CN109087506B

CN109087506B - Vehicle monitoring method and device

Info

Publication number: CN109087506B
Application number: CN201810837107.XA
Authority: CN
Inventors: 董俊龙; 王洋; 徐丽丽; 王宇飞
Original assignee: Neusoft Corp
Current assignee: Neusoft Corp
Priority date: 2018-07-26
Filing date: 2018-07-26
Publication date: 2020-08-11
Anticipated expiration: 2038-07-26
Also published as: CN109087506A

Abstract

The embodiment of the application discloses a vehicle monitoring method and device, wherein the method comprises the following steps: acquiring current driving data of a vehicle; judging whether the vehicle has risk behaviors or not according to the current running data of the vehicle; if the vehicle has the behavior of entering the monitoring area, the risk probability of the vehicle is calculated according to the current position of the vehicle, and therefore, by the technical scheme of the application, the current driving data of the vehicle can be obtained in real time, whether the vehicle has the risk behavior or not is judged according to the current driving data of the vehicle, and when the vehicle has the behavior of entering the monitoring area in the risk behavior, the risk probability of the vehicle is calculated, so that road supervision personnel can further take corresponding control measures according to the risk probability of the vehicle, and the occurrence of critical vehicle risk events is effectively prevented.

Description

Vehicle monitoring method and device

Technical Field

The application relates to the technical field of safety, in particular to a vehicle monitoring method and device.

Background

With the steady progress of national urbanization construction and infrastructure construction, the service range and the transportation frequency of some large-scale engineering transportation vehicles are gradually increased. In addition, other large-scale vehicles meeting various business operations and special road vehicles for transporting dangerous chemicals, fireworks and crackers and civil explosive substances are also increased in successive years, and the vehicles are mainly characterized by great weight, large volume and partial carrying of dangerous transported substances and can be regarded as critical vehicles. The currently defined critical vehicles generally refer to various construction vehicles, special vehicles, various cleaning vehicles for municipal administration, various buses, unit large-scale transportation vehicles, school buses, cargo transportation vehicles with more than two tons, petroleum, natural gas and chemical transportation vehicles and the like which run in urban areas.

The social security problem is that governments and vehicle monitoring departments need to carry out comprehensive security supervision on local critical vehicles, so that extremely severe behaviors that lawless persons use the critical vehicles to manufacture and damage the society are avoided.

In the prior art, the dangerous and heavy vehicles can be monitored based on the road videos, but at present, the number of the dangerous and heavy vehicles is large, the range of motion is wide, the number of the supervision personnel is limited, the deployment is limited, the dangerous and heavy vehicles cannot be found in time in the mode, and therefore effective monitoring on the dangerous and heavy vehicles cannot be achieved.

Disclosure of Invention

In view of this, embodiments of the present application provide a vehicle monitoring method and apparatus, so as to solve the technical problem in the prior art that a critical vehicle cannot be effectively monitored in time.

In order to solve the above problem, the technical solution provided by the embodiment of the present application is as follows:

a vehicle monitoring method, the method comprising:

acquiring current driving data of a vehicle, wherein the current driving data of the vehicle comprises a current position of the vehicle;

judging whether the vehicle has a risk behavior according to the current running data of the vehicle, wherein the risk behavior comprises a behavior of driving into a monitoring area;

and if the vehicle has the behavior of entering the monitoring area, calculating the risk probability of the vehicle according to the current position of the vehicle.

In one possible implementation, the risk behaviors further include one or more of abnormal driving behaviors, outlier driving behaviors, and out-of-range behaviors; the method further comprises the following steps:

and if the vehicle has the risk behaviors, generating prompt information of the risk behaviors of the vehicle.

In one possible implementation manner, the determining whether the vehicle has the risk behavior according to the current driving data of the vehicle further includes:

judging whether the vehicle has abnormal driving behaviors according to the current driving data of the vehicle, wherein the abnormal driving behaviors comprise at least one of traffic violation behaviors, behaviors that parking time exceeds a time threshold value, behaviors that the vehicle runs around a fixed area and violent driving behaviors;

if the vehicle is in a fleet, judging whether the vehicle has an outlier driving behavior according to the current position of the vehicle, wherein the outlier driving behavior comprises a behavior that the distance between the vehicle and other vehicles in the fleet exceeds a distance threshold;

acquiring historical driving data of a vehicle, wherein the historical driving data of the vehicle is used for determining a frequent track route of the vehicle, and judging whether the vehicle has a behavior of exiting a specified area according to the current position of the vehicle and the frequent track route of the vehicle, wherein the behavior of exiting the specified area comprises a behavior of exiting the frequent track route and/or a behavior of exiting a preset area;

and judging whether the vehicle has the behavior of entering a monitoring area or not according to the current position of the vehicle.

In one possible implementation, the method further includes:

if the vehicle has the behavior of entering the monitoring area, judging whether the vehicle enters a no-entry area in the monitoring area;

if the vehicle enters the no-entry area, taking a remote braking measure aiming at the vehicle;

and if the vehicle does not enter the no-entry area, generating and displaying a predicted driving path of the vehicle.

In one possible implementation, the generating and displaying the predicted travel path of the vehicle includes:

acquiring at least one planned path of which the current position of the vehicle reaches the no-entry area according to the current position of the vehicle and the driving direction of the vehicle, wherein each planned path has a path direction; judging whether the vehicle is on any one of the planned paths;

if the vehicle is on any one of the planned paths, determining the planned path where the vehicle is located as a target planned path;

judging whether the driving direction of the vehicle is consistent with the path direction of the target planned path or not;

if the driving direction of the vehicle is consistent with the path direction of the target planned path, adding the weight of the target planned path, deleting other planned paths, displaying the planned path with the highest weight in a map, marking the position of an interception point in the planned path with the highest weight, returning to judge whether the vehicle is positioned on any one of the planned paths, wherein the position of the interception point is the position of at least one point in the planned path with the highest weight;

and if the vehicle is not positioned on any one of the planned paths, or the driving direction of the vehicle is not consistent with the path direction of the target planned path, returning to the step of obtaining at least one planned path of which the current position of the vehicle reaches the forbidden area according to the current position of the vehicle and the driving direction of the vehicle.

In one possible implementation, the calculating the risk probability of the vehicle according to the current position of the vehicle includes:

if the vehicle enters a no-entry area in the monitoring area, setting the risk probability of the vehicle to be 1;

if the vehicle does not enter the no-entry area, acquiring a risk distance, and calculating the risk probability of the vehicle according to the risk distance, wherein the risk probability of the vehicle and the risk distance are in an inverse proportional relation, and the risk distance is the shortest distance between the current position of the vehicle and the no-entry area boundary of the monitoring area.

In one possible implementation, the method further includes:

and if the vehicle has the behavior of entering the monitoring area, improving the frequency of acquiring the current driving data of the vehicle.

A vehicle monitoring apparatus, the apparatus comprising:

an acquisition unit configured to acquire current travel data of a vehicle, the current travel data of the vehicle including a current position of the vehicle;

the system comprises a first judging unit, a second judging unit and a monitoring unit, wherein the first judging unit is used for judging whether the vehicle has risk behaviors according to current running data of the vehicle, and the risk behaviors comprise behaviors of driving into a monitoring area;

and the calculating unit is used for calculating the risk probability of the vehicle according to the current position of the vehicle if the vehicle has the behavior of entering the monitoring area.

In one possible implementation, the apparatus further includes:

the second judgment unit is used for judging whether the vehicle enters a no-entry area in the monitoring area or not if the vehicle has the behavior of entering the monitoring area;

a braking unit for taking a remote braking measure for the vehicle if the vehicle enters the no-entry region;

and the display unit is used for generating and displaying the predicted driving path of the vehicle if the vehicle does not enter the no-entry area.

In one possible implementation, the display unit includes:

the acquisition subunit is configured to acquire, according to the current position of the vehicle and the driving direction of the vehicle, at least one planned path where the current position of the vehicle reaches the no-entry area, where each planned path has a path direction;

the first judging subunit is used for judging whether the vehicle is positioned on any one planned path;

the determining subunit is configured to determine, if the determination result of the first determining subunit is that the vehicle is on any one of the planned paths, the planned path where the vehicle is located as a target planned path;

the second judgment subunit is used for judging whether the driving direction of the vehicle is consistent with the path direction of the target planned path or not;

a display subunit, configured to, if the determination result of the second determination subunit is that the driving direction of the vehicle is consistent with the path direction of the target planned path, add the weight of the target planned path, delete another planned path, display the planned path with the highest weight in a map, mark the location of an intercept point in the planned path with the highest weight, and return to the first determination subunit to perform determination on whether the vehicle is located on any one of the planned paths, where the intercept point is the location of at least one point in the planned path with the highest weight;

and the triggering subunit is configured to, if the judgment result of the first judging subunit is that the vehicle is not located on any one of the planned paths, or if the judgment result of the second judging subunit is that the driving direction of the vehicle is not consistent with the path direction of the target planned path, re-trigger the obtaining subunit to perform, according to the current position of the vehicle and the driving direction of the vehicle, obtaining at least one planned path where the current position of the vehicle reaches the no-entry area.

In a possible implementation manner, the computing unit specifically includes:

the setting subunit is used for setting the risk probability of the vehicle to be 1 if the vehicle enters a no-entry area in the monitoring area;

and the calculating subunit is used for acquiring a risk distance if the vehicle does not enter the no-entry area, and calculating the risk probability of the vehicle according to the risk distance, wherein the risk probability of the vehicle and the risk distance are in an inverse proportion relationship, and the risk distance is the shortest distance between the current position of the vehicle and the no-entry area boundary of the monitoring area.

A computer-readable storage medium having stored therein instructions which, when run on a terminal device, cause the terminal device to execute the above-described vehicle monitoring method.

A computer program product which, when run on a terminal device, causes the terminal device to execute the above-mentioned vehicle monitoring method.

Therefore, the embodiment of the application has the following beneficial effects:

the embodiment of the application can acquire the current driving data of the vehicle in real time, such as the current position of the vehicle, judge whether the vehicle has a risk behavior, and calculate the risk probability of the vehicle when the vehicle has a behavior of driving into a monitoring area in the risk behavior, so that a road supervisor can further take corresponding control measures according to the risk probability of the vehicle, thereby providing enough security deployment time for the road supervisor, or controlling a suspected dangerous vehicle in advance, and effectively preventing the dangerous vehicle from occurring.

Drawings

Fig. 1 is a flowchart of a vehicle monitoring method according to an embodiment of the present disclosure;

fig. 2 is a division diagram of an early warning area in a monitoring area according to an embodiment of the present disclosure;

fig. 3 is a flow chart of monitoring frequency switching according to an embodiment of the present disclosure;

FIG. 4 is a risk probability graph according to an embodiment of the present disclosure;

FIG. 5 is an exemplary flow chart of a vehicle monitoring method provided by an embodiment of the present application;

FIG. 6 is a flowchart of a method for generating a predicted travel path according to an embodiment of the present disclosure;

FIG. 7 is an exemplary flow chart of another vehicle monitoring method provided by embodiments of the present application;

fig. 8 is a structural diagram of a vehicle monitoring device according to an embodiment of the present application.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments accompanying the drawings are described in detail below.

In order to facilitate understanding of the technical solutions provided in the present application, the following briefly describes the research background of the technical solutions in the present application.

In the prior art, road videos are mainly used for monitoring driving behaviors of critical vehicles, however, due to the fact that the number of the critical vehicles in a city is large, the moving range is wide, and hands of supervision personnel are limited, abnormal behaviors of the critical vehicles cannot be found in time, and therefore the critical vehicles cannot be effectively controlled.

Based on the above, the present application provides a vehicle monitoring method and apparatus, which can obtain the current position of the vehicle and the speed of the vehicle in real time, determine whether the vehicle has a risk behavior, generate a prompt message when the vehicle has the risk behavior, prompt the risk behavior of the vehicle, and calculate the risk probability of the vehicle when the vehicle enters a monitoring area, so that a road supervisor can further take corresponding control measures according to the risk probability of the vehicle, thereby providing sufficient security deployment time for the road supervisor, or performing advanced control on a suspected dangerous vehicle, and effectively preventing the occurrence of a dangerous event of the dangerous vehicle.

In order to facilitate understanding of the technical solutions provided by the present application, a vehicle monitoring method provided in an embodiment of the present application will be described in detail below with reference to the accompanying drawings.

Referring to fig. 1, which shows a flowchart of a vehicle monitoring method provided in an embodiment of the present application, the embodiment of the present application may be applied to a monitoring system, which may be implemented by a server, as shown in fig. 1, the method includes:

s101: the current driving data of the vehicle is acquired.

In this embodiment, in order to implement real-time monitoring on a critical vehicle, current driving data of the vehicle needs to be acquired so as to acquire a current driving state of the vehicle. In practical application, a critical vehicle which needs to be subjected to data acquisition may be marked in advance, for example, the critical vehicle is numbered, and then the current driving data of the marked vehicle is acquired. The driving data may include a current position of the vehicle, and the driving data may also include information such as a speed of the vehicle.

In practical application, in order to reduce the load of the collection quantity, the collection frequency can be preset, and then the current driving data of the vehicle can be obtained according to the preset frequency. In specific implementation, the driving data of the vehicle can be collected by a Global Positioning System (GPS) module mounted on the vehicle, and the collected data is sent to a monitoring system, and is stored and analyzed by the monitoring system. The GPS can acquire data such as longitude, latitude, altitude, speed and time of a geographic position where the vehicle is located, information such as the longitude, the latitude, the altitude and the like acquired by the GPS can be used for determining the current position of the vehicle, the speed acquired by the GPS can be used for determining the current speed of the vehicle, and the time acquired by the GPS can be used for determining acceleration of the vehicle, recording time of occurrence of risk behaviors and the like. The above travel data of the vehicle may be used to further determine whether the vehicle has risky behavior.

S102: and judging whether the vehicle has risk behaviors or not according to the current running data of the vehicle.

In this embodiment, whether the current driving state of the vehicle has a risk behavior is determined according to the acquired current driving data of the vehicle, so that corresponding measures are taken according to the determination result.

In one possible implementation, the risk behavior may include an entry into a monitored area behavior. Further, the risk behavior may also include one or more of abnormal driving behavior, outlier driving behavior, and exit from a regulated area behavior.

The following describes specific implementations of determining whether the vehicle has the above-mentioned risk behavior according to the current driving data of the vehicle.

1. Drive-in monitoring zone behavior

In this embodiment, whether the vehicle has a behavior of entering the monitoring area may be determined according to the current position of the vehicle. During specific implementation, the current position data of the vehicle is obtained, and whether the vehicle enters the monitoring area is judged according to the current position of the vehicle and the position range of the monitoring area. The monitoring area can be circular or polygonal, and when the monitoring area is circular, whether the vehicle is located in the monitoring area can be judged according to the distance from the current position of the vehicle to the circle center; when the monitored area is a polygon, the judgment can be carried out by utilizing a ray algorithm.

For example, taking a certain organization as a center, setting a square circle of 1 kilometer as a monitoring area, acquiring the current geographic coordinates of the vehicle, calculating the distance between the two geographic coordinates according to the geographic coordinates of the organization, and if the distance is less than 1 kilometer, judging that the vehicle has a behavior of driving into the monitoring area.

2. Abnormal driving behavior

In the present embodiment, it may be determined whether there is an abnormal driving behavior of the vehicle based on the current running data of the vehicle. Wherein the abnormal driving behavior may include at least one of traffic violation behavior, behavior of parking time exceeding a time threshold, behavior of driving around a fixed area, and behavior of violent driving. The traffic violation behaviors can include overspeed behaviors, red light running behaviors and the like; the violent driving behaviors can include rapid acceleration, rapid deceleration, frequent lane changing behaviors and the like.

Whether the vehicle has behaviors of overspeed, rapid acceleration, rapid deceleration and the like can be determined according to the current speed of the vehicle; the parking time of the vehicle can be determined according to the current speed of the vehicle, when the parking time exceeds a preset time threshold, the abnormal behavior that the parking time exceeds the time threshold can be considered to exist in the vehicle, and the time threshold can be set according to the actual situation, and the embodiment of the application does not limit the abnormal behavior; according to the current position of the vehicle, the running track of the vehicle in a period of time can be determined, and whether the running track runs around a fixed area can be further determined.

It can be understood that, when determining whether the vehicle has traffic violations such as speeding behavior and red light running behavior according to the current running data of the vehicle, it is also necessary to obtain relevant information of the road environment, for example, obtain the speed limit of the road on which the vehicle is currently running and the state of the signal lamps at the intersection, so as to determine whether the vehicle has traffic violations according to the road environment information and the current running data of the vehicle. For example, the current running speed of the vehicle is 80Km/h, the position of the vehicle is located on a road in the center of a city, the speed limit of the road is 60Km/h, and the current running speed of the vehicle is greater than the limited speed of the road, so that the vehicle is judged to have overspeed behavior. In addition, in a possible implementation manner, the traffic violation behaviors of the vehicle, such as red light running behaviors of the vehicle, can be directly acquired from the road violation monitoring system to judge whether the vehicle has abnormal driving behaviors.

3. Driving behavior from cluster

In this embodiment, if the vehicle is in the fleet, it is determined whether the vehicle has an outlier driving behavior according to the current position of the vehicle, and if the distance between the vehicle and another vehicle in the fleet exceeds the distance threshold, it is determined that the vehicle has the outlier driving behavior. Wherein the outlier driving behavior comprises behavior in which a distance between the vehicle and other vehicles in the fleet exceeds a distance threshold. For example, a circle is drawn by taking a certain vehicle in the fleet as a center and 200 meters as a radius, and when other vehicles are out of the circle, the vehicle and other vehicles in the fleet are considered to exceed a distance threshold of 200 meters, and the vehicle is judged to have the driving behavior of an outlier. The distance threshold may be set according to an actual situation, which is not limited in the embodiment of the present application. In addition, the outlier driving behavior can be determined to exist when the percentage of the number of vehicles in the circle to the total number of the motorcade vehicles is smaller than a preset threshold.

4. Exit from defined area behavior

In this embodiment, historical driving data of the vehicle may be acquired, the historical driving data of the vehicle may be used to determine a frequent trajectory route of the vehicle, and it is determined whether a behavior of the vehicle exiting a specified area exists according to a current position of the vehicle and the frequent trajectory route of the vehicle, and if the behavior exists, it is indicated that the vehicle has a risk behavior. The behavior of exiting the specified area comprises a behavior of exiting a frequent track route and/or a behavior of exiting a preset area.

The historical driving data is data of the vehicle driving in a certain historical time period, the historical driving data can include information of a historical running track, a driving speed and the like of the vehicle, the historical driving data can be used for representing a driving rule of the vehicle, and when the difference between the current driving data and the historical driving data of the vehicle is obtained, it is indicated that the vehicle may have a behavior of driving out of a specified area. For example, the historical driving data of the bus may include a driving route, a driving speed range, an average stopping time at each station, and the like of the bus, the fixed driving route of the bus may be regarded as a frequent-track route, and when a certain bus deviates from the frequent-track route, it is determined that the bus has a behavior of driving out of the frequent-track route; the cleaning vehicles in the municipal administration have areas which need to be responsible for respectively and pre-allocated, for example, the responsible area of a certain cleaning vehicle is an urban area A, but the cleaning vehicle is determined to be currently located in an urban area B by acquiring the current position information of the cleaning vehicle, and the cleaning vehicle is determined to have the behavior of exiting the preset area when the cleaning vehicle exits the urban area A.

In practical application, when any one of abnormal driving behavior, outlier driving behavior, driving out of a specified area and driving into a monitoring area is determined according to the current driving data of the vehicle and the historical driving data of the vehicle, the vehicle can be judged to have risk behavior, and corresponding measures can be further taken according to the judgment result.

S103: and if the vehicle has the behavior of entering the monitoring area, calculating the risk probability of the vehicle according to the current position of the vehicle.

In this embodiment, when it is determined that a certain vehicle has a behavior of entering a monitoring area, which indicates that a risky behavior of the vehicle is relatively serious, a risky probability of the vehicle needs to be calculated according to a current position of the vehicle, where the risky probability is used to identify a risk degree of the vehicle, and the greater the risky probability, the greater the risk of the vehicle is. In practical application, the calculated risk probability can be displayed, so that a supervisor can take emergency measures for vehicles with higher risk behaviors according to the risk probability value. A detailed description will be given in the following embodiments regarding a specific implementation of calculating the risk probability of the vehicle based on the current position of the vehicle.

It can be seen from the above embodiments that, the present embodiment of the application can obtain the current driving data of the vehicle in real time, such as the current position of the vehicle, determine whether the vehicle has a risky behavior, and calculate the risk probability of the vehicle when the vehicle has a behavior of entering the monitoring area in the risky behavior, so that the road supervisor can further take corresponding control measures according to the risk probability of the vehicle, thereby providing sufficient security deployment time for the road supervisor, or performing advanced control on a suspected dangerous vehicle, and effectively preventing the occurrence of dangerous vehicle risk events.

Based on the foregoing embodiment, in a possible implementation manner, the vehicle monitoring method provided in the embodiment of the present application may further include: and if the vehicle has the risk behaviors, generating prompt information of the risk behaviors of the vehicle.

In this embodiment, when judging that there is any one kind of risk behavior in a certain vehicle, for making security protection personnel in time discover this risk vehicle, can produce the suggestion information that the vehicle has risk behavior to make security protection personnel can focus on the vehicle that has risk behavior, avoid the emergence of dangerous condition.

In practical applications, the prompt information of the vehicle risky behavior may include an event name, an occurrence location, an occurrence time, a vehicle identifier, other information of the vehicle, and the like, where the event name indicates which risky behavior occurs in the vehicle, for example, a behavior entering a monitoring area, and the like, and in addition, prompt information for eliminating the risky behavior may be generated for a behavior in which the vehicle exits the monitoring area. The prompt information can be prompted by means of sending short messages, voice and the like, so that the vehicle with the risk behaviors on the road is prompted to the supervisor.

In the embodiment of the application, in order to further ensure security work, the monitoring area can be divided into a no-entry area and at least one stage of early warning area, so that a supervisor can take different security measures according to different positions of the monitoring area where the vehicle is located. The no-entry area has a high early warning level, and vehicles are strictly prohibited from entering the no-entry area.

Based on this, in a possible implementation manner, when the vehicle has a behavior of entering the monitoring area, whether the vehicle enters a no-entry area in the monitoring area can be further judged; if the vehicle enters the no-entry area, a remote braking measure for the vehicle is taken, and the vehicle is prohibited from approaching further. If the vehicle does not enter the no-entry region, a predicted travel path of the vehicle is generated and displayed.

In this embodiment, whether the vehicle enters the no-entry area or not can be determined according to the current position of the vehicle and the position of the no-entry area, when it is monitored that the vehicle enters the no-entry area, it is indicated that the risk behavior of the vehicle is high, and in order to avoid the occurrence of the dangerous behavior, a supervisor can send a remote braking signal through a monitoring system to prevent the vehicle from further approaching. If the vehicle does not enter the no-entry area, the vehicle has risk behaviors due to the fact that the vehicle already enters the monitoring area, in order to continuously monitor whether the vehicle is close to the no-entry area in the future, a predicted running path can be generated for the vehicle, and whether the vehicle is close to the no-entry area is monitored according to the predicted running path and the current position of the vehicle, so that a supervisor can be timely prompted to pay attention to the vehicle. If the vehicle exits from the monitored area, the generation and display of the predicted travel path of the vehicle may be stopped. A detailed description will be given of a specific implementation of generating the predicted travel path for the vehicle in the following embodiments.

In practical application, the forbidden area can be set as a circular area, or can be set as a polygonal area according to the shape of a building, the shape of a fence, the planning of peripheral roads and the like. In specific application, no matter whether the forbidden region is a circular region or a polygonal region, the forbidden region is set as the highest-level early warning, and then the non-forbidden region in the monitoring region is set as at least one-level early warning region.

For convenience of understanding, a description is given by taking two-stage early warning areas as an example, referring to fig. 2, a circular forbidden area is taken as an example in the figure, and as shown in fig. 2, besides the forbidden area, a first-stage early warning area and a second-stage early warning area are also set, wherein the range of the first-stage early warning area is the largest, the range of the forbidden area is the smallest, and the range of the second-stage early warning area is located between the range of the first-stage early warning area and the range of the forbidden area.

When a vehicle is in a primary early warning area, indicating that the vehicle has a risk behavior of entering an forbidden area, generating a predicted driving path for the vehicle, when the driving direction of the vehicle is more matched with the predicted driving path, indicating that the vehicle is close to the forbidden area, the risk probability of the vehicle is higher, the warning level for the vehicle is higher, when the vehicle enters the forbidden area, the risk probability reaches the maximum value, and taking a remote braking measure to prohibit the vehicle from further approaching.

It should be noted that, when a vehicle has a risk behavior of entering a monitoring area, the risk coefficient of the vehicle is already high, and in order to increase monitoring of the vehicle, the frequency of obtaining the current driving data of the vehicle needs to be increased so as to grasp the movement of the vehicle in time, so that corresponding measures can be taken in time to avoid an emergency.

In practical application, the number of dangerous vehicles and no-entry areas in a city is large, so that the monitoring frequency of the vehicles can be adaptively adjusted to relieve the monitoring pressure, and if a certain vehicle does not enter the monitoring area, the real-time driving data of the vehicle can be acquired at a lower monitoring frequency; when a certain vehicle enters a monitoring area, different monitoring frequencies are adjusted according to the grade of the early warning area where the vehicle enters, and the early warning area with the higher vehicle entering grade indicates that the vehicle has higher risk probability, and the running data of the vehicle is acquired at the higher monitoring frequency. For example, setting monitoring frequencies f0, f1 and f2, wherein f0< f1< f2, and the frequency switching process is as shown in fig. 3, firstly, acquiring a real-time driving position of the vehicle, judging whether the vehicle drives into a secondary early warning area according to the driving position, and if so, setting the monitoring frequency to be f2 to monitor the vehicle; if the vehicle does not enter the secondary early warning area, judging whether the vehicle enters the primary early warning area, if so, setting the monitoring frequency to be f1 to monitor the vehicle; if the vehicle does not enter the primary early warning area, the monitoring frequency is set to f0 to monitor the vehicle.

According to the embodiment, when the vehicle has the behavior of entering the monitoring area, the risk probability of the vehicle can be calculated according to the current position of the vehicle, so that the risk coefficient of the vehicle is represented through the risk probability. In an embodiment of the present application, an implementation manner for calculating a risk probability of a vehicle is provided, which specifically includes the following steps:

1. and if the vehicle enters a no-entry area in the monitoring area, setting the risk probability of the vehicle to be 1.

2. And if the vehicle does not enter the no-entry area, acquiring a risk distance, and calculating the risk probability of the vehicle according to the risk distance, wherein the risk probability of the vehicle is in an inverse proportional relation with the risk distance, and the risk distance is the shortest distance between the current position of the vehicle and the boundary of the no-entry area of the monitoring area.

In this embodiment, the shortest distance between the vehicle and the boundary of the no-entry region is obtained, and then the risk probability of the vehicle is calculated according to the shortest distance, which may specifically be calculated by using the following formula (1):

wherein, x is the shortest distance from the current position of the vehicle to the boundary of the forbidden zone, if the forbidden zone is circular, x is equal to the distance from the vehicle to the central point of the circular zone and reduces the radius of the forbidden zone; if the forbidden area is a polygon, x is equal to the minimum value of the distance from the vehicle to each line segment of the polygon; a and b are coefficients.

In practical application, considering that the security levels of different monitoring areas are different, the security levels corresponding to areas such as government, school, market, factory and the like can be set according to specific business and local regulatory authority regulations, different monitoring areas can be set with different risk distances L and corresponding risk probability values P, L is the shortest distance from the boundary of the forbidden area, and L is the shortest distance from the boundary of the forbidden area>0, L and P are preset by the relevant regulatory authorities, which is not limited in this embodiment. When x is 0, y is 1; when x is L, y is P; then the two sets of data are substituted into the formula (1) to obtain

For example, when L is 1000 meters and P is 0.5, and a is 1000, a risk probability graph is obtained, as shown in fig. 4, it can be seen from fig. 4 that, when a vehicle enters a monitoring area, the closer the distance to the boundary of the no-entry area, the larger the corresponding risk probability value.

In order to facilitate understanding of the foregoing embodiments, the vehicle monitoring method provided in the embodiments of the present application is described with reference to an actual application scenario. Referring to fig. 5, an exemplary flowchart of a vehicle monitoring method provided in the embodiment of the present application is shown.

As shown in fig. 5, first, current driving data of a vehicle is obtained in real time, risk behaviors of the vehicle are identified according to the current driving data and historical driving data stored in a database, whether the vehicle has the risk behaviors or not is judged, and if the vehicle does not have the risk behaviors, monitoring is continued; and if the vehicle has the risk behaviors, generating prompt information of the risk behaviors of the vehicle.

If the vehicle enters the monitoring area in the risk behavior, then whether the vehicle enters the no-entry area needs to be continuously judged, if so, a remote braking measure is taken to prohibit the vehicle from further approaching; if the vehicle does not enter the no-entry area, judging whether the vehicle enters a secondary early warning area, if so, increasing the frequency of obtaining vehicle driving data, increasing the monitoring force, generating and displaying a predicted driving path of the vehicle, finally outputting the risk probability of the vehicle, and continuing to monitor the vehicle; if the vehicle does not enter the secondary early warning area, judging whether the vehicle enters the primary early warning area, if so, generating and displaying a predicted driving path, outputting the risk probability of the vehicle, and continuing to monitor the vehicle; and if the vehicle does not enter the primary early warning area, the vehicle is continuously monitored.

In this embodiment, when a vehicle has a risk behavior, it is first determined whether the vehicle enters the no-entry region, and it is determined whether the vehicle enters the secondary early warning region and the primary early warning region, so that it can be seen that, in practical application, the most dangerous behavior can be excluded first, thereby avoiding an emergency. Of course, whether the vehicle enters the primary early warning area or not can be judged first, if the vehicle enters the primary early warning area, whether the vehicle enters the secondary early warning area or not and whether the vehicle enters the no-entry area or not are judged, if the vehicle does not enter the primary early warning area, subsequent judgment is not needed, computing resources are saved, and the method for judging the vehicle risk behaviors is not limited.

It should be noted that, in fig. 5, except for the forbidden area, two stages of early warning areas are set, and the number of stages of the early warning areas set in this embodiment is not limited, and in practical application, different number of stages can be set according to the situation.

In the above-described embodiment, when the vehicle enters the monitoring area but does not enter the no-entry area, the predicted travel path of the vehicle is generated and displayed, and a specific implementation of generating the predicted travel path will be described below.

Referring to fig. 6, which illustrates a flowchart of a method of generating a predicted travel path, as shown in fig. 6, the method may include:

s601: and acquiring at least one planned path of which the current position of the vehicle reaches the no-entry area according to the current position of the vehicle and the driving direction of the vehicle, wherein each planned path has a path direction.

In this embodiment, when the vehicle enters the monitoring area but does not enter the no-entry area, at least one planned path, which is when the current position of the vehicle reaches the no-entry area, may be acquired according to the current position of the vehicle and the driving direction of the vehicle, where the acquired planned path may be acquired by real-time planning according to the current position of the vehicle, the driving direction of the vehicle, and the no-entry area, or may be an already existing planned path, which is acquired from a database and reaches the no-entry area from the current position of the vehicle and along the driving direction of the vehicle.

The traveling direction of the vehicle may be determined according to the current position of the vehicle and the position of the vehicle at the previous time. The path direction of the planned path may be a direction in which the vehicle on each planned path travels from the current position to the no-entry region along the travel direction. It is understood that, due to the different driving directions of the vehicles, the planned route from the current position of the vehicle to the no-entry area may also be different.

In practical application, when a path needs to be planned for a vehicle, the path is planned along the driving direction of the vehicle by taking the current position of the vehicle as a starting point and taking a no-entry area as an end point. It should be noted that the current position of the vehicle may be an intersection region of a plurality of monitoring regions, and therefore, when performing path planning, path planning needs to be performed for a forbidden region in each monitoring region, so as to determine a forbidden region where the vehicle is to approach according to the planned path and the real-time position of the vehicle. In practical applications, multiple paths can be planned for a vehicle for each forbidden zone, and then the planned path into which the vehicle is going to enter is determined, which is described below by taking one forbidden zone as an example.

With the current position of the vehicle as a starting point and a certain position P of the no-entry region as an end point, routes may be planned for the vehicle along the driving direction of the vehicle by using navigation services, shortest path algorithms, or map data, for example, n routes L1, L2, …, Ln are planned, and the weight of each planned route is initialized to 0.

It will be appreciated that the planned route is actually a set of broken segments formed by a plurality of GPS latitude and longitude coordinates, for example, the planned route Li ═ { p1, p2, p3, …, pm }, and is formed by m broken segments, each broken segment being formed by GPS latitude and longitude coordinates, and each broken segment may represent a road, for example, a road between two intersections.

After at least one planned path where the current position of the vehicle reaches the no-entry region is acquired, S602 may be executed to determine whether the vehicle is on a certain planned path.

S602: and judging whether the vehicle is in any planned path, if so, executing step 603, and if not, deleting all current planned paths and returning to step 601.

In this embodiment, it may be determined whether the vehicle is on a planned path according to the real-time driving position of the vehicle, and if the vehicle is on the planned path, S603 is continuously executed; if the vehicle is not in any planned path, it indicates that the currently acquired planned path is invalid, and may delete all existing planned paths and reacquire the planned path of the vehicle, that is, return to S601.

In practical application, since the planned path may be formed by at least one broken line segment, it may be specifically considered to determine whether a point is on a certain broken line when determining whether a vehicle is driving on a certain planned path.

Step 603: and determining the planned path of the vehicle as a target planned path.

When the vehicle is on a certain planned path, the planned path can be used as a target planned path for further judgment.

S604: and judging whether the driving direction of the vehicle is consistent with the path direction of the target planned path or not, if so, executing S605, otherwise, deleting all current planned paths, and returning to S601.

Because the monitored vehicle has uncontrollable property, when the vehicle is on the target planned path, two situations also occur, wherein one situation is that the driving direction of the vehicle is consistent with the path direction of the target planned path, namely the vehicle drives to a no-entry area along the target planned path, S605 is executed, and the weight of the target planned path is increased; in another case, although the vehicle is on the target planned path, the driving direction may be changed, and the driving direction of the vehicle is not consistent with the current path direction of the target planned path, which indicates that the vehicle does not drive to the no-entry area along the target planned path, but because the vehicle is in the monitoring area, the risk of the vehicle cannot be eliminated, the planned path of the vehicle needs to be obtained again according to the driving direction of the vehicle, that is, all current planned paths are deleted, and the process returns to S601.

S605: and increasing the weight of the target planned path, deleting other planned paths, displaying the planned path with the highest weight in the map, marking the position of the interception point in the planned path with the highest weight, and returning to the step 602.

In this embodiment, when it is determined that the vehicle is traveling along a route on a certain planned route, which indicates that the vehicle is approaching an exclusion area, the weight of the planned route is increased to identify that the vehicle is approaching the exclusion area through the planned route. In this embodiment, the planned path with the highest weight is displayed on the map, so that monitoring personnel can visually check possible future driving tracks of the vehicle, and meanwhile, the interception point position in the planned path with the highest weight is marked, so that security personnel can perform interception and fortification at the inflection point position. The interception point position is a position of at least one point in the planned path with the highest weight, and may specifically be an end point of each broken line segment in a road broken line segment set constituting the planned path.

And deleting other planned paths which are not driven into by the vehicle, so as to prevent the planned path with the highest display weight from being wrong due to the fact that the weights of other planned paths are smaller after the vehicle drives into other planned paths from the target planned path. The method can also be used for periodically judging whether the vehicle runs on a certain planned path, if the vehicle is continuously judged to run on the current target planned path, the weight of the target planned path is continuously increased, and if the vehicle does not run on the target planned path, the planned path of the vehicle can be obtained again because other planned paths are deleted and no planned path exists.

Through the embodiment, when the vehicle enters the monitoring area, the planned path from the current position of the vehicle to the no-entry area in the monitoring area can be obtained, whether the vehicle enters a certain planned path or not is judged according to the real-time position of the vehicle, when the vehicle enters the planned path, the weight of the planned path is increased and displayed in a map, so that a supervisor can take measures for the vehicle in time according to the display information, the vehicle is prevented from further approaching the no-entry area, and the monitoring strength for the dangerous vehicle is improved.

The following describes a vehicle monitoring method provided by the embodiment of the present application with reference to an actual application scenario. Referring to fig. 7, the figure is an exemplary flowchart of a vehicle monitoring method provided in an embodiment of the present application.

As shown in fig. 7, the current driving position of the vehicle is firstly obtained in real time, and then whether the vehicle enters the primary early warning area is judged, if not, the monitoring is continued; and if so, monitoring the risk path, and judging whether a planned path to a no-entry area corresponding to the primary early warning area exists according to the current position of the vehicle.

If the planned path exists, judging whether the vehicle is on a certain planned path, if so, increasing the weight of the planned path where the vehicle is located, deleting other planned paths, displaying the planned path with the highest weight in a map, marking the inflection point position in the planned path with the highest weight, calculating and displaying the risk probability of the vehicle according to the position of the vehicle, finally adjusting the monitoring frequency according to the position of the vehicle, and continuously monitoring the vehicle according to the adjusted monitoring frequency.

And if the vehicle is not in any planned path, deleting all the existing planned paths, re-planning the paths, initializing the weight value of the planned path to 0, and re-judging whether the vehicle is in the planned path and performing subsequent operations.

If the planned path from the current position of the vehicle to the forbidden area does not exist in the database, the path is planned for the vehicle, the weight value is initialized, and then the subsequent operation is executed.

In the embodiment of the application, the monitoring on the dangerous vehicles can be realized, after the vehicles enter the monitoring area, the predicted driving paths of the vehicles can be further determined and displayed, the risk probability of the vehicles can be calculated, so that the supervisors can conveniently find the vehicles with risks in time according to the display information, measures can be taken for the vehicles, the vehicles are prevented from being further close to the forbidden area, and the monitoring force on the dangerous vehicles is improved.

Based on the above method embodiment, the present application further provides a vehicle monitoring device, which will be described below with reference to the accompanying drawings.

Referring to fig. 8, which shows a structure diagram of a vehicle monitoring apparatus provided in an embodiment of the present application, the structure diagram may include:

an obtaining unit 801, configured to obtain current driving data of a vehicle, where the current driving data of the vehicle includes a current location of the vehicle.

A first determining unit 802, configured to determine whether a risk behavior exists in the vehicle according to current driving data of the vehicle, where the risk behavior includes a behavior of driving into a monitoring area.

A calculating unit 803, configured to calculate a risk probability of the vehicle according to the current location of the vehicle if the vehicle has the behavior of entering the monitoring area.

In one possible implementation, the risk behaviors further include one or more of abnormal driving behaviors, outlier driving behaviors, and out-of-range behaviors; the device further comprises:

and the generating unit is used for generating prompt information of the risk behaviors of the vehicle if the vehicle has the risk behaviors.

In a possible implementation manner, the current driving data of the vehicle further includes a speed of the vehicle, and the first determining unit specifically includes:

the third judgment bullet element is used for judging whether the vehicle has abnormal driving behaviors according to the current driving data of the vehicle, wherein the abnormal driving behaviors comprise at least one of traffic violation behaviors, behaviors that parking time exceeds a time threshold value, behaviors that the vehicle drives around a fixed area and violent driving behaviors;

a fourth judgment bullet cell, configured to judge whether there is an outlier driving behavior of the vehicle according to the current position of the vehicle if the vehicle is in a fleet of vehicles, where the outlier driving behavior includes a behavior in which a distance between the vehicle and another vehicle in the fleet of vehicles exceeds a distance threshold;

the fifth judgment bullet element is used for acquiring historical driving data of the vehicle, the historical driving data of the vehicle is used for determining a frequent track route of the vehicle, and whether the vehicle has a behavior of exiting a specified area is judged according to the current position of the vehicle and the frequent track route of the vehicle, and the behavior of exiting the specified area comprises a behavior of exiting the frequent track route and/or a behavior of exiting a preset area;

and the sixth judgment bullet element is used for judging whether the vehicle has the behavior of entering the monitoring area according to the current position of the vehicle.

In one possible implementation, the apparatus further includes:

In one possible implementation, the display unit includes:

In a possible implementation manner, the computing unit specifically includes:

In one possible implementation, the apparatus further includes:

and the improving unit is used for improving the frequency of acquiring the current running data of the vehicle if the vehicle has the behavior of entering the monitoring area.

It should be noted that, for specific implementation of each unit in this embodiment, reference may be made to the above method embodiment, and this embodiment is not described herein again.

In addition, the embodiment of the application also provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are run on a terminal device, the terminal device is caused to execute the above-mentioned vehicle monitoring method.

The embodiment of the present application further provides a computer program product, which when running on a terminal device, enables the terminal device to execute the above vehicle monitoring method.

It should be noted that, in the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the system or the device disclosed by the embodiment, the description is simple because the system or the device corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.

It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

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

if the vehicle has the behavior of entering the monitoring area, calculating the risk probability of the vehicle according to the current position of the vehicle, and judging whether the vehicle enters a no-entry area in the monitoring area;

if the vehicle does not drive into the no-entry area, acquiring at least one planned path, of which the current position reaches the no-entry area, of the vehicle according to the current position of the vehicle and the driving direction of the vehicle, wherein each planned path has a path direction; judging whether the vehicle is on any one of the planned paths;

2. The method of claim 1, wherein the risk behavior further comprises one or more of abnormal driving behavior, outlier driving behavior, and exit from a regulated area behavior; the method further comprises the following steps:

3. The method of claim 2, wherein the current driving data of the vehicle further includes a speed of the vehicle, and the determining whether the vehicle has a risky behavior according to the current driving data of the vehicle comprises:

4. The method of claim 1, wherein the calculating the risk probability of the vehicle based on the current location of the vehicle comprises:

5. The method of claim 1, further comprising:

6. A vehicle monitoring apparatus, characterized in that the apparatus comprises:

the calculating unit is used for calculating the risk probability of the vehicle according to the current position of the vehicle if the vehicle has the behavior of entering the monitoring area;

a display unit for generating and displaying a predicted travel path of the vehicle if the vehicle does not enter the no-entry region;

7. The apparatus according to claim 6, wherein the computing unit specifically comprises:

8. A computer-readable storage medium having stored therein instructions that, when run on a terminal device, cause the terminal device to perform the vehicle monitoring method of any one of claims 1-5.