CN116011800A

CN116011800A - Traffic event early warning method and equipment

Info

Publication number: CN116011800A
Application number: CN202111209181.5A
Authority: CN
Inventors: 陈维强; 刘洪蕾; 孙卓毅; 许晶玉; 姜东昕
Original assignee: Hisense TransTech Co Ltd
Current assignee: Hisense TransTech Co Ltd
Priority date: 2021-10-18
Filing date: 2021-10-18
Publication date: 2023-04-25

Abstract

The application provides a traffic event early warning method and equipment; for any vehicle to be identified, based on the pass information acquired in the pass management system by adopting the identification information of the vehicle to be identified, determining that the vehicle to be identified handles the pass in the current jurisdiction, and after the vehicle is not overdue, determining the running behavior of the vehicle to be identified based on the vehicle-mounted data reported by the vehicle-mounted equipment and the bayonet data reported by the bayonet equipment; based on the driving behavior, when the vehicle to be identified does not drive according to the related rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded; and when the number of the candidate vehicles reaches a threshold value in the same time period, performing early warning treatment on a target object corresponding to the attribute information of the candidate vehicles based on risk information of traffic events of the candidate vehicles determined by adopting at least one risk factor corresponding to each candidate vehicle and a risk early warning rule.

Description

Traffic event early warning method and equipment

Technical Field

The invention relates to the technical field of traffic safety control, in particular to a traffic event early warning method and equipment.

Background

Because the number of times of traffic incidents is high, the traffic incident early warning method has become a main research direction in the technical field of traffic safety management and control. At present, a scheme for traffic event early warning based on fatigue driving and a scheme for traffic event early warning based on overspeed exist.

The scheme for carrying out traffic event early warning based on fatigue driving mainly comprises the steps of determining whether a driver is in a fatigue driving state according to the definition of fatigue driving illegal behaviors of road traffic safety law, and carrying out traffic event early warning based on the fatigue driving state of the driver. When determining whether a driver is tired to drive, whether the vehicle is always driven by the same driver cannot be accurately judged, and a great amount of police force is needed to guide the vehicle into a service area to conduct manual one-to-one anti-fatigue reminding, so that the traffic accident early warning accuracy is low;

the scheme for traffic event early warning based on overspeed is mainly determined according to the corresponding speed limit of each road section and the running speed of the vehicle; when the running speed of the vehicle is determined, the average speed determined based on the length of the running section of the vehicle and the running time is determined, so even if the running speed is too fast on a section of the road, when the average speed of the entire section of the road does not exceed the speed limit of the section of the road, it is recognized that the speed is not exceeded, and thus the accuracy of traffic event early warning is low.

In addition to factors affecting traffic events such as fatigue driving and overspeed, factors affecting traffic events include factors related to rules related to the pass such as whether the vehicle is traveling on a traffic line, whether the vehicle is traveling on a traffic time, whether a pass is handled, and whether the pass is overdue. However, a method for realizing traffic event early warning based on the related rules of the pass is not provided in the prior art.

Disclosure of Invention

The application provides a traffic event early warning method and equipment, and provides a method for realizing traffic event early warning based on a pass related rule, so that the accuracy of traffic event early warning is improved, possible traffic events are avoided in advance, driving safety is improved, and resources are saved.

In a first aspect, an embodiment of the present application provides a method for traffic event early warning, where the method includes:

aiming at any vehicle to be identified, acquiring the pass information of the vehicle to be identified in a pass management system based on the identification information of the vehicle to be identified;

determining that the vehicle to be identified has transacted a pass in the current jurisdiction area based on the pass information, and determining the running behavior of the vehicle to be identified based on vehicle-mounted global positioning system (Global Positioning System, GPS) data reported by vehicle-mounted equipment mounted on the vehicle to be identified and bayonet data reported by bayonet equipment after the transacted pass is not overdue, wherein the running behavior is used for representing the running state of the vehicle to be identified in the current time period and the current road section;

Based on the driving behavior, when the vehicle to be identified does not drive according to the related rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded;

when the number of the candidate vehicles reaches a number threshold value in the same time period, determining risk information of traffic events of each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle, wherein the risk factors are used for representing factors of the traffic events of the vehicles to be identified;

and performing early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.

In the embodiment of the application, a method for realizing traffic event early warning based on a related rule of a pass is provided. After the pass is checked in the current jurisdiction, the running behavior of the vehicle to be identified is determined based on the vehicle-mounted GPS data reported by the vehicle-mounted equipment and the bayonet data reported by the bayonet equipment, and the running behavior of the vehicle to be identified is determined based on the fusion of the vehicle-mounted GPS data and the bayonet data, so that the accuracy of the running behavior is improved; based on the determined driving behavior, when the vehicle to be identified does not drive according to the related rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, attribute information of the candidate vehicle is recorded, and due to the accuracy of driving behavior identification, the accuracy of determining the candidate vehicle is ensured; when the number of the candidate vehicles reaches the threshold value, the risk information of the traffic event is determined based on at least one risk factor corresponding to each candidate vehicle, the risk information of the traffic event is determined based on the risk information corresponding to each candidate vehicle, and the risk early warning rule, the target object corresponding to the attribute information of the candidate vehicle is subjected to early warning treatment, and when the number of the candidate vehicles reaches the threshold value, the risk information of the traffic event is determined based on the risk factor corresponding to each candidate vehicle, and the early warning treatment is performed based on the risk information and the risk early warning rule, so that the possible traffic event can be avoided in advance, and the driving safety is improved.

In one possible implementation manner, after the pass information of the vehicle to be identified is acquired in the pass management system, if it is determined that the vehicle to be identified does not handle the pass in the current jurisdiction based on the pass information, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded.

In the embodiment of the application, if the fact that the vehicle to be identified does not handle the pass in the current jurisdiction is determined based on the pass information, the fact that the vehicle to be identified runs in the jurisdiction which does not allow the pass is indicated, the vehicle to be identified is used as a candidate vehicle which allows traffic event early warning, and accuracy of identification of the candidate vehicle is guaranteed.

In one possible implementation manner, for any vehicle to be identified, based on identification information of the vehicle to be identified, before acquiring pass information of the vehicle to be identified in a pass management system, determining that the image information contains an important vehicle based on image information in the bayonet data reported by the bayonet equipment, and taking the important vehicle as the vehicle to be identified; and/or

Aiming at any vehicle, determining that the vehicle is an important vehicle based on a vehicle type identifier carried in vehicle-mounted GPS data reported in real time by vehicle-mounted equipment installed on the vehicle, and taking the important vehicle as the vehicle to be identified;

Wherein, the key vehicle comprises one or a combination of a dangerous chemical vehicle and a residue soil vehicle.

In the embodiment of the application, in order to reduce the workload, each vehicle running on the road is not used as a vehicle to be identified, but the vehicles running on the road are screened, and the vehicles meeting the conditions are screened to be used as the vehicles to be identified. Therefore, a method for determining the vehicle to be identified is provided to accurately determine whether the vehicle running on the road is the vehicle to be identified, so that the workload in the early warning process of traffic incidents is further reduced.

In one possible implementation manner, based on the driving behavior, determining that the vehicle to be identified is not driving according to the relevant rule of the pass includes:

if the specific running rule corresponding to the processed pass is stored in the pass management system, when the fact that the current time period corresponding to the running behavior is not consistent with the specific running time period corresponding to the specific running rule and/or the fact that the current road section corresponding to the running behavior is not consistent with the specific running road section corresponding to the specific running rule is determined, the fact that the vehicle to be identified does not run according to the pass related rule is determined;

if the specific running rule corresponding to the processed pass is not stored in the pass management system, based on the road section management rule stored in the pass management system, determining that the current time period corresponding to the running behavior is matched with the forbidden time period in the road section management rule, and/or determining that the vehicle to be identified does not run according to the pass related rule when the current road section corresponding to the running behavior is determined to be matched with the forbidden road section in the road section management rule.

In the embodiment of the application, an implementation mode of whether the vehicle to be identified runs according to the relevant rule of the pass is provided for determining whether the vehicle to be identified runs according to the relevant rule of the pass.

In one possible implementation, determining risk information of traffic events occurring in each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle includes:

for any candidate vehicle, determining at least one risk factor matched with the candidate vehicle according to the vehicle type identification of the candidate vehicle, and determining a risk value set formed based on risk values corresponding to each of the at least one risk factor;

and determining a risk level corresponding to the risk value set based on a trained clustering model, and taking the risk level as risk information of traffic events of the candidate vehicles, wherein the clustering model is obtained after training by a clustering algorithm based on the historical risk value set of the historical candidate vehicles.

In the embodiment of the application, the risk level is used as the risk information of the traffic event of the candidate vehicle, and a mode for determining the risk level of the candidate vehicle is provided so as to accurately determine the risk level of the candidate vehicle.

for any candidate vehicle, determining at least one risk factor matched with the candidate vehicle according to the vehicle type identification of the candidate vehicle, and determining a risk value corresponding to each risk factor in the at least one risk factor;

and determining a risk early-warning value corresponding to the candidate vehicle based on each risk value and the corresponding weight, and taking the risk early-warning value as risk information of traffic events of the candidate vehicle.

In the embodiment of the application, the risk early-warning value is used as the risk information of the traffic event of the candidate vehicle, and a mode for determining the risk early-warning value of the candidate vehicle is provided so as to accurately determine the risk early-warning value of the candidate vehicle.

In one possible implementation manner, performing early warning treatment on a target object corresponding to attribute information of a candidate vehicle based on risk information corresponding to each candidate vehicle and a risk early warning rule, includes:

for any candidate vehicle, based on the corresponding relation between the risk level set in the risk early warning rule and the early warning treatment rule, determining the early warning treatment rule corresponding to the candidate vehicle according to the risk level corresponding to the candidate vehicle, and carrying out early warning treatment on the target object corresponding to the attribute information of the candidate vehicle according to the early warning treatment rule through the event processing end.

In the embodiment of the application, when the risk information is determined to be the risk level, a mode of performing early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk level of each candidate vehicle and the risk early warning rule is provided, different early warning treatments are performed based on different risk levels, and at the moment, the situation of performing early warning treatment in a short message informing mode does not need to be manually warned, so that police resources are saved.

and screening candidate vehicles with risk early warning values reaching a first risk threshold value from the candidate vehicles according to the risk early warning values corresponding to the candidate vehicles based on screening rules set in the risk early warning rules, and carrying out early warning treatment on target objects corresponding to the attribute information of the screened candidate vehicles through an event processing end.

In the embodiment of the application, when the risk information is determined to be the risk early warning value, a risk early warning value based on each candidate vehicle and a risk early warning rule are provided, the candidate vehicles are screened, the candidate vehicles with the risk early warning value reaching the first risk threshold are screened out, early warning treatment is only carried out on the screened candidate vehicles, early warning treatment is not required to be carried out on all the candidate vehicles, and police resources are saved.

In one possible implementation, if the target object includes a belonging enterprise of the candidate vehicle, the belonging enterprise is subjected to early warning treatment when the following conditions are satisfied:

determining all target key vehicles contained under the enterprise, and acquiring target risk early warning values of all target key vehicles;

and carrying out weighted average on the obtained target risk early-warning values, determining an enterprise risk early-warning value corresponding to the enterprise, and carrying out early-warning treatment on the enterprise through an event processing end when the enterprise risk early-warning value reaches a second risk threshold.

In the embodiment of the application, in order to improve the accuracy of traffic event early warning and the driving safety, the enterprise is also subjected to early warning treatment.

In a second aspect, an embodiment of the present application provides a traffic event early warning device, where the device at least includes:

a communication interface and a processor, wherein:

the communication interface is used for receiving vehicle-mounted GPS data reported by vehicle-mounted equipment installed on a vehicle to be identified and receiving bayonet data reported by bayonet equipment;

the processor is used for acquiring the pass information of the vehicle to be identified in the communication card management system based on the identification information of the vehicle to be identified aiming at any vehicle to be identified; determining the running behavior of the vehicle to be identified based on the vehicle-mounted GPS data reported by the vehicle-mounted equipment and the bayonet data reported by the bayonet equipment, wherein the running behavior is used for representing the running state of the vehicle to be identified in the current time period and the current road section after the vehicle to be identified has transacted the pass in the current jurisdiction range based on the pass information; based on the driving behavior, when the vehicle to be identified does not drive according to the related rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded; when the number of the candidate vehicles reaches a number threshold value in the same time period, determining risk information of traffic events of each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle, wherein the risk factors are used for representing factors for enabling the traffic events of the vehicles to be identified to occur; and performing early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.

In a third aspect, an embodiment of the present application provides a traffic event early warning device, including:

the acquisition module is used for acquiring the pass information of the vehicle to be identified in the pass management system based on the identification information of the vehicle to be identified aiming at any vehicle to be identified;

the first determining module is used for determining that the vehicle to be identified has transacted a pass in the current jurisdiction based on the pass information, and determining the running behavior of the vehicle to be identified based on the vehicle-mounted GPS data reported by the vehicle-mounted equipment and the bayonet data reported by the bayonet equipment which are installed on the vehicle to be identified after the transacted pass is not overdue, wherein the running behavior is used for representing the running state of the vehicle to be identified in the current time period and the current road section;

the second determining module is used for determining that the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning when the vehicle to be identified does not run according to the related rule of the pass based on the running behavior, and recording attribute information of the candidate vehicle;

the third determining module is used for determining risk information of traffic events of each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle when the number of the candidate vehicles reaches a threshold value in the same time period, wherein the risk factors are used for representing factors for enabling the traffic events of the vehicles to be identified to occur;

And the early warning module is used for carrying out early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the method steps of traffic event early warning provided by embodiments of the present application.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.

Drawings

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

Fig. 1 is a schematic diagram of an application scenario in an embodiment of the present application;

FIG. 2 is a block diagram of a traffic event early warning device according to an embodiment of the present application;

FIG. 3 is a flow chart of a method for traffic event early warning in an embodiment of the present application;

FIG. 4 is a flow chart of determining risk information for a traffic event for a candidate vehicle in an embodiment of the present application;

FIG. 5 is a flowchart of a method for training a cluster model according to an embodiment of the present application;

FIG. 6 is a flowchart of another embodiment of determining risk information for a traffic event of a candidate vehicle;

FIG. 7 is a schematic diagram of a vehicle security risk early warning treatment according to an embodiment of the present application;

fig. 8 is a schematic diagram of a fatigue driving determination flow in an embodiment of the present application;

fig. 9 is a flowchart of a method for determining a red eye passenger car according to an embodiment of the present application;

fig. 10 is a flowchart of a method for determining a relevant rule pre-warning for a pass according to an embodiment of the present application;

FIG. 11 is a flowchart of a method for driving early warning determination for a specific driving rule according to an embodiment of the present application;

fig. 12 is a flowchart of a method for driving early warning determination according to a road segment management rule in an embodiment of the present application;

fig. 13 is a block diagram of a traffic event early warning device in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantageous effects of the present application more clear, 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 some embodiments, but not all embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.

The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein.

The following is a brief description of the design concept of the embodiments of the present application.

Because the number of times of traffic incidents is high, early warning is carried out in advance aiming at the traffic incidents which possibly occur in vehicles, the possibility of the traffic incidents is reduced, and the driving safety is improved so as to succeed in the main research direction in the technical field of traffic safety management and control.

The occurrence of traffic incidents is influenced by factors such as fatigue driving, red-eye passenger cars, overspeed and the like, and also by factors related to the relevant rules of the pass such as non-passing line driving, non-passing time driving, forbidden zone running, non-handling of communication passes, overdue pass and the like.

At present, in the related art, a technical scheme of traffic event early warning is proposed by aiming at single influencing factors such as fatigue driving, red eye passenger cars, overspeed and the like, but a technical scheme of comprehensively carrying out traffic event early warning by factors related to relevant rules of the pass such as non-passing line driving, non-passing time driving, forbidden zone running, non-handling of communication passes, pass overdue and the like is not provided.

In view of this, the embodiment of the application provides a method for realizing traffic event early warning based on the relevant rule of the pass, and in the embodiment of the application, vehicle-mounted GPS data is combined with bayonet data, so that accuracy of determining the driving behavior of the vehicle to be identified is improved, whether the vehicle to be identified is driven according to the relevant rule of the pass or not is determined based on the driving behavior, the vehicle to be identified which is not driven according to the relevant rule of the pass is used as a candidate vehicle for allowing traffic event early warning, and attribute information of the candidate vehicle is recorded; and determining at least one risk factor corresponding to each candidate vehicle when the number of the candidate vehicles on the same road section reaches a number threshold value in the same time period, and determining risk information of traffic incidents of the candidate vehicles based on the risk factors, so as to perform early warning treatment on target objects corresponding to attribute information of the candidate vehicles based on the risk information and a risk early warning rule, thereby improving the accuracy of traffic incident early warning, avoiding possible traffic incidents in advance, improving driving safety and saving resources.

After the design concept of the embodiment of the present application is introduced, some simple descriptions are made below for application scenarios applicable to the technical solution of the embodiment of the present application, and it should be noted that the application scenarios described below are only used to illustrate the embodiment of the present application and are not limiting. In the specific implementation process, the technical scheme provided by the embodiment of the application can be flexibly applied according to actual needs.

Referring to fig. 1, fig. 1 is a schematic diagram of a possible application scenario provided in an embodiment of the present application, where the application scenario includes a vehicle 10 to be identified, a bayonet device 20, a traffic event early warning device 30, and an event processing end 40;

the bayonet device 20 may be a monitoring device, for acquiring information of vehicles on a road;

the traffic event early warning device 30 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), basic cloud computing services such as big data and artificial intelligence platforms; but also a terminal device.

The event processing terminal 40 may be a portable terminal device such as a mobile phone, a palm computer (Personal Digital Assistant, PDA) or the like assigned to a traffic police.

In one possible implementation, the vehicle 10 to be identified and the bayonet device 20 may communicate with the traffic event pre-warning device 30 over a communication network, which may be a wired network or a wireless network. Thus, the vehicle 10 to be identified and the bayonet device 20 may be directly or indirectly connected with the traffic event pre-warning device 30 by means of wired or wireless communication. For example, the vehicle 10 to be identified may be indirectly connected to the traffic event early warning device 30 through the wireless access point 11, or the vehicle 10 to be identified may be directly connected to the traffic event early warning device 30 through the internet, which is not limited herein. Similarly, the traffic event early warning device 30 and the event processing end 40 may communicate through a communication network, where the communication network is a wired network or a wireless network, and the detailed description is omitted herein.

In one possible application scenario, the traffic event early warning device 30 acquires vehicle-mounted GPS data reported by a vehicle-mounted terminal mounted on the vehicle 10 to be identified, and acquires bayonet data reported by the bayonet device 20; and determining whether traffic event early warning is required for the vehicle to be identified based on the fusion of the vehicle-mounted GPS data and the bayonet data, and performing early warning treatment on a target object corresponding to the attribute information of the vehicle 10 to be identified through the event processing end 40 after determining that the traffic event early warning is required for the vehicle to be identified.

Referring to fig. 2, fig. 2 is a schematic structural diagram illustrating an apparatus 30 for traffic event early warning in an embodiment of the present application.

It should be understood that the traffic event pre-warning device 30 shown in fig. 2 is merely one example, and that the traffic event pre-warning device 30 may have more or fewer components than shown in fig. 2, may combine two or more components, or may have a different configuration of components. The various components shown in fig. 2 may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and/or application specific integrated circuits.

A hardware configuration block diagram of the traffic event early warning device 30 according to an exemplary embodiment is illustrated in fig. 2. As shown in fig. 2, the traffic event early warning apparatus 30 includes: radio Frequency (RF) circuitry 300, memory 301, input/output interface 302, display unit 303, camera 304, communication interface 305, wireless fidelity (Wireless Fidelity, wi-Fi) module 306, processor 307, power supply 308, and the like.

The RF circuit 300 may be configured to receive and transmit signals during a message or call, and may receive downlink data from a base station and then transmit the downlink data to the processor 307 for processing; uplink data may be sent to the base station. Typically, RF circuitry includes, but is not limited to, antennas, at least one amplifier, transceivers, couplers, low noise amplifiers, diplexers, and the like.

Memory 301 is used to store computer programs and data that may be run on processor 307; the computer programs, when executed by the processor 307, cause the processor 307 to perform each step in the methods of traffic event early warning of various exemplary embodiments in this application.

In one possible implementation, the memory 301 may include a readable medium in the form of volatile memory, such as high-speed Random Access Memory (RAM) and/or cache memory, and may further include Read Only Memory (ROM); non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device, may also be included.

Memory 301 may also include a program/utility having a set of (at least each) program modules, with reference to FIG. 2, a partial block diagram of memory 301 is illustratively provided in FIG. 2; program modules include, but are not limited to: an operating system, each one or more application programs, other program modules, and program data.

The input/output interface 302 may be used to receive numeric or character information, generate signal inputs related to the functional control of the traffic event early-warning device 30, and in particular, the input/output interface 302 may include a touch panel 3021 disposed on the front side of the traffic event early-warning device 30, for gathering touch operations on the touch panel 3021, determining various instructions, such as clicking a button, dragging a scroll box, and the like.

In one possible implementation, the input/output interface 302 also includes other input devices 3022, such as a voice input, and the like.

The display unit 303 may be used to display a graphical user interface (graphical user interface, GUI) of various menus of the traffic event pre-warning device 30. In particular, the display unit 303 may include a display panel 3031 disposed on the front of the traffic event early warning device 30. The display panel 3031 may be configured in the form of a liquid crystal display, a light emitting diode, or the like.

In one possible implementation, the touch panel 3021 may be overlaid on the display panel 3031, or the touch panel 3021 may be integrated with the display panel 3031 to implement the input and output functions of the traffic event early warning device 30, and after integration, may be simply referred to as a touch display screen. The display unit 303 may display an application program and corresponding operation steps.

The camera 304 may be used to capture still images or video. The object generates an optical image through the lens and projects the optical image onto the photosensitive element. The photosensitive element may be a charge coupled device (charge coupled device, CCD) or a Complementary Metal Oxide Semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, which is then transferred to the processor 307 for conversion into a digital image signal.

The communication interface 305 is configured to receive vehicle-mounted GPS data reported by a vehicle-mounted device installed on a vehicle to be identified, and receive bayonet data reported by a bayonet device.

Wi-Fi belongs to a short-distance wireless transmission technology, and the device 30 for traffic event early warning can help a user to send and receive e-mails, browse web pages, access streaming media and the like through the Wi-Fi module 306, so that wireless broadband Internet access is provided for the user.

The processor 307 is a control center of the traffic event early-warning device 30, connects the respective parts of the entire traffic event early-warning device 30 using various interfaces and lines, performs various functions of the traffic event early-warning device 30 and processes data by running or executing a software program for traffic event early-warning stored in the memory 301, and calling data stored in the memory 301.

In some embodiments, processor 307 may include one or more processing units; processor 307 may also integrate an application processor that primarily handles operating systems, user interfaces, applications, etc., and a baseband processor that primarily handles wireless communications. It will be appreciated that the baseband processor described above may not be integrated into the processor 307. In the embodiment of the present application, the processor 307 may run the operating system and the response message, and the traffic event early warning method in the embodiment of the present application.

In the embodiment of the present application, the processor 307 is configured to obtain, for any vehicle to be identified, pass information of the vehicle to be identified in the communication card management system based on identification information of the vehicle to be identified; determining the running behavior of the vehicle to be identified based on the vehicle-mounted GPS data reported by the vehicle-mounted equipment and the bayonet data reported by the bayonet equipment, wherein the running behavior is used for representing the running state of the vehicle to be identified in the current time period and the current road section after the vehicle to be identified has transacted the pass in the current jurisdiction range based on the pass information; based on the driving behavior, when the vehicle to be identified does not drive according to the related rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded; when the number of the candidate vehicles reaches a number threshold value in the same time period, determining risk information of traffic events of each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle, wherein the risk factors are used for representing factors for enabling the traffic events of the vehicles to be identified to occur; and performing early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.

In one possible implementation, after obtaining the pass information of the vehicle to be identified in the pass management system, the processor 307 is further configured to:

if the fact that the vehicles to be identified do not handle the pass in the current jurisdiction is determined based on the pass information, the vehicles to be identified are used as candidate vehicles allowing traffic event early warning, and attribute information of the candidate vehicles is recorded.

In one possible implementation, the processor 307 is further configured to, for any vehicle to be identified, before acquiring the pass information of the vehicle to be identified in the pass management system based on the identification information of the vehicle to be identified:

based on the image information in the bayonet data reported by the bayonet equipment, after the fact that the image information contains the key vehicles is determined, the key vehicles are used as vehicles to be identified; and/or

In one possible implementation, the processor 307 is specifically configured to:

And determining a risk level corresponding to the risk value set based on a trained clustering model, and taking the risk level as the risk level of the traffic event of the candidate vehicle, wherein the clustering model is obtained after training the historical risk value set of the historical candidate vehicle by a clustering algorithm.

In one possible implementation, if the target object includes the affiliated business of the candidate vehicle, the processor 307 performs the pre-warning treatment on the affiliated business when the following conditions are satisfied:

It should be noted that, the traffic event early warning device 30 provided in the embodiment of the present application further includes a bluetooth module, a sensor, an audio circuit, a speaker, a microphone, and the like. Wherein:

And the Bluetooth module is used for carrying out information interaction with other Bluetooth devices with the Bluetooth module through a Bluetooth protocol. For example, the traffic event pre-warning device 30 may establish a bluetooth connection with a wearable electronic device (e.g., a smart watch) that also has a bluetooth module through the bluetooth module, thereby performing data interaction.

The traffic event pre-warning device 30 may also include at least one sensor, such as an acceleration sensor, a distance sensor, a fingerprint sensor, a temperature sensor. The traffic event warning device 30 may also be configured with other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, light sensors, motion sensors, and the like.

Audio circuitry, speakers, microphones may provide an audio interface between the user and the traffic event alert device 30. The audio circuit can transmit the received electric signal after the audio data conversion to a loudspeaker, and the loudspeaker converts the electric signal into a sound signal to be output. The traffic event alert device 30 may also be configured with a volume button for adjusting the volume of the sound signal. On the other hand, the microphone converts the collected sound signal into an electrical signal, which is received by the audio circuit and converted into audio data, which is output to the RF circuit for transmission to, for example, another terminal, or to the memory for further processing. The microphone can acquire the voice of the user.

The traffic event warning device 30 also includes a power source 308 (e.g., a battery) that provides power to the various components. The power supply may be logically connected to the processor 307 through a power management system, so that functions of managing charging, discharging, power consumption, and the like are realized through the power management system. The traffic event warning device 30 may also be configured with power buttons for power on and off, and screen locking functions.

Based on the above application scenario, the method for traffic event early warning provided in the exemplary embodiment of the present application is described below with reference to the above application scenario described above, and it should be noted that the above application scenario is only shown for the convenience of understanding the spirit and principles of the present application, and embodiments of the present application are not limited in this respect.

Referring to fig. 3, fig. 3 is a flowchart illustrating a method for traffic event early warning in an embodiment of the present application, including the following steps:

step S300, for any vehicle to be identified, obtaining the pass information of the vehicle to be identified in the pass management system based on the identification information of the vehicle to be identified.

In the embodiment of the application, the traffic event early warning is performed not for all vehicles running on the road, but only for the vehicles to be identified which meet the condition. Therefore, it is necessary to identify a vehicle traveling on a road and determine a vehicle to be identified.

The method comprises the steps that after an important vehicle is determined to be contained in image information based on image information in bayonet data reported by bayonet equipment, the important vehicle is taken as a vehicle to be identified; and/or

After the vehicle to be identified is determined, acquiring the pass information of the vehicle to be identified in a pass management system based on the identification information of the vehicle to be identified aiming at the vehicle to be identified;

the identification information of the vehicle to be identified can be a number plate number of the vehicle to be identified, and the pass information of the vehicle to be identified is acquired in the pass management system based on the number plate number of the vehicle to be identified; wherein the communication certificate information includes, but is not limited to: whether the pass is transacted, whether the pass is overdue, namely, whether the pass is in the validity period, the validity period of the pass, and whether the pass corresponds to a specific driving rule.

In one possible implementation manner, after the pass information of the vehicle to be identified is acquired, if it is determined that the vehicle to be identified does not handle the pass in the current jurisdiction based on the pass information, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded, wherein the attribute information of the candidate vehicle includes, but is not limited to, identification information of the candidate vehicle and identification information of an enterprise to which the candidate vehicle belongs.

In another possible implementation manner, after the pass information of the vehicle to be identified is acquired, if it is determined that the vehicle to be identified has transacted a pass in the current jurisdiction based on the pass information, determining whether the transacted pass is overdue based on the valid period in the pass information, taking the vehicle to be identified as a candidate vehicle allowing traffic event early warning after determining that the transacted pass is overdue, and recording attribute information of the candidate vehicle; after determining that the processed pass is not overdue, the determination is continued as to whether the vehicle to be identified is traveling according to the specific traveling rule of the pass, see, in particular, the detailed discussion of step S301 and step S302.

Step S301, determining that the vehicle to be identified has transacted a pass in the current jurisdiction based on the pass information, and determining a driving behavior of the vehicle to be identified based on the vehicle-mounted GPS data reported by the vehicle-mounted device mounted on the vehicle to be identified and the bayonet data reported by the bayonet device after the transacted pass is not overdue, wherein the driving behavior is used for representing the driving state of the vehicle to be identified in the current time period and the current road section.

Step S302, based on the driving behavior, when the vehicle to be identified is determined not to drive according to the relevant rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded;

In one possible implementation, based on the driving behavior, it is determined whether the vehicle to be identified is driving according to the rule related to the pass:

firstly, determining whether a specific running rule of a processed pass corresponding to a vehicle to be identified is stored in a communication card management system, wherein the specific running rule prescribes a specific running road section and/or specific running time of the vehicle to be identified;

it should be noted that: a specific travel section is set in the specific travel rule, but in order to set the travel time of the characteristic travel section, it is determined that the travel can be performed on the specific travel section at any time; or a specific running time is set in the specific running rule, but the running road sections are not limited, and the fact that running can be performed on all the running road sections in the jurisdiction in the specific running time is determined; or a specific travel section is set in the specific travel rule and a specific travel time is set for the specific travel section, it is determined that only traveling on the specific travel section is possible within the specific travel time.

For example, if it is determined that the specific running rule of the processed pass corresponding to the vehicle to be identified is stored in the pass management system, it is determined whether the current period corresponding to the running behavior of the vehicle to be identified is consistent with the specific running period corresponding to the specific running rule, and/or whether the current road segment corresponding to the running behavior is consistent with the specific running road segment corresponding to the specific running rule;

After determining that the current time period corresponding to the running behavior of the vehicle to be identified is inconsistent with the specific running time period corresponding to the specific running rule and/or determining that the current road section corresponding to the running behavior is inconsistent with the specific running road section corresponding to the specific running rule, determining that the vehicle to be identified does not run according to the pass related rule;

after determining that the current time period corresponding to the running behavior of the vehicle to be identified accords with the specific running time period corresponding to the specific running rule, and determining that the current road section corresponding to the running behavior accords with the specific running road section corresponding to the specific running rule, determining that the vehicle to be identified runs according to the pass related rule.

For example, if the specific running rule corresponding to the processed pass is not stored in the pass management system, determining whether the current period corresponding to the running behavior is consistent with the forbidden time period in the road section management rule and/or determining whether the current road section corresponding to the running behavior is consistent with the forbidden road section in the road section management rule based on the road section management rule stored in the pass management system;

after determining that the current time period corresponding to the running behavior of the vehicle to be identified accords with the forbidden time period in the road section management rule and/or determining that the current road section corresponding to the running behavior accords with the forbidden road section in the road section management rule, determining that the vehicle to be identified does not run according to the pass related rule;

And after determining that the current time period corresponding to the driving behavior of the vehicle to be identified is inconsistent with the forbidden time period in the road section management rule and determining that the current road section corresponding to the driving behavior is inconsistent with the forbidden road section in the road section management rule, determining that the vehicle to be identified is driven according to the pass related rule.

When the vehicle to be identified is determined not to run according to the related rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded, wherein the attribute information of the candidate vehicle at least comprises the candidate vehicle and a company to which the candidate vehicle belongs.

In step S303, when the number of the candidate vehicles reaches the number threshold in the same time period, risk information of traffic events occurring in each candidate vehicle is determined based on at least one risk factor corresponding to each candidate vehicle, where the risk factor is used to represent factors that cause the traffic events to occur in the vehicle to be identified.

In the embodiment of the application, a corresponding relation between the type of the candidate vehicle and the risk factor is set, and then the risk factor matched with the type of the candidate vehicle is selected from the set corresponding relation based on the type of the candidate vehicle;

For example, aiming at a vehicle with the type of the vehicle being a dangerous chemical vehicle, setting corresponding risk factors to be one or a combination of accidents, illegal laws, early warning times, driving ages, driving time rules, whether the vehicle is scrapped or not and dangerous article grades;

corresponding risk factors are set as one or a combination of accidents, illegal laws, early warning times, driving ages, driving time rules, whether the vehicle is scrapped or hung up or not according to other vehicle types, namely vehicles of the non-dangerous chemical vehicles.

After at least one risk factor corresponding to the candidate vehicles is acquired, the risk information of traffic events of each candidate vehicle can be determined by the following method:

mode one:

referring to fig. 4, fig. 4 is a flowchart for exemplarily providing risk information for determining that a traffic event occurs in a candidate vehicle according to an embodiment of the present application, including the steps of:

step S400, selecting at least one risk factor corresponding to the candidate vehicle based on the vehicle type of the candidate vehicle;

for example, if the type of the candidate vehicle is a dangerous chemical vehicle, the risk factors corresponding to the candidate vehicle are accidents, illegal, early warning times, driving ages, travel time rules, whether the candidate vehicle is scrapped or not, and dangerous article grades.

Step S401, determining risk values corresponding to all risk factors in at least one risk factor;

in one possible implementation manner, a rule for calculating a corresponding risk value is set for each risk factor, which is specifically as follows:

calculation rules corresponding to accident risk value S1: adding 1 minute to each accident, and dividing the maximum score into 2 minutes;

calculation rule corresponding to illegal risk value S2: each time of illegal addition is 0.5 point, the highest point is 2 points;

calculation rules corresponding to early warning times risk value S3: each time an early warning is added with 0.2, the maximum score is 2;

calculation rule corresponding to driving age risk value S4: the driving age is less than 3 years to obtain 1 score, and the driving age is more than or equal to 3 years to obtain 0 score;

calculation rule corresponding to travel time rule S5: the night (8:00-8:00 early) driving time exceeds 4 hours, or the day (8:00 early-8:00 late) driving time exceeds 6 hours, 1 score is obtained, otherwise 0 score is obtained;

whether the calculation rule corresponding to the scrapping risk value S6 is close to: the time of the adjacent scrapping is less than one year, and the score is 1;

calculation rule corresponding to vehicle hanging risk value S7: hanging to obtain 1 score;

calculation rule corresponding to dangerous goods grade risk value S8: the first grade is 1, the second grade is 0.75, the third grade is 0.5, and the fourth grade is 0.25.

Step S402, each determined risk value is composed into a risk value set;

if the risk factors in step S400 are accidents, violations, early warning times, driving ages, driving time rules, whether the risk factors are scrapped or not, and the risk values corresponding to the risk factors are determined in step S401, the risk values are formed into risk value sets S { S1, S2, S3, S4, S5, S6, S8}.

Step S403, inputting the risk value set into a trained cluster model, determining a risk level corresponding to the risk value set, and taking the risk level as risk information of traffic events of the candidate vehicles;

the clustering model is obtained after training by a clustering algorithm based on a historical risk value set of the historical vehicle;

in one possible implementation manner, the risk class is divided into three types of high, medium and low, in the process of performing cluster model training, setting N sample data, namely N historical risk value sets, setting 3 cluster points, randomly selecting 3 historical risk value sets from the N data as cluster centers, namely initializing the cluster centers, and generating lists center1, center2 and center3;

respectively distributing the rest N-3 sample data into a clustering center with similarity reaching a similarity threshold value, and calculating average error, wherein the similarity threshold value is determined based on Euclidean distance between the distributed sample data and the clustering center data;

Judging whether the distributed result is empty or not, if so, re-initializing a clustering center, if not, calculating the average value of all risk factors in each cluster, taking the average value of all risk factors as a new clustering center, then distributing again, and calculating an average error;

and judging whether the average error of the front and the rear times is larger than an error threshold value, if so, continuing to determine a new clustering center according to the average value of the risk factors, otherwise, ending and outputting three risk grades.

Referring to fig. 5, fig. 5 is a flowchart for exemplarily providing a method for training a cluster model in an embodiment of the present application, which specifically includes the following steps:

step S500, selecting N sample data and initializing 3 clustering centers;

step S501, distributing the rest sample data to clusters corresponding to the clustering centers with the data similarity reaching a similarity threshold value of the clustering center data respectively, and calculating average errors;

step S502, judging whether the distributed result is empty, if so, returning to step S500, otherwise, executing step S503;

step S503, updating a clustering center according to the average value of the risk factors in the sample data;

step S504, the distribution is carried out again, and the average error is calculated;

Step S505, judging whether the average error of the two times is larger than an error threshold value, if yes, returning to step S503, otherwise, executing step S506;

step S506, outputting the clustering centers of the three risk levels.

Mode two:

referring to fig. 6, fig. 6 is an exemplary flowchart for providing another risk information for determining a traffic event of a candidate vehicle according to an embodiment of the present application, including the following steps:

step S600, selecting at least one risk factor corresponding to the candidate vehicle based on the vehicle type of the candidate vehicle.

In step S601, a risk value corresponding to each risk factor in the at least one risk factor is determined.

Step S602, determining a risk early-warning value corresponding to the candidate vehicle based on each risk value and corresponding weight, and taking the risk early-warning value as risk information of traffic events of the candidate vehicle;

for example, if the type of the candidate vehicle is a dangerous chemical vehicle, the risk factors are accidents, illegal, early warning times, driving ages, running time rules, whether the candidate vehicle is scrapped or not, and the risk values corresponding to the risk factors are respectively S1, S2, S3, S4, S5, S6 and S8; the weights corresponding to the risk factors are w1, w2, w3, w4, w5, w6, w8, and w1+w2+w3+w4+w5+w6+w8=1;

The risk early-warning value y=s1×w1+s2×w2+s3×w3+s4×w4+s5×w5+s6×w6+s8×w8, and the determined risk early-warning value Y is used as risk information.

Step S304, performing early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.

Because risk information in the embodiment of the present application may be at least one of a risk level and a risk early warning value, the present application respectively provides a method for performing early warning treatment on a target object corresponding to attribute information of a candidate vehicle when the risk information is the risk level and the risk information is the risk early warning value:

mode one: for any candidate vehicle, determining an early warning treatment rule corresponding to the candidate vehicle according to the risk level corresponding to the candidate vehicle based on the corresponding relation between the risk level set in the risk early warning rule and the early warning treatment rule, and carrying out early warning treatment on a target object corresponding to attribute information of the candidate vehicle according to the early warning treatment rule through an event processing end;

for example, the low-level corresponding early warning treatment rule is set as a short message notice, the medium-level corresponding early warning treatment rule is a reading/visiting rule, and the high-level corresponding early warning treatment rule is a real-time checking and controlling rule, so that police resources can be saved.

Mode two: and screening candidate vehicles with risk early warning values reaching a first risk threshold value from the candidate vehicles according to the risk early warning values corresponding to the candidate vehicles based on screening rules set in the risk early warning rules, and carrying out early warning treatment on target objects corresponding to the attribute information of the screened candidate vehicles through an event processing end.

In this embodiment of the present application, the target object is at least one of a vehicle to be identified and an enterprise to which the vehicle to be identified belongs, if the target object is the vehicle to be identified, the vehicle to be identified is directly subjected to early warning treatment according to an early warning treatment rule, and if the target object is the enterprise to which the vehicle to be identified belongs, the enterprise to which the vehicle to be identified belongs is subjected to early warning treatment when it is determined that the following conditions are satisfied:

In the embodiment of the application, in the process of traffic event early warning, besides the traffic event early warning based on the relevant rules of the pass, the early warning types such as fatigue driving, red eye passenger car overspeed and the like are comprehensively determined whether the traffic event early warning is carried out on the target object corresponding to the attribute information of the candidate vehicle or not, so that the comprehensiveness and accuracy of the traffic event early warning are improved, and a complete management and control system is formed for managing and controlling the risk vehicles. Referring to fig. 7, fig. 7 is a schematic diagram illustrating a vehicle security risk early warning treatment in an embodiment of the present application;

As can be seen from fig. 7, the early warning treatment process includes a data analysis process, a real-time early warning process and an early warning treatment process;

data analysis process: analyzing the early warning type of the vehicle to be identified in real time, wherein the early warning type comprises the following steps: the method comprises the following steps of fatigue driving, red-eye passenger cars, running without passing through a route, running without passing through time, running without passing through an exclusion zone, handling pass, pass overdue, overspeed and the like, wherein the 5 types of running without passing through the route, running without passing through the time, running with passing through the exclusion zone, handling pass and pass overdue are related to the related rules of the pass, so the method is generally called as the related rule early warning of the pass.

Exemplary, the method for determining fatigue driving early warning is as follows:

public security traffic authorities specify according to the sixty-second seventh clause of the regulations of the law of road traffic safety: "driving a vehicle must have continuous driving of the vehicle for more than 4 hours with no rest or with a rest time of less than 20 minutes, can be a legal penalty for violating legal regulations. The scheme is based on the bayonet and the vehicle-mounted GPS data, the description of time-space rules of key vehicles is completed based on the advantage of good continuity of the vehicle-mounted GPS data, the advantage that a driver can be identified by combining with the bayonet snapshot is achieved, the judgment of whether a person is replaced in the middle of the vehicle is completed, and therefore the judgment of fatigue driving behaviors is achieved.

Referring to fig. 8, fig. 8 schematically provides a fatigue driving determination flow, which includes the following steps:

step S800, determining the starting time of the vehicle to be identified, judging whether the vehicle is stopped or not based on the real-time speed and longitude and latitude continuously acquired by the vehicle-mounted GPS data, and determining the stopping time when the vehicle to be identified is determined to be stopped;

step S801 of determining a running time of a vehicle to be identified based on the start time and the stop time;

step S802, judging whether the running time is greater than 4 hours, if so, executing step S808, otherwise, executing step S803;

step S803, determining a driver rest time based on a start time and a previous stop time of the vehicle to be identified for restarting;

step S804, judging whether the rest time of the driver is more than 20 minutes, if so, executing step S805, otherwise, executing step S806;

step S805, zeroing the running time of the vehicle to be identified;

step S806, acquiring two-time bayonet data closest to the starting time of restarting the vehicle to be identified;

step S807, judging whether the driver is the same person according to the bayonet data, if so, executing step S808, otherwise, executing step S805;

Step S808, fatigue driving early warning is carried out.

Exemplary, a method for determining a red eye passenger car early warning is as follows:

according to the forbidden rule, "the passenger car is not allowed to run from 2 hours to 5 hours in the early morning, and the passenger car driver has to rest in a parking service area from 2 to 5 points at night".

And based on the fusion judgment of the vehicle-mounted GPS data and the bayonet data, early warning is carried out when one of the vehicle-mounted GPS data and the bayonet data detects the vehicle running data.

Wherein, based on the vehicle-mounted GPS data, one is that the vehicle speed value exists in N continuous detection periods, and N defaults to 3; the other mode is that the longitude and latitude are changed in N continuous detection periods, N is 3 by default, and red eye passenger car early warning is carried out when at least one of the two conditions is met; based on the bayonet data, when the passenger car is captured in the early morning from 2 hours to 5 hours, red eye passenger car early warning is carried out. Referring to fig. 9, fig. 9 is a flowchart illustrating a method for determining a red eye passenger car according to an embodiment of the present application.

Exemplary, the method for determining overspeed early warning is as follows:

when the speed limit value of the road section exists, the special speed limit standard of the road section is adopted; when no specific speed limit exists, the speed is 60km/h according to the urban road, the speed is 80km/h, and the speed is 120km/h.

Based on vehicle-mounted GPS data, calculating average speed in N continuous periods, and carrying out early warning when the average speed overspeed value is 10% greater than the speed threshold value, wherein N is 3 by default. The average speed is 10% lower than the overspeed standard for N consecutive periods, N defaults to 3 periods, assuming the alarm is eliminated. When continuous overspeed behavior exists, the continuous alarm sets an alarm interval, so that continuous and continuous alarm of the system is avoided, judgment of police officers is affected, and the interval standard defaults to 10 minutes.

Based on equipment such as a bayonet, when the overspeed behavior is captured, whether the vehicle type is the important vehicle type or not is judged based on secondary identification, and overspeed early warning is carried out if the vehicle type is the important vehicle.

Illustratively, the method for judging the relevant rule pre-warning for the pass comprises the following steps:

the illegal behavior related to the pass comprises unqualified pass early warning, pass overdue early warning, no pass line running early warning, no pass period running early warning and forbidden zone running early warning.

Referring to fig. 10, fig. 10 is a flowchart for exemplarily providing a method for determining a relevant rule pre-warning for a pass according to an embodiment of the present application, including the following steps:

step S1000, based on the identification information of the vehicle to be identified, obtaining the pass information of the vehicle to be identified in the pass management system.

Step S1001, based on the pass information, it is determined whether the to-be-identified vehicle has transacted a pass in the current jurisdiction, if so, step S1003 is performed, otherwise step S1002 is performed.

Step S1002, performing an early warning of the non-handling pass.

Step S1003, determining whether the transacted pass is overdue, if yes, executing step S1004, otherwise executing step S1005.

Step S1004, carrying out pass overdue early warning.

Step S1005, determining a driving behavior of the vehicle to be identified based on the vehicle-mounted GPS data reported by the vehicle-mounted device mounted on the vehicle to be identified and the bayonet data reported by the bayonet device.

Step S1006, judging whether the specific running rule corresponding to the processed pass is stored in the pass management system, if yes, executing step S1007, otherwise executing step S1009.

Step S1007, based on the running behavior of the vehicle to be identified, judging whether the vehicle to be identified runs according to the specific running rule, if so, executing step S1011, otherwise, executing step S1008;

step S1008, performing early warning that the vehicle does not run according to a specific running rule;

in one possible implementation manner, when judging whether the vehicle to be identified runs according to a specific running rule based on the running behavior of the vehicle to be identified, setting a specific running time period and a specific running road section in the specific running rule; referring to fig. 11, fig. 11 is a flowchart for exemplarily providing a method for determining a driving early warning for a specific driving rule according to an embodiment of the present application, including the following steps:

step S1100, determining the driving behavior of the vehicle to be identified based on the vehicle-mounted GPS data reported by the vehicle-mounted equipment mounted on the vehicle to be identified and the bayonet data reported by the bayonet equipment;

Step S1101, based on the driving behavior of the vehicle to be identified, determining whether the vehicle to be identified is driving according to a specific driving time period in a specific driving rule, if yes, executing step S1102, otherwise executing step S1103;

step S1102, based on the driving behavior of the vehicle to be identified, determining whether the vehicle to be identified is driving according to a specific driving road section in a specific driving rule, if so, executing step S1104, otherwise, executing step S1105;

step S1103, performing a travel warning for a prescribed period of time without a pass;

step S1104, the pass verification is finished;

step S1105, performing travel warning on a road section not in accordance with the pass.

Step S1009, based on the driving behavior of the vehicle to be identified, determining whether the vehicle to be identified is driving according to the road segment management rules stored in the pass management system, if yes, executing step S1011, otherwise executing step 1010;

step S1010, performing early warning of running without the rule of road section management;

in one possible implementation manner, after determining that a specific running rule corresponding to a pass is stored, judging whether the vehicle to be identified runs according to a road section management rule, wherein the road section management rule refers to a space-time range running rule regulated according to key vehicle management, and a forbidden time period and a forbidden road period are regulated in the running rule; referring to fig. 12, fig. 12 is a flowchart for exemplarily providing a method for driving early warning determination for a road segment management rule according to an embodiment of the present application, including the following steps:

Step S1200, determining the driving behavior of the vehicle to be identified based on the vehicle-mounted GPS data reported by the vehicle-mounted equipment mounted on the vehicle to be identified and the bayonet data reported by the bayonet equipment;

step S1201, based on the driving behavior of the vehicle to be identified, determining whether the vehicle to be identified is driving in the restricted road segment of the road segment management rule, if so, executing step S1202, otherwise, executing step S1203;

step S1202, performing forbidden zone running and line violation early warning;

step S1203, based on the driving behavior of the vehicle to be identified, determining whether the vehicle to be identified is driving in the forbidden time period of the road section management rule, if yes, executing step S1204, otherwise executing step S1205;

step S1204, performing forbidden zone running and time violation early warning;

step S1205, the pass verification ends.

Step S1011 ends.

Real-time early warning process: and (3) according to the parameters of the early warning 'receiving range' (whole city, large team district, bayonet), 'vehicle type' (dangerous chemical vehicle, highway passenger transport, tourist bus and dregs vehicle), 'early warning type' (traveling without passing line, traveling without passing time period, fatigue driving and the like), early warning risk behavior in real time. Meanwhile, a vehicle risk grade is given for the early warning vehicle, and a disposal means is given for the auxiliary traffic police.

Early warning treatment process: for early warning, there are three optional treatments:

on-site checking and controlling, intercepting, checking and dealing with early-warning illegal behaviors by surrounding polices, and opening punishment decision books according to specific conditions;

and (3) source management: the early-warning vehicle information is included in a shoveling list, and a high-risk enterprise list is formed by combining data such as illegal and accident data for shoveling and visiting;

and (3) short message notification, namely, quickly completing the editing and sending of the short message content according to a short message template for the contact of the telephone of the driver.

The GPS and the bayonet data of the key vehicles are fused, various risks of the key vehicles are comprehensively considered, comprehensiveness and accuracy of multi-class safety risk early warning of the key vehicles are improved, and a complete management system is formed for management and control of the risk vehicles. And when police resources are limited, the method can assist traffic police to formulate a treatment mode according to the vehicle risk level, and can carry out classification and grading treatment means such as real-time checking control, short message notification, shoveling and the like on the early-warning vehicles, so that the main road traffic potential safety hazards caused by key vehicles are reduced.

Based on the same inventive concept, the embodiment of the present application further provides a traffic event early warning device 1300, referring to fig. 13, fig. 13 exemplarily provides a traffic event early warning device 1300 in the embodiment of the present application, where the device includes:

An obtaining module 1301, configured to obtain, for any vehicle to be identified, pass information of the vehicle to be identified in a pass management system based on identification information of the vehicle to be identified;

a first determining module 1302, configured to determine, based on the pass information, that a vehicle to be identified has transacted a pass in a current jurisdiction, and after the transacted pass is not overdue, determine a driving behavior of the vehicle to be identified based on vehicle-mounted GPS data reported by a vehicle-mounted device mounted on the vehicle to be identified and bayonet data reported by a bayonet device, where the driving behavior is used to characterize a driving state of the vehicle to be identified in a current time period and a current road section;

the second determining module 1303 is configured to determine, based on the driving behavior, that the vehicle to be identified is a candidate vehicle that allows traffic event early warning when the vehicle to be identified is not driving according to the rule related to the pass, and record attribute information of the candidate vehicle;

a third determining module 1304, configured to determine risk information of traffic events occurring in each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle when the number of candidate vehicles reaches the number threshold in the same time period, where the risk factor is used to characterize a factor that causes the traffic event to occur in the vehicle to be identified;

And the early warning module 1305 is used for carrying out early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.

In one possible implementation, the first determining module 1302 is further configured to:

In one possible implementation manner, the obtaining module 1301 is further configured to, for any vehicle to be identified, before obtaining the pass information of the vehicle to be identified in the pass management system based on the identification information of the vehicle to be identified:

In one possible implementation, the second determining module 1303 is specifically configured to:

In one possible implementation, the third determining module 1304 is specifically configured to:

In one possible implementation, the early warning module 1305 is specifically configured to:

In one possible implementation, if the target object includes a belonging business of the candidate vehicle, the early warning module 1305 performs early warning treatment on the belonging business when the following conditions are satisfied:

and carrying out weighted average on the obtained target risk early-warning values, determining an enterprise risk early-warning value corresponding to the enterprise, and carrying out early-warning treatment on the enterprise to which the event processing end belongs when the enterprise risk early-warning value reaches a second risk threshold.

In some possible embodiments, aspects of the traffic event early warning method provided herein may also be implemented in the form of a program product comprising program code for causing a computer device to carry out the steps of the traffic event early warning method according to the various exemplary embodiments of the present application as described herein above, when the program product is run on the computer device.

The program product may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having each or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The program product of the short message transmission control of the embodiments of the present application may employ a portable compact disc read only memory (CD-ROM) and include program code and may run on a computing device.

The readable signal medium may comprise a data signal propagated in baseband or as a carrier wave sub-model in which the readable program code is embodied. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with a command execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

It should be noted that although several units or sub-units of the apparatus are mentioned in the above detailed description, such a division is merely exemplary and not mandatory. Indeed, according to embodiments of the present application, the feature vectors and functions of two or more units described above may be embodied in each unit. Conversely, the feature vectors and functions of each unit described above may be further divided into units for materialization.

Furthermore, although the operations of the methods of the present application are depicted in the drawings in a particular order, this is not required to or suggested that these operations must be performed in this particular order or that all of the illustrated operations must be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into each step performed, and/or each step decomposed into multiple steps performed.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.

Claims

1. A method of traffic event early warning, the method comprising:

for any vehicle to be identified, acquiring the pass information of the vehicle to be identified in a pass management system based on the identification information of the vehicle to be identified;

determining that the vehicle to be identified has transacted a pass in a current jurisdiction based on the pass information, and determining the running behavior of the vehicle to be identified based on vehicle-mounted Global Positioning System (GPS) data reported by vehicle-mounted equipment installed on the vehicle to be identified and bayonet data reported by bayonet equipment after the transacted pass is not overdue, wherein the running behavior is used for representing the running state of the vehicle to be identified in a current time period and a current road section;

based on the driving behavior, when the vehicle to be identified does not drive according to the relevant rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded;

Determining risk information of traffic events of each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle when the number of the candidate vehicles reaches a number threshold value in the same time period, wherein the risk factors are used for representing factors of the traffic events of the vehicles to be identified;

and carrying out early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.

2. The method of claim 1, wherein after the obtaining of the pass information of the vehicle to be identified in the pass management system, further comprises:

and if the to-be-identified vehicle does not transact the pass in the current jurisdiction area based on the pass information, taking the to-be-identified vehicle as a candidate vehicle allowing traffic event early warning, and recording attribute information of the candidate vehicle.

3. The method of claim 1, wherein for any vehicle to be identified, based on identification information of the vehicle to be identified, prior to obtaining the pass information of the vehicle to be identified in a pass management system, further comprising:

Based on image information in the bayonet data reported by the bayonet equipment, determining that the image information contains an important vehicle, and taking the important vehicle as the vehicle to be identified; and/or

wherein, the key vehicle comprises one or a combination of a hazardous chemical substance vehicle and a residue soil vehicle.

4. The method of claim 1, wherein the determining that the vehicle to be identified is not traveling according to the pass-related rule based on the traveling behavior comprises:

if the specific running rule corresponding to the processed pass is stored in the pass management system, when the fact that the current time period corresponding to the running behavior is not matched with the specific running time period corresponding to the specific running rule and/or the fact that the current road section corresponding to the running behavior is not matched with the specific running road section corresponding to the specific running rule is determined, the fact that the vehicle to be identified does not run according to the pass related rule is determined;

If the specific running rule corresponding to the processed pass is not stored in the pass management system, determining that the current time period corresponding to the running behavior is matched with the forbidden time period in the road section management rule based on the road section management rule stored in the pass management system, and/or determining that the vehicle to be identified does not run according to the pass related rule when the current road section corresponding to the running behavior is determined to be matched with the forbidden road section in the road section management rule.

5. The method of claim 1, wherein the determining risk information for each of the candidate vehicles for the occurrence of a traffic event based on at least one risk factor for each of the candidate vehicles comprises:

for any candidate vehicle, determining at least one risk factor matched with the candidate vehicle according to the vehicle type identification of the candidate vehicle, and determining a risk value set formed based on risk values corresponding to all the at least one risk factor;

and determining a risk level corresponding to the risk value set based on a trained cluster model, and taking the risk level as risk information of traffic events of the candidate vehicles, wherein the cluster model is obtained after training by a clustering algorithm based on a historical risk value set of the historical candidate vehicles.

6. The method of claim 1, wherein determining risk information for each of the candidate vehicles for the occurrence of a traffic event based on at least one risk factor for each of the candidate vehicles, comprises:

for any candidate vehicle, determining at least one risk factor matched with the candidate vehicle according to the vehicle type identifier of the candidate vehicle, and determining a risk value corresponding to each risk factor in the at least one risk factor;

and determining a risk early warning value corresponding to the candidate vehicle based on each risk value and the corresponding weight, and taking the risk early warning value as risk information of traffic events of the candidate vehicle.

7. The method according to claim 5, wherein the performing early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule includes:

for any candidate vehicle, determining an early warning treatment rule corresponding to the candidate vehicle according to the risk grade corresponding to the candidate vehicle based on the corresponding relation between the risk grade set in the risk early warning rule and the early warning treatment rule, and carrying out early warning treatment on a target object corresponding to the attribute information of the candidate vehicle according to the early warning treatment rule through an event processing end.

8. The method of claim 6, wherein the performing early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and a risk early warning rule comprises:

9. The method according to any one of claims 1 to 8, wherein if the target object comprises a affiliated business of the candidate vehicle, the affiliated business is subjected to a pre-warning treatment when the following condition is satisfied:

and carrying out weighted average on the obtained target risk early-warning values, determining an enterprise risk early-warning value corresponding to the affiliated enterprise, and carrying out early-warning treatment on the affiliated enterprise through an event processing end when the enterprise risk early-warning value reaches a second risk threshold.

10. An apparatus for traffic event early warning, the apparatus comprising at least: a communication interface and a processor, wherein:

the processor is used for acquiring the pass information of any vehicle to be identified in the communication card management system based on the identification information of the vehicle to be identified; determining that the vehicle to be identified has transacted a pass in the current jurisdiction range based on the pass information, and determining the running behavior of the vehicle to be identified based on vehicle-mounted GPS data reported by vehicle-mounted equipment installed on the vehicle to be identified and bayonet data reported by bayonet equipment after the transacted pass is not overdue, wherein the running behavior is used for representing the running state of the vehicle to be identified in the current time period and the current road section; based on the driving behavior, when the vehicle to be identified does not drive according to the relevant rule of the pass, the vehicle to be identified is used as a candidate vehicle allowing traffic event early warning, and attribute information of the candidate vehicle is recorded; determining risk information of traffic events of each candidate vehicle based on at least one risk factor corresponding to each candidate vehicle when the number of the candidate vehicles reaches a number threshold value in the same time period, wherein the risk factors are used for representing factors of the traffic events of the vehicles to be identified; and carrying out early warning treatment on the target object corresponding to the attribute information of the candidate vehicle based on the risk information corresponding to each candidate vehicle and the risk early warning rule.