CN112215093A - Method and device for evaluating vehicle driving ability level - Google Patents
Method and device for evaluating vehicle driving ability level Download PDFInfo
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Abstract
The embodiment of the application discloses a method and a device for evaluating the driving ability level of a vehicle, which are used for evaluating the driving ability of a driving vehicle and a driver from multiple aspects. The method in the embodiment of the application comprises the following steps: acquiring target vehicle state information and target driving information under a real driving environment; analyzing the state information of the target vehicle and the target driving information through a safety recognition model, and generating current driving behavior data; comparing the current driving behavior data with standard driving behavior data, and generating judgment behavior data according to the comparison result; storing the current driving behavior data and the corresponding judging behavior data in a local database and uploading the current driving behavior data and the corresponding judging behavior data to a cloud database; generating driving capacity data by the driving behavior data required and taken out from the local database or the cloud database and the corresponding judgment behavior data through an evaluation model; and generating corresponding driving ability evaluation according to the driving ability data.
Description
Technical Field
The embodiment of the application relates to the field of data processing, in particular to a method and a device for evaluating a vehicle driving ability level.
Background
With the development of the current society, the automobile industry has also gained rapid development, and the appearance of the current vehicles and the perfection of road traffic facilities bring great convenience to daily trips of people.
Along with the increasing of the number of all vehicle people, the number of traffic accidents and the loss and harm caused by the accidents are more and more, the safety of the vehicle and the driver is more and more emphasized by people, the vehicle can only display partial running state information, for example, the vehicle can only display a very small amount of information such as the vehicle speed, the engine speed and the like on an instrument panel, the running environment of the vehicle, the driver and the action of the driver can not be comprehensively monitored, the formed evaluation is single, and therefore the driving ability level of the driver can not be scientifically and reasonably reported and evaluated.
Disclosure of Invention
The embodiment of the application provides a method and a device for evaluating the driving ability level of a vehicle, which can evaluate the driving ability of a driving vehicle and a driver from multiple aspects, so that the evaluation on the driving ability level of the driver has more stability and reliability.
In a first aspect, an embodiment of the present application provides a method for evaluating a driving ability level of a vehicle, including:
acquiring target vehicle state information in a real driving environment;
acquiring target driving information under a real driving environment, wherein the target driving information comprises current driving environment information and current driver driving behavior information;
analyzing the state information of the target vehicle and the target driving information through a safety recognition model, and generating current driving behavior data, wherein the current driving behavior data are operation data of the target vehicle in a current driving environment and behavior data of a current driver, and the safety recognition model is used for analyzing behavior states of the target vehicle and the driver;
comparing the current driving behavior data with standard driving behavior data, and generating judgment behavior data according to the comparison result on the steps and details of the operation behavior of the driver in the current driving behavior data;
storing the current driving behavior data and the corresponding judging behavior data in a local database and uploading the current driving behavior data and the corresponding judging behavior data to a cloud database;
generating driving capacity data by using the required driving behavior data and the corresponding judging behavior data which are extracted from the local database or the cloud database through an evaluation model, wherein the evaluation model is used for evaluating the driving behavior data and the corresponding judging behavior data which are extracted from the database;
and generating corresponding driving ability evaluation according to the driving ability data.
Optionally, after the driving performance data generated by the evaluation model according to the required driving performance data retrieved from the local database or the cloud database and the corresponding determination performance data, the method further includes:
updating the security identification model through the evaluation model.
Optionally, the acquiring target driving information in the real driving environment includes:
acquiring an action attitude image/video of a current driver under a real driving environment according to a camera in a target vehicle;
acquiring an image/video of the current surrounding environment of the target vehicle in the real driving environment according to a camera at the windshield of the target vehicle;
and acquiring target driving information according to the action posture image/video of the current driver and the image/video of the current surrounding environment.
Optionally, the acquiring the state information of the target vehicle in the real driving environment includes:
acquiring a sensing signal of a sensor on a target vehicle in the current environment, wherein the sensing signal is a signal carrying state data of the target vehicle;
and acquiring the state information of the target vehicle according to the sensing signal.
Optionally, after generating the corresponding driving ability evaluation according to the driving ability data, the method further includes:
and authorizing the driving ability evaluation to a related platform, wherein the related platform is a driver personal platform and a driving training platform, so that the driving ability evaluation is inquired by a user and an official party.
Optionally, after generating the corresponding driving ability evaluation according to the driving ability data, the method further includes:
and judging whether the area where the target vehicle exists is the area covered by the fifth generation mobile communication technology base station, if so, carrying out network communication by using a fifth generation mobile communication technology data terminal at the vehicle-mounted end of the target vehicle.
Optionally, after determining whether the area where the target vehicle exists is an area covered by a fifth-generation mobile communication technology base station, the method further includes:
if not, the communication link is established by utilizing a self-established wireless local area network base station mode to realize communication.
In a second aspect, an embodiment of the present application provides an apparatus for evaluating a driving ability level of a vehicle, including:
a first acquisition unit configured to acquire target vehicle state information in a real driving environment;
the second acquisition unit is used for acquiring target driving information under a real driving environment, wherein the target driving information comprises current driving environment information and current driver driving behavior information;
the first generation unit is used for analyzing the state information of the target vehicle and the target driving information through a safety recognition model and generating current driving behavior data, wherein the current driving behavior data are operation data of the target vehicle in a current driving environment and behavior data of a current driver, and the safety recognition model is used for analyzing behavior states of the target vehicle and the driver;
the judging unit is used for comparing the current driving behavior data with standard driving behavior data and generating judging behavior data according to the comparison result on the steps and details of the operation behavior of the driver in the current driving behavior data;
the storage unit is used for storing the current driving behavior data in a local database and uploading the current driving behavior data to a cloud database;
the second generation unit is used for generating driving capacity data by the driving behavior data required and the corresponding judgment behavior data which are extracted from the local database or the cloud database through an evaluation model, and the evaluation model is used for evaluating the driving behavior data extracted from the database and the corresponding judgment behavior data;
and the third generating unit is used for generating corresponding driving ability evaluation according to the driving ability data.
Optionally, the apparatus further comprises:
and the updating unit is used for updating the safety identification model through the evaluation model.
Optionally, the second obtaining unit includes:
the third acquisition module is used for acquiring an action posture image/video of the current driver in the real driving environment according to the camera in the target vehicle;
the fourth acquisition module is used for acquiring the image/video of the current surrounding environment of the target vehicle in the real driving environment according to the camera at the windshield of the target vehicle;
and the fifth acquisition module is used for acquiring target driving information according to the action posture image/video of the current driver and the image/video of the current surrounding environment.
Optionally, the first obtaining unit includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a sensing signal of a sensor on a target vehicle in the current environment, and the sensing signal is a signal carrying state data of the target vehicle;
and the sixth acquisition module is used for acquiring the state information of the target vehicle according to the sensing signal.
Optionally, the apparatus further comprises:
the authorization query unit is used for authorizing the driving ability evaluation to a related platform, wherein the related platform is a driver personal platform and a driving training platform so that a user and an official party can query the driving ability evaluation;
a first judgment unit, configured to judge whether an area where a target vehicle exists is an area covered by a fifth-generation mobile communication technology base station;
the first execution unit is used for establishing network communication by utilizing a fifth generation mobile communication technology data terminal at the vehicle-mounted end of the target vehicle when the first judgment unit determines that the area where the target vehicle exists is the area covered by the fifth generation mobile communication technology base station;
and the second execution unit is used for establishing a communication link by utilizing a self-established wireless local area network base station to realize communication when the first judgment unit determines that the area without the target vehicle is the area covered by the fifth generation mobile communication technology base station.
In a third aspect, an embodiment of the present application provides an evaluation device for a vehicle drivability level, including:
the device comprises a processor, a memory, an input and output unit and a bus;
the processor is connected with the memory, the input and output unit and the bus;
the processor specifically performs the following operations:
acquiring target vehicle state information in a real driving environment;
acquiring target driving information under a real driving environment, wherein the target driving information comprises current driving environment information and current driver driving behavior information;
analyzing the state information of the target vehicle and the target driving information through a safety recognition model, and generating current driving behavior data, wherein the current driving behavior data are operation data of the target vehicle in a current driving environment and behavior data of a current driver, and the safety recognition model is used for analyzing behavior states of the target vehicle and the driver;
comparing the current driving behavior data with standard driving behavior data, and generating judgment behavior data according to the comparison result on the steps and details of the operation behavior of the driver in the current driving behavior data;
storing the current driving behavior data and the corresponding judging behavior data in a local database and uploading the current driving behavior data and the corresponding judging behavior data to a cloud database;
generating driving capacity data by using the required driving behavior data and the corresponding judging behavior data which are extracted from the local database or the cloud database through an evaluation model, wherein the evaluation model is used for evaluating the driving behavior data and the corresponding judging behavior data which are extracted from the database;
and generating corresponding driving ability evaluation according to the driving ability data.
Optionally, the processor is further configured to perform the operations of any of the alternatives of the first aspect.
A computer readable storage medium having a program stored thereon, the program, when executed on a computer, performing the method of the first aspect as well as any of the alternatives of the first aspect.
According to the technical scheme, the embodiment of the application has the following advantages:
according to the method and the device for evaluating the vehicle driving ability level, the obtained target vehicle state information and the obtained target driving information under the real driving environment can be analyzed through the safety recognition model, current driving behavior data are generated, and the current driving behavior data can display the process data of a current driver and a driven vehicle; and then comparing the current driving behavior data with the standard behavior data to obtain a comparison result to generate judgment data, then storing the current driving behavior data and the corresponding judgment data in a database, calling the driving behavior data needing to be subjected to driving ability level evaluation and the corresponding judgment data from the database to generate driving ability data through evaluation model training when the target driving ability needs to be evaluated, and finally generating driving ability evaluation according to the driving ability data. Therefore, comprehensive monitoring can be carried out through the running environment of the vehicle, the driver and the operation of the driver, and the driving ability level evaluation of the driver is more stable and reliable.
Drawings
FIG. 1 is a schematic flow chart illustrating an embodiment of a method for evaluating a driving ability level of a vehicle according to an embodiment of the present disclosure;
2-1 and 2-2 are schematic flow charts illustrating another embodiment of a method for evaluating a driving ability level of a vehicle according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an embodiment of an evaluation device for vehicle drivability level according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of another embodiment of an evaluation device for vehicle drivability level according to an embodiment of the present application;
fig. 5 is a schematic flowchart of another embodiment of an apparatus for evaluating a vehicle drivability level according to an embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of the present invention.
The embodiment of the application discloses a method and a device for evaluating the driving ability level of a vehicle, which are used for evaluating the driving ability of a driving vehicle and a driver from multiple aspects, so that the evaluation on the driving ability level of the driver is more stable and reliable.
In this embodiment, the method for evaluating the driving ability level of the vehicle may be implemented in a system, a server, or a terminal, and is not specifically limited. For convenience of description, the embodiment of the present application uses the system as an example for the execution subject.
Referring to fig. 1, an embodiment of a method for evaluating a driving ability level of a vehicle according to an embodiment of the present application includes:
101. the system acquires state information of a target vehicle in a real driving environment;
the system needs to acquire driving state information generated by a target vehicle in a real driving environment during driving so as to obtain a motion state of a component of the target vehicle, and the motion state of the component of the target vehicle that can be acquired may be various, for example: the state of a vehicle door switch, the telescopic state of a safety belt, the accelerator depth state, the clutch treading depth state, the engine speed state, the states of various vehicle lamps, the gear state and the like, and specific target vehicle state information is not limited here.
102. The method comprises the steps that a system obtains target driving information under a real driving environment, wherein the target driving information comprises current driving environment information and current driver driving behavior information;
the system acquires target driving information generated in the real driving process of the vehicle so as to obtain the operation behavior of the vehicle driver for driving the vehicle and the action of the vehicle on the operation behavior of the driver. The current driving environment information may include various information, such as backing up and warehousing, hill starting, turning around in a narrow road, tunnel crossing, and the like, and the driving environment information that may be specifically acquired is not limited here.
The current driver driving behavior information may include a variety of information, such as: the driving behavior information of the driver is obtained by the method of driving the vehicle, and the driving behavior information is not limited here.
The implementation manner of obtaining the target driving information may be various, the driving environment information in the current real driving environment may be determined by using a GNSS positioning system, the driving behavior information of the current driver may be determined by scanning the operation of a driver in the vehicle by a thermal imaging system, the angle position and the orientation information of the target vehicle may also be obtained by using dual-antenna line positioning, and the specific implementation manner is not limited herein.
103. The system analyzes the state information of the target vehicle and the target driving information through a safety recognition model and generates current driving behavior data;
the system analyzes through a safety recognition model according to the state information of the current target vehicle and the current driving information to determine the operation content of the driver.
The safety identification model is a combination of one or more models with a data analysis function, can identify the target vehicle state data and the target driving behavior information data collected under different driving environments in real time, and outputs the result. The system carries out data real-time calculation through the safety recognition model, analyzes the operation behavior and details of the current driver in the real driving environment, and analyzes the relevance and independence of the running state of the target vehicle. For example: in a certain specified time period, the target vehicle state information and the target driving information are input into the safety recognition model for analysis, when the target vehicle goes up a slope, the driver turns right a steering lamp, the distance between the right wheel of the vehicle and the edge line is 30 centimeters, but the driver extinguishes in the process of going up the slope, the operation is not carried out in the accurate time period of starting or stopping, and the operation belongs to dangerous behaviors.
104. The system compares the current driving behavior data with standard driving behavior data, and generates judgment behavior data according to the comparison result on the steps and details of the operation behavior of the driver in the current driving behavior data;
when the system generates the current driving behavior data through the safety recognition model, the current driving behavior data is compared with the standard driving behavior data, for example: the current driving behavior data indicate that the line pressing behavior does not exist when the driver A backs up and enters the garage by using the target vehicle, but the hand brake is not completely released when the driver A restarts; the standard driving behavior data is that when the driver A backs a car and enters a garage by using the target vehicle, no line pressing behavior exists, and when the driver A restarts, the hand brake is completely released. And comparing the two data, judging that the backing-up and warehousing behaviors are correct, judging that the restarting behaviors are wrong, and generating judgment behavior data according to the compared result.
105. The system stores the current driving behavior data and the corresponding judgment behavior data in a local database and uploads the current driving behavior data and the corresponding judgment behavior data to a cloud database;
the system uploads the current driving behavior data of the driving to the cloud and stores the current driving behavior data in the local database, so that other operations such as system calling, query and the like can be performed on the data after networking, and the specific operation mode is not limited here. After the system generates the current driving behavior data through the safety recognition model, the driving behavior data needs to be compared with the standard behavior data, so that accurate analysis data is obtained.
The storage database is used for temporary storage of the driving behavior data and total storage calculation of historical driving behavior data.
106. The system generates driving capacity data by the aid of an evaluation model according to the required driving behavior data called from the local database or the cloud database and the corresponding judgment behavior data;
after the system uploads the current driving behavior data of the driving to the cloud and stores the current driving behavior data in the local database, when a certain user needs to analyze the driving behavior data of the user, the driving behavior data needed by the user can be called from the local database or the cloud database and input into the evaluation model, and therefore driving capacity data are generated. For example: the driver A calls current driving behavior data of the driver A from the database and inputs the current driving behavior data into the evaluation model, the evaluation model can set standard evaluation indexes from five aspects of control ability, space perception ability, safety awareness, growing scene recording and pre-processing ability to analyze the input driving behavior data, and the evaluation model outputs scores obtained through analysis and calculation to generate driving ability data.
107. And the system generates corresponding driving ability evaluation according to the driving ability data.
And the system correspondingly evaluates the driving ability according to the score of the driving ability data. For example: the method comprises the steps that the single-party evaluation in an evaluation model is 100 points, driving A calculates and obtains driving ability data of the driving A according to the evaluation model, the display control ability is 70 points, the space perception ability is 65 points, the safety awareness is 65 points, the growth scene record is 75 points and the pretreatment ability is 65 points, the total point is 340 points, the driving ability evaluation range is 0-300 points and is a fail point, 301-350 points and is a pass point, 351-425 points and is good, 426-500 points and is excellent, and therefore the system generates corresponding driving ability evaluation of the driving A according to the total point 340 points and the evaluation range. The above is only one method for evaluating the driving ability, and more specific implementation manners are not limited herein.
In the embodiment, the system firstly inputs the acquired state information and driving information of the target vehicle into a safety identification model for analysis to obtain current driving behavior data, then compares the current driving behavior data with standard behavior data to generate judgment data, then stores the current driving behavior data and the corresponding judgment data into a database, calls the current driving behavior data to be evaluated from the database and inputs the judgment data into an evaluation model for learning when driving capacity evaluation needs to be carried out on the target vehicle and a driver to generate driving capacity data, and finally generates corresponding driving capacity evaluation according to the driving capacity data. Therefore, the driving ability data can be obtained by learning and analyzing the current driving behavior data, so that the driving ability of the driving vehicle and the driver can be evaluated from multiple aspects, and the stability and the reliability of the data are improved.
For clarity of description of the evaluation method of the driving ability level of the vehicle, the embodiment of the present application will be described in detail with reference to fig. 2-1 and 2-2.
Referring to fig. 2-1 and 2-2, another embodiment of the method for evaluating the driving ability level of a vehicle according to the embodiment of the present application includes:
201. the system collects the sensing signals of the sensors on the target vehicle in the current environment;
202. the system acquires state information of the target vehicle according to the sensing signal;
the system needs to acquire the state information of the target vehicle in a real driving environment to obtain the running state of the target vehicle component, so that a micro sensor needs to be installed on each component needing to be monitored on the target vehicle, and the state information of the target vehicle is acquired by collecting sensing signals of the sensor and processing, calculating and transmitting results of the sensing signals in the process of driving the target vehicle.
203. The system acquires an action attitude image/video of a current driver under a real driving environment according to a camera in a target vehicle;
204. the system acquires an image/video of the current surrounding environment of the target vehicle in the real driving environment according to a camera at the windshield of the target vehicle;
205. the system acquires target driving information according to the action posture image/video of the current driver and the image/video of the current surrounding environment;
the system needs to acquire target driving information in a real driving environment to obtain the operation behavior of a vehicle driver for driving the vehicle and the action of the vehicle on the operation behavior of the driver. Therefore, the system needs to acquire an image/video of the corresponding content through a camera in the target vehicle. For example: one camera is installed and fixed on the left side and the right side of a steering wheel, the right upper side of a front right vehicle instrument panel of a driver A can be arranged, the other camera is installed in the middle of the right rear roof of the driver A and is approximately in the middle of a first row of seats in a target vehicle, the body key part of the driver A can be monitored at the optimal position by adjusting the orientation of the two cameras, the front camera can detect the upper half body, the head and the facial gestures of the driver A, and the face recognition, the expression recognition and the head gesture recognition can be realized. The rear camera can detect the positions of the upper half body and the two hands of the driver A on the steering wheel, monitors the behaviors of fatigue driving, call making during driving, smoke sucking during driving, left-right head swinging, head lowering and gear watching, observation window outside and the like of the driver A in real time, can also be arranged in front of a windshield or on an instrument desk of a target vehicle to acquire images/videos of the surrounding environment, and finally acquires the current driving environment information and the current driving behavior information of the driver from the acquired images/videos. The type of the acquired driving information is not limited here.
206. The system analyzes the state information of the target vehicle and the target driving information through a safety recognition model and generates current driving behavior data;
207. the system compares the current driving behavior data with standard driving behavior data, and generates judgment behavior data according to the comparison result on the steps and details of the operation behavior of the driver in the current driving behavior data;
208. the system stores the current driving behavior data and the corresponding judgment behavior data in a local database and uploads the current driving behavior data and the corresponding judgment behavior data to a cloud database;
209. the system generates driving capacity data by the aid of an evaluation model according to the required driving behavior data called from the local database or the cloud database and the corresponding judgment behavior data;
210. The system updates the safety identification model through the evaluation model;
the system updates the safety recognition model according to the evaluation model, the safety recognition model analyzes and feeds back real-time driving operation of a driver, the evaluation model analyzes the operation behavior of the driver and the running state of a target vehicle through a series of standards to obtain new data, and the new data is transmitted to the safety recognition model to be updated, so that the capability of the safety recognition model in recognizing the behavior and the state can be further enhanced.
211. The system generates corresponding driving ability evaluation according to the driving ability data;
step 211 in this embodiment is similar to step 107 in the previous embodiment, and is not repeated here.
212. The system authorizes the driving ability evaluation to a related platform, wherein the related platform is a driver personal platform and a driving training platform;
the system sends driving ability evaluation data to the authorized related platform, the purpose is to transmit the driving ability of the driver to the required platform, and the user corresponding to the evaluation data can also refer to the own data through the platform, so that the user can be further familiar with the driving process.
213. The system judges whether the area with the target vehicle is the area covered by the fifth generation mobile communication technology base station, if yes, step 214 is executed; if not, go to step 215;
in order to optimize the system between the communication link of the target vehicle and the basic environment system, a network connection mode with high priority level is required. Therefore, the system needs to first determine whether the area where the target vehicle exists is the area covered by the fifth generation mobile communication technology base station, if yes, execute step 214; if not, go to step 215.
214. The system establishes network communication by utilizing a fifth generation mobile communication technology data terminal at the vehicle-mounted end of the target vehicle;
when the system determines that the area where the target vehicle exists is the area covered by the fifth generation mobile communication technology base station, the system establishes network communication by using a fifth generation mobile communication technology data terminal on the vehicle-mounted end of the target vehicle.
215. The system builds a communication link by utilizing a self-building wireless local area network base station to realize communication.
When the system determines that the area where the target vehicle exists is not the area covered by the fifth generation mobile communication technology base station, the system carries out communication link construction by utilizing a self-built wireless local area network base station to realize communication.
In the embodiment, after the system generates the corresponding driving ability evaluation for the target driving vehicle and the driver, the driving ability evaluation can be subjected to multi-party authorization, so that the driving ability evaluation is inquired by the user and the official, and the convenience of data inquiry of the user and the official is improved; and secondly, judging whether the area where the target driving vehicle is located is covered by the fifth generation mobile communication technology, and selecting the optimal scheme to build a communication link according to the judgment result so as to realize network communication in the vehicle.
The above description has been made on the evaluation method of the vehicle drivability level in the embodiment of the present application, and the following description is made on an evaluation apparatus of the vehicle drivability level in the embodiment of the present application:
referring to fig. 3, an embodiment of an apparatus for evaluating a driving ability level of a vehicle according to an embodiment of the present application includes:
a first acquisition unit 301 configured to acquire target vehicle state information in a real driving environment;
a second obtaining unit 302, configured to obtain target driving information in a real driving environment, where the target driving information includes current driving environment information and current driver driving behavior information;
a first generating unit 303, configured to analyze the target vehicle state information and the target driving information through a safety recognition model, and generate current driving behavior data, where the current driving behavior data is operation data of the target vehicle in a current driving environment and behavior data of a current driver, and the safety recognition model is used to analyze behavior states of the target vehicle and the driver;
a determination unit 304, configured to compare the current driving behavior data with standard driving behavior data, and generate determination behavior data according to a comparison result for steps and details of an operation behavior of a driver in the current driving behavior data;
the storage unit 305 is configured to perform local database storage on the current driving behavior data and upload the current driving behavior data to a cloud database;
a second generating unit 306, configured to generate driving ability data from the required driving behavior data and the corresponding determination behavior data retrieved from the local database or the cloud database through an evaluation model, where the evaluation model is used to evaluate the driving behavior data and the corresponding determination behavior data retrieved from the database;
a third generating unit 307, configured to generate a corresponding driving ability evaluation according to the driving ability data.
In this embodiment, after the first obtaining unit 301 and the second obtaining unit 302 respectively obtain the target vehicle state information and the target driving information under the real driving environment, the first generating unit 303 analyzes the two pieces of obtained information to generate current driving behavior data, then the determining unit 304 compares the generated current driving behavior data with standard driving behavior data to obtain determined behavior data with steps and detail labels, then the storage unit 305 stores the current driving behavior data and the corresponding determined behavior data, the second generating unit 306 inputs the data retrieved from the database storage into the evaluation model for learning and training to generate driving ability data, and finally the third generating unit 307 generates driving ability evaluation according to the driving ability data, so that the generated driving ability evaluation has more aspects of evaluation results, and has better reliability.
Referring to fig. 4, another embodiment of the apparatus for evaluating a driving ability level of a vehicle according to the embodiment of the present application includes:
a first acquisition unit 401 configured to acquire target vehicle state information in a real driving environment;
a second obtaining unit 402, configured to obtain target driving information in a real driving environment, where the target driving information includes current driving environment information and current driver driving behavior information;
a first generating unit 403, configured to analyze the target vehicle state information and the target driving information through a safety recognition model, and generate current driving behavior data, where the current driving behavior data is operation data of the target vehicle in a current driving environment and behavior data of a current driver, and the safety recognition model is used to analyze behavior states of the target vehicle and the driver;
a determination unit 404, configured to compare the current driving behavior data with standard driving behavior data, and generate determination behavior data according to a comparison result for steps and details of an operation behavior of a driver in the current driving behavior data;
the storage unit 405 is used for storing the current driving behavior data in a local database and uploading the current driving behavior data to a cloud database;
a second generating unit 406, configured to generate driving ability data from the required driving behavior data and the corresponding determination behavior data retrieved from the local database or the cloud database through an evaluation model, where the evaluation model is used to evaluate the driving behavior data and the corresponding determination behavior data retrieved from the database;
an updating unit 407 for updating the secure identification model by the evaluation model;
a third generating unit 408, configured to generate a corresponding driving ability evaluation according to the driving ability data;
the authorization query unit 409 is used for authorizing the driving ability evaluation to relevant platforms, wherein the relevant platforms are a driver personal platform and a driving training platform, so that users and authorities query the driving ability evaluation;
a first judging unit 410, configured to judge whether an area where the target vehicle exists is an area covered by a fifth generation mobile communication technology base station;
a first executing unit 411, configured to establish network communication by using a fifth generation mobile communication technology data terminal on a vehicle-mounted side of the target vehicle when the first judging unit 410 determines that the area where the target vehicle exists is an area covered by a fifth generation mobile communication technology base station;
a second executing unit 412, configured to, when the first determining unit 410 determines that the area where the target vehicle does not exist is the area covered by the fifth-generation mobile communication technology base station, perform communication link establishment by using a self-established wireless local area network base station to implement communication.
In this embodiment, the second acquisition unit 402 includes a third acquisition module 4021, a fourth acquisition module 4022, and a fifth acquisition module 4023.
A third obtaining module 4021, configured to obtain an action posture image/video of a current driver in a real driving environment according to a camera in a target vehicle;
a fourth obtaining module 4022, configured to obtain an image/video of a current surrounding environment of the target vehicle in the real driving environment according to the camera at the windshield of the target vehicle;
a fifth obtaining module 4023, configured to obtain target driving information according to the current motion posture image/video of the driver and the current image/video of the surrounding environment.
In this embodiment, the first obtaining unit 401 includes an acquiring module 4011 and a sixth obtaining module 4012.
The acquisition module 4011 is configured to acquire a sensing signal of a sensor on a target vehicle in a current environment, where the sensing signal is a signal carrying target vehicle state data;
and a sixth obtaining module 4012, configured to obtain the state information of the target vehicle according to the sensing signal.
In the above embodiment, the functions of each unit and module correspond to the steps in the embodiment shown in fig. 2, and are not described herein again.
Referring to fig. 5, a detailed description is given below of an evaluation apparatus for a vehicle drivability level in an embodiment of the present application, where another embodiment of the evaluation apparatus for a vehicle drivability level in the embodiment of the present application includes:
a processor 501, a memory 502, an input/output unit 503, and a bus 504;
the processor 501 is connected to the memory 502, the input/output unit 503, and the bus 504;
the processor 501 specifically executes the following operations:
acquiring target vehicle state information in a real driving environment;
acquiring target driving information under a real driving environment, wherein the target driving information comprises current driving environment information and current driver driving behavior information;
analyzing the state information of the target vehicle and the target driving information through a safety recognition model, and generating current driving behavior data, wherein the current driving behavior data are operation data of the target vehicle in the current driving environment and behavior data of a current driver, and the safety recognition model is used for analyzing behavior states of the target vehicle and the driver;
comparing the current driving behavior data with standard driving behavior data, and generating judgment behavior data according to the steps and details of the operation behavior of the driver in the current driving behavior data;
storing the current driving behavior data and the corresponding judging behavior data in a local database and uploading the current driving behavior data and the corresponding judging behavior data to a cloud database;
generating driving capacity data by using the required driving behavior data extracted from the local database or the cloud database and the corresponding judgment behavior data through an evaluation model, wherein the evaluation model is used for evaluating the driving behavior data extracted from the database and the corresponding judgment behavior data;
and generating corresponding driving ability evaluation according to the driving ability data.
In this embodiment, the functions of the processor 501 correspond to the steps in the embodiments described in fig. 1 to fig. 4, and are not described herein again.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like.
Claims (10)
1. A method of evaluating a vehicle drivability level, characterized by comprising:
acquiring target vehicle state information in a real driving environment;
acquiring target driving information under a real driving environment, wherein the target driving information comprises current driving environment information and current driver driving behavior information;
analyzing the state information of the target vehicle and the target driving information through a safety recognition model, and generating current driving behavior data, wherein the current driving behavior data are operation data of the target vehicle in a current driving environment and behavior data of a current driver, and the safety recognition model is used for analyzing behavior states of the target vehicle and the driver;
comparing the current driving behavior data with standard driving behavior data, and generating judgment behavior data according to the comparison result on the steps and details of the operation behavior of the driver in the current driving behavior data;
storing the current driving behavior data and the corresponding judging behavior data in a local database and uploading the current driving behavior data and the corresponding judging behavior data to a cloud database;
generating driving capacity data by using the required driving behavior data and the corresponding judging behavior data which are extracted from the local database or the cloud database through an evaluation model, wherein the evaluation model is used for evaluating the driving behavior data and the corresponding judging behavior data which are extracted from the database;
and generating corresponding driving ability evaluation according to the driving ability data.
2. The evaluation method according to claim 1, wherein after the required driving behavior data retrieved from the local database or the cloud database and the corresponding determination behavior data are used to generate driving ability data through an evaluation model, the method further comprises:
updating the security identification model through the evaluation model.
3. The evaluation method according to claim 1, wherein the acquiring target driving information in a real driving environment includes:
acquiring an action attitude image/video of a current driver under a real driving environment according to a camera in a target vehicle;
acquiring an image/video of the current surrounding environment of the target vehicle in the real driving environment according to a camera at the windshield of the target vehicle;
and acquiring target driving information according to the action posture image/video of the current driver and the image/video of the current surrounding environment.
4. The evaluation method according to claim 1, wherein the acquiring target vehicle state information in a real driving environment includes:
acquiring a sensing signal of a sensor on a target vehicle in the current environment, wherein the sensing signal is a signal carrying state data of the target vehicle;
and acquiring the state information of the target vehicle according to the sensing signal.
5. The evaluation method according to any one of claims 1 to 4, characterized in that after the generating of the respective driving ability evaluation from the driving ability data, the method further comprises:
and authorizing the driving ability evaluation to a related platform, wherein the related platform is a driver personal platform and a driving training platform, so that the driving ability evaluation is inquired by a user and an official party.
6. The evaluation method of claim 5, wherein after generating the respective driving ability evaluation from the driving ability data, the method further comprises:
and judging whether the area with the target vehicle is the area covered by the fifth generation mobile communication technology base station, if so, establishing network communication by using a fifth generation mobile communication technology data terminal at the vehicle-mounted end of the target vehicle.
7. The evaluation method according to claim 6, wherein after determining whether the area where the target vehicle exists is an area covered by a fifth generation mobile communication technology base station, the method further comprises:
if not, the communication link is established by utilizing a self-established wireless local area network base station mode to realize communication.
8. An evaluation device of a vehicle drivability level, characterized by comprising:
a first acquisition unit configured to acquire target vehicle state information in a real driving environment;
the second acquisition unit is used for acquiring target driving information under a real driving environment, wherein the target driving information comprises current driving environment information and current driver driving behavior information;
the first generation unit is used for analyzing the state information of the target vehicle and the target driving information through a safety recognition model and generating current driving behavior data, wherein the current driving behavior data are operation data of the target vehicle in a current driving environment and behavior data of a current driver, and the safety recognition model is used for analyzing behavior states of the target vehicle and the driver;
the judging unit is used for comparing the current driving behavior data with standard driving behavior data and generating judging behavior data according to the comparison result on the steps and details of the operation behavior of the driver in the current driving behavior data;
the storage unit is used for storing the current driving behavior data and the corresponding judgment behavior data in a local database and uploading the current driving behavior data and the corresponding judgment behavior data to a cloud database;
the second generation unit is used for generating driving capacity data by the driving behavior data required and the corresponding judgment behavior data which are extracted from the local database or the cloud database through an evaluation model, and the evaluation model is used for evaluating the driving behavior data extracted from the database and the corresponding judgment behavior data;
and the third generating unit is used for generating corresponding driving ability evaluation according to the driving ability data.
9. The evaluation device of claim 8, further comprising:
and the updating unit is used for updating the safety identification model through the evaluation model.
10. The evaluation apparatus according to claim 8, wherein the second acquisition unit includes:
the third acquisition module is used for acquiring an action posture image/video of the current driver in the real driving environment according to the camera in the target vehicle;
the fourth acquisition module is used for acquiring the image/video of the current surrounding environment of the target vehicle in the real driving environment according to the camera at the windshield of the target vehicle;
and the fifth acquisition module is used for acquiring target driving information according to the action posture image/video of the current driver and the image/video of the current surrounding environment.
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