Vehicle control method and device

Abstract

The invention provides a vehicle control method and device. The method can be applied to the field of intelligent driving. The method comprises the steps of obtaining information of an obstacle in front of a vehicle; controlling the vehicle to decelerate by adopting a braking strategy according to the information of the obstacle; when the vehicle distance shortening value between the vehicle and the following vehicle behind the vehicle is larger than or equal to the vehicle distance shortening limit value, the vehicle is controlled to decelerate by adopting another braking strategy, and the vehicle distance shortening limit value is obtained through sample data statistics; the sample data includes data indicative of a driving parameter of a sample vehicle and a driving parameter of a following vehicle of the sample vehicle. The method can be applied to an intelligent automobile or an electric automobile, and the risk of rear-end collision between the following automobile and the automobile in the braking process of the automobile can be reduced.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving, and more specifically, to a vehicle control method and device. Background Art

[0002] For vehicles equipped with assisted driving and advanced autonomous driving functions, the vehicle will directly control the brakes, control the vehicle speed or avoid collisions based on the forward obstacles and scenario requirements.

[0003] Even if there are obstacles ahead (e.g., static obstacles, pedestrians crossing the road, etc.), the vehicle should not only focus on the target ahead when braking to avoid collision, but should also consider the following vehicles behind. For example, in a scenario where there are cartons or scattered branches in front of the vehicle and there is a closely following vehicle behind, it would be unreasonable to cause the following vehicle to rear-end the vehicle in order to completely avoid collision with the target ahead.

[0004] Therefore, how to balance the risk of rear-end collision during braking has become an urgent problem to be solved. Summary of the invention

[0005] The present application provides a vehicle control method and device, which are helpful to reduce the risk of rear-end collision between a following vehicle and the vehicle during braking.

[0006] In a first aspect, a vehicle control method is provided, the method comprising: obtaining information of an obstacle in front of a vehicle; controlling the vehicle to decelerate using a first braking strategy according to the information of the obstacle; controlling the vehicle to decelerate using a second braking strategy when a distance shortening value between the vehicle and a following vehicle behind the vehicle within a first time period is greater than or equal to a first distance shortening limit value, the first distance shortening limit value being obtained by statistics of sample data, the sample data comprising data indicating driving parameters of the sample vehicle and driving parameters of a following vehicle of the sample vehicle; wherein the first braking strategy indicates that a braking deceleration of the vehicle within a second time period is a first braking deceleration, the second braking strategy indicates that a braking deceleration of the vehicle within the second time period is a second braking deceleration, the first braking deceleration is greater than the second braking deceleration, and the second time period is located after the first time period.

[0007] Based on the above technical solution, when the vehicle determines that the distance between the following vehicle and the vehicle is shortened too fast during braking, the braking deceleration can be controlled to decrease, so as to avoid rear-end collision between the vehicle and the following vehicle. At the same time, the first distance shortening limit is obtained based on the driving parameters of the sample vehicle and the driving parameters of the following vehicle of the sample vehicle. Different from overly conservative empirical data, it can maximize the performance of the vehicle and solve the uncertainty technical problem of the vehicle's perception system to a certain extent.

[0008] In addition, the vehicle will judge the relationship between the distance shortening value within a period of time and the first distance shortening limit value, and will not limit the instantaneous braking capability, which will impose less instantaneous constraints on the active braking function.

[0009] In some possible implementations, the method further includes: receiving information of the first vehicle distance shortening limit sent by a cloud server.

[0010] In some possible implementations, the sample data may be raw data collected by a sensor (e.g., a camera, a millimeter-wave radar, a laser radar, etc.) located behind the sample vehicle, or may be driving parameters of the sample vehicle and driving parameters of the following vehicle of the sample vehicle determined by the sample vehicle based on the raw data collected by the sensor located behind the sample vehicle. In some possible implementations, the second braking strategy may avoid a collision between the vehicle and an obstacle, or the second braking deceleration may be greater than the third braking deceleration, and the third braking deceleration is a limit deceleration for avoiding a collision between the vehicle and an obstacle.

[0011] In some possible implementations, controlling the vehicle to slow down using the first braking deceleration based on the obstacle information may include controlling the vehicle to slow down using the first braking strategy after the vehicle detects that the vehicle in front of the vehicle brakes; or controlling the vehicle to slow down using the first braking strategy when the vehicle detects that it is about to reach a traffic light intersection and the intersection indicator light is red.

[0012] The braking deceleration in the embodiment of the present application can be understood as the absolute value of the acceleration of the vehicle during the braking process.

[0013] In combination with the first aspect, in certain implementations of the first aspect, the sample data includes data indicating the initial speed of the sample vehicle during braking, the initial vehicle distance between the sample vehicle and the vehicle following the sample vehicle, the reaction time of the vehicle following the sample vehicle, and the speed characteristics of the vehicle following the sample vehicle.

[0014] Based on the above technical solution, typical rear vehicle models under different vehicle speeds and scenarios can be generalized based on on-site statistical data. Combined with the distance change information between the sample vehicle and the following vehicle of the sample vehicle, the relationship between the distance reduction limit and the braking time between the vehicle and the following vehicle during the braking process can be obtained. Different from overly conservative empirical data, it can maximize the performance of the vehicle and solve the uncertainty technical problem of the vehicle's perception system to a certain extent.

[0015] In some possible implementations, the sample data includes information indicating the initial speed of the sample vehicle during braking, the initial vehicle distance between the sample vehicle and the vehicle following the sample vehicle, the reaction time of the vehicle following the sample vehicle, and the change in braking deceleration of the vehicle following the sample vehicle.

[0016] In some possible implementations, the sample data includes information indicating the initial speed of the sample vehicle during braking, the initial vehicle distance between the sample vehicle and the vehicle following the sample vehicle, the reaction time of the vehicle following the sample vehicle, and the vehicle distance change information between the sample vehicle and the vehicle following the sample.

[0017] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: when the vehicle adopts the first braking strategy to decelerate, obtaining a first speed of the vehicle; determining the first vehicle distance shortening limit value based on the first speed and a mapping relationship, wherein the mapping relationship includes a correspondence between the vehicle speed and the vehicle distance shortening limit value.

[0018] Based on the above technical solution, since the distance between the vehicle and the following vehicle and the driver's tolerance for the shortened distance are different at different initial vehicle speeds, the embodiment of the present application can refine the scene based on the vehicle speed, and have different restriction strategies under different vehicle speed scenes. In this way, the vehicle can obtain the corresponding distance shortening limit value under different scenes, which helps to improve the accuracy of the vehicle's longitudinal control and avoid rear-end collisions.

[0019] In some possible implementations, the mapping relationship includes a correspondence between vehicle speed, reaction time, initial vehicle distance and vehicle distance shortening limit, and the method includes: when the vehicle adopts the first braking strategy to decelerate, obtaining the first speed of the vehicle, the first reaction time of the following vehicle and the first initial vehicle distance between the vehicle and the following vehicle; determining the first vehicle distance shortening limit according to the first speed and the mapping relationship, including: determining the first vehicle distance shortening limit according to the first speed, the first reaction time, the first initial vehicle distance and the mapping relationship.

[0020] In combination with the first aspect, in certain implementations of the first aspect, the mapping relationship includes a correspondence between vehicle speed, vehicle type, and vehicle distance shortening limit, and the method further includes: obtaining the type of the following vehicle; wherein, determining the first vehicle distance shortening limit based on the first speed and the mapping relationship includes: determining the first vehicle distance shortening limit based on the first speed, the type of the following vehicle, and the mapping relationship.

[0021] Based on the above technical solution, different types of following vehicles have different braking performances, which will lead to different braking capabilities. When performing data statistics, the relationship between different types of following vehicles and the vehicle distance reduction limit can be considered. In this way, for different types of following vehicles, the vehicle can find the corresponding vehicle distance reduction limit through the mapping relationship, which helps to improve the accuracy of the vehicle's longitudinal control, thereby helping to improve the safety of the vehicle.

[0022] Exemplarily, the mapping relationship includes the correspondence between vehicle speed, passenger vehicles (such as sedans, SUVs, etc.) and vehicle distance reduction limit values, and the correspondence between vehicle speed, large vehicles (such as buses, trucks, etc.) and vehicle distance reduction limit values.

[0023] In combination with the first aspect, in certain implementations of the first aspect, the mapping relationship includes a correspondence between vehicle speed, season, and vehicle distance shortening limit, and the method further includes: obtaining information about the season in which the vehicle is located; wherein, determining the first vehicle distance shortening limit based on the first speed and the mapping relationship includes: determining the first vehicle distance shortening limit based on the first speed, information about the season, and the mapping relationship.

[0024] Based on the above technical solution, due to different parameters such as the grip and tire pressure of the vehicle's tires in different seasons, its braking ability will be different. The relationship between different seasons and the distance reduction limit can be considered when performing data statistics. In this way, for different seasons, the vehicle can find the corresponding distance reduction limit through the mapping relationship, which helps to improve the accuracy of the vehicle's longitudinal control, thereby helping to improve the safety of the vehicle.

[0025] In combination with the first aspect, in certain implementations of the first aspect, the mapping relationship includes a correspondence between vehicle speed, city, and vehicle distance shortening limit, and the method further includes: obtaining information of a first city in which the vehicle is located; wherein, determining the first vehicle distance shortening limit based on the first speed and the mapping relationship includes: determining the first vehicle distance shortening limit based on the first speed, information of the first city, and the mapping relationship.

[0026] Based on the above technical solution, due to the regional differences in traffic congestion levels in different cities, driving habits or personality of drivers, different vehicle braking restriction strategies will be caused. When performing data statistics, the relationship between different cities and the vehicle headway reduction limit can be considered. In this way, for different cities, the vehicle can find the corresponding vehicle headway reduction limit through the mapping relationship, which helps to improve the accuracy of the vehicle's longitudinal control, thereby helping to improve the safety of the vehicle.

[0027] In combination with the first aspect, in certain implementations of the first aspect, determining the first vehicle distance shortening limit value based on the first speed and the mapping relationship includes: determining multiple vehicle distance shortening limit values ​​based on the first speed and the mapping relationship, the multiple vehicle distance shortening limit values ​​including the first vehicle distance shortening limit value corresponding to the first time period.

[0028] Based on the above technical solution, the vehicle distance reduction limit values ​​in different time periods are obtained based on the driving parameters of the sample vehicle and the driving parameters of the following vehicle of the sample vehicle. Different from overly conservative empirical data, the vehicle performance can be released to the maximum extent, and the uncertainty technical problem of the vehicle perception system can be solved to a certain extent. At the same time, the vehicle can detect the distance reduction value between the vehicle and the following vehicle based on the vehicle distance reduction limit values ​​in different time periods, which helps to further improve the accuracy of the vehicle longitudinal control, thereby helping to improve the safety of the vehicle.

[0029] In combination with the first aspect, in certain implementations of the first aspect, the method also includes: sending data indicating the initial speed of the vehicle during braking, the initial vehicle distance between the vehicle and the vehicle following the vehicle, the reaction time of the vehicle's following vehicle, and the speed characteristics of the vehicle's following vehicle to a cloud server.

[0030] Based on the above technical solution, after the braking process is completed, the vehicle can send data indicating the parameters of the vehicle and the vehicle following it during the braking process to the cloud server. In this way, after receiving multiple sample data, the cloud server can update the statistical results of the vehicle distance reduction limit value. This ensures the accuracy (or "freshness") of the vehicle distance reduction limit values ​​in different scenarios obtained by the cloud server.

[0031] In combination with the first aspect, in some implementations of the first aspect, the method further includes: receiving the updated mapping relationship sent by the cloud server.

[0032] Based on the above technical solution, the vehicle can receive the updated mapping relationship, so that the updated mapping relationship can be saved in the vehicle. The vehicle can determine the corresponding vehicle distance shortening limit based on the updated mapping relationship, which helps to improve the accuracy of the vehicle longitudinal control, thereby helping to improve the safety of the vehicle.

[0033] In combination with the first aspect, in certain implementations of the first aspect, the second braking deceleration is less than an average value of the braking deceleration of the vehicle in the first time period.

[0034] Based on the above technical solution, the braking deceleration of the vehicle in the second time period can be controlled to be less than the average braking deceleration in the first time period. In this way, when the distance between the vehicle and the vehicle following it is shortened too much in the first time period, the braking deceleration of the vehicle can be controlled to decrease, thereby reducing the risk of the rear vehicle rear-ending the front vehicle.

[0035] In combination with the first aspect, in certain implementations of the first aspect, controlling the vehicle to decelerate using a first braking strategy based on the information of the obstacle includes: when an automatic emergency braking (AEB) function is triggered based on the information of the obstacle, controlling the vehicle to decelerate using the first braking strategy.

[0036] Based on the above technical solution, when the AEB function is triggered, the vehicle can formulate the first braking strategy according to the information of the obstacle. In the process of executing the first braking strategy, the vehicle can determine whether to adjust the braking strategy based on the relationship between the vehicle distance reduction value between the vehicle and the vehicle following it and the first vehicle distance reduction limit. In this way, the vehicle can comprehensively consider the information of the obstacle in front of the vehicle and the vehicle following it, which helps to avoid a collision between the vehicle and the obstacle, and can also avoid a rear-end collision between the following vehicle and the vehicle.

[0037] In some possible implementations, the vehicle is in an automatic driving state. Exemplarily, the vehicle is in a state where an adaptive cruise control (ACC) function, an integrated cruise assist (ICA) function, or a navigation cruise assist (NCA) function is turned on.

[0038] In a second aspect, a vehicle control device is provided, which includes: an acquisition unit for acquiring information about an obstacle in front of the vehicle; a control unit for controlling the vehicle to adopt a first braking strategy to decelerate according to the information about the obstacle; the control unit is also used to control the vehicle to adopt a second braking strategy to decelerate when a distance reduction value between the vehicle and a following vehicle behind the vehicle in a first time period is greater than or equal to a first distance reduction limit value, the first distance reduction limit value being obtained by statistics of sample data, the sample data including data for indicating driving parameters of the sample vehicle and driving parameters of the following vehicle of the sample vehicle; wherein the first braking strategy indicates that the braking deceleration of the vehicle in the second time period is a first braking deceleration, the second braking strategy indicates that the braking deceleration of the vehicle in the second time period is a second braking deceleration, the first braking deceleration is greater than the second braking deceleration, and the second time period is located after the first time period.

[0039] In combination with the second aspect, in certain implementations of the second aspect, the sample data includes data indicating the initial speed of the sample vehicle during braking, the initial vehicle distance between the sample vehicle and the vehicle following the sample vehicle, the reaction time of the vehicle following the sample vehicle, and the speed characteristics of the vehicle following the sample vehicle.

[0040] In combination with the second aspect, in certain implementations of the second aspect, the device also includes a determination unit, wherein the acquisition unit is further used to acquire a first speed of the vehicle when the vehicle adopts the first braking strategy to decelerate; the determination unit is used to determine the first vehicle distance shortening limit based on the first speed and a mapping relationship, and the mapping relationship includes a correspondence between the vehicle speed and the vehicle distance shortening limit.

[0041] In combination with the second aspect, in certain implementations of the second aspect, the mapping relationship includes a correspondence between vehicle speed, vehicle type, and vehicle distance shortening limit value, and the acquisition unit is further used to obtain the type of the following vehicle; the determination unit is used to determine the first vehicle distance shortening limit value based on the first speed, the type of the following vehicle, and the mapping relationship.

[0042] In combination with the second aspect, in certain implementations of the second aspect, the mapping relationship includes a correspondence between vehicle speed, season, and vehicle distance shortening limit, and the acquisition unit is further used to obtain information about the season in which the vehicle is located; the determination unit is used to determine the first vehicle distance shortening limit based on the first speed, the season information, and the mapping relationship.

[0043] In combination with the second aspect, in certain implementations of the second aspect, the mapping relationship includes a correspondence between vehicle speed, city, and vehicle distance shortening limit, and the acquisition unit is used to obtain information about a first city in which the vehicle is located; the determination unit is used to determine the first vehicle distance shortening limit based on the first speed, information about the first city, and the mapping relationship.

[0044] In combination with the second aspect, in some implementations of the second aspect, the determination unit is further used to: determine a plurality of vehicle distance shortening limit values ​​according to the first speed and the mapping relationship, the plurality of vehicle distance shortening limit values ​​including the first vehicle distance shortening limit value corresponding to the first time period.

[0045] In combination with the second aspect, in certain implementations of the second aspect, the device also includes: a sending unit, used to send data to a cloud server indicating the initial speed of the vehicle during braking, the initial vehicle distance between the vehicle and the vehicle following the vehicle, the reaction time of the vehicle's following vehicle, and the speed characteristics of the vehicle's following vehicle.

[0046] In combination with the second aspect, in some implementations of the second aspect, the device further includes: a receiving unit, configured to receive the updated mapping relationship sent by the cloud server.

[0047] In combination with the second aspect, in certain implementations of the second aspect, the second braking deceleration is less than an average value of the braking deceleration of the vehicle in the first time period.

[0048] In combination with the second aspect, in certain implementations of the second aspect, the control unit is used to: when the automatic emergency braking AEB function is triggered according to the information of the obstacle, control the vehicle to decelerate by adopting the first braking strategy.

[0049] In a third aspect, a vehicle control device is provided, which includes a processing unit and a storage unit, wherein the storage unit is used to store instructions, and the processing unit executes the instructions stored in the storage unit to enable the device to perform any possible longitudinal control method in the first aspect.

[0050] In a fourth aspect, the present application provides a vehicle, comprising any possible vehicle control device in the second aspect or the third aspect.

[0051] In a fifth aspect, the present application provides a computer program product, comprising: a computer program code, when the computer program code is run on a computer, the computer executes any possible method of the first aspect above.

[0052] It should be noted that the above-mentioned computer program code can be stored in whole or in part on the first storage medium, wherein the first storage medium can be packaged together with the processor or separately packaged with the processor, and the embodiments of the present application do not specifically limit this.

[0053] In a sixth aspect, the present application provides a computer-readable medium storing a program code, and when the computer program code is executed on a computer, the computer executes any possible method in the first aspect.

[0054] In a seventh aspect, the present application provides a chip, comprising a circuit, wherein the circuit is used to execute any possible method in the first aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a functional block diagram of a vehicle provided in an embodiment of the present application.

[0056] Figure 2 It is a schematic diagram of an application scenario provided by an embodiment of the present application.

[0057] Figure 3It is a schematic diagram of the initial vehicle distance and the reaction time of the driver of the following vehicle provided in an embodiment of the present application.

[0058] Figure 4 It is a curve of the speed change of vehicle 1 and vehicle 2 over time provided in the embodiment of the present application.

[0059] Figure 5 It is a schematic flow chart of the vehicle control method provided in an embodiment of the present application.

[0060] Figure 6 It is another schematic flow chart of the vehicle control method provided in an embodiment of the present application.

[0061] Figure 7 This is the process of obtaining the vehicle distance shortening limit by statistics provided in the embodiment of the present application.

[0062] Figure 8 It is a schematic block diagram of a vehicle control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. Among them, in the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of associated objects, indicating that three relationships can exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. "At least one" means one or more. For example, "at least one of A and B" is similar to "A and / or B", describing the association relationship of associated objects, indicating that three relationships can exist, for example, at least one of A and B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0064] In the embodiments of the present application, prefixes such as "first" and "second" are used only to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects. The use of prefixes such as ordinal numbers to distinguish description objects in the embodiments of the present application does not constitute a limitation on the described objects. For the statement of the described objects, please refer to the description in the context of the claims or embodiments, and no unnecessary limitation should be constituted due to the use of such prefixes. In addition, in the description of the present embodiment, unless otherwise specified, the meaning of "multiple" is two or more.

[0065] Figure 1It is a functional block diagram of a vehicle 100 provided in an embodiment of the present application. The vehicle 100 may include a perception system 110 and a computing platform 120, wherein the perception system 110 may include one or more sensors for sensing information about the environment around the vehicle 100. For example, the perception system 110 may include a positioning system, and the positioning system may be a global positioning system (GPS), or a Beidou system or other positioning systems. For another example, the perception system 110 may include one or more of an inertial measurement unit (IMU), a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera device.

[0066] Some or all functions of the vehicle 100 may be controlled by the computing platform 120. The computing platform 120 may include one or more processors, such as processors 121 to 12n (n is a positive integer). The processor is a circuit with signal processing capability. In one implementation, the processor may be a circuit with instruction reading and execution capability, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor may implement certain functions through the logical relationship of a hardware circuit, and the logical relationship of the hardware circuit is fixed or reconfigurable, such as a hardware circuit implemented by a processor as an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as a field programmable gate array (FPGA). In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, the processor may also be a hardware circuit designed for artificial intelligence, which may be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc. In addition, the computing platform 120 may also include a memory, the memory is used to store instructions, and some or all of the processors 121 to 12n may call instructions in the memory to implement corresponding functions.

[0067] Figure 2 A schematic diagram showing an application scenario provided by an embodiment of the present application is shown.

[0068] like Figure 2 As shown in (a), at T 1 At time 1, vehicle 1 detects a pedestrian in front and triggers the AEB function. At this time, the speed of vehicle 1 is v 0 , the speed of vehicle 2 behind vehicle 1 is v 0 After the AEB function is triggered, vehicle 1 starts to decelerate and the brake lights of vehicle 1 are turned on. The initial distance between vehicle 2 and vehicle 1 is d 0 .

[0069] like Figure 2 As shown in (b), at T 2 At time d, vehicle 2 is behind vehicle 1. When the driver of vehicle 2 sees that the brake lights of vehicle 1 are on, he starts to brake vehicle 2. The reaction time d of the driver of vehicle 2 is t =T 2 -T 1 In T 1 The speed of vehicle 1 at this moment is v 1 .

[0070] like Figure 2 As shown in (c), at T 3 At time t, the speed of vehicle 1 changes from v 0 Reduce to v 2 And the speed of vehicle 2 changes from v 0 Reduce to v 3 At this time, vehicle 2 rear-ends vehicle 1.

[0071] The above vehicle 1 can also be referred to as the front vehicle, and the vehicle 2 can also be referred to as the rear vehicle.

[0072] above Figure 2 As shown in the figure, during the process in which vehicle 2 rear-ends vehicle 1 due to the braking of vehicle 1, the initial distance d between vehicle 1 and vehicle 2 0 and the reaction time d of the driver of vehicle 2 t It can be understood as a deterministic boundary. For the deterministic boundary, there may be a braking strategy of the vehicle 1 that makes the risk of front and rear collision of the vehicle 1 moderate. In the embodiment of the present application, the braking strategy is determined by the vehicle 1, so that the safety risk of the vehicle 1 can be reduced.

[0073] For the initial vehicle distance d 0 , which is related to the speed between vehicle 1 and vehicle 2, the driver's habits, personality, cultural background, region and other factors. Individual differences increase, and from a macro social perspective, the overall distribution law is determined. For the reaction time d t , which is related to the distance between vehicles 1 and 2, the attention, caution, age and physical condition of the driver of vehicle 2, etc., and has large individual differences. From a macro social perspective, it also obeys a certain distribution law. The degree of braking of vehicle 1 can depend on the braking strategy of the autonomous driving system. The severity of the rear-end collision between vehicles 1 and 2 is related to the speed difference between vehicles 2 and 1 at the time of collision (v 3 -v 2 ) related.

[0074] For example, Figure 3 The initial vehicle distance d provided by the embodiment of the present application is shown 0 and the reaction time of the following vehicle dt It can be seen that the initial vehicle distance d 0 and reaction time d t In line with the normal distribution law, the initial vehicle distance d 0 The horizontal axis is the reaction time d t With as the vertical axis, a probability heat map can be drawn.

[0075] Based on the magnitude of the probability of occurrence, the first risk area and the second risk area can be defined as the main action areas of the braking strategy of the vehicle 1, and based on the relationship between the collision severity and the collision speed in SAE J2980, it can be defined that the collision speed of the first risk area is less than or equal to the first preset speed and the collision speed of the second risk area is less than or equal to the second preset speed. For example, the first preset speed can be 25 kph, and the second preset speed can be 50 kph.

[0076] For example, if the initial distance between vehicle 1 and vehicle 2 is 30 m when braking begins, and the driver of vehicle 2 has a reaction time of 1 s (e.g. Figure 3 The braking strategy should ensure that when the distance between vehicle 1 and vehicle 2 is shortened to 0, the relative speed between vehicle 1 and vehicle 2 is less than or equal to 25 kph.

[0077] For example, Figure 4 The speed variation curves of vehicle 1 and vehicle 2 provided in the embodiment of the present application are shown. Among them, curve 1 can be the speed variation curve of vehicle 1 over time, or it can also be called the braking strategy output curve of vehicle 1; curve 2 can be the speed variation curve of vehicle 2 over time during braking. It can be seen that the area of ​​the shaded part can be the shortening value of the vehicle distance between vehicle 1 and vehicle 2. At the 3rd second from the start of braking of vehicle 1, a rear-end collision occurred between vehicle 1 and vehicle 2. When the rear-end collision occurred, the speed of vehicle 1 was 5kph, and the speed of vehicle 2 was 30kph. The braking strategy of vehicle 1 can make the relative speed between vehicle 1 and vehicle 2 less than or equal to 25kph when vehicle 1 and vehicle 2 rear-end each other, thereby meeting the safety risk requirements of vehicle 1.

[0078] Figure 5 A schematic flow chart of a vehicle control method 500 provided in an embodiment of the present application is shown. The method 500 can be executed by the vehicle 1 and the cloud server. The method 500 includes:

[0079] S510, when there is a following vehicle behind the vehicle 1, the vehicle 1 sends the following distance of the following vehicle to the cloud server.

[0080] For example, when a stable following vehicle appears behind vehicle 1, vehicle 1 can trigger a data feedback, and the cloud server can store the following vehicle distance transmitted back by vehicle 1.

[0081] Taking the following vehicle as the above-mentioned vehicle 2 as an example, the above stable following vehicle can be understood as the distance between vehicle 2 and vehicle 1 is less than or equal to the preset distance and vehicle 2 travels in the same lane at a speed equivalent to vehicle 1 for greater than or equal to the preset time.

[0082] The above vehicle 2 traveling at a speed equivalent to that of vehicle 1 can be understood as the difference between the speeds of vehicle 2 and vehicle 1 being less than or equal to a preset speed difference. For example, the preset speed difference is 3 kph.

[0083] Exemplarily, the preset distance may be 50 m.

[0084] Exemplarily, the preset duration may be 5 seconds.

[0085] In the embodiment of the present application, the vehicle 1 may be equipped with a rearward sensing system, which may include one or more of a rearward camera, a rearward laser radar, and a rearward millimeter-wave radar. The vehicle 1 may determine the following distance of the following vehicle based on the data collected by the rearward sensing system and send it to the cloud server.

[0086] S520: If there is a following vehicle behind the vehicle 1 when the vehicle 1 brakes, the vehicle 1 may record the reaction time of the following vehicle and the speed characteristics of the following vehicle during the braking process of the vehicle 1.

[0087] The above description is based on the example that vehicle 1 records the reaction time of the following vehicle and the braking deceleration of the following vehicle during the braking process of vehicle 1, and the embodiments of the present application are not limited to this. For example, vehicle 1 can record the reaction time of the following vehicle during the braking process of vehicle 1 and the distance change information between vehicle 1 and the following vehicle.

[0088] For example, if there is a stable following vehicle behind vehicle 1 when vehicle 1 brakes, vehicle 1 can record the reaction time of the following vehicle and the braking deceleration change information of the following vehicle during the braking process of vehicle 1. After vehicle 1 brakes, vehicle 1 can trigger a data return, and the cloud server collects and stores the reaction time and braking deceleration change information of the following vehicle sent back by vehicle 1.

[0089] The above is an example of vehicle 1 sending data collected by the rearward sensing system to the cloud server, and the embodiments of the present application are not limited thereto. For example, the cloud server can receive data sent by different vehicles, thereby obtaining a large amount of sample data, which can be used to count the vehicle distance shortening limit values ​​under different working conditions.

[0090] S530, the cloud server calculates the vehicle distance shortening limit under different working conditions based on the information sent by vehicle 1.

[0091] For example, taking the initial speed of the vehicle as 80-120 kph, the cloud server can collect information on the following distance between different vehicles and their following vehicles, the reaction time of the following vehicles, and the braking deceleration of the following vehicles. Among them, these following vehicles include vehicles that have not rear-ended the vehicle during the braking process of the vehicle, and vehicles whose relative speed with the vehicle is less than or equal to 25 kph when rear-ending the vehicle. The cloud server can collect statistics on the changes in the shortening of the distance between the vehicle and the following vehicles, so as to obtain the shortening limit of the distance in different time periods from the start of braking of the vehicle.

[0092] For example, the cloud server can count the distribution of the reaction time of the following vehicle, the distribution of the initial vehicle distance, and the distribution of the vehicle distance reduction limit. For example, when the front vehicle brakes at a speed of 80-120 kph, Figure 3 The distribution of the distance shortening values ​​between the leading vehicle and the following vehicle within 1 second from the time when the leading vehicle starts braking in the sample data in the first risk zone and the second risk zone is statistically analyzed, so that x_90 can be defined as a limit value (meaning: P(x>=x_90)=90%; x is the distance shortening; x_90 is the 90% threshold limit value, that is, there is a relationship P(x>=x_90)=90%, which means that if x_90 is used as the threshold, it can be ensured that at least 90% of the following vehicles will not rear-end the leading vehicle). This limit value can be used as the distance shortening limit value within 1 second when the leading vehicle speed is 80-120 kph. For another example, the cloud server can calculate (for example, take the average value) the distance shortening values ​​between the leading vehicle and the following vehicle within 1 second from the time when the leading vehicle starts braking in the sample data in the first risk zone and the second risk zone to obtain the distance shortening limit value within 1 second when the leading vehicle speed is 80-120 kph.

[0093] For example, the cloud server can Figure 3 The distribution of the distance shortening values ​​within 2 seconds from the start of braking of the front vehicle in the sample data in the first risk area and the second risk area is statistically analyzed, so that x_90 can be defined as a limit value, which can be used as the distance shortening limit value within 2 seconds when the front vehicle speed is 80-120 kph. For another example, the cloud server can calculate (for example, take the average value) the distance shortening values ​​between the front vehicle and the rear vehicle within 2 seconds from the start of braking of the front vehicle in the sample data in the first risk area and the second risk area to obtain the distance shortening limit value within 2 seconds when the front vehicle speed is 80-120 kph.

[0094] For example, the cloud server can collect statistics on the distance change information between the following vehicles, the reaction delay of the following vehicles, and the statistical distribution of the braking deceleration of the following vehicles when the vehicle speed is within the range of 80 kph to 120 kph and the following vehicle is a passenger vehicle (e.g., a sedan or SUV), and then calculate the distance reduction limit value in Table 1. The distance reduction limit value can avoid 99% of the rear vehicles from rear-ending the front vehicle, and for the other 1% of the vehicles that rear-end the front vehicle, it can also ensure that the relative speed between the front vehicle and the rear vehicle is less than 25 kph when the rear-end collision occurs.

[0095] Assuming that the initial speed of vehicle 1 is 80-120 kph, Table 1 shows the vehicle distance reduction limit between the vehicle and the following vehicle in different time periods after the vehicle starts braking, calculated by the cloud server.

[0096] Table 1

[0097]

[0098] Taking the initial speed of vehicle 1 as 60-80 kph as an example, Table 2 shows the vehicle distance reduction limit between the vehicle and the following vehicle in different time periods after the vehicle starts braking, calculated by the cloud server.

[0099] Table 2

[0100]

[0101] Taking the initial speed of vehicle 1 as less than 60 kph as an example, Table 3 shows the vehicle distance reduction limit between the vehicle and the following vehicle in different time periods after the vehicle starts braking, calculated by the cloud server.

[0102] Table 3

[0103]

[0104] In the above Tables 1 to 3, each interval of 1 second corresponds to a vehicle distance shortening limit value, and the embodiments of the present application are not limited thereto. For example, each interval of 0.5 second may correspond to a vehicle distance shortening limit value.

[0105] Tables 1 to 3 above are described by taking five vehicle distance shortening limit values ​​as an example, but the embodiments of the present application are not limited thereto. For example, the vehicle distance shortening limit value may also be one, such as including the vehicle distance shortening limit value within 3 seconds from the start of vehicle braking.

[0106] In one embodiment, for different types of following vehicles, the cloud server can obtain statistical information on the shortening limit of the get-off distance at different time lengths.

[0107] Exemplarily, Table 4 shows different types of following vehicles calculated by the cloud server, and the vehicle distance reduction limit between the vehicle and the following vehicle in different time periods after the vehicle starts braking.

[0108] Table 4

[0109]

[0110] The above passenger cars may include sedans and SUVs, etc., and large vehicles may include trailers, vans, trucks, etc.

[0111] In one embodiment, the cloud server can also calculate the vehicle distance reduction limit between the vehicle and the following vehicle in different cities in different time periods from the start of braking of the vehicle.

[0112] For example, Table 5 shows the vehicle distance reduction limit between the vehicle and the following vehicle in different time periods after the vehicle starts braking in different cities, calculated by the cloud server.

[0113] Table 5

[0114]

[0115] In one embodiment, the cloud server can also calculate the vehicle distance reduction limit between the vehicle and the following vehicle in different time periods from the start of braking of the vehicle in different seasons.

[0116] The statistical results of the above different dimensions can also be combined with each other. For example, the cloud server can also count the vehicle distance reduction limit between the vehicle and the following vehicle in different time periods from the start of braking of the vehicle under different vehicle types, cities, and seasons.

[0117] S540, the cloud server sends information on the vehicle distance shortening limit under different working conditions to vehicle 1.

[0118] In the above embodiment, the cloud server is used to count the speed reduction limit values ​​under different initial vehicle speeds. The embodiment of the present application is not limited to this. For example, the cloud server can also count the distance reduction limit values ​​under different initial vehicle speeds, initial vehicle distances, and reaction times. For example, when the speed of the preceding vehicle is 80-120 kph, the cloud server can count the vehicle speed reduction limit values ​​under different initial vehicle speeds, initial vehicle distances, and reaction times. Figure 3 In the sample data with an initial distance of 29m and a reaction time of 1s for the rear car, the distribution of the distance reduction value between the front car and the rear car within 1s from the start of braking of the front car is statistically analyzed, so that x_90 can be defined as a limit value, which can be used as the distance reduction limit value within 1s under the initial conditions that the front car speed is 80-120kph, the initial distance is 29m and the reaction time of the rear car is 1s. For another example, the cloud server can Figure 3In the sample data with an initial distance of 29m and a reaction time of 1s for the rear vehicle, the distribution of the distance reduction value between the front vehicle and the rear vehicle within 2s from the start of braking of the front vehicle is statistically analyzed, so that x_90 can be defined as a limit value, which can be used as the distance reduction limit value within 2s under the initial condition that the front vehicle speed is 80-120kph, the initial distance is 29m, and the reaction time of the rear vehicle is 1s. In this way, the speed reduction limit values ​​in different time periods constitute the corresponding relationship between different time lengths and the distance reduction limit values ​​when the initial distance is 29m and the reaction time of the rear vehicle is 1s1.

[0119] Exemplarily, Table 6 shows information on the limit of shortening of the vehicle distance over time under different working conditions sent by the cloud server to the vehicle 1.

[0120] Table 6

[0121] Working conditions Limit value of vehicle distance reduction over time The initial vehicle distance is 29m and the reaction time is 1s Correspondence between different time lengths from braking and the distance reduction limit 1 The initial vehicle distance is 30m and the reaction time is 1s Correspondence between different time lengths from braking and the distance reduction limit 2 The initial vehicle distance is 31m and the reaction time is 1s Correspondence between different time lengths from braking and the distance reduction limit 3 The initial vehicle distance is 32m and the reaction time is 1s Correspondence between different time lengths from braking and the distance reduction limit 4 … … The initial vehicle distance is 29m and the reaction time is 1.1s Correspondence between different time lengths from braking and the limit value of vehicle distance reduction 5 The initial vehicle distance is 30m and the reaction time is 1.2s Correspondence between different time lengths from braking and the limit value of vehicle distance reduction 6 The initial vehicle distance is 31m and the reaction time is 1.3s Correspondence between different time lengths from braking and the limit value of vehicle distance reduction 7 The initial vehicle distance is 32m and the reaction time is 1.4s Correspondence between different time lengths from braking and the limit value of vehicle distance reduction 8 … …

[0122] Exemplarily, the above correspondence 2 between different time lengths from the start of braking and the vehicle distance shortening limit value may be as shown in the above Table 1.

[0123] S550: When the active braking is triggered, the vehicle 1 is controlled to brake using a first braking strategy.

[0124] Exemplarily, vehicle 1 may determine a first braking strategy according to different confidence levels of a target obstacle (eg, a stationary obstacle in front of vehicle 1, or a pedestrian crossing in front of vehicle 1, or a red light at an intersection in front of vehicle 1).

[0125] S560: When the distance shortening value between the vehicle 1 and the following vehicle is greater than or equal to the distance shortening limit value, the vehicle 1 is controlled to brake using the second braking strategy, or the prompting device is controlled to prompt the user to reduce the braking deceleration.

[0126] Taking vehicle 1 in manual driving state as an example, when the distance shortening value between vehicle 1 and the vehicle it follows is greater than or equal to the distance shortening limit value, the sound emitting device (for example, a speaker) can be controlled to emit a prompt sound "There is a risk of rear-end collision with the vehicle behind, it is recommended to slightly reduce the braking deceleration."

[0127] Take vehicle 1 in the automatic driving state as an example, assuming that the current time is t, if the distance reduction value between vehicle 1 and the following vehicle during the time period tx to t is greater than or equal to the distance reduction limit threshold corresponding to xs, vehicle 1 can limit the braking deceleration of vehicle 1 during the time period t to t+1. For example, vehicle 1 can control the braking deceleration of vehicle 1 during the time period t to t+1 to be lower than the average deceleration of vehicle 1 during the time period tx to t.

[0128] S570, the cloud server updates the information of the vehicle distance shortening limit under different working conditions through over the air (OTA) technology.

[0129] For example, the cloud server may calculate information about the vehicle distance reduction limit under different working conditions at a fixed frequency (e.g., once a week). When the vehicle distance reduction limit calculated under the same initial following distance and reaction time changes, the new vehicle distance reduction limit may be sent to the vehicle 1 through OTA technology.

[0130] Figure 6 A schematic flow chart of a vehicle control method 600 provided in an embodiment of the present application is shown. The method 600 may be executed by the vehicle 100, or the computing platform 120, or the system consisting of the perception system 110 and the computing platform 120, or the system-on-a-chip (SoC) in the computing platform 120, or the processor, chip or circuit in the computing platform 120. The method 600 includes:

[0131] S610, obtaining information about obstacles in front of the vehicle.

[0132] Optionally, the vehicle is in an automatic driving state, or the vehicle is configured with an active braking function (e.g., an AEB function).

[0133] Exemplarily, the vehicle is in a state where the ACC function, the ICA function or the NCA function is turned on.

[0134] S620: According to the information about the obstacle, control the vehicle to decelerate by adopting a first braking strategy.

[0135] Optionally, after the vehicle triggers the active braking function according to the information of the obstacle, it can determine a first braking strategy according to the information of the obstacle and use the first braking strategy to control the vehicle to decelerate.

[0136] For example, if a vehicle detects a pedestrian crossing the road while driving and the vehicle determines that it will collide with the pedestrian at the current speed, active braking will be triggered.

[0137] For another example, when the vehicle is in manual driving and it is detected that the vehicle will collide with a stationary obstacle in front (e.g., a stationary vehicle) when traveling at the current speed, active braking will be triggered.

[0138] For another example, before the vehicle reaches a traffic light intersection, it is determined that the indicator light is red when the vehicle reaches the intersection at the current speed. The vehicle can be decelerated by the first braking strategy, thereby controlling the vehicle to stop before the intersection.

[0139] S630, when the distance shortening value between the vehicle and the following vehicle behind the vehicle within the first time period is greater than or equal to a first distance shortening limit value, the vehicle is controlled to decelerate using a second braking strategy, and the first distance shortening limit value is obtained by statistics of sample data, and the sample data includes data for indicating driving parameters of the sample vehicle and driving parameters of the following vehicle of the sample vehicle.

[0140] Optionally, the sample data includes raw data collected by the sample vehicle's rearward perception system (e.g., a rearward camera, a rearward millimeter-wave radar, a rearward lidar, etc.), or the sample data includes driving parameters of the sample vehicle determined by the sample vehicle and driving parameters of the vehicle following the sample vehicle.

[0141] The above first vehicle-to-vehicle distance shortening limit value may be preset in the vehicle when the vehicle leaves the factory, or may be sent to the vehicle after being collected by the cloud server through sample data.

[0142] Optionally, the method 600 further includes: the vehicle receives information of the first vehicle distance shortening limit sent by a cloud server.

[0143] Optionally, the vehicle receives the information of the first vehicle-to-vehicle distance shortening limit sent by the cloud server, including: the vehicle sends request information to the cloud server according to the navigation information, and the request information is used to request the corresponding vehicle-to-vehicle distance shortening limit. For example, when the navigation information indicates that the vehicle is traveling on a highway and the minimum speed of the highway is 80 kph and the maximum speed is 120 kph, the vehicle can send a request information to the cloud server, and the request information is used to request the vehicle-to-vehicle distance shortening limit when the vehicle is at a high speed (80-120 kph); the vehicle can receive the vehicle-to-vehicle distance shortening limit when the vehicle is traveling at a high speed from the cloud server.

[0144] In some possible implementations, the sample data may be raw data collected by a sensor (e.g., a camera, a millimeter-wave radar, a lidar, etc.) located behind the sample vehicle, or it may be driving parameters of the sample vehicle and driving parameters of the following vehicle determined by the sample vehicle based on raw data collected by a sensor located behind the sample vehicle.

[0145] Optionally, the first braking strategy indicates that the braking deceleration of the vehicle in the second time period is a first braking deceleration, the second braking strategy indicates that the braking deceleration of the vehicle in the second time period is a second braking deceleration, the first braking deceleration is greater than the second braking deceleration, and the second time period is located after the first time period.

[0146] Optionally, the type of obstacle may also be considered during the braking process of the vehicle. For example, if the type of obstacle is a light obstacle (e.g., a stationary cardboard box or a branch, etc.), then when the distance reduction value between the vehicle and the following vehicle behind the vehicle is greater than or equal to the first distance reduction limit value during the first time period, the vehicle is controlled to decelerate using the second braking strategy.

[0147] For another example, if the obstacle is a heavy obstacle (e.g., pedestrians crossing the road, pedestrians riding bicycles or electric vehicles, stationary vehicles, moving vehicles, etc.), then when the distance reduction value between the vehicle and the following vehicle behind the vehicle in the first time period is greater than or equal to the first distance reduction limit, when adjusting the braking strategy to the second braking strategy, it can also be considered whether the second braking strategy can avoid the collision between the vehicle and the obstacle. If the second braking strategy can satisfy the rear-end collision between the following vehicle and the vehicle, and can also avoid the collision between the vehicle and the obstacle in front, the vehicle can be controlled to brake according to the second braking strategy.

[0148] If the vehicle is braked according to the second braking strategy, which triggers a collision between the vehicle and the obstacle, the vehicle may be decelerated according to the third braking strategy, and the third braking strategy indicates that the braking deceleration in the second time period is the third braking deceleration. The third braking strategy may be an extreme braking strategy for avoiding a collision between the vehicle and the obstacle, or the third braking deceleration may be an extreme deceleration for avoiding a collision between the vehicle and the obstacle.

[0149] In the embodiment of the present application, the vehicle will determine the relationship between the vehicle distance shortening value within a period of time and the first vehicle distance shortening limit value, and will not limit the instantaneous braking capability, which will result in less instantaneous constraints on the active braking function.

[0150] Optionally, the sample data includes data indicating an initial speed of the sample vehicle during braking, an initial vehicle distance between the sample vehicle and a vehicle following the sample vehicle, a reaction time of a vehicle following the sample vehicle, and speed characteristics of a vehicle following the sample vehicle.

[0151] Exemplarily, the first vehicle distance shortening limit value may be obtained by collecting statistics of sample data from a cloud server. Figure 7The process of obtaining the vehicle distance shortening limit value by statistics provided by the embodiment of the present application is shown. The vehicle distance shortening limit value can be obtained by combining the initial speed of the sample vehicle, the reaction time of the following vehicle of the sample vehicle, and the speed characteristics of the following vehicle for statistics.

[0152] The process of obtaining the vehicle distance shortening limit value by the cloud server based on the initial speed of the vehicle, the reaction time of the following vehicle of the sample vehicle, and the speed characteristic statistics of the following vehicle can be referred to the description in the above embodiment, which will not be repeated here.

[0153] Optionally, the method 600 further includes: when the vehicle adopts the first braking strategy to decelerate, obtaining a first speed of the vehicle; determining the first vehicle distance shortening limit value according to the first speed and a mapping relationship, wherein the mapping relationship includes a correspondence between the vehicle speed and the vehicle distance shortening limit value.

[0154] Exemplarily, the mapping relationship includes a correspondence between different vehicle speed ranges and vehicle headway reduction limits. For example, different vehicle speed ranges include a low speed range (0, 60 kph), a medium speed range [60 kph, 80 kph), and a high speed range [80 kph, 120 kph]. For example, when the vehicle brakes according to information about an obstacle, the initial vehicle speed is 100 kph, then the vehicle can determine the vehicle headway reduction limit corresponding to the high speed range according to the mapping relationship.

[0155] Exemplarily, Tables 1 to 3 above respectively show the corresponding vehicle distance shortening limits in high-speed, medium-speed and low-speed scenarios.

[0156] Optionally, the mapping relationship includes a correspondence between vehicle speed, vehicle type and vehicle distance shortening limit, and the method further includes: obtaining the type of the following vehicle; wherein, determining the first vehicle distance shortening limit based on the first speed and the mapping relationship includes: determining the first vehicle distance shortening limit based on the first speed, the type of the following vehicle and the mapping relationship.

[0157] Exemplarily, the type of vehicle may include a passenger car, a large vehicle, and the like.

[0158] Exemplarily, Table 4 shows the vehicle distance shortening limits corresponding to passenger cars and large vehicles.

[0159] Optionally, the mapping relationship includes a correspondence between vehicle speed, season and vehicle distance shortening limit, and the method further includes: obtaining information about the season in which the vehicle is located; wherein, determining the first vehicle distance shortening limit based on the first speed and the mapping relationship includes: determining the first vehicle distance shortening limit based on the first speed, information about the season and the mapping relationship.

[0160] Due to the different tire pressure and grip of vehicles in different seasons, the braking performance may be different. By combining seasonal information in the statistical process, the accuracy of the distance reduction limit can be further improved. In this way, the vehicle can combine seasonal information to obtain the appropriate distance reduction limit during the actual braking process, which helps to improve the accuracy of the vehicle's longitudinal control.

[0161] Optionally, the mapping relationship includes a correspondence between vehicle speed, city and vehicle distance shortening limit, and the method further includes: obtaining information of a first city in which the vehicle is located; wherein, determining the first vehicle distance shortening limit based on the first speed and the mapping relationship includes: determining the first vehicle distance shortening limit based on the first speed, information of the first city and the mapping relationship.

[0162] Exemplarily, Table 5 shows the vehicle distance shortening limits corresponding to different cities (city 1 and city 2).

[0163] Optionally, determining the first vehicle distance shortening limit value according to the first speed and the mapping relationship includes: determining a plurality of vehicle distance shortening limit values ​​according to the first speed and the mapping relationship, the plurality of vehicle distance shortening limit values ​​including the first vehicle distance shortening limit value corresponding to the first time period.

[0164] For example, Tables 1 to 5 above respectively show the vehicle distance shortening limit of 1 second, the vehicle distance shortening limit within 2 seconds, the vehicle distance shortening limit within 3 seconds, etc. Multiple judgments can be made based on the vehicle distance shortening limit in different time periods, which helps to improve the accuracy of vehicle longitudinal control.

[0165] Optionally, the method 600 also includes: sending data indicating the initial speed of the vehicle during braking, the initial vehicle distance between the vehicle and the vehicle following it, the reaction time of the vehicle's following vehicle, and the speed characteristics of the vehicle's following vehicle to a cloud server.

[0166] For example, the vehicle can send raw data collected by the vehicle's rearward perception system to the cloud server; or, when the vehicle determines the initial speed of the vehicle during braking, the initial vehicle distance between the vehicle and the vehicle following it, the reaction time of the vehicle's following vehicle, and the speed characteristics of the vehicle's following vehicle based on the raw data collected by the rearward perception system, the vehicle can send this information to the cloud server.

[0167] Optionally, the method 600 further includes: receiving the updated mapping relationship sent by the cloud server.

[0168] Optionally, the cloud server may periodically update the mapping relationship to ensure the accuracy (or "freshness") of the vehicle distance reduction limit. Optionally, the second braking deceleration is less than an average value of the braking deceleration of the vehicle during the first time period.

[0169] For example, the vehicle is the above-mentioned vehicle 1. Assuming that the current time is t, if the distance reduction limit value between the vehicle 1 and the following vehicle in the time period tx to t is greater than or equal to the distance reduction limit threshold corresponding to xs, the vehicle 1 can limit the braking deceleration of the vehicle 1 in the time period t to t+1. For example, the vehicle 1 can control the braking deceleration of the vehicle 1 in the time period t to t+1 to be lower than the average deceleration of the vehicle 1 in the time period tx to t.

[0170] Optionally, the vehicle is controlled to decelerate using a first braking strategy based on the information of the obstacle, including: when an automatic emergency braking (AEB) function is triggered based on the information of the obstacle, the vehicle is controlled to decelerate using the first braking strategy.

[0171] Figure 8 FIG. 8 is a schematic block diagram of a vehicle control device 800 provided in an embodiment of the present application. Figure 8 As shown, the device 800 includes: an acquisition unit 810, which is used to acquire information about an obstacle in front of the vehicle; a control unit 820, which is used to control the vehicle to decelerate by adopting a first braking strategy according to the information about the obstacle; the control unit 820 is also used to control the vehicle to decelerate by adopting a second braking strategy when a distance reduction value between the vehicle and a following vehicle behind the vehicle in a first time period is greater than or equal to a first distance reduction limit, the first distance reduction limit being obtained by statistics of sample data, the sample data including data indicating driving parameters of the sample vehicle and driving parameters of the following vehicle of the sample vehicle; wherein the first braking strategy indicates that the braking deceleration of the vehicle in the second time period is a first braking deceleration, the second braking strategy indicates that the braking deceleration of the vehicle in the second time period is a second braking deceleration, the first braking deceleration is greater than the second braking deceleration, and the second time period is located after the first time period.

[0172] Optionally, the sample data includes data indicating an initial speed of the sample vehicle during braking, an initial vehicle distance between the sample vehicle and a vehicle following the sample vehicle, a reaction time of a vehicle following the sample vehicle, and speed characteristics of a vehicle following the sample vehicle.

[0173] Optionally, the device 800 also includes a determination unit, wherein the acquisition unit 810 is further used to acquire the first speed of the vehicle when the vehicle adopts the first braking strategy to decelerate; the determination unit is used to determine the first vehicle distance shortening limit based on the first speed and a mapping relationship, and the mapping relationship includes a correspondence between the vehicle speed and the vehicle distance shortening limit.

[0174] Optionally, the mapping relationship includes a correspondence between vehicle speed, vehicle type and vehicle distance shortening limit, and the acquisition unit 810 is further used to acquire the type of the following vehicle; the determination unit is used to determine the first vehicle distance shortening limit according to the first speed, the type of the following vehicle and the mapping relationship.

[0175] Optionally, the mapping relationship includes a correspondence between vehicle speed, season and vehicle distance shortening limit, and the acquisition unit 810 is further used to obtain information about the season in which the vehicle is located; the determination unit is used to determine the first vehicle distance shortening limit based on the first speed, the season information and the mapping relationship.

[0176] Optionally, the mapping relationship includes a correspondence between vehicle speed, city and vehicle distance shortening limit, and the acquisition unit 810 is used to obtain information of a first city in which the vehicle is located; the determination unit is used to determine the first vehicle distance shortening limit based on the first speed, information of the first city and the mapping relationship.

[0177] Optionally, the determination unit is further configured to: determine a plurality of vehicle distance shortening limit values ​​according to the first speed and the mapping relationship, wherein the plurality of vehicle distance shortening limit values ​​include the first vehicle distance shortening limit value corresponding to the first time period.

[0178] Optionally, the device 800 also includes: a sending unit, used to send data indicating the initial speed of the vehicle during braking, the initial vehicle distance between the vehicle and the vehicle following the vehicle, the reaction time of the vehicle's following vehicle, and the speed characteristics of the vehicle's following vehicle to the cloud server.

[0179] Optionally, the device 800 further includes: a receiving unit, configured to receive the updated mapping relationship sent by the cloud server.

[0180] Optionally, the second braking deceleration is less than an average value of the braking deceleration of the vehicle in the first time period.

[0181] Optionally, the control unit 820 is used to: when an automatic emergency braking AEB function is triggered according to information about the obstacle, control the vehicle to decelerate by adopting the first braking strategy.

[0182] For example, the acquisition unit 810 may be Figure 1The computing platform in the computing platform or the processing circuit, processor or controller in the computing platform. Taking the acquisition unit 810 as the processor 121 in the computing platform as an example, the processor 121 can acquire the information of the obstacle in front of the vehicle.

[0183] For another example, the control unit 820 may be Figure 1 The computing platform in the computing platform or the processing circuit, processor or controller in the computing platform. Taking the control unit 820 as the processor 122 in the computing platform as an example, the processor 122 can control the vehicle to brake according to the first braking strategy based on the information of the obstacle obtained by the processor 121. The processor 122 can also control the vehicle to switch from braking according to the first braking strategy to braking according to the second braking strategy when it is determined that the distance reduction value between the following vehicle and the vehicle in the first time period is greater than or equal to the distance reduction limit.

[0184] The functions implemented by the above acquisition unit 810 and the functions implemented by the control unit 820 can be implemented by different processors, or can also be implemented by the same processor, which is not limited in the embodiment of the present application.

[0185] It should be understood that the division of the units in the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. In addition, the units in the device can be implemented in the form of a processor calling software; for example, the device includes a processor, the processor is connected to a memory, and instructions are stored in the memory. The processor calls the instructions stored in the memory to implement any of the above methods or realize the functions of the units of the device, wherein the processor is, for example, a general-purpose processor, such as a CPU or a microprocessor, and the memory is a memory in the device or a memory outside the device. Alternatively, the units in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units can be realized by designing the hardware circuits. The hardware circuit can be understood as one or more processors; for example, in one implementation, the hardware circuit is an ASIC, and the functions of some or all of the above units are realized by designing the logical relationship of the components in the circuit; for another example, in another implementation, the hardware circuit can be implemented by PLD. Taking FPGA as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured through the configuration file, so as to realize the functions of some or all of the above units. All units of the above device may be implemented entirely in the form of a processor calling software, or entirely in the form of a hardware circuit, or partially in the form of a processor calling software and the rest in the form of a hardware circuit.

[0186] Each unit in the above device can be one or more processors (or processing circuits) configured to implement the above method, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0187] In addition, all or part of the units in the above device can be integrated together, or can be implemented independently. In one implementation, these units are integrated together and implemented in the form of SoC. The SoC may include at least one processor for implementing any of the above methods or implementing the functions of each unit of the device. The type of the at least one processor may be different, for example, including CPU and FPGA, CPU and artificial intelligence processor, CPU and GPU, etc.

[0188] An embodiment of the present application also provides a device, which includes a processing unit and a storage unit, wherein the storage unit is used to store instructions, and the processing unit executes the instructions stored in the storage unit so that the device executes the method or steps executed by the above embodiment.

[0189] Alternatively, if the device is located in a vehicle, the processing unit may be Figure 1 Processors 121-12n are shown.

[0190] An embodiment of the present application also provides a vehicle, which may include the above-mentioned device 800.

[0191] The embodiment of the present application further provides a computer program product, which includes: a computer program code, and when the computer program code is executed on a computer, the computer executes the above method.

[0192] The embodiment of the present application further provides a computer-readable medium, wherein the computer-readable medium stores a program code. When the computer program code is executed on a computer, the computer executes the above method.

[0193] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or a power-on erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0194] It should be understood that in the embodiment of the present application, the memory may include a read-only memory and a random access memory, and provide instructions and data to the processor.

[0195] It should also be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0196] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0197] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0198] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0199] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0200] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0201] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0202] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered. Within the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A vehicle control method, It is characterized in that include: Obtain information about obstacles in front of the vehicle; According to the information of the obstacle, controlling the vehicle to decelerate by adopting a first braking strategy; When a distance reduction value between the vehicle and a following vehicle behind the vehicle is greater than or equal to a first distance reduction limit value within a first time period, the vehicle is controlled to decelerate using a second braking strategy, wherein the first distance reduction limit value is obtained by statistics of sample data, and the sample data includes data indicating driving parameters of the sample vehicle and driving parameters of the following vehicle of the sample vehicle; The first braking strategy indicates that the braking deceleration of the vehicle in a second time period is a first braking deceleration, the second braking strategy indicates that the braking deceleration of the vehicle in the second time period is a second braking deceleration, the first braking deceleration is greater than the second braking deceleration, and the second time period is located after the first time period.

2. The method according to claim 1, It is characterized in that The sample data includes data indicating an initial speed of the sample vehicle when braking, an initial vehicle distance between the sample vehicle and a vehicle following the sample vehicle, a reaction time of a vehicle following the sample vehicle, and a speed characteristic of a vehicle following the sample vehicle.

3. The method according to claim 1 or 2, It is characterized in that The method further comprises: When the vehicle decelerates using the first braking strategy, obtaining a first speed of the vehicle; The first vehicle distance shortening limit value is determined according to the first speed and a mapping relationship, wherein the mapping relationship includes a corresponding relationship between vehicle speeds and vehicle distance shortening limits.

4. The method according to claim 3, It is characterized in that The mapping relationship includes a correspondence between vehicle speed, vehicle type and vehicle headway shortening limit, and the method further includes: Obtaining the type of the following vehicle; The determining the first vehicle distance shortening limit value according to the first speed and the mapping relationship includes: The first vehicle distance shortening limit value is determined according to the first speed, the type of the following vehicle, and the mapping relationship.

5. The method according to claim 3 or 4, It is characterized in that The mapping relationship includes a corresponding relationship between vehicle speed, season and vehicle headway reduction limit, and the method further includes: Obtaining information about the season in which the vehicle is located; The determining the first vehicle distance shortening limit value according to the first speed and the mapping relationship includes: The first vehicle distance shortening limit value is determined according to the first speed, the season information, and the mapping relationship.

6. The method according to any one of claims 3 to 5, It is characterized in that The mapping relationship includes a corresponding relationship between vehicle speed, city, and vehicle distance shortening limit, and the method further includes: Acquiring information of a first city where the vehicle is located; The determining the first vehicle distance shortening limit value according to the first speed and the mapping relationship includes: The first vehicle distance shortening limit value is determined according to the first speed, information about the first city, and the mapping relationship.

7. The method according to any one of claims 3 to 6, It is characterized in that The determining the first vehicle distance shortening limit value according to the first speed and the mapping relationship includes: A plurality of vehicle distance shortening limit values ​​are determined according to the first speed and the mapping relationship, wherein the plurality of vehicle distance shortening limit values ​​include the first vehicle distance shortening limit value corresponding to the first time period.

8. The method according to any one of claims 1 to 7, It is characterized in that The method further comprises: Data indicating the initial speed of the vehicle during braking, the initial vehicle distance between the vehicle and the vehicle following the vehicle, the reaction time of the vehicle following the vehicle, and the speed characteristics of the vehicle following the vehicle are sent to the cloud server.

9. The method according to claim 8, It is characterized in that The method further comprises: Receive the updated mapping relationship sent by the cloud server.

10. The method according to any one of claims 1 to 9, It is characterized in that The second braking deceleration is smaller than an average braking deceleration of the vehicle in the first time period.

11. The method according to any one of claims 1 to 10, It is characterized in that The controlling the vehicle to decelerate using a first braking strategy according to the obstacle information includes: When the automatic emergency braking (AEB) function is triggered according to the information of the obstacle, the vehicle is controlled to decelerate using the first braking strategy.

12. A vehicle control device, It is characterized in that include: An acquisition unit, used to acquire information of obstacles in front of the vehicle; A control unit, configured to control the vehicle to decelerate by adopting a first braking strategy according to information about the obstacle; The control unit is further configured to control the vehicle to decelerate using a second braking strategy when a distance reduction value between the vehicle and a following vehicle behind the vehicle is greater than or equal to a first distance reduction limit value within a first time period, wherein the first distance reduction limit value is obtained by statistics of sample data, and the sample data includes data indicating driving parameters of the sample vehicle and driving parameters of a vehicle following the sample vehicle; The first braking strategy indicates that the braking deceleration of the vehicle in a second time period is a first braking deceleration, the second braking strategy indicates that the braking deceleration of the vehicle in the second time period is a second braking deceleration, the first braking deceleration is greater than the second braking deceleration, and the second time period is located after the first time period.

13. The device according to claim 12, It is characterized in that The sample data includes data indicating an initial speed of the sample vehicle when braking, an initial vehicle distance between the sample vehicle and a vehicle following the sample vehicle, a reaction time of a vehicle following the sample vehicle, and a speed characteristic of a vehicle following the sample vehicle.

14. The device according to claim 12 or 13, It is characterized in that The device further comprises a determining unit, wherein: The acquisition unit is further configured to acquire a first speed of the vehicle when the vehicle decelerates using the first braking strategy; The determining unit is used to determine the first vehicle distance shortening limit value according to the first speed and a mapping relationship, wherein the mapping relationship includes a corresponding relationship between vehicle speeds and vehicle distance shortening limit values.

15. The device according to claim 14, It is characterized in that The mapping relationship includes the corresponding relationship between the vehicle speed, the vehicle type and the vehicle distance shortening limit. The acquisition unit is further used to acquire the type of the following vehicle; The determining unit is configured to determine the first vehicle distance shortening limit value according to the first speed, the type of the following vehicle, and the mapping relationship.

16. The device according to claim 14 or 15, It is characterized in that The mapping relationship includes the corresponding relationship between vehicle speed, season and vehicle distance shortening limit, The acquisition unit is further used to acquire information about the season in which the vehicle is located; The determining unit is used to determine the first vehicle distance shortening limit value according to the first speed, the season information and the mapping relationship.

17. The device according to any one of claims 14 to 16, It is characterized in that The mapping relationship includes the corresponding relationship between vehicle speed, city and vehicle distance shortening limit, The acquiring unit is used to acquire information of a first city where the vehicle is located; The determining unit is used to determine the first vehicle distance shortening limit value according to the first speed, the information of the first city and the mapping relationship.

18. The device according to any one of claims 14 to 17, It is characterized in that The determining unit is further configured to: A plurality of vehicle distance shortening limit values ​​are determined according to the first speed and the mapping relationship, wherein the plurality of vehicle distance shortening limit values ​​include the first vehicle distance shortening limit value corresponding to the first time period.

19. The device according to any one of claims 12 to 18, It is characterized in that The device also includes: The sending unit is used to send data indicating the initial speed of the vehicle during braking, the initial vehicle distance between the vehicle and the vehicle following the vehicle, the reaction time of the vehicle following the vehicle, and the speed characteristics of the vehicle following the vehicle to the cloud server.

20. The device according to claim 19, It is characterized in that The device also includes: A receiving unit is used to receive the updated mapping relationship sent by the cloud server.

21. The device according to any one of claims 12 to 20, It is characterized in that The second braking deceleration is smaller than an average braking deceleration of the vehicle in the first time period.

22. The device according to any one of claims 12 to 21, It is characterized in that The control unit is used for: When the automatic emergency braking (AEB) function is triggered according to the information of the obstacle, the vehicle is controlled to decelerate using the first braking strategy.

23. A vehicle control device, It is characterized in that include: Memory for storing computer programs; A processor, configured to execute the computer program stored in the memory, so that the apparatus performs the method according to any one of claims 1 to 11.

24. A vehicle, It is characterized in that Comprising an apparatus as claimed in any one of claims 12 to 23.

25. A computer-readable storage medium, It is characterized in that A computer program is stored thereon, and when the computer program is executed by a computer, the method according to any one of claims 1 to 11 is implemented.

26. A chip, It is characterized in that include: A circuit for executing the method according to any one of claims 1 to 11.

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