Vehicle alarm data acquisition method, device, equipment and medium

Abstract

The invention discloses a vehicle alarm data acquisition method and device, equipment and a medium. The method comprises the following steps: acquiring driving data corresponding to a driving scene type under the condition that vehicle alarm data corresponding to the driving scene type is empty; the driving data comprises at least one driving parameter and at least one parameter value corresponding to each driving parameter; determining scene alarm data according to driving data corresponding to the driving scene type; and updating the vehicle alarm data corresponding to the driving scene type according to the scene alarm data and the standard alarm data corresponding to the driving scene type. According to the embodiment of the invention, the accuracy of obtaining the vehicle alarm data can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method, device, equipment and medium for obtaining vehicle warning data. Background Art

[0002] With the development of technology, the types and quantities of vehicles are increasing. To ensure the safe operation of vehicles, warning data can be set so that vehicle controllers give warnings according to the warning data.

[0003] At the current stage, when vehicles leave the factory, production users uniformly set the warning data of vehicles. Correspondingly, the vehicle controllers of each vehicle give warnings according to unified standards.

[0004] However, each piece of warning data cannot conform to the driving habits of all users, resulting in frequent warning messages that do not conform to the driving habits of drivers, which interfere with the drivers' attention. Summary of the Invention

[0005] The present invention provides a method, device, equipment and medium for obtaining vehicle warning data to improve the accuracy of obtaining vehicle warning data.

[0006] In a first aspect, an embodiment of the present invention provides a method for obtaining vehicle warning data, the method comprising:

[0007] When the vehicle warning data corresponding to the driving scenario type is empty, obtaining the driving data corresponding to the driving scenario type; the driving data includes: at least one driving parameter, and at least one parameter value corresponding to each driving parameter;

[0008] Determining scenario warning data according to the driving data corresponding to the driving scenario type;

[0009] Updating the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type.

[0010] In a second aspect, an embodiment of the present invention further provides a device for obtaining vehicle warning data, the device comprising:

[0011] A driving data acquisition module, configured to obtain the driving data corresponding to the driving scenario type when the vehicle warning data corresponding to the driving scenario type is empty; the driving data includes: at least one driving parameter, and at least one parameter value corresponding to each driving parameter;

[0012] A warning data determination module, configured to determine scenario warning data according to the driving data corresponding to the driving scenario type;

[0013] An alarm data update module is used to update the vehicle alarm data corresponding to the driving scenario type according to the scenario alarm data and the standard alarm data corresponding to the driving scenario type.

[0014] Thirdly, an embodiment of the present invention further provides a vehicle alarm data acquisition device, which includes:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the vehicle alarm data acquisition method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the vehicle alarm data acquisition method according to any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention, when the vehicle alarm data corresponding to the driving scenario type is empty, obtains the driving data corresponding to the driving scenario type; the driving data includes: at least one driving parameter and at least one parameter value corresponding to each driving parameter; determines the scenario alarm data according to the driving data corresponding to the driving scenario type; and updates the vehicle alarm data corresponding to the driving scenario type according to the scenario alarm data and the standard alarm data corresponding to the driving scenario type, can update the vehicle alarm data according to the driving data corresponding to the driving scenario type, so that the updated vehicle alarm data conforms to the user's driving habits, and improves the accuracy of vehicle alarm data acquisition.

[0020] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0022] Figure 1 is a flowchart of a vehicle alarm data acquisition method according to Embodiment 1 of the present invention;

[0023] Figure 2 is a flowchart of a method for obtaining vehicle warning data provided in Embodiment 2 of the present invention;

[0024] Figure 3 is a structural diagram of a device for obtaining vehicle warning data provided in an embodiment of the present invention;

[0025] Figure 4 is a schematic structural diagram of a device for obtaining vehicle warning data provided in an embodiment of the present invention. Detailed implementation manners

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0028] In the technical solutions of the embodiments of the present invention, the acquisition, storage, and application of driving parameters, etc. all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0029] Embodiment 1

[0030] Figure 1 is a flowchart of a method for obtaining vehicle warning data provided in Embodiment 1 of the present invention. The embodiments of the present invention are applicable to the situation of obtaining vehicle warning data. This method can be executed by a device for obtaining vehicle warning data, and the device for obtaining vehicle warning data can be implemented in the form of hardware and / or software.

[0031] See Figure 1 The method for obtaining vehicle warning data shown, includes:

[0032] S101. When the vehicle warning data corresponding to the driving scenario type is empty, obtain the driving data corresponding to the driving scenario type; the driving data includes: at least one driving parameter and at least one parameter value corresponding to each driving parameter.

[0033] Among them, the driving scenario type can be used to describe the types of driving operations of the driver in different driving environments. The driving operations of the driver on the vehicle corresponding to different driving scenario types are different. The vehicle warning data can be used to describe a set of conditional information for warning on each acquisition index of the vehicle. The driving data can be used to describe the data collected during the vehicle driving process. For example, the driving data includes the environmental information around the vehicle collected by the vehicle, the operation information of the driver on the vehicle, or the usage status information of each component of the vehicle. The driving parameter can be used to describe each acquisition index when collecting the driving data. The parameter value can be the data corresponding to each collected driving parameter. The driving data includes at least one driving parameter and at least one parameter value corresponding to each driving parameter.

[0034] Specifically, the driving scenario type and the vehicle warning data are in one-to-one correspondence. The vehicle warning data in the initial state of the vehicle can be empty, or the vehicle warning data corresponding to the vehicle includes the vehicle warning data of at least one driving scenario type. Obtain the current driving scenario type of the vehicle, query the vehicle warning data of the vehicle according to the driving scenario type. When the vehicle warning data corresponding to the driving scenario type is empty, it indicates that there is no vehicle warning data corresponding to this driving scenario type in the vehicle, and it is necessary to obtain the vehicle warning data corresponding to this driving scenario type, so as to monitor and warn the running state of the vehicle in this driving scenario type and ensure the driving safety of the vehicle. The vehicle warning data corresponding to the driving scenario type can be determined according to the driving data corresponding to the driving scenario type. Obtain the driving data corresponding to the driving scenario type; the driving data includes: at least one driving parameter and at least one parameter value corresponding to each driving parameter. For example, the driving parameter can be: the relative distance between the vehicle body and the lane line, the throttle opening, the radar sensing distance, the vehicle fuel gauge value, the vehicle brake opening, or the steering wheel steering angle, etc.

[0035] S102. Determine the scenario warning data according to the driving data corresponding to the driving scenario type.

[0036] Among them, the scenario warning data can be used to describe the data for monitoring and warning the driving state of the vehicle in the driving scenario type.

[0037] Specifically, different drivers have different driving habits. When facing the same type of driving scenario, different drivers have different driving operations on the vehicle, that is, different usage methods for each component in the vehicle, resulting in different parameter values for each driving parameter collected from the vehicle. Therefore, different driving data is collected from the vehicle. For the vehicle driven by a driver, driving data corresponding to the driving scenario type and conforming to the driver's driving habit is obtained, and scenario warning data is determined based on the driving data. The scenario warning data includes at least one driving parameter and the warning data corresponding to each driving parameter. Making the scenario warning data conform to the driver's driving habit can avoid the frequent generation of warning information that does not affect driving safety due to the scenario warning data not conforming to the driving habit, distracting the driver's attention and leading to the occurrence of unsafe accidents.

[0038] S103. Update the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type.

[0039] Among them, the standard warning data can be used to describe data that conforms to safety standards, and the standard warning data can be preset according to industry experience.

[0040] Specifically, the driving scenario type corresponds one-to-one with the standard warning data. The standard warning data includes at least one driving parameter and the warning data corresponding to the data range that conforms to the safety standard for each driving parameter. For each driving parameter, compare the warning data corresponding to the driving parameter in the scenario warning data with the warning data corresponding to the driving parameter in the standard warning data to determine the intersection data of the two warning data. The obtained intersection data is within the data range corresponding to the standard warning data, indicating that the intersection data conforms to the safety standards formulated by the industry. Moreover, the intersection data is also within the data range corresponding to the scenario warning data, indicating that the intersection data conforms to the driver's driving habit. Determine the target warning data to be used to update the vehicle warning data based on the intersection data, and update the vehicle warning data with the target warning data. The updated vehicle warning data not only conforms to safety standards but also conforms to the driver's driving habit, making the obtained vehicle warning data more accurate.

[0041] The technical solution of the embodiment of the present invention can, when the vehicle warning data corresponding to the driving scenario type is empty, obtain the driving data corresponding to the driving scenario type; the driving data includes: at least one driving parameter and at least one parameter value corresponding to each driving parameter; determine the scenario warning data according to the driving data corresponding to the driving scenario type; update the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type, and can update the vehicle warning data according to the driving data corresponding to the driving scenario type, so that the updated vehicle warning data conforms to the driving habit of the user, improving the accuracy of obtaining vehicle warning data.

[0042] Embodiment 2

[0043] Figure 2 The figure is a flowchart of a method for obtaining vehicle warning data provided by Embodiment 2 of the present invention. Based on the above embodiment, the operation of obtaining vehicle warning data in the present invention embodiment is optimized and improved.

[0044] Further, "determining the scenario warning data according to the driving data corresponding to the driving scenario type" is refined to "statistically calculating the parameter extreme values of at least one driving parameter from the driving data corresponding to the driving scenario type; and determining the parameter extreme values of each driving parameter as the scenario warning data", so as to improve the operation of obtaining vehicle warning data.

[0045] It should be noted that for the parts not described in detail in the embodiments of the present invention, reference can be made to the descriptions of other embodiments.

[0046] Refer to Figure 2 The method for obtaining vehicle warning data shown below includes:

[0047] S201. When the vehicle warning data corresponding to the driving scenario type is empty, obtain the driving data corresponding to the driving scenario type; the driving data includes: at least one driving parameter and at least one parameter value corresponding to each driving parameter.

[0048] S202. Statistically calculate the parameter extreme values of at least one driving parameter from the driving data corresponding to the driving scenario type.

[0049] Among them, the parameter extreme value can be used to describe the value in the extreme state among the parameter values corresponding to the driving parameter.

[0050] Specifically, different drivers have different driving habits. For example, some drivers like to accelerate and brake suddenly, while some drivers tend to drive smoothly. Therefore, the driving data corresponding to different drivers in the same driving scenario type is different. By obtaining the driving data of the vehicle corresponding to the driving scenario type and determining the parameter extreme values of each driving parameter, for each driving parameter, the data in the extreme state among the parameter values of the driving parameter in the driver's behavior mode can be determined to obtain the parameter extreme value. If the parameter extreme value corresponding to the driving parameter meets the safety standard, it indicates that all the parameter values corresponding to the driving parameter meet the safety standard; if the parameter extreme value corresponding to the driving parameter does not meet the safety standard, it indicates that there are parameter values that do not meet the safety standard among the parameter values corresponding to the driving parameter, and an alarm needs to be issued in a timely manner to prompt the driver to adjust the driving behavior mode. The numerical range of the parameter extreme value can be determined according to the driving parameter. For example, if the driving parameter is the radar sensing distance, the numerical range of the parameter extreme value is the minimum value among the parameter values; if the driving parameter is the driving speed, the numerical range of the parameter extreme value is the maximum value among the parameter values; if the driving parameter is the fuel quantity, the parameter extreme value can be a data range. From the driving data corresponding to the driving scenario type, the parameter extreme values of at least one driving parameter are statistically obtained. For example, for a driver who often accelerates suddenly, obtaining the parameter extreme values of the torque and power of his vehicle during the acceleration process can know the working limit of the power system of the vehicle in this driving mode, which is convenient for comparing the parameter extreme values of the torque and power with the alarm data of the torque and power in the standard alarm data to determine whether it meets the safety standard, so as to determine the scenario alarm data.

[0051] S203. Determine the parameter extreme values of each driving parameter as the scenario alarm data.

[0052] Specifically, one driving scenario type corresponds to one scenario warning data. The scenario warning data includes at least one driving parameter and the warning data corresponding to each driving parameter. Obtain the parameter extreme values of each driving parameter, and for each driving parameter, determine the parameter extreme value corresponding to the driving parameter as the warning data corresponding to the driving parameter. Determine the driving parameters corresponding to the driving scenario type and the parameter extreme values corresponding to each driving parameter as the scenario warning data corresponding to the driving scenario type. That is, first determine the scenario warning data that conforms to the driving habit corresponding to the driving scenario type according to the driving data. Then compare the scenario warning data with the standard warning data, and update the vehicle warning data stored in the vehicle according to the comparison result. Adjust the vehicle warning data under the condition of meeting the safety standard according to the driving habit to improve the accuracy of the vehicle warning data. When the vehicle is running, the controller in the vehicle can monitor the parameter value corresponding to the driving parameter in real time, and compare the parameter value with the data range corresponding to the warning data of the driving parameter in the vehicle warning data. If the parameter value is within the data range corresponding to the warning data, it indicates that the vehicle running state meets the safety standard at this time, and there is no need to generate a warning message to prompt the driver to adjust the driving operation; if the parameter value is not within the data range corresponding to the warning data, it indicates that the vehicle running state does not meet the safety standard at this time, and a warning message needs to be generated to prompt the driver to adjust the driving operation.

[0053] S204. Update the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type.

[0054] In the embodiment of the present invention, by statistically analyzing the parameter extreme values of at least one driving parameter from the driving data corresponding to the driving scenario type; determining the parameter extreme values of each driving parameter as the scenario warning data, the scenario warning data can be determined according to the driving data corresponding to the driver's driving operation, so that the scenario warning data conforms to the driver's driving habit, which is beneficial to obtaining personalized scenario warning data.

[0055] Optionally, updating the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type includes: in the case where the scenario warning data and the standard warning data are completely different, updating the vehicle warning data according to the standard warning data; in the case where the scenario warning data and the standard warning data are not completely the same, updating the vehicle warning data according to the standard warning data and the scenario warning data; in the case where the data range of the scenario warning data includes the data range of the standard warning data, updating the vehicle warning data according to the standard warning data; in the case where the data range of the standard warning data includes the data range of the scenario warning data, updating the vehicle warning data according to the scenario warning data.

[0056] Specifically, when the scenario warning data is completely different from the standard warning data, it indicates that for each driving parameter, none of the parameter values corresponding to the driving parameters in the scenario warning data meet the safety standards, that is, the driver's driving operation does not meet the safety standards. Then, the vehicle warning data of the vehicle uses industry standard data, and the vehicle warning data is updated according to the standard warning data. When the scenario warning data and the standard warning data are not completely the same, it indicates that only some of the data in the scenario warning data meet the safety standards. Then, the intersection of the standard warning data and the scenario warning data is obtained to get the intersection data, and the vehicle warning data is updated through the intersection data. When the data range of the scenario warning data includes the data range of the standard warning data, it indicates that the data range of the standard warning data is smaller and safer. Then, the vehicle warning data is updated according to the standard warning data. When the data range of the standard warning data includes the data range of the scenario warning data, it indicates that the data range of the scenario warning data is smaller and safer. The vehicle warning data is updated according to the scenario warning data.

[0057] By updating the vehicle warning data according to the standard warning data when the scenario warning data is completely different from the standard warning data; updating the vehicle warning data according to the standard warning data and the scenario warning data when the scenario warning data and the standard warning data are not completely the same; updating the vehicle warning data according to the standard warning data when the data range of the scenario warning data includes the data range of the standard warning data; and updating the vehicle warning data according to the scenario warning data when the data range of the standard warning data includes the data range of the scenario warning data, different update methods of the vehicle warning data are executed for different comparison results of the standard warning data and the scenario warning data, which refines the update method of the vehicle warning data and improves the accuracy of the vehicle warning data update.

[0058] Optionally, the driving data corresponding to the driving scenario type is collected in the following manner: obtaining the collected data corresponding to the driving scenario type; the collected data includes at least one driving parameter; obtaining the target parameter corresponding to the driving scenario type among the driving parameters; when the target parameter meets the stable trigger condition corresponding to the driving scenario type, determining each driving parameter and the parameter value corresponding to each driving parameter as the driving data corresponding to the driving scenario type.

[0059] Among them, the collected data can be used to describe the data collected in real time during the operation of the vehicle. The target parameter can be used to describe the driving parameter that needs to be monitored for warning corresponding to the driving scenario type. The stable trigger condition can be used to describe the condition for collecting the parameter value.

[0060] Specifically, acquisition data corresponding to the driving scenario type is obtained; the acquisition data includes at least one driving parameter. The target parameter corresponding to the driving scenario type in each driving parameter is obtained, and the obtaining method can be to find it from the corresponding relationship between the preset driving scenario type and the target parameter. The stable trigger conditions for the target parameters corresponding to the preset driving scenario type can be set. The stable trigger conditions for different target parameters are different. For example, when the target parameter is the driving speed, the stable parameter condition is that the driving speed remains unchanged for 5 seconds; when the target parameter is the radar sensing distance, the stable parameter condition is that the radar sensing distance can be detected. When it is detected that the target parameter meets the stable trigger condition corresponding to the driving scenario type, it indicates that the parameter values corresponding to the target parameter are in a stable state and remain within a relatively constant range. Then, the parameter values corresponding to the target parameter can be collected, and each driving parameter and the parameter values corresponding to each driving parameter are determined as the driving data corresponding to the driving scenario type, avoiding the problem that the parameter values of the target parameter collected when the vehicle is driving unstably are inaccurate.

[0061] By obtaining the acquisition data corresponding to the driving scenario type; the acquisition data includes at least one driving parameter; obtaining the target parameter corresponding to the driving scenario type in each driving parameter; when the target parameter meets the stable trigger condition corresponding to the driving scenario type, determining each driving parameter and the parameter values corresponding to each driving parameter as the driving data corresponding to the driving scenario type, and only collecting the parameter values corresponding to the target parameter when the stable trigger condition is met, reducing the amount of collected data and improving the acquisition efficiency. And collecting data in a stable state improves the accuracy of the parameter values corresponding to the target parameter.

[0062] Optionally, the driving scenario type is an environment recognition type; the driving parameters include the relative distance and the throttle opening; from the driving data corresponding to the driving scenario type, the parameter extreme values of at least one driving parameter are statistically calculated, including: statistically calculating the parameter values of the relative distance, selecting the minimum value of the relative distance to obtain the distance warning value; statistically calculating the parameter values of the throttle opening, selecting the maximum value of the throttle opening to obtain the opening warning value; determining the scenario warning data according to the relative distance, the throttle opening, the distance warning value, and the opening warning value.

[0063] Among them, the environment recognition type can be used to describe the type that needs to be recognized by the recognition module for the driving environment around the vehicle. The relative distance can be used to describe the relative distance between the object to be recognized recognized by the recognition module and the vehicle. The throttle opening can be used to describe the opening value of the vehicle throttle at the current time.

[0064] Specifically, the driving scenario type is an environmental recognition type; the driving parameters include the relative distance and the throttle opening. At least one object to be recognized can be preset, and the object to be recognized can be an obstacle, a pedestrian, a vehicle, a lane line, etc. For each object to be recognized, the relative distance between the object to be recognized and the vehicle is recognized through the recognition module, the parameter values of the relative distance are statistically analyzed, the minimum value of the relative distance is selected to obtain the distance warning value; the parameter values of the throttle opening are statistically analyzed, the maximum value of the throttle opening is selected to obtain the opening warning value; according to the relative distance, the throttle opening, the distance warning value and the opening warning value, the scenario warning data is determined.

[0065] Since the driving scenario type is an environmental recognition type; the driving parameters include the relative distance and the throttle opening; the parameter values of the relative distance are statistically analyzed, the minimum value of the relative distance is selected to obtain the distance warning value; the parameter values of the throttle opening are statistically analyzed, the maximum value of the throttle opening is selected to obtain the opening warning value; according to the relative distance, the throttle opening, the distance warning value and the opening warning value, the scenario warning data is determined, the minimum value of the relative distance between each object to be recognized around the vehicle and the vehicle and the maximum value of the throttle opening can be obtained as the scenario warning data, ensuring that the relative distance and the throttle opening between the object to be recognized and the vehicle meet the safety requirements, otherwise an alarm is given in time to ensure the safety of the vehicle operation.

[0066] Optionally, the driving scenario type is a reverse type; the driving parameters include the radar sensing distance and the throttle opening; from the driving data corresponding to the driving scenario type, the extreme values of at least one driving parameter are statistically analyzed, including: the parameter values corresponding to the radar sensing distance are statistically analyzed, the minimum value of the radar sensing distance is selected to obtain the radar warning value; the parameter values corresponding to the throttle opening are statistically analyzed, the maximum value of the throttle opening is selected to obtain the opening warning value; according to the radar sensing distance, the throttle opening, the radar warning value and the opening warning value, the scenario warning data is determined.

[0067] Among them, the reverse type can be used to describe the operation type of the vehicle to be driven in reverse. The radar sensing distance can be used to describe the relative distance between the obstacle sensed by the radar installed on the vehicle and the vehicle.

[0068] Specifically, the driving scenario type is a reverse type; the driving parameters include the radar sensing distance and the throttle opening. The parameter values corresponding to the radar sensing distance are statistically analyzed, the minimum value of the radar sensing distance is selected to obtain the radar warning value, the parameter values corresponding to the throttle opening are statistically analyzed, the maximum value of the throttle opening is selected to obtain the opening warning value, that is, according to the driver's operation, judge the minimum distance between the vehicle and the obstacle and the maximum throttle opening when the driver is used to reversing, and determine the radar warning value and the opening warning value. According to the radar sensing distance, the throttle opening, the radar warning value and the opening warning value, the scenario warning data is determined.

[0069] By statistically analyzing the parameter values corresponding to the radar sensing distance, the minimum value of the radar sensing distance is selected to obtain the radar warning value; by statistically analyzing the parameter values corresponding to the throttle opening, the maximum value of the throttle opening is selected to obtain the opening warning value; according to the radar sensing distance, the throttle opening, the radar warning value, and the opening warning value, the scenario warning data is determined. The radar warning value and the opening warning value corresponding to the reverse type can be obtained, and the scenario warning data can be determined, and the scenario warning data that is more in line with the user's driving habits in the reverse type can be obtained, improving the accuracy of obtaining vehicle warning data.

[0070] Optionally, the driving scenario type is the high-speed driving type; the driving parameters include the lane speed limit range and the driving speed; from the driving data corresponding to the driving scenario type, the extreme values of at least one driving parameter are statistically analyzed, including: obtaining the lane speed limit range corresponding to the driving scenario type; statistically analyzing the parameter values of the driving speed, and selecting the maximum value of the driving speed to obtain the speed warning value; according to the lane speed limit range, the driving speed, and the speed warning value, the scenario warning data is determined.

[0071] Among them, the high-speed driving type can be used to describe the operation type of driving a vehicle at high speed. The lane speed limit range can be used to describe the speed limit range of the lane where the current vehicle is located. The driving speed can be used to describe the running speed of the current vehicle. The speed warning value is used to describe the warning threshold of the driving speed.

[0072] Specifically, the driving scenario type is the high-speed driving type, indicating that the running environment of the current vehicle is an environment that requires high-speed driving. The driving parameters include the lane speed limit range and the driving speed. For different lane speed limit ranges, the speeds at which drivers are accustomed to driving are different. Therefore, the lane speed limit range corresponding to the driving scenario type is obtained. Under the current lane speed limit range, the parameter values of the driving speed are statistically analyzed, and the maximum value among the parameter values is selected to determine the maximum driving speed, and the speed warning value is obtained, indicating that under the lane speed limit range, the maximum speed that the driver is accustomed to driving the vehicle to reach is the maximum driving speed. According to the lane speed limit range, the driving speed, and the speed warning value, a corresponding relationship is established to determine the scenario warning data.

[0073] By obtaining the lane speed limit range corresponding to the driving scenario type; statistically analyzing the parameter values of the driving speed, and selecting the maximum value of the driving speed to obtain the speed warning value; according to the lane speed limit range, the driving speed, and the speed warning value, the scenario warning data is determined. The maximum driving speed corresponding to different lane speed limit ranges can be obtained as the scenario warning data, and the scenario warning data that conforms to the driver's driving habits corresponding to the high-speed driving type can be accurately obtained.

[0074] Embodiment III

[0075] Figure 3Schematic diagram of a vehicle warning data acquisition device provided in Embodiment 3 of the present invention. The embodiments of the present invention are applicable to the situation of acquiring vehicle warning data. This device can execute the vehicle warning data acquisition method, and this device can be implemented in the form of hardware and / or software.

[0076] Refer to Figure 3 The vehicle warning data acquisition device shown in the figure includes: a driving data acquisition module 301, a warning data determination module 302, and a warning data update module 303, where

[0077] The driving data acquisition module 301 is configured to acquire the driving data corresponding to the driving scene type when the vehicle warning data corresponding to the driving scene type is empty; the driving data includes: at least one driving parameter and at least one parameter value corresponding to each driving parameter;

[0078] The warning data determination module 302 is configured to determine the scene warning data according to the driving data corresponding to the driving scene type;

[0079] The warning data update module 303 is configured to update the vehicle warning data corresponding to the driving scene type according to the scene warning data and the standard warning data corresponding to the driving scene type.

[0080] The technical solution of the embodiments of the present invention is to acquire the driving data corresponding to the driving scene type when the vehicle warning data corresponding to the driving scene type is empty; the driving data includes: at least one driving parameter and at least one parameter value corresponding to each driving parameter; determine the scene warning data according to the driving data corresponding to the driving scene type; update the vehicle warning data corresponding to the driving scene type according to the scene warning data and the standard warning data corresponding to the driving scene type, and the vehicle warning data can be updated according to the driving data corresponding to the driving scene type, so that the updated vehicle warning data conforms to the user's driving habits and improves the accuracy of vehicle warning data acquisition.

[0081] Optionally, the warning data determination module 302 includes:

[0082] An extreme value statistics unit, configured to statistically calculate the parameter extreme values of at least one driving parameter from the driving data corresponding to the driving scene type;

[0083] An extreme value determination unit, configured to determine the parameter extreme values of each driving parameter as the scene warning data.

[0084] Optionally, the warning data update module 303 is specifically configured to:

[0085] An opening value query sub-unit, configured to query the target signal data with an empty throttle opening value in each road spectrum signal data;

[0086] An opening value calculation sub-unit, which is used to calculate the throttle opening value corresponding to each target signal data according to the engine speed, engine torque and throttle opening formula in the target signal data, and update at least one set of road spectrum signal data;

[0087] A multi-parameter determination sub-unit, which is used to determine the load parameters to be tested, the boundary parameters to be tested and the working condition parameters to be tested of the engine corresponding to the engine type according to each road spectrum signal data. When the scenario alarm data and the standard alarm data are completely different, update the vehicle alarm data according to the standard alarm data;

[0088] When the scenario alarm data and the standard alarm data are not completely the same, update the vehicle alarm data according to the standard alarm data and the scenario alarm data;

[0089] When the data range of the scenario alarm data contains the data range of the standard alarm data, update the vehicle alarm data according to the standard alarm data;

[0090] When the data range of the standard alarm data contains the data range of the scenario alarm data, update the vehicle alarm data according to the scenario alarm data.

[0091] Optionally, the driving data corresponding to the driving scenario type is collected in the following way:

[0092] Obtain the collected data corresponding to the driving scenario type; the collected data includes at least one driving parameter;

[0093] Obtain the target parameter corresponding to the driving scenario type among each driving parameter;

[0094] When the target parameter meets the stable trigger condition corresponding to the driving scenario type, determine each driving parameter and the parameter value corresponding to each driving parameter as the driving data corresponding to the driving scenario type.

[0095] Optionally, the driving scenario type is an environment recognition type; the driving parameters include the relative distance and the throttle opening; the extreme value statistics unit is specifically used for:

[0096] Statistically analyze the parameter values of the relative distance, select the minimum value of the relative distance, and obtain the distance alarm value;

[0097] Statistically analyze the parameter values of the throttle opening, select the maximum value of the throttle opening, and obtain the opening alarm value;

[0098] Determine the scenario alarm data according to the relative distance, the throttle opening, the distance alarm value and the opening alarm value.

[0099] Optionally, the driving scenario type is a reverse type; the driving parameters include the radar sensing distance and the throttle opening; the extreme value statistical unit is specifically configured to:

[0100] Statistically analyze the parameter values corresponding to the radar sensing distance, select the minimum value of the radar sensing distance, and obtain the radar warning value;

[0101] Statistically analyze the parameter values corresponding to the throttle opening, select the maximum value of the throttle opening, and obtain the opening warning value;

[0102] Determine the scenario warning data according to the radar sensing distance, the throttle opening, the radar warning value, and the opening warning value.

[0103] Optionally, the driving scenario type is a high-speed driving type; the driving parameters include the lane speed limit range and the driving speed; the extreme value statistical unit is specifically configured to:

[0104] Obtain the lane speed limit range corresponding to the driving scenario type;

[0105] Statistically analyze the parameter values of the driving speed, select the maximum value of the driving speed, and obtain the speed warning value;

[0106] Determine the scenario warning data according to the lane speed limit range, the driving speed, and the speed warning value.

[0107] The vehicle warning data acquisition device provided by the embodiments of the present invention can execute the vehicle warning data acquisition method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the vehicle warning data acquisition method.

[0108] Embodiment 4

[0109] Figure 4 FIG. shows a schematic structural diagram of a vehicle warning data acquisition device 400 that can be used to implement the embodiments of the present invention.

[0110] As Figure 4 shown, the vehicle warning data acquisition device 400 includes at least one processor 401 and a memory communicatively connected to the at least one processor 401, such as a read-only memory (ROM) 402, a random access memory (RAM) 403, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 401 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 402 or the computer program loaded from the storage unit 408 into the random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the vehicle warning data acquisition device 400 can also be stored. The processor 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.

[0111] Multiple components in the vehicle warning data acquisition device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, an optical disc, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the vehicle warning data acquisition device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0112] The processor 401 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 401 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 401 executes the various methods and processes described above, such as the vehicle warning data acquisition method.

[0113] In some embodiments, the vehicle warning data acquisition method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed onto the vehicle warning data acquisition device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the processor 401, one or more steps of the vehicle warning data acquisition method described above can be executed. Alternatively, in other embodiments, the processor 401 can be configured to execute the vehicle warning data acquisition method by any other suitable means (e.g., by means of firmware).

[0114] The various embodiments of the systems and technologies described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] A computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a vehicle warning data acquisition device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the vehicle warning data acquisition device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0118] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected with each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0119] A computing system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is created by computer programs that run on respective computers and have a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS (Virtual Private Server) services.

[0120] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0121] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for obtaining vehicle warning data, characterized in that, The method includes: When the vehicle warning data corresponding to the driving scenario type is empty, obtaining the driving data corresponding to the driving scenario type; the driving data includes: at least one driving parameter, and at least one parameter value corresponding to each driving parameter; Determining scenario warning data according to the driving data corresponding to the driving scenario type; Updating the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type.

2. The method according to claim 1, wherein The determining scenario warning data according to the driving data corresponding to the driving scenario type includes: Statistically calculating the parameter extreme values of at least one driving parameter from the driving data corresponding to the driving scenario type; Determining the parameter extreme values of each driving parameter as the scenario warning data.

3. The method according to claim 1, characterized in that The updating the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type includes: When the scenario warning data and the standard warning data are completely different, updating the vehicle warning data according to the standard warning data; When the scenario warning data and the standard warning data are not all the same, updating the vehicle warning data according to the standard warning data and the scenario warning data; When the data range of the scenario warning data includes the data range of the standard warning data, updating the vehicle warning data according to the standard warning data; When the data range of the standard warning data includes the data range of the scenario warning data, updating the vehicle warning data according to the scenario warning data.

4. The method according to claim 1, characterized in that, The driving data corresponding to the driving scenario type is collected by the following method: Obtaining the collection data corresponding to the driving scenario type; the collection data includes at least one driving parameter; Obtaining the target parameter corresponding to the driving scenario type among each driving parameter; When the target parameter meets the stable trigger condition corresponding to the driving scenario type, determining each driving parameter and the parameter value corresponding to each driving parameter as the driving data corresponding to the driving scenario type.

5. The method according to claim 2, wherein The driving scenario type is an environment recognition type; the driving parameters include relative distance and throttle opening; The statistically calculating the parameter extreme values of at least one driving parameter from the driving data corresponding to the driving scenario type includes: Statistically calculating the parameter values of the relative distance, selecting the minimum relative distance value, and obtaining the distance warning value; Statistically calculating the parameter values of the throttle opening, selecting the maximum throttle opening value, and obtaining the opening warning value; Determining the scenario warning data according to the relative distance, the throttle opening, the distance warning value, and the opening warning value.

6. The method according to claim 2, wherein The driving scenario type is a reverse type; the driving parameters include radar sensing distance and throttle opening; The statistically calculating the parameter extreme values of at least one driving parameter from the driving data corresponding to the driving scenario type includes: Statistically calculating the parameter values corresponding to the radar sensing distance, selecting the minimum radar sensing distance value, and obtaining the radar warning value; Statistically analyze the parameter values corresponding to the throttle opening, select the maximum throttle opening, and obtain the opening warning value; Determine the scenario warning data based on the radar sensing distance, the throttle opening, the radar warning value, and the opening warning value.

7. The method according to claim 2, characterized in that, The driving scenario type is the high-speed driving type; the driving parameters include the lane speed limit range and the driving speed; From the driving data corresponding to the driving scenario type, statistically analyze the extreme values of at least one driving parameter, including: Obtain the lane speed limit range corresponding to the driving scenario type; Statistically analyze the parameter values of the driving speed, select the maximum driving speed, and obtain the speed warning value; Determine the scenario warning data based on the lane speed limit range, the driving speed, and the speed warning value.

8. A vehicle warning data acquisition device, characterized in that, The device includes: A driving data acquisition module, configured to acquire the driving data corresponding to the driving scenario type when the vehicle warning data corresponding to the driving scenario type is empty; the driving data includes: at least one driving parameter, and at least one parameter value corresponding to each driving parameter; A warning data determination module, configured to determine the scenario warning data according to the driving data corresponding to the driving scenario type; A warning data update module, configured to update the vehicle warning data corresponding to the driving scenario type according to the scenario warning data and the standard warning data corresponding to the driving scenario type.

9. A vehicle warning data acquisition device, characterized in that The vehicle warning data acquisition device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle warning data acquisition method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a processor to execute the vehicle warning data acquisition method according to any one of claims 1-7 when executed.

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