CN115759316A

CN115759316A - User driving behavior monitoring method, device, medium and equipment

Info

Publication number: CN115759316A
Application number: CN202111036090.6A
Authority: CN
Inventors: 张玉刚
Original assignee: Shanghai Pateo Network Technology Service Co Ltd
Current assignee: Shanghai Pateo Network Technology Service Co Ltd
Priority date: 2021-09-03
Filing date: 2021-09-03
Publication date: 2023-03-07

Abstract

The embodiment of the application provides a method, a device, a medium and equipment for monitoring the driving behavior of a user, wherein the method comprises the steps of acquiring the historical driving route of the user; under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period; further, whether the driving behavior of the user meets a preset condition is judged based on the historical driving route and the monitoring driving route; and executing early warning measures under the condition that the driving behaviors meet the preset conditions. Therefore, the driving behavior of the user can be monitored through the driving route of the user; therefore, under the condition that the behavior of the user meets the preset condition, the vehicle driven by the user is determined to have the risk of vehicle loss, the user can be pre-warned through the pre-warning measure, the risk of vehicle loss is favorably reduced, and the safe ecology of the shared vehicle is favorably maintained.

Description

User driving behavior monitoring method, device, medium and equipment

Technical Field

The application relates to the technical field of electronic equipment, in particular to a method, a device, a medium and equipment for monitoring driving behaviors of a user.

Background

With the popularization and development of sharing concepts, shared vehicles such as shared automobiles, shared bicycles, shared electric vehicles and the like or networked vehicles emerge in the market, currently, most of the shared vehicles realize positioning through a GPS positioning technology, and realize protection and theft prevention of the vehicles according to the positioning, however, the positioning precision of the GPS technology is greatly influenced by environmental factors, and for illegal users who seek to steal the vehicles, due to the fact that the shared vehicles are unfamiliar with various operations or positioning modes and the like at first, the shared vehicles may be rented for many times, so that the shared vehicles can be stolen and moved in unmanned or GPS-free areas, and thus, the safety ecology of the shared vehicles is not facilitated to maintain.

Disclosure of Invention

One objective of the present application is to provide a method, an apparatus, a medium, and a device for monitoring driving behaviors of a user, which are beneficial to maintaining the safe ecology of a shared vehicle.

Another objective of the present application is to provide a method for monitoring user driving behavior, which is advantageous in that a user marking a historical driving route passing through a preset area is determined, so as to distinguish an illegal user suspected of vehicle theft, so as to achieve the purpose of monitoring user behavior.

Another object of the present application is to provide a method for monitoring driving behaviors of a user, which has the advantages of predicting a driving route of the user to determine the driving behaviors of the user and further determine a risk of vehicle theft, so as to take early warning measures in time, thereby being beneficial to reducing a risk of vehicle loss.

Another objective of the present application is to provide a method for monitoring a driving behavior of a user, which has an advantage that an evaluation mechanism is set according to the number of times that the user passes through a preset area and target characteristic information in an expected driving route obtained through prediction, so as to further judge the driving behavior of the user, which is beneficial to improving the accuracy of judging the illegal user, and thus, when it is subsequently determined that the user is suspected of vehicle theft, early warning measures can be taken in time, which is beneficial to reducing the risk of vehicle loss.

Another objective of the present application is to provide a method for monitoring driving behaviors of a user, which is advantageous in that different early warning information is set according to different driving environments where the user is located, so that different preset operations are taken under the condition that the safety of the user is guaranteed, and different early warning management and control effects are achieved.

Another objective of the present application is to provide a method for monitoring a driving behavior of a user, which is advantageous in that a suspected stolen vehicle is marked, and the number of times of marking an illegal vehicle-stealing behavior of the user using the vehicle and the number of times of marking the suspected stolen vehicle of the vehicle are taken into consideration, so as to pre-judge a theft risk of the vehicle, thereby improving the accuracy of judging a theft condition of the vehicle and reducing a vehicle-losing risk.

Another objective of the present application is to provide a method for monitoring a driving behavior of a user, which has an advantage that an expected driving route of the user is analyzed and predicted in real time according to a historical driving route of the user in the current driving process and a monitored driving route obtained through real-time monitoring, so that a driving route which the user may select can be obtained in real time, and the accuracy of subsequent judgment on a car loss risk is improved.

In order to achieve the above object, in a first aspect, an embodiment of the present application provides a method for monitoring a driving behavior of a user, where the method includes:

acquiring a historical driving route of the user;

under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period;

judging whether the driving behavior of the user meets a preset condition or not based on the historical driving route and the monitoring driving route; and

and executing early warning measures under the condition that the driving behaviors meet the preset conditions.

In a second aspect, an embodiment of the present application provides a user driving behavior monitoring apparatus, where the apparatus includes: a communication unit, a processing unit and an execution unit, wherein,

the communication unit configured to receive a historical travel route of the user; receiving a monitoring driving route of the user within a preset monitoring time period under the condition that the historical driving route passes through a preset area;

the processing unit is communicatively connected with the communication unit and is configured to:

judging whether the historical driving route passes through a preset area or not based on the historical driving route;

judging whether the driving behavior of the user meets a preset condition or not based on the historical driving route and the monitoring driving route; generating an early warning instruction under the condition that the driving behavior meets the preset condition;

the execution unit is communicatively connected with the processing unit and is configured to execute the early warning measure indicated by the early warning instruction.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in any of the methods of the first aspect of the embodiment of the present application.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform some or all of the steps described in any one of the methods of the second aspect of the embodiments of the present application.

It can be seen that in the embodiments of the present application, a method, an apparatus, a medium, and a device for monitoring a driving behavior of a user are provided, where the method includes: historical driving routes of the user can be obtained; under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period; further, whether the driving behavior of the user meets a preset condition is judged based on the historical driving route and the monitoring driving route; and executing early warning measures under the condition that the driving behavior is determined to meet the preset conditions. Therefore, the driving behavior of the user can be monitored through the driving route of the user; therefore, when the behavior of the user meets the preset conditions, the fact that the vehicle driven by the user possibly has the risk of losing the vehicle is determined, the user can be pre-warned through the pre-warning measures, the risk of losing the vehicle is favorably reduced, and the safety ecology of the shared vehicle is favorably maintained.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1A is a schematic structural diagram of a user driving behavior monitoring system according to an embodiment of the present application;

fig. 1B is a schematic flowchart of another method for monitoring driving behavior of a user according to an embodiment of the present application;

fig. 1C is a scene schematic diagram of a method for monitoring a driving behavior of a user according to an embodiment of the present application;

fig. 1D is a scene schematic diagram of another method for monitoring a driving behavior of a user according to an embodiment of the present application;

fig. 2A is a schematic flowchart of another method for monitoring driving behavior of a user according to an embodiment of the present application;

fig. 2B is a schematic flowchart of another method for monitoring driving behavior of a user according to an embodiment of the present application;

fig. 3A is a schematic flowchart of another method for monitoring driving behavior of a user according to an embodiment of the present application;

fig. 3B is a schematic flowchart of another method for monitoring driving behavior of a user according to an embodiment of the present application;

fig. 4 is a schematic diagram of a user driving behavior monitoring system according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements but may alternatively include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

In order to better understand the method, the apparatus, the medium, and the device for monitoring the driving behavior of the user, which are provided in the embodiments of the present application, a system architecture of an information processing method applicable to the embodiments of the present application is described first below.

Referring to fig. 1A, fig. 1A is a schematic diagram of a framework of a user driving behavior monitoring system according to an embodiment of the present application. As shown in fig. 1A, the system architecture may include a vehicle-mounted device, a user terminal, and an electronic device, where the vehicle-mounted device may establish a communication connection with the electronic device and may report related information to the electronic device, and in this embodiment, the related information may include at least one of the following: the system comprises a historical driving route, a monitoring driving route, first mark information, second mark information and the like, wherein the historical driving route can be obtained after a user drives for a period of time or a distance, and the monitoring driving route can be obtained by monitoring the driving route of the user in real time; the second marking information can be obtained by monitoring the behavior of the vehicle and can be reported by the vehicle-mounted equipment. In some examples, for example, when the user navigates through the user terminal, the electronic device may also communicate with the user terminal, and may report related information to the electronic device, such as first tag information and the like, where the first tag information is different from the second tag information, and the first tag information may be obtained by monitoring the driving behavior of the user. In some examples, the first tag information may also be reported by the vehicle-mounted device, and if the user navigates through the vehicle-mounted device, the first tag information may be reported to the electronic device by the vehicle-mounted device; if the electronic equipment cannot communicate with the user terminal and the user terminal carries out navigation, the first mark information can be acquired by the vehicle-mounted equipment and reported to the electronic equipment.

The electronic equipment can acquire the historical driving route of the user reported by the vehicle-mounted equipment; under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period; further, based on the historical driving route and the monitoring driving route, judging whether the driving behavior of the user meets a preset condition; and executing early warning measures under the condition that the driving behavior is determined to meet the preset conditions. Therefore, the driving behavior of the user can be monitored through the driving route of the user; therefore, under the condition that the behavior of the user meets the preset condition, the vehicle driven by the user is determined to have the risk of vehicle loss, the user can be pre-warned through the pre-warning measure, the risk of vehicle loss is favorably reduced, and the safe ecology of the shared vehicle is favorably maintained.

In the embodiment of the present application, the vehicle-mounted device may be a device with vehicle-mounted monitoring management function, and may include a portable electronic device with other functions, such as a personal digital assistant and/or a music player function, and exemplary embodiments of the portable electronic device include, but are not limited to, a portable electronic device with an IOS system, an Android system, a Microsoft system, or other operating systems. The portable electronic device may also be other portable electronic devices such as a Laptop computer (Laptop) or the like.

The user terminal may be a portable electronic device, such as a cell phone, a tablet computer, a wearable electronic device with wireless communication capabilities (e.g., a smart watch), etc., that includes other functionality, such as personal digital assistant and/or music player functionality. Exemplary embodiments of the portable electronic device include, but are not limited to, portable electronic devices that carry an IOS system, an Android system, a Microsoft system, or other operating system. The portable electronic device may also be other portable electronic devices such as a Laptop computer (Laptop) or the like. The user terminal can establish communication connection with the vehicle-mounted equipment.

The electronic device may be a portable electronic device, such as a cell phone, a tablet, a wearable electronic device with wireless communication capabilities (e.g., a smart watch), etc., that includes other functionality, such as personal digital assistant and/or music player functionality. Exemplary embodiments of the portable electronic device include, but are not limited to, portable electronic devices that carry an IOS system, an Android system, a Microsoft system, or other operating system. The portable electronic device may also be other portable electronic devices such as a Laptop computer (Laptop) or the like. It should also be understood that, in other embodiments, the electronic device may further include a cloud server, a background server, a user driving behavior monitoring server, and the like, which are not limited herein.

Referring to fig. 1B, fig. 1B is a schematic flowchart of a method for monitoring a driving behavior of a user according to an embodiment of the present application, where the method includes the following steps:

and S101, acquiring the historical driving route of the target user.

The user may refer to a user who rents a shared vehicle such as a shared automobile, a shared bicycle, a shared electric vehicle, or a networked vehicle.

The electronic device may acquire a driving route of the user within a certain time or a certain distance as a historical driving route, where the historical driving route may refer to a driving route from the vehicle start to the current time of the user in the current driving or rental scene. The period of time may refer to 5min, 10min, 15min, 0.5h, 1h, etc., and is not limited herein. The certain distance may refer to 2km, 5km, 7km, 15km, and the like, which is not limited herein.

S102, under the condition that the historical driving route passes through a preset area, the monitoring driving route of the user in a preset monitoring time period is obtained.

The preset area can be set by a background manager or default by a system, or can be generated based on the occurrence position of the historical abnormal event of the vehicle, and is not limited herein; the background manager may refer to a manager of a company that provides shared vehicles such as shared cars, shared bikes, shared electric cars, or networked vehicles.

The preset area may refer to an area where no monitoring device or Global Positioning System (GPS) signal exists or where network signals are weak, or an area where coverage of GPS signals is small, and the like, which is not limited herein; the preset area may be regarded as a "dangerous area" or a "gray area" or the like, relative to an area where monitoring equipment, a Global Positioning System (GPS) signal or a network signal is strong, or an area where coverage of the GPS signal is large.

The preset monitoring time period can be set by a user or defaulted by a system, and is not limited herein; the preset monitoring time period can refer to that after the user drives for a certain distance, or after the user drives for a certain time, and the like, background behavior monitoring can be started, and a monitoring driving route of the user under the background behavior monitoring can be obtained; the monitored travel route is different from the historical travel route.

For example, the historical driving route of the user in the current driving process may be obtained after the user drives the vehicle for 10 minutes, for example, the historical driving route may be the historical driving route corresponding to the user in the previous 10 minutes driving process; and analyzing the historical driving route, if the driving route of the user in the previous 10 minutes comprises a GPS (global positioning system) no-signal or network signal weak area, or an area with low GPS signal coverage rate, or an area without monitoring equipment, starting background behavior monitoring, continuously monitoring the driving behavior of the user in the future 30 minutes, acquiring the driving route of the user in real time, and acquiring the monitored driving route.

S103, judging whether the driving behaviors of the user meet preset conditions or not based on the historical driving routes and the monitoring driving routes.

And S104, executing early warning measures under the condition that the driving behaviors meet the preset conditions.

Wherein the driving behavior may include at least one of: whether the preset area is passed, whether loitering is in the vicinity of the preset area, whether the preset area is passed multiple times, and the like, and are not limited herein.

The preset condition can be set by a background manager or default of a system, and is not limited herein; when the driving behavior is determined to meet the preset condition, it can be determined that the shared vehicles such as the shared automobile, the shared bicycle and the shared electric vehicle driven by the user or the networked vehicles may have a risk of vehicle loss, for example, the user may steal the vehicle by an illegal means.

When the driving behavior meets the preset conditions, the electronic equipment can execute early warning measures to ensure the safety of the vehicle driven by the user.

The early warning measure can be set by a background manager or defaulted by a system, and is not limited herein; for example, the vehicle may be warned by voice, or a warning process may be performed, or the vehicle may be controlled to decelerate, etc., which is not limited herein.

It can be seen that, in the embodiment of the present application, a method for monitoring a driving behavior of a user is provided, where an electronic device may obtain a historical driving route of the user; under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period; further, whether the driving behavior of the user meets a preset condition is judged based on the historical driving route and the monitoring driving route; and executing early warning measures under the condition that the driving behavior is determined to meet the preset conditions. Therefore, the driving behavior of the user can be monitored through the driving route of the user; therefore, under the condition that the behavior of the user meets the preset condition, the vehicle driven by the user is determined to have the risk of vehicle loss, the user can be pre-warned through the pre-warning measure, the risk of vehicle loss is favorably reduced, and the safe ecology of the shared vehicle is favorably maintained.

In one possible example, after determining that the historical travel route passes through a preset area, the method further includes the steps of: generating first marking information, wherein the first marking information indicates that the driving behavior of the user is suspected illegal behavior.

In specific implementation, the electronic device may mark the driving behavior of the user as a suspected illegal behavior in the background, that is, the user may have a vehicle stealing behavior, and mark the driving behavior once. Specifically, the flag may be marked once when the historical behavior route currently traveled by the user exists or includes a preset area.

In addition, in the embodiment of the application, the judgment and marking operation can be performed once when the user rents the network appointment vehicle every time, so that multiple suspected illegal behaviors can be accumulated to obtain the first marking times. And if the electronic equipment extracts the first marking times again, determining the first marking times accumulated when the electronic equipment is suspected to be illegal according to all the historical driving behaviors of the user.

As can be seen, in this example, the marking operation may be preset to mark the driving behavior of the user. Some users may not know the early warning measure of the vehicle, and there may be a point-stepping condition, so as to prevent the situation that the user may implement a vehicle-stealing behavior after stepping on the point for many times.

In one possible example, the determining whether the driving behavior of the user satisfies a preset condition based on the historical driving route and the monitoring driving route includes: predicting at least one expected travel route for the user based on the historical travel routes and the monitored travel routes; determining a plurality of pieces of characteristic information corresponding to each expected driving route according to each expected driving route to obtain a plurality of characteristic information sets, wherein each expected driving route corresponds to one characteristic information set; selecting at least one target characteristic information associated with the preset area from each characteristic information set to obtain a target characteristic information set corresponding to each expected driving route, wherein each target characteristic information set comprises the at least one target characteristic information; acquiring the marking times of the first marking information; and judging whether the driving behavior of the user meets a preset condition or not based on the marking times and the target characteristic information set.

If the user uses a network car or the like on a certain platform, when the user has a suspected illegal behavior, the user may mark the driving behavior for a plurality of times during the driving process to obtain the marking times of the first marking information.

The characteristic information may refer to some characteristic information of the expected driving route, for example, time taken to pass through a certain road segment, which road segments are passed through, GPS signal coverage rate of the road segment, road conditions of the road segment, and the like, which are not limited herein.

The target feature information may refer to some related information about a preset area in the feature information, such as: the duration of the passing of the preset region, the region range of the preset region, the number of occurrences of the preset region, and the like, are not limited herein.

The number of the marks may be 3, 5, 10, etc., and is not limited herein.

The expected driving route can be obtained by performing path planning according to the historical driving route and the monitoring driving route of the user, and the specific path planning mode is not limited herein.

In specific implementation, a target characteristic information set corresponding to each expected driving route can be determined according to at least one expected driving route obtained by path planning, and then the driving behavior of the user can be judged according to the target characteristic information in the target characteristic information set and the marking times so as to determine whether the preset condition is met.

As can be seen, in this example, the electronic device may judge the parameters according to the two types of parameters, that is, the marking times and the target feature information set corresponding to the first marking information; the driving behavior of the user can be judged according to the two judging parameters. Therefore, the method is beneficial to solving the problem of behavior judgment of the user, and the driving behavior is associated with the characteristic information of the driving route of the user, so that the judgment accuracy is improved.

In one possible example, the predicting at least one expected travel route of the user based on the historical travel routes and the monitored travel routes includes: predicting a driving parameter of a vehicle corresponding to the user based on the monitoring driving route; determining historical driving parameters of the user based on the historical driving route; predicting a first driving lane of the vehicle based on the driving parameters and the historical driving parameters to obtain a first expected driving road section corresponding to the vehicle in a first time period; predicting a second driving lane of the vehicle according to a first expected driving road section corresponding to the first time period to obtain a second expected driving road section corresponding to a second time period of the vehicle, wherein the second time period is later than the first time period; by analogy, obtaining an nth expected driving road section corresponding to the vehicle in an nth time period, wherein N is a positive integer greater than 1; and combining the N expected running road sections corresponding to the N time periods to obtain at least one expected running route.

Wherein the historical driving parameters and/or driving parameters may include at least one of: speed, direction, yaw rate, steering angle, etc., without limitation.

The historical driving parameters can reflect the driving habits of the user, and can include destinations (such as common destinations) in addition to the speed, direction, yaw rate and steering angle.

In a specific implementation, when the first expected driving route is predicted, whether the historical driving route is overlapped with the monitoring driving route or not can be determined, if the overlapped part exists, the destination included in the historical driving parameters can be further used as the destination of the current driving route, so that at least one driving route from the current position to the destination can be determined, and the at least one driving route can also be used as the expected driving route.

Furthermore, the second driving lane of the vehicle may be predicted according to the first expected driving road segment, and the specific prediction mode is consistent with the historical driving parameter based on the driving parameter and the historical driving route, and the prediction mode of the first driving lane of the vehicle is not repeated herein. And so on, obtaining an nth expected driving road section corresponding to the nth time period of the vehicle, wherein N is a positive integer greater than 1, and finally combining the N expected driving road sections to obtain at least one expected driving route.

For example, as shown in fig. 1C, the present invention is a scene diagram of a method for monitoring a driving behavior of a user, as shown in fig. 1C, when the user approaches an intersection, the user may determine a possible direction according to a driving parameter corresponding to the user, and obtain a plurality of driving road segments. For example, as shown in fig. 1C, if the vehicle a (solid line vehicle) is the driving direction of the user originally on the road, it may be determined that the current driving direction of the user is straight; if the yaw rate in the driving parameters is determined to be less than or equal to a threshold value, determining that the driving direction of the user is still straight; if it is determined that the yaw rate in the driving parameter is greater than the threshold value, it may be determined that the user may change the driving direction of the straight driving, and then a new driving direction of the user may be determined according to the steering angle in the driving parameter, and if the steering angle of the user is a right turn, it may be obtained that the user may turn right to switch the driving lane (may be a lane to the right of the current lane), or turn right, and so on; as shown by the dashed line vehicle in fig. 1C, which is the direction in which the vehicle a may travel, a variety of travel paths are thus available.

It can be seen that, in the present example, the driving route of the user can be predicted according to the driving parameters of the user, and preparation is made for monitoring or determining the driving behavior of the user at a later stage. In addition, each expected driving route is associated with the last moment, so that the real-time expected driving route can be realized, and the prediction accuracy of the driving route is improved.

In one possible example, the determining whether the driving behavior of the user meets a preset condition based on the marking times and the target feature information set includes: when the marking times are larger than or equal to a first preset threshold value, determining the type and the characteristic value corresponding to each target characteristic information in the target characteristic information set; determining at least one first evaluation value corresponding to each target feature information set according to a mapping relation between a preset feature value of target feature information and the first evaluation value, wherein each first evaluation value corresponds to one target feature information in the target feature information sets; determining a second evaluation value corresponding to the type of each target characteristic information in each target characteristic information set according to a preset mapping relation between the type of the target characteristic information and the second evaluation value, and obtaining the second evaluation value corresponding to each target characteristic information set; acquiring a first weight corresponding to the characteristic value and a second weight corresponding to the type, wherein the sum of the first weight and the second weight is 1; obtaining at least one third evaluation value corresponding to at least one expected driving route based on the at least one first evaluation value, the at least one second evaluation value, the first weight and the second weight; calculating the sum of the at least one third evaluation value to obtain a target evaluation value; and determining that the driving behavior satisfies the preset condition when the target evaluation value is greater than or equal to a preset evaluation value.

The first preset threshold value can be set by a background manager or defaulted by a system, and is not limited herein; the first preset threshold may be used to determine whether the historical driving behavior of the user is suspected illegal. The first preset threshold may be dynamically set according to a historical driving route of each user, and in a specific implementation, may be set according to a historical driving route of the user. For example, an initial value of the first preset threshold may be set, and the number of the preset areas normally existing in the historical driving route may be set as the initial value (for example, 2 tunnels with weak GPS signals are included in the route from the point a to the point B, then 2 may be used as the initial value), in particular, the historical driving route of the user may be divided into a plurality of historical driving sections, the number of the preset areas normally existing in the plurality of historical driving sections may be counted, and the number of each historical driving route is accumulated to obtain the initial value; in this way, the initial value may be set according to the corresponding historical driving route during the real-time driving of each user, and the first preset threshold may be set to a value greater than the initial value, for example, if the initial value is set to 3 times, the first preset threshold may be set to 5 times, 6 times, and so on, which is not limited herein. Therefore, the initial value can be dynamically set according to the condition that whether the preset area normally exists on the road section currently driven by the user, so that the first preset threshold value can be dynamically obtained, the preset area under the normal condition is eliminated, and the occurrence of the condition of misjudgment of suspected illegal behaviors is favorably reduced.

The type corresponding to the target feature information may include at least one of the following: duration, regional GPS signal parameters, number of occurrences, number of dwells, and the like, without limitation; the feature value may refer to specific data corresponding to each type, such as a specific duration corresponding to a duration, an area corresponding to a region range, a specific number of occurrences, and the like, which are not limited herein. The feature values may correspond one-to-one to each type.

The electronic device may preset a mapping relationship between a feature value of preset target feature information and the first evaluation value, and a mapping relationship between a type of the preset target feature information and the second evaluation value.

In a specific implementation, the first evaluation value may be set according to a feature value of the target feature information, and the first evaluation value may be specifically set according to the feature value, and generally, when a value corresponding to the feature value is larger, the first evaluation value may be set to be larger, and the larger the first evaluation value is, the larger the judgment influence of the first evaluation value on the driving behavior of the user is; however, the individual characteristic value may be specifically set, for example, when the characteristic value is a regional GPS signal parameter, the smaller the corresponding numerical value is, the larger the corresponding first evaluation value is; specifically, the range of the feature value of different target feature information may be set, and for example, the number of times of stay is set to 2 in the range of [0,1], the first evaluation value is set to 3 in the range of [2,5], and the first evaluation value is set to 5 in the range of [6,15 ]. The specific setting mode may be set based on the influence of the characteristic value on the judgment that the driving behavior is a suspected illegal behavior.

Further, the second evaluation value corresponding to the type of the target feature information may be set in accordance with the influence of the type on the determination that the driving behavior is a pseudo-illegal behavior, and the larger the influence, the larger the corresponding second evaluation value.

Still further, a weight may be set for the feature value and the type, and the larger the weight is, the greater the influence of the determination that the driving behavior is suspected to be illegal behavior, or the larger the specific gravity is, the sum of the weight corresponding to the feature value and the type may be 1, for example, the first weight corresponding to the feature value may be set to 0.6, and the first weight corresponding to the type may be set to 0.4. Determining a second evaluation value corresponding to the type of each target characteristic information in each target characteristic information set, and further obtaining at least one second evaluation value corresponding to at least one target characteristic information set; determining a first evaluation value corresponding to the characteristic value of each target characteristic information in each target characteristic information set to obtain at least one first evaluation value corresponding to each target characteristic information set; further, for each target feature information set, there may be corresponding: at least one first evaluation value, at least one second evaluation value, the first weight and the second weight are subjected to weighted summation to obtain a third evaluation value corresponding to each target feature information set; and finally, summing at least one third evaluation value to obtain a target evaluation value, comparing the target evaluation value with a preset evaluation value (which may be set by a background manager or default of a system, but is not limited herein), and when the target evaluation value is greater than or equal to the preset evaluation value, determining that the driving behavior of the user is suspected illegal behavior, and the user may have a vehicle stealing risk, and determining that the driving behavior meets a preset condition.

As can be seen, in this example, the electronic device may set an evaluation mechanism according to the type and the feature value corresponding to the target feature value, and in this embodiment, the evaluation parameter in the evaluation mechanism is not limited; furthermore, the formal behavior of the user can be judged based on the evaluation mechanism, so that the driving behavior of the user can be judged more accurately.

In one possible example, the performing the pre-warning measure includes: determining a driving environment corresponding to the user; and generating early warning information under the condition that the driving environment meets a preset environment, wherein the early warning information comprises information for prompting that the user is about to execute a preset operation.

The driving environment may refer to a scene during the current driving process of the user, and may be, for example, a high-speed driving environment, a low-speed driving environment, a rain and snow driving environment, and the like, which is not limited herein. The preset environment and/or the early warning operation can be set by a background manager or default by a system, the preset environment is not limited, the preset environment can be set to be a high-speed driving environment, if a user is in the high-speed driving environment, forced speed reduction or parking management can not be performed on the user through early warning measures, and therefore different early warning information can be set according to different preset environments to require the user to take different preset operations. The early warning information may correspond to an early warning operation.

In specific implementation, for example, if it is determined that the driving environment of the user is a high-speed driving environment, the early warning management and control may be set according to whether a service area exists in the environment where the user is located, that is, the user is required to execute a preset operation, and in the case of the service area, the user is reminded of how many minutes (which may be set as the driving time from the current position to the service area when the vehicle is driven under a normal condition) the user is to perform driving intervention in order to remind the user to stop the vehicle at the service area.

For another example, the preset operation may be specifically set according to a scene, and for another example, the user may be forced to stop for some minutes and forced to perform driving intervention to gradually reduce the driving speed of the vehicle; meanwhile, the vehicle can be immediately reported to a background manager, the background manager can directly acquire the environment image of the vehicle, and if the vehicle is in an illegal area, the vehicle can acquire personal information of the illegal user to perform alarm processing and the like.

For example, as shown in fig. 1D, the method is a scene diagram of a user driving behavior monitoring method, and if it is determined that the driving environment of the user is a high-speed driving environment, the method may set an early warning management and control according to whether a service area exists in the environment where the user is located, that is, the user is required to perform a preset operation, and when the service area does not exist, the method may remind the user how many minutes (which may be set as a driving time from a current position to the service area when the vehicle is driven under a normal condition) for driving intervention to remind the user to stop the vehicle a in an emergency lane.

Therefore, in this example, the electronic device may set different early warning information according to different preset environments to adopt different preset operations, so as to achieve different early warning management and control effects; and can reach early warning management and control under the condition of guaranteeing user's driving safety, it is more humanized, be favorable to improving user experience.

In one possible example, after determining that the historical travel route includes a preset region, the method further comprises: generating second marker information indicating that the vehicle is a suspected target vehicle; when the marking frequency of the second marking information is larger than or equal to a second preset threshold value, acquiring the identity authentication information of the user; acquiring the marking times of the first marking information corresponding to the user based on the identity authentication information; and when the marking times of the first marking information are larger than or equal to a third preset threshold value, executing the early warning measure.

The second marking information is different from the first marking information, the first marking information is marked according to the behaviors of the users, and the second marking information can be marked according to the vehicles, so that the situation that some users use the same vehicle by stepping on the point for multiple times by one person or multiple persons at different time points and want to steal the same vehicle is prevented, for example, a polling mode is adopted.

The second preset threshold and/or the third preset threshold may be set by a background manager or default, and is not limited herein. The third preset threshold may be the same as or different from the first preset threshold.

In specific implementation, when the marking frequency of the second marking information is greater than or equal to a second preset threshold value, the vehicle can be preliminarily judged to be possibly aimed and possibly a target vehicle which is expected to be stolen by an illegal user; further, a first marking number of times of a user driving the vehicle may be acquired, and further, in a case where the first marking number of times is greater than or equal to a third preset threshold, it is determined that the vehicle may be a target vehicle that the user wants to steal, and further, an early warning measure may be taken or executed.

Further, the electronic device may clear the second flag information after a certain period of time, because it is considered that it is impossible for an illegal user to stare at only one vehicle a year.

As can be seen, in this example, the electronic device may determine the risk of stealing the vehicle through the first number of times of marking obtained by monitoring the user behavior and the second number of times of marking obtained by monitoring the vehicle driving behavior, and prevent some users from using the same vehicle by stepping on the point for multiple times by one or more people at different time points in a polling manner, and from stealing the same vehicle.

Referring to fig. 2A, please refer to fig. 2A in accordance with the embodiment shown in fig. 1B, where fig. 2A is a schematic flow chart of another method for monitoring a driving behavior of a user according to an embodiment of the present application; as shown in the figure, the user driving behavior monitoring method includes:

s201, the electronic equipment acquires the historical driving route of the user.

S202, the electronic equipment acquires the monitoring driving route of the user in a preset monitoring time period under the condition that the historical driving route passes through a preset area.

S203, the electronic equipment generates first mark information, and the first mark information indicates that the driving behavior of the user is suspected illegal behavior.

S204, the electronic equipment predicts at least one expected driving route of the user based on the historical driving route and the monitoring driving route.

S205, the electronic device determines a plurality of feature information corresponding to each expected driving route according to each expected driving route to obtain a plurality of feature information sets, and each expected driving route corresponds to one feature information set.

S206, the electronic device selects at least one target feature information associated with the preset area from each feature information set to obtain a target feature information set corresponding to each expected driving route, where each target feature information set includes the at least one target feature information.

S207, the electronic equipment acquires the marking times of the first marking information.

S208, the electronic equipment judges whether the driving behavior of the user meets a preset condition or not based on the marking times and the target characteristic information set.

S209, the electronic equipment executes early warning measures under the condition that the driving behaviors meet the preset conditions.

The specific implementation manner of steps S201 to S209 may refer to the description related to the user driving behavior monitoring method in fig. 1B, and is not described herein again.

Referring to fig. 2B, fig. 2B is a schematic flowchart illustrating another method for monitoring a driving behavior of a user according to an embodiment of the present disclosure.

It can be seen that, in the embodiment of the present application, a method for driving behaviors of a user is provided, where an electronic device obtains a historical driving route of the user; under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period; generating first mark information, wherein the first mark information indicates that the driving behavior of the user is suspected illegal behavior; predicting at least one expected driving route of the user based on the historical driving route and the monitoring driving route; determining a plurality of characteristic information corresponding to each expected driving route according to each expected driving route to obtain a plurality of characteristic information sets, wherein each expected driving route corresponds to one characteristic information set; selecting at least one target characteristic information associated with the preset area from each characteristic information set to obtain a target characteristic information set corresponding to each expected driving route, wherein each target characteristic information set comprises the at least one target characteristic information; acquiring the marking times of the first marking information; judging whether the driving behavior of the user meets a preset condition or not based on the marking times and the target characteristic information set; and finally, executing early warning measures under the condition that the driving behavior meets the preset conditions. Therefore, the electronic equipment can judge parameters according to the two types of judgment parameters, namely the marking times corresponding to the first marking information and the target characteristic information set; the driving behavior of the user can be judged according to the two judging parameters. Therefore, the method is beneficial to solving the problem of behavior judgment of the user, and the driving behavior is associated with the characteristic information of the driving route of the user, so that the judgment accuracy is improved.

In accordance with the embodiment shown in fig. 1B, please refer to fig. 3A, fig. 3A is a schematic flowchart of another method for monitoring driving behaviors of a user according to an embodiment of the present application; as shown in the figure, the user driving behavior monitoring method includes:

s301, the electronic equipment acquires the historical driving route of the user.

S302, the electronic equipment acquires the monitoring driving route of the user in a preset monitoring time period under the condition that the historical driving route passes through a preset area.

S303, the electronic device generates first tag information, where the first tag information indicates that the driving behavior of the user is a suspected illegal behavior.

S304, the electronic equipment generates second mark information, and the second mark information indicates that the vehicle is a suspected target vehicle;

s305, when the marking frequency of the second marking information is greater than or equal to a second preset threshold value, the electronic equipment acquires the identity authentication information of the user;

s306, the electronic equipment acquires the marking times of the first marking information corresponding to the user based on the identity authentication information;

s307, when the marking times of the first marking information are larger than or equal to a third preset threshold value, the electronic equipment executes the early warning measure.

The specific implementation manner of steps S301 to S307 may refer to the related description of the user driving behavior monitoring method in fig. 1B, and is not described herein again.

Referring to fig. 3B, fig. 3B is a schematic flowchart illustrating another method for monitoring a driving behavior of a user according to an embodiment of the present disclosure.

It can be seen that in the embodiment of the present application, a method for driving behaviors of a user is provided, and an electronic device obtains a historical driving route of the user. And under the condition that the historical driving route passes through a preset area, acquiring the monitoring driving route of the user in a preset monitoring time period. Generating first mark information, wherein the first mark information indicates that the driving behavior of the user is suspected illegal behavior. Generating second marker information indicating that the vehicle is a suspected target vehicle; when the marking times of the second marking information are larger than or equal to a second preset threshold value, acquiring the identity authentication information of the user, and acquiring the marking times of the first marking information corresponding to the user based on the identity authentication information; and when the marking times of the first marking information are larger than or equal to a third preset threshold value, executing the early warning measure. Therefore, the electronic equipment can determine the risk of stealing the vehicle by the first marking times obtained by monitoring the user behavior and the second marking times obtained by monitoring the vehicle driving behavior, and prevent the situation that some users step on the same vehicle for multiple times by one person or multiple persons at different time points in a polling mode and want to steal the same vehicle from happening.

In accordance with the embodiments shown in fig. 1B, fig. 2A, and fig. 3A, please refer to fig. 4, which is a schematic structural diagram of an embodiment of a user driving behavior monitoring apparatus 400 provided in the embodiment of the present application. The user driving behavior monitoring apparatus 400 described in the present embodiment includes: a communication unit 401, a processing unit 402, and an execution unit 403, wherein,

the communication unit 401 configured to receive a historical travel route of the user; receiving a monitoring driving route of the user in a preset monitoring time period under the condition that the historical driving route passes through a preset area;

the processing unit 402 is communicatively connected with the communication unit 401, and is configured to:

the execution unit 403 is communicatively connected with the processing unit 402, and is configured to execute the warning measure indicated by the warning instruction.

It can be seen that, by using the user driving behavior monitoring device described in the embodiment of the present application, the historical driving route of the user can be obtained; under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period; further, based on the historical driving route and the monitoring driving route, judging whether the driving behavior of the user meets a preset condition; and executing early warning measures under the condition that the driving behaviors meet the preset conditions. Therefore, the driving behavior of the user can be monitored through the driving route of the user; therefore, under the condition that the behavior of the user meets the preset condition, the vehicle driven by the user is determined to have the risk of vehicle loss, the user can be pre-warned through the pre-warning measure, the risk of vehicle loss is favorably reduced, and the safe ecology of the shared vehicle is favorably maintained.

In a possible example, in terms of the determining whether the driving behavior of the user satisfies the preset condition based on the historical driving route and the monitoring driving route, the processing unit 402 is specifically configured to:

predicting at least one expected driving route of the user based on the historical driving route and the monitoring driving route;

determining a plurality of characteristic information corresponding to each expected driving route according to each expected driving route to obtain a plurality of characteristic information sets, wherein each expected driving route corresponds to one characteristic information set;

selecting at least one target characteristic information associated with the preset area from each characteristic information set to obtain a target characteristic information set corresponding to each expected driving route, wherein each target characteristic information set comprises the at least one target characteristic information;

acquiring the marking times of the first marking information; and

and judging whether the driving behavior of the user meets a preset condition or not based on the marking times and the target characteristic information set.

In a possible example, in terms of the determining whether the driving behavior of the user meets the preset condition based on the marking times and the target feature information set, the processing unit 402 is specifically configured to:

when the marking times are larger than or equal to a first preset threshold value, determining the type and the characteristic value corresponding to each target characteristic information in the target characteristic information set;

determining at least one first evaluation value corresponding to each target feature information set according to a mapping relation between a preset feature value of target feature information and the first evaluation value, wherein each first evaluation value corresponds to one target feature information in the target feature information sets;

determining a second evaluation value corresponding to each type of the target characteristic information in each target characteristic information set according to a preset mapping relation between the type of the target characteristic information and the second evaluation value, and obtaining at least one second evaluation value corresponding to each target characteristic information set;

acquiring a first weight corresponding to the characteristic value and a second weight corresponding to the type, wherein the sum of the first weight and the second weight is 1;

obtaining at least one third evaluation value corresponding to at least one expected driving route based on the at least one first evaluation value, the at least one second evaluation value, the first weight and the second weight;

calculating the sum of the at least one third evaluation value to obtain a target evaluation value; and

and when the target evaluation value is greater than or equal to a preset evaluation value, determining that the driving behavior meets the preset condition.

In a possible example, in terms of performing the early warning measure, the execution unit 403 is specifically configured to:

determining a driving environment corresponding to the user; and

and generating early warning information under the condition that the driving environment meets a preset environment, wherein the early warning information comprises information for prompting that the user is about to execute preset operation.

In one possible example, in terms of the predicting at least one expected travel route of the user based on the historical travel routes and the monitored travel routes, the processing unit 402 is specifically configured to:

predicting a driving parameter of a vehicle corresponding to the user based on the monitoring driving route;

determining historical driving parameters of the user based on the historical driving route;

predicting a first driving lane of the vehicle based on the driving parameters and the historical driving parameters to obtain a first expected driving road section corresponding to the vehicle in a first time period;

predicting a second driving lane of the vehicle according to a first expected driving road section corresponding to the first time period to obtain a second expected driving road section corresponding to the vehicle in a second time period, wherein the second time period is later than the first time period; by analogy, obtaining an nth expected driving road section corresponding to the vehicle in an nth time period, wherein N is a positive integer greater than 1; and

and combining the N expected running road sections corresponding to the N time periods to obtain at least one expected running route.

The scheme of the embodiment of the present application is introduced mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed in hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

Consistent with the embodiments shown in fig. 1B, fig. 2A, and fig. 3A, please refer to fig. 5, fig. 5 is a schematic structural diagram of an electronic device 500 provided in an embodiment of the present application, as shown in the figure, the electronic device 500 includes a processor 510, a memory 520, a communication interface 530, and one or more programs 521, where the one or more programs 521 are stored in the memory 520 and configured to be executed by the processor 510, and the one or more programs 521 include instructions for performing the following steps;

acquiring a historical driving route of the user;

It can be seen that, in the embodiment of the present application, there is provided a user driving behavior monitoring apparatus,

historical driving routes of the user can be obtained; under the condition that the historical driving route passes through a preset area, acquiring a monitoring driving route of the user in a preset monitoring time period; further, based on the historical driving route and the monitoring driving route, judging whether the driving behavior of the user meets a preset condition; and executing early warning measures under the condition that the driving behavior is determined to meet the preset conditions. Therefore, the driving behavior of the user can be monitored through the driving route of the user; therefore, under the condition that the behavior of the user meets the preset condition, the vehicle driven by the user is determined to have the risk of vehicle loss, the user can be pre-warned through the pre-warning measure, the risk of vehicle loss is favorably reduced, and the safe ecology of the shared vehicle is favorably maintained.

In one possible example, after determining that the historical travel route passes through a preset area, the instructions in the program are specifically configured to: generating first mark information, wherein the first mark information indicates that the driving behavior of the user is suspected illegal behavior.

In one possible example, the determining whether the driving behavior of the user meets a preset condition based on the historical driving route and the monitoring driving route is performed by specifically executing the following operations: predicting at least one expected travel route for the user based on the historical travel routes and the monitored travel routes; determining a plurality of characteristic information corresponding to each expected driving route according to each expected driving route to obtain a plurality of characteristic information sets, wherein each expected driving route corresponds to one characteristic information set; selecting at least one target characteristic information associated with the preset area from each characteristic information set to obtain a target characteristic information set corresponding to each expected driving route, wherein each target characteristic information set comprises the at least one target characteristic information; acquiring the marking times of the first marking information; and judging whether the driving behavior of the user meets a preset condition or not based on the marking times and the target characteristic information set.

In a possible example, the determining whether the driving behavior of the user meets a preset condition based on the marking times and the target feature information set includes: when the marking times are larger than or equal to a first preset threshold value, determining the type and the characteristic value corresponding to each target characteristic information in the target characteristic information set; determining at least one first evaluation value corresponding to each target feature information set according to a mapping relation between a preset feature value of target feature information and the first evaluation value, wherein each first evaluation value corresponds to one target feature information in the target feature information sets; determining a second evaluation value corresponding to each type of the target characteristic information in each target characteristic information set according to a preset mapping relation between the type of the target characteristic information and the second evaluation value, and obtaining at least one second evaluation value corresponding to each target characteristic information set; acquiring a first weight corresponding to the characteristic value and a second weight corresponding to the type, wherein the sum of the first weight and the second weight is 1; obtaining at least one third evaluation value corresponding to the at least one expected driving route based on the at least one first evaluation value, the at least one second evaluation value, the first weight and the second weight; calculating the sum of the at least one third evaluation value to obtain a target evaluation value; and determining that the driving behavior satisfies the preset condition when the target evaluation value is greater than or equal to a preset evaluation value.

In one possible example, the instructions in the program are specifically for performing the following: determining a driving environment corresponding to the user; and generating early warning information under the condition that the driving environment meets a preset environment, wherein the early warning information comprises information for prompting that the user is about to execute a preset operation.

In one possible example, after determining that the historical travel route includes a preset region, the instructions in the program are specifically configured to: generating second mark information, wherein the second mark information indicates that the vehicle is a suspected target vehicle; when the marking frequency of the second marking information is larger than or equal to a second preset threshold value, acquiring the identity authentication information of the user; acquiring the marking times of the first marking information corresponding to the user based on the identity authentication information; and when the marking times of the first marking information are larger than or equal to a third preset threshold value, executing the early warning measure.

In one possible example, the predicting of at least one expected travel route of the user based on the historical travel routes and the monitored travel routes, the instructions in the program are further specifically configured to: predicting a driving parameter of a vehicle corresponding to the user based on the monitoring driving route; determining historical driving parameters of the user based on the historical driving route; predicting a first driving lane of the vehicle based on the driving parameters and the historical driving parameters to obtain a first expected driving road section corresponding to the vehicle in a first time period; predicting a second driving lane of the vehicle according to a first expected driving road section corresponding to the first time period to obtain a second expected driving road section corresponding to the vehicle in a second time period, wherein the second time period is later than the first time period; by analogy, obtaining an nth expected driving road section corresponding to the vehicle in an nth time period, wherein N is a positive integer greater than 1; and combining the N expected running road sections corresponding to the N time periods to obtain at least one expected running route.

In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a hardware mode, and can also be realized in a software functional unit mode. It should be noted that, in the embodiment of the present application, the division of the unit is schematic, and is only one logic function division, and when the actual implementation is realized, another division manner may be provided.

Embodiments of the present application also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, the computer program causes a computer to execute part or all of the steps of any one of the methods as set forth in the method embodiments, and the computer includes an electronic device.

It should be noted that for simplicity of description, the above-mentioned embodiments of the method are described as a series of acts, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In this embodiment, the description of each embodiment has its own emphasis, and reference may be made to the related description of other embodiments for parts that are not described in detail in a certain embodiment.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the unit is only one type of logical function division, and other division manners may be possible in actual implementation, for example, multiple 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 coupling or direct coupling or communication connection between each other may be through some interfaces, indirect coupling or communication connection between devices or units, and may be in an electrical 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 as a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several 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 memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Those skilled in the art will appreciate that all or part of the steps of the various methods of this embodiment may be performed by associated hardware as instructed by a program, which may be stored in a computer readable memory, which may include: flash Memory disks, read-Only memories (ROMs), random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A method for monitoring driving behavior of a user, the method comprising the steps of:

acquiring a historical driving route of the user;

2. The method of claim 1, further comprising, after determining that the historical travel route passes through a preset area:

generating first mark information, wherein the first mark information indicates that the driving behavior of the user is suspected illegal behavior.

3. The method according to claim 2, wherein the determining whether the driving behavior of the user satisfies a preset condition based on the historical driving route and the monitoring driving route comprises the steps of:

predicting at least one expected travel route for the user based on the historical travel routes and the monitored travel routes;

determining a plurality of pieces of characteristic information corresponding to each expected driving route according to each expected driving route to obtain a plurality of characteristic information sets, wherein each expected driving route corresponds to one characteristic information set;

acquiring the marking times of the first marking information; and

4. The method according to claim 3, wherein the step of determining whether the driving behavior of the user meets a preset condition based on the marking times and the target feature information set comprises the following steps:

determining a second evaluation value corresponding to the type of each target feature information in each target feature information set according to a mapping relation between the type of preset target feature information and the second evaluation value, and obtaining at least one second evaluation value corresponding to each target feature information set;

5. The method of claim 1, the performing an early warning measure, comprising the steps of:

determining a driving environment corresponding to the user; and

6. The method of claim 2, after determining that the historical driving route includes a preset region, the method further comprising:

generating second mark information, wherein the second mark information indicates that the vehicle is a suspected target vehicle;

when the marking times of the second marking information are larger than or equal to a second preset threshold value, acquiring the identity authentication information of the user;

acquiring the marking times of the first marking information corresponding to the user based on the identity authentication information; and

and when the marking times of the first marking information are greater than or equal to a third preset threshold value, executing the early warning measure.

7. The method of claim 3, the predicting at least one of the expected travel routes for the user based on the historical travel routes and the monitored travel routes, comprising:

8. A user driving behavior monitoring apparatus, characterized in that the apparatus comprises: a communication unit, a processing unit and an execution unit, wherein,

the communication unit configured to receive a historical travel route of the user; receiving a monitoring driving route of the user in a preset monitoring time period under the condition that the historical driving route passes through a preset area;

9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a computer program stored for data exchange, which computer program, when being executed by a processor, carries out the method according to any one of claims 1-7.

10. An electronic device, comprising:

at least one processor;

a memory for storing processor-executable instructions, the memory communicatively coupled with the at least one processor;

wherein the at least one processor is configured to invoke the memory-stored instructions to perform the method of any one of claims 1-7.