CN120804609A

CN120804609A - Driving state monitoring method and device

Info

Publication number: CN120804609A
Application number: CN202511300611.2A
Authority: CN
Inventors: 陆阳; 袁娟
Original assignee: Fullsee Technology Co ltd
Current assignee: Fullsee Technology Co ltd
Priority date: 2025-09-12
Filing date: 2025-09-12
Publication date: 2025-10-17

Abstract

The embodiment of the application provides a driving state monitoring method and device, wherein a driving track and driving data of a target vehicle are acquired, when the continuous driving duration in the driving data exceeds a preset continuous driving duration threshold value and the continuous driving speed of the target vehicle exceeds a preset speed threshold value, the driving behavior of the target vehicle is determined to be a preliminary fatigue driving behavior, a real-time road type corresponding to the driving track is determined, a vehicle image of the target vehicle is acquired under the condition that the road type is a non-congestion type, the vehicle image is compared with registration information of the current target vehicle, and under the condition that the comparison result is that the vehicle is consistent, the driving behavior of the target vehicle is determined to be a fatigue driving behavior, and a fatigue driving data packet corresponding to the data is generated and uploaded to a server. The method effectively solves the defects in the aspects of limited interference elimination, reliability of evidence solidification and the like, and remarkably improves the accuracy and reliability of fatigue driving judgment.

Description

Driving state monitoring method and device

Technical Field

The application relates to the field of data processing, in particular to a driving state monitoring method and device.

Background

In the prior art, the detection method of fatigue driving can rely on a driver self-reporting mode or a detection method of a vehicle-mounted sensor to judge whether the current driver is tired driving or not, however, the subjectivity and the accuracy are higher in the mode of relying on the driver self-reporting, the detection method of the vehicle-mounted sensor is easy to be interfered by environmental factors, and the misjudgment rate is higher.

With the development of intelligent traffic technology, the problem can be solved by judging fatigue driving through multi-source data fusion, however, the existing method for judging fatigue driving through multi-source data fusion still has the defects in the aspects of data fusion accuracy, interference elimination limitation, evidence solidification reliability and the like, and is difficult to meet the actual judgment requirement.

Disclosure of Invention

Aiming at the problems in the prior art, the application provides the driving state monitoring method and the driving state monitoring device, which can effectively solve the defects of the traditional technology in the aspects of judging the accuracy of the fatigue driving in data fusion, the limited interference elimination, the reliability of evidence solidification and the like, and remarkably improve the accuracy and the reliability of the fatigue driving judgment.

In order to solve at least one of the problems, the application provides the following technical scheme:

in a first aspect, the present application provides a driving state monitoring method, including:

Acquiring a running track and running data of a target vehicle, and determining the running behavior of the target vehicle as a preliminary fatigue driving behavior when the continuous running duration in the running data exceeds a preset continuous running duration threshold value and the continuous running speed of the target vehicle exceeds a preset speed threshold value, wherein the running data comprises the continuous running duration and the continuous running speed;

Determining a real-time road type corresponding to a running track in an inverse geocoding mode, acquiring a vehicle image shot by a target vehicle through a bayonet in the middle of the running track under the condition that the road type is a non-congestion type, and comparing the vehicle image with registration information of a current target vehicle to obtain a comparison result, wherein the road type comprises a congestion type and a non-congestion type, and the comparison result comprises a consistent vehicle and a non-consistent vehicle;

And under the condition that the comparison result shows that the vehicles are consistent, updating the preliminary fatigue driving behavior of the target vehicle into the fatigue driving behavior, and carrying out encryption processing on the running track, the running data and the vehicle image of the target vehicle to generate a fatigue driving data packet and uploading the fatigue driving data packet to the server.

Further, the method further comprises the steps of inputting the initial coordinates and the real-time coordinates of the running track to a map interface, and obtaining geographic position information corresponding to the initial coordinates, the real-time coordinates and the running track as tracks, wherein the geographic position information comprises road names and real-time congestion indexes corresponding to all roads;

when the real-time congestion index indicates that the current road is a congestion road section, determining an initial road type as an initial congestion type, and when the real-time congestion index indicates that the current road is a non-congestion road section, determining the initial road type as an initial non-congestion type;

And determining each initial road type corresponding to the running track, determining the road type corresponding to the current running track as the congestion type when the initial congestion type exceeding the preset congestion quantity threshold exists in the initial road types, and updating the running behavior corresponding to the target vehicle as the non-fatigue driving behavior.

Further, the method further comprises the steps of identifying license plate information in the vehicle image, and comparing the license plate information with license plate information in the registration information to obtain license plate comparison results;

And when the license plate comparison result is consistent, extracting the appearance characteristics of the vehicle in the vehicle image, and comparing the appearance characteristics of the vehicle with the appearance characteristics of the vehicle in the registration information to obtain a comparison result, wherein the appearance characteristics of the vehicle comprise the color of the vehicle body, the vehicle type and the vehicle identifier.

Further, after obtaining the license plate comparison result, the method further comprises the following steps:

When the license plate comparison results are inconsistent, acquiring a historical driving image of the target vehicle, and comparing the historical driving image, the vehicle image and the registration information to obtain a fake license plate comparison result, wherein the fake license plate comparison result is a suspicious vehicle and a recognition error vehicle;

when the fake-licensed comparison result is that the vehicle is in doubt, processing the vehicle image, the historical driving image and the registration information into fake-licensed data packets, and sending the fake-licensed data packets to corresponding fake-licensed processing platforms;

And when the fake license plate comparison result is that the wrong vehicle is identified, the step of acquiring the vehicle image shot by the target vehicle through the bayonet halfway in the driving track is re-executed until the comparison result is obtained.

Further, the method further comprises the step of determining low-speed driving duration corresponding to the continuous driving speed lower than the preset speed threshold under the condition that the continuous driving speed is lower than the preset speed threshold;

Initializing the running track and the running data of the target vehicle when the low-speed running time exceeds a preset low-speed running time threshold value so as to redetermine the running track and the running data of the target vehicle;

and when the low-speed running duration does not exceed the preset low-speed running duration threshold, removing the low-speed running duration from the continuous running duration and not resetting the record of the continuous running duration.

Further, after collecting the driving track and the driving data of the target vehicle, the method further comprises:

Determining a lost start time, a lost end time, a lost duration and a lost position of the lost data point under the condition that continuous lost data points exist in the driving track;

Determining a lost area based on the lost start time, the lost end time and the lost position under the condition that the lost time exceeds a preset lost time threshold;

Extracting a valid data point before the loss, which is nearest to the start time before the loss, from the running track, extracting a valid data point after the loss, which is nearest to the end time after the loss, from the running track, and determining the space distance between the valid data point before the loss and the valid data point after the loss;

and under the condition that the space distance exceeds the lost area, determining the data segment corresponding to the continuous lost data point as an invalid data segment, and skipping the invalid data segment in the continuous driving duration.

Further, encrypting the running track, the running data and the vehicle image of the target vehicle by a preset encryption algorithm to generate a ciphertext data block;

And performing safe hash algorithm operation on the ciphertext data block, generating a hash value, generating a fatigue driving data packet based on the hash value and the ciphertext data block, and uploading the fatigue driving data packet to a server.

In a second aspect, the present application provides a driving state monitoring device including:

The first processing module is used for acquiring the running track and running data of the target vehicle, and determining the running behavior of the target vehicle as the preliminary fatigue driving behavior when the continuous running duration in the running data exceeds a preset continuous running duration threshold value and the continuous running speed of the target vehicle exceeds a preset speed threshold value, wherein the running data comprises the continuous running duration and the continuous running speed;

The second processing module is used for determining a real-time road type corresponding to the running track in an inverse geocoding mode, acquiring a vehicle image shot by a target vehicle through a bayonet in the middle of the running track under the condition that the road type is a non-congestion type, and comparing the vehicle image with registration information of the current target vehicle to obtain a comparison result, wherein the road type comprises the congestion type and the non-congestion type, and the comparison result comprises the consistency of vehicles and the non-consistency of vehicles;

And the third processing module is used for updating the preliminary fatigue driving behavior of the target vehicle into the fatigue driving behavior under the condition that the comparison result is that the vehicles are consistent, and encrypting the running track, the running data and the vehicle image of the target vehicle to generate a fatigue driving data packet and uploading the fatigue driving data packet to the server.

In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the driving state monitoring method when executing the program.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the driving state monitoring method.

In a fifth aspect, the application provides a computer program product comprising computer programs/instructions which when executed by a processor implement the steps of the driving state monitoring method.

According to the technical scheme, the driving state monitoring method and the driving state monitoring device are characterized in that through creatively collecting the driving track and the driving data of the target vehicle, when the continuous driving duration in the driving data exceeds a preset continuous driving duration threshold value and the continuous driving speed of the target vehicle exceeds a preset speed threshold value, the driving behavior of the target vehicle is determined to be the preliminary fatigue driving behavior, the real-time road type corresponding to the driving track is determined through the inverse geocoding mode, the vehicle image shot by the target vehicle through the bayonet in the middle of the driving track is obtained under the condition that the road type is of a non-congestion type, the vehicle image is compared with the registration information of the current target vehicle to obtain a comparison result, and when the comparison result is that the vehicle is consistent, the preliminary fatigue driving behavior of the target vehicle is updated to the fatigue driving behavior, and the driving track, the driving data and the vehicle image of the target vehicle are encrypted to generate a fatigue driving data packet and are uploaded to a server. The method effectively solves the defects of the traditional technology in the aspects of judging the accuracy of the fatigue driving in data fusion, the limitation of interference elimination, the reliability of evidence solidification and the like, and remarkably improves the accuracy and the reliability of the fatigue driving judgment.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flow chart of a driving state monitoring method according to an embodiment of the application;

fig. 2 is a structural diagram of a driving state monitoring device in an embodiment of the present application;

Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Reference numerals:

An electronic device 9600, a central processor 9100, a memory 9140, a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, a power supply 9170, a buffer memory 9141, an application/function storage portion 9142, a data storage portion 9143, a driver storage portion 9144, an antenna 9111, a speaker 9131, and a microphone 9132.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The technical scheme of the application obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.

In consideration of the problems in the prior art, the application provides a driving state monitoring method and device, which are used for constructing a closed-loop evidence chain by integrating multidimensional data such as a driving track, geographic information, images shot by a route and a bayonet, accurately judging the fatigue driving behavior of a target vehicle and generating a reliable fatigue driving data packet so as to provide powerful support.

In order to effectively solve the defects of the traditional technology in terms of judging the accuracy of fatigue driving in data fusion, the limitation of interference elimination, the reliability of evidence solidification and the like, the application provides an embodiment of a driving state monitoring method, which specifically comprises the following steps:

Step S101, acquiring a running track and running data of a target vehicle, and determining the running behavior of the target vehicle as a preliminary fatigue driving behavior when the continuous running duration in the running data exceeds a preset continuous running duration threshold value and the continuous running speed of the target vehicle exceeds a preset speed threshold value.

Wherein the driving data includes a continuous driving duration and a continuous driving speed.

Optionally, the present embodiment collects a driving track and driving data of the target vehicle, where the driving track of the target vehicle may be obtained by a global positioning system (Global Positioning System, GPS) in a vehicle-mounted terminal of the target vehicle, the GPS track data of the target vehicle may be obtained at preset time intervals (for example, once per second), and the track data may include, but is not limited to, a time stamp, longitude and latitude, and speed information.

The time stamp is used for recording the position and the speed of the target vehicle at each moment, the longitude and the latitude are used for determining the geographic position of the target vehicle, the speed information is used for judging whether the target vehicle is in a running state, and the running data also comprise the continuous running duration and the continuous running speed of the target vehicle.

In addition, when the continuous running duration in the running data exceeds a preset continuous running duration threshold value and the continuous running speed of the target vehicle exceeds a preset speed threshold value, the running behavior of the target vehicle is determined to be the preliminary fatigue driving behavior, namely, two conditions that the continuous running duration exceeds the preset running duration threshold value and the continuous running speed exceeds the preset speed threshold value in the continuous running duration time period are required to be met, and the running behavior of the target vehicle can be determined to be the preliminary fatigue driving behavior.

The preset continuous driving duration threshold is set based on related regulations and driving safety standards, for example, 8 hours, and is used for judging whether a driver of a target vehicle continuously drives for more than a corresponding preset continuous driving duration, and the preset speed threshold is used for eliminating misjudgment of the target vehicle in low-speed driving scenes such as a parking lot, a road construction area and the like, wherein the preset speed threshold can be 3 km/hour.

The method and the device realize that whether the driver in the target vehicle has the preliminary fatigue driving behavior can be determined through the driving track and the driving data of the target vehicle, wherein the driving track and the driving data are obtained through the multi-source sensor, and the accuracy and the reliability of the obtained preliminary fatigue driving behavior are improved.

Step S102, determining a real-time road type corresponding to the running track through an inverse geocoding mode, acquiring a vehicle image shot by a target vehicle through a bayonet in the middle of the running track under the condition that the road type is a non-congestion type, and comparing the vehicle image with registration information of the current target vehicle to obtain a comparison result.

The road type comprises a congestion type and a non-congestion type, and the comparison result comprises a vehicle consistency and a vehicle inconsistency.

Optionally, in this embodiment, after determining that the target vehicle has the preliminary fatigue driving behavior, the starting point coordinate and the ending point coordinate of the driving track may be converted into specific geographic location information, for example, an expressway name, a city road name, and the like, and the geographic location information corresponding to the driving track may be obtained by calling a map interface, so as to determine a real-time road type of the driving track, where the starting point coordinate and the ending point coordinate may be combined with a preset road type database to perform comparison to obtain the real-time road type, where the road type includes a congestion type and a non-congestion type, and the congestion type may be that the target vehicle slowly travels for a long time due to traffic congestion, and the non-congestion type may not cause the target vehicle to slowly travel for a long time due to traffic congestion.

In addition, under the condition that the road type is a non-congestion type, a vehicle image shot by the target vehicle through a bayonet in the middle of a driving track is further acquired, wherein vehicle appearance characteristics and license plate information in the vehicle image can be extracted in an image recognition mode and compared with target vehicle registration information, and the vehicle appearance characteristics comprise, but are not limited to, vehicle body colors, vehicle types and vehicle identifications, and the comparison results comprise vehicle consistency and vehicle inconsistency.

Furthermore, the multi-dimensional information such as the running posture of the target vehicle and the internal condition of the cab can be compared, and the vehicle image can be preprocessed in an image enhancement mode under the conditions of low illumination or bad weather, so that the quality of the vehicle image is improved, and the accuracy of a comparison result is improved.

The embodiment realizes that the real-time road type is determined through the driving track, and the accuracy and the reliability of the initial fatigue driving behavior are further determined according to the comparison result obtained by the real-time road type, the vehicle image and the registration information of the target vehicle.

And step 103, updating the preliminary fatigue driving behavior of the target vehicle into the fatigue driving behavior under the condition that the comparison result shows that the vehicles are consistent, and encrypting the running track, the running data and the vehicle image of the target vehicle to generate a fatigue driving data packet and uploading the fatigue driving data packet to the server.

Optionally, in this embodiment, when a comparison result of the vehicle image and the registration information of the target vehicle is that the vehicle is consistent, the preliminary fatigue driving behavior of the target vehicle is updated to be the fatigue driving behavior, and the driving track, the driving data and the vehicle image of the target vehicle are encrypted to generate a fatigue driving data packet, and the fatigue driving data packet is uploaded to the server.

The encryption processing may be performed by an asymmetric encryption algorithm (e.g., RSA algorithm), and the generated fatigue driving data packet includes, but is not limited to, information such as a timestamp, a hash value, etc. of the driving data, so as to ensure the integrity and authenticity of the driving data.

Furthermore, the fatigue driving data packet can be encrypted and stored in a blockchain mode to ensure the non-tamper property and traceability of the fatigue driving data packet, and the data can be classified by a multi-level encryption mechanism and respectively encrypted for different levels of data (such as driving track, driving data and vehicle image), so that the data security is improved.

According to the embodiment, under the condition that the running behavior of the target vehicle is determined to be the fatigue driving behavior, the running track, the running data and the vehicle image of the target vehicle are encrypted, and the fatigue driving data packet is generated, so that the safety and traceability of the data are enhanced, and the overall safety and reliability are improved.

The embodiment realizes that by collecting the running track and the running data of the target vehicle and combining the reverse geocoding mode, the vehicle image and the data encryption mode, a precise, efficient and safe fatigue driving judging method is formed, the fatigue driving behavior can be effectively judged, reliable evidence is generated, and meanwhile, the judging process of the fatigue driving is the result obtained by multi-source data fusion, so that the limitation of interference elimination is relieved when interference is eliminated, the reliability of the evidence is improved, and the accuracy and the reliability of the fatigue driving behavior judgment are improved.

In some embodiments, determining the real-time road type corresponding to the driving track by the inverse geocoding method includes:

Inputting the initial coordinates and the real-time coordinates of the running track to a map interface, and acquiring geographic position information corresponding to the initial coordinates serving as a starting point, the real-time coordinates serving as an end point and the running track serving as a track, wherein the geographic position information comprises road names and real-time congestion indexes corresponding to all roads;

Optionally, the starting coordinates and the real-time coordinates of the driving track are input to the map interface, so that the geographic position information corresponding to the driving track with the starting coordinates as a starting point and the real-time coordinates as an end point is obtained according to the map interface, wherein the map interface is a map application programming (Application Programming Interface, API) interface, and the geographic position information includes, but is not limited to, road names and real-time congestion indexes corresponding to each road.

The map API interface can be an interface of a high-precision map service provider, can provide detailed geographic position and traffic condition data, and can reflect the congestion state of a road more accurately, so that the accuracy of judging fatigue driving behaviors is improved.

In addition, whether the current road is a congested road section is determined according to a real-time congestion index, wherein the real-time congestion index is usually a numerical value, and indicates the congestion degree of the current road, for example, 0 indicates smoothness and 100 indicates severe congestion.

If the real-time congestion index indicates that the current road is a congestion road section, determining the initial road type as the initial congestion type, and if the real-time congestion index indicates that the current road is a non-congestion road section, determining the initial road type as the initial non-congestion type.

In addition, statistical analysis is performed on each initial road type corresponding to the driving track, if initial congestion types exceeding a preset congestion quantity threshold exist in the initial road types, for example, 3 continuous initial road types are initial congestion types, the road type corresponding to the current driving track is determined to be the congestion type, and the driving behavior corresponding to the target vehicle is updated to be the non-fatigue driving behavior, so that misjudgment caused by traffic congestion is eliminated, and more accurate judgment of the fatigue driving behavior is ensured.

Furthermore, the judgment logic of the road type can be dynamically adjusted by combining real-time traffic data, such as traffic flow, accident information and the like, so as to better cope with sudden traffic incidents and reduce misjudgment.

The embodiment realizes the determination of the real-time road type corresponding to the driving track through the inverse geocoding technology, and the judgment of the road type by combining the real-time congestion index, so that the actual traffic condition of the road can be reflected in time, the instantaneity and the adaptability of the judgment of the fatigue driving behavior can be improved, the misjudgment caused by traffic congestion can be effectively eliminated, and the accuracy of the judgment of the fatigue driving behavior can be improved.

In some embodiments, comparing the vehicle image with registration information of the current target vehicle to obtain a comparison result includes:

Identifying license plate information in the vehicle image, and comparing the license plate information with license plate information in the registration information to obtain a license plate comparison result;

Optionally, the present embodiment extracts license plate information from the vehicle image by means of optical character recognition (Optical Character Recognition, OCR), where the OCR technology is able to automatically recognize characters on the license plate and convert them into a readable text format.

In addition, the extracted license plate information is compared with license plate information in registration information of the target vehicle, and if the license plate information is consistent, vehicle appearance characteristics in a vehicle image are extracted, wherein the registration information is stored in a preset database, and comprises, but not limited to, the license plate number of the target vehicle, vehicle owner information and vehicle appearance.

The vehicle image can be analyzed in an image recognition mode, the vehicle appearance characteristics are extracted, for example, the vehicle body color of the target vehicle is determined through a color recognition algorithm, the vehicle model is determined through a vehicle model recognition algorithm, and the vehicle identification is recognized through a sign recognition algorithm.

In addition, the extracted vehicle appearance characteristics are compared with vehicle appearance characteristics in the registration information, and a comparison result is obtained, wherein the vehicle appearance characteristics in the registration information are recorded when the vehicle is registered, and generally comprise a vehicle body color, a vehicle type, a vehicle identifier and the like.

Furthermore, the driver information can be compared, and when the comparison result is that the driver information is inconsistent and the comparison result of other data is consistent, the running track and the running data of the current target vehicle are reset, namely, the situation that the target vehicle has replaced the driver and no fatigue driving behavior exists is judged.

And when the comparison result is consistent with the driver information and the comparison result of other data is consistent with the driver information, the fatigue driving behavior of the current target vehicle is identified.

The embodiment realizes that the vehicle image and the registration information of the target vehicle are compared, so that the false judgment can be reduced through double verification, the fairness of the fatigue driving behavior judgment can be ensured, the vehicle information of the target vehicle can be accurately identified, the vehicle image data can be rapidly processed and analyzed even in a complex environment, the response time is reduced, and the fatigue driving behavior can be timely found and processed.

In some embodiments, after obtaining the license plate comparison result, the method further includes:

Optionally, in this embodiment, when the license plate comparison result is inconsistent, a history running image of the target vehicle is called, where the history running image may be stored in the monitoring system, and is used to record running conditions of the target vehicle at different times and places.

The historical driving images can be obtained by inquiring a database of the monitoring system, and snap images of the target vehicle at all bayonets are stored in the database of the monitoring system.

In addition, the currently captured vehicle image and the historical driving image are compared, and comprehensive analysis is carried out by combining the registration information of the target vehicle to obtain a fake license plate comparison result, wherein the comparison content comprises but is not limited to license plate information and vehicle appearance characteristics (such as vehicle body color, vehicle type and vehicle identification).

If the vehicle information in the history driving image is consistent with the currently-captured vehicle image but is inconsistent with the registration information, determining a fake-licensed comparison result of the target vehicle as an in-doubt vehicle, and if the history driving image is inconsistent with the currently-captured vehicle image, determining the fake-licensed comparison result of the target vehicle as an identification error vehicle.

In addition, when the fake-licensed comparison result is an in-doubt vehicle, the vehicle image, the historical driving image and the registration information are processed into fake-licensed data packets, and the fake-licensed data packets are sent to the corresponding fake-licensed processing platforms, wherein the fake-licensed data packets comprise but are not limited to detailed vehicle information and fake-licensed comparison result, and further investigation and processing by relevant management departments are facilitated.

In addition, when the fake license plate comparison result is that the wrong vehicle is identified, the step of acquiring the vehicle image shot by the target vehicle through the bayonets in the middle of the driving track is re-executed until the consistent comparison result is obtained, namely, the vehicle image shot by each bay is compared with the historical driving image, or different vehicles in the same picture are compared, so that the error of judging the fatigue driving behavior caused by the error of identifying the target vehicle is avoided, namely, the purpose of re-acquiring the vehicle image is to ensure the accuracy of judging the fatigue driving behavior, and the error judgment caused by the image quality problem or the error of an identification algorithm is avoided.

The embodiment realizes that through comparing the historical driving image, the vehicle image and the registration information, misjudgment can be reduced through multidimensional comparison, fake-licensed vehicles or recognition errors can be effectively recognized, fairness is ensured, target vehicles can be accurately recognized in a complex environment, and reliability is improved.

In some embodiments, further comprising:

under the condition that the continuous running speed is lower than a preset speed threshold value, determining low-speed running duration corresponding to the continuous running speed lower than the preset speed threshold value;

Optionally, in this embodiment, when the continuous running speed of the target vehicle is lower than the preset speed threshold, the low-speed running duration is recorded, where the low-speed running duration is a duration of continuous running of the target vehicle in a state that the speed threshold is lower, and recording of the low-speed running duration may be implemented by analyzing running data of the target vehicle, that is, continuously monitoring a speed change of the target vehicle, and starting timing when the continuous running speed is lower than the preset speed threshold.

In addition, if the low-speed driving duration exceeds a preset low-speed driving duration threshold, for example, 10 minutes, the driving track and the driving data of the target vehicle are initialized, that is, the recording of the driving track and the driving data of the target vehicle is restarted, so as to ensure that the determination of the fatigue driving behavior is based on accurate data.

The purpose of the initialization is to eliminate the influence of long-time low-speed driving on the fatigue driving judgment, such as moving vehicles in a parking lot or slowly driving in traffic jams, so as to ensure the accuracy of the fatigue driving behavior.

In addition, if the low-speed running duration does not exceed the preset low-speed running duration threshold, removing the part of the low-speed running duration when the continuous running duration is determined, but not resetting the record of the continuous running duration, namely, allowing the calculation of the continuous running duration to be reasonably adjusted under the condition that the low-speed running is not completely ignored, so that the actual running condition of the target vehicle is more accurately reflected.

Further, because reasonable time periods of low-speed running may be different under different traffic conditions, the low-speed running state can be flexibly processed according to actual conditions by dynamically adjusting the preset speed threshold, and erroneous judgment caused by fixing the preset speed threshold is avoided.

Furthermore, the real-time data processing mode can be combined to rapidly process and analyze the vehicle speed data of the road where the target vehicle is located, and a feedback mechanism is established to improve the accuracy and reliability of fatigue driving behavior judgment.

According to the embodiment, the low-speed driving duration is monitored, different processing modes are adopted according to whether the low-speed driving duration exceeds the preset speed threshold, misjudgment caused by low-speed driving can be effectively eliminated, and the accuracy of fatigue driving behavior judgment is improved.

In some embodiments, after collecting the travel track and the travel data of the target vehicle, further comprising:

Optionally, in this embodiment, when detecting that there are consecutive missing data points in the driving track, the missing start time, the missing end time, the missing duration, and the missing position of the missing data points are determined.

The loss start time and the loss end time respectively represent the start time and the end time of the loss of the running track, the loss duration is the time difference between the two time points, and the loss position is the approximate geographic position of the target vehicle during the data loss period.

In addition, if the loss duration exceeds a preset loss duration threshold, for example, 10 minutes, a loss area is determined based on the loss start time, the loss end time and the loss position, wherein the loss area is a range in which the target vehicle may travel in the loss duration, and the loss area can be obtained by analyzing valid data points before and after loss and loss duration estimation.

In addition, a pre-loss valid data point nearest before the loss start time and a post-loss valid data point nearest after the loss end time can be extracted from the driving track, the spatial distance between the two valid data points is determined according to the pre-loss valid data point and the post-loss valid data point, and the distance that the vehicle can drive during the loss is determined.

If the space distance between the effective data point before the loss and the effective data point after the loss exceeds the range of the loss area, determining the data segment corresponding to the continuously lost data point as an invalid data segment, and skipping the invalid data segment when the continuous running duration of the target vehicle is determined, so as to ensure that the calculation of the continuous running duration is not influenced by the data loss.

The embodiment realizes that after the running track and the running data of the target vehicle are acquired, misjudgment caused by data loss can be effectively avoided by processing the running data loss, and meanwhile, the fatigue driving behavior judgment accuracy and reliability can be improved by working normally under the condition of the running data loss.

In some embodiments, encrypting the driving track, the driving data and the vehicle image of the target vehicle to generate a fatigue driving data packet and uploading the fatigue driving data packet to the server comprises:

Encrypting the running track, running data and vehicle images of the target vehicle through a preset encryption algorithm to generate ciphertext data blocks;

Optionally, in this embodiment, the running track, the running data and the vehicle image of the target vehicle are encrypted by a preset encryption algorithm to generate the ciphertext data block, where the preset encryption algorithm may be an AES-256 encryption algorithm or an RSA encryption algorithm, and the selection of the preset encryption algorithm is based on the security and efficiency of the algorithm itself, so as to ensure that the data to be encrypted is not tampered or stolen in the transmission and storage process.

The encryption process involves converting the original data into ciphertext so that the recipient with the correct key can decrypt the restored data to obtain the correct data in the ciphertext data block.

In addition, a secure hash algorithm (e.g., SHA-256) is performed on the generated ciphertext data block to generate a hash value, wherein the hash value is a digital fingerprint of the data, has uniqueness and irreversibility, is used for verifying the integrity and authenticity of the data, and the hash value generation process ensures that even if the data has a small change, the hash value is significantly changed, so that whether the data is tampered can be detected.

In addition, a fatigue driving data packet is generated according to the hash value and the ciphertext data block, wherein the fatigue driving data packet comprises the hash value and the ciphertext data block so as to ensure the integrity and traceability of the fatigue driving data packet, and the safety and verifiability of the fatigue driving data packet are also considered, so that the authenticity of the data can be quickly verified according to the hash value when the fatigue driving data packet is received.

In addition, the generated fatigue driving data packet is uploaded to a server, wherein the server can be a special server or a cloud storage platform of a related department, the uploading process can ensure the safety of data transmission through a safe communication protocol, and the server receives and stores the fatigue driving data packet to provide reliable evidence support for subsequent related operations.

Furthermore, the fatigue driving data packet in the server can be backed up periodically, so that the server can be restored quickly under the condition of data loss or damage, and the backup data can be stored in a plurality of geographic positions so as to prevent the data loss caused by natural disasters or human factors.

The embodiment realizes that after the driving track, the driving data and the vehicle image of the target vehicle are acquired, the fatigue driving data packet is generated through encryption processing and uploaded to the server, and the fatigue driving data packet is verified through the hash value, so that the fatigue driving data packet is not tampered or stolen in the transmission and storage processes, and the safety, reliability, integrity and traceability of the fatigue driving data are ensured.

In order to effectively solve the defects of the traditional technology in terms of judging the accuracy of fatigue driving in data fusion, the limitation of interference elimination, the reliability of evidence solidification and the like, the application provides an embodiment of a driving state monitoring device for realizing all or part of the content of driving state monitoring, which specifically comprises the following contents:

The first processing module 10 is configured to collect a driving track and driving data of the target vehicle, and determine a driving behavior of the target vehicle as a preliminary fatigue driving behavior when a continuous driving duration in the driving data exceeds a preset continuous driving duration threshold and a continuous driving speed of the target vehicle exceeds a preset speed threshold, where the driving data includes the continuous driving duration and the continuous driving speed;

The second processing module 20 is configured to determine a real-time road type corresponding to the driving track by using an inverse geocoding manner, obtain a vehicle image of the target vehicle photographed by the target vehicle through the gate in the middle of the driving track in case that the road type is a non-congestion type, and compare the vehicle image with registration information of the current target vehicle to obtain a comparison result, where the road type includes a congestion type and a non-congestion type, and the comparison result includes a vehicle consistency and a vehicle inconsistency;

And the third processing module 30 is configured to update the preliminary fatigue driving behavior of the target vehicle to be a fatigue driving behavior if the comparison result indicates that the vehicles are consistent, encrypt the driving track, the driving data and the vehicle image of the target vehicle to generate a fatigue driving data packet, and upload the fatigue driving data packet to the server.

As can be seen from the above description, the driving state monitoring device provided by the embodiment of the present application is capable of creatively collecting the driving track and the driving data of the target vehicle, determining the driving behavior of the target vehicle as the preliminary fatigue driving behavior when the continuous driving duration in the driving data exceeds the preset continuous driving duration threshold and the continuous driving speed of the target vehicle exceeds the preset speed threshold, determining the real-time road type corresponding to the driving track by the inverse geocoding mode, obtaining the vehicle image captured by the target vehicle through the bayonet in the middle of the driving track when the road type is the non-congestion type, comparing the vehicle image with the registration information of the current target vehicle to obtain the comparison result, updating the preliminary fatigue driving behavior of the target vehicle as the fatigue driving behavior when the comparison result is that the vehicle is consistent, and encrypting the driving track, the driving data and the vehicle image of the target vehicle to generate the fatigue driving data packet and uploading the fatigue driving data packet to the server. The method effectively solves the defects of the traditional technology in the aspects of judging the accuracy of the fatigue driving in data fusion, the limitation of interference elimination, the reliability of evidence solidification and the like, and remarkably improves the accuracy and the reliability of the fatigue driving judgment.

In order to effectively solve the defects of the traditional technology in terms of accuracy of data fusion, limited interference elimination, reliability of evidence solidification and the like of judging fatigue driving, and remarkably improve the accuracy and the reliability of fatigue driving judgment, the application provides an embodiment of electronic equipment for realizing all or part of contents in the driving state monitoring method, which specifically comprises the following contents:

The system comprises a processor (processor), a memory (memory), a communication interface (Communications Interface) and a bus, wherein the processor, the memory and the communication interface are in communication with each other through the bus, the communication interface is used for realizing information transmission between a driving state monitoring device and related equipment such as a core service system, a user terminal and a related database, and the logic controller can be a desktop computer, a tablet personal computer, a mobile terminal and the like, and the embodiment is not limited to the above. In this embodiment, the logic controller may refer to an embodiment of the driving state monitoring method and an embodiment of the driving state monitoring device in the embodiments, and the contents thereof are incorporated herein, and the repetition is omitted.

It is understood that the user terminal may include a smart phone, a tablet electronic device, a network set top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Wherein, intelligent wearing equipment can include intelligent glasses, intelligent wrist-watch, intelligent bracelet etc..

In practical applications, part of the driving state monitoring method may be performed on the electronic device side as described above, or all operations may be performed in the client device. Specifically, the selection may be made according to the processing capability of the client device, and restrictions of the use scenario of the user. The application is not limited in this regard. If all operations are performed in the client device, the client device may further include a processor.

The client device may have a communication module (i.e. a communication unit) and may be connected to a remote server in a communication manner, so as to implement data transmission with the server. The server may include a server on the side of the task scheduling center, and in other implementations may include a server of an intermediate platform, such as a server of a third party server platform having a communication link with the task scheduling center server. The server may include a single computer device, a server cluster formed by a plurality of servers, or a server structure of a distributed device.

Fig. 3 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 3, the electronic device 9600 can include a central processor 9100 and a memory 9140, the memory 9140 being coupled to the central processor 9100. It is noted that this fig. 3 is exemplary, and that other types of structures may be used in addition to or in place of the structures to implement telecommunications functions or other functions.

In one embodiment, the driving state monitoring method functions may be integrated into the central processor 9100. The central processor 9100 may be configured to perform the following control:

Step S101, acquiring a running track and running data of a target vehicle, and determining the running behavior of the target vehicle as a preliminary fatigue driving behavior when the continuous running duration in the running data exceeds a preset continuous running duration threshold value and the continuous running speed of the target vehicle exceeds a preset speed threshold value, wherein the running data comprises the continuous running duration and the continuous running speed;

Step S102, determining a real-time road type corresponding to a running track in an inverse geocoding mode, acquiring a vehicle image shot by a target vehicle through a bayonet in the middle of the running track under the condition that the road type is a non-congestion type, and comparing the vehicle image with registration information of the current target vehicle to obtain a comparison result, wherein the road type comprises the congestion type and the non-congestion type, and the comparison result comprises the consistency of vehicles and the non-consistency of vehicles;

As can be seen from the above description, by innovatively acquiring the driving track and the driving data of the target vehicle, when the continuous driving duration in the driving data exceeds the preset continuous driving duration threshold and the continuous driving speed of the target vehicle exceeds the preset speed threshold, determining the driving behavior of the target vehicle as the preliminary fatigue driving behavior, determining the real-time road type corresponding to the driving track by the inverse geocoding mode, acquiring the vehicle image captured by the target vehicle through the bayonet during the driving track if the road type is the non-congestion type, comparing the vehicle image with the registration information of the current target vehicle to obtain a comparison result, updating the preliminary fatigue driving behavior of the target vehicle as the fatigue driving behavior if the comparison result is that the vehicle is consistent, encrypting the driving track, the driving data and the vehicle image of the target vehicle to generate a fatigue driving data packet, and uploading the fatigue driving data packet to the server. The method effectively solves the defects of the traditional technology in the aspects of judging the accuracy of the fatigue driving in data fusion, the limitation of interference elimination, the reliability of evidence solidification and the like, and remarkably improves the accuracy and the reliability of the fatigue driving judgment.

In another embodiment, the driving state monitoring device may be configured separately from the central processor 9100, for example, the driving state monitoring device may be configured as a chip connected to the central processor 9100, and the driving state monitoring method function is implemented by control of the central processor.

As shown in fig. 3, the electronic device 9600 may further include a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 does not necessarily include all the components shown in fig. 3, and furthermore, the electronic device 9600 may include components not shown in fig. 3, to which reference is made in the prior art.

As shown in fig. 3, the central processor 9100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, which central processor 9100 receives inputs and controls the operation of the various components of the electronic device 9600.

The memory 9140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information about failure may be stored, and a program for executing the information may be stored. And the central processor 9100 can execute the program stored in the memory 9140 to realize information storage or processing, and the like.

The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, but not limited to, an LCD display.

The memory 9140 may be a solid state memory such as Read Only Memory (ROM), random Access Memory (RAM), SIM card, etc. But also a memory which holds information even when powered down, can be selectively erased and provided with further data, an example of which is sometimes referred to as EPROM or the like. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 storing application programs and function programs or a flow for executing operations of the electronic device 9600 by the central processor 9100.

The memory 9140 may also include a data store 9143, the data store 9143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, address book applications, etc.).

The communication module 9110 is a transmitter/receiver that transmits and receives signals via the antenna 9111. The communication module 9110 (transmitter/receiver) is coupled to the central processor 9100 to provide input signals and receive output signals, as in the case of conventional mobile communication terminals.

Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, etc., may be provided in the same electronic device. The communication module 9110 (transmitter/receiver) is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and to receive audio input from the microphone 9132 to implement usual telecommunications functions. The audio processor 9130 can include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100 so that sound can be recorded locally through the microphone 9132 and sound stored locally can be played through the speaker 9131.

The embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps in the driving state monitoring method in which the execution subject is the server or the client in the above embodiment, the computer-readable storage medium storing thereon a computer program which, when executed by a processor, implements all the steps in the driving state monitoring method in which the execution subject is the server or the client in the above embodiment, for example, the processor implements the following steps when executing the computer program:

As can be seen from the above description, the computer readable storage medium provided by the embodiment of the present application acquires, through innovatively, a driving track and driving data of a target vehicle, determines a driving behavior of the target vehicle as a preliminary fatigue driving behavior when a continuous driving duration in the driving data exceeds a preset continuous driving duration threshold and a continuous driving speed of the target vehicle exceeds a preset speed threshold, determines a real-time road type corresponding to the driving track through a reverse geocoding manner, acquires a vehicle image captured by the target vehicle through a bayonet in the middle of the driving track when the road type is a non-congestion type, compares the vehicle image with registration information of a current target vehicle to obtain a comparison result, updates the preliminary fatigue driving behavior of the target vehicle as the fatigue driving behavior when the comparison result is that the vehicle is consistent, encrypts the driving track, the driving data and the vehicle image of the target vehicle to generate a fatigue driving data packet, and uploads the fatigue driving data packet to a server. The method effectively solves the defects of the traditional technology in the aspects of judging the accuracy of the fatigue driving in data fusion, the limitation of interference elimination, the reliability of evidence solidification and the like, and remarkably improves the accuracy and the reliability of the fatigue driving judgment.

The embodiment of the present application further provides a computer program product capable of implementing all the steps in the driving state monitoring method in which the execution subject is the server or the client in the above embodiment, and the computer program/instructions implement the steps of the driving state monitoring method when executed by the processor, for example, the computer program/instructions implement the steps of:

As can be seen from the above description, the computer program product provided by the embodiment of the present application acquires, through innovatively, the driving track and the driving data of the target vehicle, determines the driving behavior of the target vehicle as the preliminary fatigue driving behavior when the continuous driving duration in the driving data exceeds the preset continuous driving duration threshold and the continuous driving speed of the target vehicle exceeds the preset speed threshold, determines the real-time road type corresponding to the driving track through the inverse geocoding method, acquires the vehicle image captured by the target vehicle through the bayonet in the middle of the driving track when the road type is the non-congestion type, compares the vehicle image with the registration information of the current target vehicle to obtain a comparison result, updates the preliminary fatigue driving behavior of the target vehicle as the fatigue driving behavior when the comparison result is that the vehicle is consistent, and encrypts the driving track, the driving data and the vehicle image of the target vehicle to generate a fatigue driving data packet and uploads the fatigue driving data packet to the server. The method effectively solves the defects of the traditional technology in the aspects of judging the accuracy of the fatigue driving in data fusion, the limitation of interference elimination, the reliability of evidence solidification and the like, and remarkably improves the accuracy and the reliability of the fatigue driving judgment.

It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While the principles and embodiments of the present invention have been described in detail in the foregoing application of the principles and embodiments of the present invention, the above examples are provided for the purpose of aiding in the understanding of the principles and concepts of the present invention and may be varied in many ways by those of ordinary skill in the art in light of the teachings of the present invention, and the above descriptions should not be construed as limiting the invention.

Claims

1. A driving state monitoring method, characterized in that the method comprises:

Determining a real-time road type corresponding to the running track in an inverse geocoding mode, acquiring a vehicle image shot by the target vehicle through a bayonet in the middle of the running track under the condition that the road type is a non-congestion type, and comparing the vehicle image with the current registration information of the target vehicle to obtain a comparison result, wherein the road type comprises a congestion type and a non-congestion type, and the comparison result comprises a vehicle consistency and a vehicle non-consistency;

and under the condition that the comparison result shows that the vehicles are consistent, updating the preliminary fatigue driving behavior of the target vehicle into fatigue driving behavior, and carrying out encryption processing on the running track of the target vehicle, the running data and the vehicle image to generate a fatigue driving data packet and uploading the fatigue driving data packet to a server.

2. The method according to claim 1, wherein the determining the real-time road type corresponding to the driving track by the inverse geocoding method includes:

Inputting the initial coordinates and the real-time coordinates of the running track to a map interface, and obtaining geographic position information corresponding to the initial coordinates serving as a starting point, the real-time coordinates serving as an ending point and the running track serving as a track, wherein the geographic position information comprises road names and real-time congestion indexes corresponding to all roads;

determining each initial road type corresponding to the running track, determining the road type corresponding to the current running track as the congestion type when the initial congestion type exceeding a preset congestion quantity threshold exists in the initial road types, and updating the running behavior corresponding to the target vehicle as non-fatigue driving behavior.

3. The method according to claim 1, wherein comparing the vehicle image with registration information of the current target vehicle to obtain a comparison result includes:

And when the license plate comparison result is consistent, extracting vehicle appearance characteristics in the vehicle image, and comparing the vehicle appearance characteristics with the vehicle appearance characteristics in the registration information to obtain the comparison result, wherein the vehicle appearance characteristics comprise vehicle body color, vehicle type and vehicle identification.

4. The method according to claim 3, wherein after obtaining the license plate comparison result, further comprising:

When the license plate comparison result is inconsistent, acquiring a historical driving image of the target vehicle, and comparing the historical driving image, the vehicle image and the registration information to obtain a fake-licensed comparison result, wherein the fake-licensed comparison result is a suspicious vehicle and a recognition error vehicle;

And when the fake license plate comparison result is that the wrong vehicle is identified, the step of acquiring the vehicle image shot by the target vehicle through a bayonet in the midway of the driving track is re-executed until the comparison result is obtained.

5. The method as recited in claim 1, further comprising:

under the condition that the continuous running speed is lower than the preset speed threshold, determining low-speed running duration corresponding to the continuous running speed lower than the preset speed threshold;

Initializing the travel track and the travel data of the target vehicle to re-determine the travel track and the travel data of the target vehicle when the low-speed travel duration exceeds a preset low-speed travel duration threshold;

6. The method according to claim 1, further comprising, after collecting the travel track and the travel data of the target vehicle:

under the condition that continuous lost data points exist in the running track, determining the lost starting time, the lost ending time, the lost duration and the lost position of the lost data points;

7. The method of claim 1, wherein encrypting the travel track of the target vehicle, the travel data, and the vehicle image to generate a fatigue driving data packet and uploading to a server comprises:

Encrypting the running track, the running data and the vehicle image of the target vehicle through a preset encryption algorithm to generate a ciphertext data block;

and executing safe hash algorithm operation on the ciphertext data block, generating a hash value, generating a fatigue driving data packet based on the hash value and the ciphertext data block, and uploading the fatigue driving data packet to a server.

8. A driving state monitoring device, characterized in that the device comprises:

The first processing module is used for collecting the running track and running data of the target vehicle, and determining the running behavior of the target vehicle as the preliminary fatigue driving behavior when the continuous running duration in the running data exceeds a preset continuous running duration threshold value and the continuous running speed of the target vehicle exceeds a preset speed threshold value, wherein the running data comprises the continuous running duration and the continuous running speed;

The second processing module is used for determining a real-time road type corresponding to the running track in an inverse geocoding mode, acquiring a vehicle image shot by the target vehicle through a bayonet in the middle of the running track under the condition that the road type is a non-congestion type, and comparing the vehicle image with the registration information of the current target vehicle to obtain a comparison result, wherein the road type comprises a congestion type and a non-congestion type, and the comparison result comprises a vehicle consistency and a vehicle non-consistency;

And the third processing module is used for updating the preliminary fatigue driving behavior of the target vehicle into fatigue driving behavior under the condition that the comparison result shows that the vehicles are consistent, and carrying out encryption processing on the running track of the target vehicle, the running data and the vehicle image to generate a fatigue driving data packet and uploading the fatigue driving data packet to a server.

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the driving state monitoring method of any one of claims 1 to 7 when the program is executed by the processor.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the driving state monitoring method according to any one of claims 1 to 7.