Vehicle data processing method, safety belt control method and vehicle

Abstract

The invention discloses a vehicle data processing method, a safety belt control method and a vehicle. The vehicle data processing method comprises the following steps: acquiring vehicle driving information of a vehicle; and based on the vehicle driving information, determining a data sampling frequency of the running state information of the vehicle, and collecting the running state information according to the data sampling frequency. According to the vehicle data processing method, the data sampling frequency corresponding to the running state information of the vehicle is determined through the vehicle driving information of the vehicle, the running state information of the vehicle is sampled according to different data sampling frequencies, data can be effectively processed in time, the state of the whole vehicle can be accurately judged, and the real-time performance and the response speed of a vehicle system are guaranteed.

Description

Technical Field

[0001] The present application belongs to the field of vehicle technology, and in particular relates to a vehicle data processing method, a seat belt control method and a vehicle. Background Art

[0002] With the continuous development of electric vehicle technology, vehicle systems integrate a variety of sensors, controllers and actuators to realize intelligent control of vehicle acceleration, braking, steering, suspension and seat belt control functions to improve vehicle handling, safety and comfort.

[0003] For example, the intelligent seat belt system is a seat belt usage system based on the vehicle level. It determines the status of the vehicle by collecting many signals from the sensing end and gives the corresponding actions that the seat belt needs to perform. For example, when radar and external cameras sense and monitor that there is a sudden risk of collision with people or cars around, the vehicle control system such as the Electronic Control Unit (ECU) assesses the risk level and determines whether to trigger the seat belt locking action. When the assessment is high risk, the locking action is triggered to restrict the movement of the belt.

[0004] The vehicle system not only needs to sense and analyze numerous signals, but also needs to output corresponding control states to external devices, and also needs to coordinate the actions of various vehicle systems. The system processing capacity is limited and cannot process data in a timely and effective manner, affecting the real-time and response speed of the vehicle system. Summary of the invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a vehicle data processing method, a seat belt control method and a vehicle, which can process data in a timely and effective manner to ensure the real-time performance and response speed of the vehicle system.

[0006] In a first aspect, the present application provides a vehicle data processing method, the method comprising:

[0007] Obtaining vehicle driving information of the vehicle;

[0008] Based on the vehicle driving information, a data sampling frequency of the vehicle's operating status information is determined, and the operating status information is collected according to the data sampling frequency.

[0009] According to the vehicle data processing method of the present application, the data sampling frequency corresponding to the vehicle's operating status information is determined through the vehicle driving information. By sampling the vehicle's operating status information according to different data sampling frequencies, the data can be processed in a timely and effective manner, the status of the entire vehicle can be accurately judged, and the real-time and response speed of the vehicle system can be ensured.

[0010] According to one embodiment of the present application, the operating status information includes at least one of driving speed information, vehicle gear information, vehicle body posture information and driving environment information.

[0011] According to an embodiment of the present application, the vehicle driving information includes driving mode information, the running state information includes driving speed information, and determining the data sampling frequency of the running state information of the vehicle based on the vehicle driving information includes:

[0012] determining an upper limit of a driving speed of the vehicle based on the driving mode information;

[0013] The data sampling frequency of the driving speed information is determined based on an upper limit of the driving speed of the vehicle.

[0014] According to an embodiment of the present application, determining the data sampling frequency of the driving speed information based on the driving speed upper limit includes:

[0015] In the case where it is determined that the upper limit of the driving speed of the vehicle is less than a first speed threshold, determining that the data sampling frequency corresponding to the driving speed information is a first sampling frequency;

[0016] Alternatively, when it is determined that the upper limit of the vehicle's driving speed is greater than or equal to the first speed threshold, the data sampling frequency corresponding to the driving speed information is determined to be a second sampling frequency, and the first sampling frequency is less than the second sampling frequency.

[0017] According to an embodiment of the present application, the vehicle driving information includes driving road condition information, the running state information includes at least one of driving speed information, vehicle body posture information and driving environment information, and determining the data sampling frequency of the running state information of the vehicle based on the vehicle driving information includes:

[0018] Based on the driving road condition information, determining a road scene where the vehicle is traveling;

[0019] Based on the road scene where the vehicle is traveling, the data sampling frequency of at least one of the driving speed information, the vehicle body posture information and the driving environment information is determined.

[0020] According to an embodiment of the present application, determining the data sampling frequency of at least one of the driving speed information, the vehicle body posture information, and the driving environment information based on the road scene where the vehicle is traveling includes:

[0021] In the case where it is determined that the vehicle is traveling on a first road scene, determining that the data sampling frequency corresponding to the driving speed information is a third sampling frequency, and determining that the data sampling frequency corresponding to the vehicle body posture information is a fifth sampling frequency;

[0022] Alternatively, when it is determined that the vehicle is traveling on a second road scene, the data sampling frequency corresponding to the driving speed information is determined to be a fourth sampling frequency, and the data sampling frequency corresponding to the vehicle body posture information is determined to be a sixth sampling frequency;

[0023] Among them, the third sampling frequency is greater than the fourth sampling frequency, the fifth sampling frequency is less than the sixth sampling frequency, and the average slope of the first road scene is less than the average slope of the second road scene.

[0024] According to an embodiment of the present application, determining the data sampling frequency of at least one of the driving speed information, the vehicle body posture information, and the driving environment information based on the road scene where the vehicle is traveling includes:

[0025] In a case where it is determined that the vehicle is traveling on a third road scene, determining that the data sampling frequency corresponding to the first state information of the vehicle is a seventh sampling frequency, wherein the first state information includes at least one of the vehicle body posture information and the driving environment information;

[0026] Alternatively, when it is determined that the vehicle is traveling on a fourth road scene, determining that the data sampling frequency corresponding to the first state information is an eighth sampling frequency;

[0027] Among them, the eighth sampling frequency is greater than the seventh sampling frequency, and the road complexity of the fourth road scene is greater than the road complexity of the third road scene.

[0028] According to one embodiment of the present application, the road complexity is determined based on the obstacle information and slope information in the driving road condition information.

[0029] In a second aspect, the present application also provides a seat belt control method, comprising:

[0030] Obtaining vehicle driving information of the vehicle;

[0031] Determine a data sampling frequency of the vehicle's operating status information based on the vehicle's driving information, and collect the operating status information according to the data sampling frequency;

[0032] Based on the operating status information, an operation of a seat belt of the vehicle is controlled.

[0033] According to the seat belt control method of the present application, the data sampling frequency corresponding to the vehicle's operating status information is determined through the vehicle driving information. The vehicle's operating status information is sampled according to different data sampling frequencies, which can timely and effectively process data, accurately judge the status of the entire vehicle, and quickly and accurately control the seat belt action, thereby improving safety and enhancing the wearing experience.

[0034] According to an embodiment of the present application, after obtaining the vehicle driving information of the vehicle, the method further includes:

[0035] Determining a control response speed of the vehicle based on the vehicle driving information;

[0036] The controlling the seat belt operation of the vehicle based on the operating status information includes:

[0037] Based on the operation status information, the seat belt operation is controlled according to the control response speed.

[0038] According to an embodiment of the present application, controlling the seat belt action of the vehicle based on the operating status information includes:

[0039] When the running state information satisfies a first action triggering condition, controlling the seat belt to perform a first action and acquiring the running state information;

[0040] When the running status information satisfies a second action triggering condition, the seat belt is controlled to switch from executing the first action to executing the second action, and the priority of the second action is greater than the priority of the first action.

[0041] According to an embodiment of the present application, the seat belt includes a mechanical vehicle sensing mechanism and an electronic vehicle sensing mechanism, and controlling the seat belt action of the vehicle based on the operating state information includes:

[0042] When the operating state information satisfies the locking triggering condition, controlling the electronic vehicle sensing mechanism of the seat belt to perform a locking action;

[0043] Alternatively, when the operating state information does not satisfy the locking triggering condition, the mechanical vehicle sensing mechanism of the seat belt is inhibited from performing an action.

[0044] In a third aspect, the present application provides a vehicle data processing device, the device comprising:

[0045] A first acquisition module, used to acquire vehicle driving information of a vehicle;

[0046] The second processing module is used to determine the data sampling frequency of the vehicle's operating status information based on the vehicle driving information, and collect the operating status information according to the data sampling frequency.

[0047] In a fourth aspect, the present application provides a seat belt control device, the device comprising:

[0048] A second acquisition module is used to acquire vehicle driving information of the vehicle;

[0049] A second processing module, configured to determine a data sampling frequency of the running status information of the vehicle based on the vehicle driving information, and collect the running status information according to the data sampling frequency;

[0050] A control module is used to control the seat belt action of the vehicle based on the operating status information.

[0051] In a fifth aspect, the present application provides a vehicle, comprising:

[0052] A sensor system, the sensor system is used to collect operating status information of the vehicle;

[0053] As described in the third aspect above, the vehicle data processing device is connected to the sensor system.

[0054] In a sixth aspect, the present application further provides a vehicle, comprising:

[0055] A sensor system and a seat belt, wherein the sensor system is used to collect operating status information of the vehicle;

[0056] As for the seat belt control device described in the fourth aspect above, the control device is connected to the sensor system and the seat belt.

[0057] According to one embodiment of the present application, the seat belt includes a mechanical vehicle sensing mechanism and an electronic vehicle sensing mechanism.

[0058] In the seventh aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the vehicle data processing method as described in the first aspect or the seat belt control method as described in the second aspect is implemented.

[0059] In an eighth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the vehicle data processing method described in the first aspect or the seat belt control method described in the second aspect is implemented.

[0060] In a ninth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the vehicle data processing method described in the first aspect or the seat belt control method described in the second aspect.

[0061] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0063] Figure 1 is a flow chart of a vehicle data processing method provided in an embodiment of the present application;

[0064] Figure 2 It is one of the flow charts of the seat belt control method provided in the embodiment of the present application;

[0065] Figure 3 is a system schematic diagram of a vehicle provided in an embodiment of the present application;

[0066] Figure 4 This is a second flow chart of the seat belt control method provided in the embodiment of the present application;

[0067] Figure 5 This is a third flow chart of the seat belt control method provided in the embodiment of the present application;

[0068] Figure 6 This is a fourth flow chart of the seat belt control method provided in an embodiment of the present application;

[0069] Figure 7 It is one of the structural schematic diagrams of the safety belt provided in the embodiment of the present application;

[0070] Figure 8 This is the second structural schematic diagram of the safety belt provided in the embodiment of the present application;

[0071] Fig. 9 This is the third structural schematic diagram of the safety belt provided in the embodiment of the present application;

[0072] Fig.10 is a structural schematic diagram of a vehicle data processing device provided in an embodiment of the present application;

[0073] Fig.11 is a schematic structural diagram of a seat belt control device provided in an embodiment of the present application;

[0074] Fig.12It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0075] Reference numerals:

[0076] Ratchet tooth portion 604 , rocker rod 605 , valve core 606 , first relay 607 , steel ball 609 , vehicle-sensing follow-up claw 610 , second relay 611 , locking lever 612 . DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0078] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0079] In the following, in conjunction with the accompanying drawings, the vehicle data processing method, the seat belt control method, the vehicle data processing device, the seat belt control device, the vehicle, the electronic device and the readable storage medium provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0080] Among them, the vehicle data processing method can be applied to a vehicle, and can be specifically executed by hardware or software in the vehicle.

[0081] like Figure 3 As shown in the figure, the vehicle system can be divided into a perception layer, a control layer and an execution layer. The perception layer can collect numerous signals from the vehicle's domain controller, electronic stability program (ESP), advanced driver assistance system (ADAS), radar, body posture and other perception terminals.

[0082] The Electronic Control Unit (ECU) of the control layer can analyze the numerous signals of the perception layer, determine the status of the vehicle, and give corresponding actions that need to be performed in the execution layer.

[0083] In actual implementation, the control layer may include a power module, an information analysis module, a self-protection module, a status monitoring module, a drive module, an event recording module, etc. The control layer can not only monitor and analyze various signals, but also output corresponding status to devices such as seat belts, coordinate the actions of various systems on the vehicle, and make corresponding records.

[0084] like Figure 1 As shown, the vehicle data processing method includes: step 110 and step 120.

[0085] Step 110: Obtain vehicle driving information of the vehicle.

[0086] Among them, vehicle driving information is information that characterizes the current driving state of the vehicle and can be obtained through the vehicle's perception layer.

[0087] In this embodiment, the vehicle driving information includes at least one of driving mode information and driving road condition information. The vehicle driving mode information may be the current driving mode of the vehicle, and the vehicle driving road condition information may be the current road condition type of the vehicle.

[0088] In actual implementation, the vehicle's driving modes include but are not limited to sports mode, economy mode, standard mode, off-road mode, low-speed off-road mode and snow mode. Each driving mode has unique characteristics and applicable scenarios. The vehicle driver can choose different driving modes according to actual needs and road conditions.

[0089] For example, the sports mode is suitable for flat roads with fewer vehicles and wider driving range. After turning on the sports mode, the electronic control unit will increase the engine speed, and the vehicle torque is sufficient to achieve quick starting and stopping.

[0090] For example, the economic mode, also known as the energy-saving mode, is suitable for medium and low speed driving conditions. It reduces unnecessary fuel consumption by reducing the response speed of power output and makes the vehicle speed more stable.

[0091] For example, the off-road mode is suitable for road conditions such as rugged roads and slippery roads. After the off-road mode is activated, the drive system will brake the slipping or idling wheels to improve the vehicle's off-road performance.

[0092] The road condition types that vehicles travel on can be classified according to specific road types, including but not limited to expressways, mountain roads, wading roads, bridges and tunnels, etc., and can also be classified according to the quality of road conditions. Vehicle driving road conditions are diverse and have a great impact on vehicle driving.

[0093] For example, the road surface of a highway is smooth, the traffic volume is large, and the vehicles travel at a faster speed.

[0094] For example, mountain roads are winding and have steep slopes, and the driver's field of vision is easily limited when the vehicle is driving. There may be risks of natural disasters such as falling rocks and landslides. The vehicle travels at a slow speed and needs to remain stable.

[0095] For example, bridges are prone to freezing due to rain and snow, the light in tunnels is dim and the road surface is slippery, so it is necessary to control the vehicle speed and avoid emergency braking and lane changes.

[0096] It is understandable that different vehicles have different driving mode options, and vehicles can switch to different driving modes when driving on different roads.

[0097] In this step, the vehicle's driving mode information may be obtained, the vehicle's driving road condition information may be obtained, or both the vehicle's driving mode information and the vehicle's driving road condition information may be obtained.

[0098] In actual implementation, vehicle driving information such as vehicle driving mode information and road condition information can be obtained through multiple terminals in the vehicle's perception layer.

[0099] Step 120: Based on the vehicle driving information, determine the data sampling frequency of the vehicle's operating status information, and collect the operating status information according to the data sampling frequency.

[0100] Among them, the vehicle's operating status information can be information that can characterize the state of the entire vehicle during the operation of the vehicle, such as vehicle speed, body posture, vehicle gear, surrounding environment and other information. The vehicle's operating status information can be collected through the vehicle's perception layer.

[0101] In this step, the data sampling frequency corresponding to the vehicle's operating status information is analyzed based on the vehicle's driving information, and then the corresponding operating status information is collected according to the data sampling frequency to analyze and obtain the current vehicle status.

[0102] In actual implementation, the data sampling frequency corresponding to the vehicle's operating status information can be analyzed and determined based on the vehicle's driving mode information, or the data sampling frequency corresponding to the vehicle's operating status information can be analyzed and determined based on the vehicle's driving mode information and driving road condition information, or the data sampling frequency corresponding to the vehicle's operating status information can be analyzed and determined based on the vehicle's driving mode information and driving road condition information.

[0103] It can be understood that there can be multiple types of operating status information for a vehicle. When determining the data sampling frequency based on the vehicle's driving information, one type of data sampling frequency for operating status information can be determined, or the data sampling frequencies corresponding to multiple types of operating status information can be determined, and the operating status information can be collected according to their corresponding data sampling frequencies.

[0104] For example, the vehicle's operating status information includes signal A, signal B and signal C. When the vehicle's driving mode is switched to off-road mode, the data sampling frequency of signal A can be increased, while the data sampling frequencies of signal B and signal C can be reduced. This reduces the amount of data in the operating status information while increasing the proportion of important data in the operating status information. The operating status information sampled according to the data sampling frequency can more accurately reflect the status of the entire vehicle.

[0105] It should be noted that the data sampling frequency of the operating status information is determined based on the vehicle driving information of the vehicle. When the vehicle driving information changes, the data sampling frequency of the operating status information can be adjusted accordingly.

[0106] In related technologies, the control system not only needs to sense and analyze numerous signals, but also needs to output corresponding control states to external devices, and also needs to coordinate the actions of various vehicle systems. The system processing capacity is limited and cannot process data in a timely and effective manner, affecting the real-time and response speed of the vehicle system.

[0107] In the embodiment of the present application, the data sampling frequency corresponding to the vehicle's operating status information is analyzed through the vehicle driving information of the vehicle. Under different vehicle driving information, the vehicle's operating status information is sampled according to different data sampling frequencies for analysis and judgment. This can reduce the amount of data in the operating status information and also increase the proportion of important data in the operating status information. The status of the entire vehicle can be accurately judged, and data can be processed in a timely and effective manner to ensure the real-time and response speed of the vehicle system.

[0108] According to the vehicle data processing method provided in the embodiment of the present application, the data sampling frequency corresponding to the vehicle's operating status information is determined through the vehicle driving information. By sampling the vehicle's operating status information according to different data sampling frequencies, the data can be processed in a timely and effective manner, the status of the entire vehicle can be accurately judged, and the real-time and response speed of the vehicle system can be ensured.

[0109] In some embodiments, the operating status information includes at least one of driving speed information, vehicle gear information, vehicle body posture information, and driving environment information.

[0110] The driving speed information includes the current speed, average speed, current acceleration, etc. of the vehicle.

[0111] The vehicle gear information is the current gear of the vehicle, for example, reverse gear, neutral gear, parking gear, and speed gear (different speed gears correspond to different vehicle speeds and power requirements).

[0112] The vehicle body posture information is used to characterize the current position state of the vehicle. The vehicle body posture information may include information such as the tilt angle. The vehicle body posture information may be obtained by sampling the inertial sensors, ranging sensors, etc. on the vehicle.

[0113] The driving environment information is used to characterize the information of the environment in which the vehicle is located. The driving environment information may include obstacle information, slope information, etc. of the environment in which the vehicle is located.

[0114] In this embodiment, the vehicle's operating status information may include a combination of one or more of driving speed information, vehicle gear information, body posture information and driving environment information. When determining the data sampling frequency of the operating status information based on the vehicle's driving information, the data sampling frequency corresponding to one or more of the driving speed information, vehicle gear information, body posture information and driving environment information can be determined, and the status information can be collected according to the corresponding data sampling frequency.

[0115] It should be noted that the types of operating status information to be collected can be adjusted according to the vehicle driving information of the vehicle. When the vehicle driving information changes, some types of operating status information are no longer collected to reduce the amount of data processed.

[0116] For example, at a first moment, the vehicle's operating status information including signal A, signal B and signal C is collected according to the vehicle's driving mode. At a second moment, the vehicle's driving mode is switched, and the vehicle's operating status information including signal A is collected, and signal B and signal C are no longer collected, that is, the data sampling frequency of signal B and signal C is adjusted to 0.

[0117] In some embodiments, the vehicle driving information includes driving mode information, and the running state information includes driving speed information. Step 120, based on the vehicle driving information, determining the data sampling frequency of the vehicle running state information may include:

[0118] Based on the driving pattern information, determine the upper limit of the vehicle's driving speed;

[0119] The data sampling frequency of the driving speed information is determined based on the upper limit of the driving speed of the vehicle.

[0120] In this embodiment, the driving mode information and the upper limit of the vehicle's driving speed have a corresponding relationship, and the upper limit of the vehicle's driving speed may be a maximum speed value that the vehicle can reach in the current driving mode.

[0121] It can be understood that, based on the maximum speed that the vehicle can reach in the current driving mode, it can be determined whether the vehicle is running at a high speed or a low speed.

[0122] When the vehicle runs at high speed, the extreme value of the speed is large, the speed variation range is also large, and the driving speed information has a greater impact on vehicle control. The data sampling frequency of the driving speed information can be increased. When the vehicle runs at low speed, the extreme value of the speed is small, the speed variation range is also small, and the driving speed information has a smaller impact on vehicle control. The data sampling frequency of the driving speed information can be reduced.

[0123] In this embodiment, the upper limit of the driving speed is determined based on the driving mode information of the vehicle, and the driving speed of the vehicle is judged. According to the different driving speed conditions of the vehicle, different data sampling frequencies are set for the driving speed information of the vehicle to ensure the real-time performance and response speed of the vehicle system.

[0124] In some embodiments, determining the data sampling frequency of the driving speed information based on the upper limit of the driving speed of the vehicle may include:

[0125] When it is determined that the upper limit of the vehicle's driving speed is less than the first speed threshold, determining that the data sampling frequency corresponding to the vehicle's driving speed information is the first sampling frequency;

[0126] Alternatively, when it is determined that the upper limit of the vehicle's driving speed is greater than or equal to the first speed threshold, the data sampling frequency corresponding to the driving speed information is determined to be the second sampling frequency, and the first sampling frequency is less than the second sampling frequency.

[0127] The first speed threshold is a preset critical value of the driving speed, and different vehicles may correspond to different first speed thresholds.

[0128] When the upper limit of the driving speed corresponding to the driving mode information is less than the first speed threshold, the data sampling frequency corresponding to the vehicle's driving speed information is the first sampling frequency; when the upper limit of the driving speed corresponding to the driving mode information is greater than or equal to the first speed threshold, the data sampling frequency corresponding to the vehicle's driving speed information is the second sampling frequency, and the first sampling frequency is less than the second sampling frequency.

[0129] In this embodiment, when it is determined based on the driving mode information that the upper limit of the vehicle's driving speed is less than the first speed threshold, it indicates that the vehicle's current driving mode has a low speed. The data sampling frequency corresponding to the driving speed information in the vehicle's operating status information can be reduced, and the data sampling frequency of other types of information in the vehicle's operating status information can remain unchanged or be appropriately adjusted, thereby reducing the amount of data processed by the vehicle, helping to reduce the judgment time, and achieving rapid control.

[0130] A specific embodiment is described below.

[0131] According to the driving mode information, the vehicle is in a low-speed off-road mode. At this time, the vehicle speed is limited to not exceed a first speed threshold of 40 km / h to provide stronger off-road performance and traction. The data sampling frequency of the driving speed information is the first sampling frequency.

[0132] It is understandable that under this upper speed limit, there are fewer dangerous situations caused by speed. When performing signal perception, the data sampling frequency of driving speed information such as speed and acceleration can be reduced, which helps to reduce the amount of data processed by the ECU, shorten the ECU judgment time, and quickly and accurately control the seat belt action.

[0133] According to the driving mode information, when the vehicle switches to the off-road mode, the vehicle speed is limited to exceed the first speed threshold of 40km / h, and the data sampling frequency of the driving speed information is increased to the second sampling frequency.

[0134] In some embodiments, the vehicle driving information includes driving road condition information, the running state information includes at least one of driving speed information, vehicle body posture information, and driving environment information, and based on the vehicle driving information, determining the data sampling frequency of the vehicle running state information includes:

[0135] Determine the road scene where the vehicle is traveling based on the driving road condition information;

[0136] Based on a road scene on which the vehicle is traveling, a data sampling frequency of at least one of the traveling speed information, the vehicle body posture information, and the traveling environment information is determined.

[0137] In this embodiment, the road scene on which the vehicle is traveling can be determined based on the vehicle's driving road condition information, and the data sampling frequency of the corresponding operating status information can be determined for different road scenes.

[0138] It is understandable that when a vehicle is traveling in different road scenarios, the driving speed information, body posture information and driving environment information have different degrees of influence on vehicle control. According to different road scenarios, the data collection frequency corresponding to the driving speed information, body posture information and driving environment information is set to ensure the real-time and response speed of the vehicle system.

[0139] In some embodiments, determining the data sampling frequency of at least one of the driving speed information, the vehicle body posture information, and the driving environment information based on the road scene of the vehicle may include:

[0140] Based on the determination that the vehicle is traveling on the first road scene, determining that the data sampling frequency corresponding to the vehicle's driving speed information is the third sampling frequency, and determining that the data sampling frequency corresponding to the vehicle's body posture information is the fifth sampling frequency;

[0141] Alternatively, based on the determination that the vehicle is traveling on the second road scene, the data sampling frequency corresponding to the driving speed information is determined to be the fourth sampling frequency, the data sampling frequency corresponding to the vehicle body posture information is determined to be the sixth sampling frequency, the third sampling frequency is greater than the fourth sampling frequency, the fifth sampling frequency is less than the sixth sampling frequency, and the average slope of the first road scene is less than the average slope of the second road scene.

[0142] In this embodiment, the first road scene and the second road scene can be distinguished according to the average road slope in the driving road condition information. The average slope of the first road scene is smaller than the average slope of the second road scene. The first road scene is a gently changing road surface with few inclined roads with large slopes. The second road scene has more inclined roads than the first road scene.

[0143] In actual implementation, a slope threshold corresponding to the average slope can be preset. When the average slope of the road surface in the driving road condition information is less than the slope threshold, it indicates that the vehicle is driving in the first road scene. When the average slope of the road surface in the driving road condition information is greater than or equal to the slope threshold, it indicates that the vehicle is driving in the second road scene.

[0144] When it is determined according to the average road slope in the driving road condition information that the vehicle is driving on the first road scene, the data sampling frequency corresponding to the driving speed information is set to the third sampling frequency, and the data sampling frequency corresponding to the vehicle body posture information is set to the fifth sampling frequency.

[0145] According to the average road slope in the driving road condition information, when it is judged that the vehicle switches from the first road scene to the second road scene, the data sampling frequency corresponding to the driving speed information is reduced, and the data sampling frequency corresponding to the vehicle body posture information is increased. The data sampling frequency corresponding to the driving speed information is set to the fourth sampling frequency, and the data sampling frequency corresponding to the vehicle body posture information is set to the sixth sampling frequency to cope with road conditions with an increase in inclined road surfaces.

[0146] In this embodiment, when it is determined based on the driving road condition information that the vehicle is traveling in the first road scene, it is rare for the vehicle to travel on an inclined road surface with a large slope. Therefore, the data sampling frequency corresponding to the vehicle body posture information such as the vehicle tilt angle can be reduced. At the same time, the vehicle speed may be relatively fast, so the data sampling frequency corresponding to the driving speed information can be increased, thereby reducing the amount of data processed by the vehicle and increasing the data proportion of important perception signals. This allows the seat belt to be quickly and accurately controlled.

[0147] A specific embodiment is described below.

[0148] According to the driving road condition information, the first road scenario of the vehicle driving on a paved highway is judged. There are few inclined roads with a slope exceeding 27 degrees on the paved highway. The data sampling frequency corresponding to the vehicle body posture information such as the vehicle tilt angle can be reduced. At the same time, the speed is fast and there are many vehicles on the paved highway. The data sampling frequency corresponding to the driving speed information such as speed and acceleration is appropriately increased. When danger occurs through analysis of the vehicle's operating status information (for example, the speed exceeds the set threshold), the seat belt locking signal is triggered to control the locking of the seat belt.

[0149] In some embodiments, determining the data sampling frequency of at least one of the driving speed information, the vehicle body posture information, and the driving environment information based on the road scene of the vehicle may include:

[0150] When it is determined that the vehicle is traveling on a third road scene, determining that a data sampling frequency corresponding to first state information of the vehicle is a seventh sampling frequency, wherein the first state information includes at least one of body posture information and driving environment information of the vehicle;

[0151] Alternatively, when it is determined that the vehicle is traveling on the fourth road scene, the data sampling frequency corresponding to the first state information is determined to be the eighth sampling frequency, the eighth sampling frequency is greater than the seventh sampling frequency, and the road complexity of the fourth road scene is greater than the road complexity of the third road scene.

[0152] The first state information includes vehicle body posture information such as the vehicle's tilt angle, and driving environment information such as obstacles in the vehicle's environment.

[0153] In actual implementation, the data collection frequency corresponding to the vehicle body posture information can be adjusted according to different driving road condition information, or the data collection frequency corresponding to the driving environment information can be adjusted, or the data collection frequencies of the vehicle body posture information and the driving environment information can be adjusted simultaneously.

[0154] In this embodiment, the third road scene and the fourth road scene can be distinguished according to the road complexity in the driving road condition information. The road complexity of the fourth road scene is greater than the road complexity of the third road scene. The fourth road scene is a complex road with many obstacles and large slope changes.

[0155] In some embodiments, the road complexity is determined based on obstacle information and slope information in the driving road condition information.

[0156] In actual implementation, thresholds of parameters such as the number of obstacles and the slope change rate can be preset. When the obstacle information and slope information in the driving road condition information exceed the corresponding thresholds, it can be determined that the vehicle is driving on the fourth road scenario.

[0157] When it is determined according to the driving road condition information that the vehicle is driving on the third road scene, the data sampling frequency corresponding to the first state information of the vehicle is set to the seventh sampling frequency.

[0158] According to the driving road condition information, it is judged that when the vehicle switches from the third road scene to the fourth road scene, the number of obstacles increases and the slope change increases. The data sampling frequency of the vehicle's body posture information and driving environment information can be increased, and the data sampling frequency corresponding to the vehicle's first state information can be set to the eighth sampling frequency. The data proportion of important perception signals is increased to cope with complex and changing road conditions, accurately control the action of the seat belt, and improve the safety of the vehicle.

[0159] A specific embodiment is described below.

[0160] For the fourth road scenario with many humps and slopes, the collection frequency of sensors such as radar and tilt angle on the vehicle can be increased, that is, the data sampling frequency of the vehicle's body posture information and driving environment information can be improved to judge the humps and slopes on the road surface. When danger occurs through the analysis of the vehicle's operating status information, the seat belt locking signal is triggered to control the locking of the seat belt and improve vehicle safety.

[0161] It should be noted that the identification of the road scene the vehicle is traveling on can also be determined based on the vehicle's driving mode information. For example, when the vehicle's driving mode is off-road mode, it can also be determined that the vehicle is traveling on a complex road scene, and the data sampling frequency of the vehicle body posture information and driving environment information can be increased.

[0162] The embodiment of the present application also provides a method for controlling a seat belt.

[0163] Among them, the seat belt control method can be applied to vehicles, and can be specifically executed by hardware or software in the vehicle.

[0164] It should be noted that the seat belt control method uses the vehicle's operating status information to control the action of the seat belt, and the vehicle's operating status information can be collected by the above-mentioned vehicle data processing method.

[0165] like Figure 2 As shown, the seat belt control method includes: step 210, step 220 and step 230.

[0166] Step 210: Obtain vehicle driving information of the vehicle.

[0167] Among them, vehicle driving information is information that characterizes the current driving state of the vehicle and can be obtained through the vehicle's perception layer.

[0168] In this embodiment, the vehicle driving information includes at least one of driving mode information and driving road condition information. The vehicle driving mode information may be the current driving mode of the vehicle, and the vehicle driving road condition information may be the current road condition type of the vehicle.

[0169] In actual implementation, the vehicle's driving modes include but are not limited to sports mode, economy mode, standard mode, off-road mode, low-speed off-road mode and snow mode. Each driving mode has unique characteristics and applicable scenarios. The vehicle driver can choose different driving modes according to actual needs and road conditions.

[0170] The road condition types that vehicles travel on can be classified according to specific road types, including but not limited to expressways, mountain roads, wading roads, bridges and tunnels, etc., and can also be classified according to the quality of road conditions. Vehicle driving road conditions are diverse and have a great impact on vehicle driving.

[0171] It is understandable that different vehicles have different driving mode options, and vehicles can switch to different driving modes when driving on different roads.

[0172] In this step, the vehicle's driving mode information may be obtained, the vehicle's driving road condition information may be obtained, or both the vehicle's driving mode information and the vehicle's driving road condition information may be obtained.

[0173] In actual implementation, vehicle driving information such as vehicle driving mode information and road condition information can be obtained through multiple terminals in the vehicle's perception layer.

[0174] Step 220: Based on the vehicle driving information, determine the data sampling frequency of the vehicle's operating status information, and collect the operating status information according to the data sampling frequency.

[0175] Among them, the vehicle's operating status information can be information that can characterize the state of the entire vehicle during the operation of the vehicle, such as vehicle speed, body posture, vehicle gear, surrounding environment and other information. The vehicle's operating status information can be collected through the vehicle's perception layer.

[0176] In this step, the data sampling frequency corresponding to the vehicle's operating status information is analyzed based on the vehicle's driving information, and then the corresponding operating status information is collected according to the data sampling frequency to analyze and obtain the current vehicle status.

[0177] In actual implementation, the data sampling frequency corresponding to the vehicle's operating status information can be analyzed and determined based on the vehicle's driving mode information, or the data sampling frequency corresponding to the vehicle's operating status information can be analyzed and determined based on the vehicle's driving mode information and driving road condition information, or the data sampling frequency corresponding to the vehicle's operating status information can be analyzed and determined based on the vehicle's driving mode information and driving road condition information.

[0178] It can be understood that there can be multiple types of operating status information for a vehicle. When determining the data sampling frequency based on the vehicle's driving information, one type of data sampling frequency for operating status information can be determined, or the data sampling frequencies corresponding to multiple types of operating status information can be determined, and the operating status information can be collected according to their corresponding data sampling frequencies.

[0179] For example, the vehicle's operating status information includes signal A, signal B and signal C. When the vehicle's driving mode is switched to off-road mode, the data sampling frequency of signal A can be increased, while the data sampling frequencies of signal B and signal C can be reduced. This reduces the amount of data in the operating status information while increasing the proportion of important data in the operating status information. The operating status information sampled according to the data sampling frequency can more accurately reflect the status of the entire vehicle.

[0180] It should be noted that the data sampling frequency of the operating status information is determined based on the vehicle driving information of the vehicle. When the vehicle driving information changes, the data sampling frequency of the operating status information can be adjusted accordingly.

[0181] Step 230: Based on the operation status information, control the seat belt operation of the vehicle.

[0182] In this step, the vehicle's operating status information is obtained by sampling at a data sampling frequency, the vehicle's operating status information is analyzed, the vehicle status is determined, and the vehicle's seat belts are controlled to perform corresponding actions.

[0183] For example, the vehicle samples the vehicle's operating status information according to the data sampling frequency through the perception layer. When the radar, external camera and other sensors monitor the presence of people or vehicles around the vehicle and there is a risk of collision, the control layer ECU can assess the risk level as high risk, trigger the locking action, control the vehicle's seat belt locking, ensure the safety of people in the vehicle, and send a message to record the judgment result.

[0184] In related technologies, the control system not only needs to sense and analyze numerous signals, but also needs to output corresponding control states to external devices and coordinate the actions of various vehicle systems. The control system has limited processing capabilities and cannot quickly and accurately control the seat belt actions, which results in low safety and affects the seat belt wearing experience of people on the vehicle.

[0185] In an embodiment of the present application, the data sampling frequency corresponding to the vehicle's operating status information is analyzed through the vehicle's driving information. Under different driving modes and driving conditions, the vehicle's operating status information is sampled according to different data sampling frequencies for analysis and judgment. This can reduce the amount of data in the operating status information and also increase the proportion of important data in the operating status information. The status of the entire vehicle can be accurately judged, and the seat belt action can be quickly and accurately controlled to improve safety and enhance the seat belt wearing experience of people on the vehicle.

[0186] According to the seat belt control method provided in the embodiment of the present application, the data sampling frequency corresponding to the vehicle's operating status information is determined through the vehicle's driving information, the vehicle's operating status information is sampled according to different data sampling frequencies, the data is processed timely and effectively, and the status of the entire vehicle is accurately judged. The seat belt action can be controlled quickly and accurately, thereby improving safety and enhancing the wearing experience.

[0187] In some embodiments, after obtaining the vehicle driving information of the vehicle, the seat belt control method may further include:

[0188] Determine the control response speed of the vehicle based on the vehicle driving information;

[0189] Based on the operating status information, the vehicle's seat belt action is controlled, including:

[0190] Based on the operating status information, the seat belt operation is controlled according to the control response speed.

[0191] In this embodiment, based on the vehicle driving information, the data sampling frequency corresponding to the vehicle's operating status information can be determined, and the control response speed corresponding to the control action can also be determined. The seat belt action is subsequently controlled according to the control response speed, which helps to quickly and accurately control the seat belt action.

[0192] Among them, the control response speed refers to how quickly the vehicle's seat belt and other systems respond to user operations or external commands issued by the control layer.

[0193] In actual implementation, the response speed can be the time interval from the issuance of the action instruction to the actual execution of the corresponding action by the vehicle system. The vehicle's control layer can adjust the specific value of the response speed.

[0194] It should be noted that the data sampling frequency of the operating status information and the control response speed of the vehicle are determined based on the vehicle driving information. When the vehicle driving information changes, the data sampling frequency of the operating status information and the control response speed of the vehicle can be adjusted accordingly.

[0195] For example, based on the driving road condition information, the first road scenario in which the vehicle is driving on a paved highway is judged. There are few inclined roads on paved highways with a slope exceeding 27 degrees. The data sampling frequency corresponding to the vehicle posture information such as the vehicle tilt angle can be reduced, and the data sampling frequency corresponding to the driving speed information such as speed and acceleration can be increased. At the same time, the control response speed of the seat belt system is improved. When danger occurs through analysis of the vehicle's operating status information, the seat belt locking signal is triggered to quickly control the locking of the seat belt.

[0196] For another example, for the fourth road scenario with many humps and slopes, the acquisition frequency of sensors such as radar and tilt angle on the vehicle can be increased, the data sampling frequency of the vehicle's body posture information and driving environment information can be increased, the conditions of humps and slopes on the road surface can be judged, and the control response speed of the seat belt system can be improved. When danger occurs through analysis of the vehicle's operating status information, the seat belt locking signal can be triggered to quickly control the locking of the seat belt.

[0197] It can be understood that the seat belts can be controlled to perform different actions. The seat belts can be controlled to lock, the webbing stops retracting and releasing, and the movement of people is restricted. The seat belts can also be controlled to be unlocked, the webbing can be retracted and released, and the movement of people is not restricted. The passive locking components such as the mechanical vehicle sensing mechanism in the seat belt system can also be controlled to reduce noise.

[0198] In some embodiments, based on the operating status information, controlling the seat belt action of the vehicle includes:

[0199] When the running state information satisfies the first action triggering condition, the seat belt is controlled to execute the first action and the running state information is obtained;

[0200] When the running status information meets the second action triggering condition, the seat belt is controlled to switch from executing the first action to executing the second action.

[0201] In this embodiment, the vehicle's operating status information is obtained. When the operating status information meets the first action trigger condition, the seat belt is controlled to perform the first action. During this process, the operating status information meets the second action trigger condition, and the seat belt is controlled to perform the second action. According to the real-time operating status information, the seat belt is controlled to perform different actions.

[0202] The priority of the second action is greater than the priority of the first action.

[0203] In actual implementation, the priority of seat belt execution actions can be divided according to safety performance requirements. Seat belt locking can protect personnel safety, and the priority of seat belt locking action can be higher than the priority of seat belt free retraction and extension action.

[0204] For example, the second action is a locking action, and the first action is a free retracting action.

[0205] A specific embodiment is described below.

[0206] like Figure 4 As shown, after the vehicle system is powered on, the control layer can carry out the initialization program. The initialization program is the seat belt system matching calibration process. By setting the calibration theoretical origin, information comparison is performed, the deviation between the current state and the calibration theoretical origin is confirmed, the deviation compensation is performed, and the internal parameters are self-adjusted. After completing the initial definition calibration, the corresponding status record is output and the seat belt system enters the standby state.

[0207] After the seat belt system is activated by the trigger signal, it monitors the demand signal in real time. The control layer compares the threshold of the operating status information, performs calculations and judgments, compares the real-time status of the seat belt, and controls the seat belt to perform corresponding actions.

[0208] like Figure 5 As shown, the ECU is first activated and initialized. After the initialization is completed, the seat belt status confirmation will be carried out immediately to confirm the status of each sensing terminal on the vehicle. If the status does not conform to the set status (some sensors have errors and cannot sense signals), the status information will be uploaded to the background, and the most recent system work record will be compared to generate the corresponding information code and included in the system's data stream processing.

[0209] When the set status is met, the vehicle completes the standby confirmation and enters the standby state. In the standby state, the ECU will receive the corresponding operating status information in real time and conduct trigger condition judgment. If the trigger condition is not met, it will cyclically capture and compare. If the trigger condition is met, the corresponding function will be executed, the execution status will be output at the same time, and the trigger trend of high-priority functions will be detected.

[0210] When the corresponding function A is executed, the seat belt is controlled to execute the action corresponding to function A, the execution status is output, and the triggering trend of high-priority functions is detected. When the high-priority function B is executed, the seat belt is controlled to execute the action corresponding to high-priority function B, the execution action record is uploaded, the status parameters are output, the functional status is monitored in real time, the current status is maintained, or the ECU initiates a new round of information capture and comparison trigger.

[0211] In some embodiments, the seat belt includes a mechanical vehicle sensing mechanism and an electronic vehicle sensing mechanism, and based on the operation status information, controls the seat belt action of the vehicle, including:

[0212] When the operating status information meets the locking triggering conditions, the electronic vehicle sensing mechanism of the seat belt is controlled to perform the locking action;

[0213] Alternatively, when the operating status information does not satisfy the locking triggering condition, the mechanical vehicle sensing mechanism of the seat belt is inhibited from taking action.

[0214] Among them, the mechanical vehicle sensing mechanism is a passive vehicle sensing mechanism. When the vehicle speed exceeds a certain threshold or emergency braking occurs, the mechanical structure in the mechanical vehicle sensing mechanism will automatically lock the seat belt without the need for control by the vehicle control layer; the electronic vehicle sensing mechanism is an active vehicle sensing mechanism, which is controlled by the vehicle control layer and performs corresponding actions.

[0215] In this embodiment, the operating status information meets the locking trigger condition, and the electronic vehicle sensing mechanism of the seat belt is controlled to perform the locking action, actively locking the seat belt to prevent the mechanical vehicle sensing mechanism from failing and being unable to lock normally, thereby effectively improving the safety performance of the vehicle.

[0216] In the related technologies, mechanical vehicle sensors are mostly mechanical structures such as vehicle sensor steel balls. When the vehicle is driving normally, the mechanical structures such as vehicle sensor steel balls vibrate and cause abnormal noises, affecting the comfort of people on the vehicle.

[0217] In this embodiment, the operating status information does not meet the locking triggering condition, and the mechanical vehicle sensing mechanism of the seat belt is inhibited from executing an action, which can reduce noise, ensure safety, and improve the comfort of the occupants of the vehicle.

[0218] In this embodiment, when the mechanical vehicle sensing mechanism of the seat belt is inhibited from performing an action, the electronic vehicle sensing mechanism may be in a state of performing a locking action or in a non-locking state.

[0219] A specific embodiment is described below.

[0220] like Figure 6 As shown, the seat belt wearing information is detected. After the seat belt is worn, the vehicle driving mode and driving road condition information are detected in real time.

[0221] According to the driving mode information, the vehicle is in low-speed off-road mode, where the speed is limited to no more than 40km / h to provide stronger off-road performance and traction.

[0222] Under the condition of the upper speed limit, there are fewer dangers caused by speed. When performing signal perception, the frequency of speed signal collection can be reduced, and the frequency of position signal collection (body posture information and driving environment information) can be increased to determine whether the driving status information exceeds the set threshold, control the electronic vehicle sensing mechanism to perform the locking action, or inhibit the mechanical vehicle sensing mechanism of the seat belt from performing the action.

[0223] Based on the driving road condition information, it is judged that the vehicle is driving on a paved highway. There are few inclined roads with a slope exceeding 27 degrees on the paved highway. The frequency of collecting speed signals is increased, and the frequency of collecting position signals is reduced. It is determined whether the driving status information exceeds the set threshold, and the electronic vehicle sensing mechanism is controlled to perform the locking action, or the mechanical vehicle sensing mechanism of the seat belt is inhibited from performing the action.

[0224] For example, Figure 7 As shown, the first relay 607 is energized to attract the valve core 606, and the valve core 606 retracts downward, driving the rocker arm 605 to rotate counterclockwise around the fulcrum, driving the vehicle sensing follow-up claw 610 of the mechanical vehicle sensing mechanism to rotate downward, thereby suppressing the execution of the mechanical vehicle sensing mechanism of the seat belt. The steel ball 609 no longer rotates with the movement of the vehicle, which can reduce noise.

[0225] like Figure 8 As shown, the mechanical vehicle sensing mechanism is inhibited from performing an action, and at the same time, the second relay 611 is energized, the locking lever 612 pops out and engages with the ratchet tooth portion 604, and the electronic vehicle sensing mechanism performs a locking action, thereby achieving the effect of restraining the actions of people on the vehicle.

[0226] In actual execution, when the mechanical vehicle sensing mechanism is not suppressed from performing actions, the mechanical vehicle sensing mechanism is in a decoupled state.

[0227] like Fig. 9 As shown, the first relay 607 is de-energized, the valve core 606 extends upward, driving it to rotate clockwise around the fulcrum and lift up, and the mechanical vehicle sensing mechanism takes effect, sensing the acceleration change through the steel ball 609, pushing the vehicle sensing follow-up claw 610, and locking can be achieved.

[0228] When the seat belt system is powered off or fails, the ECU controls the first relay 607 and the second relay 611 to be powered off at the same time, and the mechanical vehicle sensing mechanism takes effect. At this time, the seat belt can still be locked.

[0229] In this embodiment, by suppressing the action of the mechanical vehicle sensing mechanism, the seat belt can be freely sent and received, which can meet the needs of zero-gravity seat conditions and large-angle adjustment of the seat. At the same time, the vehicle sensing noise is suppressed to improve the comfort of use. The electronic vehicle sensing mechanism can achieve active locking to ensure the safety of people in the car.

[0230] The vehicle data processing method provided in the embodiment of the present application can be executed by a vehicle data processing device. In the embodiment of the present application, the vehicle data processing device provided in the embodiment of the present application is described by taking the vehicle data processing device executing the vehicle data processing method as an example.

[0231] An embodiment of the present application also provides a vehicle data processing device.

[0232] like Fig.10 As shown, the vehicle data processing device includes:

[0233] The first acquisition module 1010 is used to acquire vehicle driving information of the vehicle;

[0234] The first processing module 1020 is used to determine the data sampling frequency of the vehicle's operating status information based on the vehicle's driving information, and collect the operating status information according to the data sampling frequency.

[0235] According to the vehicle data processing device provided in the embodiment of the present application, the data sampling frequency corresponding to the vehicle's operating status information is determined through the vehicle's driving information, and the vehicle's operating status information is sampled according to different data sampling frequencies, so that the data can be processed timely and effectively, the vehicle status can be accurately judged, and the real-time performance and response speed of the vehicle system can be ensured. In some embodiments, the operating status information includes at least one of driving speed information, vehicle gear information, vehicle body posture information, and driving environment information.

[0236] In some embodiments, the vehicle driving information includes driving mode information, and the running state information includes driving speed information. The first processing module 1020 is used to determine the data sampling frequency of the vehicle running state information based on the vehicle driving information, including:

[0237] Based on the driving pattern information, determine the upper limit of the vehicle's driving speed;

[0238] The data sampling frequency of the driving speed information is determined based on the upper limit of the driving speed of the vehicle.

[0239] In some embodiments, the first processing module 1020 is used to determine the data sampling frequency of the driving speed information based on the upper limit of the driving speed of the vehicle, including:

[0240] When it is determined that the upper limit of the vehicle's driving speed is less than the first speed threshold, determining that the data sampling frequency corresponding to the vehicle's driving speed information is the first sampling frequency;

[0241] Alternatively, when it is determined that the upper limit of the vehicle's driving speed is greater than or equal to the first speed threshold, the data sampling frequency corresponding to the driving speed information is determined to be the second sampling frequency, and the first sampling frequency is less than the second sampling frequency.

[0242] In some embodiments, the vehicle driving information includes driving road condition information, and the running state information includes at least one of driving speed information, vehicle body posture information, and driving environment information. The first processing module 1020 is used to determine the data sampling frequency of the vehicle running state information based on the vehicle driving information, including:

[0243] Determine the road scene where the vehicle is traveling based on the driving road condition information;

[0244] Based on a road scene on which the vehicle is traveling, a data sampling frequency of at least one of the traveling speed information, the vehicle body posture information, and the traveling environment information is determined.

[0245] In some embodiments, the first processing module 1020 is used to determine the data sampling frequency of at least one of the driving speed information, the vehicle body posture information and the driving environment information based on the road scene of the vehicle, including:

[0246] When it is determined that the vehicle is traveling on the first road scene, the data sampling frequency corresponding to the driving speed information of the vehicle is determined to be the third sampling frequency, and the data sampling frequency corresponding to the body posture information of the vehicle is determined to be the fifth sampling frequency;

[0247] Alternatively, when it is determined that the vehicle is traveling on the second road scene, the data sampling frequency corresponding to the driving speed information is determined to be the fourth sampling frequency, and the data sampling frequency corresponding to the vehicle body posture information is determined to be the sixth sampling frequency;

[0248] Among them, the third sampling frequency is greater than the fourth sampling frequency, the fifth sampling frequency is less than the sixth sampling frequency, and the average slope of the first road scene is less than the average slope of the second road scene.

[0249] In some embodiments, the first processing module 1020 is used to determine the data sampling frequency of at least one of the driving speed information, the vehicle body posture information and the driving environment information based on the road scene of the vehicle, including:

[0250] When it is determined that the vehicle is traveling on a third road scene, determining that a data sampling frequency corresponding to first state information of the vehicle is a seventh sampling frequency, wherein the first state information includes at least one of body posture information and driving environment information of the vehicle;

[0251] Alternatively, when it is determined that the vehicle is traveling on the fourth road scene, the data sampling frequency corresponding to the first state information is determined to be the eighth sampling frequency;

[0252] Among them, the eighth sampling frequency is greater than the seventh sampling frequency, and the road complexity of the fourth road scene is greater than the road complexity of the third road scene.

[0253] In some embodiments, the road complexity is determined based on obstacle information and slope information in the driving road condition information.

[0254] The vehicle data processing device in the embodiment of the present application may be an electronic device, or a component in an electronic device, such as an integrated circuit or a chip.

[0255] The vehicle data processing device provided in the embodiment of the present application can implement each process implemented in the embodiment of the vehicle data processing method. To avoid repetition, it will not be described again here.

[0256] The seat belt control method provided in the embodiment of the present application can be executed by a seat belt control device. In the embodiment of the present application, the seat belt control device executing the seat belt control method is taken as an example to illustrate the seat belt control device provided in the embodiment of the present application.

[0257] An embodiment of the present application also provides a seat belt control device.

[0258] like Fig.11 As shown, the control device of the seat belt includes:

[0259] The second acquisition module 1110 is used to acquire vehicle driving information of the vehicle;

[0260] A second processing module 1120 is used to determine a data sampling frequency of the running status information of the vehicle based on the vehicle driving information, and collect the running status information according to the data sampling frequency;

[0261] The control module 1130 is used to control the seat belt operation of the vehicle based on the operating status information.

[0262] According to the seat belt control device provided in the embodiment of the present application, the data sampling frequency corresponding to the vehicle's operating status information is determined through the vehicle's driving information, the vehicle's operating status information is sampled according to different data sampling frequencies, the data is processed timely and effectively, and the status of the entire vehicle is accurately judged. The seat belt action can be controlled quickly and accurately, thereby improving safety and enhancing the wearing experience.

[0263] In some embodiments, after obtaining the vehicle driving information of the vehicle, the second processing module 1120 is further used to determine the control response speed of the vehicle based on the vehicle driving information;

[0264] The control module 1130 is used to control the seat belt operation of the vehicle based on the operation status information, including:

[0265] Based on the operating status information, the seat belt operation is controlled according to the control response speed.

[0266] In some embodiments, the control module 1130 is used to control the seat belt operation of the vehicle based on the operating status information, including:

[0267] When the running state information satisfies the first action triggering condition, the seat belt is controlled to execute the first action and the running state information is obtained;

[0268] When the running status information meets the triggering condition of the second action, the seat belt is controlled to switch from executing the first action to executing the second action, and the priority of the second action is greater than the priority of the first action.

[0269] In some embodiments, the seat belt includes a mechanical vehicle sensing mechanism and an electronic vehicle sensing mechanism, and the control module 1130 is used to control the seat belt action of the vehicle based on the operation status information, including:

[0270] When the operating status information meets the locking triggering conditions, the electronic vehicle sensing mechanism of the seat belt is controlled to perform the locking action;

[0271] Alternatively, when the operating status information does not satisfy the locking triggering condition, the mechanical vehicle sensing mechanism of the seat belt is inhibited from taking action.

[0272] The seat belt control device in the embodiment of the present application may be an electronic device, or a component in an electronic device, such as an integrated circuit or a chip.

[0273] The seat belt control device provided in the embodiment of the present application can implement each process implemented in the embodiment of the seat belt control method, and will not be described again here to avoid repetition.

[0274] An embodiment of the present application also provides a vehicle.

[0275] The vehicle comprises: a sensor system and the vehicle data processing device as described above, the sensor system is used to collect the running status information of the vehicle; the vehicle data processing device is connected to the sensor system.

[0276] The vehicle data processing device can determine the data sampling frequency of the vehicle's operating status information based on the vehicle driving information, and control the sensor system to collect the operating status information according to the data sampling frequency.

[0277] In actual implementation, the sensing system can be the perception layer of the vehicle, collecting numerous signals from the vehicle's domain controller, ESP, ADAS radar, body posture and other sensing ends. The control unit can be the ECU, which analyzes the numerous signals from the perception layer, determines the status of the entire vehicle, and gives corresponding actions that need to be executed in the execution layer.

[0278] According to the vehicle provided in the embodiment of the present application, the data sampling frequency corresponding to the vehicle's operating status information is determined through the vehicle's driving information, and the vehicle's operating status information is sampled according to different data sampling frequencies, so that data can be processed timely and effectively, the vehicle status can be accurately determined, and the real-time performance and response speed of the vehicle system can be ensured. The embodiment of the present application also provides a vehicle.

[0279] The vehicle comprises: a sensor system, a seat belt and a control device for the seat belt as described above, the sensor system is used to collect running status information of the vehicle; the control device is connected to the sensor system and the seat belt.

[0280] The control device can obtain the vehicle driving information of the vehicle, determine the data sampling frequency of the vehicle's operating status information based on the vehicle driving information, and control the sensor system to collect the operating status information according to the data sampling frequency, and control the vehicle's seat belt action based on the operating status information.

[0281] In actual implementation, the sensing system can be the perception layer of the vehicle, collecting numerous signals from the vehicle's domain controller, ESP, ADAS radar, body posture and other sensing ends. The control device can be an ECU, which analyzes numerous signals from the perception layer, determines the status of the entire vehicle, and gives corresponding actions that the seat belt needs to perform in the execution layer.

[0282] According to the vehicle provided in the embodiment of the present application, the data sampling frequency corresponding to the running status information of the vehicle is determined through the vehicle driving information of the vehicle, and the running status information of the vehicle is sampled according to different data sampling frequencies.

[0283] It can process data in a timely and effective manner, accurately determine the status of the entire vehicle, and can quickly and accurately control the movement of the seat belts, thereby improving safety and enhancing the wearing experience.

[0284] In some embodiments, the seat belt includes a mechanical vehicle sensing mechanism and an electronic vehicle sensing mechanism.

[0285] Among them, the mechanical vehicle sensing mechanism is a passive vehicle sensing mechanism. When the vehicle speed exceeds a certain threshold or emergency braking occurs, the mechanical structure in the mechanical vehicle sensing mechanism will automatically lock the seat belt without the need for control by the vehicle control layer; the electronic vehicle sensing mechanism is an active vehicle sensing mechanism, which is controlled by the vehicle control layer and performs corresponding actions.

[0286] In this embodiment, the operating status information satisfies the locking trigger condition, and the control device can control the electronic vehicle sensing mechanism of the seat belt to perform the locking action, actively lock the seat belt, and prevent the mechanical vehicle sensing mechanism from failing and being unable to lock normally, thereby effectively improving the safety performance of the vehicle.

[0287] In this embodiment, the operating status information does not meet the locking triggering condition, and the control device can suppress the mechanical vehicle sensing mechanism of the seat belt from executing the action, which can reduce noise, ensure safety, and improve the comfort of the occupants.

[0288] In this embodiment, when the mechanical vehicle sensing mechanism of the seat belt is inhibited from performing an action, the electronic vehicle sensing mechanism may be in a state of performing a locking action or in a non-locking state.

[0289] A specific embodiment is described below.

[0290] For example, Figure 7 As shown, the first relay 607 is energized to attract the valve core 606, and the valve core 606 retracts downward, driving the rocker arm 605 to rotate counterclockwise around the fulcrum, driving the vehicle sensing follow-up claw 610 of the mechanical vehicle sensing mechanism to rotate downward, thereby suppressing the execution of the mechanical vehicle sensing mechanism of the seat belt. The steel ball 609 no longer rotates with the movement of the vehicle, which can reduce noise.

[0291] like Figure 8As shown, the mechanical vehicle sensing mechanism is inhibited from performing an action, and at the same time, the second relay 611 is energized, the locking lever 612 pops out and engages with the ratchet tooth portion 604, and the electronic vehicle sensing mechanism performs a locking action, thereby achieving the effect of restraining the actions of people on the vehicle.

[0292] In actual execution, when the mechanical vehicle sensing mechanism is not suppressed from performing actions, the mechanical vehicle sensing mechanism is in a decoupled state.

[0293] like Fig. 9 As shown, the first relay 607 is powered off, the valve core 606 extends upward, driving it to rotate clockwise around the fulcrum and lift up, the mechanical vehicle sensing mechanism takes effect, and the steel ball 609 senses the acceleration change and pushes the vehicle sensing follow-up claw 610 to achieve locking.

[0294] When the seat belt system is powered off or fails, the ECU controls the first relay 607 and the second relay 611 to be powered off at the same time, and the mechanical vehicle sensing mechanism takes effect. At this time, the seat belt can still be locked.

[0295] In this embodiment, by suppressing the action of the mechanical vehicle sensing mechanism, the seat belt can be freely sent and received, which can meet the needs of zero-gravity seat conditions and large-angle adjustment of the seat. At the same time, the vehicle sensing noise is suppressed to improve the comfort of use. The electronic vehicle sensing mechanism can achieve active locking to ensure the safety of people in the car.

[0296] In some embodiments, Fig.12 As shown, an embodiment of the present application also provides an electronic device 1200, including a processor 1201, a memory 1202, and a computer program stored in the memory 1202 and executable on the processor 1201. When the program is executed by the processor 1201, each process of the above-mentioned vehicle data processing method or seat belt control method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0297] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0298] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned vehicle data processing method or seat belt control method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0299] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0300] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above-mentioned vehicle data processing method or seat belt control method when executed by a processor.

[0301] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0302] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned vehicle data processing method or seat belt control method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0303] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0304] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0305] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0306] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0307] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0308] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A vehicle data processing method, characterized in that: include: Obtaining vehicle driving information of the vehicle; Based on the vehicle driving information, a data sampling frequency of the vehicle's operating status information is determined, and the operating status information is collected according to the data sampling frequency.

2. The vehicle data processing method according to claim 1, characterized in that: The running status information includes at least one of driving speed information, vehicle gear information, vehicle body posture information and driving environment information.

3. The vehicle data processing method according to claim 1, characterized in that: The vehicle driving information includes driving mode information, the running state information includes driving speed information, and determining the data sampling frequency of the running state information of the vehicle based on the vehicle driving information includes: determining an upper limit of a driving speed of the vehicle based on the driving mode information; The data sampling frequency of the driving speed information is determined based on an upper limit of the driving speed of the vehicle.

4. The vehicle data processing method according to claim 3, characterized in that: The step of determining the data sampling frequency of the driving speed information based on the driving speed upper limit includes: In the case where it is determined that the upper limit of the driving speed of the vehicle is less than a first speed threshold, determining that the data sampling frequency corresponding to the driving speed information is a first sampling frequency; Alternatively, when it is determined that the upper limit of the vehicle's driving speed is greater than or equal to the first speed threshold, the data sampling frequency corresponding to the driving speed information is determined to be a second sampling frequency, and the first sampling frequency is less than the second sampling frequency.

5. The vehicle data processing method according to any one of claims 1 to 4, characterized in that: The vehicle driving information includes driving road condition information, the running state information includes at least one of driving speed information, vehicle body posture information and driving environment information, and determining the data sampling frequency of the running state information of the vehicle based on the vehicle driving information includes: Based on the driving road condition information, determining a road scene where the vehicle is traveling; Based on the road scene where the vehicle is traveling, the data sampling frequency of at least one of the driving speed information, the vehicle body posture information and the driving environment information is determined.

6. The vehicle data processing method according to claim 5, characterized in that: The determining, based on the road scene where the vehicle is traveling, the data sampling frequency of at least one of the driving speed information, the vehicle body posture information, and the driving environment information comprises: In the case where it is determined that the vehicle is traveling on a first road scene, determining that the data sampling frequency corresponding to the driving speed information is a third sampling frequency, and determining that the data sampling frequency corresponding to the vehicle body posture information is a fifth sampling frequency; Alternatively, when it is determined that the vehicle is traveling on a second road scene, the data sampling frequency corresponding to the driving speed information is determined to be a fourth sampling frequency, and the data sampling frequency corresponding to the vehicle body posture information is determined to be a sixth sampling frequency; Among them, the third sampling frequency is greater than the fourth sampling frequency, the fifth sampling frequency is less than the sixth sampling frequency, and the average slope of the first road scene is less than the average slope of the second road scene.

7. The vehicle data processing method according to claim 5, characterized in that: The determining, based on the road scene where the vehicle is traveling, the data sampling frequency of at least one of the driving speed information, the vehicle body posture information, and the driving environment information comprises: In a case where it is determined that the vehicle is traveling on a third road scene, determining that the data sampling frequency corresponding to the first state information of the vehicle is a seventh sampling frequency, wherein the first state information includes at least one of the vehicle body posture information and the driving environment information; Alternatively, when it is determined that the vehicle is traveling on a fourth road scene, determining that the data sampling frequency corresponding to the first state information is an eighth sampling frequency; Among them, the eighth sampling frequency is greater than the seventh sampling frequency, and the road complexity of the fourth road scene is greater than the road complexity of the third road scene.

8. The vehicle data processing method according to claim 7, characterized in that: The road complexity is determined based on the obstacle information and slope information in the driving road condition information.

9. A method for controlling a seat belt, characterized in that: include: Obtaining vehicle driving information of the vehicle; Determine a data sampling frequency of the vehicle's operating status information based on the vehicle's driving information, and collect the operating status information according to the data sampling frequency; Based on the operating status information, an operation of a seat belt of the vehicle is controlled.

10. The seat belt control method according to claim 9, characterized in that: After obtaining the vehicle driving information of the vehicle, the method further includes: Determining a control response speed of the vehicle based on the vehicle driving information; The controlling the seat belt operation of the vehicle based on the operating status information includes: Based on the operation status information, the seat belt operation is controlled according to the control response speed.

11. The seat belt control method according to claim 9, characterized in that: The controlling the seat belt operation of the vehicle based on the operating status information includes: When the running state information satisfies a first action triggering condition, controlling the seat belt to perform a first action and acquiring the running state information; When the running status information satisfies a second action triggering condition, the seat belt is controlled to switch from executing the first action to executing the second action, and the priority of the second action is greater than the priority of the first action.

12. The seat belt control method according to any one of claims 9 to 11, characterized in that: The seat belt includes a mechanical vehicle sensing mechanism and an electronic vehicle sensing mechanism, and the control of the seat belt action of the vehicle based on the operation status information includes: When the operating state information satisfies the locking triggering condition, controlling the electronic vehicle sensing mechanism of the seat belt to perform a locking action; Alternatively, when the operating state information does not satisfy the locking triggering condition, the mechanical vehicle sensing mechanism of the seat belt is inhibited from performing an action.

13. A vehicle data processing device, characterized in that: include: A first acquisition module, used to acquire vehicle driving information of a vehicle; The first processing module is used to determine the data sampling frequency of the vehicle's operating status information based on the vehicle driving information, and collect the operating status information according to the data sampling frequency.

14. A seat belt control device, characterized in that: include: A second acquisition module is used to acquire vehicle driving information of the vehicle; A second processing module, configured to determine a data sampling frequency of the running status information of the vehicle based on the vehicle driving information, and collect the running status information according to the data sampling frequency; A control module is used to control the seat belt action of the vehicle based on the operating status information.

15. A vehicle, characterized in that: include: A sensor system, the sensor system is used to collect operating status information of the vehicle; The vehicle data processing device according to claim 13, wherein the vehicle data processing device is connected to the sensor system.

16. A vehicle, characterized in that: include: A sensor system and a seat belt, wherein the sensor system is used to collect operating status information of the vehicle; The seat belt control device according to claim 14, wherein the control device is connected to the sensor system and the seat belt.

17. The vehicle according to claim 16, characterized in that The safety belt includes a mechanical vehicle sensing mechanism and an electronic vehicle sensing mechanism.

18. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the vehicle data processing method according to any one of claims 1 to 8 or the seat belt control method according to any one of claims 9 to 12 is implemented.

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