CN114954307A - Driving assistance system based on artificial intelligence - Google Patents

Abstract

The invention discloses an assisted driving system based on artificial intelligence, comprising a central control module; a surrounding environment monitoring module for monitoring the environmental conditions around the vehicle and feeding back to the central control module; and an in-vehicle environment monitoring module for monitoring the vehicle The internal environmental conditions are fed back to the central control module; the vehicle status monitoring module is used to monitor the running status of the vehicle body and fed back to the central control module; the driver status monitoring module is used to monitor the current driver's fatigue status and Feedback to the central control module; the driving assistance module, under the control of the central control module, realizes the functions of speed adjustment, lane adjustment, overtaking, braking and parking, so as to realize the driver's driving assistance to the vehicle during the driving process; the advantage is that it can improve safe driving. coefficient, reminding drivers to operate properly, avoid road safety risks, ensure the safety of people and vehicles, and reduce the occurrence of traffic accidents.

Description

An artificial intelligence-based assisted driving system

technical field

The present invention relates to the field, in particular to an assisted driving system based on artificial intelligence.

Background technique

With the development of social economy and the improvement of people's living standards, people use more and more cars, and cars are gradually integrated into people's lives. The issue of safe driving has become particularly important, and artificial intelligence driving assistance technology has become a social research hot spot. At present, assisted driving systems are generally based on camera and radar technology. By providing environmental data in front, side and rear of the vehicle and taking corresponding actions, it can warn the driver of imminent risks and provide assistance to the driver. They can also provide control. Intuitive prompts or actions, such as motion and steering inputs, help “guide” the driver to stay in the lane, or provide convenience features such as adaptive cruise control.

However, the traditional assisted driving system has limited functions, and does not have the functions of in-vehicle environment monitoring and driver monitoring and analysis. Especially in recent years, the traffic accident rate is getting higher and higher, and most traffic accidents are caused by human factors, such as driver fatigue. Driving, drunk driving, drunk driving, etc.; data shows that inattentive driving is one of the important factors leading to car accidents; therefore, it is urgent to increase the driver monitoring function on the existing assisted driving system to improve the safe driving factor and remind driving Operators should operate in a standardized manner, avoid road safety risks, ensure the safety of personnel and vehicles, and reduce the occurrence of traffic accidents.

SUMMARY OF THE INVENTION

In order to solve the above-mentioned deficiencies in the prior art, the present invention provides an assisted driving system based on artificial intelligence, which can improve the safe driving factor, remind drivers to operate in a standardized manner, avoid safe road safety risks, ensure the safety of personnel and vehicles, reduce the occurrence of traffic accidents.

The technical solution adopted by the present invention to solve the above technical problems is as follows: an assisted driving system based on artificial intelligence, comprising:

Central control module;

a surrounding environment monitoring module for monitoring the environmental conditions around the vehicle and feeding back to the central control module;

an in-vehicle environment monitoring module, which is used to monitor the environmental conditions inside the vehicle and feed it back to the central control module;

a vehicle state monitoring module for monitoring the running state of the vehicle body and feeding back to the central control module;

a driver state monitoring module, which is used to monitor the fatigue state of the current driver and feed it back to the central control module;

A driving assistance module, which realizes the functions of vehicle speed adjustment, lane adjustment, overtaking, braking and parking under the control of the central control module, so as to realize the driver's driving assistance to the vehicle during the driving process;

a warning module, which realizes an alarm reminder under the control of the central control module;

The communication module is used for the communication between the central control module and the remote cloud;

The terminal module is electrically connected with the remote cloud, and is used for realizing interactive communication with the remote cloud.

Preferably, the surrounding environment monitoring module includes an atmospheric monitoring unit, a millimeter-wave radar module, a camera module and a fill light, and the atmospheric monitoring unit is provided on the vehicle and is used to monitor the current atmospheric environment and feed back to the a central control module, the millimeter-wave radar module is arranged on the top of the vehicle and is used to monitor the distance between obstacles and the vehicle in real time, the millimeter-wave radar module is electrically connected to the central control module, and the camera module It is used to detect the road conditions around the vehicle and feed it back to the central control module. The supplementary light is arranged on the vehicle and is electrically connected to the central control module to improve the brightness of the target area. In this structure, the atmospheric monitoring unit is used to monitor the atmospheric environment of the current vehicle environment. The atmospheric environment includes air temperature and humidity, light intensity, rainfall information, PM2.5, etc., so as to better control the equipment in the vehicle through the central control module ;The millimeter wave radar module and the camera module can be used together to identify the image information of pedestrians, road conditions, target vehicles and obstacles in real time around the vehicle. Make adjustments, and can also play the received real-time road condition information and alarm information, remind the driver in real time, and issue an alarm when the target distance is detected to further improve the safety of driving.

Preferably, when the atmospheric monitoring unit monitors that the current environment where the vehicle is located is dark, it sends a first instruction to the central control module, and the received central control module generates a fill light instruction after receiving the first instruction, and It is sent to the supplementary light, and the supplementary light performs supplementary light processing on the target area after receiving the supplementary light instruction. In this structure, in the case of insufficient light, the central control module sends a supplementary light command to start the supplementary light to increase the brightness of the target area to supplement the light, and maintain the original brightness of other areas. When the lighting conditions are not good, it can effectively improve the lack of blurring of the collected images. By supplementing the light in the target area, it can improve the imaging quality and detection distance, reduce the impact of the weather and environment on the driver, and reduce the occurrence of accidents.

Preferably, the atmospheric monitoring unit includes a rain sensor, a light sensor, a PM2.5 sensor, a wind speed sensor and a temperature and humidity sensor, the rain sensor, the light sensor, the PM2.5 sensor, the wind speed sensor and The temperature and humidity sensors are respectively electrically connected to the central control module. In this structure, the rain sensor is used to detect the amount of rain, and once it exceeds the threshold, the wiper will be turned on; the light sensor is used to detect the light intensity of the current environment, and once the threshold is exceeded, the fill light and searchlight will be turned on; the PM2.5 sensor is used for Detect the PM2.5 value of the current environment. Once the value exceeds the threshold, the air purification equipment will be activated to ensure the health of the people in the car; the wind speed sensor is used to detect the air volume of the current environment. Once the threshold value is exceeded, the driving assistance module will be involved to Enhance driving safety; the temperature and humidity sensor is used to detect the temperature and humidity of the current environment, so as to facilitate the temperature adjustment of the air conditioner in the car.

Preferably, the in-vehicle environment monitoring module includes a high-definition camera, and the high-definition camera is arranged in the vehicle and is electrically connected to the central control module, so that when an emergency occurs in the vehicle, the central control module controls the camera. The warning module sends out an alarm reminder, and the specific steps are as follows:

S1: Push the instruction of whether to open the high-definition camera to the user. If the user chooses to open it, it will enter S2. If the user does not agree, the high-definition camera will be in a silent state;

S2: The high-definition camera starts to work, shoots the situation in the vehicle in real time, and sends the collected video information to the image processing module for storage;

S3: The image processing module is used to store the video information sent by the high-definition camera and forward it to the deep learning judgment module for behavior analysis;

S4: The deep learning judgment module is pre-trained with an abnormal behavior judgment model, conducts behavior judgment on the received video information according to the abnormal behavior judgment model, and feeds back the judgment result to the central control module;

S5: If the judgment result is abnormal, the central control module controls the warning module to issue an alarm reminder, and reports to the remote cloud through the communication module, and transmits the video information to the vehicle storage medium for backup; if the judgment result is normal, the Video information is directly input to the vehicle storage medium for backup.

In this structure, the user's consent will be obtained when the in-vehicle camera is performed to protect the privacy of the occupants in the vehicle. The recognition method is accurate in action recognition, and the deep learning judgment module is used for human action detection, which has strong generalization ability. , and the action model, through the analysis and modeling of offline data, very accurately captures the specific law and range of motion of the action, so that it can accurately match the action of the person. Once abnormal behavior occurs, such as robbery, falling into the water, car accident, driver In the case of unconsciousness, etc., it can quickly alarm, and at the same time, the driving assistance module will intervene.

Preferably, the vehicle state monitoring module includes a vehicle speed monitoring unit, a tire pressure monitoring unit, a water temperature monitoring unit, an oil quantity monitoring unit and a circuit monitoring unit, the vehicle speed monitoring unit, the tire pressure monitoring unit, the water temperature monitoring unit, the fuel quantity monitoring unit The monitoring unit and the circuit monitoring unit are respectively electrically connected with the central control module.

Preferably, the driver state monitoring module is implemented by a face acquisition unit arranged in the vehicle, and the specific steps are as follows:

Step 1: periodically collect the driver's face image through the face acquisition unit;

Step 2: normalize and grayscale the obtained driver's face image to obtain the face area;

Step 3: locate the centroid and pupil area of the pupil of the human eye in the face area, obtain the state parameters of the human eye and track the human eye;

Step 4: Put the human eye state parameters into the pre-trained fatigue feature state judgment model to determine whether the driver is in a fatigue state, if so, go to Step 5; otherwise, return to Step 1;

Step 5: The central control module controls the warning module to issue an alarm reminder, and reports to the remote cloud through the communication module.

In this structure, there is no need for direct contact with the driver, and the interference of environmental noise is effectively removed through the driver's face image, and it has high real-time performance. It combines the centroid of the pupil and the pupil area of the human eye to improve the key feature pairing results. The proportion of influence further improves the detection accuracy of the driver's driving state, and has better use value.

Preferably, the terminal module is a smart phone, the central control module has a unique serial number, the remote cloud has a storage list, and the unique serial number in the storage list corresponds to a mobile phone registration number. When the monitoring module detects that the current driver is a stranger, the central control module sends a confirmation instruction to the remote cloud through the communication module. After receiving the confirmation instruction, the remote cloud pushes a message to the mobile phone registration number corresponding to the central control module. After the corresponding terminal module receives the push message, if it agrees to start, the vehicle can drive normally; if it refuses to start, the vehicle refuses to start, and an alarm reminder is issued. In this structure, since there are strangers driving the vehicle, in order to facilitate the identification of such groups of people, once a stranger is in the driving position, the remote cloud will immediately push a message to the corresponding terminal module, if the terminal module agrees to start If the terminal module refuses to start the vehicle, it will be regarded as an illegal intrusion, and an alarm reminder will be issued to ensure the safety of the vehicle.

Compared with the prior art, the present invention has the advantages of: a surrounding environment monitoring module for monitoring the environmental conditions around the vehicle, an in-vehicle environment monitoring module for monitoring the environmental conditions inside the vehicle, and a vehicle state monitoring module for monitoring The running status of the vehicle body and the driver status monitoring module are used to monitor the fatigue status of the current driver, so as to conduct multi-directional comprehensive monitoring to obtain more external and internal data, so that the central control module can better judge and analyze, Remind drivers to operate properly, avoid road safety risks, ensure the safety of people and vehicles, and reduce the occurrence of traffic accidents.

Description of drawings

Fig. 1 is the principle block diagram of the present invention;

Fig. 2 is the principle block diagram of the surrounding environment monitoring module in the present invention;

Fig. 3 is the principle block diagram of the vehicle state monitoring module in the present invention;

FIG. 4 is a schematic flow chart of the in-vehicle environment monitoring module in the present invention when working.

Detailed ways

The present invention will be described in further detail below with reference to the accompanying drawings and embodiments, but it is not intended to limit the present invention.

Embodiment 1: As shown in the figure, an assisted driving system based on artificial intelligence, including

Central control module 1;

The surrounding environment monitoring module 2 is used to monitor the environmental conditions around the vehicle and feed it back to the central control module 1;

The in-vehicle environment monitoring module 3 is used to monitor the environmental conditions inside the vehicle and feed it back to the central control module 1;

The vehicle status monitoring module 4 is used to monitor the running status of the vehicle body and feed it back to the central control module 1;

The driver state monitoring module 5 is used to monitor the fatigue state of the current driver and feed it back to the central control module 1;

The driving assistance module 6 realizes the functions of vehicle speed adjustment, lane adjustment, overtaking, braking and parking under the control of the central control module 1, so as to realize the driving assistance of the driver to the vehicle during the driving process;

The warning module 7 realizes the alarm reminder under the control of the central control module 1;

The communication module 8 is used for the communication between the central control module 1 and the remote cloud 10;

The terminal module 9 is electrically connected to the remote cloud 10 for realizing interactive communication with the remote cloud 10 .

Preferably, the surrounding environment monitoring module 2 includes an atmospheric monitoring unit 21, a millimeter-wave radar module 22, a camera module 23 and a fill light 24. The atmospheric monitoring unit 21 is arranged on the vehicle and is used to monitor the current atmospheric environment and feed back to the The central control module 1, the millimeter-wave radar module 22 is arranged on the top of the vehicle, and is used to monitor the distance between the obstacle and the vehicle in real time, the millimeter-wave radar module 22 is electrically connected to the central control module 1, and the camera module 23 is used to detect The road conditions around the vehicle are fed back to the central control module 1. The fill light 24 is provided on the vehicle and is electrically connected to the central control module 1 to improve the brightness of the target area. In this structure, the atmospheric monitoring unit 21 is used to monitor the atmospheric environment of the current environment where the vehicle is located. The atmospheric environment includes air temperature and humidity, light intensity, rainfall information, PM2.5, etc., so that the central control module 1 can better control the interior of the vehicle. The millimeter wave radar module 22 and the camera module 23 are used together to identify the image information of pedestrians, road conditions, target vehicles and obstacles in the surrounding road conditions of the vehicle in real time, and cooperate with the driving assistance module 6, so that when driving, Targeted adjustments are made according to the on-site situation, and the received real-time road condition information and alarm information can also be played, reminding the driver in real time, and issuing an alarm for the detected target distance to further improve driving safety.

Embodiment 2: As shown in the figure, the difference from Embodiment 1 is that when the atmosphere monitoring unit 21 monitors that the current environment where the vehicle is located is dark, it sends a first instruction to the central control module 1, and the central control module 1 receives the first instruction. After receiving the first instruction, a fill light instruction is generated and sent to the fill light lamp 24, and the fill light lamp 24 performs fill light processing on the target area after receiving the fill light instruction. In this structure, in the case of insufficient light, the central control module 1 sends a supplementary light command to activate the supplementary light 24 to increase the brightness of the target area to perform supplementary light, and maintain the original brightness of other areas, so that it can be used at night, rain and snow. In the case of poor lighting conditions such as haze, it can effectively improve the lack of blurring of captured images. By supplementing the light in the target area, it can improve the imaging quality and detection distance, reduce the impact of the weather environment on the driver, and reduce the occurrence of accidents.

Preferably, the atmospheric monitoring unit 21 includes a rain sensor, a light sensor, a PM2.5 sensor, a wind speed sensor and a temperature and humidity sensor, and the rain sensor, light sensor, PM2.5 sensor, wind speed sensor and temperature and humidity sensor are respectively connected with the central control module 1 electrical connection. In this structure, the rain sensor is used to detect the amount of rain, and once it exceeds the threshold, the wiper will be turned on; the light sensor is used to detect the light intensity of the current environment, and once the threshold is exceeded, the fill light 24 and searchlight will be turned on; the PM2.5 sensor is used for It is used to detect the PM2.5 value of the current environment. Once the threshold value is exceeded, the air purification equipment will be activated to ensure the health of the people in the car; the wind speed sensor is used to detect the air volume of the current environment. Once the threshold value is exceeded, the driving assistance module 6 will be involved. , to enhance driving safety; the temperature and humidity sensor is used to detect the temperature and humidity of the current environment to facilitate the temperature adjustment of the air conditioner in the car.

Preferably, the in-vehicle environment monitoring module 3 includes a high-definition camera, and the high-definition camera is arranged in the vehicle and is electrically connected to the central control module 1, so that when an emergency occurs in the vehicle, the central control module 1 controls the warning module 7 to issue an alarm Reminder, the specific steps are as follows:

S1: Push the instruction of whether to open the high-definition camera to the user. If the user chooses to open it, it will enter S2. If the user does not agree, the high-definition camera will be in a silent state;

S2: The high-definition camera starts to work, shoots the situation in the vehicle in real time, and sends the collected video information to the image processing module for storage;

S3: The image processing module is used to store the video information sent by the high-definition camera and forward it to the deep learning judgment module for behavior analysis;

S4: The deep learning judgment module is pre-trained with an abnormal behavior judgment model, conducts behavior judgment on the received video information according to the abnormal behavior judgment model, and feeds back the judgment result to the central control module 1;

S5: If the judgment result is abnormal, the central control module 1 controls the warning module 7 to issue an alarm reminder, and reports to the remote cloud through the communication module 8, and simultaneously transmits the video information to the vehicle-mounted storage medium for backup; if the judgment result is normal , the video information is directly input into the vehicle storage medium for backup.

In this structure, the user's consent will be obtained when the in-vehicle camera is performed to protect the privacy of the occupants in the vehicle. The recognition method is accurate in action recognition, and the deep learning judgment module is used for human action detection, which has strong generalization ability. , and the action model, through the analysis and modeling of offline data, very accurately captures the specific law and range of motion of the action, so that it can accurately match the action of the person. Once abnormal behavior occurs, such as robbery, falling into the water, car accident, driver In the case of unconsciousness, etc., the alarm can be quickly alerted, and the driving assistance module 6 will intervene in the work at the same time.

Embodiment 3: As shown in the figure, different from Embodiment 2, the vehicle state monitoring module 4 includes a vehicle speed monitoring unit 41, a tire pressure monitoring unit 42, a water temperature monitoring unit 43, an oil quantity monitoring unit 44 and a circuit monitoring unit 45, The vehicle speed monitoring unit 41 , the tire pressure monitoring unit 42 , the water temperature monitoring unit 43 , the fuel quantity monitoring unit 44 and the circuit monitoring unit 45 are respectively electrically connected to the central control module 1 .

Preferably, the driver state monitoring module 5 is implemented by a face acquisition unit arranged in the vehicle, and the specific steps are as follows:

Step 1: periodically collect the driver's face image through the face collection unit;

Step 2: normalize and grayscale the obtained driver's face image to obtain the face area;

Step 3: locate the centroid and pupil area of the pupil of the human eye in the face area, obtain the state parameters of the human eye and track the human eye;

Step 4: Put the human eye state parameters into the pre-trained fatigue feature state judgment model to determine whether the driver is in a fatigue state, if so, go to Step 5; otherwise, return to Step 1;

Step 5: The central control module 1 controls the warning module 7 to issue an alarm reminder, and reports to the remote cloud through the communication module 8 .

In this structure, there is no need for direct contact with the driver, and the interference of environmental noise is effectively removed through the driver's face image, and it has high real-time performance. It combines the centroid of the pupil and the pupil area of the human eye to improve the key feature pairing results. The proportion of influence further improves the detection accuracy of the driver's driving state, and has better use value.

Preferably, the terminal module 9 is a smart phone, the central control module 1 has a unique serial number, the remote cloud has a storage list, and the unique serial number in the storage list corresponds to a mobile phone registration number. When the in-vehicle environment monitoring module 3 monitors the current When the driver is a stranger, the central control module 1 sends a confirmation instruction to the remote cloud through the communication module 8. After receiving the confirmation instruction, the remote cloud pushes a message to the mobile phone registration number corresponding to the central control module 1. After the terminal module 9 receives the push message, if it agrees to start, the vehicle can drive normally; if it refuses to start, the vehicle refuses to start, and sends out an alarm reminder. In this structure, since there are strangers driving the vehicle, in order to facilitate the identification of such groups of people, once a stranger is in the driving position, the remote cloud will immediately push a message to the corresponding terminal module 9, such as the terminal module 9 If the terminal module 9 refuses to start the vehicle, it will be regarded as an illegal intrusion, and an alarm reminder will be issued to ensure the safety of the vehicle.

It is worth noting that the above are only the preferred embodiments of the present invention, which do not limit the scope of patent protection of the present invention. The present invention can also improve the materials and structures of the above-mentioned various parts and components, or adopt technical equivalents. things are replaced. Therefore, all equivalent structural changes made by using the descriptions and illustrations of the present invention, or directly or indirectly applied to other related technical fields, are all included within the scope of the present invention.

Claims (8)

1. an assisted driving system based on artificial intelligence, is characterized in that: comprising: Central control module; a surrounding environment monitoring module for monitoring the environmental conditions around the vehicle and feeding back to the central control module; an in-vehicle environment monitoring module, which is used to monitor the environmental conditions inside the vehicle and feed it back to the central control module; a vehicle state monitoring module for monitoring the running state of the vehicle body and feeding back to the central control module; a driver state monitoring module, which is used to monitor the fatigue state of the current driver and feed it back to the central control module; A driving assistance module, which realizes the functions of vehicle speed adjustment, lane adjustment, overtaking, braking and parking under the control of the central control module, so as to realize the driver's driving assistance to the vehicle during the driving process; a warning module, which realizes an alarm reminder under the control of the central control module; The communication module is used for the communication between the central control module and the remote cloud; The terminal module is electrically connected with the remote cloud, and is used for realizing interactive communication with the remote cloud. 2. The artificial intelligence-based assisted driving system according to claim 1, wherein the surrounding environment monitoring module comprises an atmospheric monitoring unit, a millimeter-wave radar module, a camera module and a fill light, and the atmospheric monitoring module The unit is arranged on the vehicle to monitor the current atmospheric environment and feedback to the central control module, the millimeter wave radar module is arranged on the top of the vehicle, and is used to monitor the distance between the obstacle and the vehicle in real time, The millimeter-wave radar module is electrically connected to the central control module, the camera module is used to detect road conditions around the vehicle, and feed back to the central control module, the fill light is provided on the vehicle, and is connected to the central control module. The control module is electrically connected to improve the brightness of the target area. 3. An artificial intelligence-based assisted driving system according to claim 2, characterized in that: when the atmospheric monitoring unit monitors that the environment where the current vehicle is located is dark, it sends a first instruction to the central control module, The received central control module generates a supplementary light instruction after receiving the first instruction, and sends it to the supplementary light, and the supplementary light performs supplementary light processing on the target area after receiving the supplementary light instruction. 4. a kind of artificial intelligence-based assisted driving system according to claim 2, is characterized in that: described atmospheric monitoring unit comprises rain sensor, light sensor, PM2.5 sensor, wind speed sensor and temperature and humidity sensor, described rainfall The sensor, the light sensor, the PM2.5 sensor, the wind speed sensor and the temperature and humidity sensor are respectively electrically connected to the central control module. 5 . The artificial intelligence-based assisted driving system according to claim 1 , wherein the in-vehicle environment monitoring module comprises a high-definition camera, and the high-definition camera is arranged in the vehicle and is connected with the central control module. 6 . It is electrically connected, so that when an emergency occurs in the vehicle, the central control module controls the warning module to issue an alarm reminder. The specific steps are as follows: S1: Push the instruction of whether to open the high-definition camera to the user. If the user chooses to open it, it will enter S2. If the user does not agree, the high-definition camera will be in a silent state; S2: The high-definition camera starts to work, shoots the situation in the vehicle in real time, and sends the collected video information to the image processing module for storage; S3: The image processing module is used to store the video information sent by the high-definition camera and forward it to the deep learning judgment module for behavior analysis; S4: The deep learning judgment module is pre-trained with an abnormal behavior judgment model, conducts behavior judgment on the received video information according to the abnormal behavior judgment model, and feeds back the judgment result to the central control module; S5: If the judgment result is abnormal, the central control module controls the warning module to issue an alarm reminder, and reports to the remote cloud through the communication module, and transmits the video information to the vehicle storage medium for backup; if the judgment result is normal, the Video information is directly input to the vehicle storage medium for backup. 6 . The artificial intelligence-based assisted driving system according to claim 1 , wherein the vehicle state monitoring module comprises a vehicle speed monitoring unit, a tire pressure monitoring unit, a water temperature monitoring unit, an oil quantity monitoring unit and a circuit monitoring unit. 7 . The vehicle speed monitoring unit, the tire pressure monitoring unit, the water temperature monitoring unit, the fuel quantity monitoring unit and the circuit monitoring unit are respectively electrically connected to the central control module. 7. a kind of assisted driving system based on artificial intelligence according to claim 1, is characterized in that: described driver state monitoring module is realized by the face acquisition unit that is arranged in the vehicle, and concrete steps are as follows, Step 1: periodically collect the driver's face image through the face acquisition unit; Step 2: normalize and grayscale the obtained driver's face image to obtain the face area; Step 3: locate the centroid and pupil area of the pupil of the human eye in the face area, obtain the state parameters of the human eye and track the human eye; Step 4: Put the human eye state parameters into the pre-trained fatigue feature state judgment model to determine whether the driver is in a fatigue state, if so, go to Step 5; otherwise, return to Step 1; Step 5: The central control module controls the warning module to issue an alarm reminder, and reports to the remote cloud through the communication module. 8. The artificial intelligence-based assisted driving system according to claim 1, wherein the terminal module is a smart phone, the central control module has a unique serial number, and the remote cloud has a storage list, The unique serial number in the storage list corresponds to a mobile phone registration number. When the in-vehicle environment monitoring module detects that the current driver is a stranger, the central control module sends a confirmation instruction to the remote cloud through the communication module. After the remote cloud receives the confirmation instruction Push the message to the mobile phone registration number corresponding to the central control module. When the terminal module corresponding to the mobile phone registration number receives the push message, if it agrees to start, the vehicle can drive normally; if it refuses to start, the vehicle refuses to start. and issue an alarm reminder.

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