CN113165615A

CN113165615A - Vehicle control method and device

Info

Publication number: CN113165615A
Application number: CN202180000616.7A
Authority: CN
Inventors: 汪洁; 邹文韬; 李小凯; 杜引
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-03-16
Filing date: 2021-03-16
Publication date: 2021-07-23
Also published as: WO2022193137A1

Abstract

The application provides a vehicle control method and a vehicle control device, belongs to the field of automatic driving or intelligent driving, and is suitable for various vehicles such as traditional automobiles, new energy automobiles and intelligent automobiles, wherein the method comprises the following steps: acquiring information of a target vehicle, wherein the information of the target vehicle comprises movement information of the target vehicle and pressure information of a brake master cylinder of the target vehicle; and sending indication information of target brake deceleration, wherein the indication information of the target brake deceleration is used for indicating the target vehicle to perform brake pressurization on the brake master cylinder, and the target brake deceleration is predicted according to the information of the target vehicle. The method can provide proper braking deceleration, better accords with the subjective intention of a driver, and improves the user experience in the vehicle braking process.

Description

Vehicle control method and device

Technical Field

The present application relates to the field of vehicle control, and in particular, to a vehicle control method and apparatus.

Background

Under the emergency braking working condition, if the driver has the problems of insufficient driving experience, insufficient response speed, insufficient pedal force or inaccurate danger judgment and the like, the braking distance of the vehicle is too long, and the possibility of vehicle collision is increased. In order to avoid a collision, an Emergency Brake Assist (EBA) system on a vehicle can perform emergency braking on the vehicle when a current driving state is in a dangerous state. The emergency braking assistance system actively boosts pressure after recognizing an emergency braking condition. Therefore, the pressure can be reduced more quickly, the braking sliding distance of the vehicle is greatly reduced, and the vehicle is prevented from colliding as much as possible.

However, the emergency braking assistance system on the vehicle does not consider the braking requirement of the driver when performing emergency braking, but outputs a preset braking force to perform braking, so that the user experience is poor, and even a potential safety hazard exists. For example, in a non-emergency braking scene such as an intersection or a parking lot, if a driver suddenly steps on a brake pedal with a large force, the emergency braking assistance system may misinterpret the situation as an emergency braking condition, and further falsely trigger the emergency braking assistance function to provide unnecessary deceleration for the vehicle. Unnecessary deceleration or excessive deceleration do not accord with the subjective intention of the driver, so that the user experience is reduced, and even potential safety hazards such as rear-end collision of a rear vehicle and the like may exist.

Therefore, how to improve the user experience in the vehicle braking process becomes an urgent problem to be solved.

Disclosure of Invention

The application provides a vehicle control method and device, which can provide proper braking deceleration, better meet the subjective intention of a driver and improve the user experience in the vehicle braking process.

In a first aspect, a vehicle control method is provided, including: acquiring information of a target vehicle, wherein the information of the target vehicle comprises movement information of the target vehicle and pressure information of a brake master cylinder of the target vehicle; and sending indication information of target brake deceleration, wherein the indication information of the target brake deceleration is used for indicating the target vehicle to perform brake pressurization on the brake master cylinder, and the target brake deceleration is predicted according to the information of the target vehicle.

According to the scheme of the embodiment of the application, the information of the target vehicle before active pressurization is obtained by the driver in the natural driving process, and the subjective intention of the driver can be reflected. The target braking deceleration is predicted through the information of the target vehicle before active pressurization, the braking intention of a driver can be accurately quantized, the braking process of the vehicle is made to accord with the subjective intention of the driver, and the user experience and the driving safety are improved. In addition, the target braking deceleration is predicted through the motion information of the target vehicle and the pressure information of the brake master cylinder, so that the target braking deceleration can better accord with the braking intention of the driver, the prediction accuracy is further improved, the braking process of the vehicle can better accord with the subjective intention of the driver, and the user experience and the driving safety are further improved. In addition, the scheme of the embodiment of the application does not depend on hardware devices such as a pedal position sensor, a pedal simulator or a brake-by-wire system and the like, so that the hardware cost is saved.

For example, the indication information of the target braking deceleration may include the target braking deceleration itself or information that can be used to obtain the target braking deceleration, for example, the indication information of the target braking deceleration may be a difference value between the target braking deceleration and the current braking deceleration, and the application is not particularly limited.

The motion information of the vehicle refers to information related to a motion state of the vehicle. For example, the motion information of the target vehicle includes at least one of: the speed of the target vehicle, the acceleration of the target vehicle, or the like.

The pressure information of the master cylinder refers to information related to the pressure of the master cylinder. For example, the pressure information of the master cylinder includes at least one of: the pressure gradient of the master cylinder, the pressure of the master cylinder, etc.

Brake deceleration refers to the ratio of the amount of change in speed after braking to the time it takes for the change in speed to occur.

With reference to the first aspect, in certain implementations of the first aspect, the target braking deceleration is determined based on a first braking deceleration that is obtained by processing information of the target vehicle through a braking deceleration prediction model.

The brake deceleration prediction model is used for predicting a first brake deceleration according to the information in the input model. For example, the brake deceleration prediction model predicts the first brake deceleration based on the input information of the target vehicle.

The first brake deceleration is the brake deceleration requested by the driver.

Illustratively, the braking deceleration prediction model may be a neural network model, such as a Recurrent Neural Network (RNN) model.

Illustratively, the target braking deceleration is a first braking deceleration.

In the scheme of the embodiment of the application, the neural network model can be used as a braking deceleration prediction model, the braking deceleration model is trained based on data collected in the natural driving process, the braking deceleration requested by the driver is predicted through the trained braking deceleration model, and the strong characteristic expression capability of the neural network model can improve the prediction accuracy of the braking deceleration requested by the driver.

With reference to the first aspect, in certain implementations of the first aspect, the brake deceleration prediction model is trained based on at least one training sample, the training sample including information of the training vehicle and a sample label of the training sample, the information of the training vehicle including motion information of the training vehicle and pressure information of a brake master cylinder of the training vehicle, the sample label of the training sample indicating a brake deceleration requested by a driver of the training vehicle.

The at least one training sample is derived from natural driving test data.

The natural driving test data is brake data during a brake operation performed by the driver obtained without active boosting of a system such as an emergency brake assist system.

With reference to the first aspect, in certain implementations of the first aspect, the method further includes: acquiring environment perception information of a target vehicle; wherein the target braking deceleration is predicted based on information of the target vehicle and the environmental awareness information of the target vehicle.

Further, the first braking deceleration is obtained by processing the information of the target vehicle and the environment perception information of the target vehicle by the braking deceleration prediction model.

In this case, the training samples may include information of the training vehicle, environmental perception information of the training vehicle, and sample tags of the training samples.

According to the embodiment of the application, the environment perception information of the training vehicle is used for training the model, so that the model can judge whether the driver needs emergency braking or not based on actual collision risk, and the accuracy of the prediction model is improved. Correspondingly, in the reasoning process, the environment perception information of the target vehicle is also used as the input of the model, so that the braking result can better meet the subjective will of the driver, and the user experience and the safety are improved.

With reference to the first aspect, in certain implementations of the first aspect, the pressure information of the brake master cylinder of the target vehicle includes a pressure slope of the brake master cylinder of the target vehicle that is greater than or equal to a first threshold value before the sending of the information indicative of the target brake deceleration.

With reference to the first aspect, in certain implementations of the first aspect, the motion information of the target vehicle includes a speed of the target vehicle, and the first threshold is determined according to the speed of the target vehicle.

With reference to the first aspect, in certain implementations of the first aspect, the target braking deceleration is determined according to a second braking deceleration, the second braking deceleration is obtained by processing the first braking deceleration by a target gain factor, and the target gain factor has a mapping relationship with the risk level of the current driving scenario.

Illustratively, the target gain factor is determined by mapping relationships between the plurality of gain factors and the risk levels of the plurality of driving scenes and the risk level of the current driving scene. The target gain factor is one of a plurality of gain factors.

In one implementation, the higher the hazard level, the lower the probability of a vehicle collision, and the smaller the corresponding gain factor. In this case, the risk level can also be understood as a safety level.

In another implementation, the higher the hazard level, the greater the probability of the vehicle colliding, and the greater the corresponding gain factor.

The danger level of the driving scene is determined based on the information of the vehicle and the environmental perception information of the vehicle.

Specifically, the risk discrimination indicator may be calculated according to the motion information of the vehicle and the environment perception information of the vehicle, and the risk level may be determined according to the risk discrimination indicator.

Illustratively, the target braking deceleration is a second braking deceleration.

According to the scheme of the embodiment of the application, the first braking deceleration is correspondingly processed according to the gain coefficient corresponding to the danger level of the current driving scene, the graded braking can be realized based on different danger levels, and the driving safety of the vehicle is improved.

With reference to the first aspect, in certain implementations of the first aspect, in a case that the risk level is greater than or equal to the first level threshold, the gain coefficient corresponding to the risk level is greater than 1.

That is, the first brake deceleration is subjected to the amplification process in the case where the risk level is greater than or equal to the first level threshold value.

The gain factors corresponding to the different hazard levels may be predetermined. Alternatively, the mapping relationship between the gain coefficients and the risk levels may be predetermined.

Through the scheme of the embodiment of the application, under the condition that the danger level is high, the first braking deceleration is amplified, and the driving safety is further improved.

With reference to the first aspect, in certain implementations of the first aspect, the hazard level of the current driving scenario is greater than or equal to the second level threshold before the information indicative of the target brake deceleration is transmitted.

With reference to the first aspect, in certain implementations of the first aspect, the target braking deceleration is determined based on one of the second braking deceleration and a safer braking deceleration, which is used to indicate a braking deceleration required by the target vehicle to avoid the collision, being larger in absolute value.

Specifically, the safe braking deceleration is a braking deceleration required to avoid the occurrence of the collision, which is determined based on the motion information of the target vehicle and the environment perception information of the target vehicle.

Alternatively, the target braking deceleration is one of the second braking deceleration and the safety braking deceleration, the absolute value of which is large.

Alternatively, the target braking deceleration is a smaller value between the one having the larger absolute value and the braking deceleration threshold value.

Illustratively, the brake deceleration threshold is determined by the ABS.

According to the embodiment of the application, the safe braking deceleration is determined through the motion information of the target vehicle and the environment perception information of the target vehicle, and the target braking deceleration is determined according to the one of the safe braking deceleration and the second braking deceleration with a larger absolute value, so that the collision risk can be effectively avoided on the premise that the subjective intention of a driver is met as much as possible, and the driving safety is further improved.

In a second aspect, there is provided a vehicle control apparatus comprising: an acquisition unit configured to acquire information of a target vehicle, the information of the target vehicle including movement information of the target vehicle and pressure information of a brake master cylinder of the target vehicle; and a transmitting unit for transmitting indication information of a target braking deceleration for indicating that the target vehicle performs brake boosting on the brake master cylinder, the target braking deceleration being predicted from information of the target vehicle.

With reference to the second aspect, in certain implementations of the second aspect, the target braking deceleration is determined based on a first braking deceleration that is obtained by processing information of the target vehicle through a braking deceleration prediction model.

With reference to the second aspect, in certain implementations of the second aspect, the brake deceleration prediction model is trained based on at least one training sample, the training sample including information of the training vehicle and a sample label of the training sample, the information of the training vehicle including motion information of the training vehicle and pressure information of a brake master cylinder of the training vehicle, the sample label of the training sample indicating a brake deceleration requested by a driver of the training vehicle.

With reference to the second aspect, in certain implementations of the second aspect, the pressure information of the brake master cylinder of the target vehicle includes a pressure slope of the brake master cylinder of the target vehicle that is greater than or equal to the first threshold value before the indication of the target brake deceleration is sent.

With reference to the second aspect, in certain implementations of the second aspect, the motion information of the target vehicle includes a speed of the target vehicle, and the first threshold is determined according to the speed of the target vehicle.

With reference to the second aspect, in some implementations of the second aspect, the target braking deceleration is determined according to a second braking deceleration, the second braking deceleration is obtained by processing the first braking deceleration by a target gain factor, and the target gain factor has a mapping relationship with the risk level of the current driving scenario.

With reference to the second aspect, in certain implementations of the second aspect, the target braking deceleration is determined according to one of the second braking deceleration and a safer braking deceleration, which is used to indicate a braking deceleration required by the target vehicle to avoid the collision, of which the absolute value is larger.

In a third aspect, a chip is provided, where the chip includes at least one processor and an interface circuit, and the at least one processor obtains instructions stored in a memory through the interface circuit, and executes the method in any one implementation manner of the first aspect.

Optionally, as an implementation manner, the chip may further include a memory, where instructions are stored in the memory, and the processor is configured to execute the instructions stored in the memory, and when the instructions are executed, the processor is configured to execute the method in any implementation manner of the first aspect.

In a fourth aspect, a computer readable medium is provided, which stores program code for execution by a device, the program code comprising instructions for performing the method of any one of the implementations of the first aspect.

In a fifth aspect, a computer program product containing instructions is provided, which when run on a computer causes the computer to perform the method of any one of the implementations of the first aspect.

A sixth aspect provides a terminal comprising the apparatus of any one of the implementation manners of the second aspect.

Optionally, the terminal further comprises a master cylinder.

Illustratively, the terminal may be a vehicle, and the apparatus according to the second aspect is used for controlling the vehicle.

Drawings

FIG. 1 is a schematic structural diagram of an autonomous vehicle according to an embodiment of the present disclosure;

FIG. 2 is a schematic structural diagram of a vehicle control device provided in an embodiment of the present application;

FIG. 3 is a schematic flow chart diagram of a vehicle control method provided by an embodiment of the present application;

FIG. 4 is a schematic diagram of the relationship between pressure slope and brake deceleration of a master cylinder provided in an embodiment of the present application;

FIG. 5 is a schematic illustration of a first brake deceleration prediction process provided by an embodiment of the present application;

FIG. 6 is a schematic flow chart of a graduated braking process provided by an embodiment of the present application;

FIG. 7 is a schematic illustration of a graduated auxiliary braking effect provided by an embodiment of the present application;

FIG. 8 is a schematic flow chart diagram of an arbitration process for a target brake deceleration provided by an embodiment of the present application;

FIG. 9 is a schematic diagram of braking effect under different scenarios provided by embodiments of the present application;

fig. 10 is a schematic diagram of a method for determining a mapping relationship between a first threshold value and a speed of a vehicle according to an embodiment of the present application;

FIG. 11 is a schematic diagram illustrating a distribution of pressure slopes of a brake master cylinder according to an embodiment of the present disclosure;

FIG. 12 is a schematic flow chart diagram of a driver braking intention identification method provided by an embodiment of the application;

fig. 13 is a schematic diagram of a vehicle control device according to an embodiment of the present application;

fig. 14 is a schematic diagram of another vehicle control device provided in the embodiment of the present application.

Detailed Description

The technical solution in the present application will be described below with reference to the accompanying drawings.

The scheme of the embodiment of the application can be applied to a braking system of a vehicle, for example, an emergency braking auxiliary system, and provides proper braking deceleration for the vehicle.

Fig. 1 is a functional block diagram of a vehicle 100 provided in an embodiment of the present application. In one embodiment, the vehicle 100 is configured in a fully or partially autonomous driving mode.

In one example, the vehicle 100 may control the target vehicle while in the autonomous driving mode, and may determine a current state of the vehicle and its surroundings by human operation, determine a likely behavior of at least one other vehicle in the surroundings, and determine a confidence level corresponding to a likelihood that the other vehicle will perform the likely behavior, controlling the vehicle 100 based on the determined information. While the vehicle 100 is in the autonomous driving mode, the vehicle 100 may be placed into operation without human interaction.

Vehicle 100 may include various subsystems such as a travel system 110, a sensing system 120, a control system 130, one or more peripherals 140, as well as a power supply 160, a computer system 150, and a user interface 170. Alternatively, vehicle 100 may include more or fewer subsystems, and each subsystem may include multiple elements. In addition, each of the sub-systems and elements of the vehicle 100 may be interconnected by wire or wirelessly.

For example, the travel system 110 may include components for providing powered motion to the vehicle 100. In the embodiment of the application, the traveling system can be used for driving the vehicle to perform corresponding motion behaviors, such as forward movement, backward movement, steering and the like, in the obstacle avoidance process. The travel system 110 includes an engine 111, a transmission 112, an energy source 113, and wheels 114.

The sensing system 120 may include several sensors that sense information about the environment surrounding the vehicle 100. In the embodiment of the present application, the sensing system may be configured to acquire environmental information and road structure information, and thereby perform subsequent control based on these acquired information.

For example, the sensing system 120 may include a positioning system 121 (e.g., a Global Positioning System (GPS), a beidou system, or other positioning system), an Inertial Measurement Unit (IMU) 122, a radar 123, a laser range finder 124, a camera 125, and a vehicle speed sensor 126. The sensing system 120 may also include sensors of internal systems of the monitored vehicle 100 (e.g., an in-vehicle air quality monitor, a fuel gauge, an oil temperature gauge, etc.). Sensor data from one or more of these sensors may be used to detect the object and its corresponding characteristics (position, shape, orientation, velocity, etc.). Such detection and identification is a critical function of the safe operation of the autonomous vehicle 100.

The positioning system 121 may be used, among other things, to estimate the geographic location of the vehicle 100. The IMU 122 may be used to sense position and orientation changes of the vehicle 100 based on inertial acceleration. In one embodiment, the IMU 122 may be a combination of an accelerometer and a gyroscope.

For example, the radar 123 may utilize radio signals to sense objects within the surrounding environment of the vehicle 100. In some embodiments, in addition to sensing objects, radar 123 may also be used to sense the speed and/or heading of an object.

For example, the laser rangefinder 124 may utilize laser light to sense objects in the environment in which the vehicle 100 is located. In some embodiments, laser rangefinder 124 may include one or more laser sources, laser scanners, and one or more detectors, among other system components.

Illustratively, the camera 125 may be used to capture multiple images of the surrounding environment of the vehicle 100. For example, the camera 125 may be a still camera or a video camera.

Illustratively, a vehicle speed sensor 126 may be used to measure the speed of the vehicle 100. For example, the vehicle may be tested for speed in real time. The measured vehicle speed may be communicated to the control system 130 to effect control of the vehicle.

The control system 130 is for controlling the operation of the vehicle 100 and its components. Control system 130 may include various elements, such as may include a steering system 131, a throttle 132, a braking unit 133, a computer vision system 134, a route control system 135, and an obstacle avoidance system 136.

For example, the steering system 131 may be operable to adjust the heading of the vehicle 100. For example, in one embodiment, a steering wheel system. The throttle 132 may be used to control the operating speed of the engine 111 and thus the speed of the vehicle 100.

For example, the brake unit 133 may be used to control the vehicle 100 to decelerate; the brake unit 133 may use friction to slow the wheel 114. In other embodiments, the brake unit 133 may convert the kinetic energy of the wheel 114 into an electrical current. The brake unit 133 may take other forms to slow the rotational speed of the wheels 114 to control the speed of the vehicle 100.

As shown in FIG. 1, the computer vision system 134 may be operable to process and analyze images captured by the camera 125 in order to identify objects and/or features in the environment surrounding the vehicle 100. Such objects and/or features may include traffic signals, road boundaries, and obstacles. The computer vision system 134 may use object recognition algorithms, motion from motion (SFM) algorithms, video tracking, and other computer vision techniques. In some embodiments, the computer vision system 134 may be used to map an environment, track objects, estimate the speed of objects, and so forth.

For example, route control system 135 may be used to determine a travel route for vehicle 100. Obstacle avoidance system 136 may be used to identify, assess, and avoid or otherwise negotiate potential obstacles in the environment of vehicle 100.

In one example, the control system 130 may additionally or alternatively include components other than those shown and described. Or may reduce some of the components shown above.

As shown in fig. 1, the vehicle 100 may interact with external sensors, other vehicles, other computer systems, or users through peripheral devices 140.

In some embodiments, the peripheral device 140 may provide a means for the vehicle 100 to interact with the user interface 170. Wireless communication system 141 may wirelessly communicate with one or more devices directly or via a communication network.

The power supply 160 may provide power to various components of the vehicle 100.

Some or all of the functionality of the vehicle 100 may be controlled by a computer system 150, wherein the computer system 150 may include at least one processor 151, and the processor 151 executes instructions 153 stored in a non-transitory computer readable medium, such as in a memory 152. The computer system 150 may also be a plurality of computing devices that control individual components or subsystems of the vehicle 100 in a distributed manner.

For example, processor 151 may be any conventional processor, such as a commercially available Central Processing Unit (CPU).

Alternatively, the processor may be a dedicated device such as an Application Specific Integrated Circuit (ASIC) or other hardware-based processor. Although fig. 1 functionally illustrates a processor, memory, and other elements of a computer in the same block, those skilled in the art will appreciate that the processor, computer, or memory may actually comprise multiple processors, computers, or memories that may or may not be stored within the same physical housing. For example, the memory may be a hard drive or other storage medium located in a different enclosure than the computer. Thus, references to a processor or computer are to be understood as including references to a collection of processors or computers or memories which may or may not operate in parallel. Rather than using a single processor to perform the steps described herein, some components, such as the steering component and the retarding component, may each have their own processor that performs only computations related to the component-specific functions.

In various aspects described herein, the processor may be located remotely from the vehicle and in wireless communication with the vehicle. In other aspects, some of the processes described herein are executed on a processor disposed within the vehicle and others are executed by a remote processor, including taking the steps necessary to perform a single maneuver.

In some embodiments, the memory 152 may contain instructions 153 (e.g., program logic), which instructions 153 may be used by the processor 151 to perform various functions of the vehicle 100, including those described above. The memory 152 may also include additional instructions, such as instructions to send data to, receive data from, interact with, and/or control one or more of the travel system 110, the sensing system 120, the control system 130, and the peripheral devices 140.

Illustratively, in addition to instructions 153, memory 152 may also store data such as road maps, route information, location, direction, speed of the vehicle, and other such vehicle data, among other information. Such information may be used by the vehicle 100 and the computer system 150 during operation of the vehicle 100 in autonomous, semi-autonomous, and/or manual modes.

User interface 170 may be used to provide information to and receive information from a user of vehicle 100. Optionally, the user interface 170 may include one or more input/output devices within the collection of peripheral devices 140, such as a wireless communication system 141, an in-vehicle computer 142, a microphone 143, and a speaker 144.

In embodiments of the present application, the computer system 150 may control the functions of the vehicle 100 based on inputs received from various subsystems (e.g., the travel system 110, the sensing system 120, and the control system 130) and from the user interface 170. For example, the computer system 150 may utilize inputs from the control system 130 in order to control the brake unit 133 to avoid obstacles detected by the sensing system 120 and the obstacle avoidance system 136. In some embodiments, the computer system 150 is operable to provide control over many aspects of the vehicle 100 and its subsystems.

Alternatively, one or more of these components described above may be mounted or associated separately from the vehicle 100. For example, the memory 152 may exist partially or completely separate from the vehicle 100. The above components may be communicatively coupled together in a wired and/or wireless manner.

Optionally, the above components are only an example, in an actual application, components in the above modules may be added or deleted according to an actual need, and fig. 1 should not be construed as limiting the embodiment of the present application.

The autonomous automobile vehicle 100 or a computing device associated with the autonomous vehicle 100 (e.g., the computer system 112, the computer vision system 140, the data storage 114 of fig. 1) may predict behavior of the identified objects based on characteristics of the identified objects and the state of the surrounding environment (e.g., traffic, rain, ice on the road, etc.). Optionally, each identified object depends on the behavior of each other, so it is also possible to predict the behavior of a single identified object taking all identified objects together into account. The vehicle 100 is able to adjust its speed based on the predicted behaviour of said identified object. In other words, the autonomous vehicle is able to determine what steady state the vehicle will need to adjust to (e.g., accelerate, decelerate, or stop) based on the predicted behavior of the object. In this process, other factors may also be considered to determine the speed of the vehicle 100, such as the lateral position of the vehicle 100 in the road on which it is traveling, the curvature of the road, the proximity of static and dynamic objects, and so forth.

The vehicle 100 may be a conventional vehicle, a new energy vehicle, an intelligent vehicle, and the like, where the conventional vehicle is a vehicle that provides energy by using a vehicle, diesel oil, and the like, the new energy vehicle is a vehicle that provides energy by using new energy such as electric energy, gas, and the like, and the intelligent vehicle is a vehicle equipped with an intelligent device such as an intelligent control unit, and the vehicle type of the vehicle 100 may include a car, a truck, a bus, an engineering vehicle, a bus, and the like, for example, and the embodiment of the present application is not particularly limited. In the embodiment of the present application, various automobiles running on a road are mainly taken as an example for description.

In order to improve the safety of the vehicle under the emergency braking working condition, an emergency braking auxiliary system on the vehicle can perform emergency braking on the vehicle when the current driving state is in a dangerous state.

Generally, an emergency braking auxiliary system on a vehicle does not consider the braking requirement of a driver when performing emergency braking, and performs braking according to preset braking force, so that user experience is poor, and even potential safety hazards exist. For example, an Automatic Emergency Braking (AEB) system senses a surrounding environment through a sensor, and performs braking according to a preset braking force when a current driving state is a dangerous state. However, this braking process does not take into account the driver's braking demand, and sudden braking can result in a poor user experience. For another example, the emergency braking assistance system may misjudge the non-emergency braking condition as the emergency braking condition, and then trigger the emergency braking assistance function by mistake, so as to provide unnecessary deceleration for the vehicle, and the emergency braking assistance system usually directly outputs the maximum braking force after judging that the current condition is the emergency braking condition. Unnecessary deceleration or excessive deceleration do not accord with the subjective intention of the driver, so that the user experience is reduced, and even potential safety hazards such as rear-end collision of a rear vehicle and the like may exist.

The embodiment of the application provides a vehicle control method, which provides proper braking deceleration, better accords with the subjective will of a driver, and can improve the user experience in the vehicle braking process.

In order to better describe the method of the embodiment of the present application, a vehicle control device 200 provided in the embodiment of the present application is described below with reference to fig. 2. The device 200 may perform braking control on the vehicle by using the method in the embodiment of the present application.

Fig. 2 shows a vehicle control device provided in an embodiment of the present application. The apparatus 200 of fig. 2 includes an emergency braking intent recognition module 210, a driver requested deceleration prediction module 220, a graduated braking module 230, and a brake deceleration decision module 240.

The emergency braking intention identifying module 210 is configured to identify an emergency braking intention of the driver, that is, determine whether the driver needs emergency braking currently, or identify whether the driver is in an emergency braking condition currently.

It should be noted that the emergency braking intention identification module 210 is an optional module. For example, if the apparatus 200 is applied to an EBA system, the emergency braking intention recognition module 210 is integrated into the apparatus 200, and may be provided separately from the apparatus 200. Alternatively, if the apparatus 200 is not employed in an EBA system, the emergency braking intent identification module 210 is a province module. For example, when the apparatus 200 is employed in an AEB system, the emergency braking intent recognition module 210 may not be provided in the system.

Illustratively, the driver requested deceleration prediction module 220, the graduated braking module 230, or the braking deceleration decision module 240 is activated in the event that the current operating condition is an emergency braking condition.

The emergency braking intention identification module 210 may identify the driver's emergency braking intention from the information of the target vehicle.

The information of the target vehicle includes pressure information of a brake master cylinder of the target vehicle and motion information of the target vehicle.

The driver requested deceleration prediction module 220 is used to predict the deceleration requested by the driver.

Specifically, the driver-requested deceleration prediction module 220 may predict a driver-requested brake deceleration, i.e., a first brake deceleration, from information of the target vehicle. Further, the driver-requested deceleration prediction module 220 may predict a driver-requested braking deceleration based on the information of the target vehicle and the environmental awareness information.

The graduated braking module 230 is configured to process the braking deceleration requested by the driver according to the danger level of the current driving scenario, and obtain a second braking deceleration.

That is, the output result of the deceleration prediction module 220 requested by the driver is input to the stepped brake module 230, and the stepped brake module 230 processes the braking deceleration requested by the driver according to the gain coefficient corresponding to the risk level of the current driving scene, that is, the target gain coefficient, and outputs the second braking deceleration.

It should be noted that the staged braking module 230 is an optional module.

Brake deceleration decision block 240 is configured to determine a target brake deceleration, which is the brake deceleration output by device 200.

For example, in the event that apparatus 200 does not include a graduated braking module 230, driver requested deceleration prediction module 220 may input a first brake deceleration to brake deceleration decision module 240. The brake deceleration decision module 240 may take the larger absolute value of the safe brake deceleration and the first brake deceleration as the target brake deceleration.

Here, the safe braking deceleration is used to indicate the braking deceleration required for the target vehicle to avoid the collision.

Alternatively, where the apparatus 200 includes the graduated braking module 230, the graduated braking module 230 may output a second braking deceleration to the braking deceleration decision module 240. The brake deceleration decision module 240 may take, as the target brake deceleration, a value whose absolute value is larger, from among the safe deceleration and the second brake deceleration output by the stepped brake module 230.

It should be noted that the brake deceleration decision block 240 is an optional block.

For example, in the case where the apparatus 200 does not include the deceleration brake decision module 240, the target brake deceleration may be the second brake deceleration output by the stepped brake module 230.

Further, in the case where apparatus 200 does not include deceleration brake decision module 240 and staging brake module 230, the target brake deceleration may be the first brake deceleration output by driver-requested deceleration prediction module 220.

Fig. 3 shows a schematic flowchart of a vehicle control method 300 provided by an embodiment of the present application. The method 300 includes steps S310 to S320. Next, step S310 to step S320 will be explained.

And S310, acquiring information of the target vehicle, wherein the information of the target vehicle comprises the motion information of the target vehicle and the pressure information of a brake master cylinder of the target vehicle.

For example, the motion information of the target vehicle may be obtained by the sensing system 120 in fig. 1. The speed of the target vehicle is obtained by, for example, the vehicle speed sensor 126. For another example, the acceleration of the target vehicle is obtained by the inertia measurement unit 122.

The pressure gradient of the master cylinder can be understood as the rate of change of the pressure of the master cylinder. For example, the pressure gradient of the master cylinder during the pressure increase of the master cylinder may also be referred to as the pressure rising rate of the master cylinder.

For example, the pressure gradient of the master cylinder may be determined by periodically acquiring the value of the pressure of the master cylinder.

For example, pressure information of the master cylinder may be obtained by the sensing system 120 of fig. 1. For example, pressure information of the brake master cylinder is obtained by a sensor of the internal system.

And S320, sending indication information of target brake deceleration, wherein the indication information of the target brake deceleration is used for indicating the target vehicle to perform active pressurization on the brake master cylinder, and the target brake deceleration is predicted according to the information of the target vehicle. The function of the step is to control the vehicle to perform active pressurization on the brake master cylinder.

Specifically, the indication information of the target brake deceleration is sent to the actuator of the target vehicle, so that the target vehicle can be indicated or triggered to perform active pressurization on the brake master cylinder, and the target vehicle can perform braking according to the target brake deceleration.

Alternatively, the indication information of the target braking deceleration may include the target braking deceleration itself, or information that can be used to obtain the target braking deceleration, for example, the indication information of the target braking deceleration may be a difference between the target braking deceleration and the current braking deceleration, and the application is not particularly limited.

Brake deceleration (decelaration) refers to the ratio of the amount of change in speed after braking to the time it takes for the change in speed to occur. Brake deceleration can also be understood as acceleration.

Active boost refers to boost performed autonomously by the vehicle, rather than by the driver via the brake pedal, e.g., by an emergency brake assist system on the vehicle.

The information of the target vehicle is the information of the target vehicle at or before the active supercharging starting time.

In a traditional non-wire control brake system, pedal force is coupled with pressure of a brake master cylinder, and a scheme of calculating brake deceleration requested by a driver in real time through pedal opening, pedal opening change rate or cylinder pressure information is not suitable for a scene of vehicle active pressurization. When the emergency brake auxiliary system is actively boosted, the pedal opening and the change rate of the pedal opening are influenced by the coupled brake cylinder pressure, and the real intention of the driver cannot be accurately quantified through parameters such as real-time pedal force.

In the scheme of the embodiment of the application, the information of the target vehicle before active pressurization is obtained by the driver in the natural driving process, and the subjective intention of the driver can be reflected. The target braking deceleration is predicted through the information of the target vehicle before active pressurization, the braking intention of a driver can be accurately quantized, the braking process of the vehicle is made to accord with the subjective intention of the driver, and the user experience and the driving safety are improved.

In the case where the motion information of the vehicle is different, the braking intention of the driver reflected on the cylinder pressure information of the same master cylinder may be different. For example, when the vehicle speed is different, the brake deceleration requested by the driver may be different even if the cylinder pressure gradient of the master cylinder is the same. The braking deceleration requested by the driver is small when the vehicle speed is low, and the braking deceleration requested by the driver is large when the vehicle speed is high.

According to the embodiment of the application, the target braking deceleration is predicted through the motion information of the target vehicle and the pressure information of the brake master cylinder, so that the target braking deceleration can better accord with the braking intention of a driver, the prediction accuracy is further improved, the braking process of the vehicle can better accord with the subjective intention of the driver, and the user experience and the driving safety are further improved.

In addition, the scheme of the embodiment of the application does not depend on hardware devices such as a pedal position sensor, a pedal simulator or a brake-by-wire system and the like, so that the hardware cost is saved.

In one possible implementation, the method 300 may be performed by an EBA system, in which case the target brake deceleration is the brake deceleration that the EBA system needs to perform, or the target brake deceleration is the brake deceleration that the EBA system outputs, and the actuator controls the target vehicle to actively boost the brake master cylinder according to the target brake deceleration.

Therefore, in the emergency braking working condition, the EBA system can provide an emergency braking auxiliary function based on the target braking deceleration so as to realize auxiliary braking, and the maximum braking force is not directly output, so that the subjective intention of a driver is better met, and the user experience and the driving safety are improved.

In another possible implementation, the method 300 may be performed by an AEB system, in which case the target braking deceleration is the braking deceleration that the AEB system needs to perform, or the target braking deceleration is the braking deceleration that the AEB system outputs, and the actuator controls the target vehicle to actively pressurize the brake master cylinder according to the target braking deceleration.

Therefore, in the emergency braking working condition, the AEB system can provide the emergency braking function based on the target braking deceleration so as to realize emergency braking, and the AEB system does not directly output the preset braking force, so that the subjective intention of a driver is better met, and the user experience and the driving safety are improved.

It should be understood that the above two application scenarios are only illustrative, and the method 300 in the embodiment of the present application may also be applied to other braking systems, which is not limited by the embodiment of the present application. For convenience of description and illustration, the method 300 is hereinafter described as being applied to the EBA system as an example, and the application scenario of the embodiment of the present application is not limited.

Alternatively, the target braking deceleration is determined based on the first braking deceleration. The first braking deceleration is obtained by processing information of the target vehicle by a braking deceleration prediction model.

Further, the brake deceleration prediction model is trained based on at least one training sample, the training sample comprises information of the training vehicle and a sample label of the training sample, and the information of the training vehicle comprises motion information of the training vehicle and pressure information of the brake master cylinder. The sample labels of the training samples are used to indicate the brake deceleration requested by the driver of the training vehicle.

The first brake deceleration is the brake deceleration requested by the driver.

That is, the motion information of the target vehicle and the pressure information of the brake master cylinder are input as the brake deceleration prediction model, feature extraction is performed by the brake deceleration prediction model, and the output of the model is obtained based on the extracted features. The output of the brake deceleration model is the first brake deceleration.

The braking deceleration prediction model may be a neural network model, such as a Recurrent Neural Network (RNN) model.

The at least one training sample is derived from natural driving test data.

One training sample may be determined from data during a braking process during natural driving of the training vehicle, i.e. the motion information of the training vehicle and the pressure information of the master cylinder of the training vehicle are data during the braking process. The brake deceleration requested by the driver of the training vehicle can be understood as the brake deceleration that is ultimately requested by the driver during this braking. For example, the brake deceleration that is ultimately requested by the driver may be a value of the stable brake deceleration that the training vehicle ultimately reaches during this braking event. Alternatively, the brake deceleration that the driver ultimately requests may be the maximum brake deceleration that the training vehicle reaches during this braking. It should be understood that the magnitude of the braking deceleration in the embodiment of the present application refers to the magnitude of the absolute value of the braking deceleration.

Specifically, deriving a braking deceleration prediction model based on the training samples may include: the motion information of the training vehicle and the pressure information of a brake master cylinder of the training vehicle are used as the input of a brake deceleration prediction model, and the brake deceleration requested by a driver of the training vehicle is used as the target output of the brake deceleration prediction model to train the model, so that the trained brake deceleration prediction model is obtained.

Wherein the training process may be done off-line (offline).

In the braking process of natural driving, the operation of the driver is a time sequence process, but under a certain braking intention, the operation rule of the driver is basically kept consistent. The operation rule of the driver can be embodied by parameters such as pressure information of a brake master cylinder of the vehicle and motion information of the vehicle in the braking process. As shown in fig. 4, the trend of change in the pressure slope of the brake master cylinder of the vehicle during primary braking in natural driving substantially corresponds to the trend of change in the braking deceleration. As the pressure gradient of the brake master cylinder of the vehicle increases, the braking force provided to the vehicle increases, and accordingly, the absolute value of the braking deceleration of the vehicle increases. For example, the brake deceleration in fig. 4, which is the largest in absolute value, is taken as the brake deceleration that is ultimately requested by the driver. The brake deceleration that is finally requested by the driver, i.e., the predicted point in fig. 4, can be predicted from the motion information of the vehicle corresponding to the time at which the pressure gradient of the master cylinder is maximum and the pressure information of the master cylinder, i.e., the calculated point in fig. 4.

Alternatively, the motion information of the training vehicle in the training sample may include motion information corresponding to a time when the pressure slope of the master cylinder of the training vehicle is maximum. The pressure information of the master cylinder of the training vehicle includes pressure information of the master cylinder corresponding to a time point when the pressure gradient of the master cylinder of the training vehicle is maximum. The sample label of the training sample includes the brake deceleration that is ultimately requested by the driver of the training vehicle.

The motion information of the training vehicle and the pressure information of the brake master cylinder collected at the time of the calculation point are used as the input of a brake deceleration prediction model, and the brake deceleration collected at the time of the prediction point is used as the target output of the brake deceleration prediction model to train the model, so that the trained predicted deceleration model is obtained.

Taking the braking process shown in fig. 4 as an example, the motion information of the training vehicle in one training sample may include the motion information of the training vehicle at time t2, and the pressure information of the master cylinder of the training vehicle may include the pressure information of the master cylinder of the training vehicle at time t 2. The sample label of the training sample, i.e., the brake deceleration requested by the driver, may be the brake deceleration at time t3 in fig. 4. That is, the motion information of the training vehicle at the time t2 and the pressure information of the master cylinder of the training vehicle may be used as the inputs of the brake deceleration prediction model, and the brake deceleration at the time t3 may be used as the sample label to train the brake deceleration model.

As shown in fig. 4, in the braking process of natural driving, the maximum slope is reached after a certain time (e.g., Δ t in fig. 4) elapses after a time (e.g., t1 in fig. 4) at which the slope of the pressure of the master cylinder reaches the first threshold value.

That is, a time after a first period of time elapses after the pressure slope of the master cylinder of the target vehicle reaches the first threshold value may be regarded as a time at which the pressure slope of the master cylinder of the target vehicle is maximum.

The first time period may be preset, for example, the first time period may be determined in advance by a statistical rule of natural driving test data.

The first threshold may be determined based on the speed of the target vehicle. There is a mapping relationship between the first threshold and the speed of the target vehicle, as described in more detail below with reference to method 1000.

Alternatively, the motion information of the target vehicle may include motion information corresponding to a time that is a distance from a time when a pressure slope of a brake master cylinder of the target vehicle reaches a first threshold value after the time. The pressure information of the brake master cylinder of the target vehicle includes pressure information of the brake master cylinder corresponding to a time that is a distance from a time when the pressure slope of the brake master cylinder of the target vehicle reaches a first threshold value to the time.

That is, the first brake deceleration may be obtained by processing the information of the target vehicle acquired after the time at which the pressure gradient of the brake master cylinder of the target vehicle reaches the first threshold value and the time at which the time is separated by the first time period, as the input of the brake deceleration model.

Wherein the training process may be done off-line (offline). The prediction process may be done online (online). I.e. the braking deceleration model may be a model trained offline in advance.

It should be understood that fig. 4 is only an example of the variation trend of the relevant parameter during one braking process, and the values of the pressure slope and the brake deceleration of the brake master cylinder in fig. 4 do not limit the scheme in the embodiment of the present application.

It should be noted that the training samples and the parameters for inputting the braking deceleration model are only examples, and the first braking deceleration may be obtained by training the braking deceleration prediction model using information of the training vehicle at another time or in another period collected in the braking process as the input of the braking deceleration prediction model in the training process, and using information of the target vehicle at another time or in another period collected in the braking process as the input of the braking deceleration model in the inference process. The embodiment of the present application does not limit the specific form of the parameter input to the brake deceleration model.

The target vehicle may perform step S320 of actively pressurizing the brake master cylinder after a first period of time elapses after a pressure slope of the brake master cylinder of the target vehicle reaches a first threshold value. When the method 300 is applied to the EBA system, the EBA system on the target vehicle starts performing the emergency brake assist operation, i.e., outputting the target brake deceleration to perform the active boosting of the brake master cylinder, after a first period of time elapses after the pressure slope of the brake master cylinder reaches the first threshold value.

In this way, the first braking deceleration is predicted through the information before active pressurization, so that the real braking intention of the driver can be reflected, and the prediction accuracy of the braking deceleration requested by the driver can be improved.

In the embodiment of the application, the neural network model is used as a braking deceleration prediction model, the braking deceleration model is trained based on data collected in a natural driving process, the braking deceleration requested by a driver is predicted through the trained braking deceleration model, and the prediction accuracy of the braking deceleration requested by the driver can be improved through the strong characteristic expression capability of the neural network model.

Further, step S310 further includes acquiring the environmental awareness information of the target vehicle. In this case, the target braking deceleration is predicted from the information of the target vehicle and the environment perception information of the target vehicle.

The environment awareness information of the vehicle refers to information related to the environment around the vehicle. For example, the context awareness information of the target vehicle includes at least one of: the speed of the obstacle, the acceleration of the obstacle, or the relative position between the obstacle and the target vehicle, etc. Illustratively, the obstacle may include his car or pedestrian, or the like.

Illustratively, the context awareness information may be obtained by the sensing system 120 of FIG. 1.

As described above, the target brake deceleration may be determined based on the first brake deceleration. The first braking deceleration may be a result of processing the target vehicle information and the environment perception information of the target vehicle by a braking deceleration prediction model.

That is, the motion information of the target vehicle, the pressure information of the brake master cylinder, and the environment perception information of the target vehicle are input as the brake deceleration prediction model, feature extraction is performed by the brake deceleration prediction model, and the output of the model is obtained based on the extracted features. The output of the brake deceleration model is the first brake deceleration.

The acquisition time of the environmental awareness information of the target vehicle and the acquisition time of the information of the target vehicle may be the same.

One training sample may be determined from data during a braking process during natural driving of the training vehicle, that is, motion information of the training vehicle, pressure information of a master cylinder of the training vehicle, and environmental perception information of the training vehicle are data during the braking process. The acquisition time of the environmental awareness information of the training vehicle may be the same as the acquisition time of the information of the training vehicle.

Deriving a braking deceleration prediction model based on the training samples may include: the motion information of the training vehicle, the pressure information of a brake master cylinder of the training vehicle and the environment perception information of the training vehicle are used as the input of a brake deceleration prediction model, the brake deceleration requested by a driver of the training vehicle is used as the target output of the brake deceleration prediction model, the model is trained, and the trained brake deceleration prediction model is obtained.

Fig. 5 shows a schematic diagram of a training and reasoning process of a brake deceleration prediction model. As shown in fig. 5, the brake deceleration prediction model is trained based on natural driving data, and this training process may be done off-line. Wherein the natural driving data is used to obtain training samples. The training samples comprise motion information of the training vehicle, pressure information of a brake master cylinder of the training vehicle, environment perception information of the training vehicle and sample labels of the training samples. And inputting the motion information of the target vehicle, the pressure information of the brake master cylinder and the environment perception information of the target vehicle into a trained brake deceleration prediction model to obtain a first brake deceleration. The prediction process may be done online.

In the emergency braking condition and the non-emergency braking condition, even if the motion information of the vehicle and the pressure information of the master cylinder of the vehicle are the same, the brake deceleration actually requested by the driver may be different. According to the embodiment of the application, the environment perception information of the training vehicle is used for training the model, so that the model can judge whether the driver needs emergency braking or not based on actual collision risk, and the accuracy of the prediction model is improved. Correspondingly, in the reasoning process, the environment perception information of the target vehicle is also used as the input of the model, so that the braking result can better meet the subjective will of the driver, and the user experience and the safety are improved. When the method 300 is applied in an emergency braking assistance system, it is advantageous to avoid false triggering of the emergency braking function during non-emergency braking conditions.

Optionally, the target braking deceleration is determined from the first braking deceleration, including: the target braking deceleration is the first braking deceleration.

The first braking deceleration is used as the target braking deceleration, so that the braking intention of the driver can be better reflected.

Optionally, the target braking deceleration is determined from the first braking deceleration, including: the target braking deceleration is determined according to a second braking deceleration, the second braking deceleration is obtained by processing the first braking deceleration through a target gain factor, and the target gain factor has a mapping relation with the danger level of the current driving scene.

Alternatively, the target gain factor is determined by mapping the gain factor to the risk level of the driving scene.

That is, the gain coefficient corresponding to the danger level of the current driving scenario, i.e., the target gain coefficient, may be determined according to the mapping relationship between the danger level of the driving scenario and the gain coefficient, and the first braking deceleration may be processed according to the target gain coefficient to obtain the second braking deceleration.

In another implementation, the higher the hazard level, the greater the probability of the vehicle colliding, and the greater the corresponding gain factor. For ease of description and understanding, the method 300 is described hereinafter by way of example only and is not intended to limit the aspects of the embodiments of the present application.

According to the embodiment of the application, the first braking deceleration is correspondingly processed according to the gain coefficient corresponding to the danger level of the current driving scene, the graded braking can be realized based on different danger levels, and the driving safety of the vehicle is improved.

Processing the first brake deceleration may include any one of: the first brake deceleration is subjected to an enlargement process, the first brake deceleration is subjected to a reduction process, or the first brake deceleration is set as the second brake deceleration.

The result of the processing of the first brake deceleration may be different for different gain factors. In one implementation, the second braking deceleration is obtained by multiplying the first braking deceleration by a target gain factor. In this case, if the target gain factor is greater than 1, the processing of the first braking deceleration is substantially to amplify the first braking deceleration, and the amplified first braking deceleration is set as the second braking deceleration; if the target gain factor is 1, processing the first braking deceleration substantially means not processing the first braking deceleration and setting the first braking deceleration as the second braking deceleration; if the target gain factor is smaller than 1, the first braking deceleration is processed substantially by reducing the first braking deceleration, and the first braking deceleration obtained after the reduction is set as the second braking deceleration.

Further, the plurality of gain factors are greater than or equal to 1. That is to say the target gain factor is greater than or equal to 1.

In this case, the processing of the first brake deceleration includes amplification processing of the first brake deceleration or setting the first brake deceleration as the second brake deceleration.

Optionally, in a case that the risk level is greater than or equal to the first level threshold, the gain coefficient corresponding to the risk level is greater than 1. That is, the first brake deceleration is subjected to the amplification process in the case where the risk level is greater than or equal to the first level threshold value.

Further, in the case that the danger level is smaller than the first level threshold, the gain factor corresponding to the danger level is equal to 1. That is, in the case where the risk level is less than the first level threshold value, the first brake deceleration is taken as the second brake deceleration.

For example, the first level threshold may be 1.

In the face of an emergency braking condition, due to insufficient experience, insufficient pedaling force or not rapid response, the braking deceleration requested by an ordinary driver may not be enough to achieve obstacle avoidance. Through the scheme of the embodiment of the application, under the condition that the danger level is high, the first braking deceleration is amplified, and the driving safety is further improved. And under the condition of lower danger level, the first brake deceleration is directly used as the second brake deceleration, so that the subjective intention of a driver is better met, and the user experience is improved.

For example, the gain factors for the different hazard levels may be determined based on the brake deceleration requested by the professional driver.

Specifically, the professional driver calibrates the braking deceleration requested by the driver at different danger levels to obtain the gain coefficients at different danger levels.

For example, in the course of natural driving, the braking deceleration requested by the professional driver in the scene of a danger level is divided by the braking deceleration requested by the average driver, and the result is obtained as the gain factor corresponding to the danger level.

Compared with a common driver, the professional driver can judge the emergency braking condition more accurately, the gain coefficient calibrated by the professional driver is used for performing gain processing on the braking deceleration requested by the common driver, and the driving safety can be improved on the premise of meeting the subjective intention of the common driver as much as possible.

Illustratively, the risk judgment index is compared with a calibrated threshold value, and the risk level is determined according to the comparison result.

For example, the risk discrimination indicator may include at least one of: time To Collision (TTC), Time To Brake (TTB), or headway (THW).

It should be understood that the above-mentioned methods for dividing the risk judgment index and the risk level are merely illustrative, and the methods for dividing the risk judgment index and the risk level may be determined in other ways, which is not limited in this embodiment of the present application.

A schematic flow chart of a hierarchical braking process provided by an embodiment of the present application is shown in fig. 6. Step S320 is explained below with reference to fig. 6. The scheme in fig. 6 can be regarded as a specific implementation manner of step S320.

Illustratively, FIG. 6 may be performed by the graduated braking module 230 of FIG. 2.

The scheme in fig. 6 includes steps S610 to S640.

And S610, calculating a danger judgment index according to the motion information and the environment perception information of the target vehicle.

For example, the risk discrimination indicator includes at least one of: TTC, TTB or THW.

And S620, determining the danger level of the current driving scene according to the danger judging index.

Illustratively, the danger judging index is compared with a calibrated threshold value, and the danger level of the current driving scene is determined according to the comparison result.

For example, the danger level of the driving scene may include a plurality of levels, such as 0,1,2,3, etc., and the danger level of the current driving scene is one of the danger levels.

S630, determining a target gain coefficient corresponding to the danger level of the current driving scene according to the mapping relation between the danger level and the gain coefficient.

For example, the danger levels of the driving scene include four levels of 0,1,2, and 3, and the corresponding gain coefficients are k0, k1, k2, and k3, respectively.

And S640, processing the first braking deceleration according to the target gain coefficient to obtain a second braking deceleration.

Optionally, the target braking deceleration is determined based on a second braking deceleration, comprising: the target braking deceleration is the second braking deceleration.

The second brake deceleration is obtained by calibrating the first brake deceleration by a professional driver, meets the subjective will of the driver, and improves the driving safety.

Further, the hazard level of the current driving scenario is greater than or equal to the second level threshold before the indication of the target brake deceleration is transmitted.

Or it may be understood that the condition that the risk level of the current driving scenario is greater than or equal to the second level threshold is one of the trigger conditions for sending the information indicative of the target brake deceleration. In the case where the risk level of the current driving scenario is less than the second level threshold, step S320 is not performed.

The second level threshold may be the same as or different from the first level threshold.

For example, the second level threshold is 1, and when the risk level of the current driving scenario is 0, step S320 is not performed.

That is, when the risk level is low, the vehicle may not perform active supercharging but perform supercharging by driver pedal braking.

As indicated previously, the solution of the embodiment of the present application may be applied in an EBA system for providing an emergency brake assist function. When the method 300 is applied to an EBA system, the emergency braking assist function may not be triggered in the event that the risk level of the current driving scenario is less than the second level threshold. Therefore, the collision risk is identified through the danger level, and the condition of false triggering of the emergency braking auxiliary function is further avoided.

Fig. 7 shows the variation of the braking deceleration of the vehicle at different dangerous levels. The target braking deceleration in the scheme of fig. 7 is the second braking deceleration.

As shown in fig. 7, when the risk level is 0, the target gain factor is 1, the first brake deceleration is not processed, and the EBA system may not provide the emergency brake assist function, and the curve reflects the change of the brake deceleration when the ordinary driver performs the braking operation. As the risk level increases, the gain factor gradually increases and the second braking deceleration also increases, and the second braking deceleration obtained when the risk level is 3 in fig. 7 is the maximum braking deceleration that can be output by the vehicle. As shown in fig. 7, as the danger level increases, the second brake deceleration increases, and with the assistance of the EBA system, the pressure can be built up faster, so that the vehicle can reach the required brake deceleration as soon as possible, or reach the second brake deceleration as soon as possible, thereby implementing the graded auxiliary braking that better meets the subjective intention of the driver, and ensuring the safety of the vehicle at different danger levels.

However, the calibration results of professional drivers cannot completely avoid collisions. The driving safety is further improved through the safe braking deceleration in the embodiment of the application.

Optionally, the target braking deceleration is determined from a second braking deceleration, comprising: the target braking deceleration is determined based on the one of the second braking deceleration and the safety braking deceleration, the absolute value of which is large.

The safe braking deceleration is used to indicate the braking deceleration required for the target vehicle to avoid the collision.

The second braking deceleration and the safe braking deceleration are compared and arbitrated, and the target braking deceleration is determined based on one of the items in which the absolute value is larger.

Alternatively, the target braking deceleration is determined according to one of the second braking deceleration and the safe braking deceleration, of which absolute value is larger, including: the target braking deceleration is one of the second braking deceleration and the safety braking deceleration, the absolute value of which is large.

Alternatively, the target braking deceleration is determined as one of the second braking deceleration and the safety braking deceleration, which is larger in absolute value, including: the target braking deceleration is a smaller value between the one having the larger absolute value and the braking deceleration threshold value.

Illustratively, the brake deceleration threshold is determined by the ABS.

Alternatively, the target braking deceleration is determined based on the first braking deceleration, including the target braking deceleration being determined based on the larger absolute value of the first braking deceleration and the safety braking deceleration.

The first braking deceleration and the safe braking deceleration are compared and arbitrated, and the target braking deceleration is determined based on one of the items in which the absolute value is larger.

That is, if method 300 does not include processing the first brake deceleration, the target brake deceleration may be determined based on the first brake deceleration and the safest brake deceleration.

Alternatively, the target braking deceleration is determined based on one of the first braking deceleration and a greater absolute value of safety, including: the target braking deceleration is one of the first braking deceleration and the safety braking deceleration, the absolute value of which is large.

Alternatively, the target brake deceleration is determined as one of the first brake deceleration and the safety brake deceleration, which is larger in absolute value, including: the target braking deceleration is a term in which the absolute value between the term in which the absolute value is larger and the braking deceleration threshold value is smaller.

Illustratively, the brake deceleration threshold is determined by the ABS.

Fig. 8 shows a schematic flowchart of a method for determining a target braking deceleration provided by an embodiment of the present application. The scheme in fig. 8 can be regarded as a specific implementation manner of step S320.

Illustratively, fig. 8 may be performed by brake deceleration decision module 240 in fig. 2.

The scheme shown in fig. 8 includes steps S710 to S730, and the steps S710 to S730 are explained below.

And S710, determining safe braking deceleration according to the motion information and the environment perception information of the target vehicle.

In step S720, when the first brake deceleration is processed, the one of the safe brake deceleration and the second brake deceleration, which has the larger absolute value, is determined.

In the case where the first braking deceleration is not processed, the larger value of the safe braking deceleration and the first braking deceleration is determined.

S730, the one with the larger absolute value in step S720 and the one with the smaller absolute value in the ABS-determined brake deceleration threshold are determined.

The smaller absolute value of the two is taken as the target braking deceleration.

The target braking deceleration may be achieved as quickly as possible by actively boosting the brake deceleration value required to be executed by the emergency brake assist system or the brake deceleration value output by the emergency brake assist system.

The scheme of the embodiment of the application can be applied to an EBA system and used for providing an emergency braking auxiliary function. Fig. 9 shows the change in braking deceleration under different scenarios. Fig. 9 (a) shows a change in the braking deceleration of the different scene in the case where the second braking deceleration is larger than the safe braking deceleration, and fig. 9 (b) shows a change in the braking deceleration of the different scene in the case where the second braking deceleration is smaller than the safe braking deceleration.

As shown in fig. 9, in the emergency braking condition, due to the problems of inaccurate judgment and the like, the brake deceleration requested by the driver (i.e., the first brake deceleration) is difficult to realize safe obstacle avoidance.

As shown in fig. 9 (a), the braking deceleration requested by the professional driver in the emergency condition is larger than the safe braking deceleration, and safe obstacle avoidance can be achieved. Meanwhile, a professional driver is generally superior to a normal driver in terms of reaction speed and the like, and as shown in fig. 9, the rising rate of the curve of the brake deceleration corresponding to the professional driver is significantly higher than that of the normal driver, that is, the professional driver can achieve the required brake deceleration faster when driving the vehicle. The second brake deceleration in the embodiment of the present application may be calibrated by the professional driver for the first brake deceleration, and the brake deceleration requested by the professional driver in fig. 9 may also be understood as the second brake deceleration in the embodiment of the present application. In the case where the second brake deceleration is larger than the safe brake deceleration, the EBA system takes the second brake deceleration as the target brake deceleration. The EBA system provides the emergency brake assist function based on the target brake deceleration, and as shown in fig. 9 (a), the rising rate of the curve of the brake deceleration corresponding to the EBA system is higher than that of the brake deceleration corresponding to the professional driver, that is, in the case that the target brake deceleration is the same, the EBA system can provide the emergency brake assist function to realize the active build-up of the pressure, so that the vehicle can reach the target brake deceleration more quickly, and the driving safety is improved.

As shown in fig. 9 (b), the braking deceleration requested by the professional driver in the emergency condition is smaller than the safe braking deceleration, and safe obstacle avoidance cannot be achieved, as shown in fig. 9 (b). The second brake deceleration in the embodiment of the present application may be calibrated by the professional driver for the first brake deceleration, and the brake deceleration requested by the professional driver in fig. 9 may also be understood as the second brake deceleration in the embodiment of the present application. In the case where the second brake deceleration is smaller than the safe brake deceleration, the EBA system takes the safe brake deceleration as the target brake deceleration. The EBA system provides an emergency braking auxiliary function based on the target braking deceleration so as to realize active pressure build-up, so that the vehicle can reach the target braking deceleration more quickly, and the driving safety is improved.

In addition, as can be seen from fig. 9, in the case of the emergency braking condition, the other emergency braking auxiliary systems directly output the threshold value of the ABS system, that is, the maximum braking deceleration, without considering the subjective intention of the driver and the safe braking deceleration, which affects the user experience, or even has a potential safety hazard.

As previously described, method 300 may be applied during an emergency braking condition. Illustratively, in the case of an emergency braking condition, step S320 is executed to transmit an indication of the target braking deceleration.

The identification process of the emergency braking condition in the embodiment of the application can also be understood as the identification process of the emergency braking intention of the driver.

If the method 300 is applied to an EBA system, after recognizing the current situation as an emergency braking condition or recognizing the driver's emergency braking intention, the emergency braking assistance function may be triggered, that is, sending the indication information of the target braking deceleration, and instructing the target vehicle to actively boost the brake master cylinder.

Optionally, before sending the indication information of the target brake deceleration, the pressure information of the brake master cylinder of the target vehicle satisfies at least one of the following conditions: the slope of the pressure of the master cylinder of the target vehicle is greater than or equal to a first threshold value or the pressure of the master cylinder of the target vehicle is greater than or equal to a second threshold value, the first threshold value being determined according to the speed of the target vehicle. The second threshold is determined based on the speed of the target vehicle.

The first threshold and the second threshold are described in detail in method 1000.

That is, the EBA system can recognize the driver's emergency braking intention from the speed of the target vehicle and the pressure information of the master cylinder of the target vehicle. For example, when the pressure information of the master cylinder of the target vehicle satisfies at least one item described above, it is determined that the driver has an emergency braking intention, and the emergency braking assist function is triggered.

The conventional emergency braking auxiliary system generally compares information such as pedal signals or vehicle speed with a set threshold value, judges whether a current scene is an emergency braking working condition according to a comparison result, and provides an emergency braking auxiliary function after the emergency braking working condition is identified. However, the accuracy of the above determination method is low, which results in a high false triggering rate of the emergency braking assistance function, and may provide unnecessary braking deceleration for the driver, thereby reducing user experience and also having potential safety hazards.

The threshold value in the embodiment of the application is not a fixed value, but is determined according to the speed of the target vehicle, and whether the driver has the emergency braking intention or not is judged by comparing the pressure information of the brake master cylinder with the threshold value determined according to the vehicle speed, so that the accuracy of the emergency braking intention of the driver can be improved.

The embodiment of the application provides a method 900 for identifying the urgent braking intention of a driver. The method may be performed by the emergency braking intent recognition module 210 of fig. 2. The driver having an emergency braking intention may be one of the triggering conditions of step S320. That is, the result of the identification method of the driver' S emergency braking intention may be used to trigger step S320.

The method for recognizing the driver' S intention to brake urgently includes steps S910 to S920, which will be described below.

S910, information of the target vehicle is acquired.

The information of the target vehicle includes movement information of the target vehicle and pressure information of a brake master cylinder of the target vehicle.

The motion information of the target vehicle includes a speed of the target vehicle. The pressure information of the brake master cylinder of the target vehicle includes at least one of: a pressure slope of a master cylinder of the target vehicle or a pressure of a master cylinder of the target vehicle.

For example, the pressure information of the brake master cylinder of the target vehicle may be acquired periodically. For example, the pressure of the brake master cylinder is acquired every period, and the pressure gradient of the brake master cylinder of the target vehicle can be determined according to the cylinder pressure variation value of the target vehicle in the period.

It should be understood that the above is merely an illustration, and the pressure information of the brake master cylinder of the target vehicle may be obtained according to other frequencies, which is not limited in the embodiment of the present application.

And S920, when the pressure information of the brake master cylinder of the target vehicle meets at least one of the following conditions, judging that the driver has an emergency braking intention: the slope of the pressure of the master cylinder of the target vehicle is greater than or equal to a first threshold, or the pressure of the master cylinder of the target vehicle is greater than or equal to a second threshold.

Wherein the first threshold is determined based on the speed of the target vehicle. The second threshold is determined based on the speed of the target vehicle.

The determination result may be one of the triggering conditions of the step S320, or one of the triggering conditions of the emergency braking auxiliary function. That is, when the pressure information of the brake master cylinder of the target vehicle satisfies the condition in step S302, it is determined that the driver has an urgent braking intention. The driver has an emergency braking intention before the indication information of the target braking deceleration is transmitted.

Illustratively, before the indication information of the target brake deceleration is transmitted, the pressure information of the brake master cylinder of the target vehicle satisfies the following condition: the pressure slope of the master cylinder of the target vehicle is greater than or equal to a first threshold.

That is, in the case where the pressure gradient of the brake master cylinder of the target vehicle is greater than or equal to the first threshold value, it is possible to trigger transmission of the indication information of the target brake deceleration. In the case where the pressure gradient of the brake master cylinder of the target vehicle is less than the first threshold value, step S320 is not performed.

Alternatively, before the transmission of the indication information of the target brake deceleration, the pressure information of the brake master cylinder of the target vehicle satisfies the following condition: the pressure of the brake master cylinder of the target vehicle is greater than or equal to a second threshold value.

That is, in the case where the pressure of the brake master cylinder of the target vehicle is greater than or equal to the second threshold value, it is possible to trigger transmission of the indication information of the target brake deceleration. In the case where the pressure of the brake master cylinder of the target vehicle is less than the second threshold value, step S320 is not performed.

Alternatively, before the transmission of the indication information of the target brake deceleration, the pressure information of the brake master cylinder of the target vehicle satisfies the following condition: the pressure slope of the brake master cylinder of the target vehicle is greater than or equal to a first threshold value, and the pressure of the brake master cylinder of the target vehicle is greater than or equal to a second threshold value.

That is, in the case where the slope of the pressure of the master cylinder of the target vehicle is greater than or equal to the first threshold value and the pressure of the master cylinder of the target vehicle is greater than or equal to the second threshold value, it is possible to trigger the transmission of the indication information of the target brake deceleration. Step S320 is not performed in the case where the pressure gradient of the brake master cylinder of the target vehicle is less than the first threshold value or the pressure of the brake master cylinder of the target vehicle is less than the second threshold value.

Further, the recognition result of the emergency braking intention may be combined with the determination result of the danger level as the trigger condition of step S320, or in other words, as the trigger condition of the emergency braking assistance function.

Optionally, before transmitting the indication information of the target braking deceleration, at least one of the following conditions is satisfied: the danger level of the current driving scenario is greater than or equal to the second level threshold, or the driver has an emergency braking intent.

For example, in the case where the danger level of the current driving scenario is greater than or equal to the second level threshold or the driver has an urgent braking intention, the indication information of the target braking deceleration is transmitted.

Therefore, the driving safety can be further improved, and the collision risk caused by judgment errors of the driver is avoided.

Alternatively, in the case where the risk level of the current driving scenario is greater than or equal to the second level threshold and the driver has an emergency braking intention, the indication information of the target braking deceleration is transmitted.

For example, step S320 may include: and sending indication information of the target braking deceleration under the condition that the danger level of the current driving scene is greater than or equal to the second level threshold value and the pressure gradient of a brake master cylinder of the target vehicle is greater than or equal to the first threshold value.

In the case where the danger level of the current driving scenario is less than the second level threshold, or the pressure slope of the master cylinder of the target vehicle is less than the first threshold, step S320 is not performed.

Therefore, the accuracy of triggering the emergency braking auxiliary function can be further improved, the condition of false triggering is avoided, and the user experience is improved.

As previously mentioned, the first threshold is determined based on the speed of the target vehicle.

The first threshold value has a mapping relationship with the speed of the vehicle. For example, the mapping may be reflected as a functional expression, i.e. the first threshold may be expressed as a function of the speed of the vehicle.

A method 1000 of determining a mapping between a first threshold and a speed of a vehicle is shown in fig. 10. The method 1000 includes steps S1010 to S1020, and the steps S1010 to S1020 will be described below.

S1010, obtaining the maximum pressure slope of the brake master cylinder in each group of brake data in the plurality of groups of brake data.

The multiple groups of brake data are brake data acquired in the natural driving process. And respectively extracting the maximum pressure slope of the brake master cylinder in each group of brake data from the plurality of groups of brake data, namely the maximum pressure slope of the brake master cylinder in each braking process.

And S1020, fitting the relation between the first threshold value and the speed of the vehicle according to the distribution condition of the pressure slope of the maximum brake master cylinder under the emergency braking condition and the non-emergency braking condition in the plurality of groups of brake data.

The plurality of groups of braking data comprise braking data acquired under an emergency braking working condition and braking data acquired under a non-emergency braking working condition. For example, a group of brake data may be determined by a professional driver to belong to brake data collected under an emergency brake condition or brake data collected under a non-emergency brake condition.

The relationship between the first threshold and the speed of the vehicle may be expressed as: p _ thr ═ g (v).

Where v represents the speed of the vehicle, p _ thr' represents a first threshold, and g () represents a function.

FIG. 11 shows the distribution of the pressure slopes of the largest master cylinder for emergency and non-emergency braking conditions with the vehicle at the same speed. The straight line in fig. 11 is the first threshold corresponding to the speed. As shown in fig. 11, at this speed, the pressure slopes of the master cylinders under the emergency braking condition are all located at the upper part in fig. 11, and the pressure slopes of the master cylinders under the non-emergency braking condition are all located at the lower part in fig. 11, so that the threshold is obtained through fitting, and the pressure slopes of the master cylinders under the emergency braking condition and the non-emergency braking condition are distinguished, and the threshold is the first threshold corresponding to the speed.

As previously mentioned, the second threshold is determined based on the speed of the target vehicle.

The second threshold value has a mapping relationship with the speed of the vehicle. For example, the mapping may be reflected as a functional expression, i.e., the second threshold may be expressed as a function of the speed of the vehicle.

For example, the method for determining the mapping relationship between the second threshold and the speed of the vehicle may refer to the method in fig. 10. Specifically, the mapping relationship between the second threshold value and the speed of the vehicle may be determined by the following steps.

And S1, acquiring the pressure of the largest brake master cylinder in each group of brake data in the plurality of groups of brake data.

The multiple groups of brake data are brake data acquired in the natural driving process. And respectively extracting the maximum pressure of the brake master cylinder in each group of brake data, namely the maximum pressure of the brake master cylinder in each braking process from the plurality of groups of brake data.

And S2, fitting the relation between the second threshold value and the speed of the vehicle according to the maximum brake master cylinder pressure distribution under the emergency brake working condition and the non-emergency brake working condition in the plurality of groups of brake data.

The specific fitting manner can refer to the manner in fig. 11, and is not described herein again.

Fig. 12 illustrates a driver braking intention identification method 1100 provided by an embodiment of the present application, and the method 1100 in fig. 12 can be regarded as a specific implementation manner of the method 900, and specific description can be referred to the aforementioned method 900.

For example, fig. 12 may be performed by emergency braking intent identification module 210 in fig. 2.

The method 1100 includes steps S1110 to S1140, and the following describes steps S1110 to S1140.

S1110, the pressure of the brake master cylinder of the target vehicle is acquired.

For example, the pressure of the brake master cylinder is periodically detected.

S1120, the pressure slope of the master cylinder is calculated.

S1130, the speed of the target vehicle is acquired.

S1140, a first threshold value and a second threshold value are calculated according to the speed of the target vehicle.

S1150, it is determined whether the pressure slope of the brake master cylinder of the target vehicle is greater than or equal to a first threshold value and whether the pressure of the brake master cylinder of the target vehicle is greater than or equal to a second threshold value.

Taking the current scene as an emergency braking working condition under the condition that the pressure slope of the brake master cylinder of the target vehicle is greater than or equal to a first threshold value and the pressure of the brake master cylinder of the target vehicle is greater than or equal to a second threshold value; otherwise, the current scene is taken as a non-emergency braking working condition.

It should be understood that the steps of method 1100 are merely exemplary and are not intended to limit the embodiments of the present application. For example, step S1140 may also calculate the first threshold value according to the speed of the target vehicle. Accordingly, step S1150 may also be implemented by determining whether the pressure slope of the brake master cylinder of the target vehicle is greater than or equal to the first threshold. Taking the current scene as an emergency braking working condition under the condition that the pressure slope of a brake master cylinder of the target vehicle is greater than or equal to a first threshold value; and under the condition that the pressure gradient of a brake master cylinder of the target vehicle is smaller than a first threshold value, taking the current scene as a non-emergency working condition. For another example, method 1100 may not include S1120, and accordingly, step S1140 may calculate the second threshold value based on the speed of the target vehicle. Step S1150 may also be determining whether the pressure of the brake master cylinder of the target vehicle is greater than or equal to a second threshold value. Taking the current scene as an emergency braking working condition under the condition that the pressure of a brake master cylinder of the target vehicle is greater than or equal to a second threshold value; and under the condition that the pressure of a brake master cylinder of the target vehicle is smaller than a second threshold value, taking the current scene as a non-emergency working condition.

In the embodiment of the present application, whether the driver has an emergency braking intention is determined by comparing the pressure information of the brake master cylinder with the threshold value determined according to the speed of the target vehicle, which can improve the accuracy of the driver's emergency braking intention.

The apparatus according to the embodiment of the present application will be described with reference to fig. 13 to 14. It should be understood that the apparatus described below is capable of performing the method of the foregoing embodiments of the present application, and in order to avoid unnecessary repetition, the repeated description is appropriately omitted below when describing the apparatus of the embodiments of the present application.

Fig. 13 is a schematic diagram of a vehicle control device of the embodiment of the present application. The apparatus 2000 includes an acquisition unit 2001 and a transmission unit 2002. The apparatus 2000 may be configured to perform the steps of the vehicle control method according to the embodiment of the present application. For example, the acquisition unit 2001 may be used to perform step S310 in the method illustrated in fig. 3, and the transmission unit 2002 may be used to perform step S320 in the method illustrated in fig. 3.

Specifically, the acquisition unit 2001 is configured to acquire information of a target vehicle including movement information of the target vehicle and pressure information of a brake master cylinder of the target vehicle. A transmitting unit 2002 for transmitting indication information of a target braking deceleration for indicating that the target vehicle performs brake boosting on the brake master cylinder, the target braking deceleration being predicted from information of the target vehicle.

Alternatively, as one embodiment, the target braking deceleration is determined based on a first braking deceleration that is obtained by processing information of the target vehicle by a braking deceleration prediction model.

Optionally, as an embodiment, the brake deceleration prediction model is trained based on at least one training sample, the training sample includes information of the training vehicle and a sample label of the training sample, the information of the training vehicle includes motion information of the training vehicle and pressure information of a brake master cylinder of the training vehicle, and the sample label of the training sample is used for indicating the brake deceleration requested by a driver of the training vehicle.

Optionally, as an embodiment, the pressure information of the brake master cylinder of the target vehicle includes a pressure gradient of the brake master cylinder of the target vehicle, and the pressure gradient of the brake master cylinder of the target vehicle is greater than or equal to the first threshold value before the indication information of the target braking deceleration is transmitted.

Optionally, as an embodiment, the motion information of the target vehicle includes a speed of the target vehicle, and the first threshold is determined according to the speed of the target vehicle.

Alternatively, as an embodiment, the target braking deceleration is determined according to a second braking deceleration, which is obtained by processing the first braking deceleration by a target gain factor, and the target gain factor has a mapping relation with the danger level of the current driving scenario.

Alternatively, as one embodiment, the target braking deceleration is determined based on the larger absolute value of the second braking deceleration and a safety braking deceleration that is used to indicate the braking deceleration required by the target vehicle to avoid the collision.

Fig. 14 is a schematic diagram of a control device according to an embodiment of the present application. The apparatus 3000 may include at least one processor 3002 and a communication interface 3003.

Optionally, the apparatus 3000 may further comprise at least one of a memory 3001 and a bus 3004. Any two or all three of the memory 3001, the processor 3002 and the communication interface 3003 may be communicatively coupled to each other via a bus 3004.

Alternatively, the memory 3001 may be a Read Only Memory (ROM), a static memory device, a dynamic memory device, or a Random Access Memory (RAM). The memory 3001 may store a program, and the processor 3002 and the communication interface 3003 are used to execute the respective steps of the control method of the vehicle of the embodiment of the present application when the program stored in the memory 3001 is executed by the processor 3002. That is, the processor 3002 may retrieve stored instructions from the memory 3001 via the communication interface 3003 to perform the various steps of the vehicle control method of the embodiments of the present application.

Alternatively, the memory 3001 may have the function of the memory 152 shown in fig. 1 to realize the above-described function of storing the program. Alternatively, the processor 3002 may be a general-purpose CPU, a microprocessor, an ASIC, a Graphics Processing Unit (GPU) or one or more integrated circuits, and is configured to execute a relevant program to implement the functions required to be executed by the units in the control device according to the embodiment of the present application or to execute the steps of the control method according to the embodiment of the present application.

Alternatively, the processor 3002 may have the functions of the processor 151 shown in fig. 1 to implement the above-described functions of executing the relevant programs.

Alternatively, the processor 3002 may be an integrated circuit chip having signal processing capability. In implementation, the steps of the control method of the embodiment of the present application may be implemented by integrated logic circuits of hardware in a processor or instructions in the form of software.

Alternatively, the processor 3002 may be a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory, and in conjunction with hardware thereof, performs functions required to be performed by units included in the control device of the vehicle of the embodiment of the present application, or performs the respective steps of the vehicle control method of the embodiment of the present application.

Alternatively, communication interface 3003 may enable communication between the apparatus and other devices or communication networks using transceiver means such as, but not limited to, a transceiver. The communication interface 3003 may also be an interface circuit, for example.

Bus 3004 may include a pathway to transfer information between various components of the device (e.g., memory, processor, communication interface).

Embodiments of the present application also provide a computer program product containing instructions, which when executed by a computer, cause the computer to implement the method in the above method embodiments.

An embodiment of the present application further provides a terminal, where the terminal includes any one of the above control devices, for example, the control device shown in fig. 13 or fig. 14.

Illustratively, the terminal may be a vehicle. Alternatively, the terminal may be a terminal for remotely controlling the vehicle.

The control device may be mounted on the target vehicle or may be independent of the target vehicle, and may control the target vehicle using, for example, an unmanned aerial vehicle, another vehicle, a robot, or the like.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the present application in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

Various aspects or features of the disclosure may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques. The term "article of manufacture" as used herein is intended to encompass a computer program accessible from any computer-readable device, carrier, or media. For example, computer-readable media may include, but are not limited to: magnetic storage devices (e.g., hard disk, floppy disk, or magnetic tape), optical disks (e.g., Compact Disk (CD), Digital Versatile Disk (DVD), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memory (EPROM), card, stick, or key drive, etc.).

Various storage media described herein can represent one or more devices and/or other machine-readable media for storing information. The term "machine-readable medium" can include, but is not limited to: wireless channels and various other media capable of storing, containing, and/or carrying instruction(s) and/or data.

It should be noted that when the processor is a general-purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, the memory (memory module) may be integrated into the processor.

It should also be noted that the memories described herein are intended to comprise, without being limited to, these and any other suitable types of memories.

Those of ordinary skill in the art will appreciate that the various illustrative elements and 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.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. Furthermore, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through 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 unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, or portions thereof, may be embodied in the form of a computer software product stored in a storage medium, the computer software product including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the methods described in the embodiments of the present application. The foregoing storage media may include, but are not limited to: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A vehicle control method characterized by comprising:

acquiring information of a target vehicle, wherein the information of the target vehicle comprises movement information of the target vehicle and pressure information of a brake master cylinder of the target vehicle;

and sending indication information of target brake deceleration, wherein the indication information of the target brake deceleration is used for indicating the target vehicle to perform brake pressurization on a brake master cylinder, and the target brake deceleration is predicted according to the information of the target vehicle.

2. The method according to claim 1, characterized in that the target braking deceleration is determined from a first braking deceleration, which is obtained by processing information of the target vehicle by a braking deceleration prediction model.

3. The method according to claim 2, wherein the brake deceleration prediction model is trained based on at least one training sample, the training sample comprising information of a training vehicle and a sample label of the training sample, the information of the training vehicle comprising motion information of the training vehicle and pressure information of a brake master cylinder of the training vehicle, the sample label of the training sample being indicative of a brake deceleration requested by a driver of the training vehicle.

4. The method according to any one of claims 1 to 3, further comprising:

acquiring environment perception information of the target vehicle;

wherein the target braking deceleration is predicted from information of the target vehicle and environment perception information of the target vehicle.

5. The method according to any one of claims 1 to 4, wherein the pressure information of the brake master cylinder of the target vehicle includes a pressure slope of the brake master cylinder of the target vehicle, the pressure slope of the brake master cylinder of the target vehicle being greater than or equal to a first threshold value before the information indicative of the target brake deceleration is sent.

6. The method of claim 5, wherein the motion information of the target vehicle comprises a speed of the target vehicle, and the first threshold is determined based on the speed of the target vehicle.

7. The method according to any one of claims 2 to 6, characterized in that the target brake deceleration is determined from a second brake deceleration, which is obtained by processing the first brake deceleration by a target gain factor, which has a mapping relationship with the risk level of the current driving scenario.

8. The method according to claim 7, characterized in that the target braking deceleration is determined according to one of the second braking deceleration and a safety braking deceleration, the absolute value of which is larger, the safety braking deceleration being used to represent a braking deceleration required for collision avoidance of the target vehicle.

9. A vehicle control apparatus characterized by comprising:

an acquisition unit configured to acquire information of a target vehicle, the information of the target vehicle including movement information of the target vehicle and pressure information of a brake master cylinder of the target vehicle;

a transmitting unit configured to transmit indication information of a target brake deceleration, which is used to indicate that the target vehicle performs brake boosting on a brake master cylinder, the target brake deceleration being predicted from information of the target vehicle.

10. The apparatus according to claim 9, characterized in that the target braking deceleration is determined based on a first braking deceleration that is obtained by processing information of the target vehicle by a braking deceleration prediction model.

11. The apparatus of claim 10, wherein the brake deceleration prediction model is trained based on at least one training sample, the training sample including information of a training vehicle and a sample label of the training sample, the information of the training vehicle including motion information of the training vehicle and pressure information of a brake master cylinder of the training vehicle, the sample label of the training sample indicating a brake deceleration requested by a driver of the training vehicle.

12. The apparatus according to any one of claims 9 to 11, wherein the pressure information of the brake master cylinder of the target vehicle includes a pressure slope of the brake master cylinder of the target vehicle, the pressure slope of the brake master cylinder of the target vehicle being greater than or equal to a first threshold value before the indication information of the target brake deceleration is transmitted.

13. The apparatus of claim 12, wherein the motion information of the target vehicle includes a speed of the target vehicle, and the first threshold is determined based on the speed of the target vehicle.

14. The apparatus according to any one of claims 10 to 13, characterized in that the target brake deceleration is determined according to a second brake deceleration that is obtained by processing the first brake deceleration by a target gain factor having a mapping relationship with a risk level of a current driving scene.

15. The apparatus according to claim 14, characterized in that the target braking deceleration is determined according to one of the second braking deceleration and a safety braking deceleration, the absolute value of which is larger, the safety braking deceleration being used to represent a braking deceleration required for collision avoidance of the target vehicle.

16. A chip comprising at least one processor and interface circuitry, the at least one processor fetching instructions stored on a memory through the interface circuitry to perform the method of any one of claims 1 to 8.

17. A computer-readable storage medium, characterized in that the computer-readable medium stores program code for execution by a device, the program code comprising instructions for performing the method of any of claims 1 to 8.

18. A terminal, characterized in that it comprises an arrangement according to any of claims 9-15.

19. The terminal of claim 18, further comprising a master cylinder.