CN116504070B - Traffic accident early warning method and system combining road characteristics - Google Patents
Traffic accident early warning method and system combining road characteristics Download PDFInfo
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention provides a traffic accident early warning method and a system combining road characteristics, which relate to the technical field of traffic accident monitoring, and the method comprises the following steps: acquiring radar monitoring information and camera shooting monitoring information of the same time sequence of a preset road area; extracting traffic characteristics to generate a traffic characteristic matrix; extracting road characteristics from the radar monitoring information and the camera monitoring information to generate dynamic road characteristics; the static road characteristics of the preset road area are called from a road database of the remote management terminal, and traffic characteristic threshold multi-objective mapping is carried out by combining the dynamic road characteristics to generate a traffic characteristic constraint matrix; when the traffic feature matrix does not meet the traffic feature constraint matrix, traffic pre-warning information of a preset road area is generated for pre-warning, the technical problems of insufficient pre-warning accuracy and timeliness in the prior art are solved, and the technical effect of improving the pre-warning accuracy and timeliness is achieved.
Description
Technical Field
The invention relates to the technical field of traffic accident monitoring, in particular to a traffic accident early warning method and system combining road characteristics.
Background
Along with the mention of living standard, more and more trolleys on the road, the number of deaths caused by traffic accidents is very small each year. In order to reduce traffic accidents and improve travel safety, a traffic early warning system needs to be developed, and the traffic early warning system is installed on an accident frequent road section to achieve reminding effects on pedestrians and drivers.
At present, when road traffic monitoring and early warning are carried out in the prior art, the type of a used sensor is single, the accuracy of a data acquisition result is insufficient, and the operation process of a system is complex, so that the early warning accuracy and timeliness are insufficient.
Disclosure of Invention
The invention provides a traffic accident early warning method and system combining road characteristics, which are used for solving the technical problems of insufficient early warning accuracy and timeliness in the prior art.
According to a first aspect of the present invention, there is provided a traffic accident warning method in combination with road characteristics, comprising: acquiring radar monitoring information and camera shooting monitoring information of the same time sequence of a preset road area; extracting traffic characteristics of the radar monitoring information and the camera shooting monitoring information to generate a traffic characteristic matrix; extracting road characteristics from the radar monitoring information and the camera monitoring information to generate dynamic road characteristics; the static road characteristics of the preset road area are called from a road database of the remote management terminal, and traffic characteristic threshold multi-objective mapping is carried out by combining the dynamic road characteristics to generate a traffic characteristic constraint matrix; when the traffic feature matrix does not meet the traffic feature constraint matrix, generating traffic early warning information of a preset road area for early warning; the traffic characteristic threshold multi-objective mapping is realized by a multi-objective mapping model embedded in the remote management terminal.
According to a second aspect of the present invention, there is provided a traffic accident warning system incorporating road features, comprising: the monitoring information acquisition module is used for acquiring radar monitoring information and camera shooting monitoring information of the same time sequence of a preset road area; the traffic feature extraction module is used for extracting traffic features of the radar monitoring information and the camera monitoring information to generate a traffic feature matrix; the road feature extraction module is used for extracting road features of the radar monitoring information and the camera monitoring information and generating dynamic road features; the multi-target mapping module is used for calling static road characteristics of the preset road area from a road database of the remote management terminal, and carrying out traffic characteristic threshold multi-target mapping in combination with the dynamic road characteristics to generate a traffic characteristic constraint matrix; the traffic early warning module is used for generating traffic early warning information of a preset road area to early warn when the traffic characteristic matrix does not meet the traffic characteristic constraint matrix; the traffic characteristic threshold multi-objective mapping is realized by a multi-objective mapping model embedded in the remote management terminal.
According to the traffic accident early warning method combining the road characteristics, the radar and the camera are used for simultaneously monitoring the road, so that the traffic characteristics are extracted, the traffic characteristic matrix is generated, and the effect of ensuring the comprehensiveness and the accuracy of the traffic characteristics is achieved; further, road feature extraction is carried out on radar monitoring information and camera monitoring information, dynamic road features are generated, static road features of the preset road area are called from a road database of the remote management terminal, traffic feature threshold multi-objective mapping is carried out by combining the dynamic road features, and associated road features of different traffic feature types are obtained, so that a traffic feature constraint matrix is generated, and the traffic feature constraint matrix is used as a judgment basis of early warning, so that the effect of ensuring the accuracy of early warning is achieved; further, early warning is carried out in a preset road area and preset mobile equipment respectively, so that the technical effects of ensuring the comprehensiveness and accuracy of early warning are achieved; the method provided by the invention is applied to the remote management terminal, the remote management is carried out through the remote management terminal, the calculation power is strong, the intelligent rapid early warning is realized, the centralized management of traffic accidents is realized, and the early warning timeliness is improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following brief description will be given of the drawings used in the description of the embodiments or the prior art, it being obvious that the drawings in the description below are only exemplary and that other drawings can be obtained from the drawings provided without the inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a traffic accident early warning method combining road features according to an embodiment of the present invention;
FIG. 2 is a flow chart of generating the multi-objective mapping model according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of generating traffic early warning information of a preset road area for early warning in the embodiment of the invention;
fig. 4 is a schematic structural diagram of a traffic accident warning system with road features according to an embodiment of the present invention.
Reference numerals illustrate: the system comprises a monitoring information acquisition module 11, a traffic feature extraction module 12, a road feature extraction module 13, a multi-target mapping module 14 and a traffic early warning module 15.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In order to solve the technical problems of insufficient early warning accuracy and timeliness in the prior art, the inventor of the invention obtains the traffic accident early warning method and system combining road characteristics through creative labor.
Embodiment one:
fig. 1 is a diagram of a traffic accident early warning method combining road features, which is provided by an embodiment of the present invention, and the method is applied to a remote management terminal, as shown in fig. 1, and the method includes:
step S100: acquiring radar monitoring information and camera shooting monitoring information of the same time sequence of a preset road area;
specifically, the remote management terminal is a terminal service port installed by a server, is provided with a remote control tool, can log in the server at any place, has strong calculation power, and can realize remote centralized management of road traffic accidents.
The invention can be used for various areas of road traffic, the preset road area refers to the road area where a user wants to perform traffic accident early warning management, the road area is provided with a radar and a camera, the radar and the camera are connected, the radar monitoring information and the camera monitoring information of the same time sequence (same time) of the preset road area are acquired, most of the camera is used for monitoring the traffic state of the road, and the other part of the camera is also used for speed measurement, and the speed measurement camera is accompanied with a radar antenna, so that the radar mainly detects the running speed of the vehicle, when the vehicle enters a detection range (the preset road area), the radar can send two waves to detect the position of the vehicle, after the waves sent out twice are received, the running distance can be calculated according to the principle of a trigonometric function, the running distance is divided by the running speed of the vehicle, the characteristics such as the position and the flow of the vehicle can be acquired based on the radar, the radar can detect the position and the speed of the vehicle, the obstacle information on the road can be used for acquiring radar monitoring information, the characteristics and the vehicle characteristics, the radar monitoring information can be used for recording the road characteristics, the basic functions and the radar monitoring information and the radar information are the acquired information, the basic functions and the acquired information types are basically the same, and the road monitoring information can be more fully acquired, and the road information can be more completely acquired.
Step S200: extracting traffic characteristics of the radar monitoring information and the camera shooting monitoring information to generate a traffic characteristic matrix;
the step S200 of the embodiment of the present invention further includes:
step S210: carrying out traffic characteristic analysis according to the radar monitoring information to obtain initial traffic characteristic information;
step S220: and compensating the initial traffic characteristic information according to the camera monitoring information to construct the traffic characteristic matrix.
Specifically, the radar monitoring information and the camera monitoring information are both information about road traffic characteristics, and the information such as vehicle speed, running direction and the like can be obtained only by carrying out traffic characteristic analysis through one of the information, but considering the incompleteness of information monitoring, the radar monitoring information and the camera monitoring information are comprehensively utilized to extract traffic characteristics, firstly, the traffic characteristic analysis is carried out through one of the information to obtain initial traffic characteristic information, then the traffic characteristic analysis is carried out again through the other monitoring information, the initial traffic characteristic information is compensated according to the analysis result, a traffic characteristic matrix is constructed according to the compensated traffic characteristic information, the accuracy of the traffic characteristic analysis is guaranteed, and the accuracy of traffic accident early warning is improved.
Specifically, the traffic characteristic analysis is performed according to the radar monitoring information to obtain initial traffic characteristic information, where the initial traffic characteristic information includes one or more of a traffic flow characteristic (vehicles passing through in unit time), a single vehicle speed characteristic (vehicle individual speed), a vehicle group average speed characteristic (average speed of a plurality of vehicles), a vehicle flow direction characteristic (vehicle traveling direction), a vehicle reverse travel characteristic (number of reverse vehicles), a traffic flow characteristic (number of people passing through in unit time), and the like, and then the initial traffic characteristic information is compensated according to the image capturing monitoring information. The compensated initial characteristic information comprises one or more of traffic flow characteristics, single vehicle speed characteristics, vehicle group average speed characteristics, vehicle flow direction characteristics, vehicle retrograde characteristics, traffic flow characteristics and crowding degree characteristics, and the initial characteristic information is orderly arranged into a data matrix as a traffic characteristic matrix according to the characteristic types in the initial characteristic information, so that the traffic characteristic matrix at least comprises one of the following: the traffic flow characteristics, the single vehicle speed characteristics, the vehicle group average speed characteristics, the vehicle flow direction characteristics, the vehicle retrograde characteristics, the pedestrian flow characteristics and the crowding degree characteristics, and the effects of ensuring the accuracy of traffic characteristic analysis and improving the accuracy of traffic accident early warning are achieved.
Step S300: extracting road characteristics from the radar monitoring information and the camera monitoring information to generate dynamic road characteristics;
specifically, the dynamic road feature refers to a feature related to the nature of the road itself, and includes at least one of the following: the method comprises the steps of identifying the position characteristics of the obstacle according to radar monitoring information, and taking the position characteristics of the obstacle as the obstacle distribution characteristics; the road surface humidity characteristic, the road surface hardness characteristic and the road surface mud water characteristic can be obtained according to the analysis of the shooting information of the road in the shooting monitoring information.
Step S400: the static road characteristics of the preset road area are called from a road database of the remote management terminal, and traffic characteristic threshold multi-objective mapping is carried out by combining the dynamic road characteristics to generate a traffic characteristic constraint matrix, wherein the traffic characteristic threshold multi-objective mapping is realized by a multi-objective mapping model embedded in the remote management terminal;
as shown in fig. 2, step S400 of the embodiment of the present invention further includes:
step S410: traversing a plurality of traffic feature types corresponding to the traffic feature threshold, and performing association analysis on the traffic feature types, the static road features and the dynamic road features to obtain a plurality of groups of association road features of the traffic feature types;
Step S420: taking the ith group of associated road features of the multiple groups of associated road features as input independent variables, taking the ith traffic feature type of the multiple traffic feature types corresponding to the ith group of associated road features as follow-up dependent variables, and carrying out simulation analysis in a traffic simulation module to construct a mapping data set from the ith group of associated road features to the ith traffic feature type;
step S430: training a first sub-target mapping model according to a mapping dataset of the first group of associated road features to the first traffic feature type;
step S440: training an ith sub-target mapping model according to the mapping data set from the ith group of associated road features to the ith traffic feature type;
step S450: and merging the first sub-target mapping model to the ith sub-target mapping model as parallel network nodes to generate the multi-target mapping model.
The step S410 of the embodiment of the present invention further includes:
step S411: taking the static road feature and the dynamic road feature as preset variables, taking the ith traffic feature type of the traffic feature types as a following variable, and collecting a traffic state monitoring log, wherein the traffic state monitoring log comprises an ith traffic feature state sequence corresponding to the ith traffic feature type one by one and a road feature state sequence of the static road feature and the dynamic road feature;
Step S412: normalizing and adjusting the ith traffic characteristic state sequence and the road characteristic state sequence to obtain an ith traffic characteristic state reference sequence and a road characteristic state comparison sequence;
step S413: and carrying out association degree analysis on the ith traffic characteristic state reference sequence and the road characteristic state comparison sequence, obtaining the road characteristic state with association degree larger than or equal to an association degree threshold value, adding the road characteristic state into the ith group of association road characteristics, and adding the road characteristic state into the multiple groups of association road characteristics.
Specifically, the static road characteristics of the preset road area are called from the road database of the remote management terminal, and the static road characteristics at least comprise one of the following: calculating the speed characteristic, namely the running speed of the vehicle; designing traffic capacity characteristics, which means the number of vehicles which can pass through a road; the width characteristic of the road width refers to the width of the road; terrain type features such as straight, curved, etc. And then, according to the static road characteristics, carrying out traffic characteristic threshold multi-objective mapping in combination with the dynamic road characteristics to generate a traffic characteristic constraint matrix, wherein the traffic characteristic threshold multi-objective mapping is realized by a multi-objective mapping model embedded in the remote management terminal.
Specifically, the traffic feature threshold value refers to a safety constraint interval of traffic flow features, single vehicle speed features, vehicle group average speed features, vehicle flow direction features and the like corresponding to the traffic feature types, or within the interval range, the occurrence probability of the corresponding traffic feature types is minimum, further, relevance analysis is carried out on the traffic feature types, static road features and dynamic road features, colloquially speaking, road features focused by different traffic feature types are different, for example, traffic flow features, vehicle speed features and the like are focused by traffic jam, therefore, relevance between a plurality of features in the static road features and the dynamic road features and the traffic feature types is analyzed, and features with larger relevance are obtained as a plurality of sets of relevant road features, and one traffic feature type corresponds to a set of relevant road features.
Taking the ith group of associated road features of multiple groups of associated road features as input independent variables, taking the ith traffic feature type of multiple traffic feature types corresponding to the ith group of associated road features as a follow-up dependent variable, performing simulation analysis on the follow-up dependent variable in a traffic simulation module, wherein the follow-up dependent variable is a variable which changes along with the independent variable, in short, the associated road features change, the corresponding traffic feature types possibly change, the data in the associated road features are changed through the traffic simulation module, the traffic feature types are simulated, the simulation process is monitored, constraint intervals of the associated road features corresponding to the multiple traffic feature types are obtained through simulation analysis, the probability of occurrence of the corresponding traffic feature types in the constraint intervals is the lowest, and a mapping data set from the ith group of associated road features to the ith traffic feature type is constructed based on the simulation analysis, wherein the mapping data set comprises: associated road characteristics, and constraint interval data for a corresponding first traffic characteristic type under a constraint condition (constraint interval) of the associated road characteristics.
Training a first sub-target mapping model according to a mapping data set from a first group of associated road features to a first traffic feature type, wherein the first sub-target mapping model is used for mapping constraint intervals of the first traffic feature type under different road states, training an i sub-target mapping model according to a mapping data set from an i group of associated road features to an i traffic feature type, and mapping constraint intervals of the i traffic feature type under different road states, wherein the first sub-target mapping model is used for merging the first sub-target mapping model to the i sub-target mapping model as a parallel network node, namely, generating a multi-target mapping model by using the i sub-target mapping model, and the multi-target mapping model comprises i sub-target mapping models which are used for outputting the constraint intervals of the i traffic feature types.
And then, carrying out traffic characteristic threshold multi-objective mapping according to the multi-objective mapping model, and acquiring a plurality of constraint intervals corresponding to a plurality of traffic characteristic types, wherein the constraint intervals form a traffic characteristic constraint matrix.
Specifically, traversing a plurality of traffic feature types corresponding to the traffic feature threshold, and performing association analysis on the static road features and the dynamic road features as follows: the method comprises the steps of taking static road features and dynamic road features as preset variables, taking the ith traffic feature type of a plurality of traffic feature types as a following variable, wherein the following variable is a variable which changes along with the preset variable, and ensuring that the acquired preset variable and the following variable are in a one-to-one correspondence relationship. The traffic state monitoring log is further acquired, the traffic state monitoring log comprises an ith traffic feature state sequence and a road feature state sequence of static road features and dynamic road features, the ith traffic feature type state changes along with the changes of the static road features and the dynamic road features, and the whole change process of a preset variable and a following variable is acquired to be used as the ith traffic feature state sequence and the road feature state sequence. The i-th traffic characteristic state sequence and the road characteristic state sequence are subjected to normalization adjustment, the normalization is a data processing mode, the processed data can be limited in a certain fixed range, subsequent analysis is facilitated, and the normalization is in two forms, wherein the data is processed into decimal between 0 and 1 under normal conditions, and the purpose of the normalization is to be more convenient in the subsequent data processing process. The other is to change the dimensionality expression into a dimensionless expression by normalization. The difference of dimension units leads to no comparability among data, and meanwhile, the magnitude of the data is different for different dimensions, after normalization adjustment, the influence of the dimensions can be eliminated, and each data can be normalized to the same magnitude, so that the comparability problem among the data is solved.
And acquiring an ith traffic characteristic state reference sequence and a road characteristic state comparison sequence after normalization adjustment, selecting a relevance analysis method to analyze the relevance of the ith traffic characteristic state reference sequence and the road characteristic state comparison sequence, acquiring the road characteristic state with the relevance greater than or equal to a relevance threshold value, adding the road characteristic state into an ith group of relevant road characteristics, and adding the road characteristic state into the multiple groups of relevant road characteristics. Preferably, a gray association analysis method is selected for association analysis, firstly, an ith traffic characteristic state reference sequence is used as a parent sequence, the influence degree of a road characteristic state comparison sequence (a child sequence) on the parent sequence is analyzed, an association coefficient is calculated, and the association coefficient has the following calculation formula:
，
wherein, the liquid crystal display device comprises a liquid crystal display device,representing a correlation coefficient; />Is a plurality of time sequence state data in a parent sequence (i-th traffic characteristic state reference sequence); />Is the sub-sequence (road feature status alignment sequence) and +.>Status data corresponding to the time sequence; />Called resolution factor, +.>The smaller the resolution, the greater the resolution, generally +.>The value interval of (1, 0) is determined according to the condition, whenAt the same time, the resolution is best, usually +.>；/>Refers to the minimum value in the road feature status comparison sequence, Refers to the maximum value in the road feature state comparison sequence.
The relevance is further calculated according to the relevance coefficient by adopting the following formula:
；
representing the degree of association->Is a correlation coefficient, ++>The number of the plurality of time sequence states in the road feature state comparison sequence is expressed, in short, the plurality of association coefficients of each traffic feature type and each road feature are calculated, and the plurality of association coefficients are averaged to be used as the association degree between one traffic feature type and one road feature.
In summary, the association degree between a plurality of traffic feature types and any one of the static road feature and the dynamic road feature can be obtained through calculation, further, the association degree is sorted from big to small, the road feature states with the association degree greater than or equal to the association degree threshold value are obtained and added into the ith group of associated road features, a plurality of groups of associated road features corresponding to the plurality of traffic feature types are added, and the association degree threshold value needs to be set according to actual conditions. Thus, multiple sets of associated road features for multiple traffic feature types are obtained.
Step S500: and when the traffic feature matrix does not meet the traffic feature constraint matrix, generating traffic early warning information of a preset road area for early warning.
As shown in fig. 3, step S500 of the embodiment of the present invention further includes:
step S510: extracting traffic characteristic states of the traffic characteristic matrixes which do not meet the traffic characteristic constraint matrix and setting the traffic characteristic states as early warning traffic characteristic state information;
step S520: analyzing the traffic accident frequency according to the early warning traffic characteristic state information to obtain a plurality of traffic accident types and a plurality of traffic accident frequencies;
step S530: extracting the traffic accident types with the traffic accident frequencies greater than or equal to a frequency threshold value, and setting the traffic accident types as early warning traffic accident types;
step S540: and adding the early warning traffic characteristic state information and the early warning traffic accident type into the traffic early warning information of the preset road area to perform early warning.
Specifically, the traffic feature constraint matrix is constructed by a plurality of constraint intervals of road features corresponding to a plurality of traffic feature types, the probability of occurrence of various traffic feature types is lowest in the range of the traffic feature constraint matrix, the traffic feature matrix can be regarded as real-time data of the road features, and when the traffic feature matrix does not meet the traffic feature constraint matrix, the condition that traffic accidents can exist in a preset road area is explained, and traffic early warning information of the preset road area is generated for early warning.
Specifically, the feature constraint matrix comprises constraint intervals of different traffic feature types, the constraint intervals in the traffic feature matrix and the feature constraint matrix are compared, the traffic feature state corresponding to any constraint interval in the traffic feature constraint matrix is extracted, the traffic feature state which does not meet the requirement of the traffic feature constraint matrix is set as early warning traffic feature state information, the early warning traffic feature state information comprises data corresponding to different road features, namely one or more of traffic flow features, single vehicle speed features, vehicle group average speed features, vehicle flow direction features, vehicle retrograde features, people flow features and congestion degree features, the traffic accident types and the frequency thereof which occur when the traffic feature matrix is early warning are counted in the big data according to the early warning traffic feature state information, specifically, the total frequency of occurrence of all traffic accident types is acquired, then the traffic accident frequencies corresponding to the traffic accident types are arranged from big to small by using the ratio between the occurrence frequency and the total frequency of each traffic accident type as the traffic accident frequencies, the traffic accident frequencies corresponding to the traffic accident types are set as the traffic accident frequencies, the traffic accident frequency threshold is set as the traffic accident frequency threshold according to the traffic accident frequency, and the traffic accident frequency is set as the traffic accident frequency history. The traffic pre-warning information of the preset road area is added with the traffic pre-warning information of the pre-warning traffic characteristic state information and the pre-warning traffic accident type, and the remote management terminal is used for pre-warning, so that traffic accidents possibly occurring in the preset road area of a vehicle driver and pedestrians are reminded, and the technical effects of improving the pre-warning accuracy and efficiency and guaranteeing the safety of the personnel and the vehicle are achieved.
The step S600 of the embodiment of the present invention includes:
step S610: receiving preset road area traffic early warning information sent by the remote management terminal, wherein the preset road area traffic early warning information comprises early warning traffic characteristic state information and early warning traffic accident types;
step S620: generating broadcasting early warning voice according to the early warning traffic characteristic state information and the early warning traffic accident type, and broadcasting early warning on preset broadcasting equipment in a preset road area;
step S630: and generating display early warning information according to the early warning traffic characteristic state information and the early warning traffic accident type, and displaying early warning in a preset display area of the preset road area.
Specifically, the preset road area traffic early warning information sent by the remote management terminal is received, the preset road area traffic early warning information comprises early warning traffic characteristic state information and early warning traffic accident types, a voice function module is embedded in the remote management terminal, the early warning traffic characteristic state information and the early warning traffic accident types are identified through the voice function module, broadcasting early warning voice is generated, broadcasting early warning is carried out on preset broadcasting equipment in a preset road area, and the preset broadcasting equipment is connected with the remote management terminal, such as a sound box, a loudspeaker and the like. Further, the early warning information is generated and displayed according to the early warning traffic characteristic state information and the early warning traffic accident type, and different display colors are set for different early warning traffic characteristic state information and early warning traffic accident types, and color display early warning is carried out on the early warning traffic characteristic state information and the early warning traffic accident type in a preset display area (such as an electronic display screen) of a preset road area, so that drivers or pedestrians can clearly know the early warning information, and personnel safety is guaranteed.
The step S700 of the embodiment of the present invention includes:
step S710: receiving preset road area traffic early warning information sent by the remote management terminal, wherein the preset road area traffic early warning information comprises early warning traffic characteristic state information and early warning traffic accident types;
step S720: when the fact that the preset mobile device enters an upstream adjacent area of a preset road area is detected, generating display early warning information and broadcasting early warning voice according to the early warning traffic characteristic state information and the early warning traffic accident type;
step S730: displaying the display early warning information in a specific display area arranged in the preset mobile equipment;
step S740: and a voice broadcasting device arranged in the preset mobile equipment plays the broadcasting early warning voice.
Specifically, the preset mobile device may be a vehicle with a positioning function, a vehicle-mounted GPS is arranged in the vehicle, real-time positioning information of the preset mobile device is detected in real time, when the preset mobile device is detected to enter an upstream adjacent area of a preset road area, display early warning information and broadcast early warning voice are generated according to early warning traffic characteristic state information and early warning traffic accident types, the upstream adjacent area is an area adjacent to the preset road area and can be set by itself, for example, a position area 0-500 m away from the preset road area, and at the moment, vehicles or pedestrians which do not enter the preset road area are warned in time to avoid the traffic accident area, so that self safety is ensured. The text display is further carried out on the display early warning information in a specific display area (navigation display screen) arranged in the preset mobile equipment, different color display modes are set according to the difference of the display early warning information, meanwhile, a voice broadcasting device (such as a voice function module carried by a vehicle navigation system) arranged in the preset mobile equipment is utilized to broadcast the broadcasting early warning voice, dual early warning of the text and the voice is achieved, and the early warning effect is improved.
Based on the analysis, the invention provides a traffic accident early warning method combining road characteristics, in the embodiment, the radar and the camera are used for simultaneously monitoring the road, so that the traffic characteristics are extracted, a traffic characteristic matrix is generated, and the effect of ensuring the comprehensiveness and the accuracy of the traffic characteristics is achieved; further, road feature extraction is carried out on radar monitoring information and camera monitoring information, dynamic road features are generated, static road features of the preset road area are called from a road database of the remote management terminal, traffic feature threshold multi-objective mapping is carried out by combining the dynamic road features, and associated road features of different traffic feature types are obtained, so that a traffic feature constraint matrix is generated, and the traffic feature constraint matrix is used as a judgment basis of early warning, so that the effect of ensuring the accuracy of early warning is achieved; further, early warning is carried out in a preset road area and preset mobile equipment respectively, so that the technical effects of ensuring the comprehensiveness and accuracy of early warning are achieved; the method provided by the invention is applied to the remote management terminal, the remote management is carried out through the remote management terminal, the calculation power is strong, the intelligent rapid early warning is realized, the centralized management of traffic accidents is realized, and the early warning timeliness is improved.
Embodiment two:
based on the same inventive concept as the traffic accident pre-warning method combining road features in the foregoing embodiment, as shown in fig. 4, the present invention further provides a traffic accident pre-warning system combining road features, applied to a remote management terminal, where the system includes:
the monitoring information acquisition module 11 is used for acquiring radar monitoring information and camera shooting monitoring information with the same time sequence of a preset road area by the monitoring information acquisition module 11;
the traffic feature extraction module 12 is configured to perform traffic feature extraction on the radar monitoring information and the camera monitoring information, so as to generate a traffic feature matrix;
the road feature extraction module 13 is used for extracting road features of the radar monitoring information and the camera monitoring information to generate dynamic road features;
the multi-target mapping module 14 is configured to invoke the static road feature of the preset road area from the road database of the remote management terminal, and perform traffic feature threshold multi-target mapping in combination with the dynamic road feature to generate a traffic feature constraint matrix;
The traffic early warning module 15 is configured to generate traffic early warning information of a preset road area for early warning when the traffic feature matrix does not meet the traffic feature constraint matrix;
the traffic characteristic threshold multi-objective mapping is realized by a multi-objective mapping model embedded in the remote management terminal.
Further, the system further comprises:
the initial traffic characteristic information acquisition module is used for carrying out traffic characteristic analysis according to the radar monitoring information to acquire initial traffic characteristic information;
and compensating the initial traffic characteristic information according to the camera monitoring information to construct the traffic characteristic matrix.
Further, the system further comprises:
the relevance analysis module is used for traversing a plurality of traffic feature types corresponding to the traffic feature threshold, carrying out relevance analysis on the traffic feature types, the static road features and the dynamic road features, and obtaining a plurality of groups of relevance road features of the traffic feature types;
the simulation analysis module is used for carrying out simulation analysis in the traffic simulation module by taking the ith group of associated road features of the multiple groups of associated road features as input independent variables and the ith traffic feature type of the multiple traffic feature types corresponding to the ith group of associated road features as follow-up dependent variables to construct a mapping data set from the ith group of associated road features to the ith traffic feature type;
The first sub-target mapping model training module is used for training a first sub-target mapping model according to a mapping data set from a first group of associated road features to a first traffic feature type;
the ith sub-target mapping model training module is used for training an ith sub-target mapping model according to the mapping data set from the ith group of associated road features to the ith traffic feature type;
and the multi-target mapping model generation module is used for merging the first sub-target mapping model to the ith sub-target mapping model as parallel network nodes to generate the multi-target mapping model.
Further, the system further comprises:
the traffic state monitoring log acquisition module is used for acquiring a traffic state monitoring log by taking the static road feature and the dynamic road feature as preset variables and taking the ith traffic feature type of the traffic feature types as a following variable, wherein the traffic state monitoring log comprises an ith traffic feature state sequence in one-to-one correspondence and a road feature state sequence of the static road feature and the dynamic road feature;
The normalization adjustment module is used for performing normalization adjustment on the ith traffic characteristic state sequence and the road characteristic state sequence to obtain an ith traffic characteristic state reference sequence and a road characteristic state comparison sequence;
and the second association degree analysis module is used for carrying out association degree analysis on the ith traffic characteristic state reference sequence and the road characteristic state comparison sequence, acquiring the road characteristic state with association degree larger than or equal to an association degree threshold value, adding the road characteristic state into the ith group of association road characteristics, and adding the road characteristic state into the multiple groups of association road characteristics.
Further, the system further comprises:
the early warning traffic characteristic state information setting module is used for extracting that the traffic characteristic state of the traffic characteristic matrix which does not meet the traffic characteristic constraint matrix is set as early warning traffic characteristic state information;
the traffic accident frequency analysis module is used for carrying out traffic accident frequency analysis according to the early warning traffic characteristic state information to acquire a plurality of traffic accident types and a plurality of traffic accident frequencies;
The early warning traffic accident type setting module is used for extracting the traffic accident types with the traffic accident frequencies greater than or equal to a frequency threshold value and setting the traffic accident types as early warning traffic accident types;
the second early warning module is used for adding the early warning traffic characteristic state information and the early warning traffic accident type into the traffic early warning information of the preset road area to carry out early warning.
Further, the system further comprises:
the first receiving module of the traffic early warning information of the preset road area is used for receiving the traffic early warning information of the preset road area sent by the remote management terminal, and the traffic early warning information of the preset road area comprises early warning traffic characteristic state information and early warning traffic accident types;
the broadcasting early warning module is used for generating broadcasting early warning voice according to the early warning traffic characteristic state information and the early warning traffic accident type, and broadcasting early warning is carried out on preset broadcasting equipment in a preset road area;
the display early warning module is used for generating display early warning information according to the early warning traffic characteristic state information and the early warning traffic accident type, and displaying early warning is carried out in a preset display area of the preset road area.
Further, the system further comprises:
the second receiving module of the traffic early warning information of the preset road area is used for receiving the traffic early warning information of the preset road area sent by the remote management terminal, and the traffic early warning information of the preset road area comprises early warning traffic characteristic state information and early warning traffic accident types;
the mobile equipment detection module is used for generating display early warning information and broadcasting early warning voice according to the early warning traffic characteristic state information and the early warning traffic accident type when detecting that the preset mobile equipment enters an upstream adjacent area of a preset road area;
the early warning information display module is used for displaying the display early warning information in a specific display area arranged in the preset mobile equipment;
the early warning voice playing module is used for playing the broadcast early warning voice through a voice broadcasting device arranged in the preset mobile equipment.
Wherein, the traffic characteristic matrix at least comprises one of the following: traffic flow characteristics, single vehicle speed characteristics, vehicle group average speed characteristics, vehicle flow direction characteristics, vehicle reverse travel characteristics, traffic flow characteristics and congestion characteristics;
The dynamic road characteristics include at least one of: road surface humidity characteristics, road surface hardness characteristics, road surface mud water quantity characteristics and barrier distribution characteristics;
the static road feature comprises at least one of: calculating the characteristics of vehicle speed, design traffic capacity, road width and terrain type.
The specific example of the traffic accident pre-warning method with road features in the first embodiment is also applicable to the traffic accident pre-warning system with road features in the present embodiment, and those skilled in the art can clearly know the traffic accident pre-warning system with road features in the present embodiment through the foregoing detailed description of the traffic accident pre-warning method with road features, so that the details of the description are not repeated here for brevity.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and are not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (7)
1. The traffic accident early warning method combining the road characteristics is characterized by being applied to a remote management terminal and comprising the following steps of:
acquiring radar monitoring information and camera shooting monitoring information of the same time sequence of a preset road area;
extracting traffic characteristics of the radar monitoring information and the camera shooting monitoring information to generate a traffic characteristic matrix; and
extracting road characteristics from the radar monitoring information and the camera monitoring information to generate dynamic road characteristics;
the static road characteristics of the preset road area are called from a road database of the remote management terminal, and traffic characteristic threshold multi-objective mapping is carried out by combining the dynamic road characteristics to generate a traffic characteristic constraint matrix;
when the traffic feature matrix does not meet the traffic feature constraint matrix, generating traffic early warning information of a preset road area for early warning;
Wherein, the traffic characteristic threshold multi-objective mapping is realized by a multi-objective mapping model embedded in the remote management terminal;
the method comprises the steps of calling static road features of the preset road area from a road database of the remote management terminal, carrying out traffic feature threshold multi-target mapping in combination with the dynamic road features, and generating a traffic feature constraint matrix, wherein the method comprises the following steps:
traversing a plurality of traffic feature types corresponding to the traffic feature threshold, and performing association analysis on the traffic feature types, the static road features and the dynamic road features to obtain a plurality of groups of association road features of the traffic feature types;
taking the ith group of associated road features of the multiple groups of associated road features as input independent variables, taking the ith traffic feature type of the multiple traffic feature types corresponding to the ith group of associated road features as follow-up dependent variables, and carrying out simulation analysis in a traffic simulation module to construct a mapping data set from the ith group of associated road features to the ith traffic feature type;
training a first sub-target mapping model according to a mapping dataset of the first group of associated road features to the first traffic feature type;
training an ith sub-target mapping model according to the mapping data set from the ith group of associated road features to the ith traffic feature type;
Merging the first sub-target mapping model to the ith sub-target mapping model as parallel network nodes to generate the multi-target mapping model;
when the traffic feature matrix does not meet the traffic feature constraint matrix, generating traffic early warning information of a preset road area for early warning, wherein the method comprises the following steps:
comparing the traffic feature matrix with a plurality of constraint intervals in the feature constraint matrix, extracting that a traffic feature state corresponding to any constraint interval in the traffic feature constraint matrix is not met by the traffic feature matrix, and setting the traffic feature state as early warning traffic feature state information;
analyzing the traffic accident frequency according to the early warning traffic characteristic state information to obtain a plurality of traffic accident types and a plurality of traffic accident frequencies;
extracting the traffic accident types with the traffic accident frequencies greater than or equal to a frequency threshold value, and setting the traffic accident types as early warning traffic accident types;
and adding the early warning traffic characteristic state information and the early warning traffic accident type into the traffic early warning information of the preset road area to perform early warning.
2. The traffic accident pre-warning method according to claim 1, wherein the traffic feature extraction is performed on the radar monitoring information and the camera monitoring information to generate a traffic feature matrix, and the traffic feature matrix comprises:
Carrying out traffic characteristic analysis according to the radar monitoring information to obtain initial traffic characteristic information;
and compensating the initial traffic characteristic information according to the camera monitoring information to construct the traffic characteristic matrix.
3. The traffic accident pre-warning method according to claim 1, wherein traversing a plurality of traffic feature types corresponding to the traffic feature threshold, performing association analysis with the static road feature and the dynamic road feature, and obtaining a plurality of groups of associated road features of the plurality of traffic feature types, comprises:
taking the static road feature and the dynamic road feature as preset variables, taking the ith traffic feature type of the traffic feature types as a following variable, and collecting a traffic state monitoring log, wherein the traffic state monitoring log comprises an ith traffic feature state sequence corresponding to the ith traffic feature type one by one and a road feature state sequence of the static road feature and the dynamic road feature;
normalizing and adjusting the ith traffic characteristic state sequence and the road characteristic state sequence to obtain an ith traffic characteristic state reference sequence and a road characteristic state comparison sequence;
And carrying out association degree analysis on the ith traffic characteristic state reference sequence and the road characteristic state comparison sequence, obtaining the road characteristic state with association degree larger than or equal to an association degree threshold value, adding the road characteristic state into the ith group of association road characteristics, and adding the road characteristic state into the multiple groups of association road characteristics.
4. The traffic accident pre-warning method combining road features according to claim 1, further applied to a road pre-warning end, comprising:
receiving preset road area traffic early warning information sent by the remote management terminal, wherein the preset road area traffic early warning information comprises early warning traffic characteristic state information and early warning traffic accident types;
generating broadcasting early warning voice according to the early warning traffic characteristic state information and the early warning traffic accident type, and broadcasting early warning on preset broadcasting equipment in a preset road area; and
and generating display early warning information according to the early warning traffic characteristic state information and the early warning traffic accident type, and displaying early warning in a preset display area of the preset road area.
5. The traffic accident pre-warning method combining road features according to claim 1 is further applied to a mobile pre-warning terminal, and comprises the following steps:
Receiving preset road area traffic early warning information sent by the remote management terminal, wherein the preset road area traffic early warning information comprises early warning traffic characteristic state information and early warning traffic accident types;
when the fact that the preset mobile device enters an upstream adjacent area of a preset road area is detected, generating display early warning information and broadcasting early warning voice according to the early warning traffic characteristic state information and the early warning traffic accident type;
displaying the display early warning information in a specific display area arranged in the preset mobile equipment; and
and a voice broadcasting device arranged in the preset mobile equipment plays the broadcasting early warning voice.
6. The traffic accident pre-warning method combining road features according to claim 1, comprising:
the traffic feature matrix comprises at least one of the following: traffic flow characteristics, single vehicle speed characteristics, vehicle group average speed characteristics, vehicle flow direction characteristics, vehicle reverse travel characteristics, traffic flow characteristics and congestion characteristics;
the dynamic road characteristics include at least one of: road surface humidity characteristics, road surface hardness characteristics, road surface mud water quantity characteristics and barrier distribution characteristics;
The static road feature comprises at least one of: calculating the characteristics of vehicle speed, design traffic capacity, road width and terrain type.
7. A traffic accident pre-warning system incorporating road features, the system performing the method of any one of claims 1 to 6, applied to a remote management terminal, comprising:
the monitoring information acquisition module is used for acquiring radar monitoring information and camera shooting monitoring information of the same time sequence of a preset road area;
the traffic feature extraction module is used for extracting traffic features of the radar monitoring information and the camera monitoring information to generate a traffic feature matrix; and
the road feature extraction module is used for extracting road features of the radar monitoring information and the camera monitoring information and generating dynamic road features;
the multi-target mapping module is used for calling static road characteristics of the preset road area from a road database of the remote management terminal, and carrying out traffic characteristic threshold multi-target mapping in combination with the dynamic road characteristics to generate a traffic characteristic constraint matrix;
The traffic early warning module is used for generating traffic early warning information of a preset road area to early warn when the traffic characteristic matrix does not meet the traffic characteristic constraint matrix;
the traffic characteristic threshold multi-objective mapping is realized by a multi-objective mapping model embedded in the remote management terminal.
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