CN118193613A - Intelligent analysis method and system for OD (optical density) of expressway vehicle - Google Patents
Intelligent analysis method and system for OD (optical density) of expressway vehicle Download PDFInfo
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Abstract
The embodiment of the invention discloses an intelligent analysis method and an intelligent analysis system for an expressway vehicle OD, which are used for acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data; integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range; responding to a selection request of the query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition; and classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of the high-speed management platform. The intelligent analysis method for the expressway vehicle OD solves the problem that the expressway vehicle OD cannot be analyzed intelligently in the prior art.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an intelligent analysis method, an intelligent analysis system, electronic equipment and a storage medium for an expressway vehicle OD.
Background
The OD is collectively referred to as "Origin and Destination", i.e., the origin and destination. In the expressway OD survey, "O" represents the place of departure, and "D" represents the destination of arrival; the analysis of the expressway vehicle OD is performed to understand the travel demands of people in the target area, the frequency of use of vehicles, and the condition of cargo transportation.
In the prior art, the analysis of the road vehicle OD has the problems of slow information flow, incomplete information, information sharing and lack of data analysis.
Therefore, a method capable of intelligently and precisely analyzing the OD of the road vehicle is needed.
Disclosure of Invention
The embodiment of the invention aims to provide an intelligent analysis method, an intelligent analysis system, electronic equipment and a storage medium for an expressway vehicle OD, which are used for solving the problem that the expressway vehicle cannot be analyzed intelligently in the prior art.
In order to achieve the above objective, an embodiment of the present invention provides an intelligent analysis method for an OD of an expressway vehicle, including:
acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data;
Building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model;
Integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range;
Responding to a selection request of a query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition;
and classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform.
Based on the technical scheme, the invention can also be improved as follows:
further, the building of the vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model, including:
dividing the ETC portal traffic data, charging detail data and monitoring data into a training set, a verification set and a test set;
Training the vehicle OD data analysis model based on the training set;
Performing performance evaluation on the trained vehicle OD data analysis model based on the verification set to obtain a vehicle OD data analysis model meeting performance conditions;
And evaluating an analysis result of the vehicle OD data analysis model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the vehicle OD data analysis model.
Further, the topic module comprises a toll station total travel number statistics module, a traffic flow GIS map display module, an OD pair set accumulation size ranking module, a travel time distribution analysis module, a travel distance distribution analysis module and a vehicle OD scale distribution analysis module.
Further, the classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform includes:
screening and classifying the vehicle OD data based on the departure point and the destination of the vehicle OD data to obtain classified data;
constructing a highway traffic OD pair set based on the classification data;
ranking the expressway traffic OD pairs in real time according to the size sequence of each classification data;
and displaying the real-time ranking on the OD pair set accumulated size ranking module.
Further, the classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform, further includes:
and responding to a configuration request displayed by the traffic flow GIS map, and configuring the traffic flow GIS map, wherein the configuration comprises a migration map line fine range, a migration map circular radius range and a migration map value range screening range.
Further, the classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform, further includes:
And displaying real-time vehicle OD data of the target area through the traffic flow GIS map display module.
Further, the intelligent analysis method of the expressway vehicle OD further comprises the following steps:
And displaying travel time distribution, travel distance distribution and vehicle OD scale distribution through the line graph.
An intelligent analysis system for an expressway vehicle OD, comprising:
The acquisition module is used for acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data;
The building module is used for building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model;
The integration module is used for integrating the vehicle OD data analysis model into a high-speed management platform and configuring query conditions and a topic module for the high-speed management platform, wherein the query conditions comprise a regional range and a time range;
The analysis module is used for responding to a selection request of the query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, inputting a trained vehicle OD data analysis model, and obtaining vehicle OD data corresponding to the query condition;
And the display module is used for classifying the vehicle OD data based on the topic module to obtain classification results, and displaying the classification results on a front-end page of the high-speed management platform.
An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method when the computer program is executed.
A non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method.
The embodiment of the invention has the following advantages:
According to the intelligent analysis method for the expressway vehicle OD, a certain amount of ETC portal traffic data, charging detail data and monitoring data are obtained; building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model; integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range; responding to a selection request of a query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition; classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform; the method solves the problem that the OD of the expressway vehicle cannot be intelligently analyzed in the prior art.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those skilled in the art from this disclosure that the drawings described below are merely exemplary and that other embodiments may be derived from the drawings provided without undue effort.
The structures, proportions, sizes, etc. shown in the present specification are shown only for the purposes of illustration and description, and are not intended to limit the scope of the invention, which is defined by the claims, so that any structural modifications, changes in proportions, or adjustments of sizes, which do not affect the efficacy or the achievement of the present invention, should fall within the scope of the invention.
FIG. 1 is a flow chart of a method of intelligent analysis of an expressway vehicle OD of the present invention;
FIG. 2 is a block diagram of an intelligent analysis system for an expressway vehicle OD of the present invention;
fig. 3 is a schematic diagram of an entity structure of an electronic device according to the present invention.
Wherein the reference numerals are as follows:
the system comprises an acquisition module 10, a construction module 20, an integration module 30, an analysis module 40, a display module 50, an electronic device 60, a processor 601, a memory 602 and a bus 603.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Fig. 1 is a flowchart of an embodiment of an intelligent analysis method for an expressway vehicle OD, and as shown in fig. 1, the intelligent analysis method for an expressway vehicle OD provided by the embodiment of the invention includes the following steps:
s101, acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data;
Specifically, the ETC portal comprises an industrial personal computer, an antenna, license plate recognition equipment, an RSU, a PSAM and a cabinet, is a high-speed toll collection facility, and has the functions of segmented charging, flow investigation, video monitoring, overspeed screening and the like. After the automobile runs to the ETC portal, the system can automatically charge, and the charging is carried out according to the running mileage of the automobile.
The ETC portal system is designed to enable the expressway to pass more efficiently, and meanwhile, the driving path of the vehicle is recorded, so that convenience is brought to vehicle owners. The development of this technology will further increase the traffic efficiency of the highway.
The ETC portal traffic data contains fields including: charging license plate number, charging model code, portal HEX character string, portal name, portal station name, passing time, portal time, charging mileage, accumulated mileage before and accumulated mileage after transaction, toll station code, toll station Chinese name, county of toll station, portal number code, portal Chinese name, portal road name and whether the portal is provincial boundaries portal;
The charging detail data contains fields including: billing license plate number, billing vehicle model code, inbound number, inbound name, ingress time, egress number, egress name, and egress time.
S102, constructing a vehicle OD data analysis model, inputting ETC portal traffic data, charging detail data and monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model;
specifically, ETC portal traffic data and charging vehicle detail data are divided into a training set, a verification set and a test set;
Training the vehicle OD data analysis model based on the training set;
Performing performance evaluation on the trained vehicle OD data analysis model based on the verification set to obtain a vehicle OD data analysis model meeting performance conditions;
And evaluating an analysis result of the vehicle OD data analysis model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the vehicle OD data analysis model.
Performing performance evaluation on the trained vehicle OD data analysis model based on the verification set to obtain a vehicle OD data analysis model meeting performance conditions; and evaluating a similarity calculation result of the vehicle OD data analysis model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the vehicle OD data analysis model. Performing performance evaluation on the vehicle OD data analysis model to obtain a percentage score (namely, the maximum score is 100 points and the minimum score is 0 points), and determining the vehicle OD data analysis model with the score larger than a set value based on the percentage score, wherein for example, the vehicle OD data analysis model with the score larger than 90 points is the vehicle OD data analysis model meeting the performance condition;
And calculating an evaluation index of the vehicle OD data analysis model meeting the performance condition to obtain the evaluation index of the vehicle OD data analysis model, and calculating to obtain an evaluation value corresponding to each evaluation index, wherein the evaluation value is used for representing the capability value of the vehicle OD data analysis model on the evaluation index.
S103, integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range;
Specifically, the topic module comprises a toll station total travel number statistics module, a traffic flow GIS map display module, an OD pair set accumulation size ranking module, a travel time distribution analysis module, a travel distance distribution analysis module and a vehicle OD scale distribution analysis module.
S104, responding to a selection request of the query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition.
A preferred embodiment is: the regional range is selected from Suzhou city, and the time range is selected from 00.00 to 10.00;
ETC portal traffic data, charging detail data and monitoring data corresponding to 00.00-10.00 in Suzhou are acquired, and a trained vehicle OD data analysis model is input to obtain vehicle OD data corresponding to 00.00-10.00 in Suzhou.
S105, classifying the OD data of the vehicle based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of the high-speed management platform;
Specifically, screening and classifying the vehicle OD data based on the departure point and the destination of the vehicle OD data to obtain classified data;
constructing a highway traffic OD pair set based on the classification data;
A preferred embodiment is: the highway traffic OD pair set includes: kunshan City-Gusu district; gusu district-Kunshan city; frequent market-Gusu district; wujiang-Gusu district; phase urban area-Gusu area; gusu district-Wu Jiangou; gusu-phase city; zhang Jiang Kong City-Gusu district; gusu district-Zhang Jiang Kong City;
ranking the expressway traffic OD pairs in real time according to the size sequence of each classification data;
and displaying the real-time ranking on the OD pair set accumulated size ranking module.
And responding to a configuration request displayed by the traffic flow GIS map, and configuring the traffic flow GIS map, wherein the configuration comprises a migration map line fine range, a migration map circular radius range and a migration map value range screening range.
And displaying real-time vehicle OD data of the target area through the traffic flow GIS map display module.
And displaying travel time distribution, travel distance distribution and vehicle OD scale distribution through the line graph.
According to the intelligent analysis method of the expressway vehicle OD, a certain amount of ETC portal traffic data, charging detail data and monitoring data are obtained; building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model; integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range; responding to a selection request of a query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition; and classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform. The method solves the problem that the OD of the expressway vehicle cannot be intelligently analyzed in the prior art.
FIG. 2 is a schematic diagram of an embodiment of an intelligent analysis system for an expressway vehicle OD of the present invention; as shown in fig. 2, the intelligent analysis system for an OD of an expressway vehicle provided by the embodiment of the invention includes the following steps:
An acquisition module 10 for acquiring a certain number of ETC portal traffic data, charging detail data and monitoring data;
the construction module 20 is configured to construct a vehicle OD data analysis model, and input the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, so as to obtain a trained vehicle OD data analysis model;
the building block 20 is also configured to:
dividing the ETC portal traffic data, charging detail data and monitoring data into a training set, a verification set and a test set;
Training the vehicle OD data analysis model based on the training set;
Performing performance evaluation on the trained vehicle OD data analysis model based on the verification set to obtain a vehicle OD data analysis model meeting performance conditions;
And evaluating an analysis result of the vehicle OD data analysis model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the vehicle OD data analysis model.
An integration module 30, configured to integrate the vehicle OD data analysis model into a high-speed management platform, and configure a query condition and a topic module for the high-speed management platform, where the query condition includes a regional range and a time range;
The topic module comprises a toll station total travel number statistics module, a traffic flow GIS map display module, an OD pair set accumulated size ranking module, a travel time distribution analysis module 40, a travel distance distribution analysis module 40 and a vehicle OD scale distribution analysis module 40.
The analysis module 40 is configured to respond to a selection request of a query condition, select the query condition, acquire ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and input a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition;
the display module 50 is configured to classify the vehicle OD data based on the topic module, obtain a classification result, and display the classification result on a front page of a high-speed management platform;
The display module 50 is also used for;
screening and classifying the vehicle OD data based on the departure point and the destination of the vehicle OD data to obtain classified data;
constructing a highway traffic OD pair set based on the classification data;
ranking the expressway traffic OD pairs in real time according to the size sequence of each classification data;
and displaying the real-time ranking on the OD pair set accumulated size ranking module.
And responding to a configuration request displayed by the traffic flow GIS map, and configuring the traffic flow GIS map, wherein the configuration comprises a migration map line fine range, a migration map circular radius range and a migration map value range screening range.
And displaying real-time vehicle OD data of the target area through the traffic flow GIS map display module.
And displaying travel time distribution, travel distance distribution and vehicle OD scale distribution through the line graph.
According to the intelligent analysis system for the expressway vehicle OD, the acquisition module 10 is used for acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data; building a vehicle OD data analysis model through a building module 20, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model;
Integrating the vehicle OD data analysis model into a high-speed management platform through an integration module 30, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range; responding to a selection request of query conditions through an analysis module 40, selecting the query conditions, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query conditions, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query conditions; the vehicle OD data is classified based on the topic module through the display module 50, a classification result is obtained, and the classification result is displayed on a front-end page of a high-speed management platform. The intelligent analysis method of the expressway vehicle OD solves the problem that the expressway vehicle OD cannot be analyzed intelligently in the prior art, and achieves total travel number statistics of a toll station, GIS map display of traffic flow, accumulated rank of OD pairs, travel time distribution analysis, travel distance distribution analysis, vehicle OD scale distribution analysis and the like.
Fig. 3 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present invention, as shown in fig. 3, an electronic device 60 includes: a processor 601 (processor), a memory 602 (memory), and a bus 603;
wherein, the processor 601 and the memory 602 complete communication with each other through the bus 603;
The processor 601 is configured to invoke program instructions in the memory 602 to perform the methods provided by the method embodiments described above, including, for example: acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data; building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model; integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range; responding to a selection request of a query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition; and classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform.
The present embodiment provides a non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described method embodiments, for example, including: acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data; building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model; integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range; responding to a selection request of a query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition; and classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: various storage media such as ROM, RAM, magnetic or optical disks may store program code.
The apparatus embodiments described above are merely illustrative, wherein elements illustrated as separate elements may or may not be physically separate, and elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on such understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the embodiments or the methods of some parts of the embodiments.
While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (10)
1. An intelligent analysis method for an expressway vehicle OD, which is characterized by comprising the following steps:
acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data;
Building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model;
Integrating the vehicle OD data analysis model into a high-speed management platform, and configuring query conditions and topic modules for the high-speed management platform, wherein the query conditions comprise a regional range and a time range;
Responding to a selection request of a query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, and inputting a trained vehicle OD data analysis model to obtain vehicle OD data corresponding to the query condition;
and classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform.
2. The intelligent analysis method of the expressway vehicle OD according to claim 1, wherein the constructing a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model includes:
dividing the ETC portal traffic data, charging detail data and monitoring data into a training set, a verification set and a test set;
Training the vehicle OD data analysis model based on the training set;
Performing performance evaluation on the trained vehicle OD data analysis model based on the verification set to obtain a vehicle OD data analysis model meeting performance conditions;
And evaluating an analysis result of the vehicle OD data analysis model meeting the performance condition based on the test set to obtain an evaluation index corresponding to the vehicle OD data analysis model.
3. The intelligent analysis method of the expressway vehicle OD according to claim 1, wherein the topic module comprises a toll station total travel number statistics module, a traffic flow GIS map display module, an OD pair set cumulative size ranking module, a travel time distribution analysis module, a travel distance distribution analysis module and a vehicle OD scale distribution analysis module.
4. The intelligent analysis method of the expressway vehicle OD according to claim 3, wherein classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform includes:
screening and classifying the vehicle OD data based on the departure point and the destination of the vehicle OD data to obtain classified data;
constructing a highway traffic OD pair set based on the classification data;
ranking the expressway traffic OD pairs in real time according to the size sequence of each classification data;
and displaying the real-time ranking on the OD pair set accumulated size ranking module.
5. The intelligent analysis method of the expressway vehicle OD according to claim 3, wherein said classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform, further comprises:
and responding to a configuration request displayed by the traffic flow GIS map, and configuring the traffic flow GIS map, wherein the configuration comprises a migration map line fine range, a migration map circular radius range and a migration map value range screening range.
6. The intelligent analysis method of the expressway vehicle OD according to claim 3, wherein said classifying the vehicle OD data based on the topic module to obtain a classification result, and displaying the classification result on a front-end page of a high-speed management platform, further comprises:
And displaying real-time vehicle OD data of the target area through the traffic flow GIS map display module.
7. The intelligent analysis method of an expressway vehicle OD according to claim 1, further comprising:
And displaying travel time distribution, travel distance distribution and vehicle OD scale distribution through the line graph.
8. An intelligent analysis system for an expressway vehicle OD, comprising:
The acquisition module is used for acquiring a certain amount of ETC portal traffic data, charging detail data and monitoring data;
The building module is used for building a vehicle OD data analysis model, inputting the ETC portal traffic data, the charging detail data and the monitoring data into the vehicle OD data analysis model for training, and obtaining a trained vehicle OD data analysis model;
The integration module is used for integrating the vehicle OD data analysis model into a high-speed management platform and configuring query conditions and a topic module for the high-speed management platform, wherein the query conditions comprise a regional range and a time range;
The analysis module is used for responding to a selection request of the query condition, selecting the query condition, acquiring ETC portal traffic data, charging detail data and monitoring data corresponding to the query condition, inputting a trained vehicle OD data analysis model, and obtaining vehicle OD data corresponding to the query condition;
And the display module is used for classifying the vehicle OD data based on the topic module to obtain classification results, and displaying the classification results on a front-end page of the high-speed management platform.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 7 when the computer program is executed.
10. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1 to 7.
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