Method, device and electronic equipment for suppressing vehicle acceleration

Abstract

The present application provides a method, device, and electronic device for suppressing vehicle acceleration, which are used to accurately determine abnormal vehicle acceleration and promptly suppress vehicle acceleration to avoid traffic accidents caused by the driver accidentally braking. The method includes: collecting driving parameters and driving parameters, and determining coefficients of the driving parameters and the driving parameters; classifying the driving parameters and the driving parameters based on a preset mapping relationship, and determining the abnormal acceleration probability of the classified parameter categories and the suppression threshold of the parameter categories; in response to the abnormal acceleration probability of any parameter category being greater than the suppression threshold, determining to generate a speed suppression signal; wherein the speed suppression signal indicates that vehicle acceleration should be suppressed.

Description

Technical Field

[0001] The present application relates to the field of safe driving technology, and in particular to a method, device, and electronic device for suppressing vehicle acceleration. Background Art

[0002] Currently, the number of traffic accidents caused by drivers accidentally pressing the accelerator remains high, becoming a major issue in road safety. To prevent drivers from accidentally pressing the accelerator, existing technologies generally use the throttle position and the rate of change of the throttle position within a preset time range in conjunction with the presence of obstacles on the road to determine the cause.

[0003] On the one hand, the accuracy of obstacle recognition methods and obstacle orientation determination methods actually used on vehicles still needs to be improved. In addition, when approaching an obstacle (such as an animal), the driver may also actively accelerate to avoid the obstacle. On the other hand, in order to avoid the situation where the driver mistakenly suppresses acceleration when actively accelerating, when judging the throttle opening and the throttle opening change, the best time to suppress acceleration may be missed, that is, it is difficult to suppress the abnormal acceleration of the vehicle in time. The above is due to the failure to accurately judge whether the vehicle is in abnormal acceleration or normal acceleration. Therefore, the existing technology has the problem of inaccurate judgment of abnormal vehicle acceleration. Summary of the Invention

[0004] The present application provides a method, device and electronic device for suppressing vehicle acceleration, which are used to accurately determine whether a vehicle is accelerating abnormally and to suppress vehicle acceleration in a timely manner, thereby avoiding traffic accidents caused by reasons such as the driver accidentally stepping on the brakes.

[0005] In a first aspect, an embodiment of the present application provides a method for suppressing vehicle acceleration, comprising:

[0006] Collecting travel parameters and driving parameters, and determining coefficients of the travel parameters and coefficients of the driving parameters; wherein each of the travel parameters includes at least one influencing factor, and each of the driving parameters includes at least one influencing factor, and the influencing factor corresponds to the coefficient;

[0007] Based on a preset mapping relationship, the driving parameters and the driving parameters are classified, and the abnormal acceleration probability of the classified parameter categories and the suppression threshold of the parameter categories are determined; wherein the mapping relationship includes the weight of each parameter in the parameter category and the corresponding relationship between the parameter category and the suppression threshold; the parameter category includes the driving parameters and / or the driving parameters;

[0008] In response to the abnormal acceleration probability of any of the parameter categories being greater than the inhibition threshold, generating a speed inhibition signal; wherein the speed inhibition signal indicates inhibiting vehicle acceleration.

[0009] The method provided in the embodiments of the present application comprehensively assesses whether a vehicle is accelerating abnormally by comprehensively considering multiple factors that may lead to abnormal vehicle acceleration (especially driver's misapplication of the brakes). The method also categorizes each factor (i.e., driving parameters and driving parameters) based on their influence and sets corresponding thresholds. This allows for accurate and timely identification of abnormal vehicle acceleration, including the possibility of driver's misapplication of the brakes, to avoid misidentification of abnormal vehicle acceleration and effectively prevent traffic accidents.

[0010] In a possible implementation manner, the parameter categories include a first category, a second category, and a third category; wherein, in any parameter category, the difference between the weights of any two parameters is not greater than a preset threshold; the first category includes the emotion parameter, attention parameter, and steering wheel control parameter in the driving parameters, the second category includes the road scene parameter and obstacle parameter in the driving parameters, and the third category includes the gender parameter in the driving parameters and the speed parameter in the driving parameters; wherein the obstacle is an obstacle located on the driving trajectory of the vehicle and the distance between the obstacle and the vehicle is less than a preset distance.

[0011] In one possible implementation, the classifying of the travel parameters and the driving parameters based on a preset mapping relationship, and determining the abnormal acceleration probability of the classified parameter category and the suppression threshold of the parameter category includes:

[0012] Based on the mapping relationship, determining the weight of each parameter in the parameter category;

[0013] The sum of the products of the weights of the parameters and the coefficients of the parameters is determined, where the sum of the products is the abnormal acceleration probability of the parameter category.

[0014] In a possible implementation manner, the suppression thresholds correspond one-to-one to the parameter categories, or the suppression thresholds correspond one-to-one to the influencing factors in the parameter categories.

[0015] In one possible implementation, the speed suppression signal includes a first suppression signal and a second suppression signal; wherein the first suppression signal instructs the braking system to control the vehicle to decelerate to a safe speed range at a first preset acceleration, and the second suppression signal instructs the braking system to control the vehicle to decelerate to a stop at a second preset acceleration;

[0016] Then, in response to the abnormal acceleration probability of any of the parameter categories being greater than the suppression threshold, determining to generate a speed suppression signal includes:

[0017] In response to the abnormal driving probability of any of the parameter categories being greater than the suppression threshold of the parameter category, marking the parameter category having the abnormal driving probability greater than the suppression threshold as a target category;

[0018] determining a difference between the abnormal driving probability corresponding to the target category and the suppression threshold corresponding to the target category;

[0019] In response to the difference being smaller than a second preset threshold, outputting the first suppression signal; or,

[0020] In response to the difference being greater than or equal to the second preset threshold, the second suppression signal is output.

[0021] In a possible implementation manner, after marking the parameter category having the abnormal driving probability greater than the suppression threshold as a target category, the method further includes:

[0022] Obtaining the throttle opening, the rate of change of the throttle opening within a preset time range, the weight of the throttle opening, and the weight of the rate of change of the throttle opening;

[0023] Determine the product of the throttle opening and the weight of the throttle opening, the product of the throttle opening change rate within the preset time range and the weight of the throttle opening change rate, and the sum of the products to obtain a throttle parameter;

[0024] Then, in response to the difference being less than a second preset threshold, outputting a first suppression signal comprises:

[0025] In response to the difference being smaller than the second preset threshold and the throttle parameter being larger than a third preset threshold, it is determined to output the first inhibition signal.

[0026] In a second aspect, an embodiment of the present application provides a device for suppressing vehicle acceleration, comprising:

[0027] a collection unit, configured to collect travel parameters and driving parameters, and determine coefficients of the travel parameters and the driving parameters; wherein each of the travel parameters includes at least one influencing factor, and each of the driving parameters includes at least one influencing factor, and the influencing factor corresponds to the coefficient;

[0028] a mapping unit, configured to classify the travel parameters and the driving parameters based on a preset mapping relationship, and determine an abnormal acceleration probability for each parameter category obtained by the classification, and a suppression threshold for each parameter category; wherein the mapping relationship includes a weight of each parameter in the parameter category and a corresponding relationship between the parameter category and the suppression threshold; and the parameter category includes the travel parameters and / or the driving parameters;

[0029] The response unit is configured to determine and generate a speed suppression signal in response to the abnormal acceleration probability of any of the parameter categories being greater than the suppression threshold; wherein the speed suppression signal indicates suppressing vehicle acceleration.

[0030] In a possible implementation manner, the parameter categories include a first category, a second category, and a third category; wherein, in any parameter category, the difference between the weights of any two parameters is not greater than a preset threshold; the first category includes the emotion parameter, attention parameter, and steering wheel control parameter in the driving parameters, the second category includes the road scene parameter and obstacle parameter in the driving parameters, and the third category includes the gender parameter in the driving parameters and the speed parameter in the driving parameters; wherein the obstacle is an obstacle located on the driving trajectory of the vehicle and the distance between the obstacle and the vehicle is less than a preset distance.

[0031] In one possible implementation, the mapping unit is specifically used to determine the weight of each parameter in the parameter category based on the mapping relationship; determine the sum of the products between the weight of each parameter and the coefficient of each parameter, and the sum of the products is the abnormal acceleration probability of the parameter category.

[0032] In a possible implementation manner, the suppression thresholds correspond one-to-one to the parameter categories, or the suppression thresholds correspond one-to-one to the influencing factors in the parameter categories.

[0033] In one possible implementation, the speed suppression signal includes a first suppression signal and a second suppression signal; wherein, the first suppression signal instructs the braking system to control the vehicle to decelerate to a safe speed range at a first preset acceleration, and the second suppression signal instructs the braking system to control the vehicle to decelerate to a stop at a second preset acceleration; the response unit is specifically used to, in response to the abnormal driving probability of any of the parameter categories being greater than the suppression threshold of the parameter category, mark the parameter category with the abnormal driving probability greater than the suppression threshold as a target category; determine the difference between the abnormal driving probability corresponding to the target category and the suppression threshold corresponding to the target category; in response to the difference being less than the second preset threshold, output the first suppression signal; or, in response to the difference being greater than or equal to the second preset threshold, output the second suppression signal.

[0034] In a possible implementation manner, the device further includes a parameter unit, which is specifically used to obtain the throttle opening, the throttle opening change rate within a preset time range, the weight of the throttle opening, and the weight of the throttle opening change rate; determine the product between the throttle opening and the weight of the throttle opening, the product between the throttle opening change rate within the preset time range and the weight of the throttle opening change rate, and the sum of the products to obtain a throttle parameter; and the response unit is further used to determine to output the first inhibition signal in response to the difference being less than the second preset threshold and the throttle parameter being greater than a third preset threshold.

[0035] In a third aspect, an embodiment of the present application further provides a readable storage medium, comprising:

[0036] Memory,

[0037] The memory is used to store instructions. When the instructions are executed by the processor, the device including the readable storage medium completes the method described in the first aspect and any possible implementation manner.

[0038] In a fourth aspect, an embodiment of the present application further provides an electronic device, including:

[0039] Memory for storing computer programs;

[0040] The processor is configured to execute the computer program stored in the memory to implement the method described in the first aspect and any possible implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a method for suppressing abnormal acceleration of a vehicle provided in an embodiment of the present application;

[0042] Figure 2 A schematic structural diagram of a device for suppressing vehicle acceleration provided in an embodiment of the present application;

[0043] Figure 3 A schematic diagram of the structure of an electronic device for suppressing abnormal acceleration of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] To address the inaccurate identification of abnormal vehicle acceleration in existing technologies, an embodiment of the present application provides a method for suppressing vehicle acceleration. The method collects driving parameters indicating the vehicle's driving state and driving parameters indicating the driver's driving state. For each parameter (driving parameter and driving parameter), a unique influencing factor is determined for each of the one or more influencing factors, along with a corresponding coefficient indicating the degree of influence. Furthermore, each parameter is classified. When any parameter category obtained by classification is greater than its corresponding suppression threshold, the method determines that the vehicle is accelerating abnormally.

[0045] The method comprehensively evaluates whether the vehicle has abnormal acceleration through vehicle-side parameters and driver-side parameters, and classifies each parameter. Each category of parameters has its own corresponding suppression threshold, so that when a parameter in any parameter category is abnormal, the problem of abnormal vehicle acceleration can be discovered in a timely and accurate manner to suppress vehicle acceleration, thereby improving the accuracy of judging abnormal vehicle acceleration and timely suppressing abnormal vehicle acceleration.

[0046] In order to better understand the above technical solution, the technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0047] Please refer to Figure 1 This application proposes a method for suppressing vehicle acceleration to improve the accuracy of the result of determining whether the vehicle's accelerator has been accidentally pressed. The method specifically includes the following implementation steps:

[0048] Step 101: collecting travel parameters and driving parameters, and determining coefficients of the travel parameters and coefficients of the driving parameters.

[0049] Among them, the driving parameters indicate the vehicle state parameters that affect the driver's stepping on the accelerator, and each driving parameter includes at least one influencing factor, and the influencing factor corresponds to a coefficient. That is to say, the driving parameters indicate the parameters on one side of the vehicle that may affect the driver's mistaken stepping on the accelerator and the corresponding influence size. When a certain driving parameter includes one influencing factor, the influencing factor of the driving parameter is uniquely determined, and its coefficient is uniquely determined. When a certain driving parameter includes multiple influencing factors, the current influencing factor of the parameter is determined according to the specific situation of the collected parameter. For example, the road scene parameter, where the influencing factors include underground parking, parking lot entry, downhill, curve, etc., the coefficients of the aforementioned influencing factors are, for example, 10, 15, 20, 15. If it is determined to be an underground parking according to the collected road scene parameter, the coefficient of the road scene parameter is determined to be 10.

[0050] The driving parameters indicate the driver's state parameters that affect the driver's stepping on the accelerator. Each driving parameter includes at least one influencing factor, and the influencing factor corresponds to a coefficient. In other words, the driving parameters indicate the parameters on the driver's side that may affect the accidental stepping on the accelerator and the corresponding influence size. Similar to the driving parameters, first, based on the driving parameters, the influencing factor corresponding to the current driving parameter is uniquely determined among the multiple influencing factors corresponding to the driving parameters, that is, the coefficient of the driving parameter is determined. For example, the influencing factors of the gender parameter include male and female, and their respective coefficients are 12 and 10. After determining that the driver's gender is male based on the current driving parameters, the coefficient of the gender parameter can be determined to be 12.

[0051] The driving parameters may include road scene parameters, obstacle parameters, and speed parameters. The obstacle is an obstacle located on the driving track of the vehicle and the distance between the obstacle and the vehicle is less than a preset distance.

[0052] Among them, the influencing factors included in the road scene parameters can include basement, parking lot entrance, downhill, curve, and intersection. The influencing factors included in the obstacle parameters can include imminent collision, possible collision, and passing. The influencing factors included in the speed parameters can include ultra-high speed, high speed, medium speed, and low speed.

[0053] Driving parameters may include gender parameters, emotion parameters, steering wheel control parameters, and attention parameters.

[0054] The gender parameter can include factors such as male and female. The emotion parameter can include factors such as joy, peace, sadness, and irritability. The steering wheel control parameter can include factors such as one-handed (controlled), two-handed (controlled), and hands-off (uncontrolled). The attention parameter can include factors such as eyes-on and eyes-off.

[0055] Therefore, although each travel parameter or driving parameter includes multiple influencing factors, the influencing factor is uniquely determined for each travel parameter or driving parameter determined each time; accordingly, each driving parameter and the coefficient of the travel parameter are uniquely determined.

[0056] The aforementioned driving parameters can be collected through in-vehicle and out-vehicle sensors (e.g., cameras, radar, lasers, etc.), as well as high-precision positioning combined with maps. For example, vehicle speed parameters can be collected by using the vehicle bus to measure the average speed within a preset time range (e.g., 1 minute). For example, obstacle parameters can be determined by using parameters collected by in-vehicle and out-vehicle sensors to identify obstacles within a preset distance and to determine the changing parameters of the relative positional relationship between the obstacle and the vehicle (e.g., distance, rate of change of distance, etc.).

[0057] Similarly, the above-mentioned driving parameters can also be collected by in-vehicle and out-vehicle sensors, especially in-vehicle sensors (such as cameras and infrared detectors). For example, steering wheel control parameters can be collected by the capacitive sensor on the steering wheel to determine whether the steering wheel is being held with one hand, two hands, or hands-free. For example, eye parameters can be collected as attention parameters by a camera located diagonally above and in front of the driver. Among them, gender parameters can be determined by recognition and judgment by the in-vehicle camera, or can be determined by active input from the driver.

[0058] Step 102: Based on a preset mapping relationship, the travel parameters and the driving parameters are classified, and the abnormal acceleration probability of the classified parameter category and the suppression threshold of the parameter category are determined.

[0059] The mapping relationship includes the weight of each parameter in the parameter category. The sum of the weights of the parameters in all parameter categories is 1. The parameters here can be driving parameters or driving parameters, that is, the parameter category can include driving parameters and / or driving parameters.

[0060] The mapping relationship also includes the correspondence between each parameter category and the specific parameters therein (travel parameters and / or driving parameters). The specific parameter categories can be divided according to weight. In one embodiment of the present application, the parameter categories include a first category, a second category, and a third category. The difference in weights between any two parameters in any parameter category does not exceed a preset threshold. The weights of the parameters in each parameter category are similar.

[0061] The first category includes emotion parameters, attention parameters, and steering wheel control parameters in driving parameters. The second category includes road scene parameters and obstacle parameters in driving parameters. The third category includes gender parameters and speed parameters in driving parameters.

[0062] The influence of the above three parameter categories on the driver's accidental accelerator pressing decreases in sequence; therefore, the inhibition threshold of each parameter category or the inhibition threshold in each parameter category increases in sequence, that is, the inhibition threshold of the first parameter category (medium) is lower than the inhibition threshold of the second parameter category (medium), and the inhibition threshold of the second parameter category (medium) is lower than the inhibition threshold of the third parameter category (medium).

[0063] The following further explains how to determine the abnormal acceleration probability: First, based on the aforementioned mapping relationships, the weights of the parameters within the aforementioned parameter categories are determined. Next, the weights of each parameter are multiplied by the parameter's coefficient, resulting in the product of each parameter's weight and coefficient. These products are then summed for each parameter category, resulting in the abnormal acceleration probability for each parameter category.

[0064] For example, if the influencing factor of the emotion parameter is sadness, the coefficient is 0.5. If the influencing factor is joy, the coefficient is 0.2. If the influencing factor is irritability, the coefficient is 0.2. The corresponding unified weight of the emotion parameter is 0.8.

[0065] Therefore, the weights indicate the possibility of each parameter affecting the driver's mistaken braking, and each coefficient indicates the degree of influence of the influencing factor (i.e., the current driver state or vehicle state) corresponding to the parameter on the driver's mistaken braking. In the embodiment of the present application, the correspondence between the weights and each parameter (including traveling parameters and driving parameters), as well as the correspondence between the influencing factors in each parameter (including traveling parameters and driving parameters) and their respective coefficients are obtained based on a simulation test data set. The simulation data set includes each parameter, the influencing factor in each parameter, and the corresponding result of whether the driver mistakenly brakes. Specifically, it can be obtained through inductive analysis or deep learning algorithm.

[0066] Furthermore, the above-mentioned mapping relationship also includes a correspondence between parameter categories and suppression thresholds. According to the preset mapping relationship, the suppression threshold corresponding to each parameter category obtained by classification is determined. That is, different parameter categories have different suppression thresholds. For a parameter category that is more likely to affect the driver's mistaken stepping on the accelerator pedal, the greater the probability of abnormal acceleration of the parameter category, the more likely the driver is to mistakenly step on the accelerator; accordingly, the lower the suppression threshold. That is, the suppression threshold is inversely proportional to the influence of each parameter in the parameter category on the driver's stepping on the accelerator. The embodiment of the present application provides two implementation methods for setting the correspondence between the suppression threshold and the parameter category in the mapping relationship in combination with the aforementioned simulation data. The first method is to make the suppression threshold correspond to the parameter category one-to-one. The second method is to make the suppression threshold correspond to the influencing factor in the parameter one-to-one. Specifically, in the first method, the number of suppression thresholds is the same as the number of parameter categories. Each parameter category uniquely corresponds to one suppression threshold. The second method is to make each parameter category correspond to multiple suppression thresholds, and the number of suppression thresholds corresponds to the influencing factor in the parameter and the number of parameters.

[0067] For example, in a certain category of parameters, the parameters are {steering wheel control parameters, emotional parameters, attention parameters}. The influencing factors of each parameter (coefficients not shown) can be {(steering wheel control parameters, hands off), (emotional parameters, irritability), (attention parameters, eyes off)}. The influencing factors of each parameter in the above category parameters can also be {(steering wheel control parameters, hands off), (emotional parameters, sadness), (attention parameters, eyes off)}. For the first implementation of the suppression threshold, the suppression threshold for the parameter category {steering wheel control parameters, emotional parameters, attention parameters} is uniformly 60%, that is, the suppression thresholds of {(steering wheel control parameters, hands off), (emotional parameters, irritability), (attention parameters, eyes off), and {(steering wheel control parameters, hands off), (emotional parameters, sadness), (attention parameters, eyes off)} are all 60%. As for the second implementation method of the inhibition threshold, the inhibition threshold of {(steering wheel control parameter, hands off), (emotional parameter, irritability), (attention parameter, eyes off) is 10%, and the inhibition threshold of {(steering wheel control parameter, hands off), (emotional parameter, sadness), (attention parameter, eyes off)} is 40%.

[0068] Step 103: In response to the abnormal acceleration probability of any of the parameter categories being greater than the suppression threshold, determine to generate a speed suppression signal.

[0069] The speed suppression signal indicates that the vehicle acceleration should be suppressed. The speed suppression signal can be sent to the braking system or the engine system to suppress the vehicle acceleration and ensure the safety of the vehicle and the passengers.

[0070] The above-mentioned speed suppression signal may include a first suppression signal and a second suppression signal. The first suppression signal instructs the braking system to control the vehicle to decelerate at a first preset acceleration until it reaches a safe speed range, and the second suppression signal instructs the braking system to decelerate at a second preset acceleration until it stops. The following is a specific description. In response to the abnormal driving probability of any parameter category being greater than its corresponding suppression threshold, the parameter category is marked, that is, the parameter category with the abnormal driving probability greater than its suppression threshold is marked as the target category. Then, the difference between the abnormal driving probability corresponding to the target category and the suppression threshold corresponding to the target category is further determined. In response to the difference being less than the second preset threshold, the above-mentioned first suppression signal is output. Alternatively, in response to the difference being greater than or equal to the second preset threshold, the second suppression signal is output.

[0071] Furthermore, the throttle opening and the rate of change of the throttle opening within a preset time range can be combined to determine whether the driver has accidentally stepped on the accelerator. Specifically, after determining the target category, the throttle opening, the rate of change of the throttle opening within a preset time range, the weight of the throttle opening, and the weight of the throttle opening rate of change are first obtained. The throttle parameter is then obtained by multiplying the throttle opening by the weight of the throttle opening, the product of the rate of change of the throttle opening within the preset time range and the weight of the throttle opening rate of change, and the sum of these products.

[0072] At this point, a comprehensive judgment can be made based on the aforementioned difference and the throttle parameter. Specifically, if the difference is less than the second preset threshold and the throttle parameter is greater than the third preset threshold, a first suppression signal is determined to be output. Alternatively, if the difference is greater than or equal to the second preset threshold and the throttle parameter is greater than the fourth preset threshold, a second suppression signal is determined to be output. In other words, a greater throttle opening and a greater rate of change in the throttle opening correspond to a higher throttle parameter.

[0073] The above judgment method can be expressed based on the following expression: Input{P(acceleration abnormality probability), A(throttle opening, throttle opening change rate)}, Output{Y(acceleration suppression or not)}; or, Input{D(difference), A(throttle opening, throttle opening change rate)}, Output{Y(acceleration suppression or not)}.

[0074] Based on the same inventive concept, a device for suppressing vehicle acceleration is provided in an embodiment of the present application. Figure 1 The method for suppressing vehicle acceleration shown in FIG. 1 corresponds to the method for suppressing vehicle acceleration shown in FIG. 1 , and the specific implementation of the device can be found in the description of the aforementioned method embodiment. The repeated parts will not be repeated here. Figure 2 , the device comprises:

[0075] The collecting unit 201 is used to collect travel parameters and driving parameters, and determine coefficients of the travel parameters and coefficients of the driving parameters.

[0076] Each of the driving parameters includes at least one influencing factor, and each of the driving parameters includes at least one influencing factor, and the influencing factor corresponds to the coefficient.

[0077] The mapping unit 202 is configured to classify the travel parameters and the driving parameters based on a preset mapping relationship, and determine the abnormal acceleration probability of the parameter category obtained by classification and the suppression threshold of the parameter category.

[0078] The mapping relationship includes the weight of each parameter in the parameter category and the corresponding relationship between the parameter category and the suppression threshold.

[0079] The parameter categories include a first category, a second category and a third category; wherein, in any parameter category, the difference between the weights of any two parameters is not greater than a preset threshold; the first category includes the emotion parameter, attention parameter, and steering wheel control parameter in the driving parameters, the second category includes the road scene parameter and obstacle parameter in the driving parameters, and the third category includes the gender parameter in the driving parameters and the speed parameter in the driving parameters; wherein the obstacle is an obstacle located on the driving trajectory of the vehicle and the distance between the obstacle and the vehicle is less than a preset distance.

[0080] The mapping unit 202 is specifically used to determine the weight of each parameter in the parameter category based on the mapping relationship; determine the sum of the products between the weight of each parameter and the coefficient of each parameter, and the sum of the products is the abnormal acceleration probability of the parameter category.

[0081] The response unit 203 is specifically configured to determine to generate a speed suppression signal in response to the abnormal acceleration probability of any parameter category being greater than the suppression threshold.

[0082] The speed suppression signal indicates that vehicle acceleration is suppressed.

[0083] The suppression threshold corresponds to the parameter category one-to-one, or the suppression threshold corresponds to the influencing factor in the parameter category one-to-one.

[0084] The above-mentioned speed suppression signal includes a first suppression signal and a second suppression signal; wherein, the first suppression signal instructs the braking system to control the vehicle to decelerate to a safe speed range at a first preset acceleration, and the second suppression signal instructs the braking system to control the vehicle to decelerate to a stop at a second preset acceleration; the response unit 203 is specifically used to, in response to the abnormal driving probability of any of the parameter categories being greater than the suppression threshold of the parameter category, mark the parameter category with the abnormal driving probability greater than the suppression threshold as a target category; determine the difference between the abnormal driving probability corresponding to the target category and the suppression threshold corresponding to the target category; in response to the difference being less than the second preset threshold, output the first suppression signal; or, in response to the difference being greater than or equal to the second preset threshold, output the second suppression signal.

[0085] The above-mentioned device for suppressing vehicle acceleration also includes a parameter unit, which is specifically used to obtain the throttle opening, the throttle opening change rate within a preset time range, the weight of the throttle opening and the weight of the throttle opening change rate; determine the product between the throttle opening and the weight of the throttle opening, the product between the throttle opening change rate within the preset time range and the weight of the throttle opening change rate, and the sum of the products to obtain the throttle parameter; the response unit 203 is also used to determine to output the first suppression signal in response to the difference being less than the second preset threshold and the throttle parameter being greater than the third preset threshold.

[0086] Based on the same inventive concept, an embodiment of the present application further provides a readable storage medium, including:

[0087] Memory,

[0088] The memory is used to store instructions, and when the instructions are executed by the processor, the device including the readable storage medium performs the method of suppressing vehicle acceleration as described above.

[0089] Based on the same inventive concept as the above-mentioned method for suppressing vehicle acceleration, an electronic device is also provided in an embodiment of the present application. The electronic device can implement the function of the above-mentioned method for suppressing vehicle acceleration. Please refer to Figure 3 , the electronic device includes:

[0090] At least one processor 301, and a memory 302 connected to the at least one processor 301. The specific connection medium between the processor 301 and the memory 302 is not limited in the embodiment of the present application. Figure 3 In the example, the processor 301 and the memory 302 are connected via the bus 300. Figure 3 The bus 300 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The diagram is represented by only one thick line, but this does not mean that there is only one bus or one type of bus. Alternatively, the processor 301 may also be referred to as a controller, without limitation to the name.

[0091] In the embodiment of the present application, the memory 302 stores instructions that can be executed by at least one processor 301. The at least one processor 301 can execute the method of suppressing vehicle acceleration discussed above by executing the instructions stored in the memory 302. The processor 301 can implement Figure 2 The functions of each module in the device shown.

[0092] Among them, the processor 301 is the control center of the device, which can use various interfaces and lines to connect the various parts of the entire control device, and monitor the device as a whole by running or executing instructions stored in the memory 302 and calling data stored in the memory 302, the various functions of the device and processing data.

[0093] In one possible design, processor 301 may include one or more processing units. Processor 301 may integrate an application processor and a modem processor. The application processor primarily processes the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 301. In some embodiments, processor 301 and memory 302 may be implemented on the same chip. In some embodiments, they may also be implemented on separate chips.

[0094] The processor 301 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method for suppressing vehicle acceleration disclosed in the embodiments of this application can be directly implemented as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0095] The memory 302 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 302 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmable Read Only Memory, PROM), a read-only memory (Read Only Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 302 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 302 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0096] By programming the processor 301, the code corresponding to the method for suppressing vehicle acceleration described in the above embodiment can be fixed into the chip, so that the chip can execute the method when running. Figure 1 The steps of the method for suppressing vehicle acceleration are shown. How to design and program the processor 301 is a technique well known to those skilled in the art and will not be described in detail here.

[0097] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-mentioned systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0098] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, 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.

[0099] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0100] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0101] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: a universal serial bus flash disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0102] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for suppressing vehicle acceleration, characterized in that: include: Collecting travel parameters and driving parameters, and determining coefficients of the travel parameters and coefficients of the driving parameters; wherein each travel parameter includes at least one influencing factor, each driving parameter includes at least one influencing factor, and one influencing factor corresponds to one coefficient; Based on a preset mapping relationship, the travel parameters and the driving parameters are classified, and the abnormal acceleration probability of the classified parameter category and the suppression threshold of the parameter category are determined; wherein the mapping relationship includes the weight of each parameter in the parameter category, the mapping relationship includes the correspondence between the parameter category and the parameters therein, and the correspondence between the parameter category and the suppression threshold, and the correspondence between each parameter and the weight is obtained based on a simulated test data set; In response to the abnormal acceleration probability of any of the parameter categories being greater than the inhibition threshold, generating a speed inhibition signal; wherein the speed inhibition signal indicates inhibiting vehicle acceleration.

2. The method according to claim 1, wherein The parameter categories include a first category, a second category and a third category; wherein, in any parameter category, the difference between the weights of any two parameters is not greater than a preset threshold; the first category includes the emotion parameter, attention parameter, and steering wheel control parameter in the driving parameters, the second category includes the road scene parameter and obstacle parameter in the driving parameters, and the third category includes the gender parameter in the driving parameters and the speed parameter in the driving parameters; wherein the obstacle is an obstacle located on the driving trajectory of the vehicle and the distance between the obstacle and the vehicle is less than a preset distance.

3. The method according to claim 1 or 2, wherein: The classifying the travel parameters and the driving parameters based on the preset mapping relationship, and determining the abnormal acceleration probability of the classified parameter category and the suppression threshold of the parameter category includes: Based on the mapping relationship, determining the weight of each parameter in the parameter category; The sum of the products of the weights of the parameters and the coefficients of the parameters is determined, where the sum of the products is the abnormal acceleration probability of the parameter category.

4. The method according to claim 1, wherein The suppression thresholds correspond to the parameter categories in a one-to-one manner, or the suppression thresholds correspond to the influencing factors in the parameter categories in a one-to-one manner.

5. The method according to any one of claims 1 to 2, 4, characterized in that: The speed suppression signal includes a first suppression signal and a second suppression signal; wherein the first suppression signal instructs the braking system to control the vehicle to decelerate to a safe speed range at a first preset acceleration, and the second suppression signal instructs the braking system to control the vehicle to decelerate to a stop at a second preset acceleration; Then, in response to the abnormal acceleration probability of any of the parameter categories being greater than the suppression threshold, determining to generate a speed suppression signal includes: In response to the abnormal driving probability of any of the parameter categories being greater than the suppression threshold of the parameter category, marking the parameter category having the abnormal driving probability greater than the suppression threshold as a target category; determining a difference between the abnormal driving probability corresponding to the target category and the suppression threshold corresponding to the target category; In response to the difference being smaller than a second preset threshold, outputting the first suppression signal; or, In response to the difference being greater than or equal to the second preset threshold, the second suppression signal is output.

6. The method according to claim 5, wherein After marking the parameter category having the abnormal driving probability greater than the suppression threshold as a target category, the method further includes: Obtaining the throttle opening, the rate of change of the throttle opening within a preset time range, the weight of the throttle opening, and the weight of the rate of change of the throttle opening; Determine the product of the throttle opening and the weight of the throttle opening, the product of the throttle opening change rate within the preset time range and the weight of the throttle opening change rate, and the sum of the products to obtain a throttle parameter; Then, in response to the difference being less than a second preset threshold, outputting a first suppression signal comprises: In response to the difference being smaller than the second preset threshold and the throttle parameter being larger than a third preset threshold, it is determined to output the first inhibition signal.

7. A device for suppressing vehicle acceleration, characterized in that: include: a collection unit, configured to collect travel parameters and driving parameters, and determine coefficients of the travel parameters and the driving parameters; wherein each travel parameter includes at least one influencing factor, each driving parameter includes at least one influencing factor, and one influencing factor corresponds to one coefficient; a mapping unit, configured to classify the travel parameters and the driving parameters based on a preset mapping relationship, and determine an abnormal acceleration probability for each parameter category obtained by the classification, and a suppression threshold for each parameter category; wherein the mapping relationship includes a weight for each parameter in the parameter category, a correspondence between the parameter category and the parameters therein, and a correspondence between the parameter category and the suppression threshold, and the correspondence between each parameter and the weight is obtained based on a simulated test data set; The response unit is configured to determine and generate a speed suppression signal in response to the abnormal acceleration probability of any of the parameter categories being greater than the suppression threshold; wherein the speed suppression signal indicates suppressing vehicle acceleration.

8. The device according to claim 7, wherein The mapping unit is specifically used to determine the weight of each parameter in the parameter category based on the mapping relationship; determine the sum of the products between the weight of each parameter and the coefficient of each parameter, and the sum of the products is the abnormal acceleration probability of the parameter category.

9. A readable storage medium, characterized in that: include, Memory, The memory is used to store instructions, and when the instructions are executed by the processor, the device including the readable storage medium performs the method according to any one of claims 1 to 6.

10. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the method according to any one of claims 1 to 6 when executing the computer program stored in the memory.

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