output layer node can be calculated according to the following formula, based on the expected output Y of the network model (i.e. the actual brake lever longitudinal displacement p) and the predicted output O:

[0128] E j = Y j - Oj (j = 1, 2, …, p)

[0129] wherein, E j is the network error at each output layer node, Y j is the expected output of the network model, O j is the output of the output layer, and the total network error of all samples is: (g is the number of training samples, and the expected training accuracy requirement is 0.02), when the network error value is less than 0.02, it is considered that the training is completed, and the loop is ended, otherwise the loop is continued, and step 4 is executed.

[0130] Step 4, the connection weight ω ik and ω kj of the network can be updated through the following formula:

[0131]

[0132] wherein, |ω ik is the updated weight between the input layer and the hidden layer, |ω kj is the updated weight between the hidden layer and the input layer, ω ik is the original weight between the input layer and the hidden layer, ω kj is the original weight between the hidden layer and the input layer, the learning rate η = 0.6, H k is the output of the hidden layer, E j is the network error at each output layer node.

[0133] Step 5, the vector threshold a and b of the network can be updated through the following formula:

[0134]

[0135] wherein, |a k is the updated threshold of the kth hidden layer neuron, |b j is the updated threshold of the jth output layer neuron, and step 2 is re-executed until the network error value is less than 0.02, and the loop is ended.

[0136] Step S504, pedal position mapping relationship fitting.

[0137] In the technical solution provided in the above step S504 of the application, based on the existing brake pedal 7 and brake lever 8 of the vehicle, the brake pedal 7 is installed Figure 2 and Figure 3The different output displacements of the electric cylinder 22 and the different longitudinal displacements of the brake lever 8 corresponding thereto under different traffic scenarios are collected after the installation of each accessory in the dual-redundant auxiliary braking device, wherein the control mode between the electric cylinder and the brake lever can be that the electric cylinder 22 works, the output displacement of the action lever 21 is output, the sleeve ring 20 drives the action amplification arm 17 and the bearing sleeve 18 to rotate counterclockwise around the rotating shaft 19, the left end of the action amplification arm 17 drives the rear fixed plate 13 to move downward, thereby driving the brake lever 8 and the brake pedal 7 to move downward.

[0138] Optionally, Table 2 is a data set based on the output displacement of the electric cylinder and the longitudinal displacement of the brake lever under different traffic scenarios according to an embodiment of the present application, as shown in Table 2, serial numbers 1-g are used to represent different traffic scenarios in the driving process of the target vehicle, t1-t g for representing the output displacement of the electric cylinder under different traffic scenarios, q 11 for representing the output displacement of the electric cylinder under different traffic scenarios, q 1g for representing the longitudinal displacement of the brake lever under different traffic scenarios.

[0139] Table 2 is a data set based on the output displacement of the electric cylinder and the longitudinal displacement of the brake lever under different traffic scenarios according to an embodiment of the present application

[0140] Serial number 1 2 ... f Electric cylinder output displacement [t1] [t2] ... [CAT g ]]> Brake lever longitudinal displacement q 11 ]]> q 12 ]]> ... q 1g ]]>

[0141] Optionally, input in the software matrix laboratory (matrix laboratory, abbreviated as matlab):

[0142] T = [t1, t2,..., t g ];

[0143] Q1 = [q 11 , q 12 ,..., q 1g ];

[0144] K1 = polyfit(T, Q, 3);

[0145] Then, the polynomial fitting coefficient K1 = [k 10 , k 11 , k 12 , k 13 ] can be obtained, and the fitting equation of the longitudinal position of the brake lever 8 corresponding to the different output displacements of the electric cylinder 22 is as follows:

[0146] Q = k 10 T + k 11 T + k 12 T 2 + k 13 T 3

[0147] Wherein, Q is the first fitting equation, T is the output displacement of the electric cylinder. The equation is the first fitting equation, and the first fitting equation can be stored in the first processor 3.

[0148] Optionally, the longitudinal positions of the electric motor 31 at different output angles and the corresponding longitudinal displacement 8 of the brake lever are collected, wherein the control mode between the electric motor and the brake lever is that the electric motor 31 works to output a rotation angle through the output shaft 30, the movement is transmitted to the second cylindrical gear 26 through the first cylindrical gear 29, the rotating second cylindrical gear 26 drives the long rack 25 to displace downward, and the right part of the action lever 24 can push the brake lever 8, and then the brake pedal 7 moves downward.

[0149] Optionally, Table 3 is a data set based on the output angle of the electric motor and the longitudinal displacement of the brake lever under different traffic scenarios according to an embodiment of the application, as shown in Table 3, serial numbers 1-g are used to represent different traffic scenarios in the driving process of the target vehicle, for representing the output angle of the electric motor under different traffic scenarios, q 21 ~q 2g for representing the longitudinal displacement of the brake lever under different traffic scenarios.

[0150] Table 3 is a data set based on the output angle of the electric motor and the longitudinal displacement of the brake lever under different traffic scenarios according to an embodiment of the application

[0151]

[0152] Optionally, input in matlab:

[0153]

[0154] Q2=[q 21 ,q 22 ,……,q 2g ];

[0155]

[0156] Further, the polynomial fitting coefficient K2=[k 20 ,k 21 ,k 22 ,k 23 ] corresponding to the different output angles of the electric motor 31 corresponding to the longitudinal position of the brake lever 8 can be obtained, and the fitting equation is as follows:

[0157]

[0158] Wherein, For the second fitting equation, T is the output displacement of the motor. The equation is the second fitting equation, and the second fitting equation can be stored in the second processor 4.

[0159] Step S506, judge the working condition and auxiliary braking.

[0160] In the technical solution provided by the above step S506 of the application, based on Figure 2 and Figure 3 Install a dual-redundant auxiliary braking system, and the vehicle controller 33 will send the actual brake lever longitudinal displacement p a The intelligent camera 1 sends the front vehicle distance d, the front vehicle relative speed v, and the front vehicle relative acceleration a to the first processor 3 and the second processor 4 through the signal line 2, respectively, and stores the network model trained in step 1 in the first processor 3 and the second processor 4. Then, the first processor 3 and the second processor 4 calculate the expected brake lever longitudinal displacement p p The difference coefficient can be calculated by the following formula:

[0161]

[0162] Where k is the difference coefficient, p a is the actual brake lever longitudinal displacement of the vehicle, p p is the ideal brake lever longitudinal displacement of the vehicle.

[0163] Optionally, when k≥0.2 and p p ≥0.5*p max , where p max corresponds to the maximum value of the brake lever longitudinal displacement of the vehicle (i.e., the position corresponding to the maximum braking force), it can be considered that the current working condition has a high risk of collision and the driver's depression of the brake pedal is not sufficient to ensure safety. The first processor 3 calculates the output displacement size of the electric cylinder 22 required to make the brake lever 8 reach p p according to the first fitting equation, and transmits it to the electric cylinder controller 5 through the signal line 2. Then, the electric cylinder controller 5 controls the electric cylinder 22 to work and output the corresponding displacement, and performs dual-redundant auxiliary braking on the vehicle, thereby avoiding a collision accident with the front vehicle.

[0164] Optionally, considering the failure of the electric cylinder 22, in order to best ensure functional safety, backup redundancy is needed when k≥0.2+Δk and p p ≥0.5*p max +Δp (where Δk represents the coefficient threshold, which can be 0.1, and Δp represents the displacement threshold, which can be 0.1*p max), the second processor 4 calculates p according to the second fitting equation, so that the brake lever 8 reaches the corresponding p p The required motor 31 output angle size, and through the signal line 2 to the motor controller 6, and the motor controller 6 controls the motor 31 work and output corresponding angle, double redundant auxiliary braking effect on the vehicle, avoid the collision accident with the front vehicle.

[0165] Optionally, based on the output displacement or output angle of the electric cylinder or motor, the longitudinal displacement of the brake lever can be determined, and the vehicle is controlled to travel based on the longitudinal displacement of the brake lever.

[0166] The embodiment of the present application collects the actual displacement of the brake lever at the current time and the driving data of the vehicle in front of the vehicle during the driving of the vehicle, analyzes the collected driving data of the vehicle in front of the vehicle, determines the expected displacement of the brake lever of the vehicle at the current time, determines the control data required for braking of the vehicle at the future time through the expected displacement and the actual displacement of the brake lever at the current time, and controls the vehicle to travel based on the control data, thereby solving the technical problem of poor control effect of vehicle emergency braking and achieving the technical effect of improving the control effect of vehicle emergency braking.

[0167] Embodiment 3

[0168] According to the embodiment of the present application, a vehicle emergency braking control device is also provided. It should be noted that the vehicle emergency braking control device can be used to execute the vehicle emergency braking control method in embodiment 1.

[0169] Figure 6 is a schematic diagram of a vehicle emergency braking control device according to an embodiment of the present application. As shown in Figure 6 The vehicle emergency braking control device 600 can include an acquisition unit 602, a first determination unit 604, a second determination unit 606, and a control unit 608.

[0170] The acquisition unit 602 is configured to acquire driving data of a vehicle driving in front of a target vehicle.

[0171] The first determination unit 604 is configured to determine an expected displacement of a brake lever in the target vehicle at a current time based on the driving data.

[0172] The second determination unit 606 is configured to determine control data of the target vehicle at a future time based on the expected displacement and an actual displacement of the brake lever at the current time.

[0173] The control unit 608 is configured to control the target vehicle to travel at the future time based on the control data.

[0174] Optionally, the second determining unit 606 can comprise: a first determining module configured to determine, based on the obtained expected displacement and actual displacement, difference data between the expected displacement and the actual displacement, wherein the difference data is used to represent a difference degree between the expected displacement and the actual displacement; and a second determining module configured to determine, based on the difference data and the expected displacement, the control data.

[0175] Optionally, the second determining module can comprise: a first obtaining sub-module configured to obtain state data of the electric cylinder in the target vehicle, wherein the state data is used to represent a working state of the electric cylinder in the target vehicle; and a first determining sub-module configured to determine, based on the state data, the difference data and the expected data, the control data.

[0176] Optionally, the second determining unit 606 can further comprise: a third determining module configured to, in response to the state data representing that the electric cylinder is in a normal working state and the difference data being greater than or equal to a difference threshold value and the expected displacement being greater than or equal to a displacement threshold value, determine the control data based on an output displacement of the electric cylinder at a current time.

[0177] Optionally, the second determining unit 606 further comprises: a fourth determining module configured to perform polynomial fitting on historical output displacements of the electric cylinder and historical longitudinal displacements of the brake lever to obtain a first fitting coefficient; and a fifth determining module configured to fit the output displacement of the electric cylinder at the current time according to the first fitting coefficient to obtain the control data.

[0178] Optionally, the second determining module 606 further comprises: a sixth determining module configured to, in response to the state data representing that the electric cylinder is in an abnormal working state and the difference data being greater than or equal to a difference threshold value and the expected displacement being greater than or equal to a displacement threshold value, determine the control data based on an output displacement of the electric motor in the target vehicle at a current time.

[0179] Optionally, the second determining module 606 further comprises: a seventh determining module configured to perform polynomial fitting on historical output displacements of the electric motor and historical longitudinal displacements of the brake lever to obtain a second fitting coefficient; and an eighth determining module configured to fit the output displacement of the electric motor at the current time according to the second fitting coefficient to obtain the control data.

[0180] Optionally, the control device of the vehicle emergency braking can further comprise: a first obtaining unit configured to obtain historical driving data of a vehicle driving in front of the target vehicle and historical displacement data of a brake lever of the target vehicle in a plurality of traffic scenarios; and a first determining unit configured to train a target model by taking the historical data and the historical displacement data of the brake lever as training data, wherein the target model is used to process the driving data to obtain the expected displacement.

[0181] According to the embodiment of the present application, the obtaining unit is configured to obtain driving data of a vehicle driving in front of the target vehicle; the first determining unit is configured to determine an expected displacement of a brake lever in the target vehicle at a current time based on the driving data; the second determining unit is configured to determine control data of the target vehicle at a future time based on the expected displacement and an actual displacement of the brake lever at the current time; and the control unit is configured to control the target vehicle to drive at the future time based on the control data, thereby solving the technical problem of poor control effect of vehicle emergency braking and achieving the technical effect of improving the control effect of vehicle emergency braking.

[0182] Embodiment 4

[0183] According to the embodiment of the present application, a computer readable storage medium is also provided, which includes a stored program, wherein the program performs the vehicle emergency braking control method described in the embodiment 1.

[0184] Embodiment 5

[0185] According to the embodiment of the present application, a processor is also provided, which is used to run a program, wherein the program performs the vehicle emergency braking control method described in the embodiment 1 when running.

[0186] Embodiment 6

[0187] According to the embodiment of the present application, a vehicle is also provided, which is used to perform the vehicle emergency braking control method of the embodiment of the present application.

[0188] The above-mentioned embodiment numbers of the present application are only for description, and do not represent the advantages or disadvantages of the embodiments.

[0189] In the above-mentioned embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0190] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be realized by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division way, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0191] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0192] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0193] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical scheme of the present application or the part of the present application which contributes to the prior art or the whole or part of the technical scheme can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various program code storage media.

[0194] The above is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A control method of emergency braking of a vehicle, characterized by, The method comprises: acquiring driving data of a vehicle driving in front of a target vehicle; determining an expected displacement of a brake lever in the target vehicle at a current time based on the driving data; determining control data of the target vehicle at a future time based on the expected displacement and an actual displacement of the brake lever at the current time; controlling the target vehicle to drive at the future time based on the control data; wherein the determination of the expected displacement of the brake lever in the target vehicle at the current time based on the driving data comprises inputting the driving data into a target model to obtain the expected displacement, wherein the target model is trained based on historical driving data of a vehicle driving in front of the target vehicle and historical longitudinal displacement of the brake lever, and the target model at least comprises a mapping relationship between the driving data and the longitudinal displacement of the brake lever; the determination of the control data of the target vehicle at the future time based on the expected displacement and the actual displacement of the brake lever at the current time comprises: acquiring state data of an electric cylinder in the target vehicle, wherein the state data is used to represent the working state of the electric cylinder; in response to the working state of the electric cylinder being a normal state, determining difference data between the expected displacement and the actual displacement based on the acquired expected displacement and actual displacement, wherein the difference data is used to represent the difference between the expected displacement and the actual displacement; determining the control data based on the state data of the electric cylinder, the difference data and the expected displacement; in response to the working state of the electric cylinder being an abnormal state, acquiring state data of an electric motor in the target vehicle, and determining the control data based on the state data of the electric motor, the difference data and the expected displacement.

2. The control method of vehicle emergency braking according to claim 1, characterized in that, determining the control data based on the state data of the electric cylinder, the difference data and the expected displacement comprises: in response to the state data representing that the working state of the electric cylinder is the normal state and the difference data is greater than or equal to a difference threshold value and the expected displacement is greater than or equal to a displacement threshold value, determining the control data based on the output displacement of the electric cylinder at the current time.

3. The control method of vehicle emergency braking according to claim 2, characterized in that, determining the control data based on the output displacement of the electric cylinder at the current time comprises: performing polynomial fitting on the historical output displacement of the electric cylinder and the historical longitudinal displacement of the brake lever to obtain a first fitting coefficient; fitting the output displacement of the electric cylinder at the current time according to the first fitting coefficient to obtain the control data.

4. The control method of vehicle emergency braking according to claim 2, characterized in that, in response to the working state of the electric cylinder being an abnormal state, acquiring state data of an electric motor in the target vehicle, and determining the control data based on the state data of the electric motor, the difference data and the expected displacement comprises: in response to the working state of the electric cylinder being the abnormal state and the difference data being greater than or equal to the difference threshold value and the expected displacement being greater than or equal to the displacement threshold value, determining the control data based on the output angle of the electric motor in the target vehicle at the current time.

5. The control method of vehicle emergency braking according to claim 4, characterized in that, determining the control data based on an output angle of the electric motor in the target vehicle at the current time, comprising: polynomial fitting the historical output angle of the electric motor and the historical longitudinal displacement of the brake lever to obtain a second fitting coefficient; fitting the output angle of the electric motor at the current time according to the second fitting coefficient to obtain the control data.

6. The control method of vehicle emergency braking according to claim 1, characterized by, The method further comprises: obtaining the historical driving data of a vehicle driving in front of the target vehicle and the historical longitudinal displacement of the brake lever of the target vehicle under multiple traffic scenarios; training the target model using the historical driving data and the historical longitudinal displacement of the brake lever as training data, wherein the target model is used to process the driving data to obtain the expected displacement.

7. A control device for emergency braking of a vehicle, characterized by comprising: comprises: an obtaining unit, configured to obtain driving data of a vehicle driving in front of a target vehicle; a first determining unit, configured to determine an expected displacement of a brake lever in the target vehicle at a current time based on the driving data; a second determining unit, configured to determine control data of the target vehicle at a future time based on the expected displacement and an actual displacement of the brake lever at the current time; a control unit, configured to control the target vehicle to drive at the future time based on the control data; wherein the first determining unit is configured to determine the expected displacement of the brake lever in the target vehicle at the current time based on the driving data by inputting the driving data into a target model to obtain the expected displacement, wherein the target model is trained based on historical driving data of a vehicle driving in front of the target vehicle and historical longitudinal displacement of the brake lever, and at least includes a mapping relationship between the driving data and the longitudinal displacement of the brake lever in the target model; the second determining unit is further configured to perform the following steps: obtaining state data of an electric cylinder in the target vehicle, wherein the state data is used to represent a working state of the electric cylinder; in response to the working state of the electric cylinder being a normal state, determining difference data between the expected displacement and the actual displacement based on the obtained expected displacement and actual displacement, wherein the difference data is used to represent a difference degree between the expected displacement and the actual displacement; determining the control data based on the state data of the electric cylinder, the difference data, and the expected displacement; in response to the working state of the electric cylinder being an abnormal state, obtaining state data of an electric motor in the target vehicle, and determining the control data based on the state data of the electric motor, the difference data, and the expected displacement.

8. A vehicle characterized by comprising: A control method for performing emergency braking of a vehicle according to any one of claims 1 to 6. A control method for performing emergency braking of a vehicle according to any one of claims 1 to 6.

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