Stress protection method, electronic equipment, storage medium and driving equipment

Abstract

The invention relates to the technical field of driving equipment safety, in particular to a stress protection method, electronic equipment, a storage medium and driving equipment, and aims to solve the problems that protection measures adopted by an existing safety system are relatively single and cannot be dynamically adjusted. In order to achieve the purpose, the method comprises the steps that S1, whether driving equipment is in a high-risk state or not is judged based on a safety system, and the high-risk state comprises at least one of a driver high-risk state, a vehicle body high-risk state and an environment high-risk state; s2, when the driving equipment is in a high-risk state, adjusting the operation capability of a safety system, and executing a corresponding stress protection action according to the type of the high-risk state; and S3, repeatedly executing the steps S1-S2 based on the safety system obtained in the step S2 until the risk score of the driving equipment is less than or equal to a risk threshold. Through the implementation mode, the accident rate can be effectively reduced in a complex and changeable actual driving scene, and the safety of the vehicle, a driver and passengers is guaranteed.

Description

Technical Field

[0001] The present application relates to the technical field of driving equipment safety, and in particular to a stress protection method, electronic equipment, storage medium and driving equipment. Background Art

[0002] With the rapid development of intelligent driving, the importance of vehicle safety technology has become increasingly prominent, becoming the core of improving driving experience and protecting the lives of passengers. Existing driving equipment widely uses safety systems (such as automatic emergency braking, lane keeping assist, blind spot monitoring, etc.) to reduce the accident rate.

[0003] However, the current safety system has some shortcomings. On the one hand, the protection measures it adopts are relatively simple and do not take into account how to deal with accidents when they are inevitable. On the other hand, after the system triggers relevant protection measures, the state of the driving equipment and the environment in which it is located will change, but the system cannot perceive the changes in time and make adaptive adjustments, nor can it adjust the triggered protection measures in time, which limits the role of the system in complex and changeable actual driving scenarios and makes it difficult to provide effective protection for drivers and passengers.

[0004] Accordingly, the art needs a new technical solution to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects, the present application is proposed to provide a stress protection method, electronic device, storage medium and driving device that solve or at least partially solve the technical problem that the protection measures taken by the existing safety system are relatively simple and cannot be dynamically adjusted.

[0006] In a first aspect, a stress protection method is provided, which is applied to a driving device, wherein the driving device includes a safety system, and the method includes:

[0007] S1. Determining whether the driving device is in a high-risk state based on the safety system; wherein the risk score corresponding to the high-risk state is higher than the risk threshold, and the high-risk state includes at least one of a driver high-risk state, a vehicle body high-risk state, and an environment high-risk state;

[0008] S2. When the driving device is in the high-risk state, adjusting the operating capability of the safety system and performing corresponding stress protection actions according to the type of the high-risk state;

[0009] S3. Based on the safety system obtained in step S2, steps S1-S2 are repeatedly executed until the risk score is less than or equal to the risk threshold.

[0010] In a technical solution of the above stress protection method, the safety system includes a perception module and a decision module, and the method further includes:

[0011] Acquire perception data of the driving device based on the perception module; the perception data includes cockpit perception data, vehicle body perception data and environment perception data.

[0012] In a technical solution of the above stress protection method, the adjusting the operating capability of the safety system includes at least one of the following:

[0013] Performing data enhancement processing on the perception data, and dynamically adjusting the perception algorithm parameters of the perception module based on the perception data after the data enhancement processing;

[0014] Optimizing the decision algorithm parameters of the decision module to control the driving device to perform the stress protection action based on the optimized decision module;

[0015] Improve the decision-making speed of the decision-making module.

[0016] In a technical solution of the above stress protection method, the decision algorithm parameters of the optimization decision module include:

[0017] Acquire new perception data in real time based on the perception module;

[0018] Dynamically adjusting a preset weight parameter corresponding to the perception data based on the new perception data;

[0019] Based on the new perception data and the dynamically adjusted preset weight parameters, the decision algorithm parameters of the decision module are adjusted.

[0020] In a technical solution of the above stress protection method, the step of improving the decision speed of the decision module includes:

[0021] Based on a multi-core processor or a distributed computing platform, the decision algorithm of the decision module is processed in parallel.

[0022] In a technical solution of the above stress protection method, the safety system further includes a transmission module, and the transmission module is used to transmit the perception data acquired by the perception module to the decision module; the adjusting the operating capability of the safety system also includes:

[0023] Improve the data transmission speed of the transmission module.

[0024] In a technical solution of the above stress protection method, the cockpit perception data includes the driver's attention data and health data, the body perception data includes the speed data, steering data and braking data of the driving device, and the environment perception data includes the point cloud data and image data of the environment around the driving device; the judging whether the driving device is in a high-risk state based on the safety system includes:

[0025] Obtaining the quantized value and preset weight parameter corresponding to each perception data;

[0026] Obtaining a driver risk score, a vehicle body risk score, and an environment risk score based on the quantified value and preset weight parameters;

[0027] It is determined whether the driving device is in the high-risk state based on the driver risk score, the vehicle body risk score, and the environment risk score.

[0028] In a technical solution of the above stress protection method, determining whether the driving device is in the high-risk state based on the driver risk score, the vehicle body risk score and the environment risk score includes:

[0029] respectively determining whether the driver risk score, the vehicle body risk score, and the environment risk score are higher than the risk threshold;

[0030] When at least one of the driver risk score, the vehicle body risk score, and the environment risk score is higher than the risk threshold, it is determined that the driving device is in the high-risk state.

[0031] In a technical solution of the above stress protection method, executing corresponding stress protection actions according to the type of the high-risk state includes:

[0032] Acquire stress protection action database;

[0033] Based on the type of the high-risk state, executing the corresponding stress protection action in the stress protection action database;

[0034] Among them, the stress protection actions include turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending risk notifications, turning off driving experience related functions, storing driving equipment status data and sending rescue information.

[0035] In a technical solution of the above stress protection method, executing the corresponding stress protection action in the stress protection action database based on the type of the high-risk state includes:

[0036] When the driving device is in the high-risk state for the driver, performing at least one of turning on a warning light, adjusting a seat position, tightening a seat belt, honking a horn, sending a risk notification, storing driving device state data, and sending a rescue message;

[0037] When the driving device is in the high-risk state of the vehicle body, performing at least one of turning on the warning light, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, honking the horn, sending a risk notification, storing the driving device status data, and sending a rescue message;

[0038] When the driving device is in the high-risk state of the environment, at least one of turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending a risk notification, turning off driving experience related functions, storing driving device status data and sending rescue information is executed.

[0039] In a technical solution of the above stress protection method, the method further comprises:

[0040] When the driving device is in the high-risk state, determining a risk scenario corresponding to the type of the high-risk state;

[0041] The corresponding stress protection action is executed based on the risk scenario.

[0042] In a technical solution of the above stress protection method, the risk scenario includes a driver risk scenario, a vehicle body risk scenario and an environmental risk scenario; when the driving device is in the high-risk state, determining the risk scenario corresponding to the type of the high-risk state includes:

[0043] When the driving device is in the driver high risk state, determining the driver risk scenario based on the driver risk score;

[0044] When the driving device is in the vehicle body high risk state, determining the vehicle body risk scenario based on the vehicle body risk score;

[0045] When the driving device is in the environmental high risk state, determining the environmental risk scenario based on the environmental risk score;

[0046] Among them, the driver risk scenarios include at least distraction scenarios, fatigue scenarios and sudden illness scenarios, the body risk scenarios include at least tire blowout scenarios, side slip scenarios and accidental pedal pressing scenarios, and the environmental risk scenarios include at least collision scenarios and rollover scenarios.

[0047] In a second aspect, an electronic device is provided, which includes a processor and a memory, wherein the memory is suitable for storing multiple program codes, and the program codes are suitable for being loaded and run by the processor to execute the stress protection method described in any one of the technical solutions of the above-mentioned stress protection method.

[0048] In a third aspect, a computer-readable storage medium is provided, in which a plurality of program codes are stored, wherein the program codes are suitable for being loaded and run by a processor to execute the stress protection method described in any one of the technical solutions of the above-mentioned stress protection method.

[0049] In a fourth aspect, a driving device is provided, the driving device comprising a safety system and the electronic device according to the technical solution of the above electronic device, the safety system comprising a perception module and a decision module;

[0050] The perception module is used to obtain the perception data of the driving device; the perception data includes cockpit perception data, vehicle body perception data and environment perception data;

[0051] The decision module is used to determine whether the driving device is in a high-risk state based on the perception data.

[0052] In a technical solution of the above driving device, the driving device further comprises at least one of a lighting system, an active hood system, a passive safety system, a braking system, a high-voltage management system, an active suspension system, a horn system, a vehicle networking technology communication system, a central control system, an event data recording system, and an emergency rescue system;

[0053] Wherein, the passive safety system at least includes a seat adjustment module and a seat belt tightening module.

[0054] Solution 1. A stress protection method, applied to a driving device, characterized in that the driving device includes a safety system, and the method includes:

[0055] S1. Determining whether the driving device is in a high-risk state based on the safety system; wherein the risk score corresponding to the high-risk state is higher than the risk threshold, and the high-risk state includes at least one of a driver high-risk state, a vehicle body high-risk state, and an environment high-risk state;

[0056] S2. When the driving device is in the high-risk state, adjusting the operating capability of the safety system and performing corresponding stress protection actions according to the type of the high-risk state;

[0057] S3. Based on the safety system obtained in step S2, steps S1-S2 are repeatedly executed until the risk score is less than or equal to the risk threshold.

[0058] Solution 2. The stress protection method according to Solution 1 is characterized in that the safety system includes a perception module and a decision module, and the method further includes:

[0059] Acquire perception data of the driving device based on the perception module; the perception data includes cockpit perception data, vehicle body perception data and environment perception data.

[0060] Solution 3. The stress protection method according to Solution 2 is characterized in that the step of adjusting the operating capability of the safety system comprises at least one of the following:

[0061] Performing data enhancement processing on the perception data, and dynamically adjusting the perception algorithm parameters of the perception module based on the perception data after the data enhancement processing;

[0062] Optimizing the decision algorithm parameters of the decision module to control the driving device to perform the stress protection action based on the optimized decision module;

[0063] Improve the decision-making speed of the decision-making module.

[0064] Solution 4. The stress protection method according to Solution 3 is characterized in that the decision algorithm parameters for optimizing the decision module include:

[0065] Acquire new perception data in real time based on the perception module;

[0066] Dynamically adjusting a preset weight parameter corresponding to the perception data based on the new perception data;

[0067] Based on the new perception data and the dynamically adjusted preset weight parameters, the decision algorithm parameters of the decision module are adjusted.

[0068] Solution 5. The stress protection method according to Solution 3 is characterized in that the step of improving the decision speed of the decision module comprises:

[0069] Based on a multi-core processor or a distributed computing platform, the decision algorithm of the decision module is processed in parallel.

[0070] Solution 6. The stress protection method according to Solution 3 is characterized in that the safety system further includes a transmission module, and the transmission module is used to transmit the perception data acquired by the perception module to the decision module; the adjusting the operating capability of the safety system also includes:

[0071] Improve the data transmission speed of the transmission module.

[0072] Solution 7. The stress protection method according to Solution 2 is characterized in that the cockpit perception data includes the driver's attention data and health data, the body perception data includes the speed data, steering data and braking data of the driving device, and the environment perception data includes the point cloud data and image data of the environment around the driving device; and judging whether the driving device is in a high-risk state based on the safety system includes:

[0073] Obtaining the quantized value and preset weight parameter corresponding to each perception data;

[0074] Obtaining a driver risk score, a vehicle body risk score, and an environment risk score based on the quantified value and preset weight parameters;

[0075] It is determined whether the driving device is in the high-risk state based on the driver risk score, the vehicle body risk score, and the environment risk score.

[0076] Solution 8. The stress protection method according to Solution 7 is characterized in that the determining whether the driving device is in the high-risk state based on the driver risk score, the vehicle body risk score and the environment risk score comprises:

[0077] respectively determining whether the driver risk score, the vehicle body risk score, and the environment risk score are higher than the risk threshold;

[0078] When at least one of the driver risk score, the vehicle body risk score, and the environment risk score is higher than the risk threshold, it is determined that the driving device is in the high-risk state.

[0079] Solution 9. The stress protection method according to Solution 1 is characterized in that performing corresponding stress protection actions according to the type of the high-risk state includes:

[0080] Acquire stress protection action database;

[0081] Based on the type of the high-risk state, executing the corresponding stress protection action in the stress protection action database;

[0082] Among them, the stress protection actions include turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending risk notifications, turning off driving experience related functions, storing driving equipment status data and sending rescue information.

[0083] Solution 10. The stress protection method according to Solution 9 is characterized in that executing the corresponding stress protection action in the stress protection action database based on the type of the high-risk state comprises:

[0084] When the driving device is in the high-risk state for the driver, performing at least one of turning on a warning light, adjusting a seat position, tightening a seat belt, honking a horn, sending a risk notification, storing driving device state data, and sending a rescue message;

[0085] When the driving device is in the high-risk state of the vehicle body, performing at least one of turning on the warning light, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, honking the horn, sending a risk notification, storing the driving device status data, and sending a rescue message;

[0086] When the driving device is in the high-risk state of the environment, at least one of turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending a risk notification, turning off driving experience related functions, storing driving device status data and sending rescue information is executed.

[0087] Solution 11. The stress protection method according to Solution 2, characterized in that the method further comprises:

[0088] When the driving device is in the high-risk state, determining a risk scenario corresponding to the type of the high-risk state;

[0089] The corresponding stress protection action is executed based on the risk scenario.

[0090] Solution 12. The stress protection method according to Solution 11 is characterized in that the risk scenarios include driver risk scenarios, vehicle body risk scenarios and environmental risk scenarios; when the driving device is in the high-risk state, determining the risk scenario corresponding to the type of the high-risk state includes:

[0091] When the driving device is in the driver high risk state, determining the driver risk scenario based on the driver risk score;

[0092] When the driving device is in the vehicle body high risk state, determining the vehicle body risk scenario based on the vehicle body risk score;

[0093] When the driving device is in the environmental high risk state, determining the environmental risk scenario based on the environmental risk score;

[0094] Among them, the driver risk scenarios include at least distraction scenarios, fatigue scenarios and sudden illness scenarios, the body risk scenarios include at least tire blowout scenarios, side slip scenarios and accidental pedal pressing scenarios, and the environmental risk scenarios include at least collision scenarios and rollover scenarios.

[0095] Solution 13. An electronic device, comprising a processor and a memory, wherein the memory is suitable for storing multiple program codes, and wherein the program codes are suitable for being loaded and run by the processor to execute the stress protection method described in any one of Solutions 1 to 12.

[0096] Solution 14. A computer-readable storage medium storing a plurality of program codes, wherein the program codes are suitable for being loaded and run by a processor to execute the stress protection method described in any one of Solutions 1 to 12.

[0097] Solution 15. A driving device, characterized in that the driving device comprises a safety system and the electronic device according to Solution 13, wherein the safety system comprises a perception module and a decision module;

[0098] The perception module is used to obtain the perception data of the driving device; the perception data includes cockpit perception data, vehicle body perception data and environment perception data;

[0099] The decision module is used to determine whether the driving device is in a high-risk state based on the perception data.

[0100] Solution 16. The driving device according to Solution 15 is characterized in that the driving device also includes at least one of a lighting system, an active engine hood system, a passive safety system, a braking system, a high-voltage management system, an active suspension system, a horn system, a vehicle networking technology communication system, a central control system, an event data recording system, and an emergency rescue system;

[0101] Wherein, the passive safety system at least includes a seat adjustment module and a seat belt tightening module.

[0102] The above one or more technical solutions of this application have at least one or more of the following Beneficial effects:

[0103] In the technical solution for implementing the present application, the driving device includes a safety system, and the safety system includes a perception module and a decision module; the stress protection method includes: S1, judging whether the driving device is in a high-risk state based on the safety system; wherein the risk score corresponding to the high-risk state is higher than the risk threshold, and the high-risk state includes at least one of the driver high-risk state, the vehicle body high-risk state and the environment high-risk state; S2, when the driving device is in a high-risk state, adjusting the operating capacity of the safety system, and performing corresponding stress protection actions according to the type of the high-risk state; S3, based on the safety system obtained in step S2, repeatedly performing steps S1-S2 until the risk score of the driving device is less than or equal to the risk threshold. Through the above implementation, the safety system of the driving device can perceive the risk early enough, perform a series of actions before the danger occurs, and timely adjust the operating capacity of the safety system and the corresponding stress protection actions according to the perceived changes in the driving device and the environment, until the risk score is less than or equal to the risk threshold, thereby effectively reducing the accident rate in complex and changeable actual driving scenarios and ensuring the safety of vehicles and drivers and passengers. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] The disclosure of the present application will become easier to understand with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present application. Among them:

[0105] Figure 1 This is a schematic flow chart of the main steps of a stress protection method according to an embodiment of the present application;

[0106] Figure 2 is a flowchart of main steps for determining whether a driving device is in a high-risk state based on a safety system according to an embodiment of the present application;

[0107] Figure 3 This is a flowchart of main steps for executing corresponding stress protection actions according to the type of high-risk state according to an embodiment of the present application;

[0108] Figure 4 is a schematic diagram of the main process of a stress protection method according to an embodiment of the present application;

[0109] Figure 5 It is a schematic diagram of the main structure of an electronic device according to an embodiment of the present application.

[0110] List of reference numerals:

[0111] 51: processor; 52: memory. DETAILED DESCRIPTION

[0112] Some embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the protection scope of the present application.

[0113] In the description of this application, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, memories, and may also include software parts, such as program codes, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware or a combination of the two. Non-temporary computer-readable storage media include any suitable media that can store program codes, such as disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc.

[0114] The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one of A or B" or "at least one of A and B" has a similar meaning to "A and / or B" and may include only A, only B, or A and B. The singular forms "a", "the" and "the" may also include plural forms.

[0115] Here we first explain some terms involved in this application.

[0116] The biological stress system refers to a series of physiological and psychological response mechanisms that the body initiates when facing various risks to help the organism adapt to environmental changes and protect itself from harm. When the organism feels threatened, the nervous system will quickly transmit signals to the endocrine system, triggering a stress response. For example, when an animal encounters a natural enemy, the brain will immediately sense the danger and send signals to the adrenal glands through the nervous system, prompting the adrenal glands to secrete stress hormones such as adrenaline and cortisol.

[0117] As described in the background technology, the current safety system has some shortcomings. On the one hand, the protective measures it adopts are relatively simple and do not take into account how to deal with accidents when they are inevitable. On the other hand, after the system triggers relevant protective measures, the state of the driving equipment and the environment in which it is located will change, but the system cannot perceive the changes in time and make adaptive adjustments, nor can it adjust the triggered protective measures in time, which limits the role of the system in complex and changeable actual driving scenarios and makes it difficult to provide effective protection for drivers and passengers.

[0118] In order to solve the above problems, the present application is inspired by the stress system used by organisms for self-protection, and provides a stress protection method, electronic device, storage medium and driving device, which applies the natural reaction of organisms for self-protection to the safety system of driving equipment. Among them, the safety system can include a perception module, a transmission module and a decision module.

[0119] See attached Figure 1 , Figure 1 FIG. 1 is a schematic flow chart of the main steps of a stress protection method according to an embodiment of the present application. Figure 1 As shown, the stress protection method in the embodiment of the present application mainly includes the following steps S101 to S103.

[0120] Step S101: determining whether the driving device is in a high-risk state based on the safety system;

[0121] Among them, the risk score corresponding to the high-risk state is higher than the risk threshold, and the high-risk state includes at least one of a high-risk state for the driver, a high-risk state for the vehicle body, and a high-risk state for the environment.

[0122] Step S102: When the driving device is in a high-risk state, the operating capability of the safety system is adjusted, and corresponding stress protection actions are performed according to the type of the high-risk state;

[0123] Step S103: Based on the safety system obtained in step S102, the steps S101 to S102 are repeatedly executed until the risk score is less than or equal to the risk threshold.

[0124] Based on the method described in steps S101 to S103 above, the safety system of the driving device can perceive the risk early enough, perform a series of actions before the danger occurs, and timely adjust the operating capability of the safety system and the corresponding stress protection actions according to the perceived changes in the driving device and the environment until the risk score is less than or equal to the risk threshold, thereby effectively reducing the accident rate in complex and changeable actual driving scenarios and ensuring the safety of the vehicle and passengers.

[0125] The above steps 101 to S103 are further explained below.

[0126] In some implementations of step S101, when determining whether the driving device is in a high-risk state based on the safety system, the perception data of the driving device can be first obtained based on the perception module, including cockpit perception data, body perception data and environment perception data.

[0127] Specifically, the driving device is provided with multiple types of sensors, including cockpit sensors, body sensors, and environmental sensors, etc. The perception module can obtain cockpit perception data, body perception data, and environmental perception data of the driving device based on the above sensors.

[0128] Furthermore, the cockpit sensor is used to obtain cockpit perception data, mainly including driver's attention data and health data, etc. The cockpit sensor may include an occupant monitoring system (OMS), an in-vehicle camera, a seat sensor, and a seat belt sensor, etc.

[0129] Among them, OMS is a comprehensive monitoring system that can detect the driver's various conditions with the help of cameras, radars and other technical means. For example, the camera can capture the driver's facial expressions and body movements to determine whether the occupant is in a state of fatigue, or whether there are distracting behaviors such as using mobile phones and lack of concentration; radar sensors can detect the driver's vital signs, such as heart rate and breathing rate, to detect whether there is a sudden illness.

[0130] The in-car camera can be installed in a suitable position in the cockpit, such as above the center console, near the rearview mirror, etc. In addition to assisting the OMS in determining the driver's status, the in-car camera can also independently monitor the overall situation in the car and provide intuitive image information to ensure in-car safety.

[0131] Seat sensors are generally installed inside the seats. By detecting information such as pressure distribution and weight changes on the seats, they can determine whether there are passengers sitting on the seats. On the other hand, they can also assist in determining the passengers' sitting posture. For driving devices with seat adjustment functions, they can also combine other information to automatically adjust the seats to the optimal position and other operations.

[0132] Seat belt sensors are usually installed on the buckle or body of the seat belt to detect whether the seat belt is worn correctly. When the occupant fastens the seat belt, the sensor will transmit the corresponding signal. If the seat belt is unfastened or not worn properly during driving, the safety system can issue a reminder to ensure passenger safety.

[0133] The body sensor is used to obtain body perception data, mainly including the speed data, steering data and braking data of the driving equipment. The body sensor can include wheel speed sensor, tire pressure sensor, steering system sensor, power system sensor, brake system sensor, high-voltage monitoring system (mainly monitoring voltage, current, insulation resistance and other data), active safety monitoring system, passive safety monitoring system, etc.

[0134] Among them, the wheel speed sensor is usually installed near the wheel to monitor the rotation speed of the wheel in real time and convert the speed information into an electrical signal for transmission. The tire pressure sensor is generally installed inside the tire or at the valve stem, and can monitor the air pressure inside the tire in real time. The steering system sensor is located in the relevant parts of the steering mechanism, such as the steering column, steering rod, etc., and is responsible for detecting parameters such as the steering wheel's rotation angle, rotation speed, and steering torque.

[0135] Power system sensors are distributed in various key parts of the powertrain, such as the engine and transmission. For example, the engine crankshaft position sensor can monitor the crankshaft angle and speed to control the ignition timing; the throttle position sensor can detect the throttle opening, which in turn affects the engine's air intake and power output. The sensor on the transmission can monitor information such as gear status.

[0136] Braking system sensors are arranged on the brake pedal, brake lines and brake components of each wheel. The sensors on the brake pedal can detect the force and travel of the driver's pedal, while the sensors on the brake lines and wheel brake components can monitor the brake pressure, brake pad wear, etc.

[0137] The high-voltage monitoring system mainly targets the high-voltage circuit part of the driving equipment, monitoring the operating voltage, current size and insulation resistance of high-voltage components such as battery packs and motors.

[0138] The active safety monitoring system covers monitoring sensors corresponding to active safety functions such as automatic emergency braking, lane keeping assist, blind spot monitoring, etc. Among them, the automatic emergency braking system relies on sensors such as millimeter wave radar and camera to monitor obstacles in front of the vehicle, as well as the distance and relative speed to the vehicle in front; the lane keeping assist system uses the camera to identify the lane line and determine whether the vehicle deviates from the lane; the blind spot monitoring system uses radar and other sensors to detect the blind spot situation on the side and rear of the vehicle.

[0139] The passive safety monitoring system mainly includes relevant sensors that play a role when the driving equipment collides with other accidents, such as collision sensors installed on the front, sides and rear of the vehicle body. They can sense the intensity, direction and other information of the collision. When the collision reaches a certain threshold, it triggers passive safety devices such as airbag popping out and seat belt pre-tensioning to maximize the safety of the passengers in the car.

[0140] Environmental sensors are used to obtain environmental perception data, mainly including point cloud data and image data of the environment around the driving device. Cockpit sensors can include millimeter wave radar, lidar, camera and other sensors.

[0141] Among them, millimeter-wave radar can use electromagnetic waves in the millimeter-wave frequency band to detect target objects and measure information such as the distance, relative speed, and azimuth angle between the target object and the driving device.

[0142] LiDAR constructs a three-dimensional point cloud map of the surrounding environment by emitting laser beams and receiving reflected light, which can provide detailed information such as the shape, position and distance of objects around the vehicle.

[0143] Cameras are usually installed on the front, rear, sides and rearview mirrors of the driving equipment to capture image information around the vehicle from different angles, thereby identifying various target objects such as road signs (such as lane lines, traffic signs, traffic lights, etc.), other vehicles, pedestrians, non-motor vehicles, etc.

[0144] It should be pointed out that the above examples of sensors provided in driving equipment and perception data acquired by the perception module are only for illustrative purposes. In practical applications, those skilled in the art may make settings according to specific scenarios, which are not limited here.

[0145] Through the above implementation, various types of sensors can be used to monitor the status of the driver, driving equipment and surrounding environment in real time. Compared with relying solely on a single sensor or a specific system, this integration of multi-dimensional perception can provide more comprehensive data for vehicle safety.

[0146] Furthermore, after the perception module obtains the perception data of the driving device, the perception data obtained by the perception module can be transmitted to the decision module through the transmission module.

[0147] Specifically, the transmission module can transmit the perception data to the decision module through CAN, LIN, FlexRay, Ethernet, Bluetooth, Wi-Fi and other transmission methods.

[0148] In some embodiments, the transmission module must have a redundant design for the transmission of the sensing data. For example, dual-channel transmission is performed through two different lines (such as CAN bus and FlexRay bus) at the same time, or when Ethernet is used to transmit data, a backup communication link is set up, and when the main link fails, it automatically switches to the backup link to ensure the integrity of the transmitted data.

[0149] The redundant design of data transmission can increase the reliability of the system. Such redundant design is particularly important in security systems and ensures the high availability and stability of the system.

[0150] Furthermore, after the transmission module transmits the perception data to the decision module, it can determine whether the driving device is in a high-risk state based on the decision module and the perception data.

[0151] Specifically, the electronic controller (ECU) of the decision module can make risk judgments on the cockpit perception data, body perception data and environmental perception data of the driving device to determine whether the driving device is in a high-risk state.

[0152] Among them, the high-risk state means that the driving equipment may be in imminent danger, especially the danger of causing injury to people inside and outside the vehicle, such as collision, rollover, loss of control, etc.

[0153] The cockpit perception data is mainly used to determine whether the driver is distracted, fatigued, or has a sudden illness. If it is found that the driver's condition is at risk of losing the ability to drive, it is judged to be a high-risk state.

[0154] The vehicle body perception data is mainly used to determine whether the driving device itself has normal drivability and safety. If it is found that the state of the driving device (including steering, braking, acceleration, etc.) has changed, affecting the drivability and safety, it is judged to be a high-risk state.

[0155] Environmental perception data is mainly used to determine the risk of accidents between the driving equipment and the external environment (including other road users, road facilities, etc.). If a collision, rollover, etc. is found to be possible, it is judged to be a high-risk state.

[0156] For details, see the attached Figure 2 , Figure 2 1 is a flow chart of the main steps of determining whether a driving device is in a high-risk state based on a safety system according to an embodiment of the present application. Figure 2 As shown, it mainly includes the following steps S201 to S203.

[0157] Step S201: Obtaining a quantization value and a preset weight parameter corresponding to each perception data;

[0158] The quantized value corresponding to each perception data is a numerical value that can be measured and compared by converting various perception data in the driving device through certain mathematical methods or rules. This numerical value can more intuitively reflect the degree of the actual situation represented by the perception data.

[0159] For example, when the camera in the cockpit is used to monitor the direction of the driver's line of sight, the angle range in which the driver's line of sight is focused on the road directly ahead is defined as the standard range. If the camera detects that the driver's line of sight deviates from this standard range, the quantification value can be set as follows: quantification is based on the angle of the line of sight deviating from the road directly ahead. If the line of sight deviates from the angle between 0-10 degrees, the quantification value is 0 (indicating that there is basically no distraction); if the deviation angle is between 10-30 degrees, the quantification value is 0.3; if the deviation angle exceeds 30 degrees, the quantification value is 0.6 (indicating a high degree of distraction).

[0160] When using millimeter-wave radar to measure the distance between the driving device and the vehicle in front, if the safe following distance is set to greater than 5 meters, when the distance to the vehicle in front is between 5-3 meters, the quantized value is 0.3; when the distance is between 3-1 meters, the quantized value is 0.6; when the distance is less than 1 meter, the quantized value is 0.9 (indicating a high risk of collision), etc.

[0161] The quantitative values ​​provide basic data for subsequent risk assessment and decision-making. When calculating the risk score, these quantitative values ​​are combined with the corresponding preset weight parameters.

[0162] Specifically, in order to accurately evaluate the risk score of the driving device, each perception data is set with a corresponding preset weight parameter. The preset weight parameter reflects the relative importance of different perception data in risk assessment.

[0163] For example, when assessing driver risk, driver distraction (such as using a mobile phone) may be given a higher weight because it poses a greater threat to driving safety; while when assessing vehicle body risk, brake system failure may be given a higher weight.

[0164] Step S202: obtaining a driver risk score, a vehicle body risk score, and an environment risk score based on the quantified value and preset weight parameters;

[0165] Taking the calculation of driver risk score as an example, if three cockpit perception data are obtained: driver fatigue (represented by A), driver distraction (represented by B) and driver operation proficiency (represented by C), their corresponding preset weight parameters are 0.4, 0.4 and 0.2 respectively. If the quantized value corresponding to A is 0.6 (for example, 0-1 represents fatigue, 0.6 represents relatively fatigued), the quantized value corresponding to B is 0.8 (indicating more serious distraction), and the quantized value corresponding to C is 0.3 (indicating lower operation proficiency).

[0166] The decision module will calculate the driver risk score, vehicle body risk score and environmental risk score based on these perception data and their preset weight parameters.

[0167] Taking the calculation of driver risk score as an example, if three cockpit perception data are obtained: driver fatigue (represented by A), driver distraction (represented by B) and driver operation proficiency (represented by C), their corresponding preset weight parameters are 0.4, 0.4 and 0.2 respectively. If the quantized value corresponding to A is 0.6 (for example, between 0-1 represents fatigue, 0.6 represents relatively fatigued), the quantized value corresponding to B is 0.8 (indicating serious distraction), and the quantized value corresponding to C is 0.3 (indicating low operation proficiency), then the driver risk score = A×0.4+B×0.4+C×0.2=0.6×0.4+0.8×0.4+0.3×0.2=0.24+0.32+0.06=0.62.

[0168] The same method can also be used to calculate the vehicle body risk score and environmental risk score, ultimately obtaining the driver risk score, vehicle body risk score, and environmental risk score.

[0169] Step S203: Determine whether the driving device is in a high-risk state based on the driver risk score, the vehicle body risk score, and the environment risk score.

[0170] Specifically, step S203 may include the following steps S2031 to S2032.

[0171] Step S2031: determining whether the driver risk score, the vehicle body risk score and the environment risk score are higher than the risk threshold respectively;

[0172] The risk threshold is a predetermined critical value used to distinguish different risk levels. The risk threshold is usually determined based on a large amount of experimental data, accident statistical analysis or safety regulations.

[0173] Specifically, the risk score can be represented by a value between 0 and 1. The higher the risk score, the greater the possibility that the driving device is about to be dangerous.

[0174] Taking the driver risk score as an example, when the risk score is between 0-0.3, it means that the driver is in good condition and there are basically no factors that affect driving safety; when the risk score is between 0.3-0.6, it means that the driver may have some behaviors or conditions that affect driving safety and requires attention; when the risk score is 0.6 or above, it means that the driver's condition has posed a serious threat to driving safety and immediate intervention measures may be required.

[0175] Therefore, the risk threshold can be set to 0.6 points to determine whether the driver risk score, vehicle body risk score, and environment risk score are higher than 0.6 points.

[0176] Step S2032: When at least one of the driver risk score, the vehicle body risk score, and the environment risk score is higher than the risk threshold, it is determined that the driving device is in a high-risk state.

[0177] The above is a further description of step S101 , and the following is a further description of step S102 .

[0178] In some implementations of the above step S102, when the driving device is in a high-risk state, the stress protection of the safety system will be activated. At this time, the operating capability of the safety system can be adjusted to enhance the perception capability, transmission capability and decision-making capability, so that the safety system can quickly perceive, make decisions and execute after sensing the risk, thereby avoiding danger or at least reducing the harm.

[0179] Wherein, adjusting the operational capability of the security system may include at least one of the following:

[0180] a. Perform data enhancement processing on the perception data, and dynamically adjust the perception algorithm parameters of the perception module based on the perception data after data enhancement processing.

[0181] Specifically, the perception data can be filtered in real time through an efficient filtering algorithm to remove noise, and a series of data enhancement processing such as translation, rotation, and scaling can be performed on the perception data to increase the diversity and robustness of the perception data. The parameters of the perception algorithm (such as target detection algorithm, semantic segmentation algorithm, depth estimation algorithm, etc.) of the perception module can be dynamically adjusted through the perception data after data enhancement processing.

[0182] For example, when driving at high speed, the sensitivity of the target detection algorithm in the perception module can be increased to detect other vehicles and obstacles in the distance more quickly; in congested urban road conditions, the false alarm rate of the target detection algorithm can be reduced to avoid frequent false alarms affecting the driving experience.

[0183] b. Improve the data transmission speed of the transmission module.

[0184] Specifically, a more efficient data transmission method can be adopted, such as optimizing the existing vehicle network communication protocol (including CAN, Ethernet, etc.) or adopting new high-speed transmission technology to increase the speed of data transmission.

[0185] c. Optimize the decision algorithm parameters of the decision module to control the driving device to perform stress protection actions based on the optimized decision module.

[0186] In some embodiments, optimizing the decision algorithm parameters of the decision module may include the following steps 11 to 13.

[0187] Step 11: Acquire new perception data in real time based on the perception module;

[0188] Step 12: dynamically adjusting the preset weight parameters corresponding to the perception data based on the new perception data;

[0189] Since actual driving scenarios are complex and changeable, and the preset weight parameters corresponding to the perception data reflect the relative importance of different perception data in risk assessment, the preset weight parameters corresponding to the perception data can be dynamically adjusted as the actual driving scenarios change.

[0190] For example, in normal weather, good road conditions and normal driver status, the distance data between the driving device and other surrounding vehicles and pedestrians in the environmental perception data is important, but the preset weight parameter in the overall risk assessment may be relatively low; however, when encountering rainy and snowy weather and the vision is severely obstructed, the distance data becomes crucial for judging the collision risk, and accordingly it is necessary to increase its preset weight parameter in the risk assessment.

[0191] Step 13: Based on the new perception data and the dynamically adjusted preset weight parameters, adjust the decision algorithm parameters of the decision module.

[0192] The decision module relies on specific decision algorithms and corresponding parameter settings when making decisions such as determining whether the driving device is in a high-risk state and deciding what stress protection action to take. Therefore, when the driving device is in a high-risk state and new perception data and its corresponding preset weight parameters are obtained, some key parameters in the decision algorithm need to be adjusted accordingly.

[0193] For example, in a decision-making algorithm that determines the risk score of a driving device based on perception data, if new perception data determines that the braking system has some abnormal signs, and the preset weight parameters corresponding to the braking system fault data in the vehicle body perception data are increased, then when calculating the vehicle body risk score in the decision algorithm, the parameters related to the braking system need to be adjusted, such as increasing its proportion in the comprehensive assessment, so that the decision module will focus more on considering the impact of the braking system status on the overall risk assessment in subsequent operations.

[0194] If it is determined through new perception data that the current driving situation is nighttime and the road conditions are complex, the parameters regarding target recognition reliability in the vehicle's automatic emergency braking decision algorithm need to be improved, so that the system can be more rigorous in confirming the target object when deciding whether to trigger automatic emergency braking, and avoid incorrect braking due to misjudgment. This allows the entire decision logic and final decision results of the decision module to match the actual complex driving scenarios at the moment, and to more reasonably and accurately control the driving equipment to deal with various possible risk situations.

[0195] d. Improve the decision-making speed of the decision-making module.

[0196] In some implementations, the decision algorithm of the decision module may be processed in parallel based on a multi-core processor or a distributed computing platform to improve the speed of decision making.

[0197] For example, a multi-core processor can be used to divide the decision algorithm into multiple subtasks and assign them to different core processors for simultaneous calculation, thus shortening the overall calculation time. The distributed computing platform also works on a similar principle. It can distribute the decision algorithm to multiple computing nodes for simultaneous operation, so that large amounts of data processing and complex logical judgments can be carried out in parallel, further improving the calculation speed of the decision module, allowing decisions to be completed in a shorter time, thereby improving the decision speed of the decision module.

[0198] By parallelizing the decision-making algorithm, the reliability of the security system can be increased and the response speed can be improved.

[0199] The above is a further explanation of the operational capabilities of the adjustment safety system.

[0200] In some implementations of the above step S102, when the driving device is in a high-risk state and the stress protection of the safety system is activated, corresponding stress protection actions can be performed before the danger occurs according to the type of high-risk state to avoid dangerous situations.

[0201] For details, see the attached Figure 3 , Figure 3 FIG. 1 is a flow chart of the main steps of executing corresponding stress protection actions according to the type of high-risk state according to an embodiment of the present application. Figure 3 As shown, it mainly includes the following steps S301 to S302.

[0202] Step S301: Acquire a stress protection action database;

[0203] The stress protection action database is a pre-built information base that stores various specific stress protection actions for dealing with different high-risk states.

[0204] Specifically, the driving equipment may include one or more of a lighting system, an active hood system, a passive safety system, a braking system, a high-voltage management system, an active suspension system, a horn system, a vehicle networking technology communication system, a central control system, an event data recording system, and an emergency rescue system; wherein the passive safety system includes at least a seat adjustment module and a seat belt tightening module.

[0205] Furthermore, the stress protection actions in the stress protection action database include at least one of turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending risk notifications, turning off driving experience related functions, storing driving equipment status data and sending rescue information.

[0206] Among them, turning on the warning lights (double flash lights) through the lighting system can alert other driving equipment, pedestrians and other road users around that the vehicle is in a special situation, prompting them to remain vigilant, avoid in advance or take corresponding safety measures to avoid collisions and other dangerous situations, effectively reducing the possibility of road traffic accidents.

[0207] Opening the active bonnet via the active bonnet system increases the distance between the bonnet and hard points in the cabin, thereby cushioning the forces of external impact when danger is unavoidable and reducing the risk of injury.

[0208] The seat adjustment module of the passive safety system can adjust the seat position to the optimal safety position. The optimal safety position is determined after a large number of collision tests and safety studies. This position enables passive safety devices such as seat belts and airbags to play the best protective role in the event of an accident, minimizing the injuries to the occupants in the car.

[0209] Braking through the braking system is one of the most basic and important safety operations of driving equipment. When danger is predicted, braking in advance can slow down the vehicle, reduce the vehicle's kinetic energy, and thus reduce the impact energy in the event of a possible collision.

[0210] By cutting off the high voltage of non-power systems through the high-voltage management system, such as cutting off equipment such as compressors powered by high-voltage power, the risk of short circuit and thermal runaway after a collision can be reduced when a collision is unavoidable.

[0211] Tightening the seat belt through the seat belt tightening module of the passive safety system can make the seat belt fit the occupant's body, eliminate the excess gap between the seat belt and the occupant's body, and improve the effect of passive safety protection in high-risk situations.

[0212] Adjusting the suspension height through the active suspension system includes raising or lowering the suspension height. The active suspension system of the driving device can adjust the height of the driving device from the ground according to the control signal received. Changing the suspension height has different effects when facing different risk situations. For example, raising the suspension height can increase the vehicle's passability. In some cases where the road conditions are poor and the vehicle cannot avoid in time, it can prevent the vehicle chassis from scraping the ground or even getting stuck, ensuring that the vehicle can continue to drive safely; lowering the suspension height can lower the center of gravity of the vehicle, enhance the stability of the vehicle in high-speed driving, sharp turns, etc., reduce the possibility of dangerous situations such as rollovers, and enable the vehicle to maintain better handling performance when facing risks, thereby avoiding accident risks.

[0213] The horn system can alert other road users by making them aware of possible dangers and allowing them to take action in advance to avoid risks.

[0214] When risk notifications are sent through the Vehicle to Everything (V2X) communication system, other vehicles can be notified of dangerous conditions and possible accident risks can be notified to other nearby vehicles, allowing them to take measures in advance to reduce possible risks.

[0215] By shutting down driving experience-related functions, such as those related to comfort (seat heating, air conditioning, etc.) and entertainment (car audio, multimedia display, etc.), through the central control system, energy consumption can be reduced and it can be ensured that the driving equipment has sufficient energy to ensure the normal operation of key systems (such as emergency lighting, airbag triggering, rescue signal sending, etc.).

[0216] The driving device status data, including video images and other data during driving, can be stored through the driving recorder and event data recorder (EDR). These data can intuitively reflect the road conditions in front of and around the driving device, driving operations, etc., for subsequent viewing and analysis.

[0217] The rescue information sent through the emergency rescue system can include information such as vehicle location, driving direction, number of passengers in the vehicle, risk type, etc., to facilitate rescue personnel to implement rescue in dangerous situations.

[0218] It should be pointed out that the above examples of stress protection actions are only illustrative. In practical applications, those skilled in the art can make settings according to specific scenarios, which are not limited here.

[0219] The above is a further description of step S301.

[0220] Step S302: Based on the type of the high-risk state, execute a corresponding stress protection action in the stress protection action database.

[0221] Once the type of high-risk condition is determined, the safety system will search for matching stress protection actions in the stress protection action database and execute them.

[0222] Specifically, when the driving device is in a high-risk state for the driver, one or more stress protection actions may be performed, including turning on the warning light, adjusting the seat position, tightening the seat belt, honking the horn, sending a risk notification, storing the driving device status data, and sending a rescue message;

[0223] When the driving device is in a high-risk state, one or more stress protection actions can be performed, including turning on the warning light, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, honking the horn, sending risk notifications, storing the driving device status data, and sending rescue information;

[0224] When the driving device is in a high-risk environmental state, one or more stress protection actions can be performed, including turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending risk notifications, turning off driving experience-related functions, storing driving device status data, and sending rescue information.

[0225] Furthermore, in some implementations, risk scenarios can be divided into driver risk scenarios, vehicle body risk scenarios, and environmental risk scenarios according to the type of high-risk state. On this basis, the risk scenarios corresponding to each type of high-risk state can be further refined into multiple sub-scenarios to flexibly adjust response measures according to different risk scenarios.

[0226] Among them, driver risk scenarios may include distraction scenarios, fatigue scenarios and sudden illness scenarios, body risk scenarios may include tire blowout scenarios, side slip scenarios and accidental pedal pressing scenarios, and environmental risk scenarios may include collision scenarios (such as collision with pedestrians, collision with passenger cars, collision with trucks, collision with obstacles) and rollover scenarios.

[0227] Furthermore, when the driving device is in a high-risk state, a risk scenario corresponding to the type of the high-risk state may be determined, and a corresponding stress protection action may be performed based on the risk scenario.

[0228] Specifically, when the driving device is in a high-risk state for the driver, a driver risk scenario may be determined based on the driver risk score.

[0229] The driver risk score is calculated using a variety of cockpit perception data, where each type of cockpit perception data has a corresponding quantitative value and preset weight parameter. Therefore, the score of each type of cockpit perception data in the driver risk score can be obtained, thereby determining the driver risk scenario based on the score of each type of cockpit perception data.

[0230] For example, the three cockpit perception data obtained are driver fatigue data (represented by A), driver distraction data (represented by B) and driver disease data (represented by C), and the corresponding preset weight parameters are 0.3, 0.3 and 0.4 respectively. If the quantization value corresponding to A is 0.7 (for example, between 0-1 represents the degree of fatigue, and 0.6 represents relatively fatigued), the quantization value corresponding to B is 0.8 (indicating that the distraction is more serious), and the quantization value corresponding to C is 0.4 (indicating that the probability of the driver's sudden illness is low), the driver's risk score at this time is 0.61, which exceeds the risk threshold, and it can be determined that the driving device is in a high-risk driver scenario. Therefore, the risk scores of each cockpit perception data can be specifically viewed, among which the risk score of driver fatigue data is 0.21, the risk score of driver distraction data is 0.24, and the risk score of driver disease data is 0.16. At this time, it can be determined that the driver's high-risk state may be caused by driver distraction, so it is determined to be a distraction scenario in the driver risk scenario.

[0231] Similarly, when the driving device is in a high-risk state for the vehicle body, a vehicle body risk scenario can be determined based on the vehicle body risk score; when the driving device is in a high-risk state for the environment, an environmental risk scenario can be determined based on the environmental risk score.

[0232] Furthermore, corresponding stress protection actions can be executed based on risk scenarios.

[0233] For example, when the driving device is in a pedestrian collision scenario, it can simultaneously execute stress protection actions such as turning on the warning light, opening the active engine hood, braking, tightening the seat belt, honking the horn, sending risk notifications, and storing driving device status data; when the driving device is in a tire blowout scenario, it can simultaneously execute stress protection actions such as turning on the warning light, adjusting the seat position, braking, tightening the seat belt, honking the horn, sending risk notifications, storing driving device status data, and sending rescue information.

[0234] Through the above implementation mode, the driving device can "execute actions in advance", that is, a series of response measures are initiated before the danger actually occurs. This active protection mechanism is in sharp contrast to many existing passive safety systems (such as airbags triggered after a collision), which improves the safety of vehicles and personnel, and can adjust the executed stress protection actions in real time according to the detailed risk scenario classification, effectively reducing the accident rate.

[0235] The above is the description of step S102.

[0236] Furthermore, in some implementations of the above-mentioned step S103, the safety system can repeat the above-mentioned steps S101 to S102 based on the result obtained in step S102, that is, adjusting the operating capability and performing corresponding stress protection actions according to the type of high-risk state, such as dynamically adjusting the perception capability, transmission capability and decision-making capability of the safety system according to the perception data, and adjusting the executed stress protection actions in real time according to the detailed risk scenario classification, until the risk score of the driving device is less than or equal to the risk threshold, thereby effectively reducing the accident rate.

[0237] See attached Figure 4 , Figure 4 It is a main flow chart of a stress protection method according to an embodiment of the present application.

[0238] like Figure 4 As shown, during the driving process of the driving device, the safety system can obtain the perception data of the driving device in real time through the cockpit sensor, body sensor and environmental sensor of the perception module, and transmit the perception data to the decision module through the transmission module;

[0239] Furthermore, the decision module can determine whether the driving device is in a high-risk state based on the perception data, and continue to make judgments based on new perception data when the driving device is not in a high-risk state; activate the stress protection of the safety system when the driving device is in a high-risk state, including adjusting the operating capability of the safety system and performing corresponding stress protection actions according to the risk scenario, until the risk score of the driving device is less than or equal to the risk threshold.

[0240] Through the above-mentioned implementation mode, the safety system of the driving device can perceive the risk early enough, so that there is as much time as possible to execute a series of actions before the danger occurs to deal with possible risks, and according to the perceived changes in the driving device and the environment, timely adjust the operating capabilities of the safety system and the corresponding stress protection actions until the risk score is less than or equal to the risk threshold, thereby effectively reducing the accident rate in complex and changeable actual driving scenarios and ensuring the safety of the vehicle and passengers.

[0241] The above is an explanation of the stress protection method provided in this application.

[0242] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that in order to achieve the effect of the present application, different steps do not have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present application.

[0243] It is understood by those skilled in the art that all or part of the processes in the method for implementing the above-mentioned embodiment of the present application can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device, medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal and software distribution medium, etc. that can carry the computer program code.

[0244] Furthermore, the present application also provides an electronic device. Figure 5 , Figure 5 Schematic diagram of the main structure of an electronic device according to an embodiment of the present application. Figure 5 As shown, the electronic device in the embodiment of the present application mainly includes a processor 501 and a memory 502. The memory 502 can be configured to store a program for executing the stress protection method of the above method embodiment, and the processor 501 can be configured to execute the program in the memory 502, which includes but is not limited to the program for executing the stress protection method of the above method embodiment. For ease of explanation, only the part related to the embodiment of the present application is shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application.

[0245] In some possible implementations of the present application, the electronic device may include multiple processors 501 and multiple memories 502. The program for executing the stress protection method of the above method embodiment may be divided into multiple subprograms, and each subprogram may be loaded and run by the processor 501 to execute different steps of the stress protection method of the above method embodiment. Specifically, each subprogram may be stored in different memories 502, respectively, and each processor 501 may be configured to execute programs in one or more memories 502 to jointly implement the stress protection method of the above method embodiment, that is, each processor 501 executes different steps of the stress protection method of the above method embodiment, respectively, to jointly implement the stress protection method of the above method embodiment.

[0246] The above-mentioned multiple processors 501 may be processors deployed on the same device. For example, the above-mentioned electronic device may be a high-performance device composed of multiple processors, and the above-mentioned multiple processors 501 may be processors configured on the high-performance device. In addition, the above-mentioned multiple processors 501 may also be processors deployed on different devices. For example, the above-mentioned electronic device may be a server cluster, and the above-mentioned multiple processors 501 may be processors on different servers in the server cluster, or the above-mentioned computer device may be a driving device cluster, and the above-mentioned multiple processors 501 may be processors on different driving devices in the driving device cluster.

[0247] Furthermore, the present application also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present application, the computer-readable storage medium can be configured to store a program for executing the stress protection method of the above-mentioned method embodiment, and the program can be loaded and run by the processor to implement the above-mentioned stress protection method. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The computer-readable storage medium can be a memory device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present application is a non-temporary computer-readable storage medium.

[0248] Furthermore, the present application also provides a driving device.

[0249] The driving device includes a safety system and the electronic device described in the technical solution of the electronic device. The safety system includes a perception module and a decision module.

[0250] In some implementations, the perception module is used to obtain perception data of the driving device; the perception data includes cockpit perception data, vehicle body perception data, and environment perception data.

[0251] The decision module is used to determine whether the driving device is in a high-risk state based on the perception data.

[0252] In some embodiments, the security system further includes a transmission module, and the transmission module is used to transmit the perception data acquired by the perception module to the decision module.

[0253] In some embodiments, the driving device also includes a lighting system, an active hood system, a passive safety system, a braking system, a high-voltage management system, an active suspension system, a horn system, a vehicle networking technology communication system, a central control system, an event data recording system and an emergency rescue system; wherein the passive safety system includes at least a seat adjustment module and a seat belt tightening module.

[0254] The above system can perform corresponding stress protection actions according to the type of high-risk status, including turning on warning lights, opening the active engine hood, adjusting seat position, braking, cutting off non-power system high voltage, tightening seat belts, adjusting suspension height, honking the horn, sending risk notifications, turning off driving experience-related functions, storing driving equipment status data and sending rescue information.

[0255] It should be noted that the relevant user personal information that may be involved in the various embodiments of the present application is strictly in accordance with the requirements of laws and regulations, following the principles of legality, legitimacy and necessity, based on the reasonable purposes of business scenarios, to process the personal information that users actively provide during the use of products / services or generated due to the use of products / services, as well as the personal information obtained with the user's authorization.

[0256] The user personal information processed by this application will vary depending on the specific product / service scenario, and shall be based on the specific scenario in which the user uses the product / service. It may involve the user's account information, personal information, device information, driving information, vehicle information or other related information. This application will treat the user's personal information and its processing with a high degree of diligence.

[0257] This application attaches great importance to the security of user personal information and has taken reasonable and feasible security protection measures that meet industry standards to protect user information and prevent personal information from being accessed, disclosed, used, modified, damaged or lost without authorization.

[0258] So far, the technical solution of the present application has been described in conjunction with an embodiment shown in the accompanying drawings, but it is easy for those skilled in the art to understand that the protection scope of the present application is obviously not limited to these specific embodiments. Without departing from the principles of the present application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present application.

Claims

1. A stress protection method, applied to driving equipment, characterized in that: The driving device includes a safety system, and the method includes: S1. Determining whether the driving device is in a high-risk state based on the safety system; wherein the risk score corresponding to the high-risk state is higher than the risk threshold, and the high-risk state includes at least one of a driver high-risk state, a vehicle body high-risk state, and an environment high-risk state; S2. When the driving device is in the high-risk state, adjusting the operating capability of the safety system and performing corresponding stress protection actions according to the type of the high-risk state; S3. Based on the safety system obtained in step S2, steps S1-S2 are repeatedly executed until the risk score is less than or equal to the risk threshold.

2. The stress protection method according to claim 1, characterized in that: The security system includes a perception module and a decision module, and the method further includes: The perception data of the driving device is acquired based on the perception module; the perception data includes cockpit perception data, vehicle body perception data and environment perception data.

3. The stress protection method according to claim 2, characterized in that: The adjusting the operational capability of the safety system comprises at least one of the following: Performing data enhancement processing on the perception data, and dynamically adjusting the perception algorithm parameters of the perception module based on the perception data after the data enhancement processing; Optimizing the decision algorithm parameters of the decision module to control the driving device to perform the stress protection action based on the optimized decision module; Improve the decision-making speed of the decision-making module.

4. The stress protection method according to claim 3, characterized in that: The decision algorithm parameters for optimizing the decision module include: Acquire new perception data in real time based on the perception module; Dynamically adjusting a preset weight parameter corresponding to the perception data based on the new perception data; Based on the new perception data and the dynamically adjusted preset weight parameters, the decision algorithm parameters of the decision module are adjusted.

5. The stress protection method according to claim 3, characterized in that: Improving the decision speed of the decision module includes: Based on a multi-core processor or a distributed computing platform, the decision algorithm of the decision module is processed in parallel.

6. The stress protection method according to claim 3, characterized in that: The security system further includes a transmission module, which is used to transmit the perception data acquired by the perception module to the decision module; and the step of adjusting the operating capability of the security system further includes: Improve the data transmission speed of the transmission module.

7. The stress protection method according to claim 2, characterized in that: The cockpit perception data includes the driver's attention data and health data, the body perception data includes the speed data, steering data and braking data of the driving device, and the environment perception data includes the point cloud data and image data of the environment around the driving device; The determining whether the driving device is in a high-risk state based on the safety system includes: Obtaining the quantized value and preset weight parameter corresponding to each perception data; Obtaining a driver risk score, a vehicle body risk score, and an environment risk score based on the quantified value and a preset weight parameter; It is determined whether the driving device is in the high-risk state based on the driver risk score, the vehicle body risk score, and the environment risk score.

8. The stress protection method according to claim 7, characterized in that: The determining whether the driving device is in the high-risk state based on the driver risk score, the vehicle body risk score and the environment risk score comprises: respectively determining whether the driver risk score, the vehicle body risk score, and the environment risk score are higher than the risk threshold; When at least one of the driver risk score, the vehicle body risk score, and the environment risk score is higher than the risk threshold, it is determined that the driving device is in the high-risk state.

9. The stress protection method according to claim 1, characterized in that: The performing of corresponding stress protection actions according to the type of the high-risk state includes: Acquire stress protection action database; Based on the type of the high-risk state, executing the corresponding stress protection action in the stress protection action database; Among them, the stress protection actions include turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending risk notifications, turning off driving experience related functions, storing driving equipment status data and sending rescue information.

10. The stress protection method according to claim 9, characterized in that: The executing the corresponding stress protection action in the stress protection action database based on the type of the high-risk state includes: When the driving device is in the high-risk state for the driver, performing at least one of turning on a warning light, adjusting a seat position, tightening a seat belt, honking a horn, sending a risk notification, storing driving device state data, and sending a rescue message; When the driving device is in the high-risk state of the vehicle body, performing at least one of turning on the warning light, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, honking the horn, sending a risk notification, storing the driving device status data, and sending a rescue message; When the driving device is in the high-risk state of the environment, at least one of turning on the warning light, opening the active engine hood, adjusting the seat position, braking, cutting off the non-power system high voltage, tightening the seat belt, adjusting the suspension height, honking the horn, sending a risk notification, turning off driving experience related functions, storing driving device status data and sending rescue information is executed.

Images