CN116363334A - Intelligent traffic simulation experiment method and system - Google Patents
Intelligent traffic simulation experiment method and system Download PDFInfo
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Abstract
The invention discloses an intelligent traffic simulation experiment method and system, wherein the experiment method comprises the following steps: establishing a traffic experiment model database; acquiring a corresponding traffic experiment model from an experiment model database according to traffic experiment requirements; substituting the test requirement parameters into the acquired traffic experiment model to obtain traffic experiment data to be operated; acquiring experimental environment image data, and obtaining traffic experiment data according to the experimental environment image data and traffic experiment data to be operated; and carrying out data analysis on the traffic experiment data to obtain a traffic strategy analysis result. The traffic laboratory can be switched rapidly according to experimental scenes.
Description
Technical Field
The invention belongs to the technical field of scientific and digital traffic, and relates to an intelligent traffic simulation experiment method and system.
Background
The intelligent transportation system (Intelligent Traffic System, ITS for short) is also called an intelligent transportation system (Intelligent Transportation System), which is an integrated transportation system for effectively and comprehensively applying advanced scientific technologies (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operation study, artificial intelligence and the like) to transportation, service control and vehicle manufacturing, and enhancing the connection among vehicles, roads and users, thereby ensuring safety, improving efficiency, improving environment and saving energy. The application range comprises airport and station passenger flow guiding systems, urban traffic intelligent dispatching systems, expressway intelligent dispatching systems, operation vehicle dispatching management systems and the like.
The prior art Chinese invention patent CN201910959162.0 discloses a traffic knowledge cognition dynamic sand table system for education based on vision, which comprises a sand table model, a sand table master control analysis unit and a plurality of trolleys; the sand table system comprises a road model, a traffic signal lamp model and a traffic sign model, the sand table main control analysis unit comprises a liquid crystal display screen, a central processing unit and a communication module A, the trolley comprises a trolley body, and a communication module B, a camera module and a motion control unit which are arranged on the trolley body, and the motion control unit is used for controlling the motion of the trolley body; the system can provide a dynamic traffic knowledge cognitive sand table system with real-time visual field display of vehicles, can greatly improve intuitiveness and interestingness in the education process and gives vivid and visual learning experience to children;
however, there is a demand that the modern intelligent traffic system can not be adapted to the fast switching of specific application scenes, and the application scenes of the intelligent traffic system are wide, for example, when students perform intelligent traffic simulation experiments in schools, the intelligent scheduling system is used for simulating high-speed functions in the first class, the passenger flow guiding system is used for simulating stations in the second class, the switching time of the first class and the second class is only 15 minutes, and meanwhile, the simulation experiment equipment in the whole laboratory still needs fast layout, so that the prior art can not realize the demand.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an intelligent traffic simulation experiment method and system, and a traffic laboratory can rapidly switch according to an experiment scene.
In order to achieve the above purpose, the invention is realized by adopting the following technical scheme:
an intelligent traffic simulation experiment method comprises the following steps:
establishing a traffic experiment model database;
acquiring a corresponding traffic experiment model from an experiment model database according to traffic experiment requirements;
substituting the test requirement parameters into the acquired traffic experiment model to obtain traffic experiment data to be operated;
acquiring experimental environment image data, and obtaining traffic experiment data according to the experimental environment image data and traffic experiment data to be operated;
and carrying out data analysis on the traffic experiment data to obtain a traffic strategy analysis result.
Optionally, the method further comprises: and storing the traffic strategy analysis result and the data generated in the experimental process into a traffic experimental model database.
Optionally, the traffic experiment model database comprises a traffic road condition environment model, a vehicle and a pedestrian model; when a traffic experiment model database is established, an index label is established for the traffic experiment model in the traffic experiment model database, and a mapping relation is established between the index label and the traffic experiment model.
Optionally, obtaining the data to be run of the traffic experiment includes:
substituting the test requirement parameters into the acquired traffic experiment model to obtain a plurality of groups of test results under different scenes of the traffic experiment model;
according to the multiple groups of test results, selecting a traffic experiment model which is preferentially used for the test;
the test requirement parameters are input into a plurality of groups of traffic experiment models in different scenes in batches in advance, the test requirement parameters are classified, and the test requirement parameters are ordered according to the use requirement to obtain the data to be operated of the traffic experiment.
Optionally, obtaining traffic experiment data includes:
carrying out video image recognition and tracking positioning processing on pictures acquired by a camera, establishing a physical coordinate system, carrying out traffic facility coordinate positioning on video images, and establishing a traffic experiment simulation map;
setting the virtual personnel quantity parameter, the virtual vehicle quantity parameter and the virtual personnel and virtual vehicle positioning positions to obtain a simulation test dynamic AR image;
and carrying out data fusion rendering processing on the acquired environmental parameter data and the simulation test dynamic AR image, and constructing a traffic experiment virtual scene, wherein the environmental parameter data comprises climate and road condition data, temperature and road condition data and brightness and road condition data.
Optionally, the data analysis includes:
according to the historical traffic experiment data, the traffic experiment environment is adjusted and the experiment environment image data are collected again to obtain a corrected traffic experiment environment, and the traffic experiment test data are obtained by fusing the traffic experiment environment with the road historical personnel and the traffic experiment environment;
if traffic experiment test data personnel and vehicles are corrected and no unblocked condition appears in the road, setting virtual violation probability and weather environment influence factors for a traffic experiment model, and obtaining a traffic strategy analysis result.
An intelligent traffic simulation experiment system, comprising:
the acquisition module is used for establishing a traffic experiment model;
the input module is used for inputting the test requirement parameters to obtain the data to be operated of the traffic experiment;
the data fusion module is used for acquiring experimental environment image data and obtaining traffic experiment data according to the experimental environment image data and the traffic experiment data to be operated;
the data analysis module is used for analyzing the traffic experiment data to obtain a traffic strategy analysis result;
the data storage module is used for storing the traffic strategy analysis result and the data generated in the experimental process to form an experimental data query database.
Optionally, the acquiring module includes:
the system comprises a database construction unit, a traffic experiment model database and a control unit, wherein the database construction unit is used for constructing a traffic experiment model database, and the traffic experiment model comprises a traffic road condition environment model, a vehicle and pedestrian model, such as an airport experiment model, a station passenger flow dredging system experiment model, an urban traffic intelligent scheduling experiment model, an expressway intelligent scheduling system experiment model and an operation vehicle scheduling management experiment model;
the matching unit is used for calling a traffic experiment model which is in the traffic experiment model database and is suitable for traffic experiment requirements;
and the data indexing unit is used for establishing an index label for the traffic experiment model in the traffic experiment model database and establishing a mapping relation between the index label and the traffic experiment model.
Optionally, the input module includes:
the test unit is used for testing the test requirement parameters to obtain a plurality of groups of test results under different scenes of the traffic experiment model;
the optimizing and sequencing unit is used for selecting a traffic experiment model which is preferentially used for testing according to the multiple groups of test results;
the multiple groups of test units are used for inputting the test requirement parameters into multiple groups of traffic experiment models in different scenes in batches in advance, classifying the test requirement parameters, and sorting the test requirement parameters according to the use requirements to obtain the data to be operated of the traffic experiment.
Optionally, the data fusion module includes:
the data acquisition unit is used for carrying out video image identification and tracking positioning processing on pictures acquired by the camera, establishing a physical coordinate system, carrying out traffic facility coordinate positioning on the video images and establishing a traffic experiment simulation map;
the image construction unit is used for setting the virtual personnel quantity parameter, the virtual vehicle quantity parameter and the virtual personnel and virtual vehicle positioning positions to obtain a simulation test dynamic AR image;
the scene construction unit is used for collecting environment parameter data and simulating test dynamic AR images to perform data fusion rendering processing and constructing a traffic experiment virtual scene, wherein the environment parameter data comprises climate and road condition data, temperature and road condition data and brightness and road condition data.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an intelligent traffic laboratory system and a use method thereof, wherein a plurality of traffic experiment models are established according to actual application scenes, so that a user can use AR equipment to combine with traffic experiment models established according to the actual application scenes in a laboratory to carry out experimental detection on the set traffic and traffic flow, the traffic experiment models are selected and parameters are set according to experimental requirements, when traffic experiments are carried out, corresponding experiment models can be selected in a traffic experiment model database, and corresponding parameters are set, so that the problem that the conventional traffic laboratory cannot be switched rapidly according to the experimental scenes is solved.
Drawings
Fig. 1 is a flowchart of an intelligent traffic simulation experiment method provided by an embodiment of the invention.
Description of the embodiments
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", etc. may explicitly or implicitly include one or more such feature. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art in a specific case.
Example 1
As shown in fig. 1, an intelligent traffic simulation experiment method includes:
s1, establishing a traffic experiment model database, wherein the traffic experiment model database comprises traffic road condition environment models, vehicles and pedestrian models, establishing index labels for traffic experiment models in the traffic experiment model database when the traffic experiment model database is established, and establishing a mapping relation between the index labels and the traffic experiment models; according to traffic experiment requirements, calling a traffic experiment model which is suitable for a traffic experiment model database through an index tag;
the user side mobile equipment is connected with a camera responsible for video data acquisition through a two-dimensional code, video data acquired by the camera are transmitted to the server side through the user side mobile equipment, and the server side establishes a traffic experiment model through image data of a traffic road, a signal lamp, a traffic overpass, a vehicle, a pedestrian and the like which are established by acquired laboratory students according to traffic experiment application scenes through a background control end;
s2, substituting the test requirement parameters into the acquired traffic experiment models to obtain a plurality of groups of test results under different scenes of the traffic experiment models, selecting the traffic experiment models which are preferentially used for testing according to the plurality of groups of test results, inputting the test requirement parameters into the traffic experiment models of the plurality of groups of different scenes in advance in batches, classifying the test requirement parameters, sorting according to the use requirements to obtain traffic experiment data to be operated, and rapidly selecting and switching the experiment data according to the application scene requirements during the experiment to save the time of the traffic experiment;
s3, collecting experimental environment image data, and combining the experimental environment image data with data to be operated of a traffic experiment to obtain traffic experiment data; the method comprises the steps of carrying out video image recognition and tracking positioning processing on pictures acquired by a camera, establishing a physical coordinate system, carrying out traffic facility coordinate positioning on video images, and establishing a traffic experiment simulation map; setting the virtual personnel quantity parameter, the virtual vehicle quantity parameter and the virtual personnel and virtual vehicle positioning positions to obtain a simulation test dynamic AR image; collecting environment parameter data and simulating test dynamic AR images to perform data fusion rendering processing, and constructing a traffic experiment virtual scene, wherein the environment parameter data comprises climate and road condition data, temperature and road condition data and brightness and road condition data;
the user terminal mobile device is connected with a camera responsible for video data acquisition through the two-dimension code, the video data acquired by the camera are transmitted to the server terminal through the user terminal mobile device, the server terminal establishes a traffic experiment model through a background control terminal according to traffic roads built by students in a laboratory and image data such as traffic experiment application scenes, signal lamps, traffic overpasses, vehicles, pedestrians and the like, the traffic experiment model is operated, the traffic experiment data are obtained, the traffic experiment data show images through AR equipment of the user terminal, the user observes an experimental process through the images shown by the AR equipment, for example, whether the vehicles are jammed on roads or not, whether the roads designed by the user are reasonable or not is verified, and meanwhile, the flow of the vehicles on the roads is acquired. When the camera is placed on the ground, the user terminal AR equipment screen can display the scene of traffic and AR animation effect which are arranged in a real laboratory, the scene arranged in the real laboratory adopts a block-shaped object, the block-shaped object is provided with a two-dimension code, and virtual images, such as traffic lights, morals, bridges and the like, appear after the AR equipment scans the two-dimension code of the block-shaped object;
s4, carrying out data analysis on the traffic experimental data to obtain a traffic strategy analysis result, and if the automobiles and pedestrians on the image road presented by the AR equipment at the user end are jammed, giving out advice reminding of the road design to be adjusted by combining the collected road traffic data; the method comprises the steps of obtaining historical traffic experiment data; counting the road historic personnel and the vehicle flow according to the historical traffic experimental data, adjusting the traffic experimental environment, and collecting the experimental environment image data again to obtain a corrected traffic experimental environment, and fusing the road historic personnel and the vehicle flow with the corrected traffic experimental environment to obtain corrected traffic experimental test data; if traffic experiment test data personnel and vehicles are corrected and no non-smooth condition appears in the road, setting virtual violation probability and weather environment influence factors for a traffic experiment model to obtain a traffic strategy analysis result;
according to the method, a plurality of traffic experiment models are established according to practical application scenes and combined with an AR technology, students use AR equipment in laboratories and combine with traffic experiment models established according to practical application scenes, set human flow and vehicle flow are subjected to experimental detection, the traffic experiment models are selected and parameters are set according to experimental requirements, when the students carry out traffic experiments, for example, expressway intelligent scheduling system experiments are required, expressway intelligent scheduling system experiment models can be selected in a traffic experiment model database, if other types of traffic experiments are required to be carried out, the traffic experiment models are selected in the traffic experiment model database, and then corresponding parameters are set, so that the problem that the existing traffic laboratories cannot be rapidly switched according to experimental scenes is solved;
s5, storing the traffic strategy analysis result and data generated in the experimental process into a blockchain, and establishing an experimental data query database;
in order to avoid the false creation of experimental data, the traffic strategy analysis result and the data generated in the experimental process are stored in the blockchain, the data stored in the blockchain can only be inquired and cannot be deleted and modified, the traffic experimental data stored in the blockchain is provided with a hash value corresponding to the data, and the experimental data inquired by the experimental data inquiry database has authenticity.
Example two
As shown in fig. 1, according to the first embodiment of the present invention, an intelligent traffic simulation experiment method is provided, where the intelligent traffic simulation experiment system includes an acquisition module, an input module, a data fusion module, a data analysis module, and a data storage module;
the acquisition module is used for establishing an acquisition module of a traffic experiment model, and the acquisition module comprises:
the system comprises a database construction unit, a traffic experiment model database and a control unit, wherein the database construction unit is used for constructing a traffic experiment model database, and the traffic experiment model comprises a traffic road condition environment model, a vehicle and pedestrian model, such as an airport experiment model, a station passenger flow dredging system experiment model, an urban traffic intelligent scheduling experiment model, an expressway intelligent scheduling system experiment model and an operation vehicle scheduling management experiment model;
the matching unit is used for calling a traffic experiment model which is in the traffic experiment model database and is suitable for traffic experiment requirements;
and the data indexing unit is used for establishing an index label for the traffic experiment model in the traffic experiment model database and establishing a mapping relation between the index label and the traffic experiment model.
The input module is used for inputting test requirement parameters to obtain data to be operated of the traffic experiment, and comprises:
the test unit is used for testing the test requirement parameters to obtain a plurality of groups of test results under different scenes of the traffic experiment model;
the optimizing and sequencing unit is used for selecting a traffic experiment model which is preferentially used for testing according to the multiple groups of test results;
the multiple groups of test units are used for inputting the test requirement parameters into multiple groups of traffic experiment models in different scenes in batches in advance, classifying the test requirement parameters, and sorting the test requirement parameters according to the use requirements to obtain the data to be operated of the traffic experiment.
The data fusion module is used for acquiring experimental environment image data and obtaining traffic experiment data according to the experimental environment image data and the traffic experiment data to be operated, and comprises:
the data acquisition unit is used for carrying out video image identification and tracking positioning processing on pictures acquired by the camera, establishing a physical coordinate system, carrying out traffic facility coordinate positioning on the video images and establishing a traffic experiment simulation map;
the image construction unit is used for setting the virtual personnel quantity parameter, the virtual vehicle quantity parameter and the virtual personnel and virtual vehicle positioning positions to obtain a simulation test dynamic AR image;
the scene construction unit is used for collecting environment parameter data and simulating test dynamic AR images to perform data fusion rendering processing and constructing a traffic experiment virtual scene, wherein the environment parameter data comprises climate and road condition data, temperature and road condition data and brightness and road condition data;
the data analysis module is used for analyzing traffic experiment data to obtain traffic strategy analysis results;
the data storage module is used for storing traffic strategy analysis results and data generated in the experimental process to form an experimental data query database.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (10)
1. The intelligent traffic simulation experiment method is characterized by comprising the following steps of:
establishing a traffic experiment model database;
acquiring a corresponding traffic experiment model from an experiment model database according to traffic experiment requirements;
substituting the test requirement parameters into the acquired traffic experiment model to obtain traffic experiment data to be operated;
acquiring experimental environment image data, and obtaining traffic experiment data according to the experimental environment image data and traffic experiment data to be operated;
and carrying out data analysis on the traffic experiment data to obtain a traffic strategy analysis result.
2. The intelligent traffic simulation experiment method according to claim 1, further comprising: and storing the traffic strategy analysis result and the data generated in the experimental process into a traffic experimental model database.
3. The intelligent traffic simulation experiment method according to claim 1, wherein: the traffic experiment model database comprises a traffic road condition environment model, a vehicle and a pedestrian model; when a traffic experiment model database is established, an index label is established for the traffic experiment model in the traffic experiment model database, and a mapping relation is established between the index label and the traffic experiment model.
4. The intelligent traffic simulation experiment method according to claim 1, wherein obtaining data to be run of the traffic experiment comprises:
substituting the test requirement parameters into the acquired traffic experiment model to obtain a plurality of groups of test results under different scenes of the traffic experiment model;
according to the multiple groups of test results, selecting a traffic experiment model which is preferentially used for the test;
the test requirement parameters are input into a plurality of groups of traffic experiment models in different scenes in batches in advance, the test requirement parameters are classified, and the test requirement parameters are ordered according to the use requirement to obtain the data to be operated of the traffic experiment.
5. The intelligent traffic simulation experiment method according to claim 1, wherein obtaining traffic experiment data comprises:
carrying out video image recognition and tracking positioning processing on pictures acquired by a camera, establishing a physical coordinate system, carrying out traffic facility coordinate positioning on video images, and establishing a traffic experiment simulation map;
setting the virtual personnel quantity parameter, the virtual vehicle quantity parameter and the virtual personnel and virtual vehicle positioning positions to obtain a simulation test dynamic AR image;
and carrying out data fusion rendering processing on the acquired environmental parameter data and the simulation test dynamic AR image, and constructing a traffic experiment virtual scene, wherein the environmental parameter data comprises climate and road condition data, temperature and road condition data and brightness and road condition data.
6. The intelligent traffic simulation experiment method according to claim 1, wherein the data analysis comprises:
according to the historical traffic experiment data, the traffic experiment environment is adjusted and the experiment environment image data are collected again to obtain a corrected traffic experiment environment, and the traffic experiment test data are obtained by fusing the traffic experiment environment with the road historical personnel and the traffic experiment environment;
if traffic experiment test data personnel and vehicles are corrected and no unblocked condition appears in the road, setting virtual violation probability and weather environment influence factors for a traffic experiment model, and obtaining a traffic strategy analysis result.
7. An experimental system of the intelligent transportation simulation experimental method according to any one of claims 2 to 6, comprising:
the acquisition module is used for establishing a traffic experiment model;
the input module is used for inputting the test requirement parameters to obtain the data to be operated of the traffic experiment;
the data fusion module is used for acquiring experimental environment image data and obtaining traffic experiment data according to the experimental environment image data and the traffic experiment data to be operated;
the data analysis module is used for analyzing the traffic experiment data to obtain a traffic strategy analysis result;
the data storage module is used for storing the traffic strategy analysis result and the data generated in the experimental process to form an experimental data query database.
8. The experimental system of an intelligent traffic simulation experimental method according to claim 7, wherein the acquisition module comprises:
the system comprises a database construction unit, a traffic experiment model database and a control unit, wherein the database construction unit is used for constructing a traffic experiment model database, and the traffic experiment model comprises a traffic road condition environment model, a vehicle and pedestrian model, such as an airport experiment model, a station passenger flow dredging system experiment model, an urban traffic intelligent scheduling experiment model, an expressway intelligent scheduling system experiment model and an operation vehicle scheduling management experiment model;
the matching unit is used for calling a traffic experiment model which is in the traffic experiment model database and is suitable for traffic experiment requirements;
and the data indexing unit is used for establishing an index label for the traffic experiment model in the traffic experiment model database and establishing a mapping relation between the index label and the traffic experiment model.
9. The experimental system of an intelligent transportation simulation experimental method according to claim 7, wherein the input module comprises:
the test unit is used for testing the test requirement parameters to obtain a plurality of groups of test results under different scenes of the traffic experiment model;
the optimizing and sequencing unit is used for selecting a traffic experiment model which is preferentially used for testing according to the multiple groups of test results;
the multiple groups of test units are used for inputting the test requirement parameters into multiple groups of traffic experiment models in different scenes in batches in advance, classifying the test requirement parameters, and sorting the test requirement parameters according to the use requirements to obtain the data to be operated of the traffic experiment.
10. The experimental system of an intelligent transportation simulation experimental method according to claim 7, wherein the data fusion module comprises:
the data acquisition unit is used for carrying out video image identification and tracking positioning processing on pictures acquired by the camera, establishing a physical coordinate system, carrying out traffic facility coordinate positioning on the video images and establishing a traffic experiment simulation map;
the image construction unit is used for setting the virtual personnel quantity parameter, the virtual vehicle quantity parameter and the virtual personnel and virtual vehicle positioning positions to obtain a simulation test dynamic AR image;
the scene construction unit is used for collecting environment parameter data and simulating test dynamic AR images to perform data fusion rendering processing and constructing a traffic experiment virtual scene, wherein the environment parameter data comprises climate and road condition data, temperature and road condition data and brightness and road condition data.
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| CN202310015725.7A CN116363334A (en) | 2023-01-06 | 2023-01-06 | Intelligent traffic simulation experiment method and system |
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