Method, system and device for generating target safety control strategy of vehicle

Abstract

The invention relates to a method, a system and a device for generating a target safety control strategy of a vehicle. The method comprises the following steps: acquiring vehicle sensing data of a vehicle and driving sensing data of a driver, and identifying a vehicle driving state of the vehicle based on the vehicle sensing data; based on the driving sensing data of the driver, the driver braking intention of the driver is recognized, and based on the vehicle driving state and the driver braking intention, braking consistency information of the vehicle is recognized through a dual-core recognition strategy; and when the braking consistency information of the vehicle does not conform to preset consistency information, a target safety control strategy of the vehicle is generated based on the vehicle driving state and the driver braking intention. By adopting the method, the function safety control effect of the domain centralized architecture can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle electronic and electrical architecture, and in particular to a method, system and device for generating a target safety control strategy for a vehicle. Background Art

[0002] The domain control of automobiles means that in the traditional automobile E / E architecture, each ECU (Electronic Control Unit) is independent of each other and communicates through the bus. The electronic and electrical system of this traditional architecture is divided into multiple functional domains. Each domain is managed by a main control unit and communicates through the domain bus, realizing centralized management within the domain and coordination between domains. One of the key control factors in domain control is the highest functional safety requirement ASIL D (Automotive Safety Integrity Information) for the braking function of the entire vehicle. Among them, ASIL D indicates that when the braking function fails unexpectedly, the harm to people is unacceptable, that is, the strategy to avoid harm to people in the car when the brake fails. Therefore, how to improve the control effect of ASIL D is the current research focus.

[0003] In traditional technology, the control method for ASIL D is to coordinate the control through hardware devices such as the braking logic unit, eBooster and ESC, and the parking brake method, EPB and handbrake. However, in the current domain centralized architecture, the vehicle architecture has only one domain control unit, while the traditional control method requires at least two control units, resulting in poor functional safety control of the domain centralized architecture. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for generating a target safety control strategy for a vehicle in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for generating a target safety control strategy for a vehicle, comprising:

[0006] Acquiring vehicle sensor data of the vehicle and driving sensor data of the driver, and identifying the vehicle driving state of the vehicle based on the vehicle sensor data;

[0007] Based on the driving sensor data of the driver, identifying the driver's braking intention, and based on the vehicle driving state and the driver's braking intention, identifying the braking consistency information of the vehicle through a dual-core recognition strategy;

[0008] When the braking consistency information of the vehicle does not meet the preset consistency information, a target safety control strategy of the vehicle is generated based on the driving state of the vehicle and the braking intention of the driver.

[0009] Optionally, the identifying the driving state of the vehicle based on the vehicle sensor data includes:

[0010] Acquire the engine model of the vehicle and the wheel diameter of the vehicle, and identify the wheel speed change information of the vehicle, the engine cylinder pressure value change information of the vehicle, and the oil pipe pressure value change information of the vehicle based on the vehicle sensor data;

[0011] Calculating theoretical vehicle speed change information of the vehicle based on engine cylinder pressure value change information of the vehicle, oil pipe pressure value change information of the vehicle, and engine model of the vehicle, and calculating wheel speed change information of the vehicle based on wheel speed change information of the vehicle and wheel diameter of the vehicle;

[0012] Based on the theoretical vehicle speed change information of the vehicle and the wheel speed change information of the vehicle, the whole vehicle speed change information of the vehicle is calculated through a vehicle speed equivalent algorithm, and based on the whole vehicle speed change information, the vehicle driving state of the vehicle is identified through a vehicle state identification strategy.

[0013] Optionally, the identifying the driver's braking intention based on the driver's driving sensor data includes:

[0014] Based on the driving sensor data of the driver, identifying the braking change information of the driver and the estimated travel data of the vehicle;

[0015] Based on the braking change information of the driver, the braking state distribution information of the driver is identified through a braking state identification strategy, and based on the estimated travel data of the vehicle and the current vehicle speed data in the vehicle speed change information, the current driving planning data of the vehicle is generated through a travel planning network;

[0016] The driver's braking state distribution information and the current driving plan data of the vehicle are used to identify the driver's driving braking intention through a driving intention recognition network.

[0017] Optionally, the identifying the braking consistency information of the vehicle through a dual-core identification strategy based on the vehicle driving state and the driver's braking intention includes:

[0018] The dual-core recognition strategy is split into a vehicle braking state recognition strategy and a vehicle braking intention recognition strategy, and based on the vehicle driving state and the driver's braking intention, the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle are respectively identified through the vehicle braking state recognition strategy and the vehicle braking intention recognition strategy;

[0019] Based on the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle, the braking consistency information of the vehicle is identified through a preset braking consistency judgment strategy.

[0020] Optionally, generating a target safety control strategy for the vehicle based on the vehicle driving state and the driver's braking intention includes:

[0021] Acquire a vehicle driving state range corresponding to each braking task in a safety control database, and a driver braking intention range corresponding to each braking task;

[0022] Based on the vehicle driving state, identifying a vehicle driving state range to which the vehicle driving state belongs and a driver braking intention range to which the driver braking intention belongs, and determining a target braking task for the vehicle based on the vehicle driving state range to which the vehicle driving state belongs and the driver braking intention range to which the driver braking intention belongs;

[0023] The target braking task of the vehicle is used as the target safety control strategy of the vehicle.

[0024] Optionally, after identifying the braking consistency of the vehicle based on the vehicle driving state and the driver's braking intention through a dual-core recognition strategy, the method further includes:

[0025] When the braking consistency of the vehicle meets the preset consistency, calculating the average of the first vehicle braking abnormality probability and the second vehicle braking abnormality probability to obtain the target vehicle braking abnormality probability of the vehicle;

[0026] In a braking control database, a target braking task corresponding to a target vehicle braking abnormality probability of the vehicle is obtained, and the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle is used as a target safety control strategy of the vehicle.

[0027] In a second aspect, the present application also provides a system for generating a target safety control strategy for a vehicle, comprising:

[0028] The sensor unit is connected to the state recognition unit and the intention recognition unit respectively, and the chassis domain control unit is connected to the state recognition unit and the intention recognition unit respectively;

[0029] The sensor unit is used to obtain vehicle sensor data of the vehicle and driving sensor data of the driver, and transmit the vehicle sensor data to the state recognition unit, and transmit the driving sensor data to the intention recognition unit;

[0030] The state recognition unit is used to, after receiving the vehicle sensing data transmitted by the sensor unit, identify the vehicle driving state of the vehicle based on the vehicle sensing data, and transmit the vehicle driving state to the chassis domain control unit;

[0031] The intention recognition unit is used to recognize the driver's braking intention based on the driver's driving sensor data after receiving the driving sensor data transmitted by the sensor unit, and transmit the driver's braking intention to the chassis domain control unit;

[0032] The chassis domain control unit is configured to, after receiving the vehicle driving state transmitted by the state recognition unit and the driver's braking intention transmitted by the intention recognition unit, identify the braking consistency information of the vehicle through a dual-core recognition strategy based on the vehicle driving state and the driver's braking intention;

[0033] The chassis domain control unit is also used to generate a target safety control strategy for the vehicle based on difference information between the vehicle's driving state and the driver's braking intention when the vehicle's braking consistency information does not conform to preset consistency information, and to instruct the vehicle's braking unit to perform a braking task corresponding to the target safety control strategy based on the vehicle's target safety control strategy.

[0034] In a third aspect, the present application also provides a device for generating a target safety control strategy for a vehicle, comprising:

[0035] An acquisition module, used to acquire vehicle sensor data of the vehicle and driving sensor data of the driver, and identify the vehicle driving state of the vehicle based on the vehicle sensor data;

[0036] an identification module, configured to identify the driver's braking intention based on the driver's driving sensor data, and identify the braking consistency information of the vehicle through a dual-core identification strategy based on the vehicle driving state and the driver's braking intention;

[0037] A generating module is used to generate a target safety control strategy for the vehicle based on the vehicle driving state and the driver's braking intention when the braking consistency information of the vehicle does not meet the preset consistency information.

[0038] Optionally, the acquisition module is specifically used to:

[0039] Acquire the engine model of the vehicle and the wheel diameter of the vehicle, and identify the wheel speed change information of the vehicle, the engine cylinder pressure value change information of the vehicle, and the oil pipe pressure value change information of the vehicle based on the vehicle sensor data;

[0040] Calculating theoretical vehicle speed change information of the vehicle based on engine cylinder pressure value change information of the vehicle, oil pipe pressure value change information of the vehicle, and engine model of the vehicle, and calculating wheel speed change information of the vehicle based on wheel speed change information of the vehicle and wheel diameter of the vehicle;

[0041] Based on the theoretical vehicle speed change information of the vehicle and the wheel speed change information of the vehicle, the whole vehicle speed change information of the vehicle is calculated through a vehicle speed equivalent algorithm, and based on the whole vehicle speed change information, the vehicle driving state of the vehicle is identified through a vehicle state identification strategy.

[0042] Optionally, the identification module is specifically used to:

[0043] Based on the driving sensor data of the driver, identifying the braking change information of the driver and the estimated travel data of the vehicle;

[0044] Based on the braking change information of the driver, the braking state distribution information of the driver is identified through a braking state identification strategy, and based on the estimated travel data of the vehicle and the current vehicle speed data in the vehicle speed change information, the current driving planning data of the vehicle is generated through a travel planning network;

[0045] The driver's braking state distribution information and the current driving plan data of the vehicle are used to identify the driver's driving braking intention through a driving intention recognition network.

[0046] Optionally, the identification module is specifically used to:

[0047] The dual-core recognition strategy is split into a vehicle braking state recognition strategy and a vehicle braking intention recognition strategy, and based on the vehicle driving state and the driver's braking intention, the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle are respectively identified through the vehicle braking state recognition strategy and the vehicle braking intention recognition strategy;

[0048] Based on the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle, the braking consistency information of the vehicle is identified through a preset braking consistency judgment strategy.

[0049] Optionally, the generating module is specifically used for:

[0050] Acquire a vehicle driving state range corresponding to each braking task in a safety control database, and a driver braking intention range corresponding to each braking task;

[0051] Based on the vehicle driving state, identifying a vehicle driving state range to which the vehicle driving state belongs and a driver braking intention range to which the driver braking intention belongs, and determining a target braking task for the vehicle based on the vehicle driving state range to which the vehicle driving state belongs and the driver braking intention range to which the driver braking intention belongs;

[0052] The target braking task of the vehicle is used as the target safety control strategy of the vehicle.

[0053] Optionally, the device further comprises:

[0054] a calculation module, configured to calculate, when the braking consistency of the vehicle meets a preset consistency, an average value between the first vehicle braking abnormality probability and the second vehicle braking abnormality probability, and obtain a target vehicle braking abnormality probability of the vehicle;

[0055] The determination module is used to obtain the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle in the braking control database, and use the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle as the target safety control strategy of the vehicle.

[0056] In a fourth aspect, the present application provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0057] In a fifth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0058] In a sixth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0059] The method, system and device for generating the target safety control strategy of the above-mentioned vehicle obtain the vehicle sensor data of the vehicle and the driving sensor data of the driver, and identify the vehicle driving state of the vehicle based on the vehicle sensor data; identify the driver's braking intention based on the driver's driving sensor data, and identify the braking consistency information of the vehicle based on the vehicle driving state and the driver's braking intention through a dual-core recognition strategy; when the braking consistency information of the vehicle does not meet the preset consistency information, the target safety control strategy of the vehicle is generated based on the vehicle driving state and the driver's braking intention. This scheme uses the data of multiple sensors in the target safety control strategy generation system of the vehicle with only one domain control unit designed for this scheme to perform vehicle driving state recognition and driver braking intention recognition, so as to comprehensively identify the consistency between the driver's braking intention and the vehicle driving state of the vehicle through a dual-core recognition strategy, so as to judge whether there are vehicle functional safety situations such as brake loss of control and abnormal vehicle state, thereby generating the target safety control strategy of the vehicle. The dual-core recognition method can improve the accuracy of identifying the functional safety status of the vehicle. At the same time, through a domain-centralized architecture with a domain-space unit, the vehicle's target safety control strategy can be accurately and efficiently generated, thereby comprehensively improving the functional safety control effect of the domain-centralized architecture. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 A system architecture diagram of a system for generating a target safety control strategy for a vehicle in one embodiment;

[0062] Figure 2 A schematic flow chart of a method for generating a target safety control strategy for a vehicle in one embodiment;

[0063] Figure 3 A schematic diagram of a flow chart of an example of generating a target safety control strategy for a vehicle in one embodiment;

[0064] Figure 4 is a structural block diagram of a device for generating a target safety control strategy for a vehicle in one embodiment;

[0065] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0067] The method for generating the target safety control strategy of a vehicle provided in an embodiment of the present application can be applied to the application environment of the generation system of the target safety control strategy of the vehicle. The system includes a sensor unit, a state recognition unit, an intention recognition unit, and a chassis domain control unit, wherein: the sensor unit is respectively connected to the state recognition unit and the intention recognition unit, and the chassis domain control unit is respectively connected to the state recognition unit and the intention recognition unit. The sensor unit includes a plurality of sensors arranged at different positions of the vehicle, the state recognition unit is an ESC controller, the intention recognition unit is an eBooster controller, and the chassis domain control system includes a SOC (system-on-chip) logic processing subunit and an MCU (Microcontroller Unit) signal conversion and data processing subunit, wherein the system can be a terminal, a server, or a combination of a terminal and a server, and is realized through the interaction between the terminal and the server. Among them, the terminal can be an on-board control computer, which recognizes the vehicle driving state and the driver's braking intention through the data of multiple sensors in the generation system of the target safety control strategy of the vehicle with only one domain control unit designed for this solution, so as to comprehensively identify the consistency between the driver's braking intention and the vehicle's driving state through the dual-core recognition strategy, to determine whether there are vehicle functional safety situations such as brake loss of control and abnormal vehicle state, so as to generate the target safety control strategy of the vehicle. While improving the accuracy of identifying vehicle functional safety situations through the dual-core recognition method, the target safety control strategy of the vehicle is accurately and efficiently generated through the domain centralized architecture of a domain control unit, thereby comprehensively improving the functional safety control effect of the domain centralized architecture.

[0068] In an exemplary embodiment, Figure 2 As shown, a method for generating a target safety control strategy for a vehicle is provided, and the method is applied to Figure 1The generation system of the target safety control strategy of the vehicle in the embodiment is described by taking the terminal as an example, and includes the following steps S101 to S103. Among them:

[0069] Step S101, acquiring vehicle sensor data of the vehicle and driving sensor data of the driver, and identifying the vehicle driving state of the vehicle based on the vehicle sensor data.

[0070] In this embodiment, the terminal collects the sensor data of the vehicle in real time through the master cylinder pressure sensor set in the engine master cylinder of the vehicle, the oil pipe pressure sensor of the engine oil pipe, and the 4 wheel speed sensors of each wheel to obtain the vehicle sensor data of the vehicle. Then, the terminal collects the driving sensor data of the driver through the brake sensor set at the driver's brake pedal and the navigation data acquisition device in the vehicle navigation instrument. Among them, the above sensor data is the data obtained in real time. When executing this step, it is necessary to filter all the sensor data in the time period of the preset time period from the current moment to the present moment to obtain the vehicle sensor data of the vehicle and the driving sensor data of the driver. Then, the terminal identifies the vehicle driving state of the vehicle based on the vehicle sensor data through the ESC controller. Among them, the vehicle driving state represents the current driving state of the vehicle, and the current driving state includes two major categories, which are static state and motion state, and the motion state includes acceleration state, deceleration state, rapid acceleration state, and rapid deceleration state. The stationary state may be a state of the vehicle when the current speed data of the vehicle is lower than 5 km / h, and the moving state may be a state of the vehicle when the current speed data of the vehicle is not lower than 5 km / h. The specific identification process will be described in detail later.

[0071] Step S102, based on the driver's driving sensor data, the driver's braking intention is identified, and based on the vehicle driving state and the driver's braking intention, the vehicle's braking consistency information is identified through a dual-core recognition strategy.

[0072] In this embodiment, the terminal identifies the driver's braking intention based on the driver's driving sensor data, and identifies the braking consistency information of the vehicle through a dual-core recognition strategy based on the vehicle's driving state and the driver's braking intention. Among them, the driver's braking intention includes but is not limited to emergency braking, braking, slow braking, no braking and other braking intentions. Among them, the dual-core recognition strategy is to use the A core and B core in the SOC (system-on-chip) logic processing subunit to respectively identify the vehicle braking abnormality probability obtained through different braking abnormality probability recognition strategies, so as to judge whether the two are consistent. In the case of consistency, it indicates that the braking probability of the vehicle is in the vehicle braking abnormality probability identified by the A core and the B core. In the case of inconsistency, it indicates that there is a recognition error in the A core and the B core. This method can effectively avoid the abnormal elimination situation when there is an abnormality in the single-core recognition, and improve the recognition accuracy of the vehicle's vehicle braking abnormality probability. The specific recognition process will be described in detail later.

[0073] Step S103, when the braking consistency information of the vehicle does not meet the preset consistency information, a target safety control strategy for the vehicle is generated based on the vehicle driving state and the driver's braking intention.

[0074] In this embodiment, when the braking consistency information of the vehicle does not meet the preset consistency information, the terminal generates a target safety control strategy for the vehicle based on the vehicle driving state and the driver's braking intention. The target safety control strategy of the vehicle is the braking task of the vehicle. The specific braking task generation method will be described in detail later.

[0075] Based on the above scheme, the vehicle driving state and the driver's braking intention are identified by using the data of multiple sensors in the target safety control strategy generation system of the vehicle with only one domain control unit designed for this scheme, so as to comprehensively identify the consistency between the driver's braking intention and the vehicle's driving state through the dual-core recognition strategy, to judge whether there are functional safety situations of the vehicle such as brake loss of control and abnormal vehicle state, so as to generate the target safety control strategy of the vehicle. While improving the accuracy of identifying the functional safety situation of the vehicle through the dual-core recognition method, the target safety control strategy of the vehicle is accurately and efficiently generated through the domain centralized architecture of a domain control unit, thereby comprehensively improving the functional safety control effect of the domain centralized architecture.

[0076] Optionally, based on vehicle sensor data, the vehicle's driving state is identified, including: obtaining the vehicle's engine model and the vehicle's wheel diameter, and based on the vehicle sensor data, identifying the vehicle's wheel speed change information, the vehicle's engine cylinder pressure value change information, and the vehicle's oil pipe pressure value change information; calculating the vehicle's theoretical vehicle speed change information based on the vehicle's engine cylinder pressure value change information, the vehicle's oil pipe pressure value change information, and the vehicle's engine model, and calculating the vehicle's wheel speed change information based on the vehicle's wheel speed change information and the vehicle's wheel diameter; calculating the vehicle's entire vehicle speed change information based on the vehicle's theoretical vehicle speed change information and the vehicle's wheel speed change information through a vehicle speed equivalent algorithm, and identifying the vehicle's driving state based on the entire vehicle speed change information through a vehicle state identification strategy.

[0077] In this embodiment, the terminal obtains the engine model and wheel diameter of the vehicle, and identifies the wheel speed change information, engine cylinder pressure value change information, and oil pipe pressure value change information of the vehicle based on the vehicle sensor data. The engine model is used to indicate the mapping relationship between the engine at different engine cylinder pressure values, different oil pipe pressure values ​​and theoretical vehicle speed values, and the wheel diameter is used to calculate the wheel circumference, thereby calculating the wheel speed (i.e., wheel forward speed) of the vehicle based on the wheel speed and wheel circumference of the vehicle. The wheel speed change information includes the speed value of the wheel at different times, the engine cylinder pressure value change information includes the pressure value of the engine cylinder at different times, and the oil pipe pressure value change information includes the pressure value of the oil pipe at different times.

[0078] Then, based on the vehicle's engine cylinder pressure value change information, the vehicle's oil pipe pressure value change information, and the vehicle's engine model, the terminal identifies the vehicle's engine cylinder pressure value change information and the vehicle's oil pipe pressure value change information through the mapping relationship between different engine cylinder pressure values ​​and different oil pipe pressure values ​​and theoretical vehicle speed values, and obtains the theoretical vehicle speed change information of the vehicle at each mapped moment.

[0079] Then, the terminal obtains the wheel speed value of the vehicle at each moment based on the wheel speed change information of the vehicle and multiplies it by the wheel circumference corresponding to the wheel diameter of the vehicle, and uses the wheel speed values ​​at all moments as the wheel speed change information.

[0080] The terminal calculates the vehicle speed change information of the whole vehicle through a vehicle speed equivalent algorithm based on the vehicle's theoretical vehicle speed change information and the vehicle's wheel speed change information. The vehicle speed equivalent algorithm includes a weight parameter of the theoretical vehicle speed and a weight parameter of the wheel speed, and multiplies the theoretical vehicle speed value of the vehicle at each moment based on the weight parameter of the theoretical vehicle speed to obtain a weighted value of the theoretical vehicle speed at each moment, and multiplies the wheel speed value of the vehicle at each moment based on the weight parameter of the wheel speed to obtain a weighted value of the wheel speed at each moment. Finally, the terminal adds up the wheel speed value at each moment and the wheel speed at each moment for summation processing to obtain the whole vehicle speed value at each moment.

[0081] Finally, the terminal identifies the speed change rate, speed change direction, and speed change range of the vehicle based on the vehicle speed change information. The vehicle state recognition strategy includes the speed change rate range, speed change direction, and speed change range of the vehicle corresponding to each vehicle driving state. The terminal determines the vehicle driving state of the vehicle by identifying the speed change range to which the speed change rate of the vehicle belongs, the speed change direction corresponding to the speed change direction of the vehicle, and the speed change range to which the speed change range belongs.

[0082] Based on the above scheme, the vehicle speed change information of the vehicle is identified from multiple angles and in all directions, so as to judge the driving status of the vehicle, thereby improving the recognition accuracy of the vehicle driving status.

[0083] Optionally, based on the driver's driving sensor data, the driver's braking intention is identified, including: based on the driver's driving sensor data, identifying the driver's braking change information and the vehicle's estimated travel data; based on the driver's braking change information, identifying the driver's braking state distribution information through a braking state recognition strategy, and based on the vehicle's estimated travel data, identifying the current vehicle speed data in the vehicle's whole speed change information, and generating the vehicle's current driving planning data through a travel planning network; the driver's driving braking intention is identified through a driving intention recognition network based on the driver's braking state distribution information and the vehicle's current driving planning data.

[0084] In this embodiment, the terminal identifies the driver's braking change information and the vehicle's estimated travel data based on the driver's driving sensor data. The braking change information includes the braking information at each moment, and each braking information includes the vehicle's brake pedal depression amplitude, brake pedal depression rate, and brake pedal depression amplitude variation range. The braking state identification strategy includes the braking state corresponding to each brake pedal depression amplitude range, brake pedal depression rate range, and brake pedal depression amplitude variation range. The terminal identifies the driver's braking state at each moment based on the brake pedal depression amplitude, brake pedal depression rate, and brake pedal depression amplitude variation range at each moment. And each braking state is distributed and sorted according to the time to obtain the driver's braking state distribution information.

[0085] The estimated travel data of the vehicle includes the road travel information of the range in front of the vehicle corresponding to different current vehicle speed data, for example, the range in front of the vehicle corresponding to a speed of 20KM / h is within 30m, the range in front of the vehicle corresponding to a speed of 40KM / h is within 100m, the range in front of the vehicle corresponding to a speed of 80KM / h is within 200m, and the range in front of the vehicle corresponding to a speed of 120KM / h is within 300m. The road travel information includes road data (for example, turning, straight, uphill, downhill without roads, intersections, traffic light intersections, T-junctions, road changes, such as national highways becoming provincial highways, asphalt roads becoming gravel roads, etc.), road obstacle data (for example, vehicles, roadblocks, green belts, pedestrians, non-motorized vehicles, animals), etc.

[0086] The terminal generates the current driving planning data of the vehicle through the trip planning network based on the vehicle's estimated trip data and the current vehicle speed data in the vehicle's whole vehicle speed change information. The current driving planning data is the speed increase and decrease data of the vehicle, such as planning information of emergency braking, braking, slow braking, no braking, etc. The trip planning network is an autonomous network.

[0087] The driver's braking state distribution information and the vehicle's current driving plan data are used to identify the driver's driving braking intention through a driving intention recognition network. The driving braking intention recognition network is based on a long short-term memory (LSTM) network.

[0088] Based on the above solution, the driver's braking intention is identified from multiple angles, thereby improving the accuracy and comprehensiveness of the identification of the driver's braking intention.

[0089] Optionally, based on the vehicle's driving state and the driver's braking intention, the vehicle's braking consistency information is identified through a dual-core identification strategy, including: splitting the dual-core identification strategy into a vehicle braking state identification strategy and a vehicle braking intention identification strategy, and based on the vehicle's driving state and the driver's braking intention, respectively identifying a first vehicle braking abnormality probability and a second vehicle braking abnormality probability of the vehicle through the vehicle braking state identification strategy and the vehicle braking intention identification strategy; based on the vehicle's first vehicle braking abnormality probability and the vehicle's second vehicle braking abnormality probability, identifying the vehicle's braking consistency information through a preset braking consistency judgment strategy.

[0090] In this embodiment, the terminal splits the dual-core identification strategy into a vehicle braking state identification strategy and a vehicle braking intention identification strategy, and based on the vehicle driving state and the driver's braking intention, the terminal identifies the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle through the vehicle braking state identification strategy and the vehicle braking intention identification strategy. Among them, the dual-core identification strategies are the identification strategy corresponding to the A core and the identification strategy corresponding to the B core, respectively. The identification strategy corresponding to the A core is the vehicle braking state identification strategy, and the identification strategy corresponding to the B core is the vehicle braking intention identification strategy. Among them, the vehicle braking state identification strategy uses the vehicle driving state as the main factor for identifying the vehicle braking abnormality probability, and the driver's braking intention is the auxiliary factor for identifying the vehicle braking abnormality probability. The vehicle braking intention identification strategy uses the driver's braking intention as the main factor for identifying the vehicle braking abnormality probability, and the vehicle driving state is the auxiliary factor for identifying the vehicle braking abnormality probability.

[0091] Specifically, the terminal identifies the first initial vehicle braking abnormality probability of the vehicle based on the vehicle braking state identification strategy and the vehicle driving state, and identifies the first braking weight value corresponding to the driver's braking intention based on the vehicle braking state identification strategy. Among them, the vehicle braking state identification strategy corresponds to different vehicle driving state ranges, and different vehicle braking abnormality probabilities. The terminal identifies the vehicle driving state range corresponding to the vehicle driving state, and determines the first braking weight value of the vehicle. The vehicle braking state identification strategy also includes a weight value corresponding to each driver's braking intention. The terminal determines the first braking weight value of the vehicle based on the weight value corresponding to the driver's braking intention of the driver. Finally, the terminal performs weighted processing on the first initial vehicle braking abnormality probability of the vehicle by the first braking weight value corresponding to the driver's braking intention, and obtains the first vehicle braking abnormality probability of the vehicle.

[0092] The terminal identifies the second initial vehicle braking abnormality probability of the vehicle based on the vehicle braking intention recognition strategy and the driver's braking intention, and identifies the second braking weight value corresponding to the vehicle's driving state based on the vehicle braking intention recognition strategy. Finally, the terminal weights the second initial vehicle braking abnormality probability of the vehicle by the second braking weight value corresponding to the driver's braking intention to obtain the second vehicle braking abnormality probability of the vehicle. Among them, the vehicle braking intention strategy includes the vehicle braking abnormality probability corresponding to each driver's braking intention and the braking weight value corresponding to different vehicle driving state ranges. The specific recognition process is the same as the recognition process of identifying the first vehicle braking abnormality probability above. No redundant description is given here.

[0093] Finally, the terminal calculates the deviation value between the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle, and when the deviation value is greater than the deviation value threshold in the preset braking consistency judgment strategy, determines that the braking consistency information of the vehicle is inconsistent. When the deviation value is not greater than the deviation value threshold in the preset braking consistency judgment strategy, determines that the braking consistency information of the vehicle is consistent.

[0094] Based on the above solution, the vehicle's braking consistency information is identified through a dual-core recognition strategy, which improves the recognition accuracy of the vehicle's braking abnormality probability and the recognition fault tolerance rate.

[0095] Optionally, based on the vehicle driving state and the driver's braking intention, a target safety control strategy for the vehicle is generated, including: obtaining the vehicle driving state range corresponding to each braking task in the safety control database, and the driver's braking intention range corresponding to each braking task; based on the vehicle driving state, identifying the vehicle driving state range to which the vehicle driving state belongs, and the driver's braking intention range to which the driver's braking intention belongs, and determining the vehicle's target braking task based on the vehicle driving state range to which the vehicle driving state belongs, and the driver's braking intention range to which the driver's braking intention belongs; using the vehicle's target braking task as the vehicle's target safety control strategy.

[0096] In this embodiment, when the vehicle consistency information is inconsistent, the terminal obtains the vehicle driving state range corresponding to each braking task in the safety control database, and the driver braking intention range corresponding to each braking task. Finally, based on the vehicle driving state, the terminal identifies the vehicle driving state range to which the vehicle driving state belongs, and the driver braking intention range to which the driver braking intention belongs, and determines the target braking task of the vehicle based on the vehicle driving state range to which the vehicle driving state belongs, and the driver braking intention range to which the driver braking intention belongs. The target braking task includes, but is not limited to, emergency braking of the vehicle, slow braking of the vehicle, braking of the vehicle, and braking tasks of the vehicle without braking.

[0097] Finally, the terminal uses the vehicle's target braking task as the vehicle's target safety control strategy.

[0098] Based on the above scheme, when the probability of vehicle braking abnormality cannot be determined by braking consistency, the braking tasks applicable to the vehicle can be queried through the safety control database preset in the terminal, thereby improving the accuracy and comprehensiveness of functional safety control of the vehicle under different situations.

[0099] Optionally, based on the vehicle's driving state and the driver's braking intention, after identifying the vehicle's braking consistency through a dual-core recognition strategy, it also includes: when the vehicle's braking consistency meets the preset consistency, calculating the first vehicle's braking abnormality probability and the average value between the second vehicle's braking abnormality probability to obtain the vehicle's target vehicle braking abnormality probability; in the braking control database, obtaining the target braking task corresponding to the vehicle's target vehicle braking abnormality probability, and using the target braking task corresponding to the vehicle's target vehicle braking abnormality probability as the vehicle's target safety control strategy.

[0100] In this embodiment, when the braking consistency of the vehicle meets the preset consistency, the terminal calculates the average value between the first vehicle braking abnormality probability and the second vehicle braking abnormality probability to obtain the target vehicle braking abnormality probability of the vehicle. Then, the terminal obtains the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle in the braking control database, and uses the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle as the target safety control strategy of the vehicle. Among them, the braking control database includes the target vehicle braking abnormality probability range corresponding to different target braking tasks. Among them, the larger the vehicle braking abnormality probability range, the greater the probability of vehicle braking out of control, and emergency braking is required to ensure the personal safety of vehicle personnel at this time, and the smaller the vehicle braking abnormality probability, the weaker the driver's braking intention at this time, and at this time, the personal safety of vehicle personnel in the vehicle is ensured by not braking or slow braking.

[0101] Based on the above scheme, the braking task of the vehicle is determined through different probability ranges of vehicle braking anomalies, thereby improving the accuracy and comprehensiveness of determining the braking task of the vehicle.

[0102] In an exemplary embodiment, Figure 1As shown, a system for generating a target safety control strategy for a vehicle is provided, the system comprising a sensor unit, a state recognition unit, an intention recognition unit, and a chassis domain control unit, wherein: the sensor unit is connected to the state recognition unit and the intention recognition unit respectively, and the chassis domain control unit is connected to the state recognition unit and the intention recognition unit respectively; the sensor unit is used to obtain vehicle sensor data of the vehicle and driving sensor data of the driver, and transmit the vehicle sensor data to the state recognition unit, and transmit the driving sensor data to the intention recognition unit. The state recognition unit is used to identify the vehicle driving state of the vehicle based on the vehicle sensor data after receiving the vehicle sensor data transmitted by the sensor unit, and transmit the vehicle driving state to the chassis domain control unit. Then, the intention recognition unit is used to identify the driver's braking intention based on the driver's driving sensor data after receiving the driving sensor data transmitted by the sensor unit, and transmit the driver's braking intention to the chassis domain control unit. The chassis domain control unit is used to identify the vehicle's braking consistency information through a dual-core recognition strategy based on the vehicle's driving state and the driver's braking intention after receiving the vehicle's driving state transmitted by the state recognition unit and the driver's braking intention transmitted by the intention recognition unit; the chassis domain control unit is also used to generate a target safety control strategy for the vehicle based on the difference information between the vehicle's driving state and the driver's braking intention when the vehicle's braking consistency information does not conform to the preset consistency information, and instruct the vehicle's braking unit to perform the braking task corresponding to the target safety control strategy based on the vehicle's target safety control strategy.

[0103] Among them, the chassis domain control system includes a SOC logic processing subunit and an MCU signal conversion and data processing subunit. The SOC logic processing subunit has two cores: core A and core B. The two cores are independent and redundant. The input information sources of the two cores are exactly the same, but the input power is controlled by different relays, each with a corresponding storage unit and counter. The purpose of different relays is to ensure that they are not destroyed at the same time due to power supply abnormalities. Different hardware components ensure that the two cores will not cause abnormal working at the same time due to this failure. The MCU signal conversion and data processing subunit has a CAN signal converter, which converts the CAN signal from the outside into an internal signal and gives it to cores A and B. After the two cores are processed by the internal logic, the output signal is given to the verification module in the MCU.

[0104] This application also provides an example of generating a target safety control strategy for a vehicle, such as Figure 3 As shown, the specific processing process includes the following steps:

[0105] Step S301, acquiring vehicle sensor data of the vehicle and driving sensor data of the driver.

[0106] Step S302, obtaining the engine model of the vehicle and the wheel diameter of the vehicle, and identifying the vehicle's wheel speed change information, the vehicle's engine cylinder pressure value change information, and the vehicle's oil pipe pressure value change information based on the vehicle sensor data.

[0107] Step S303, based on the vehicle's engine cylinder pressure value change information, the vehicle's oil pipe pressure value change information, and the vehicle's engine model, calculate the vehicle's theoretical vehicle speed change information, and based on the vehicle's wheel speed change information and the vehicle's wheel diameter, calculate the vehicle's wheel speed change information.

[0108] Step S304, based on the theoretical vehicle speed change information of the vehicle and the wheel speed change information of the vehicle, the vehicle speed change information of the vehicle is calculated through the vehicle speed equivalent algorithm, and based on the vehicle speed change information, the vehicle driving state of the vehicle is identified through the vehicle state identification strategy.

[0109] Step S305, based on the driver's driving sensor data, identifying the driver's braking change information and the vehicle's estimated travel data.

[0110] Step S306, based on the driver's braking change information, the driver's braking state distribution information is identified through a braking state identification strategy, and based on the vehicle's estimated mileage data and the current vehicle speed data in the vehicle's entire vehicle speed change information, the vehicle's current driving planning data is generated through a trip planning network.

[0111] Step S307, the driver's braking state distribution information and the vehicle's current driving plan data are used to identify the driver's driving braking intention through a driving intention recognition network.

[0112] Step S308, splitting the dual-core identification strategy into a vehicle braking state identification strategy and a vehicle braking intention identification strategy, and based on the vehicle driving state and the driver's braking intention, respectively identifying the first vehicle braking abnormality probability and the second vehicle braking abnormality probability of the vehicle through the vehicle braking state identification strategy and the vehicle braking intention identification strategy.

[0113] Step S309, based on the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle, the braking consistency information of the vehicle is identified through a preset braking consistency judgment strategy.

[0114] Step S310, obtaining the vehicle driving state range corresponding to each braking task in the safety control database, and the driver's braking intention range corresponding to each braking task.

[0115] Step S311, based on the vehicle driving state, identifies the vehicle driving state range to which the vehicle driving state belongs and the driver braking intention range to which the driver's braking intention belongs, and determines the vehicle's target braking task based on the vehicle driving state range to which the vehicle driving state belongs and the driver braking intention range to which the driver's braking intention belongs.

[0116] Step S312: taking the target braking task of the vehicle as the target safety control strategy of the vehicle.

[0117] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0118] Based on the same inventive concept, the embodiment of the present application also provides a device for generating a target safety control strategy for a vehicle for implementing the method for generating a target safety control strategy for a vehicle involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the device for generating a target safety control strategy for one or more vehicles provided below can refer to the limitations of the method for generating a target safety control strategy for a vehicle above, and will not be repeated here.

[0119] In an exemplary embodiment, Figure 4 As shown, a device for generating a target safety control strategy for a vehicle is provided, comprising: an acquisition module 410, an identification module 420 and a generation module 430, wherein:

[0120] An acquisition module 410 is used to acquire vehicle sensor data of the vehicle and driving sensor data of the driver, and identify the vehicle driving state of the vehicle based on the vehicle sensor data;

[0121] an identification module 420, configured to identify the driver's braking intention based on the driver's driving sensor data, and identify the braking consistency information of the vehicle through a dual-core identification strategy based on the vehicle driving state and the driver's braking intention;

[0122] The generating module 430 is used to generate a target safety control strategy for the vehicle based on the driving state of the vehicle and the braking intention of the driver when the braking consistency information of the vehicle does not meet the preset consistency information.

[0123] Optionally, the acquisition module 410 is specifically configured to:

[0124] Acquire the engine model of the vehicle and the wheel diameter of the vehicle, and identify the wheel speed change information of the vehicle, the engine cylinder pressure value change information of the vehicle, and the oil pipe pressure value change information of the vehicle based on the vehicle sensor data;

[0125] Calculating theoretical vehicle speed change information of the vehicle based on engine cylinder pressure value change information of the vehicle, oil pipe pressure value change information of the vehicle, and engine model of the vehicle, and calculating wheel speed change information of the vehicle based on wheel speed change information of the vehicle and wheel diameter of the vehicle;

[0126] Based on the theoretical vehicle speed change information of the vehicle and the wheel speed change information of the vehicle, the whole vehicle speed change information of the vehicle is calculated through a vehicle speed equivalent algorithm, and based on the whole vehicle speed change information, the vehicle driving state of the vehicle is identified through a vehicle state identification strategy.

[0127] Optionally, the identification module 420 is specifically configured to:

[0128] Based on the driving sensor data of the driver, identifying the braking change information of the driver and the estimated travel data of the vehicle;

[0129] Based on the braking change information of the driver, the braking state distribution information of the driver is identified through a braking state identification strategy, and based on the estimated travel data of the vehicle and the current vehicle speed data in the vehicle speed change information, the current driving planning data of the vehicle is generated through a travel planning network;

[0130] The driver's braking state distribution information and the current driving plan data of the vehicle are used to identify the driver's driving braking intention through a driving intention recognition network.

[0131] Optionally, the identification module 420 is specifically configured to:

[0132] The dual-core recognition strategy is split into a vehicle braking state recognition strategy and a vehicle braking intention recognition strategy, and based on the vehicle driving state and the driver's braking intention, the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle are respectively identified through the vehicle braking state recognition strategy and the vehicle braking intention recognition strategy;

[0133] Based on the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle, the braking consistency information of the vehicle is identified through a preset braking consistency judgment strategy.

[0134] Optionally, the generating module 430 is specifically configured to:

[0135] Acquire a vehicle driving state range corresponding to each braking task in a safety control database, and a driver braking intention range corresponding to each braking task;

[0136] Based on the vehicle driving state, identifying a vehicle driving state range to which the vehicle driving state belongs and a driver braking intention range to which the driver braking intention belongs, and determining a target braking task for the vehicle based on the vehicle driving state range to which the vehicle driving state belongs and the driver braking intention range to which the driver braking intention belongs;

[0137] The target braking task of the vehicle is used as the target safety control strategy of the vehicle.

[0138] Optionally, the device further comprises:

[0139] a calculation module, configured to calculate, when the braking consistency of the vehicle meets a preset consistency, an average value between the first vehicle braking abnormality probability and the second vehicle braking abnormality probability, and obtain a target vehicle braking abnormality probability of the vehicle;

[0140] The determination module is used to obtain the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle in the braking control database, and use the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle as the target safety control strategy of the vehicle.

[0141] Each module in the above-mentioned device for generating the target safety control strategy of the vehicle can be implemented in whole or in part by software, hardware or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0142] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for generating a target safety control strategy for a vehicle is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0143] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0144] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0145] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0146] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0147] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0148] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0149] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for generating a target safety control strategy for a vehicle, characterized in that: The method comprises: Acquiring vehicle sensor data of the vehicle and driving sensor data of the driver, and identifying the vehicle driving state of the vehicle based on the vehicle sensor data; Based on the driving sensor data of the driver, identifying the driver's braking intention, and based on the vehicle driving state and the driver's braking intention, identifying the braking consistency information of the vehicle through a dual-core recognition strategy; When the braking consistency information of the vehicle does not meet the preset consistency information, a target safety control strategy of the vehicle is generated based on the driving state of the vehicle and the braking intention of the driver.

2. The method according to claim 1, characterized in that The identifying the vehicle driving state of the vehicle based on the vehicle sensor data includes: Acquire the engine model of the vehicle and the wheel diameter of the vehicle, and identify the wheel speed change information of the vehicle, the engine cylinder pressure value change information of the vehicle, and the oil pipe pressure value change information of the vehicle based on the vehicle sensor data; Calculating theoretical vehicle speed change information of the vehicle based on engine cylinder pressure value change information of the vehicle, oil pipe pressure value change information of the vehicle, and engine model of the vehicle, and calculating wheel speed change information of the vehicle based on wheel speed change information of the vehicle and wheel diameter of the vehicle; Based on the theoretical vehicle speed change information of the vehicle and the wheel speed change information of the vehicle, the whole vehicle speed change information of the vehicle is calculated through a vehicle speed equivalent algorithm, and based on the whole vehicle speed change information, the vehicle driving state of the vehicle is identified through a vehicle state identification strategy.

3. The method according to claim 2, characterized in that The identifying the driver's braking intention based on the driver's driving sensor data includes: Based on the driving sensor data of the driver, identifying the braking change information of the driver and the estimated travel data of the vehicle; Based on the braking change information of the driver, the braking state distribution information of the driver is identified through a braking state identification strategy, and based on the estimated travel data of the vehicle and the current vehicle speed data in the vehicle speed change information, the current driving planning data of the vehicle is generated through a travel planning network; The driver's braking state distribution information and the current driving plan data of the vehicle are used to identify the driver's driving braking intention through a driving intention recognition network.

4. The method according to claim 1, characterized in that The identifying the braking consistency information of the vehicle based on the vehicle driving state and the driver's braking intention through a dual-core identification strategy includes: The dual-core recognition strategy is split into a vehicle braking state recognition strategy and a vehicle braking intention recognition strategy, and based on the vehicle driving state and the driver's braking intention, the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle are respectively identified through the vehicle braking state recognition strategy and the vehicle braking intention recognition strategy; Based on the first vehicle braking abnormality probability of the vehicle and the second vehicle braking abnormality probability of the vehicle, the braking consistency information of the vehicle is identified through a preset braking consistency judgment strategy.

5. The method according to claim 4, characterized in that The generating of the target safety control strategy of the vehicle based on the vehicle driving state and the driver's braking intention comprises: Acquire a vehicle driving state range corresponding to each braking task in a safety control database, and a driver braking intention range corresponding to each braking task; Based on the vehicle driving state, identifying a vehicle driving state range to which the vehicle driving state belongs and a driver braking intention range to which the driver braking intention belongs, and determining a target braking task for the vehicle based on the vehicle driving state range to which the vehicle driving state belongs and the driver braking intention range to which the driver braking intention belongs; The target braking task of the vehicle is used as the target safety control strategy of the vehicle.

6. The method according to claim 4, characterized in that After identifying the braking consistency of the vehicle based on the vehicle driving state and the driver's braking intention through a dual-core recognition strategy, the method further includes: When the braking consistency of the vehicle meets the preset consistency, calculating the average of the first vehicle braking abnormality probability and the second vehicle braking abnormality probability to obtain the target vehicle braking abnormality probability of the vehicle; In a braking control database, a target braking task corresponding to a target vehicle braking abnormality probability of the vehicle is obtained, and the target braking task corresponding to the target vehicle braking abnormality probability of the vehicle is used as a target safety control strategy of the vehicle.

7. A system for generating a target safety control strategy for a vehicle, characterized in that: The system includes a sensor unit, a state recognition unit, an intention recognition unit, and a chassis domain control unit, wherein: The sensor unit is connected to the state recognition unit and the intention recognition unit respectively, and the chassis domain control unit is connected to the state recognition unit and the intention recognition unit respectively; The sensor unit is used to obtain vehicle sensor data of the vehicle and driving sensor data of the driver, and transmit the vehicle sensor data to the state recognition unit, and transmit the driving sensor data to the intention recognition unit; The state recognition unit is used to, after receiving the vehicle sensing data transmitted by the sensor unit, identify the vehicle driving state of the vehicle based on the vehicle sensing data, and transmit the vehicle driving state to the chassis domain control unit; The intention recognition unit is used to recognize the driver's braking intention based on the driver's driving sensor data after receiving the driving sensor data transmitted by the sensor unit, and transmit the driver's braking intention to the chassis domain control unit; The chassis domain control unit is configured to, after receiving the vehicle driving state transmitted by the state recognition unit and the driver's braking intention transmitted by the intention recognition unit, identify the braking consistency information of the vehicle through a dual-core recognition strategy based on the vehicle driving state and the driver's braking intention; The chassis domain control unit is also used to generate a target safety control strategy for the vehicle based on difference information between the vehicle's driving state and the driver's braking intention when the vehicle's braking consistency information does not conform to preset consistency information, and to instruct the vehicle's braking unit to perform a braking task corresponding to the target safety control strategy based on the vehicle's target safety control strategy.

8. A device for generating a target safety control strategy for a vehicle, characterized in that: The device comprises: An acquisition module, used to acquire vehicle sensor data of the vehicle and driving sensor data of the driver, and identify the vehicle driving state of the vehicle based on the vehicle sensor data; an identification module, configured to identify the driver's braking intention based on the driver's driving sensor data, and identify the braking consistency information of the vehicle through a dual-core identification strategy based on the vehicle driving state and the driver's braking intention; A generating module is used to generate a target safety control strategy for the vehicle based on the vehicle driving state and the driver's braking intention when the braking consistency information of the vehicle does not meet the preset consistency information.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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