CN111563456A - Driving behavior early warning method and system - Google Patents
Driving behavior early warning method and system Download PDFInfo
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- CN111563456A CN111563456A CN202010384120.1A CN202010384120A CN111563456A CN 111563456 A CN111563456 A CN 111563456A CN 202010384120 A CN202010384120 A CN 202010384120A CN 111563456 A CN111563456 A CN 111563456A
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Abstract
The invention discloses a driving behavior early warning method and a driving behavior early warning system, wherein the method comprises the following steps: the method comprises the steps of obtaining behavior information of a driver and passengers, extracting behavior characteristics from the behavior information, matching the behavior characteristics with behavior characteristic samples in a preset behavior database, taking the behavior characteristic samples successfully matched as target behavior samples, searching corresponding early warning strategies according to the target behavior samples, executing the early warning strategies, monitoring the behavior information of the driver and passengers, and executing the early warning strategies in time when a crisis situation occurs, so that real-time monitoring of the driving behavior is achieved, and safety of vehicle driving and user experience are improved.
Description
Technical Field
The invention relates to the technical field of vehicle-mounted monitoring, in particular to a driving behavior early warning method and a driving behavior early warning system.
Background
Along with the improvement of living standard of people, the automobile gradually becomes an indispensable travel tool when people go out, automobile services such as time-sharing lease, shared trip, key replacement are also gradually accepted by the public, in order to realize customer identity authentication and personalized setting and guarantee the safety of the driving process, a camera monitoring system facing a driver is assembled on the automobile, the identity of the user is identified by the camera, face brushing identification is carried out to start the automobile, then the system carries out related personalized setting of the automobile according to the identity of the user, for example, a seat of the automobile is set to be a proper position of the user, and thus, a physical key can be replaced to realize the purpose of shared trip. On the other hand, the L3-class automatic driving system needs to be able to take over the vehicle in time when the automatic driving system cannot handle the vehicle, so that the state of the driver needs to be monitored to prevent the situation that the state of the driver is not concentrated or the driver falls asleep from affecting the safe driving of the vehicle. It can be seen that, a driver monitoring system is indispensable in the L3-level automatic driving system, and the driver monitoring system needs to monitor the attention state and fatigue state of the driver and ensure that the driver can take over the vehicle at any time, so how to improve the safety and user experience of vehicle driving becomes a problem to be solved urgently.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a driving behavior early warning method and a driving behavior early warning system, and aims to solve the technical problem that the driving safety and the user experience of a vehicle cannot be guaranteed in the prior art.
In order to achieve the above object, the present invention provides a driving behavior early warning method, comprising the steps of:
acquiring behavior information of a driver and a passenger, and extracting behavior characteristics from the behavior information;
matching the behavior characteristics with behavior characteristic samples in a preset behavior database, and taking the successfully matched behavior characteristic samples as target behavior samples;
and searching a corresponding early warning strategy according to the target behavior sample, and executing the early warning strategy.
Preferably, before the step of obtaining behavior information of the driver and extracting behavior features from the behavior information, the method further includes:
detecting whether a driver of the driver and the passenger has driving authority;
and when the driver has the driving right, executing the steps of acquiring the behavior information of the driver and extracting the behavior characteristics from the behavior information.
Preferably, the step of detecting whether a driver of the driver and the passenger has driving authority includes:
collecting facial image information of a driver in a driver and a passenger, and extracting facial features from the facial image information;
matching the facial features with facial feature samples stored in a preset behavior database, and taking the successfully matched facial feature samples as target facial samples;
and detecting whether the driver has driving authority or not according to the target face sample.
Preferably, when the driver has the driving right, the step of acquiring behavior information of the driver and extracting behavior features from the behavior information is performed, and specifically includes:
when the driver has the driving right, acquiring driving preference information of the driver from a personal database corresponding to the target face sample;
and configuring the vehicle according to the personal preference information, executing the step of acquiring the behavior information of the driver and the crew and extracting the behavior characteristics from the behavior information.
Preferably, the step of acquiring behavior information of the driver and the crew and extracting behavior features from the behavior information specifically includes:
acquiring behavior information of a driver in a driver and a passenger, and extracting behavior characteristics from the behavior information of the driver, wherein the behavior characteristics comprise fatigue attribute characteristics and driving state characteristics;
wherein the fatigue attribute features include eye closure frequency, mouth opening degree, eye opening degree, action occurrence frequency and action duration;
the driving state characteristics include a continuous driving period and an accumulated driving period.
Preferably, the step of acquiring behavior information of the driver and the crew and extracting behavior features from the behavior information specifically includes:
acquiring behavior information of passengers in a driver and passengers, and extracting behavior characteristics from the behavior information of the passengers, wherein the behavior characteristics comprise life body state characteristics;
wherein the vital body state characteristics include sitting posture, respiratory rate, heartbeat rate, and body temperature.
Preferably, the step of matching the behavior characteristics with behavior characteristic samples in a preset behavior database, and taking the successfully matched behavior characteristic samples as target behavior samples specifically includes:
matching the behavior characteristics with behavior characteristic samples in a preset behavior database, and acquiring matching degree;
and when the matching degree is greater than or equal to the preset matching degree, judging that the matching is successful, and taking the behavior characteristic sample which is successfully matched as a target behavior sample.
Preferably, the step of searching for a corresponding early warning policy according to the target behavior sample and executing the early warning policy specifically includes:
determining a danger level according to the target behavior sample and the matching degree;
and searching a corresponding early warning strategy according to the danger level, and executing the early warning strategy.
In addition, in order to achieve the above object, the present invention further provides a driving behavior early warning system, including:
the characteristic extraction module is used for acquiring behavior information of drivers and passengers and extracting behavior characteristics from the behavior information;
the characteristic matching module is used for matching the behavior characteristics with behavior characteristic samples in a preset behavior database and taking the successfully matched behavior characteristic samples as target behavior samples;
and the early warning module is used for searching a corresponding early warning strategy according to the target behavior sample and executing the early warning strategy.
Preferably, the feature extraction module is further configured to acquire behavior information of a driver in a driver, and extract behavior features from the behavior information of the driver, where the behavior features include fatigue attribute features and driving state features;
wherein the fatigue attribute features include eye closure frequency, mouth opening degree, eye opening degree, action occurrence frequency and action duration;
the driving state characteristics include a continuous driving period and an accumulated driving period.
Preferably, the feature extraction module is further configured to acquire behavior information of passengers in a driver, and extract behavior features from the behavior information of the passengers, where the behavior features include life form features; wherein the vital body state characteristics include sitting posture, respiratory rate, heartbeat rate, and body temperature.
The invention monitors the behavior information of the driver and passengers, executes the early warning strategy in time when the crisis situation occurs, realizes the real-time monitoring of the driving behavior, improves the driving safety and the user experience of the vehicle, improves the judgment accuracy of the behavior information by refining the behavior characteristics corresponding to the behavior information of the driver and passengers, matches the behavior characteristics with the behavior characteristic samples in the preset behavior database by extracting the behavior characteristics from the behavior information, takes the successfully matched behavior characteristic samples as the target behavior samples, determines the danger level according to the target behavior samples and the matching degree, searches the corresponding early warning strategy according to the danger level, and executes the early warning strategy to further improve the intelligence degree of the early warning information and the driving safety of the vehicle.
Drawings
Fig. 1 is a schematic flow chart of a first embodiment of a driving behavior early warning method according to the present invention;
FIG. 2 is a flowchart illustrating a driving behavior warning method according to a second embodiment of the present invention;
fig. 3 is a block diagram showing the structure of a first embodiment of the driving behavior warning system according to the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the invention provides a driving behavior early warning method, and referring to fig. 1, fig. 1 is a flow diagram of a first embodiment of the driving behavior early warning method.
In this embodiment, the driving behavior early warning method includes the following steps:
step S10: acquiring behavior information of a driver and a passenger, and extracting behavior characteristics from the behavior information;
it is easy to understand that the execution main body of this embodiment may be an Electronic Control Unit (ECU), or may be another control Unit composed of a Microprocessor (MCU), a memory, an input/output interface (I/O), an analog-to-digital converter (a/D), and an integrated circuit for shaping and driving, where the driver includes a driver and a passenger, and the vehicle is equipped with a plurality of cameras, which can respectively monitor behavior information of the driver, behavior information of the passenger, vehicle front information, vehicle rear information, and vehicle state information.
In a specific implementation, the present embodiment may be configured to obtain behavior information of a driver among drivers and passengers, and extract behavior features from the behavior information, where the behavior features include fatigue attribute features and driving state features, the fatigue attribute features include eye closing frequency, mouth opening degree, eye opening degree, action occurrence frequency, action duration time, and the like, and the driving state features include continuous driving duration, accumulated driving duration, and the like; the behavior feature extraction method comprises the steps of obtaining behavior information of passengers in drivers and passengers, extracting behavior features from the behavior information of the passengers, wherein the behavior features comprise life body state features, wherein the life body state features comprise sitting postures, breathing frequencies, heartbeat frequencies, body temperatures, gas components in a preset range (mainly detecting the concentration of carbon dioxide and oxygen in the preset range), whether sounds conforming to crying voice prints exist, and whether safety belts are locked.
It should be understood that the above is only an example, and the technical solution of the present embodiment is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited to this.
Step S20: matching the behavior characteristics with behavior characteristic samples in a preset behavior database, and taking the successfully matched behavior characteristic samples as target behavior samples;
it should be noted that when the behavior characteristics of the driver and the passenger are obtained, the behavior characteristics are matched with behavior characteristic samples in a preset behavior database, the successfully matched behavior characteristic samples are taken as target behavior samples, the preset behavior database stores judgment standards corresponding to various data in the fatigue attribute characteristics, the driving state characteristics and the life state characteristics, and the behavior characteristic samples established according to the judgment standards, if the behavior characteristic samples of the yawning is set to have the eye closure degree less than or equal to 50% of the initial characteristics of the driver and the mouth opening degree greater than or equal to 130% of the initial characteristics of the driver, and the action duration time greater than or equal to 2 seconds, then when it is detected that the eye closure degree of the driver at a certain moment is 20% of the initial characteristics, the mouth opening degree is 170% of the initial characteristics, and the duration time is 3 seconds, the behavior characteristic of the driver at the moment can be judged to be in accordance with the yawning behavior characteristic sample in the behavior characteristic samples, and the yawning behavior characteristic sample is used as a target behavior sample. For another example, if the behavior feature sample of the overtime fatigue driving is set to be that the continuous driving time of the same driver is greater than or equal to 3 hours, when it is detected that the continuous driving of the same driver exceeds three hours, it is determined that the behavior feature sample conforms to the overtime fatigue driving in the behavior feature sample, and the behavior feature sample of the overtime fatigue driving is used as the target behavior sample. For another example, if the behavior feature sample left by the infant is set to be that the driver is not present in the driving seat, the sound conforming to the crying voiceprint is present, and the duration of the crying voiceprint is greater than or equal to 15 minutes, then it is detected that the driver is not present in the driving seat, and the sound conforming to the crying voiceprint is present, and when the duration of the sound conforming to the crying voiceprint exceeds 15 minutes, it is determined that the behavior feature of the passenger conforms to the behavior feature sample left by the infant in the behavior feature sample, and the behavior feature sample is taken as the target behavior sample.
It is easy to understand that, in this implementation, the behavior feature may be further matched with a behavior feature sample in a preset behavior database, a matching degree is obtained, when the matching degree is greater than or equal to the preset matching degree, it is determined that the matching is successful, and the successfully matched behavior feature sample is taken as a target behavior sample, for example, if the coverage rate of a preset area of the steering wheel exceeds 60% in a preset time period (for example, 5 minutes) based on the behavior feature sample of the steering wheel in the behavior feature sample of the driver's normative driving is set, and the number of different detected fingerprints is greater than or equal to 6, and when the coverage rate fluctuation of the preset area is detected to be 50% to 70% in 5 minutes and the number of different fingerprints fluctuates between 5 and 7, the matching degree may be determined according to the fluctuation frequency of the coverage rate and the fluctuation frequency of the fingerprints, so as to further determine whether the matching is successful, and if so, the behavior feature sample of the driver's call is set as that the, The hand of the driver holds the electronic equipment with the communication function, or the ear of the driver wears the electronic equipment with the communication function, or the communication function in the vehicle is started and the mouth opening and closing action is regular. When the vehicle is detected to be in a driving state, a driver only wears the electronic equipment with the communication function at the ear part, but the communication function is not started, and the opening and closing rule of the mouth part is not easy to obtain, the matching degree can be determined by comparing the opening and closing frequency of the mouth part with the preset conversation frequency, and whether the matching is successful or not is further judged.
It should be understood that the above is only an example, and the technical solution of the present embodiment is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited to this.
Step S30: and searching a corresponding early warning strategy according to the target behavior sample, and executing the early warning strategy.
It should be noted that, in this embodiment, a corresponding early warning policy needs to be searched according to the target behavior sample, and the early warning policy is executed, in the above embodiment, when it is determined that the behavior feature of the driver at the moment conforms to the behavior feature sample yawned in the behavior feature sample, corresponding preset voice prompt information may be played or preset prompt information may be displayed, and a preset audio device is started. For another example, when it is determined that the driver meets the behavior feature sample of overtime fatigue driving in the behavior feature samples, the corresponding preset voice prompt information may be played or the preset prompt information may be displayed, the corresponding audio device may be started, and the corresponding notification may be displayed to the passenger.
It is easy to understand that, this embodiment may further determine a danger level according to the target behavior sample and the matching degree, search a corresponding early warning policy according to the danger level, and execute the early warning policy, for example, when it is determined that the behavior feature of the driver at the moment conforms to the behavior feature sample of yawning in the behavior feature sample, determine that the danger level is first level, and execute the early warning policy, when it is determined that the driver conforms to the behavior feature sample of overtime fatigue driving in the behavior feature sample, determine that the danger level is second level, and execute the early warning policy, but when it is detected that the behavior feature of the driver conforms to both the behavior feature sample of yawning in the behavior feature sample and the behavior feature sample of overtime fatigue driving in the behavior feature sample, determine that the danger level is fourth level, at this time, the vehicle driving speed needs to be slowed down, and corresponding prompt information is continuously played or displayed at a preset frequency, and increasing the danger levels of all driving behaviors of the driver according with the behavior feature samples by one level within a preset time length, if the original behavior feature samples with one level of danger are yawned, when the driver continues the current driving behaviors in the state, determining that the danger levels are the second level, and executing an early warning strategy corresponding to the danger levels being the second level.
It should be understood that the above is only an example, and the technical solution of the present embodiment is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited to this.
The embodiment monitors the behavior information of drivers and passengers, executes the early warning strategy in time when a crisis situation occurs, realizes real-time monitoring of the driving behavior, improves the driving safety and user experience of vehicles, improves the accuracy of behavior information judgment by refining the behavior characteristics corresponding to the behavior information of the drivers and passengers, extracts the behavior characteristics from the behavior information, matches the behavior characteristics with behavior characteristic samples in a preset behavior database, uses the successfully matched behavior characteristic samples as target behavior samples, determines the danger level according to the target behavior samples and the matching degree, searches the corresponding early warning strategy according to the danger level, and executes the early warning strategy to further improve the intelligence degree of the early warning information and the driving safety of the vehicles.
Referring to fig. 2, fig. 2 is a flowchart illustrating a driving behavior early warning method according to a second embodiment of the present invention.
Based on the first embodiment, in this embodiment, before the step S10, the method includes:
step 00: detecting whether a driver of the driver and the passenger has driving authority;
it is easy to understand that before acquiring behavior information of a driver, whether the driver in the driver has driving authority needs to be detected, whether the vehicle is in a drivable state can be detected through preset software, whether target vehicle unlocking plain codes are input can be detected when the vehicle is in the drivable state, whether the driver has the driving authority can be determined when the input is correct, the target vehicle unlocking plain codes are generated based on user information received by the preset software, and the user information can be user payment information, user authority information and the like.
In this embodiment, the image capturing device installed in the vehicle may further be used to collect facial image information of a driver among the drivers and passengers, extract facial features from the facial image information, match the facial features with facial feature samples stored in a preset behavior database, use the successfully matched facial feature samples as target facial samples, and detect whether the driver has driving authority according to the target facial samples.
It should be understood that the above is only an example, and the technical solution of the present embodiment is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited to this.
Step 01: and when the driver has the driving authority, executing the steps of acquiring behavior information of the driver and extracting behavior characteristics from the behavior information.
In a specific implementation, the preset software may register personal information and generate a personal database based on the input personal information, and may further input driving preference information, such as seat belt stretch range, seat position, preference tracks, etc., into the personal database, where the driving preference information may also be generated according to the usage habits of the driver and the passenger, that is, when the driver has the driving right, the driving preference information of the driver is obtained from the personal database corresponding to the target face sample, vehicle configuration is performed according to the personal preference information, and a plurality of preset camera devices are activated to perform the step of obtaining behavior information of the driver and extracting behavior characteristics from the behavior information, for example, when the driver has the driving right, the seat position preference and the seat belt stretch length preference corresponding to the driver are obtained from the personal database established based on the target face sample, and moving the seat of the driving seat to a position corresponding to the seat position preference, adjusting the safety belt of the driving seat according to the telescopic length preference, as in the embodiment, when the behavior characteristic of the driver at the moment is judged to be in accordance with the behavior characteristic sample dug under the action of yawning in the behavior characteristic sample, playing corresponding preset voice prompt information or displaying preset prompt information, starting preset audio equipment, acquiring the driving preference information of the driver, starting the preset audio equipment to play the preference tracks of the driver or the tracks preset by the driver and corresponding to the behavior characteristic sample dug under the action of yawning, and further connecting music playing software preset by the driver and the driver to perform corresponding music record action.
It should be understood that the above is only an example, and the technical solution of the present embodiment is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited to this.
The embodiment realizes the rapid management of the vehicle authority by detecting whether the driver in the driver and the crew has the driving authority, ensures the privacy of the user by establishing the personal database, and further improves the safety of the driving behavior and the user experience by configuring the vehicle based on the personal data.
Based on the above embodiments, a first embodiment of the driving behavior early warning system of the present invention is proposed, and referring to fig. 3, fig. 3 is a block diagram of the structure of the first embodiment of the driving behavior early warning system of the present invention;
in this embodiment, the driving behavior warning system includes:
a feature extraction module 1001, configured to obtain behavior information of a driver and a passenger, and extract behavior features from the behavior information;
the feature matching module 1002 is configured to match the behavior features with behavior feature samples in a preset behavior database, and use the behavior feature samples successfully matched as target behavior samples;
and the early warning module 1003 is configured to search for a corresponding early warning policy according to the target behavior sample, and execute the early warning policy.
The embodiment monitors the behavior information of drivers and passengers, executes the early warning strategy in time when a crisis situation occurs, realizes real-time monitoring of the driving behavior, improves the driving safety and user experience of vehicles, improves the accuracy of behavior information judgment by refining the behavior characteristics corresponding to the behavior information of the drivers and passengers, extracts the behavior characteristics from the behavior information, matches the behavior characteristics with behavior characteristic samples in a preset behavior database, uses the successfully matched behavior characteristic samples as target behavior samples, determines the danger level according to the target behavior samples and the matching degree, searches the corresponding early warning strategy according to the danger level, and executes the early warning strategy to further improve the intelligence degree of the early warning information and the driving safety of the vehicles.
Based on the first embodiment of the driving behavior early warning system of the present invention, a second embodiment of the driving behavior early warning system of the present invention is proposed.
In this embodiment, the feature extraction module 1001 is further configured to detect whether a driver of an occupant has driving authority, and when the driver has the driving authority, perform the operation of acquiring behavior information of the occupant and extracting behavior features from the behavior information;
the face recognition device is also used for collecting face image information of a driver in the driver and passengers and extracting facial features from the face image information;
the facial features are matched with facial feature samples stored in a preset behavior database, and the successfully matched facial feature samples are used as target facial samples;
further for detecting whether the driver has driving authority based on the target face sample;
the driver is also used for acquiring the driving preference information of the driver from the personal database corresponding to the target face sample when the driver has the driving right;
the vehicle configuration is carried out according to the personal preference information, the behavior information of the driver and the passengers is obtained, and the operation of extracting behavior characteristics from the behavior information is carried out;
the fatigue detection system is also used for acquiring behavior information of a driver in a driver and passengers and extracting behavior characteristics from the behavior information of the driver, wherein the behavior characteristics comprise fatigue attribute characteristics and driving state characteristics; wherein the fatigue attribute features include eye closure frequency, mouth opening degree, eye opening degree, action occurrence frequency and action duration; the driving state characteristics include a continuous driving period and an accumulated driving period.
The behavior information of passengers in the driver and the crew is acquired, and behavior characteristics are extracted from the behavior information of the passengers, wherein the behavior characteristics comprise life physical state characteristics; wherein the vital body state characteristics include sitting posture, respiratory rate, heartbeat rate, and body temperature.
The feature matching module 1002 is further configured to match the behavior features with behavior feature samples in a preset behavior database, and obtain a matching degree;
and the matching module is also used for judging that the matching is successful when the matching degree is greater than or equal to the preset matching degree, and taking the behavior characteristic sample which is successfully matched as a target behavior sample.
The early warning module 1003 is further configured to determine a risk level according to the target behavior sample and the matching degree;
and the early warning device is also used for searching a corresponding early warning strategy according to the danger level and executing the early warning strategy.
Other embodiments or specific implementation manners of the driving behavior early warning system of the invention can refer to the above method embodiments, and are not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., a rom/ram, a magnetic disk, an optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A driving behavior early warning method, characterized in that the method comprises:
acquiring behavior information of a driver and a passenger, and extracting behavior characteristics from the behavior information;
matching the behavior characteristics with behavior characteristic samples in a preset behavior database, and taking the successfully matched behavior characteristic samples as target behavior samples;
and searching a corresponding early warning strategy according to the target behavior sample, and executing the early warning strategy.
2. The method of claim 1, wherein the step of obtaining behavior information of the occupant and extracting behavior features from the behavior information is preceded by the step of:
detecting whether a driver of the driver and the passenger has driving authority;
and when the driver has the driving right, executing the steps of acquiring the behavior information of the driver and extracting the behavior characteristics from the behavior information.
3. The method of claim 2, wherein the step of detecting whether a driver of the occupants has driving authority comprises:
collecting facial image information of a driver in a driver and a passenger, and extracting facial features from the facial image information;
matching the facial features with facial feature samples stored in a preset behavior database, and taking the successfully matched facial feature samples as target facial samples;
and detecting whether the driver has driving authority or not according to the target face sample.
4. The method according to claim 2, wherein the step of obtaining behavior information of the occupant and extracting behavior characteristics from the behavior information is performed when the driver has the driving right, and specifically includes:
when the driver has the driving right, acquiring driving preference information of the driver from a personal database corresponding to the target face sample;
and configuring the vehicle according to the driving preference information, executing the step of acquiring the behavior information of the driver and the crew and extracting the behavior characteristics from the behavior information.
5. The method according to claim 1, wherein the step of obtaining behavior information of the occupant and extracting behavior features from the behavior information comprises:
acquiring behavior information of a driver in a driver and a passenger, and extracting behavior characteristics from the behavior information of the driver, wherein the behavior characteristics comprise fatigue attribute characteristics and driving state characteristics;
wherein the fatigue attribute features include eye closure frequency, mouth opening degree, eye opening degree, action occurrence frequency and action duration;
the driving state characteristics include a continuous driving period and an accumulated driving period.
6. The method according to claim 1, wherein the step of obtaining behavior information of the occupant and extracting behavior features from the behavior information comprises:
acquiring behavior information of passengers in a driver and passengers, and extracting behavior characteristics from the behavior information of the passengers, wherein the behavior characteristics comprise life body state characteristics;
wherein the vital body state characteristics include sitting posture, respiratory rate, heartbeat rate, and body temperature.
7. The method according to claim 1, wherein the step of matching the behavior characteristics with behavior characteristic samples in a preset behavior database and taking the successfully matched behavior characteristic samples as target behavior samples specifically comprises:
matching the behavior characteristics with behavior characteristic samples in a preset behavior database, and acquiring matching degree;
when the matching degree is greater than or equal to a preset matching degree, judging that the matching is successful, and taking the behavior characteristic sample which is successfully matched as a target behavior sample;
correspondingly, the step of searching for a corresponding early warning policy according to the target behavior sample and executing the early warning policy specifically includes:
determining a danger level according to the target behavior sample and the matching degree;
and searching a corresponding early warning strategy according to the danger level, and executing the early warning strategy.
8. A driving behavior warning system, characterized in that the system comprises:
the characteristic extraction module is used for acquiring behavior information of drivers and passengers and extracting behavior characteristics from the behavior information;
the characteristic matching module is used for matching the behavior characteristics with behavior characteristic samples in a preset behavior database and taking the successfully matched behavior characteristic samples as target behavior samples;
and the early warning module is used for searching a corresponding early warning strategy according to the target behavior sample and executing the early warning strategy.
9. The system of claim 8, wherein the feature extraction module is further configured to obtain behavior information of a driver of the driver and extract behavior features from the behavior information of the driver, wherein the behavior features include fatigue property features and driving state features;
wherein the fatigue attribute features include eye closure frequency, mouth opening degree, eye opening degree, action occurrence frequency and action duration;
the driving state characteristics include a continuous driving period and an accumulated driving period.
10. The system of claim 8, wherein the feature extraction module is further configured to obtain behavior information of a passenger in a driver, and extract behavior features from the behavior information of the passenger, wherein the behavior features include life status features;
wherein the vital body state characteristics include sitting posture, respiratory rate, heartbeat rate, and body temperature.
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