CN110164130B - Traffic incident detection method, device, equipment and storage medium - Google Patents
Traffic incident detection method, device, equipment and storage medium Download PDFInfo
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- CN110164130B CN110164130B CN201910356424.4A CN201910356424A CN110164130B CN 110164130 B CN110164130 B CN 110164130B CN 201910356424 A CN201910356424 A CN 201910356424A CN 110164130 B CN110164130 B CN 110164130B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
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Abstract
The application discloses a traffic incident detection method, a device, equipment and a storage medium, which comprises the steps of defining a detection area on a current road, acquiring road structure data and traffic flow data in the detection area, acquiring running data of each vehicle in the detection area, carrying out statistical analysis on the running data to obtain corresponding running characteristics of each vehicle, detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of each vehicle, so as to detect the driving characteristics of the vehicles in the detection area, the traffic flow driving behavior of the detection area is subjected to big data analysis, so that traffic events influencing vehicle passing can be quickly and accurately detected, a traffic flow or a vehicle speed detector does not need to be installed by breaking a road, high-density detection equipment does not need to be configured, and the investment cost of highway traffic event detection is reduced.
Description
Technical Field
The present application relates to the field of traffic informatization, and in particular, to a method, an apparatus, a device, and a storage medium for detecting a traffic incident.
Background
China has become a country with the highest motor vehicle holding amount and the longest highway mileage in the world, frequent traffic safety accidents bring huge loss to lives and properties of people, and because traffic events such as sudden mass fog and the like cannot be accurately detected and early warned, serious casualty accidents are frequently reported.
The traffic events are divided into planned events and emergent events, and the planned events influencing the motor vehicle traffic can be known through reports of a planning department, and necessary early warning measures are taken to reduce the accident occurrence probability. For the emergency that affects the vehicle traffic, there are the following detection methods: the first is road surface or roadside sensor detection, which is to install a sensing coil, a camera or an intelligent spike on a road, monitor the traffic flow of the road in real time, find traffic events influencing vehicle traffic through abnormal conditions such as sudden reduction of the traffic flow and the like, but need to break the road or closely arrange a proper sensor in a detection area; the second is traffic participant sharing or reporting, and today the mobile internet is widely used, traffic participants passing through an event place are usually willing to share or report the found traffic event, and the method depends on the active reporting of the traffic participants; the third is a detection method based on sampling vehicles (floating vehicles), namely, the travel time of a certain proportion of floating vehicles on a certain road section is counted and compared with the historical travel time, if obvious change is found, the traffic incident influencing traffic can be judged to exist, but the method depends on the floating vehicles provided with vehicle-mounted positioning terminals, and for road traffic, the shortage of the number of the floating vehicles can cause the extension of the incident detection time, so that the reliability of the detected traffic incident is reduced.
Therefore, how to quickly and accurately detect the traffic incident without investing a large amount of detection cost is a technical problem which needs to be solved urgently in the field.
Disclosure of Invention
The application aims to provide a traffic incident detection method, a device, equipment and a storage medium, so that a traffic incident can be detected quickly and accurately.
In a first aspect, an embodiment of the present application provides a traffic event detection method, including:
defining a detection area on a current road;
acquiring road structure data and traffic flow data in the detection area;
acquiring running data of each vehicle in the detection area, wherein the running data comprises running speed and acceleration at each moment;
carrying out statistical analysis on the driving data to obtain driving characteristics corresponding to each vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time;
and detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of each vehicle.
In a possible implementation manner, in the method provided by the embodiment of the present application, the road structure data includes positions of element locations in the detection area, where the element locations include intersections, ramps, tunnels, bridges, speed-limiting areas, overspeed monitoring points, and tight turning sections; the traffic flow data comprises the traffic flow in the uplink direction and the traffic flow in the downlink direction of different driving sections at different moments in the detection area.
In one possible implementation manner, in the foregoing method provided by the embodiment of the present application, the traffic event includes a single point traffic event and a regional traffic event;
the detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of each vehicle comprises the following steps:
according to the road structure data, carrying out statistical analysis on the driving characteristics of each vehicle in the uplink direction or the downlink direction in the detection area to obtain the driving characteristic analysis result of each vehicle, wherein the analysis result comprises a spatial clustering result and a time distribution result;
according to the analysis result and the traffic flow data, calculating the ratio of the number of vehicles of the continuously low-speed running vehicles after the speed reduction in the uplink direction or the downlink direction to the traffic flow of different running sections;
if the ratio is larger than a preset ratio threshold, a single-point traffic event exists in the uplink direction or the downlink direction corresponding to the driving section;
and carrying out statistical analysis on the single-point traffic events appearing in the detection area, wherein if a plurality of single-point traffic events of the same type appear in a plurality of adjacent driving sections in a preset time period, regional traffic events exist in the plurality of driving sections.
In a possible implementation manner, in the foregoing method provided in an embodiment of the present application, the method further includes:
and if the traffic incident exists in the detection area, sending a prompt message to a roadside variable information board at the upstream of the detection area, wherein the prompt message is used for reminding an upstream vehicle to decelerate.
In a second aspect, an embodiment of the present application provides a traffic event detection device, including:
the marking module is used for marking a detection area on the current road;
the acquisition module is used for acquiring road structure data and traffic flow data in the detection area; acquiring running data of each vehicle in the detection area, wherein the running data comprises running speed and acceleration at each moment;
the analysis module is used for inputting the running data into a preset vehicle running characteristic analysis model for statistical analysis to obtain running characteristics corresponding to each vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time;
and the detection module is used for detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of all vehicles.
In a possible implementation manner, in the apparatus provided in this embodiment of the present application, the road structure data includes positions of element locations having speed limit requirements in the detection area, where the element locations include intersections, ramps, tunnels, bridges, speed limit areas, overspeed monitoring points, and sharp turn sections; the traffic flow data comprises the traffic flow in the uplink direction and the traffic flow in the downlink direction of different driving sections at different moments in the detection area.
In a possible implementation manner, in the above apparatus provided by the embodiment of the present application, the traffic event includes a single point traffic event and a regional traffic event;
the detection module comprises:
the analysis unit is used for carrying out statistical analysis on the driving characteristics of each vehicle in the uplink direction or the downlink direction in the detection area according to the road structure data to obtain the driving characteristic analysis result of each vehicle, and the analysis result comprises a spatial clustering result and a time distribution result;
the single-point detection unit is used for calculating the ratio of the number of vehicles of the continuously low-speed running vehicles after being decelerated in the uplink direction or the downlink direction to the traffic flow of different running sections according to the analysis result and the traffic flow data; if the ratio is larger than a preset ratio threshold, a single-point traffic event exists in the uplink direction or the downlink direction corresponding to the driving section;
the area detection unit is used for carrying out statistical analysis on the single-point traffic events appearing in the detection area, and if a plurality of single-point traffic events of the same type appear in a plurality of adjacent driving sections in a preset time period, regional traffic events exist in the plurality of driving sections.
In a possible implementation manner, in the foregoing apparatus provided in this embodiment of the present application, the apparatus further includes:
and the prompting module is used for sending a prompting message to a roadside variable information board at the upstream of the detection area if a traffic event exists in the detection area, wherein the prompting message is used for prompting the upstream vehicle to decelerate.
In a third aspect, an embodiment of the present application provides an electronic device, including: a memory and a processor;
the memory for storing a computer program;
wherein the processor executes the computer program in the memory to implement the method described in the first aspect and the various embodiments of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, in which a computer program is stored, and the computer program is used for implementing the method described in the first aspect and the implementation manners of the first aspect when executed by a processor.
Compared with the prior art, the traffic incident detection method, the device, the equipment and the storage medium provided by the application have the advantages that a detection area is defined on a current road, road structure data and traffic flow data in the detection area are obtained, driving data of each vehicle in the detection area are obtained, the driving data comprise driving speed and acceleration at each moment, and the driving data are subjected to statistical analysis to obtain driving characteristics corresponding to each vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time, whether a traffic incident exists in the detection area is detected according to the road structure data, the traffic flow data and the driving characteristics of all vehicles, and therefore large data analysis is carried out on the traffic flow driving behavior in the detection area on the basis of the driving characteristics of the vehicles in the detection area, the traffic incident influencing the vehicle passing is rapidly and accurately detected, a traffic flow or vehicle speed detector does not need to be installed by breaking the road, high-density configuration of detection equipment is not needed, and the investment cost of detecting the road traffic incident is reduced.
Drawings
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating a traffic incident detection method according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart of step S105 according to a first embodiment of the present application;
fig. 4 is a schematic structural diagram of a traffic event detection device according to a second embodiment of the present application;
fig. 5 is a schematic structural diagram of a detection module according to a second embodiment of the present application;
fig. 6 is a first schematic diagram of a server function configuration provided in an embodiment of the present application;
fig. 7 is a schematic diagram of a server function configuration provided in the embodiment of the present application;
fig. 8 is a schematic structural diagram of an electronic device according to a third embodiment of the present application.
Detailed Description
The following detailed description of embodiments of the present application is provided in conjunction with the accompanying drawings, but it should be understood that the scope of the present application is not limited to the specific embodiments.
Throughout the specification and claims, unless explicitly stated otherwise, the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated element or component but not the exclusion of any other element or component.
With the popularization of the mobile internet, the rapid development of the automobile intelligent internet technology and the automobile automatic driving technology and the development of the cloud computing technology, the running data of a large number of vehicles in a large range can be collected and analyzed in the same event, and therefore the possibility is provided for the rapid and accurate detection of traffic events influencing the vehicle passing.
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present application. As shown in the figure, the vehicle system comprises a server 200, roadside units 110 and 120, and vehicles in the uplink direction and the downlink direction, wherein the vehicles 1 and 2 in the uplink direction and the vehicles 3 and 4 in the downlink direction are intelligent networked vehicles (such as autonomous vehicles) and can be in communication connection with the roadside units or the server. The server may be deployed in the cloud, or may be deployed in a machine room of the detection area, or even on a roadside unit installed on a traffic section, that is, the server 200 may be installed on the roadside unit 110 or 120. The traffic section is a cross section of a road perpendicular to the traffic direction.
Currently, intelligent internet vehicles are gradually popularized, and the intelligent internet vehicles report driving data such as their running states, such as positions and current speeds, to a unified background server at a relatively high frequency. Based on the driving data reported by the intelligent networked vehicles, the following embodiments are provided in the application.
Fig. 2 is a schematic flow chart of the traffic event detection method according to an embodiment of the present disclosure, in practical application, the execution main body of the embodiment may be a traffic event detection device, and the traffic event detection device may be implemented by a virtual device, such as a software code, or an entity device written with a relevant execution code, such as a usb disk, or may be implemented by an entity device integrated with a relevant execution code, such as a chip, various computers, a server, and the like. The present embodiment will be described below with reference to a server as an execution subject.
As shown in fig. 2, the method provided by the present embodiment includes the following steps S101 to S105:
s101, defining a detection area on the current road.
In this embodiment, a detection area may be defined on a high-level highway such as an expressway, a first-level road, and the like, and the detection area may include a plurality of driving directions, and the plurality of driving directions may be divided into an uplink direction and a downlink direction. A plurality of traffic sections for detection are also arranged at intervals in the detection area, as shown in fig. 1.
And S102, acquiring road structure data and traffic flow data in the detection area.
The road structure data comprises the positions of element sites in the detection area, wherein the element sites comprise intersections, ramps, tunnels, bridges, speed-limiting areas, overspeed monitoring points, sharp turning road sections and other element sites with speed-limiting requirements. The traffic flow data includes the traffic flow in the up direction and the down direction of different sections at each time in the detection area.
In this embodiment, after the detection area is defined on the current road, the road structure data of the detection area may be acquired based on the existing satellite positioning system, or the road structure data of the detection area may be obtained based on the conversion of the design file of the road, which includes calibrating the positions with special speed-limiting requirements, such as an intersection, a ramp, a tunnel, a bridge, a speed-limiting area, an overspeed monitoring point, and a sharp turn road section, for example, X is used for calibrating the positions with special speed-limiting requirementsL＝{X1,X2,X3… } in which X isnThe position of each calibration point on the detection area can be represented by stake numbers or longitude and latitude coordinates, and all position data is stored in the server. Meanwhile, the motor vehicle flow statistical data of different driving sections in the detection area can be obtained, in practical application, the motor vehicle flow statistical data of different driving sections in the detection area can be obtained from a road operation unit, a maintenance unit or vehicle flow detection equipment installed on a road, and the motor vehicle flow statistical data of different driving sections in the detection area can be recordedIs Q ═ Q1,u(t)，Q1,d(t)，Q2,u(t)，Q2,d(t), … }, wherein Qi,u(t) represents the traffic flow at t in the upward direction of the ith traffic section, Qi,d(t) represents the traffic flow rate at t in the i-th cross-section downward direction.
S103, acquiring running data of each vehicle in the detection area, wherein the running data comprises running speed and acceleration at each moment.
In this embodiment, the driving data of each vehicle in the detection area is also obtained, and the driving data may be the control data of the vehicle under the condition that the driver of the vehicle operates the vehicle (such as braking, decelerating, stepping on the accelerator, and accelerating), or the vehicle is automatically driven. Specifically, the running speed, deceleration or acceleration information of the vehicle may be collected and summarized based on an in-vehicle sensor and an intelligent networking technology, for example, the vehicle-mounted intelligent networking device may be connected to a vehicle CAN bus or a vehicle-mounted detection device of an autonomous vehicle may be used to collect basic data such as the running speed, acceleration, and the like of the vehicle.
S104, carrying out statistical analysis on the driving data to obtain driving characteristics corresponding to each vehicle; the driving characteristics include a deceleration position, a deceleration time, an acceleration during deceleration, a duration of continuous low-speed driving after deceleration, and a continuous acceleration time.
In this embodiment, in order to improve the statistical speed, a vehicle driving characteristic analysis model may be constructed in advance, and the server runs the vehicle driving characteristic analysis model that is established in advance, evaluates the behavior of a single vehicle in the detection area, and primarily determines the driving characteristics of the vehicle by checking the deceleration position of the decelerated vehicle, calculating the deceleration rate (acceleration), integrating the duration of low-speed driving after deceleration, and the like, so that the driving characteristics may include the deceleration position, the deceleration time, the acceleration during deceleration, the duration of low-speed driving after deceleration, and the duration of acceleration. Specifically, the vehicle running characteristic analysis model extracts acceleration data of each vehicle on the basis of the vehicle running speed, and performs statistical analysis on the time sequence of the vehicle running data to obtain the deceleration position X, the deceleration time T, the acceleration a during deceleration and continuous low-speed running after deceleration of the vehicleDriving time t1And duration acceleration time t2And the like.
And S105, detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of each vehicle.
In this embodiment, the traffic events may include single point traffic events and regional traffic events. Accordingly, as shown in fig. 3, the step S105 may include the steps of:
s301, according to the road structure data, carrying out statistical analysis on the driving characteristics of each vehicle in the uplink direction or the downlink direction in the detection area to obtain the driving characteristic analysis result of each vehicle, wherein the analysis result comprises a spatial clustering result and a time distribution result.
The spatial clustering result refers to the correlation of the driving characteristics of each vehicle on the spatial position, such as the correlation of the deceleration position X. The time distribution result refers to the correlation of the running characteristics of each vehicle in time, such as the correlation of the deceleration time T, the similarity of the continuous running time T1 after deceleration, and the like.
S302, calculating the ratio of the number of vehicles of the continuously low-speed running vehicles after the speed reduction in the uplink direction or the downlink direction to the traffic flow of different running sections according to the analysis result and the traffic flow data.
And S303, if the ratio is greater than a preset ratio threshold, a single-point traffic event exists in the uplink direction or the downlink direction of the corresponding driving section.
S304, carrying out statistical analysis on the single-point traffic events appearing in the detection area, wherein if a plurality of single-point traffic events of the same type appear in a plurality of adjacent driving sections in a preset time period, regional traffic events exist in the plurality of driving sections.
In practical application, a single-point traffic event early warning model can be established in advance, the single-point traffic event early warning model is operated on a server, and the driving characteristics of each vehicle in the uplink direction or the downlink direction in the detection area are analyzed by adopting methods such as spatial clustering analysis and time distribution analysis according to road structure data (the step (b) (Such as big data analysis) to obtain spatial clustering results and temporal distribution results to classify each vehicle. Analysis is performed in conjunction with road configuration data, e.g. vehicle deceleration occurs at XLAnd if the vehicle is in the position, further judging whether the vehicle is in normal deceleration or not by combining the normal driving rule of the vehicle at the special points, if so, indicating that no traffic event exists, and if not, further analyzing.
In this embodiment, further analysis is performed based on the analysis result and the traffic flow data. The analysis process includes the following cases: the first condition is that the traffic flow passing through a certain driving section is small, if the similarity degree of the driving characteristics of a certain proportion of the vehicles is high (such as the correlation of deceleration time T, deceleration rate a, the similarity of continuous driving time T1 after deceleration and the like), the occurrence of a single-point traffic event in the driving section can be analyzed; the second condition is that the traffic flow passing through a certain traffic section is large, if a certain proportion of the traffic characteristics are detected to have higher similarity within a period of time (such as within 1 minute), the traffic section can be analyzed to have a single-point traffic event; the third situation is that if the running characteristics of the intelligent networked vehicles and the automatic driving vehicles exceeding a certain proportion in the defined detection area are high in similarity, a single-point traffic event can be analyzed to occur on a certain driving section. Therefore, the ratio of the number of vehicles continuously running at low speed after being decelerated in the ascending direction or the descending direction in the detection area to the traffic flow of different driving sections can be calculated, and if the ratio is larger than a preset ratio threshold (such as 60%), the condition that a single-point traffic event exists in the ascending direction or the descending direction of the corresponding driving section can be analyzed. The analyzed single-point traffic event can be verified by other existing technical means, such as monitoring videos of the adjacent event occurrence places, the traffic section flow and the traffic flow speed monitored by the flow detection equipment, and the like.
In this embodiment, after a plurality of single point traffic events occur in the detection area, whether regional traffic events exist may be further analyzed. Specifically, a regional traffic event early warning model may be established, and a spatial correlation analysis method is used to perform comprehensive analysis on single-point traffic events occurring in an uplink direction or a downlink direction in a detection region to obtain a spatial correlation relationship of each single-point traffic event, for example, if a plurality of adjacent driving sections within a preset range have a plurality of single-point traffic events of the same type within a preset time period, a regional traffic event may exist at the corresponding plurality of driving sections, the preset range may be within a range of 1 km or within a range of 3 km, the preset time period may be within a range of 10 minutes or within a range of 30 minutes, which is specifically set according to an actual situation, and the regional traffic events such as sudden mass fog, large-area road icing, large-area traffic accidents, and the like. The analyzed regional communication event can be verified by other prior art means, such as surveillance videos of nearby event occurrence sites, information provided by road maintenance patrollers, social public, and the like.
For example, the following steps are carried out: if the starting deceleration position of the vehicles on the ascending road section on the road with the same number is close to the starting acceleration position of the vehicles on the descending road section in space, the starting acceleration position of the vehicles on the ascending road section is close to the starting deceleration position of the vehicles on the descending road section, and the interval between the starting acceleration position and the starting deceleration position is 1 kilometer, the regional traffic incident affecting the two-way traffic on the road can be warned. In practical application, planned maintenance events can be eliminated by combining with a maintenance plan, water damage events can be discriminated by combining with traffic meteorological information, and if common two-way traffic influence events can be eliminated by combining with a large amount of data, the events such as sudden fog can be pre-warned.
Optionally, on the basis of the foregoing embodiment, the foregoing method may further include:
and if the traffic incident exists in the detection area, sending a prompt message to a roadside variable information board at the upstream of the detection area, wherein the prompt message is used for reminding an upstream vehicle to decelerate.
The traffic incident detection method provided by this embodiment includes defining a detection area on a current road, acquiring road structure data and traffic flow data in the detection area, acquiring running data of each internet vehicle in the detection area, where the running data includes running speed and acceleration at each time, and performing statistical analysis on the running data to obtain running characteristics corresponding to each internet vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time, and whether a traffic event exists in the detection area is detected according to the road structure data, the traffic flow data and the driving characteristics of all the networked vehicles, so that the traffic flow driving behavior in the detection area is subjected to big data analysis on the basis of the driving characteristics of the networked vehicles in the detection area, the traffic event influencing the vehicle traffic is rapidly and accurately detected, a traffic flow or vehicle speed detector does not need to be installed by breaking a road, detection equipment does not need to be configured at high density, and the investment cost for detecting the road traffic event is reduced.
The following are embodiments of the apparatus of the present application that may be used to perform embodiments of the method of the present application. For details which are not disclosed in the embodiments of the apparatus of the present application, reference is made to the embodiments of the method of the present application.
Fig. 4 is a schematic structural diagram of a traffic event detection device according to a second embodiment of the present application, and as shown in fig. 4, the device may include:
a demarcating module 410 for demarcating a detection area on the current road;
an obtaining module 420, configured to obtain road structure data and traffic flow data in the detection area; acquiring running data of each vehicle in the detection area, wherein the running data comprises running speed and acceleration at each moment;
the analysis module 430 is configured to perform statistical analysis on the driving data to obtain driving characteristics corresponding to each vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time;
a detecting module 440, configured to detect whether a traffic event exists in the detection area according to the road structure data, the traffic flow data, and the driving characteristics of each vehicle. .
The traffic incident detection device provided by this embodiment defines a detection area on a current road, acquires road structure data and traffic flow data in the detection area, acquires driving data of each vehicle in the detection area, where the driving data includes driving speed and acceleration at each time, and performs statistical analysis on the driving data to obtain driving characteristics corresponding to each vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time, whether a traffic incident exists in the detection area is detected according to the road structure data, the traffic flow data and the driving characteristics of all vehicles, and therefore large data analysis is carried out on the traffic flow driving behavior in the detection area on the basis of the driving characteristics of the vehicles in the detection area, the traffic incident influencing the vehicle passing is rapidly and accurately detected, a traffic flow or vehicle speed detector does not need to be installed by breaking the road, high-density configuration of detection equipment is not needed, and the investment cost of detecting the road traffic incident is reduced. .
Preferably, the road structure data comprises the positions of element sites in the detection area, and the element sites comprise intersections, ramps, tunnels, bridges, speed-limiting areas, overspeed monitoring points and sharp turning road sections; the traffic flow data comprises the traffic flow in the uplink direction and the traffic flow in the downlink direction of different driving sections at different moments in the detection area.
Preferably, the traffic events include single point traffic events and regional traffic events.
Accordingly, as shown in fig. 5, the detection module 440 includes:
an analyzing unit 441, configured to perform statistical analysis on the driving characteristics of each vehicle in the uplink direction or the downlink direction in the detection area according to the road structure data to obtain a driving characteristic analysis result of each vehicle, where the analysis result includes a spatial clustering result and a time distribution result;
a single-point detection unit 442, configured to calculate, according to the analysis result and the traffic flow data, a ratio between the number of vehicles that continue to run at a low speed after being decelerated in the uplink direction or the downlink direction and traffic flow of different driving sections; if the ratio is larger than a preset ratio threshold, a single-point traffic event exists in the uplink direction or the downlink direction corresponding to the driving section;
the area detection unit 443 is configured to perform statistical analysis on the single-point traffic events occurring in the detection area, and if a plurality of adjacent driving sections within a preset range have a plurality of single-point traffic events of the same type within a preset time period, a regional traffic event exists at the plurality of driving sections.
Preferably, the apparatus may further include: and the prompt module 450 is configured to send a prompt message to a roadside variable information board on the upstream of the detection area if a traffic event exists in the detection area, where the prompt message is used to prompt an upstream vehicle to decelerate.
In practical application, as shown in fig. 1, a module configuration of the server 200 will be described. The vehicle-mounted intelligent monitoring system comprises two implementation modes, wherein one implementation mode is cloud deployment, as shown in fig. 6, the cloud computing mode is adopted for implementation, a data storage device, a vehicle driving characteristic analysis model, a single-point traffic event early warning model and a regional traffic event early warning model related to the implementation mode are all deployed on a server at the cloud, and the vehicle is communicated with the server through a communication network (possibly formed by combining a wired network and a wireless network). The other is that the road side unit and the cloud are deployed in a matched manner, as shown in fig. 7, at this time, the road side unit 110 or 120 deploys a data memory, a vehicle driving feature analysis model and a single-point traffic event early warning model, and the server 200 of the cloud deploys the data memory and a regional traffic event early warning model to realize event handling coordination.
Fig. 8 is a schematic structural diagram of an electronic device according to a third embodiment of the present application, and as shown in fig. 8, the electronic device includes: a memory 801 and a processor 802;
a memory 801 for storing a computer program;
wherein the processor 802 executes the computer program in the memory 801 to implement the methods provided by the method embodiments described above.
In the embodiment, the traffic event detection device provided by the application is exemplified by an electronic device. The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
The memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. Volatile memory can include, for example, Random Access Memory (RAM), cache memory (or the like). The non-volatile memory may include, for example, Read Only Memory (ROM), a hard disk, flash memory, and the like. One or more computer program instructions may be stored on a computer-readable storage medium and executed by a processor to implement the methods of the various embodiments of the present application above and/or other desired functions. Various contents such as an input signal, a signal component, a noise component, etc. may also be stored in the computer-readable storage medium.
An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored, and the computer program is used for implementing the methods provided by the method embodiments described above when being executed by a processor.
In practice, the computer program in this embodiment may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + +, python, etc., and conventional procedural programming languages, such as the "C" programming language or similar programming languages, for performing the operations of embodiments of the present invention. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
In practice, the computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but 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 include: an electrical connection having one 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 foregoing descriptions of specific exemplary embodiments of the present application have been presented for purposes of illustration and description. It is not intended to limit the application to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain certain principles of the present application and its practical application to enable one skilled in the art to make and use various exemplary embodiments of the present application and various alternatives and modifications thereof. It is intended that the scope of the application be defined by the claims and their equivalents.
Claims (6)
1. A method of traffic event detection, comprising:
defining a detection area on a current road;
acquiring road structure data and traffic flow data in the detection area;
acquiring running data of each vehicle in the detection area, wherein the running data comprises running speed and acceleration at each moment;
carrying out statistical analysis on the driving data to obtain driving characteristics corresponding to each vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time;
detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of each vehicle; the traffic events include single point traffic events and regional traffic events;
the road structure data comprises the positions of element sites in the detection area, wherein the element sites comprise intersections, ramps, tunnels, bridges, speed-limiting areas, overspeed monitoring points and sharp turning road sections; the traffic flow data comprises the traffic flow in the uplink direction and the traffic flow in the downlink direction of different driving sections at each moment in the detection area;
the detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of each vehicle comprises the following steps:
according to the road structure data, carrying out statistical analysis on the driving characteristics of each vehicle in the uplink direction or the downlink direction in the detection area to obtain the driving characteristic analysis result of each vehicle, wherein the analysis result comprises a spatial clustering result and a time distribution result;
according to the analysis result and the traffic flow data, calculating the ratio of the number of vehicles of the continuously low-speed running vehicles after the speed reduction in the uplink direction or the downlink direction to the traffic flow of different running sections;
if the ratio is larger than a preset ratio threshold, a single-point traffic event exists in the uplink direction or the downlink direction corresponding to the driving section;
carrying out statistical analysis on the single-point traffic events appearing in the detection area, wherein if a plurality of single-point traffic events of the same type appear in a plurality of adjacent driving sections in a preset time period, regional traffic events exist in the plurality of driving sections;
the statistical analysis of the single-point traffic events in the detection area comprises the steps of establishing a regional traffic event early warning model, and comprehensively analyzing the single-point traffic events in the uplink direction or the downlink direction in the detection area by adopting a spatial correlation analysis method to obtain the spatial correlation relationship of the single-point traffic events.
2. The method of claim 1, further comprising:
and if the traffic incident exists in the detection area, sending a prompt message to a roadside variable information board at the upstream of the detection area, wherein the prompt message is used for reminding an upstream vehicle to decelerate.
3. A traffic event detection device, comprising:
the marking module is used for marking a detection area on the current road;
the acquisition module is used for acquiring road structure data and traffic flow data in the detection area; acquiring running data of each vehicle in the detection area, wherein the running data comprises running speed and acceleration at each moment;
the analysis module is used for carrying out statistical analysis on the driving data to obtain driving characteristics corresponding to each vehicle; the driving characteristics comprise a deceleration position, a deceleration moment, an acceleration during deceleration, a continuous low-speed driving duration after deceleration and a continuous acceleration time;
the detection module is used for detecting whether a traffic event exists in the detection area according to the road structure data, the traffic flow data and the driving characteristics of all vehicles; the traffic events include single point traffic events and regional traffic events;
the road structure data comprises the positions of element sites in the detection area, wherein the element sites comprise intersections, ramps, tunnels, bridges, speed-limiting areas, overspeed monitoring points and sharp turning road sections; the traffic flow data comprises the traffic flow in the uplink direction and the traffic flow in the downlink direction of different driving sections at each moment in the detection area;
the detection module comprises:
the analysis unit is used for carrying out statistical analysis on the driving characteristics of each vehicle in the uplink direction or the downlink direction in the detection area according to the road structure data to obtain the driving characteristic analysis result of each vehicle, and the analysis result comprises a spatial clustering result and a time distribution result;
the single-point detection unit is used for calculating the ratio of the number of vehicles of the continuously low-speed running vehicles after being decelerated in the uplink direction or the downlink direction to the traffic flow of different running sections according to the analysis result and the traffic flow data; if the ratio is larger than a preset ratio threshold, a single-point traffic event exists in the uplink direction or the downlink direction corresponding to the driving section;
the area detection unit is used for carrying out statistical analysis on the single-point traffic events appearing in the detection area, and if a plurality of single-point traffic events of the same type appear in a plurality of adjacent driving sections in a preset time period, regional traffic events exist in the plurality of driving sections;
the statistical analysis of the single-point traffic events in the detection area comprises the steps of establishing a regional traffic event early warning model, and comprehensively analyzing the single-point traffic events in the uplink direction or the downlink direction in the detection area by adopting a spatial correlation analysis method to obtain the spatial correlation relationship of the single-point traffic events.
4. The apparatus of claim 3, further comprising:
and the prompting module is used for sending a prompting message to a roadside variable information board at the upstream of the detection area if a traffic event exists in the detection area, wherein the prompting message is used for prompting the upstream vehicle to decelerate.
5. An electronic device, comprising: a memory and a processor;
the memory for storing a computer program;
wherein the processor executes the computer program in the memory to implement the method of any one of claims 1-2.
6. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, is adapted to carry out the method of any one of claims 1-2.
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