CN116913099A - Intelligent traffic real-time monitoring system - Google Patents
Intelligent traffic real-time monitoring system Download PDFInfo
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- CN116913099A CN116913099A CN202310927357.3A CN202310927357A CN116913099A CN 116913099 A CN116913099 A CN 116913099A CN 202310927357 A CN202310927357 A CN 202310927357A CN 116913099 A CN116913099 A CN 116913099A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 81
- 206010039203 Road traffic accident Diseases 0.000 claims abstract description 86
- 238000012545 processing Methods 0.000 claims abstract description 20
- 230000010287 polarization Effects 0.000 claims description 23
- 238000000605 extraction Methods 0.000 claims description 11
- 238000010586 diagram Methods 0.000 claims description 5
- 238000005259 measurement Methods 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 238000012806 monitoring device Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 description 16
- 230000008569 process Effects 0.000 description 8
- 230000006399 behavior Effects 0.000 description 4
- 238000013527 convolutional neural network Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 241000195940 Bryophyta Species 0.000 description 1
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- 230000033228 biological regulation Effects 0.000 description 1
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- 238000004891 communication Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
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Classifications
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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
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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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
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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
- G08G1/054—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed photographing overspeeding vehicles
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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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
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Abstract
The application relates to an intelligent traffic real-time monitoring system, which relates to the technical field of monitoring, and comprises a driving information acquisition module, a monitoring module and a monitoring module, wherein the driving information acquisition module is used for acquiring monitoring information sent by traffic monitoring equipment in real time; the violation accident analysis module is used for respectively storing the monitoring information into the corresponding traffic monitoring storage model according to the monitoring type for storage; processing the monitoring information based on a preset processing algorithm of the traffic storage model to obtain traffic violation types corresponding to the monitoring information; the report generation module is used for acquiring a violation report template based on the traffic violation type; generating a traffic violation report based on the violation report template and the monitoring information; wherein the traffic violation report template comprises violation terms and correct driving modes; and the notification module is used for acquiring the information of the violation vehicle and sending the traffic violation report to the driver of the violation vehicle. The application has the effects of timely notifying or warning the driver of the violation and reducing the occurrence probability of traffic accidents.
Description
Technical Field
The application relates to the technical field of monitoring, in particular to an intelligent traffic real-time monitoring system.
Background
Traffic is the basis of modern society, is the pulse of human socioeconomic, and the social behavior of people is closely related to traffic. Along with the continuous improvement of the living standard of people, the automobile conservation amount on the road is larger and larger, and meanwhile, along with the increase of the vehicles, drivers can possibly generate illegal driving, traffic accidents and the like in the driving process.
In the related art, when a driver breaks rules, the monitoring system usually cannot timely inform the driver of the rules breaking or warn, so that the driver with insufficient driving experience can continue to drive the rules breaking during the broken driving by the delayed notification or warning, and the occurrence probability of traffic accidents is improved.
Disclosure of Invention
In order to timely inform or warn a driver of the violation and reduce the occurrence probability of traffic accidents, the application provides an intelligent traffic real-time monitoring system.
The application provides an intelligent traffic real-time monitoring system, which adopts the following technical scheme:
an intelligent traffic real-time monitoring system, comprising:
the driving information acquisition module is used for acquiring monitoring information sent by the traffic monitoring equipment in real time;
the violation accident analysis module is used for respectively storing the monitoring information into a corresponding traffic monitoring storage model according to the monitoring type for storage; processing the monitoring information based on a preset processing algorithm of the traffic storage model to obtain traffic violation types corresponding to the monitoring information;
the report generation module is used for acquiring a violation report template based on the traffic violation type; generating a traffic violation report based on the violation report template and the monitoring information; wherein the traffic violation report template comprises violation terms and correct driving modes;
and the notification module is used for acquiring the information of the violation vehicle and sending the traffic violation report to a driver of the violation vehicle.
By adopting the technical scheme, the monitoring information acquired in real time is utilized to analyze the traffic violation type of the monitoring information monitored to traffic violations, and the corresponding traffic violation report is generated, and the traffic violation report is sent to the driver in real time, so that the driver can timely receive the traffic violation report after the traffic violations, check the rule breaking terms, the rule breaking monitoring information and the correct driving mode, the condition that the driver continues to perform the rule breaking driving in the process of driving violations is reduced, and the probability of traffic accidents is further reduced.
Optionally, the driving information acquisition module includes:
the first shooting sub-module is used for recording the video of the running automobile in a certain road section to obtain a video;
the speed measuring sub-module is used for measuring the speed of the running automobile on a certain road section to obtain speed information;
the second shooting sub-module is used for shooting the running automobile on a certain road section to obtain a shooting image;
the second shooting sub-module is specifically used for acquiring a plurality of automobile polarized images under different polarized angles; extracting orthogonal polarization components and calculating an incident angle based on the orthogonal polarization components; performing polarization filtering treatment on the multiple automobile polarized images to obtain environment light corresponding to the multiple automobile polarized images at different polarization angles one by one; and calculating target light by using the orthogonal polarization components, and reconstructing the target light based on the target light and a plurality of automobile polarization diagrams under a plurality of different polarization angles to obtain a shooting image.
Through adopting above-mentioned technical scheme, monitor the traffic through video monitoring, speed measurement control and image monitoring, to image monitoring, adopt the mode of obtaining a plurality of car polarization images under the different polarization angles to reconstruct the image for the interior image of shooting is clearer, improves the accuracy of follow-up analysis navigating mate kind of violating regulations.
Optionally, the violation accident analysis module includes:
the violation analysis sub-module is used for converting the shot image into a gray level image; binarizing the gray level to obtain an image to be identified; and extracting the characteristics of the image to be identified according to a preset violation characteristic algorithm, and determining the traffic violation type corresponding to the photographed image based on the combination of the extracted characteristic information and the speed information.
Through adopting above-mentioned technical scheme, through converting into the gray scale map with shooting the image, then carry out binarization processing to the gray scale map for the shooting image is clearer, makes the characteristic information that carries out feature extraction to the shooting image more accurate, thereby confirm that traffic violation type is more accurate.
Optionally, the violation accident analysis module further includes:
the first accident analysis submodule is used for acquiring the alarm telephone time of the driving vehicle accident;
intercepting the video based on the alarm telephone time and a first preset time intercepting strategy to obtain a first event video segment;
performing frame extraction processing on the first event video segment to obtain a plurality of frame image data;
and inputting the plurality of frame image data into an accident identification model, and outputting the traffic accident type.
By adopting the technical scheme, because the continuous traffic violation can possibly generate traffic accidents or the possibility of traffic accidents often exists on traffic roads, after the traffic accidents happen, the problem of low accident efficiency is solved, and traffic abnormality can be caused, so that the traffic accident analysis module analyzes the traffic accident behavior besides analyzing the traffic violation behavior, intercepts video recorded by the time of a traffic accident alarming telephone, so that the acquisition of the traffic accident video is more accurate, and the traffic accident type is processed and analyzed by frame extraction of the video, thereby being convenient for analyzing the traffic accident processing result.
Optionally, the second accident sub-analysis sub-module is configured to obtain congestion information of a road section, where the congestion information includes congestion time;
intercepting the video based on the congestion time and a second preset time intercepting strategy to obtain a second accident video segment;
intercepting a plurality of characteristic images in the second accident video clip according to a third preset time intercepting strategy;
extracting the characteristics of the plurality of characteristic images, and judging whether traffic accidents occur or not according to the extracted characteristic information;
if a traffic accident occurs, performing frame extraction processing on the second accident video segment to obtain a plurality of frame image data;
and inputting the plurality of frame image data into an accident identification model, and outputting the traffic accident type.
By adopting the technical scheme, the video is intercepted by utilizing the congestion time information of the road section congestion information, whether the intercepted video segments have traffic accidents or not is judged, and if the traffic accidents occur, the traffic types of the video segments with the traffic accidents are further analyzed, so that the traffic accident processing results are conveniently analyzed.
Optionally, after the outputting the traffic accident type, the method further includes:
the responsibility judging sub-module is used for judging whether the responsibility judging condition is met or not based on the monitoring video, if so, inputting the monitoring video into a preset responsibility judging model corresponding to the accident type to obtain a responsibility judging conclusion;
if not, the monitoring video is sent to a traffic police for checking the site situation and judging the police or responsibility.
By adopting the technical scheme, the responsibility judgment conclusion is quickly obtained by judging the responsibility of the traffic accident according to the traffic accident type, so that drivers can conveniently and correspondingly process the responsibility judgment conclusion, and the efficiency of solving the traffic accident is improved.
Optionally, the report generating module includes:
the accident report generation sub-module is used for acquiring a traffic accident report template based on the accident type; the traffic accident report template is a video report template;
and inputting the monitoring video and the key frame image data into the video report template to generate a traffic accident report.
By adopting the technical scheme, the corresponding traffic report template is called through the traffic accident type, and then the traffic accident related monitoring video and the key frame image data are input into the corresponding position of the video report template to generate the traffic accident report, so that the occurrence condition of the traffic accident can be conveniently checked.
Optionally, the accident report generating submodule includes:
the display unit is used for acquiring the timestamp information corresponding to the key frame image data;
inserting hyperlinks of the responsibility judgment conclusion into the first accident video clips or the second accident video clips corresponding to the time stamps;
acquiring traffic terms analyzed according to the characteristic information;
and displaying the traffic terms in the traffic term areas corresponding to the characteristic information in the traffic accident report.
By adopting the technical scheme, the traffic terms are displayed at the corresponding positions of the traffic accident reports, so that a viewer can know the driving state of a driving vehicle when viewing the traffic accident reports, and can insert hyperlinks of responsibility judgment conclusions in the traffic accident reports, thereby facilitating the viewer to view the responsibility judgment conclusions when viewing the accident video clips.
Drawings
Fig. 1 is a block diagram of an intelligent traffic real-time monitoring system according to an embodiment of the present application.
FIG. 2 is a block diagram of the structure of a violation incident analysis module according to an embodiment of the application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
The embodiment of the application provides an intelligent traffic real-time monitoring system which can be executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, a cloud server for providing cloud computing service, the terminal equipment can be a desktop computer, a notebook computer and the like, but the intelligent traffic real-time monitoring system is not limited to the intelligent traffic real-time monitoring system.
Embodiments of the application are described in further detail below with reference to the drawings. As shown in fig. 1, an intelligent traffic real-time monitoring system 20 includes a driving information acquisition module 21, a violation accident analysis module 22, a report generation module 23, and a notification module 24, and the driving information acquisition module 21, the violation accident analysis module 22, the report generation module 23, and the notification module 24 are in communication connection.
A driving information acquisition module 21, configured to acquire monitoring information sent by the traffic monitoring device in real time;
in the present embodiment, the travel information acquisition module 21 includes a first photographing sub-module, a speed measurement sub-module, and a second photographing sub-module. The first shooting sub-module is used for recording the video of the running automobile in a certain road section to obtain a video; the second shooting sub-module is used for shooting the running automobile on a certain road section to obtain a shooting image; and the speed measuring sub-module is used for measuring the speed of the running automobile on a certain road section to obtain speed information.
The road section monitoring system is characterized in that a plurality of monitoring cameras are arranged on a road section and are generally arranged at higher positions such as an overpass and an overpass at an intersection, video and shooting images of a certain road section are captured through the visual angles of the fixed cameras, so that the visual field range and definition of video and shooting image acquisition are ensured, and the purpose of monitoring traffic running conditions of a specific road section is achieved. The speed measuring submodule can measure the speed of a running automobile on a road section in a mode of combining a speed measuring radar, a video recording video and a shooting image, the video recording video and the speed measuring radar detect the running speed of the automobile on the road section in a certain direction in real time, if the overspeed of the automobile is detected, the shooting operation of the second shooting submodule is started, the overspeed of the automobile is further identified, and the image evidence of the overspeed of the automobile is reserved.
In this embodiment, the second shooting sub-module is specifically configured to: firstly, acquiring a plurality of automobile polarized images under different polarized angles; secondly, orthogonal polarization components are extracted, and the incident angle is calculated based on the orthogonal polarization components; then, carrying out polarization filtering treatment on the plurality of automobile polarized images to obtain environment light corresponding to the plurality of automobile polarized images at different polarization angles one by one; and calculating target light by using the orthogonal polarization components, and reconstructing the target light based on the target light and a plurality of automobile polarization diagrams under a plurality of different polarization angles to obtain a shooting image. The method has the advantages that the method of acquiring the multiple automobile polarized images under different polarized angles is adopted to reconstruct the images, so that the shot images in the automobile are clearer, and the accuracy of analyzing the types of violations of drivers subsequently is improved.
The violation accident analysis module 22 is used for respectively storing the monitoring information into the corresponding traffic monitoring storage model according to the information category for storage; processing the monitoring information based on a preset classification preset processing algorithm of the traffic storage model to obtain traffic accident types corresponding to the monitoring information;
in this embodiment, a plurality of traffic monitoring storage models are set, and the monitoring storage models can be divided according to different types of monitoring information, for example, video information is stored in one storage model, shot image information is stored in one storage model, and speed measurement information is stored in one storage model, so that different types of monitoring information can be searched conveniently. Of course, the traffic monitoring information storage model may also be established according to the date, and is not limited thereto.
Specifically, the violation accident analysis module 22 includes a violation analysis sub-module 221, where the violation analysis sub-module 221 is configured to convert a captured image into a gray scale map; binarizing gray scale to obtain an image to be identified, so that the shot image is clearer, and the feature information of feature extraction of the shot image is more accurate; and then, carrying out feature extraction on the image to be identified according to a preset violation feature algorithm, and determining the traffic violation type corresponding to the shot image based on the combination of the extracted feature information and the speed information, so that the determination of the traffic violation type is more accurate. It should be noted that, the method for extracting the features of the image to be identified is the prior art in the field, and will not be described herein.
Since traffic accidents may occur in continuous traffic violations or there is a possibility that traffic accidents often occur on traffic roads, and after the traffic accidents occur, the accident analysis module 22 analyzes traffic accident behaviors in addition to the analysis of traffic offences, and as an optional real-time manner of this embodiment, the accident analysis module 22 further includes a first accident analysis sub-module 222, a second accident analysis sub-module 223 and a responsibility determination sub-module 224.
A first accident analysis sub-module 222 for acquiring an alarm call time of a driving vehicle accident; intercepting video based on the alarm telephone time and a first preset time intercepting strategy to obtain a first accident video clip; performing frame extraction processing on the first accident video segment to obtain a plurality of frame image data; and inputting the plurality of frame image data into the accident identification model, and outputting the traffic accident type. In this embodiment, the first preset time interception policy may be set according to historical time experience data for viewing the video.
The video is intercepted by the time of the traffic accident alarming telephone, so that the acquisition of the traffic accident video is more accurate, and the traffic accident handling result is convenient to analyze by carrying out frame extraction processing on the video and analyzing the traffic accident type.
A second accident sub-analysis sub-module 223, configured to obtain road section congestion information, where the congestion information includes congestion time; intercepting video based on the congestion time and a second preset time intercepting strategy to obtain a second accident video segment; intercepting a plurality of characteristic images in the second accident video clip according to a third preset time intercepting strategy; extracting features of the plurality of feature images, and judging whether traffic accidents occur or not according to the extracted feature information; if a traffic accident occurs, performing frame extraction processing on the second accident video segment to obtain a plurality of frame image data; and inputting the plurality of frame image data into the accident identification model, and outputting the traffic accident type.
In this embodiment, the congestion information may be obtained by acquiring GPS data of vehicles, identifying a road congestion area according to the number change of vehicles in the road intersection area, generating a position and a range of the combined congestion area in the form of landmarks and ranges, and recording congestion time when congestion occurs.
The second preset time strategy is also set according to historical time experience data for viewing video, and video clips before congestion and video clips after congestion can be intercepted. The third preset time policy may set the number of times of capturing the feature image according to the time interval.
The accident recognition model may be a software framework capable of realizing recognition characteristic information of a deep learning algorithm, and includes: R-CNN, SPP-NET, fast R-CNN, yolov1, yolov2, yolov3; and enabling techniques for tracking vehicles in video, comprising: BOOSTING, MIL, KCF, CSRT, medianFlow, TLD, MOSSE, GOTURN, etc.
Intercepting video by utilizing congestion time information of road section congestion information, judging whether the intercepted video segments have traffic accidents, and if so, further analyzing traffic types of the video segments with the traffic accidents, thereby being convenient for analyzing traffic accident processing results.
As an optional implementation manner of this embodiment, after outputting the traffic accident type, the method further includes:
the responsibility judging sub-module 224 is configured to judge whether the responsibility judging condition is satisfied based on the monitoring video, and if so, input the monitoring video into a preset responsibility judging model corresponding to the accident type to obtain a responsibility judging conclusion; if not, the monitoring video is sent to the traffic police for checking the site situation and judging the police or responsibility.
In the present embodiment, judging whether the responsibility judgment condition is satisfied may be based on the accident type classification, and the traffic accident (for example, small scratch) that is not serious may be set to satisfy the responsibility judgment condition. The preset responsibility judgment model can be a trained neural network model.
By judging the responsibility of the traffic accident according to the traffic accident type, the responsibility judgment conclusion is quickly obtained, the driver can conveniently and correspondingly process according to the responsibility judgment conclusion, and the efficiency of solving the traffic accident is improved. If the condition of responsibility judgment is not met, the monitoring video is sent to the traffic police, and the existing site situation evidence and the like are checked through terminals such as mobile phones and the like in the process of the traffic police to know the accident situation in advance so as to quickly make judgment after arriving at the site.
After the traffic violations or traffic incidents are analyzed by the violation incident analysis module 22, the report generation module 23 generates a corresponding report for viewing by the driver or traffic police.
The report generating module 23 is configured to obtain a traffic violation report template based on the traffic accident type, and fill monitoring information into the traffic violation report template to generate a violation report;
in this embodiment, for a driving vehicle with traffic violations, after the violation analysis sub-module 221 analyzes the violations, a violation report template is obtained according to the types of violations, and a traffic violation report is generated according to the photographed images and video information of the violations, and the rule breaking terms and correct driving modes divided according to the types of violations are set in the traffic violation report template, so that the driver can normalize the driving behavior after viewing the traffic violation report.
The report generating module 23 also generates a traffic accident report for the driving vehicle having the traffic accident, so that the driver or the traffic police can check the traffic accident, and the accident handling efficiency is improved.
As an alternative embodiment, the report generating module 23 further includes:
the accident report generation sub-module is used for acquiring a traffic accident report template based on the accident types; the traffic accident report template is a video report template; and inputting the monitoring video and the key frame image data into a video report template to generate a traffic accident report.
The accident report generation submodule comprises a display unit and a display unit, wherein the display unit is used for acquiring time stamp information corresponding to key frame image data; inserting a hyperlink of a responsibility judgment conclusion in the first accident video clip or the second accident video clip corresponding to the time stamp; acquiring traffic terms analyzed according to the characteristic information; and displaying the traffic terms in the traffic term areas corresponding to the characteristic information in the traffic accident report.
By displaying the traffic terms at the corresponding positions of the traffic accident reports, a viewer can know the driving state of the driving vehicle conveniently when viewing the traffic accident reports, and hyperlinks of responsibility judgment conclusions are inserted into the traffic accident reports, so that the viewer can view the responsibility judgment conclusions when viewing the accident video clips.
The notification module 23 is configured to obtain information of the vehicle with violation, and send a traffic violation report or a traffic accident report to a corresponding vehicle driver or a traffic police.
The system analyzes the monitoring information acquired in real time, analyzes the type of the violation or the accident of the monitoring information of the monitored traffic violation or the traffic accident, generates a corresponding traffic violation report for the vehicle with the violation, and sends the report to the driver in real time, so that the driver receives the violation report in time after the traffic violation, checks the rule of the violation, the monitoring information of the violation and the correct driving mode, and reduces the occurrence of the condition that the driver continues to perform the driving violation in the process of the driving with the violation, thereby reducing the probability of the traffic accident. For vehicles with traffic accidents, traffic accident reports are received in time after the traffic accidents occur, traffic accident conclusions are checked, and the efficiency of processing the traffic accidents is improved.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the application is not limited to the specific combinations of the features described above, but also covers other embodiments which may be formed by any combination of the features described above or their equivalents without departing from the spirit of the application. Such as the above-mentioned features and the technical features having similar functions (but not limited to) applied for in the present application are replaced with each other.
Claims (8)
1. An intelligent traffic real-time monitoring system is characterized by comprising
The traffic monitoring system comprises a driving information acquisition module, a traffic monitoring device and a traffic monitoring module, wherein the driving information acquisition module is used for acquiring monitoring information sent by the traffic monitoring device in real time, and the monitoring information comprises video, speed measurement information and shot images;
the violation accident analysis module is used for respectively storing the monitoring information into a corresponding traffic monitoring storage model according to the monitoring type for storage; processing the monitoring information based on a preset processing algorithm of the traffic storage model to obtain traffic violation types corresponding to the monitoring information;
the report generation module is used for acquiring a violation report template based on the traffic violation type; generating a traffic violation report based on the violation report template and the monitoring information; wherein the traffic violation report template comprises violation terms and correct driving modes;
and the notification module is used for acquiring the information of the violation vehicle and sending the traffic violation report to a driver of the violation vehicle.
2. The system of claim 1, wherein the travel information acquisition module comprises:
the first shooting sub-module is used for recording the video of the running automobile in a certain road section to obtain a video;
the speed measuring sub-module is used for measuring the speed of the running automobile on a certain road section to obtain speed information;
the second shooting sub-module is used for shooting the running automobile on a certain road section to obtain a shooting image;
the second shooting sub-module is specifically used for acquiring a plurality of automobile polarized images under different polarized angles; extracting orthogonal polarization components and calculating an incident angle based on the orthogonal polarization components; performing polarization filtering treatment on the multiple automobile polarized images to obtain environment light corresponding to the multiple automobile polarized images at different polarization angles one by one; and calculating target light by using the orthogonal polarization components, and reconstructing the target light based on the target light and a plurality of automobile polarization diagrams under a plurality of different polarization angles to obtain a shooting image.
3. The system of claim 1 or 2, wherein the violation incident analysis module comprises:
the violation analysis sub-module is used for converting the shot image into a gray level image; binarizing the gray level to obtain an image to be identified; and extracting the characteristics of the image to be identified according to a preset violation characteristic algorithm, and determining the traffic violation type corresponding to the photographed image based on the combination of the extracted characteristic information and the speed information.
4. The system of claim 1 or 2, wherein the violation incident analysis module further comprises:
the first accident analysis submodule is used for acquiring the alarm telephone time of the driving vehicle accident;
intercepting the video based on the alarm telephone time and a first preset time intercepting strategy to obtain a first event video segment;
performing frame extraction processing on the first event video segment to obtain a plurality of frame image data;
and inputting the plurality of frame image data into an accident identification model, and outputting the traffic accident type.
5. The system of claim 1 or 2, wherein the violation incident analysis module further comprises:
the second accident sub-analysis sub-module is used for acquiring road section congestion information, wherein the congestion information comprises congestion time;
intercepting the video based on the congestion time and a second preset time intercepting strategy to obtain a second accident video segment;
intercepting a plurality of characteristic images in the second accident video clip according to a third preset time intercepting strategy;
extracting the characteristics of the plurality of characteristic images, and judging whether traffic accidents occur or not according to the extracted characteristic information;
if a traffic accident occurs, performing frame extraction processing on the second accident video segment to obtain a plurality of frame image data;
and inputting the plurality of frame image data into an accident identification model, and outputting the traffic accident type.
6. The system according to claim 4 or 5, further comprising, after the outputting of the traffic accident category:
the responsibility judging sub-module is used for judging whether the responsibility judging condition is met or not based on the monitoring video, if so, inputting the monitoring video into a preset responsibility judging model corresponding to the accident type to obtain a responsibility judging conclusion;
if not, the monitoring video is sent to a traffic police for checking the site situation and judging the police or responsibility.
7. The system of claim 4 or 5 or 6, wherein the report generating module comprises:
the accident report generation sub-module is used for acquiring a traffic accident report template based on the accident type; the traffic accident report template is a video report template;
and inputting the monitoring video and the key frame image data into the video report template to generate a traffic accident report.
8. The system of claim 7, wherein the incident report generation submodule includes:
the display unit is used for acquiring the timestamp information corresponding to the key frame image data;
inserting hyperlinks of the responsibility judgment conclusion into the first accident video clips or the second accident video clips corresponding to the time stamps;
acquiring traffic terms analyzed according to the characteristic information;
and displaying the traffic terms in the traffic term areas corresponding to the characteristic information in the traffic accident report.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310022016.1A CN116311901A (en) | 2023-01-07 | 2023-01-07 | Intelligent traffic real-time monitoring system |
| CN2023100220161 | 2023-01-07 |
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| CN202310927357.3A Pending CN116913099A (en) | 2023-01-07 | 2023-07-26 | Intelligent traffic real-time monitoring system |
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