Vehicle control method and device, electronic equipment and vehicle

Abstract

The invention relates to a vehicle control method and device, electronic equipment and a vehicle, and relates to the technical field of vehicle safety, and the vehicle control method comprises the following steps: in response to a detected collision accident of the vehicle, determining the collision severity, the fire probability and the falling-into-water probability corresponding to the vehicle based on real-time operation data of the vehicle; determining a real-time risk value of the vehicle according to the collision severity, the fire probability and the falling-into-water probability; the real-time risk value is used for representing the real-time danger degree of the vehicle after the collision accident. And determining a target risk response strategy according to the real-time risk value, and executing the target risk response strategy. Therefore, after the collision accident of the vehicle occurs, the driving condition of the vehicle is judged according to the real-time operation data, so that the risk response strategy is executed in real time according to the state of the vehicle, the response speed of the vehicle can be increased, and the safety of the vehicle is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle safety technology, specifically to vehicle control methods, devices, electronic equipment, and vehicles. Background Technology

[0002] With the rapid development of the automotive industry and the continuous advancement of intelligent technologies, vehicle safety performance is receiving increasing attention from users. As a common type of accident, how to respond to collisions after they occur to improve vehicle safety is a key technical problem that needs to be solved. Summary of the Invention

[0003] The purpose of this application is to provide a vehicle control method, device, electronic device, and vehicle for responding to a collision accident after a vehicle collision, thereby improving vehicle safety.

[0004] In a first aspect, embodiments of this application provide a vehicle control method, which includes: in response to detecting a vehicle collision, determining the collision severity, fire probability, and water-falling probability of the vehicle based on real-time operating data of the vehicle; determining a real-time risk value of the vehicle based on the collision severity, fire probability, and water-falling probability; the real-time risk value represents the real-time danger level of the vehicle after the collision; determining a target risk response strategy based on the real-time risk value, and executing the target risk response strategy.

[0005] Based on the aforementioned technical features, in the event of a vehicle collision, the severity of the collision, the probability of fire, and the probability of falling into water are determined according to the vehicle's real-time operating data. A real-time risk value for the vehicle is then determined based on these factors. Furthermore, a target risk response strategy is determined and executed based on this real-time risk value. This approach, by assessing the vehicle's driving status based on real-time operating data and executing risk response strategies accordingly, improves vehicle response speed and thus enhances vehicle safety. Additionally, determining the severity of the collision, the probability of fire, and the probability of falling into water based on real-time operating data allows for a comprehensive analysis of vehicle accidents, leading to a more comprehensive assessment of the vehicle's hazard level, a more accurate real-time risk value, and ultimately, a more suitable risk response strategy.

[0006] In one embodiment, determining a target risk response strategy based on a real-time risk value includes: if the real-time risk value exceeds a first risk value, determining the target risk response strategy as a first response strategy; the first response strategy instructs the vehicle to perform a window-breaking operation, a location reporting operation, and a power-off operation. If the real-time risk value does not exceed a second risk value, determining the target risk response strategy as a second response strategy; the second response strategy instructs the vehicle to perform a seatbelt pretensioning operation and activate a safety warning light, the light of which is used to warn surrounding vehicles. If the real-time risk value exceeds the second risk value but does not exceed the first risk value, determining the target risk response strategy as a third response strategy; the third response strategy instructs the vehicle to perform a door unlocking operation, a window opening height adjustment operation not exceeding a preset height threshold, and an emergency call triggering operation.

[0007] Based on the aforementioned technical features, when the real-time risk level is low, seatbelt pretensioning is performed. When the real-time risk level is high, actions such as breaking a window, reporting the location, and powering off are performed. In this way, a risk response strategy matching the real-time risk level is determined, thereby protecting the safety of the vehicle's occupants.

[0008] In one embodiment, before determining the severity of a collision, the vehicle control method includes: determining the probability of a fuel leak based on collision data of the vehicle; and performing a fuel isolation operation based on the probability of a fuel leak and the probability of a fire.

[0009] In one embodiment, a fuel isolation operation is performed based on the probability of oil leakage and the probability of fire, including: shutting off the vehicle's fuel pump and isolating the vehicle's fuel tank when the probability of oil leakage exceeds a preset oil leakage probability threshold and the probability of fire exceeds a preset fire probability threshold; and shutting off the vehicle's fuel system when the probability of oil leakage exceeds the preset oil leakage probability threshold and the probability of fire does not exceed the preset fire probability threshold.

[0010] Based on the aforementioned distinguishing technical features, in situations where the probability of oil leakage and fire is high, the vehicle's fuel pump should be shut off and the fuel tank isolated. This isolates the fuel, preventing the fire from escalating. In situations where the probability of fire and oil leakage is low, shutting off the vehicle's fuel system prevents the fire from spreading, thereby improving vehicle safety.

[0011] Based on the aforementioned distinguishing technical features, fuel isolation is implemented on the vehicle in the event of a potential oil leak or fire, ensuring vehicle safety.

[0012] In one embodiment, the vehicle control method includes: determining the collision probability of the vehicle based on changes in the vehicle's acceleration; and determining that a collision has occurred if the collision probability exceeds a target collision probability threshold; the target collision probability threshold is determined based on environmental data of the vehicle's environment.

[0013] Based on the aforementioned distinguishing technical features, since the data collected by the sensor in different environments may have deviations, different collision probability target thresholds are configured for different environments. In this way, the collision probability target threshold is dynamically adjusted to match the collision probability with the environment, thereby improving the accuracy of collision accident identification.

[0014] In one embodiment, the target collision probability threshold is determined as follows: A weather factor, a mode factor, and a confidence compensation factor for the vehicle are acquired. The weather factor represents the severity of the current weather, the mode factor is determined based on the vehicle's driving mode and represents the severity of the environment in which the vehicle is located, and the confidence compensation factor is determined based on the confidence level of the vehicle's acceleration sensor and represents the confidence level of the acceleration sensor. A correction coefficient is determined based on the weather factor, mode factor, and confidence compensation factor. The initial collision probability threshold is then corrected based on the correction coefficient to obtain the target collision probability threshold.

[0015] Based on the aforementioned distinguishing technical features, the initial collision probability threshold is modified according to weather factors, model factors, and credibility compensation factors, thereby enabling dynamic adjustment of the collision probability to match the environment.

[0016] In one embodiment, the vehicle includes a first acceleration sensor and a second acceleration sensor. The vehicle control method further includes: when the first acceleration sensor is the primary sensor, acquiring a data difference value, an electromagnetic interference value, and a temperature interference value of the first acceleration sensor; the data difference value characterizes the degree of difference between the data collected by the first acceleration sensor and the data collected by the second acceleration sensor; the electromagnetic interference value characterizes the degree of electromagnetic interference experienced by the first acceleration sensor; and the temperature interference value is negatively correlated with the ambient temperature where the first acceleration sensor is located. Based on the data difference value, the electromagnetic interference value, and the temperature interference value, a confidence value of the first acceleration sensor is determined. If the confidence value does not exceed a preset confidence threshold, the second acceleration sensor is switched to be the primary sensor.

[0017] Based on the aforementioned distinguishing technical features, when the reliability of the main sensor is low, the backup sensor is switched to the main sensor to ensure the accuracy of the sensor-collected data.

[0018] In one embodiment, switching the second accelerometer to the main sensor when the confidence value does not exceed a preset confidence threshold includes: switching the second accelerometer to the main sensor when the confidence value is less than the preset confidence threshold and the data difference value exceeds a preset difference value.

[0019] Based on the aforementioned distinguishing technical features, when the reliability of the main sensor is low and the data difference between the two sensors is large, the backup sensor is switched to the main sensor to avoid ineffective switching.

[0020] In one embodiment, the vehicle control method further includes: upon detecting a fire event, acquiring the collision time, fire time, and fire location of the vehicle; the collision time is the moment when the collision signal is first detected, and the fire time is the moment when the fire signal is first detected. The cause of the vehicle fire is determined based on the time interval between the collision time and the fire time, the fire location, and the collision location of the vehicle.

[0021] Based on the aforementioned distinguishing technical characteristics, the time interval between the collision and the ignition, the location of the fire, and the vehicle's collision location, the cause of the vehicle fire can be determined. This allows for the identification of the cause of the fire, facilitating the analysis of vehicle fire accidents.

[0022] Secondly, embodiments of this application provide a vehicle control device, which includes a determination unit and a control unit.

[0023] The determination unit, in response to the detection of a vehicle collision, determines the collision severity, fire probability, and water-fall probability of the vehicle based on real-time vehicle operating data. The determination unit also determines a real-time risk value for the vehicle based on the collision severity, fire probability, and water-fall probability; the real-time risk value represents the real-time danger level of the vehicle after the collision. The determination unit further determines a target risk response strategy based on the real-time risk value. The control unit executes the target risk response strategy.

[0024] Thirdly, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions. The processor is configured to execute instructions to implement the methods described in the first aspect and any possible implementation thereof.

[0025] Fourthly, a vehicle is provided that employs the electronic equipment of the third aspect.

[0026] Fifthly, a computer-readable storage medium is provided, wherein when instructions in the computer-readable storage medium are executed by a processor of a processing device, the processing device is enabled to perform the methods described in the first aspect and any possible embodiments thereof.

[0027] In a sixth aspect, a computer program product is provided, the computer program product including computer instructions that, when executed on a processing device, cause the processing device to perform the method described in the first aspect and any possible implementation thereof.

[0028] It should be noted that the technical effects of any of the implementation methods in aspects two through six can be found in the technical effects of the corresponding implementation methods in aspect one, and will not be repeated here.

[0029] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application will be described below.

[0031] Figure 1 A schematic diagram of the structure of a vehicle provided in an embodiment of this application; Figure 2 This is one of the flowcharts illustrating a vehicle control method provided in an embodiment of this application; Figure 3 This is a second schematic flowchart illustrating a vehicle control method provided in an embodiment of this application. Figure 4 The third schematic flowchart of a vehicle control method provided in this application embodiment; Figure 5 The fourth schematic flowchart of a vehicle control method provided in this application embodiment; Figure 6 Fifth of a flowchart illustrating a vehicle control method provided in this application embodiment; Figure 7 A sixth schematic flowchart illustrating a vehicle control method provided in this application embodiment; Figure 8 This is a schematic diagram of the structure of a vehicle control device provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0032] To enable those skilled in the art to better understand the technical solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0033] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0034] like Figure 1 As shown, this application embodiment provides a vehicle 10, which includes: a plurality of sensors (such as...) Figure 1 As shown, an accelerometer 1, a pressure sensor 2, a water level sensor 3, and a temperature sensor 4 are exemplary (in practical applications, there may be more or fewer sensors) and an electronic device 101. Multiple sensors are communicatively connected to the electronic device 101.

[0035] The aforementioned acceleration sensor 1 is used to collect acceleration data of the vehicle 10 and send the acceleration data to the electronic device 101. Accordingly, the electronic device 101 receives the acceleration data sent by the acceleration sensor 1 and determines the driving state of the vehicle 10 based on the acceleration data.

[0036] The number of acceleration sensors 1 mentioned above can be one or more, and this application embodiment does not limit this.

[0037] For example, vehicle 10 is equipped with two acceleration sensors: a first acceleration sensor and a second acceleration sensor. After vehicle 10 is powered on, the first acceleration sensor is set as the primary acceleration sensor, and the vehicle's driving status is determined based on the data collected by the first acceleration sensor. During vehicle 10's operation, the status of the first acceleration sensor is periodically checked, and if an abnormality is detected in the first acceleration sensor, the second acceleration sensor is switched to the primary acceleration sensor.

[0038] The water level sensor 3 is used to collect water level data from the vehicle 10 and send the water level data to the electronic device 101. Accordingly, the electronic device receives the water level data sent by the water level sensor 3 and determines whether the vehicle 10 has fallen into the water based on the water level data.

[0039] The number of the aforementioned water level sensors 3 can be one or more, and this application embodiment does not limit this.

[0040] For example, to improve the reliability of vehicle 10's water-fall detection, two water level sensors are configured in vehicle 10: a first water level sensor and a second water level sensor. After vehicle 10 is powered on, the first water level sensor is configured as the primary water level sensor, and the second water level sensor is configured as the backup water level sensor.

[0041] The aforementioned pressure sensor 2 is used to collect pressure data experienced by vehicle 10 and send the pressure data to electronic device 101. Correspondingly, electronic device 101 receives the pressure data sent by pressure sensor 2 and determines the severity of the collision experienced by vehicle 10 based on the pressure data.

[0042] The number of pressure sensors 2 can be multiple, thereby detecting collision information at multiple locations of the vehicle 10.

[0043] The pressure sensor 2 described above can be a 64-point pressure sensor matrix, or it can be other types of pressure sensor; this application does not specifically limit the form. The pressure recognition accuracy of the pressure sensor 2 described above can be 0.1N or 0.2N; this application does not specifically limit the form.

[0044] The temperature sensor 4 is used to collect the temperature of the environment in which the vehicle 10 is located and send the temperature of the environment in which the vehicle 10 is located to the electronic device 101. Accordingly, the electronic device 101 receives the temperature of the environment in which the vehicle 10 is located sent by the temperature sensor 4 and identifies the reliability of the vehicle's acceleration sensor 1 based on the temperature of the environment in which the vehicle 10 is located.

[0045] The temperature sensor 4 mentioned above can be an infrared thermal imager or other temperature sensors. This application does not specifically limit the type of sensor.

[0046] This application does not specifically limit the sampling frequency of multiple sensors. For example, the sampling frequency of accelerometer 1 can be 100 Hz, the sampling frequency of pressure sensor 2 can be 10 Hz, the sampling frequency of water level sensor 3 can be 10 Hz, and the sampling frame rate of temperature sensor 4 can be 50 frames / second.

[0047] The aforementioned electronic device 101 is also used for data cleaning and noise reduction of data collected by multiple sensors.

[0048] The specific method for data noise reduction of electronic device 101 in this embodiment is not specifically limited. For example, electronic device 101 filters the data collected by accelerometer 1 using a Kalman filter. Another example is that electronic device 101 performs infrared non-uniformity correction on the data collected by temperature sensor 4.

[0049] The aforementioned electronic device 101 is also used to extract and fuse features from data collected by multiple sensors to obtain data fusion features. Subsequently, the electronic device 101 identifies the state of the vehicle 10 based on the fused data features.

[0050] In some embodiments, the electronic device 101 acquires data from each of a plurality of sensors and extracts features from the data acquired by each sensor to obtain data features from the plurality of sensors. Further, the electronic device 101 determines the current risk type of the vehicle 10 based on the data features from the plurality of sensors, and determines the weight of the data features of each sensor based on the risk type. Subsequently, the electronic device 101 performs weighted fusion of the data features of each sensor according to the weights of the data features of each sensor to obtain data fusion features.

[0051] In this embodiment, the electronic device 101 uses different models to extract features from data collected by different sensors. For example, it uses a third-generation mobile neural network (MobileNetV3) to extract features from data collected by the temperature sensor 4, and uses a bidirectional long short-term memory network (Bi-LSTM) to extract features from data collected by the accelerometer 1.

[0052] In this embodiment, the electronic device 101 is further configured to detect the integrity of the data collected by each sensor, and to repair the data collected by the sensor if missing data is detected. For example, if missing data is detected by the accelerometer 1, a generative adversarial network interpolation (GANI) method is used to repair the data collected by the accelerometer 1 to ensure that the data collected by the accelerometer 1 is complete.

[0053] The aforementioned electronic device 101 is also used to determine the accident risk value of different accidents based on data fusion characteristics. For example, the electronic device 101 identifies the accident risk value of a collision accident as 0.95, the accident risk value of a fire accident as 0, and the accident risk value of a drowning accident as 0.65 based on data fusion characteristics.

[0054] The aforementioned electronic device 101 is also used to determine whether to send an accident based on the accident risk value of each accident and the accident risk target threshold corresponding to each accident. For example, taking a collision accident with an accident risk value of 0.95 and a collision probability target threshold of 0.72 as an example, the electronic device 101 determines that a collision accident has occurred if it detects that the accident risk value is greater than the collision probability target threshold.

[0055] In this embodiment of the application, the accident risk target threshold can be dynamically adjusted by the electronic device 101 based on the driving mode of the vehicle 10 and the environmental data of the vehicle 10.

[0056] The aforementioned electronic device 101 is also used to determine a real-time risk value based on the accident risk value of different accidents, determine a target risk response strategy based on the real-time risk value, and execute the target risk response strategy.

[0057] The aforementioned real-time risk value can be understood as an accident severity index. In this way, electronic device 101 can implement differentiated strategies based on the severity of the accident.

[0058] The aforementioned electronic device 101 can be a cockpit domain controller or a vehicle body domain controller. This application embodiment does not specifically limit the electronic device 101.

[0059] In this embodiment of the application, vehicle 10 may also be referred to as a vehicle, mobile carrier, electric vehicle (EV), hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV), fuel cell vehicle (FCV), autonomous vehicle, intelligent and connected vehicle (ICV), driverless vehicle, etc.

[0060] In this embodiment, vehicle 10 can be a sedan, sport utility vehicle (SUV), truck, electric vehicle, motorcycle, tricycle, special vehicle (such as ambulance, fire truck, police car, etc.), driverless taxi, intelligent connected bus, autonomous logistics vehicle, electric truck, etc. Furthermore, this method is also applicable to various special-purpose vehicles, such as agricultural vehicles, mining vehicles, forestry vehicles, airport vehicles, port vehicles, etc. This application does not impose specific limitations in this regard.

[0061] For ease of understanding, the following detailed description, in conjunction with the accompanying drawings, illustrates a vehicle control method provided in an embodiment of this application. See also... Figure 2 The vehicle control method may include the following steps: S201-S204.

[0062] S201. In response to the detection of a vehicle collision, determine the severity of the collision, the probability of fire, and the probability of falling into water based on the vehicle's real-time operating data.

[0063] In this embodiment of the application, the real-time operating data of the vehicle may include data collected by multiple sensors on the vehicle, including vehicle driving data and vehicle operating status data. This embodiment of the application does not specifically limit the real-time operating data.

[0064] In some embodiments, the electronic device extracts multiple data features from real-time operating data and fuses these features to obtain fused data features. Further, the electronic device determines the collision severity, fire probability, and water-fall probability of the vehicle based on the fused data features.

[0065] For example, taking real-time operational data including acceleration data collected by an accelerometer, pressure data collected by a pressure sensor, water level data collected by a water level sensor, and temperature data collected by a temperature sensor as an example, the electronic device extracts acceleration features from the acceleration data, pressure features from the pressure data, water level features from the water level data, and temperature features from the temperature sensor. Further, the electronic device performs weighted fusion of the acceleration, pressure, water level, and temperature features to obtain data fusion features. Subsequently, the electronic device inputs the data fusion features into a preset risk identification model to obtain the collision severity, fire probability, and water fall probability, respectively.

[0066] The aforementioned preset risk identification model is a pre-configured model, which can be a Bayesian network model or other models. This application does not specifically limit the specific model used in this embodiment.

[0067] In other embodiments, the electronic device determines the severity of a collision based on data collected by an acceleration sensor and a pressure sensor, determines the probability of fire based on data collected by a pressure sensor and temperature data collected by a temperature sensor, and determines the probability of falling into water based on water level data collected by a water level sensor.

[0068] S202. Determine the real-time risk value of the vehicle based on the severity of the collision, the probability of fire, and the probability of falling into water.

[0069] The real-time risk value is used to represent the real-time danger level of a vehicle after a collision.

[0070] In some embodiments, the electronic device inputs the severity of the collision, the probability of fire, and the probability of falling into water into a preset risk value determination formula to obtain a real-time risk value.

[0071] In other embodiments, the electronic device determines the weights of collision severity, fire probability, and water probability, respectively, based on the collision severity, fire probability, and water probability. Furthermore, the electronic device determines the real-time risk value by weighted summing of these factors.

[0072] In this embodiment of the application, weights can be assigned according to the severity of the accident. For example, if the electronic device is determined to have a high degree of hazard from collision and fire, higher weights can be assigned to the severity of the collision and the probability of fire, and lower weights can be assigned to the probability of falling into water.

[0073] S203. Determine the target risk response strategy based on the real-time risk value.

[0074] In some embodiments, the electronic device determines a target risk response strategy based on a real-time risk value, a first risk value, and a second risk value.

[0075] Specifically, the electronic device determines whether the real-time risk value exceeds the first risk value, and if the real-time risk value exceeds the first risk value, it determines the target risk response strategy as the first response strategy; the first response strategy is used to instruct the vehicle to perform window breaking operation, location reporting operation, and power-off operation.

[0076] When the real-time risk value exceeds the set first risk threshold, it indicates that the vehicle is in an extremely critical state, such as structural damage that may result from a severe collision, battery thermal runaway and fire, or sinking into water. Therefore, to ensure the safety of the occupants, the fastest and most forceful measures are needed to ensure the survival rate of the occupants and create the necessary conditions for external rescue. Thus, the first response strategy is automatically activated: first, a window-breaking operation is performed to immediately create a definitive emergency physical exit for the occupants if the doors cannot be opened due to deformation or electronic system failure. This is the last lifeline for escape and self-rescue or external rescue. Simultaneously, the highest priority location reporting operation is initiated, forcibly sending a distress signal containing precise satellite positioning coordinates, vehicle identification number, and event level to the cloud-based rescue platform and public emergency service center via the vehicle-to-everything (V2X) terminal, ensuring that even if the occupants are unconscious, rescue forces can be accurately guided to the scene. Finally, a forced power-off operation is performed on the entire vehicle. This is especially important for new energy vehicles, as it completely cuts off the high-voltage circuit and fundamentally eliminates the secondary risks of fire, explosion, or electric shock caused by electrical system short circuits, providing a relatively safe environment for occupant evacuation and rescue operations.

[0077] If the real-time risk value does not exceed the second risk value, the electronic device determines the target risk response strategy as the second response strategy. The second response strategy is used to instruct the vehicle to perform seat belt pretensioning and activate the safety warning light, which is used to warn surrounding vehicles.

[0078] When the real-time risk value detected does not exceed the second risk threshold, it usually corresponds to a minor collision (such as a low-speed rear-end collision) or a higher risk that the perception system anticipates but still has room for mitigation (such as emergency braking by the vehicle in front or slight vehicle skidding). At this time, the direct physical damage from the accident is relatively limited, but occupants may be impacted due to inertia, and the vehicle is in an abnormal state on the road. Therefore, the core objective of the second response strategy shifts to providing maximum occupant restraint protection at the moment of collision and proactively warning afterward to avoid more dangerous secondary collisions. The first step of the strategy is to immediately trigger seat belt pretensioning. Through coordination with the airbag control unit, within milliseconds of the impact occurring or about to occur, the motor rapidly tightens the seat belt, eliminating the slack between the webbing and the occupant's body, firmly stabilizing the occupant within the seat safety area. This, combined with the deployment of the airbag, significantly reduces the severity of head and chest injuries. At the same time, activating highly recognizable safety warning lights (such as hazard lights flashing rapidly at a specific frequency) provides a strong visual signal that can effectively penetrate complex traffic environments, clearly conveying the warning message that "this vehicle is in an abnormal state" to vehicles behind and around, prompting other road users to take evasive measures such as slowing down or changing lanes in advance. This reflects the extension from "protection during an accident" to "protection after an accident," protecting occupants through "pre-tensioning" and preventing chain accidents through "warning," which are key proactive measures to improve overall road safety.

[0079] When the real-time risk value of the electronic device exceeds the second risk value but does not exceed the first risk value, the target risk response strategy is determined to be the third response strategy. The third response strategy is used to instruct the vehicle to perform door unlocking operations, window opening height adjustment operations that do not exceed a preset height threshold, and emergency call operations.

[0080] When the real-time risk value falls between the first and second thresholds, it indicates that the vehicle has experienced a relatively serious but not catastrophic collision (such as a moderate offset collision or rollover), or a serious emergency requiring immediate intervention has occurred inside the vehicle (such as a passenger suffering a serious illness). The risk at this stage is dual: there is an urgent need for personal safety and rescue, but it hasn't reached the point where extreme destructive measures are necessary. Therefore, the essence of the third response strategy lies in a careful balance: while actively preparing for escape and seeking help, maintaining the vehicle's safety boundaries and avoiding over-response that could create new risks. This strategy first automatically unlocks all vehicle doors. This is the most basic and crucial step after an accident, ensuring that all occupants (especially children or those with mobility issues in the back seat) and the first responders can easily open the doors from the outside, avoiding the desperate situation of being "trapped inside" due to panic, mechanical deformation, or electrical interruption. Next, the windows are automatically lowered, but their opening height is strictly limited to a preset safety threshold (e.g., 10 centimeters). This "limited opening" design is ingenious: it ensures air circulation between the inside and outside of the carriage, preventing oxygen deprivation or suffocation caused by the enclosed space; it also serves as a channel for transmitting sound and delivering small items, facilitating communication with the outside world; more importantly, the limited opening provides the possibility of escape while effectively preventing the risk of being thrown out or trapped when the vehicle may roll over or when passengers (especially children) are unconscious due to the window being wide open. Finally, it triggers the onboard emergency call system, establishing a voice communication link with a professional rescue service center, allowing passengers to communicate directly with a human operator, report specific situations, or, if the operator is unable to answer, for the center to initiate a rescue process based on automatically uploaded vehicle condition and location information. The third response strategy is a smart bridge connecting "passive safety" and "active rescue," ensuring accessibility through "unlocking," ensuring safety, ventilation, and communication through "limited window opening," and ensuring information connectivity through "emergency call," providing a comprehensive and controllable solution for dealing with medium to high-risk events.

[0081] The aforementioned first and second risk values ​​can be pre-configured, and this application does not specifically limit their implementation. For example, the first risk value can be 0.7 and the second risk value can be 0.4.

[0082] In other embodiments, the electronic device determines a risk level based on a real-time risk value and a target risk response strategy based on the risk level and the vehicle's real-time accident type. The real-time accident type is determined based on real-time operational data.

[0083] For example, if the electronic device determines the risk level to be Level 1 and the real-time accident types include drowning accidents and short circuit accidents, the target risk response strategy is to activate seatbelt pretensioning. Subsequently, if the electronic device further determines the risk level to be Level 2 and the real-time accident type to be drowning accidents, the target risk response strategy is to include window breaking and drainage operations.

[0084] S204. Implement the target risk response strategy.

[0085] For example, taking the target risk response strategy as the third response strategy, the electronic device generates a door unlock command, a window height adjustment command, and an emergency call command. Further, the electronic device controls the door to unlock based on the door unlock command, controls the window opening height to not exceed a preset height threshold based on the window height adjustment command, and executes an emergency call operation based on the emergency call command.

[0086] The vehicle control method provided in this application provides at least the following beneficial effects: In the event of a vehicle collision, the severity of the collision, the probability of fire, and the probability of falling into water are determined based on the vehicle's real-time operating data. A real-time risk value for the vehicle is then determined based on these factors. Furthermore, a target risk response strategy is determined and executed based on the real-time risk value. This method, by judging the vehicle's driving status based on real-time operating data and executing the risk response strategy in real time according to the vehicle's condition, improves the vehicle's response speed and thus enhances vehicle safety. Additionally, determining the severity of the collision, the probability of fire, and the probability of falling into water based on real-time operating data allows for a comprehensive understanding of the vehicle's collision, fire, and water-related situations, enabling a more comprehensive assessment of the vehicle's real-time danger level.

[0087] As a feasible implementation method, the vehicle control method provided in this application embodiment also includes: S205-S206.

[0088] S205. Determine the probability of oil leakage of a vehicle based on its collision data.

[0089] In some embodiments, the electronic device determines the vehicle's collision probability based on the vehicle's acceleration information, and if the collision probability exceeds a target threshold, determines a first sub-oil leakage probability after the collision based on the vehicle's collision data. Further, the electronic device determines a non-collision probability based on the collision probability. Subsequently, the electronic device determines the vehicle's oil leakage probability based on the first sub-oil leakage probability, the collision probability, the non-collision probability, and a second sub-oil leakage probability. The second sub-oil leakage probability is the oil leakage probability of the vehicle in a non-collision state. The second sub-oil leakage probability can be pre-configured or determined based on the vehicle's operating status and age; this embodiment does not specifically limit its determination.

[0090] For example, by inputting the first sub-probability of oil leakage, the probability of collision, the probability of non-collision, and the second sub-probability of oil leakage into the oil leakage probability determination formula, the oil leakage probability of the vehicle can be obtained.

[0091] For example, the formula for determining the probability of oil leakage is shown in Formula 1 below.

[0092] P(fuel leak) = P(fuel leak | collision) × P(collision) + P(fuel leak | non-collision) × P(non-collision) (Formula 1) Wherein, P(fuel leak) is the probability of fuel leak, P(fuel leak|collision) is the first sub-probability of fuel leak, P(fuel leak|non-collision) is the second sub-probability of fuel leak, P(collision) is the probability of collision, and P(non-collision) is the probability of non-collision.

[0093] Taking the first child's oil leakage probability as 0.12 and collision probability as 0.8, the second child's oil leakage probability as 0.01, and P (non-collision) as 0.2 as an example, according to Formula 1, the oil leakage probability = 0.12 × 0.8 + 0.01 × 0.2 = 0.096 + 0.002 = 0.098.

[0094] In this embodiment, the collision data may include the collision location, collision force, and vehicle acceleration. The target collision probability threshold is determined based on environmental data of the vehicle's environment.

[0095] S206. Perform fuel isolation operation based on the probability of oil leakage and the probability of fire.

[0096] In some embodiments, if the probability of oil leakage exceeds a preset oil leakage probability threshold and the probability of fire exceeds a preset fire probability threshold, the electronic device shuts off the vehicle's fuel pump and isolates the vehicle's fuel tank. If the probability of oil leakage exceeds a preset oil leakage probability threshold and the probability of fire does not exceed a preset fire probability threshold, the electronic device shuts off the vehicle's fuel system.

[0097] For example, consider an oil leak probability of 0.098, a fire risk of 0.5, a preset oil leak probability threshold of 0.05, and a preset fire probability threshold of 0.4. The electronic device determines that the oil leak probability exceeds the preset oil leak probability threshold and the fire probability exceeds the preset fire probability threshold, thus determining that the vehicle is about to catch fire. It then shuts off the vehicle's fuel pump and isolates the vehicle's fuel tank.

[0098] The aforementioned preset oil leak probability threshold and preset fire probability threshold can be pre-configured, and this application embodiment does not specifically limit them.

[0099] As a feasible implementation method, the vehicle control method provided in this application embodiment determines the process of a vehicle collision accident, including: S207-S208.

[0100] S207. Determine the probability of a vehicle collision based on changes in the vehicle's acceleration.

[0101] In some embodiments, the electronic device acquires acceleration changes collected by the acceleration sensor and determines the probability of a vehicle collision based on the acceleration changes.

[0102] For example, consider an acceleration variation of 1.2 g for a duration of 25 milliseconds (ms). Inputting 1.2 g and 25 ms into the collision probability determination model yields a collision probability of 0.8.

[0103] The collision probability determination model described above was trained based on sample acceleration information.

[0104] S208. If the collision probability value exceeds the target collision probability threshold, it is determined that a vehicle collision accident has been detected.

[0105] The target collision probability threshold is determined based on environmental data of the vehicle's environment.

[0106] In some embodiments, the electronic device determines whether the collision probability value exceeds a target collision probability threshold. If the collision probability value exceeds the target collision probability threshold, it determines that a vehicle collision has been detected. If the collision probability value does not exceed the target collision probability threshold, it determines that no vehicle collision has been detected.

[0107] As a feasible implementation method, the vehicle control method provided in this application, the process of determining the target collision probability threshold, is as follows: Figure 3 As shown, it includes: S301-S303.

[0108] S301. Obtain the vehicle's weather factors, pattern factors, and credibility compensation factors.

[0109] Among them, the weather factor is used to represent the severity of the current weather, the mode factor is determined according to the vehicle's driving mode and is used to represent the severity of the environment in which the vehicle is located, and the reliability compensation factor is determined according to the reliability of the vehicle's acceleration sensor and is used to represent the reliability of the acceleration sensor.

[0110] In some embodiments, the electronic device acquires the current weather conditions, the vehicle's driving mode, and the reliability of the acceleration sensor, and determines a weather factor based on the current weather conditions, a mode factor based on the driving mode, and a reliability compensation factor based on the reliability of the acceleration sensor.

[0111] For example, assuming the current weather condition is sunny, the driving mode is city mode, and the accelerometer sensor's confidence level is 0.8, the electronic device determines the weather factor to be 1 based on the correspondence between sunny weather and the first target; determines the mode factor to be 1.1 based on the correspondence between city mode and the second target; and determines the confidence compensation factor to be 0.94 based on the accelerometer sensor's confidence level and the confidence compensation formula. The first target correspondence characterizes the relationship between weather condition and weather factor, and the second target correspondence characterizes the relationship between driving mode and mode factor.

[0112] The aforementioned credibility compensation formula can be pre-configured, and this application embodiment does not specifically limit the credibility compensation formula. For example, the credibility compensation formula is shown in Formula 2 below.

[0113] R = (1 - 0.3 × (1 – Re)) (Formula 2) Where R is the confidence compensation factor and Re is the confidence level of the accelerometer.

[0114] S302. Determine the correction coefficients based on weather factors, model factors, and confidence compensation factors.

[0115] In some embodiments, the electronic device determines the correction coefficient as the product of the weather factor, the model factor, and the confidence compensation factor.

[0116] In other embodiments, the electronic device determines the correction coefficient as a weighted sum of the weather factor, the model factor, and the confidence compensation factor.

[0117] S303. Correct the initial collision probability threshold according to the correction coefficient to obtain the target collision probability threshold.

[0118] In some embodiments, the electronic device determines the target collision probability threshold by multiplying the correction coefficient by the initial collision probability threshold.

[0119] For example, with an initial collision probability threshold of 0.7 and a correction factor of 1.034, the electronic device obtains a target collision probability threshold of 0.72.

[0120] The aforementioned initial collision probability threshold is pre-configured.

[0121] This application provides a dynamic adjustment algorithm for the collision probability threshold. The algorithm corrects the initial collision probability threshold based on the vehicle's driving mode, weather conditions, and the reliability of the acceleration sensor, and then determines the collision accident based on the target collision probability threshold. This avoids the problem of data deviation caused by environmental influences on the vehicle's sensors, which leads to a decrease in the accuracy of collision accident identification. As one feasible implementation method, the vehicle includes a first acceleration sensor and a second acceleration sensor, such as... Figure 4 As shown, the vehicle control method provided in this application embodiment further includes: S401-S403.

[0122] S401. When the first accelerometer is the main sensor, acquire the data difference value, electromagnetic interference value and temperature interference value of the first accelerometer.

[0123] Among them, the data difference value is used to characterize the degree of difference between the data collected by the first accelerometer and the data collected by the second accelerometer, the electromagnetic interference value is used to characterize the degree of electromagnetic interference suffered by the first accelerometer, and the temperature interference value is negatively correlated with the ambient temperature of the first accelerometer.

[0124] In some embodiments, the electronic device acquires data collected by a first accelerometer and data collected by a second accelerometer, and calculates the data difference between the two data. Further, the electronic device obtains a data difference value based on the data difference and a formula for determining the difference value.

[0125] For example, the formula for determining the difference value is shown in Formula 3 below.

[0126] V = 1.0 - min(d / 0.5, 1.0) (Formula 3) Where V is the data difference value and d is the data difference value.

[0127] In some embodiments, the electronic device acquires electromagnetic interference intensity data of the first accelerometer through an on-board diagnostics interface (OBD) and determines the electromagnetic interference value based on the electromagnetic interference intensity data. The electronic device acquires the ambient temperature of the first accelerometer and determines the temperature interference value based on the temperature of the first accelerometer. For example, the electronic device determines the temperature interference value based on the correspondence between the ambient temperature of the first accelerometer and the interference value. The interference value correspondence is used to characterize the relationship between the temperature of the accelerometer and the temperature interference value.

[0128] In other embodiments, the electronic device calculates the time-domain variance of the data from the first accelerometer based on the data from the first accelerometer, and determines the degree of fluctuation of the data from the first accelerometer based on the time-domain variance. For example, the electronic device inputs the time-domain variance into a preset function to obtain the degree of fluctuation.

[0129] The above preset functions are pre-configured functions.

[0130] S402. Determine the reliable value of the first accelerometer based on the data difference value, electromagnetic interference value, and temperature interference value.

[0131] In some embodiments, the electronic device inputs data difference values, electromagnetic interference values, and temperature interference values ​​into a confidence determination formula to obtain a confidence value for the first accelerometer.

[0132] For example, the credibility determination formula is shown in Formula 4 below.

[0133] R1=V×E×T Formula 4 Where R is the confidence value, V is the data difference value, E is the electromagnetic interference value, and T is the temperature interference value.

[0134] Taking a data difference value of 0.96, an electromagnetic interference value of 0.875, and a temperature interference value of 0.955 as an example, the confidence value is determined according to Formula 4 as 0.96 × 0.875 × 0.955 = 0.8.

[0135] In other embodiments, the electronic device determines the reliable value of the first accelerometer by multiplying the data difference value, the electromagnetic interference value, the temperature interference value, and the degree of fluctuation.

[0136] 403. If the confidence value does not exceed the preset confidence threshold, switch the second acceleration sensor to the main sensor.

[0137] In some embodiments, the electronic device determines whether the confidence value does not exceed a preset confidence threshold, and if the confidence value does not exceed the preset confidence threshold, switches the second acceleration sensor to the main sensor.

[0138] For example, with a confidence value of 0.8 and a preset confidence threshold of 0.7, the electronic device will determine that the confidence value exceeds the preset confidence threshold, thus deciding that there is no need to switch the second accelerometer sensor to the main sensor.

[0139] In other embodiments, the electronic device determines whether the confidence value does not exceed a preset confidence threshold and whether the data difference value exceeds a preset difference value, and switches the second acceleration sensor to the main sensor if the confidence value does not exceed the preset confidence threshold and the data difference value exceeds the preset difference value.

[0140] The aforementioned preset confidence threshold and preset difference value can be pre-configured.

[0141] As a feasible way to achieve this, such as Figure 5 As shown, the vehicle control method provided in this application embodiment further includes: S501-S502.

[0142] S501. In the event of a detected fire, obtain the time of the vehicle's collision and the time of the fire.

[0143] The collision time is the moment when the collision signal is first detected, and the ignition time is the moment when the ignition signal is first detected.

[0144] In this embodiment, after detecting a vehicle collision, the electronic device uses an infrared thermal imager to detect whether the vehicle is on fire. Specifically, the electronic device determines that the vehicle is on fire if the temperature of a target area on the vehicle exceeds the ignition temperature threshold detected by the infrared thermal imager.

[0145] In some embodiments, upon detecting a fire, the electronic equipment will shut down the fuel pump and isolate the fuel tank, and report a fire. The fire information includes the location of the fire and is used to instruct vehicle assistance.

[0146] S502. Determine the cause of the vehicle fire based on the time interval between the collision time and the fire time, the location of the fire, and the collision location of the vehicle.

[0147] In some embodiments, if the time interval does not exceed a preset time interval and the fire location is associated with the collision location, the electronic device determines the cause of the fire to be a collision-induced fire. If the time interval exceeds the preset time interval or the fire location is associated with the collision location, the electronic device determines the cause of the fire to be a non-collision-induced fire.

[0148] For example, taking a preset time interval of 7 seconds and a time interval of 0.6 seconds as an example, the electronic device determines that the time interval does not exceed the preset time interval and that the fire location is the collision location, thereby determining the cause of the fire to be a collision-induced fire.

[0149] The aforementioned preset time interval can be pre-configured or determined based on the severity of the collision; this application embodiment does not specifically limit this.

[0150] As a feasible way to achieve this, such as Figure 6 As shown, the vehicle control method provided in this application embodiment also includes: S601-S603.

[0151] S601. Acquire the data characteristics of the target sensor.

[0152] The target sensor mentioned above can be any sensor on the vehicle.

[0153] In the embodiments of this application, the data features may include at least one of time-domain features, frequency-domain features, and spatial-domain features.

[0154] S602. Determine the detection results of the target sensor based on the data characteristics.

[0155] In some embodiments, the electronic device detects data features to obtain the detection results of the target sensor.

[0156] For example, taking an accelerometer as the target sensor, the data characteristics include time-domain features, frequency-domain features, and spatial-domain features. Time-domain feature detection can be performed on whether the acceleration signal exceeds 3g and its duration exceeds 20ms. If the acceleration signal exceeds 3g but the duration does not exceed 20ms, the time-domain feature test result is failed. Frequency-domain feature detection can be performed on the acceleration signal of the accelerometer to identify the characteristic frequencies of electromagnetic interference. For example, if a specific electromagnetic interference frequency band (such as 100MHz-1GHz) is detected in the frequency domain, electromagnetic interference is determined to exist, thus indicating an abnormal frequency-domain feature. Spatial-domain feature detection can be performed on whether the deformation direction of the pressure sensor matrix matches the acceleration direction detected by the accelerometer. If the deformation direction of the pressure sensor may not match the acceleration direction, the spatial-domain feature test result is failed. Subsequently, it is determined that the detection result of the accelerometer is affected by interference.

[0157] S603. If the detection result is found to be affected by interference, correct the data collected by the target sensor.

[0158] For example, if the accelerometer reading is found to be distorted, Kalman filtering is applied to the accelerometer data, and the accelerometer's sampling frequency is reduced to 50Hz. Similarly, if the infrared thermal imager reading is found to be distorted, real-time non-uniform correction is performed on the infrared thermal imager data to reduce data noise.

[0159] In this embodiment of the application, when the data collected by the target sensor is abnormal, the data collected by the target sensor is optimized to ensure the reliability of the data collected by the target sensor.

[0160] As a feasible way to achieve this, such as Figure 7 As shown, the vehicle control method provided in this application embodiment further includes: S701-S702.

[0161] S701. Shield the target sensor with a Faraday cage.

[0162] In this embodiment, a Faraday cage is configured for the target sensor to shield it from external electromagnetic interference. The structure of the Faraday cage is determined through multiple optimizations. For example, for an accelerometer, the Faraday cage ensures that the zero-bias drift of the accelerometer does not exceed 0.05g when the accelerometer receives electromagnetic interference. Similarly, for a temperature sensor, the Faraday cage ensures that the temperature error of the temperature sensor does not exceed 1°C when the accelerometer receives electromagnetic interference.

[0163] S702. Determine the distance between the sensors.

[0164] In some embodiments, it is determined that the distance between the sensors exceeds a preset distance. This preset distance is pre-configured and is not specifically limited in this embodiment.

[0165] For example, the distance between the accelerometer and the infrared thermal imager exceeds 15cm, and a metal partition is configured between the accelerometer and the infrared thermal imager to achieve electromagnetic shielding and thermal isolation.

[0166] In addition, when interference is detected with the target sensor, the acquisition mode is switched. For example, when the accelerometer is subjected to electromagnetic interference, the accelerometer is downsampled to 50Hz and the data acquired by the accelerometer is filtered; when the accelerometer is subjected to vibration interference, the accelerometer is controlled to enable high-pass filtering to filter the signal acquired by the accelerometer.

[0167] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the communication device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0168] Figure 8 The vehicle control device 80 is illustrated according to an exemplary embodiment. The vehicle control device 80 includes a determination unit 801 and a control unit 802.

[0169] The determining unit 801 is configured to, in response to detecting a vehicle collision, determine the collision severity, fire probability, and water-fall probability of the vehicle based on real-time vehicle operating data. The determining unit 801 is also configured to determine a real-time risk value of the vehicle based on the collision severity, fire probability, and water-fall probability; the real-time risk value represents the real-time danger level of the vehicle after the collision. The determining unit 801 is further configured to determine a target risk response strategy based on the real-time risk value. The control unit 802 is configured to execute the target risk response strategy.

[0170] As a feasible implementation method, the determining unit 801 is specifically used for: determining the target risk response strategy as the first response strategy when the real-time risk value exceeds the first risk value; the first response strategy is used to instruct the vehicle to perform window breaking, location reporting, and power-off operations. When the real-time risk value does not exceed the second risk value, the target risk response strategy is determined as the second response strategy; the second response strategy is used to instruct the vehicle to perform seatbelt pretensioning and activate the safety warning light, the light of which is used to warn surrounding vehicles. When the real-time risk value exceeds the second risk value but does not exceed the first risk value, the target risk response strategy is determined as the third response strategy; the third response strategy is used to instruct the vehicle to perform door unlocking, window opening height adjustment (not exceeding a preset height threshold), and trigger an emergency call.

[0171] As a feasible implementation method, before determining the severity of the collision, the determination unit 801 is also used to: determine the probability of oil leakage of the vehicle based on the vehicle's collision data.

[0172] The control unit 802 is also used to perform fuel isolation operations based on the probability of oil leakage and the probability of fire.

[0173] As a feasible implementation method, the determining unit 801 is specifically used to: determine the collision probability of the vehicle based on the changes in the vehicle's acceleration. If the collision probability exceeds a target collision probability threshold, it is determined that a vehicle collision accident has been detected; the target collision probability threshold is determined based on environmental data of the vehicle's environment.

[0174] As a feasible implementation method, the determining unit 801 is also used to: acquire the vehicle's weather factor, mode factor, and confidence compensation factor; the weather factor is determined based on the current weather, the mode factor is determined based on the vehicle's driving mode, and the confidence compensation factor is determined based on the confidence level of the vehicle's acceleration sensor. Based on the weather factor, mode factor, and confidence compensation factor, a correction coefficient is determined. The initial collision probability threshold is corrected based on the correction coefficient to obtain the target collision probability threshold.

[0175] As one feasible implementation method, the control unit is specifically used to: shut down the vehicle's fuel pump and isolate the vehicle's fuel tank when the probability of oil leakage exceeds a preset oil leakage probability threshold and the probability of fire exceeds a preset fire probability threshold; and shut down the vehicle's fuel system when the probability of oil leakage exceeds a preset oil leakage probability threshold and the probability of fire does not exceed a preset fire probability threshold.

[0176] As a feasible way to achieve this, such as Figure 8 As shown, the vehicle control device 80 further includes an acquisition unit 803 and a switching unit 804. The acquisition unit 803 is used to acquire, when the first accelerometer is the primary sensor, a data difference value, an electromagnetic interference value, and a temperature interference value from the first accelerometer. The data difference value characterizes the degree of difference between the data acquired by the first accelerometer and the data acquired by the second accelerometer; the electromagnetic interference value characterizes the degree of electromagnetic interference experienced by the first accelerometer; and the temperature interference value is negatively correlated with the ambient temperature of the first accelerometer.

[0177] The determining unit 801 is also used to: determine the reliable value of the first acceleration sensor based on the data difference value, electromagnetic interference value and temperature interference value.

[0178] The switching unit 804 is used to switch the second acceleration sensor to the main sensor when the confidence value does not exceed a preset confidence threshold.

[0179] As a feasible implementation method, the switching unit 804 is specifically used to switch the second acceleration sensor to the main sensor when the confidence value is less than the preset confidence threshold and the data difference value exceeds the preset difference value.

[0180] As a feasible implementation method, the acquisition unit 803 is also used to acquire the collision time, fire time and fire location of the vehicle when a fire event is detected; the collision time is the time when the collision signal is first detected and the fire time is the time when the fire signal is first detected.

[0181] The determining unit 801 is also used to: determine the cause of the vehicle fire based on the time interval between the collision time and the fire time, the fire location, and the collision location of the vehicle.

[0182] Figure 9 This is a schematic diagram illustrating an electronic device according to an exemplary embodiment. Figure 9 As shown, the electronic device includes, but is not limited to, a processor 901 and a memory 902.

[0183] The aforementioned memory 902 is used to store the executable instructions of the aforementioned processor 901. It is understood that the aforementioned processor 901 is configured to execute instructions to implement the structural strength determination method in the above embodiments.

[0184] It should be noted that those skilled in the art will understand that Figure 9 The electronic device structure shown does not constitute a limitation on the electronic device; the electronic device may include, but is not limited to, other electronic devices. Figure 9 This may indicate more or fewer components, or combinations of certain components, or different component arrangements.

[0185] Processor 901 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 902, and by calling data stored in memory 902, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Processor 901 may include one or more processing units. Optionally, processor 901 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into processor 901.

[0186] The memory 902 can be used to store software programs and various data. The memory 902 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required by at least one functional module (such as a determination unit, processing unit, etc.), etc. Furthermore, the memory 902 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0187] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 902 including instructions, which can be executed by a processor 901 of an electronic device to implement the methods in the above embodiments.

[0188] Optionally, the computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0189] In an exemplary embodiment, this application also provides a computer program product including one or more instructions, which can be executed by a processor 901 of an electronic device to perform the methods described above.

[0190] It should be noted that when one or more instructions in the computer-readable storage medium or computer program product are executed by the processor of an electronic device, they implement the various processes of the above method embodiments and achieve the same technical effect as the above method. To avoid repetition, they will not be described again here.

[0191] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0192] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0193] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0194] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0195] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0196] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A vehicle control method, characterized in that, The vehicle control method includes: In response to the detection of a vehicle collision, the severity of the collision, the probability of fire, and the probability of falling into water are determined based on the real-time operating data of the vehicle. The real-time risk value of the vehicle is determined based on the severity of the collision, the probability of fire, and the probability of falling into water; the real-time risk value is used to represent the real-time danger level of the vehicle after the collision accident. The target risk response strategy is determined based on the real-time risk value, and then the target risk response strategy is executed.

2. The vehicle control method according to claim 1, characterized in that, The step of determining the target risk response strategy based on the real-time risk value includes: If the real-time risk value exceeds the first risk value, the target risk response strategy is determined to be the first response strategy; the first response strategy is used to instruct the vehicle to perform a window breaking operation, a location reporting operation, and a power-off operation; If the real-time risk value does not exceed the second risk value, the target risk response strategy is determined to be the second response strategy; the second response strategy is used to instruct the vehicle to perform seat belt pretensioning and activate the safety warning light, the light of which is used to warn surrounding vehicles of the vehicle; If the real-time risk value exceeds the second risk value but does not exceed the first risk value, the target risk response strategy is determined to be the third response strategy; the third response strategy is used to instruct the vehicle to perform door unlocking operation, window opening height adjustment operation not exceeding a preset height threshold, and emergency call operation.

3. The vehicle control method according to claim 1, characterized in that, The vehicle control method further includes: The probability of oil leakage of the vehicle is determined based on the vehicle's collision data; Based on the oil leakage probability and the fire probability, perform a fuel isolation operation.

4. The vehicle control method according to claim 3, characterized in that, The step of performing a fuel isolation operation based on the oil leakage probability and the fire probability includes: If the probability of oil leakage exceeds a preset oil leakage probability threshold and the probability of fire exceeds a preset fire probability threshold, the vehicle's fuel pump is shut down and the vehicle's fuel tank is isolated. If the probability of oil leakage exceeds a preset oil leakage probability threshold and the probability of fire does not exceed the preset fire probability threshold, the vehicle's fuel system is shut off.

5. The vehicle control method according to claim 1, characterized in that, The method further includes: The collision probability of the vehicle is determined based on the changes in the vehicle's acceleration. If the collision probability exceeds a target collision probability threshold, it is determined that a collision has occurred with the vehicle; the target collision probability threshold is determined based on environmental data of the environment in which the vehicle is located.

6. The vehicle control method according to claim 5, characterized in that, The target collision probability threshold is determined in the following way: The weather factor, mode factor, and confidence compensation factor of the vehicle are obtained; the weather factor is used to represent the severity of the current weather, the mode factor is determined according to the driving mode of the vehicle and is used to represent the severity of the environment in which the vehicle is located, and the confidence compensation factor is determined according to the confidence of the vehicle's acceleration sensor and is used to represent the confidence of the acceleration sensor. The correction coefficient is determined based on the weather factor, the model factor, and the confidence compensation factor; The initial collision probability threshold is corrected according to the correction coefficient to obtain the target collision probability threshold.

7. The vehicle control method according to any one of claims 1-6, characterized in that, The vehicle includes a first acceleration sensor and a second acceleration sensor, and the vehicle control method further includes: When the first accelerometer is the main sensor, the data difference value, electromagnetic interference value, and temperature interference value of the first accelerometer are acquired. The data difference value is used to characterize the degree of difference between the data collected by the first accelerometer and the data collected by the second accelerometer. The electromagnetic interference value is used to characterize the degree of electromagnetic interference experienced by the first accelerometer. The temperature interference value is negatively correlated with the ambient temperature of the first accelerometer. Based on the data difference value, the electromagnetic interference value, and the temperature interference value, the reliable value of the first acceleration sensor is determined; If the confidence value does not exceed a preset confidence threshold, the second acceleration sensor is switched to the main sensor.

8. The vehicle control method according to claim 7, characterized in that, The step of switching the second acceleration sensor to the main sensor when the confidence value is less than a preset confidence threshold includes: If the confidence value does not exceed the preset confidence threshold and the data difference value exceeds the preset difference value, the second acceleration sensor is switched to the main sensor.

9. The vehicle control method according to any one of claims 1-6, characterized in that, The vehicle control method further includes: In the event of a detected fire, the collision time, fire time, and fire location of the vehicle are obtained; the collision time is the moment when the first collision signal is detected, and the fire time is the moment when the first fire signal is detected. The cause of the vehicle fire is determined based on the time interval between the collision time and the fire time, the fire location, and the collision location of the vehicle.

10. A vehicle control device, characterized in that, The vehicle control device includes: a determination unit and a control unit; The determining unit is used to determine the severity of the collision, the probability of fire, and the probability of falling into water of the vehicle based on the real-time operating data of the vehicle in response to the detection of a vehicle collision accident. The determining unit is further configured to determine the real-time risk value of the vehicle based on the severity of the collision, the probability of fire, and the probability of falling into water; the real-time risk value is used to represent the real-time danger level of the vehicle after the collision accident. The determining unit is further configured to determine a target risk response strategy based on the real-time risk value; The control unit is used to execute the target risk response strategy.

11. An electronic device, characterized in that, Including memory and electronic devices; The memory and the electronic device are coupled; The memory is used to store computer program code, which includes computer instructions; When the electronic device executes the computer instructions, the electronic device performs the vehicle control method as described in any one of claims 1-9.

12. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 11.

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