A safety warning method and system for automatic driving of a vehicle

Abstract

The present invention relates to a safety warning method and system for automatic driving of a vehicle, the method comprising: obtaining the surrounding environment information of the automatic driving vehicle, determining the urgency of the vehicle based on the analysis of the surrounding environment information, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of obstacles; obtaining the driver's state information within the current preset time period, determining the driver's current driving attention based on the analysis of the driver's state information; generating a safety degree based on the urgency of the vehicle and the current driving attention, and executing a corresponding safety prompt instruction based on the safety degree. The present invention determines whether to generate a safety prompt instruction based on the actual driving state of the driver and the urgency of the vehicle, provides a flexible prompt mode, reduces unnecessary prompts based on the actual driving state, and ensures driving safety at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle automatic driving, and in particular to a safety warning method and system for vehicle automatic driving. Background Art

[0002] The safety warning system for autonomous driving is a comprehensive system that integrates multiple sensors, algorithms and interactive interfaces. It aims to improve the safety performance of autonomous driving vehicles and provide all-round driving safety protection for drivers and passengers. The system uses radar, LiDAR, high-definition cameras and other sensor devices to obtain real-time environmental information around the vehicle. After processing and analyzing these sensor data, the system can identify potential dangerous situations, such as impending collisions, vehicles driving illegally, etc., and conduct real-time risk assessment. Based on the results of the risk assessment, the safety warning system will generate prompt information. However, the existing safety warning system for autonomous driving vehicles has certain limitations. When the system detects risks, it usually generates fixed prompt information, which is less flexible. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention proposes a safety warning method and system for automatic driving of a vehicle.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A safety warning method for automatic driving of a vehicle, the method comprising the following steps:

[0006] Obtaining information about the surrounding environment of the autonomous driving vehicle, and determining the urgency of the autonomous driving vehicle based on the analysis of the surrounding environment information, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of obstacles;

[0007] Acquire the driver's state information within a current preset time period, and analyze and determine the driver's current driving attention according to the driver's state information;

[0008] A safety level is generated according to the urgency of the vehicle and the current driving attention, and a corresponding safety prompt instruction is executed according to the safety level.

[0009] As a further technical solution of the present invention, the step of obtaining the surrounding environment information of the autonomous driving vehicle and determining the urgency of the autonomous vehicle according to the surrounding environment information includes:

[0010] Obtaining the surrounding environment information of the autonomous driving vehicle, and predicting the future trajectory of the obstacle based on the monitored surrounding environment information and a preset trajectory prediction model, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of the obstacle, and the types of obstacles include vehicles, pedestrians, animals and other static objects. The urgency of the autonomous vehicle measures the time when the autonomous vehicle is about to collide with other obstacles;

[0011] Determine the future trajectory of the vehicle according to the current vehicle status information and the navigation instructions of the automatic driving system, wherein the current vehicle status information includes the current vehicle position, speed, acceleration and moving direction;

[0012] Comparing the future trajectory of the ego vehicle with the future trajectory of the obstacle to find the closest point between them, and calculating the expected time required for the collision between the ego vehicle and the obstacle based on the position and speed of the closest point;

[0013] The calculated estimated time required for collision is compared with the preset urgency table to match the urgency of the vehicle, wherein the preset urgency table includes a number of urgency levels and corresponding time intervals required for collision set in pairs. The smaller the estimated time required for collision, the greater the possibility of collision, and the higher the urgency of the vehicle.

[0014] As a further technical solution of the present invention, the step of obtaining the driver status information within the current preset time period and analyzing and determining the driver's current driving attention according to the driver status information includes:

[0015] Acquiring driver status information within a current preset time period, wherein the driver status information includes hand status information and sight status information;

[0016] Based on the driver status information, a preset driver attention table is traversed to match and obtain attention values ​​corresponding to each status information in the driver status information, wherein the preset driver attention table includes a plurality of attention values ​​and status information corresponding thereto which are set in pairs;

[0017] The current driving attention is obtained by summing up the attention values ​​of each state information in the driver state information.

[0018] As a further technical solution of the present invention, the step of generating a safety degree according to the urgency of the vehicle and the current driving attention, and executing a corresponding safety prompt instruction according to the safety degree includes:

[0019] Calculate the ratio between the current driving attention and the urgency of the vehicle to obtain the safety degree, wherein the safety degree=current driving attention / the urgency of the vehicle;

[0020] When the safety level is not lower than a first preset threshold, no safety prompt instruction is generated;

[0021] When the safety end is greater than the second preset threshold and less than the first preset threshold, matching and executing a first safety prompt instruction, the first safety prompt instruction includes a voice prompt instruction, and reminding the driver to improve driving attention according to the voice prompt instruction;

[0022] When the safety end is not higher than a second preset threshold, a second safety prompt instruction is matched and executed, where the second safety prompt instruction includes a voice prompt instruction and a temperature reduction prompt instruction.

[0023] As a further technical solution of the present invention, a method for determining the temperature reduction in the cooling prompt instruction is: obtaining the current position information of the vehicle, obtaining the weather information of the current position of the vehicle based on the current position information of the vehicle, the weather information including temperature information, when the temperature information in the weather information is not lower than a preset temperature threshold, lowering the air-conditioning temperature in the vehicle so that the air-conditioning temperature of the vehicle is adjusted to a first preset temperature; when the temperature information is lower than the preset temperature threshold, lowering the air-conditioning temperature in the vehicle so that the air-conditioning temperature of the vehicle is adjusted to a second preset temperature.

[0024] Another object of an embodiment of the present invention is to provide a safety warning system for automatic driving of a vehicle, the system comprising:

[0025] The urgency determination module is used to obtain the surrounding environment information of the autonomous driving vehicle and determine the urgency of the autonomous driving vehicle according to the surrounding environment information, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of obstacles;

[0026] An attention determination module is used to obtain the driver's state information within a current preset period, and to analyze and determine the driver's current driving attention according to the driver's state information;

[0027] The safety prompt module is used to generate a safety level according to the urgency of the vehicle and the current driving attention, and execute a corresponding safety prompt instruction according to the safety level.

[0028] As a further technical solution of the present invention, the urgency determination module includes:

[0029] An obstacle trajectory determination unit is used to obtain the surrounding environment information of the autonomous driving vehicle, and predict the future trajectory of the obstacle based on the monitored surrounding environment information and a preset trajectory prediction model, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of the obstacle, and the types of obstacles include vehicles, pedestrians, animals and other static objects. The urgency of the self-driving vehicle measures the time when the self-driving vehicle is about to collide with other obstacles;

[0030] A self-vehicle trajectory determination unit, used to determine the future trajectory of the self-vehicle according to the current vehicle state information and the navigation instruction of the automatic driving system, wherein the current vehicle state information includes the current vehicle position, speed, acceleration and moving direction;

[0031] A trajectory comparison unit, used for comparing the future trajectory of the ego vehicle with the future trajectory of the obstacle, finding the closest point between them, and calculating the expected time required for the collision between the ego vehicle and the obstacle according to the position and speed of the closest point;

[0032] The urgency determination unit is used to compare the calculated estimated time required for collision with a preset urgency table to match the urgency of the vehicle, wherein the preset urgency table includes a number of urgency levels and corresponding time intervals required for collision set in pairs. The smaller the estimated time required for collision, the greater the possibility of collision, and the higher the urgency of the vehicle.

[0033] As a further technical solution of the present invention, the attention determination module includes:

[0034] A state information acquisition unit, used to acquire the driver's state information within a current preset time period, wherein the driver's state information includes hand state information, sight state information and physiological state information, wherein the hand state information includes whether the driver's hands are off the steering wheel, the sight state information refers to whether the time the driver's sight is fixed on the road per unit time exceeds a preset time threshold, and the physiological state information refers to whether a physiological signal exceeds a preset signal threshold, and the physiological signal includes a breathing signal;

[0035] an attention matching unit, configured to traverse a preset driver attention table based on the driver state information, and match and obtain attention values ​​corresponding to each state information in the driver state information, wherein the preset driver attention table includes a plurality of attention values ​​and state information corresponding thereto, which are arranged in pairs;

[0036] The attention calculation unit is used to calculate the sum of the attention values ​​of each state information in the driver state information to obtain the current driving attention.

[0037] As a further technical solution of the present invention, the safety prompt module includes:

[0038] A safety degree calculation unit, used for calculating the ratio between the current driving attention degree and the urgency degree of the own vehicle, to obtain the safety degree, wherein the safety degree=current driving attention degree / the urgency degree of the own vehicle;

[0039] A first comparison unit, configured to not generate a safety prompt instruction when the safety level is not lower than a first preset threshold;

[0040] A second comparison unit is configured to match and execute a first safety prompt instruction when the safety end is greater than a second preset threshold and less than a first preset threshold, wherein the first safety prompt instruction includes a voice prompt instruction, and the driver is reminded to improve driving attention according to the voice prompt instruction;

[0041] The third comparison unit is used to match and execute a second safety prompt instruction when the safety end is not higher than a second preset threshold, and the second safety prompt instruction includes a voice prompt instruction and a temperature reduction prompt instruction.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a safety warning method and system in the field of vehicle automatic driving that is more flexible and in line with the actual driving status. In the present invention, the surrounding environment information of the automatic driving vehicle is first obtained to determine the urgency of the vehicle. On the basis of determining the urgency of the vehicle, the present invention further determines the current driving attention of the driver, and then calculates the current safety level according to the current driving attention of the driver and the urgency of the vehicle. Finally, it determines whether to generate a safety prompt instruction according to the current safety level, thereby realizing the determination of whether to generate a safety prompt instruction according to the actual driving status of the driver and the urgency of the vehicle, providing a flexible prompt mode, reducing unnecessary prompts on the basis of being in line with the actual driving status, and ensuring driving safety at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The present invention is a flowchart of a safety warning method for automatic driving of a vehicle.

[0044] Figure 2 The present invention is a flowchart of the step of matching target operation data in a safety warning method for vehicle autonomous driving.

[0045] Figure 3 The present invention is a flowchart of the steps of judging the urgency of a vehicle in a safety warning method for automatic driving of a vehicle.

[0046] Figure 4 The present invention is a flowchart of the steps of judging the current attention level of a driver in a safety warning method for automatic vehicle driving.

[0047] Figure 5 The present invention is a structural block diagram of a safety warning system for automatic driving of a vehicle. DETAILED DESCRIPTION

[0048] The technical solution of this patent is further described in detail below in conjunction with specific implementation methods.

[0049] like Figure 1 As shown, an embodiment of the present invention provides a safety warning method for automatic driving of a vehicle, the method comprising the following steps:

[0050] Step S100, obtaining the surrounding environment information of the autonomous driving vehicle, and determining the urgency of the autonomous vehicle according to the surrounding environment information, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of obstacles, the types of obstacles include vehicles, pedestrians, animals and other static objects, and the urgency of the autonomous vehicle measures the time when the autonomous vehicle is about to collide with other obstacles;

[0051] Step S200, obtaining the driver's state information within the current preset time period, and analyzing and determining the driver's current driving attention according to the driver's state information;

[0052] Step S300, generating a safety level according to the vehicle urgency and current driving attention, and executing a corresponding safety prompt instruction according to the safety level.

[0053] The embodiment of the present invention is a safety warning method that is activated only when the vehicle uses automatic driving. In this embodiment, the surrounding environment information of the automatic driving vehicle is first obtained to determine the urgency of the vehicle. On the basis of determining the urgency of the vehicle, the present invention further determines the driver's current driving attention, and then calculates the current safety level based on the driver's current driving attention and the urgency of the vehicle. Finally, it is determined whether to generate a safety prompt instruction based on the current safety level. This realizes the determination of whether to generate a safety prompt instruction based on the driver's actual driving state and the urgency of the vehicle. The present invention reduces unnecessary prompts on the basis of fitting the actual driving state, while ensuring driving safety.

[0054] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of obtaining the surrounding environment information of the autonomous driving vehicle and determining the urgency of the autonomous vehicle according to the surrounding environment information includes:

[0055] Step S101, obtaining the surrounding environment information of the autonomous driving vehicle, and predicting the future trajectory of the obstacle based on the monitored surrounding environment information and a preset trajectory prediction model, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of the obstacle, the types of obstacles include vehicles, pedestrians, animals and other static objects, and the urgency of the autonomous vehicle measures the time when the autonomous vehicle is about to collide with other obstacles;

[0056] Among them, the trajectory prediction model will adopt a variety of technologies, including but not limited to deep learning, machine learning, computer vision, and physical models. Some models will use LSTM (long short-term memory) networks to learn and predict the future trajectory of obstacles. This is the existing technology in this field and is not specifically described or limited in the present invention.

[0057] Step S102, determining the future trajectory of the vehicle according to the current vehicle status information and the navigation instruction of the automatic driving system, wherein the current vehicle status information includes the current vehicle position, speed, acceleration and moving direction;

[0058] Among them, the navigation instructions of the autonomous driving system will provide a historical preset planned route. According to the current vehicle status information and the historical preset planned route provided by the navigation instructions, the future trajectory of the vehicle can be further determined.

[0059] Step S103, comparing the future trajectory of the ego vehicle with the future trajectory of the obstacle, finding the closest point between them, and calculating the expected collision time between the ego vehicle and the obstacle according to the position and speed of the closest point;

[0060] Step S104, comparing the calculated estimated time required for collision with a preset urgency table to obtain the urgency of the vehicle, wherein the preset urgency table includes a number of paired urgency levels and corresponding time intervals required for collision. The smaller the estimated time required for collision, the greater the possibility of collision, and the higher the urgency of the vehicle.

[0061] In this embodiment, by predicting and comparing the future trajectory of the obstacle and the future trajectory of the vehicle, the estimated time required for the collision between the vehicle and the obstacle can be further determined, and the urgency of the vehicle can be further determined based on the estimated time required for the collision.

[0062] like Figure 3 As shown, as a preferred embodiment of the present invention, the step of obtaining the driver status information within the current preset time period and analyzing and determining the driver's current driving attention according to the driver status information includes:

[0063] Step S201, obtaining the driver status information within the current preset time period, wherein the driver status information includes hand status information and sight status information, and may also include physiological status information, wherein the hand status information includes whether the driver's hands are off the steering wheel, the sight status information refers to whether the time the driver's sight is focused on the road per unit time exceeds a preset time threshold, and the physiological status information refers to whether a physiological signal exceeds a preset signal threshold, and the physiological signal includes a breathing signal;

[0064] Among them, for the hand status information, that is, to determine whether the driver's hands are off the steering wheel, the hand-off detection function can be used. This function can be realized through a variety of sensor technologies, such as steering torque sensing technology, capacitive sensor measurement technology, pressure sensor technology, and camera image recognition technology. Steering torque sensing technology makes judgments by measuring the magnitude and direction of the torque applied by the driver on the steering wheel. Capacitive sensor measurement technology and pressure sensor technology determine whether the driver is holding the steering wheel by detecting changes in capacitance or pressure on the steering wheel. Camera image recognition technology determines whether the driver is holding the steering wheel by analyzing the captured image of the driver's hand.

[0065] The sight state information, that is, whether the time the driver looks at the road in a unit of time exceeds the preset time threshold, can usually be achieved through the DMS driver monitoring system. This system obtains the driver's eye state in real time by installing optical cameras and infrared cameras on the car, and then analyzes the acquired information through deep learning algorithms to determine the driver's sight state. Since the characteristics of infrared light can penetrate the lens, the blocked eye information can also be imaged normally, so this system can effectively solve the problem of reflection from the driver's glasses.

[0066] As for physiological status information, especially the acquisition of physiological signals such as breathing signals, millimeter wave radar technology can be used. By using millimeter wave radar sensors, human life parameters are detected by microwaves in the form of pulses. After demodulation, integration, amplification, filtering and other processing of the echo pulse sequence reflected by the human body, the data parameters of human existence can be obtained. The radar sensor can identify the heartbeat and breathing movements of the human chest and abdomen, and is suitable for detecting the driver's breathing signals in the car.

[0067] Step S202, traversing a preset driver attention table based on the driver status information, matching and obtaining attention values ​​corresponding to each status information in the driver status information, wherein the preset driver attention table includes a plurality of attention values ​​and status information corresponding thereto set in pairs;

[0068] Step S203: The sum of the attention values ​​of each state information in the driver state information is calculated to obtain the current driving attention.

[0069] In this embodiment, by acquiring the driver's status information through real-time monitoring, the driver's current driving attention can be further matched. The technical solution provided in the present invention fits the driver's actual driving status.

[0070] like Figure 4As shown, as a preferred embodiment of the present invention, the step of generating a safety degree according to the urgency of the vehicle and the current driving attention, and executing a corresponding safety prompt instruction according to the safety degree includes:

[0071] Step S301, calculating the ratio between the current driving attention and the urgency of the vehicle to obtain the safety degree, wherein the safety degree = current driving attention / urgency of the vehicle;

[0072] Step S302: when the safety level is not lower than the first preset threshold, no safety prompt instruction is generated;

[0073] Step S303, when the safety end is greater than the second preset threshold and less than the first preset threshold, matching and executing a first safety prompt instruction, wherein the first safety prompt instruction includes a voice prompt instruction, and reminding the driver to improve driving attention according to the voice prompt instruction;

[0074] Step S304, when the safety end is not higher than the second preset threshold, match and execute the second safety prompt instruction, the second safety prompt instruction includes a voice prompt instruction and a temperature reduction prompt instruction.

[0075] Among them, the method for determining the temperature reduction in the cooling prompt instruction is: obtaining the current position information of the vehicle, obtaining the weather information of the current position of the vehicle according to the current position information of the vehicle, the weather information including temperature information, when the temperature information in the weather information is not lower than the preset temperature threshold, lowering the air-conditioning temperature in the vehicle so that the air-conditioning temperature of the vehicle is adjusted to the first preset temperature; when the temperature information is lower than the preset temperature threshold, lowering the air-conditioning temperature in the vehicle so that the air-conditioning temperature of the vehicle is adjusted to the second preset temperature. In this embodiment, the safety prompt instruction can effectively increase the driver's attention to the road.

[0076] In this embodiment, it is further explained that the present invention calculates the current safety level based on the driver's current driving attention and the urgency of the vehicle, and finally determines whether to generate a safety prompt instruction based on the current safety level. This realizes the determination of whether to generate a safety prompt instruction based on the driver's actual driving status and the urgency of the vehicle, provides a flexible prompt mode, reduces unnecessary prompts based on the actual driving status, and ensures driving safety at the same time.

[0077] like Figure 5 As shown, another object of the embodiment of the present invention is to provide a safety warning system for automatic driving of a vehicle, the system comprising:

[0078] The urgency determination module 100 is used to obtain the surrounding environment information of the autonomous driving vehicle and determine the urgency of the autonomous driving vehicle according to the surrounding environment information, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of obstacles;

[0079] The attention determination module 200 is used to obtain the driver's state information within the current preset period, and to analyze and determine the driver's current driving attention according to the driver's state information;

[0080] The safety prompt module 300 is used to generate a safety level according to the urgency of the vehicle and the current driving attention, and execute a corresponding safety prompt instruction according to the safety level.

[0081] As a preferred embodiment of the present invention, the urgency determination module 100 includes:

[0082] An obstacle trajectory determination unit is used to obtain the surrounding environment information of the autonomous driving vehicle, and predict the future trajectory of the obstacle based on the monitored surrounding environment information and a preset trajectory prediction model, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of the obstacle, and the types of obstacles include vehicles, pedestrians, animals and other static objects. The urgency of the self-driving vehicle measures the time when the self-driving vehicle is about to collide with other obstacles;

[0083] A self-vehicle trajectory determination unit, used to determine the future trajectory of the self-vehicle according to the current vehicle state information and the navigation instruction of the automatic driving system, wherein the current vehicle state information includes the current vehicle position, speed, acceleration and moving direction;

[0084] A trajectory comparison unit, used for comparing the future trajectory of the ego vehicle with the future trajectory of the obstacle, finding the closest point between them, and calculating the expected time required for the collision between the ego vehicle and the obstacle according to the position and speed of the closest point;

[0085] The urgency determination unit is used to compare the calculated estimated time required for collision with a preset urgency table to match the urgency of the vehicle, wherein the preset urgency table includes a number of urgency levels and corresponding time intervals required for collision set in pairs. The smaller the estimated time required for collision, the greater the possibility of collision, and the higher the urgency of the vehicle.

[0086] As a preferred embodiment of the present invention, the attention determination module 200 includes:

[0087] A state information acquisition unit, used to acquire the driver's state information within a current preset time period, wherein the driver's state information includes hand state information, sight state information and physiological state information, wherein the hand state information includes whether the driver's hands are off the steering wheel, the sight state information refers to whether the time the driver's sight is fixed on the road per unit time exceeds a preset time threshold, and the physiological state information refers to whether a physiological signal exceeds a preset signal threshold, and the physiological signal includes a breathing signal;

[0088] an attention matching unit, configured to traverse a preset driver attention table based on the driver state information, and match and obtain attention values ​​corresponding to each state information in the driver state information, wherein the preset driver attention table includes a plurality of attention values ​​and state information corresponding thereto, which are arranged in pairs;

[0089] The attention calculation unit is used to calculate the sum of the attention values ​​of each state information in the driver state information to obtain the current driving attention.

[0090] As a preferred embodiment of the present invention, the safety prompt module 300 includes:

[0091] A safety degree calculation unit, used for calculating the ratio between the current driving attention degree and the urgency degree of the own vehicle, to obtain the safety degree, wherein the safety degree=current driving attention degree / the urgency degree of the own vehicle;

[0092] A first comparison unit, configured to not generate a safety prompt instruction when the safety level is not lower than a first preset threshold;

[0093] A second comparison unit is configured to match and execute a first safety prompt instruction when the safety end is greater than a second preset threshold and less than a first preset threshold, wherein the first safety prompt instruction includes a voice prompt instruction, and the driver is reminded to improve driving attention according to the voice prompt instruction;

[0094] The third comparison unit is used to match and execute a second safety prompt instruction when the safety end is not higher than a second preset threshold, and the second safety prompt instruction includes a voice prompt instruction and a temperature reduction prompt instruction.

[0095] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0096] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A safety warning method for automatic vehicle driving, characterized in that: The method comprises the following steps: Obtaining information about the surrounding environment of the autonomous driving vehicle, and determining the urgency of the autonomous driving vehicle based on the analysis of the surrounding environment information, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of obstacles; Acquire the driver's state information within the current preset time period, and analyze and determine the driver's current driving attention according to the driver's state information; Generate a safety degree according to the urgency of the vehicle and the current driving attention, and execute a corresponding safety prompt instruction according to the safety degree; The step of obtaining the driver status information within the current preset time period and analyzing and determining the driver's current driving attention according to the driver status information comprises: Acquiring driver status information within a current preset time period, wherein the driver status information includes hand status information and sight status information; Based on the driver status information, a preset driver attention table is traversed to match and obtain attention values ​​corresponding to each status information in the driver status information, wherein the preset driver attention table includes a plurality of attention values ​​and status information corresponding thereto which are set in pairs; The sum of the attention values ​​of each state information in the driver state information is calculated to obtain the current driving attention; The step of generating a safety degree according to the vehicle urgency and the current driving attention, and executing a corresponding safety prompt instruction according to the safety degree comprises: Calculate the ratio between the current driving attention and the urgency of the vehicle to obtain the safety degree, wherein the safety degree=current driving attention / the urgency of the vehicle; When the safety level is not lower than a first preset threshold, no safety prompt instruction is generated; When the safety level is greater than the second preset threshold and less than the first preset threshold, matching and executing a first safety prompt instruction, wherein the first safety prompt instruction includes a voice prompt instruction; When the safety level is not higher than a second preset threshold, a second safety prompt instruction is matched and executed, where the second safety prompt instruction includes a voice prompt instruction and a temperature reduction prompt instruction.

2. A safety warning method for automatic vehicle driving according to claim 1, characterized in that: The step of obtaining the surrounding environment information of the autonomous driving vehicle and determining the urgency of the autonomous vehicle according to the surrounding environment information includes: Obtaining information about the surrounding environment of the autonomous driving vehicle, and predicting the future trajectory of obstacles based on the monitored surrounding environment information and a preset trajectory prediction model; Determine the future trajectory of the vehicle according to the current vehicle status information and the navigation instructions of the automatic driving system, wherein the current vehicle status information includes the current vehicle position, speed, acceleration and moving direction; Comparing the future trajectory of the ego vehicle with the future trajectory of the obstacle to find the closest point between them, and calculating the expected time required for the collision between the ego vehicle and the obstacle based on the position and speed of the closest point; The calculated estimated time required for collision is compared with a preset urgency table to match the urgency of the vehicle, wherein the preset urgency table includes a plurality of urgency levels set in pairs and the corresponding time intervals required for collision.

3. A safety warning method for automatic vehicle driving according to claim 1, characterized in that: The method for determining the temperature reduction in the cooling prompt instruction is: obtaining the current position information of the vehicle, obtaining the weather information of the current position of the vehicle based on the current position information of the vehicle, the weather information including temperature information, when the temperature information in the weather information is not lower than a preset temperature threshold, lowering the air-conditioning temperature in the vehicle so that the air-conditioning temperature of the vehicle is adjusted to a first preset temperature; when the temperature information is lower than the preset temperature threshold, lowering the air-conditioning temperature in the vehicle so that the air-conditioning temperature of the vehicle is adjusted to a second preset temperature.

4. A safety warning system for automatic vehicle driving, characterized in that: The system comprises: The urgency determination module is used to obtain the surrounding environment information of the autonomous driving vehicle and determine the urgency of the autonomous driving vehicle according to the surrounding environment information, wherein the surrounding environment information includes the type, position, speed, acceleration and moving direction of obstacles; An attention determination module is used to obtain the driver's state information within a current preset period, and to analyze and determine the driver's current driving attention according to the driver's state information; A safety prompt module, used to generate a safety degree according to the urgency of the vehicle and the current driving attention, and execute a corresponding safety prompt instruction according to the safety degree; The attention determination module comprises: A state information acquisition unit, used to acquire the driver state information within a current preset period, wherein the driver state information includes hand state information and sight state information; an attention matching unit, configured to traverse a preset driver attention table based on the driver state information, and match and obtain attention values ​​corresponding to each state information in the driver state information, wherein the preset driver attention table includes a plurality of attention values ​​and state information corresponding thereto, which are arranged in pairs; An attention calculation unit, used to calculate the sum of attention values ​​of each state information in the driver state information to obtain the current driving attention; The safety prompt module includes: A safety degree calculation unit, used for calculating the ratio between the current driving attention degree and the urgency degree of the own vehicle, to obtain the safety degree, wherein the safety degree=current driving attention degree / the urgency degree of the own vehicle; A first comparison unit, configured to not generate a safety prompt instruction when the safety level is not lower than a first preset threshold; A second comparison unit is used to match and execute a first safety prompt instruction when the safety level is greater than a second preset threshold and less than a first preset threshold, wherein the first safety prompt instruction includes a voice prompt instruction; The third comparison unit is used to match and execute a second safety prompt instruction when the safety level is not higher than a second preset threshold, wherein the second safety prompt instruction includes a voice prompt instruction and a temperature reduction prompt instruction.

5. A safety warning system for automatic driving of a vehicle according to claim 4, characterized in that: The urgency determination module comprises: An obstacle trajectory determination unit is used to obtain the surrounding environment information of the autonomous driving vehicle and predict the future trajectory of the obstacle based on the monitored surrounding environment information and a preset trajectory prediction model; A self-vehicle trajectory determination unit, used to determine the future trajectory of the self-vehicle according to the current vehicle state information and the navigation instruction of the automatic driving system, wherein the current vehicle state information includes the current vehicle position, speed, acceleration and moving direction; A trajectory comparison unit, used for comparing the future trajectory of the ego vehicle with the future trajectory of the obstacle, finding the closest point between them, and calculating the expected time required for the collision between the ego vehicle and the obstacle according to the position and speed of the closest point; The urgency determination unit is used to compare the calculated estimated time required for collision with a preset urgency table to match the urgency of the vehicle, wherein the preset urgency table includes a plurality of urgency levels set in pairs and the corresponding time intervals required for collision.

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