CN117275239A - Traffic big data information processing method, device and storage medium - Google Patents
Traffic big data information processing method, device and storage medium Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- 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
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Abstract
The invention relates to the technical field of traffic data processing, and provides a traffic big data information processing method, a device and a storage medium, wherein the method comprises the following steps: s1, collecting traffic data of the passing number a of vehicles at an upstream intersection C and the passing number b of vehicles at a downstream intersection D of each road through a data collecting system, and uploading the traffic data to a data preprocessing platform to preprocess the collected data; s2, transmitting the preprocessed data to a data model building module, modeling the average speed, the average traffic flow and the traffic density of the road in the data, analyzing the model, and judging the road traffic condition. The accuracy of data acquisition is improved by carrying out data preprocessing on huge data collected by opposite ends in rush hour and rush hour, and the efficiency of processing road traffic condition data is effectively improved and the feasibility of road traffic planning and formulation is improved by carrying out data model establishment on the preprocessed data.
Description
Technical Field
The present invention relates to the field of traffic data processing technologies, and in particular, to a traffic big data information processing method, device and storage medium.
Background
Along with the development of society, private cars have more and more quantity, and the pressure of traffic is increased rapidly, particularly in the peak period of business hours, the pressure of traffic is more obvious, and an intelligent traffic system based on traffic big data information is considered as an effective method for alleviating traffic jams, reducing traffic problems such as traffic accidents and the like, and an important basis for developing intelligent traffic is to collect traffic data in a road network in time and extract traffic running state information such as traffic flow, occupancy, speed and the like from dynamic traffic flow data in real time, thereby realizing traffic control and travel induction service.
However, the amount of data information of the road section collected during rush hours and rush hours is huge, how to perform data screening in huge data to obtain effective data is a problem to be solved currently by an intelligent traffic system based on traffic big data information, how to establish a data model and formulate a corresponding traffic processing method is a great importance in the problem to be solved currently by the intelligent traffic system.
Therefore, the improvement is made by us, and a traffic big data information processing method, a traffic big data information processing device and a storage medium are provided.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: how to quickly acquire useful data in mass acquired data, improve the data processing speed, and quickly establish a traffic big data information model for making a corresponding traffic control plan.
(II) technical scheme
In order to achieve the above object, the present invention provides a traffic big data information processing method, comprising the steps of:
s1, collecting traffic data of the passing number a of vehicles at an upstream intersection C and the passing number b of vehicles at a downstream intersection D of each road through a data collecting system, and uploading the traffic data to a data preprocessing platform to preprocess the collected data;
s2, transmitting the preprocessed data to a data model building module, modeling the average speed, the average traffic flow and the traffic density of the road in the data, analyzing the model, and judging the traffic condition of the road;
s3, planning road traffic according to the judgment result, sending the planning result to a monitoring center, splitting the result by the monitoring center, controlling the traffic command device, and arranging command personnel to command on site;
s4, after a period of time, acquiring planned road traffic data through a data acquisition system, executing the step S2 on the acquired planned road traffic data, establishing a new data model, and comparing the data model with the road traffic data model before planning through a data comparison module to judge whether the road traffic condition is improved;
s5, sending the processing result and the comparison result to a deep learning module for deep learning of the data, and sending the learning result to a traffic planning module;
in the step S2, the road upstream portTo the downstream port->At->Average vehicle speed in time period>Average traffic flow->Traffic density->The modeling calculation formula of (2) is as follows:
then->In the method, in the process of the invention,average speed for each vehicle in the road segment;
and->All representing the total number of vehicles;
and->Indicate time of day->Is a time period;
is a road upstream crossing->Cross-section traffic flow of (2);
is under the roadCrossroad->Cross-section traffic flow of (a).
Preferably, in the step S1, the data preprocessing platform preprocesses the data, including the following steps:
s11, acquiring n data acquired by a data acquisition system through a data acquisition module, and combining the data through a data combining module to eliminate repeated data;
s12, establishing m data processing windows through a data processing window establishing module, splitting the combined data, preprocessing the data through the m windows,；
s13, the preprocessed data are integrated primarily through a data preprocessing calculation module, and an integration result is output through a data output module.
Preferably, in the step S4, if it is determined that the traffic situation is not improved, the process returns to the step S2, and the road upstream port is collected againTo the downstream port->At->Average vehicle speed in time period>Average traffic flow->Traffic density->And modeling, and executing the step S3 and the step S4 again.
Preferably, in the step S13, for each intersection upstream of the roadNumber of passing vehicles a and downstream crossing +.>The traffic data integration calculation formula of the passing quantity b of the vehicles is as follows:
in (1) the->Is an upstream crossing->At->A vehicle speed collection of each vehicle passing through the time period;
downstream crossing->At->The speed of each vehicle passing through the time period is integrated.
Preferably, in the step S2,、/>and +.>The calculation formula of (2) is as follows: />In the method, in the process of the invention,is the distance between C and D;
（/>) For vehicle->At the time of C (D) passage;
in (1) the->And->Respectively->And->The number of elements of the two sets.
The traffic big data information processing device is applied to the traffic big data information processing method, and comprises a data acquisition system, wherein the data acquisition system is connected with a data preprocessing platform through a data transmission technology and is used for preprocessing acquired data, and the data preprocessing platform is connected with a data processing analysis system through the data transmission technology and is used for modeling and analyzing the preprocessed data and making road traffic planning.
Preferably, the data processing analysis system is connected with the monitoring center through a data transmission technology, and is used for sending an analysis result and a formulated road traffic plan to the monitoring center, splitting the planning result, controlling the traffic command device, and arranging a commander to command on site, the data processing analysis system comprises a data model building module, a traffic planning module, a data comparison module and a data deep learning module, the data model building module is used for carrying out modeling analysis on the preprocessed data, the traffic planning module is used for formulating a road traffic plan according to the modeling analysis result, the data comparison module is used for collecting road traffic data after a period of time, comparing the road traffic data with the data before planning, analyzing the condition of the road traffic after planning, and the data deep learning module is used for carrying out deep learning on the model built by the data model building module and the traffic plan.
Preferably, the data acquisition system includes, but is not limited to, a loop induction coil module, a video monitoring module, a signal lamp monitoring module, a road weather monitoring module and a vehicle GPS information acquisition module, and is used for acquiring the traffic of a road, the signal lamp and the weather condition for omnibearing monitoring.
Preferably, the data preprocessing platform comprises a data acquisition module, wherein the data acquisition module is connected with a data merging module through a data transmission technology and is used for merging acquired data and screening out the same data, the data merging module is connected with a data processing window building module through the data transmission technology and is used for building a window for processing the data according to the size of the data and processing the data, the data processing window building module is connected with a data preprocessing integration module through the data transmission technology and is used for integrating the data processed by all the windows, and the data preprocessing integration module is connected with a data output module through the data transmission technology and is used for transmitting the integrated data to a data processing analysis system to process and analyze the data.
A traffic big data information processing storage medium having stored therein at least one program code for loading and executing the steps of the method of any of the above.
(III) beneficial effects
The traffic big data information processing method, the device and the storage medium provided by the invention have the beneficial effects that:
1. the method has the advantages that through data preprocessing, screening and reorganizing of huge data collected by opposite ends in rush hour, required data are effectively obtained, repeated or useless data are screened out, accuracy of data acquisition is improved, accordingly, speed of subsequent data modeling analysis and traffic planning is improved, and through a data deep learning module in a data processing analysis system, deep learning is conducted on the formulated traffic planning, and accordingly speed of traffic planning control planning of rush hour road traffic is improved.
2. By establishing a data model on the preprocessed data, analyzing the model, making a traffic plan, re-collecting traffic data of a road section after a period of time, comparing the traffic data with the modeling analysis result after modeling analysis, judging whether the traffic plan made before is effective, realizing rapid modeling analysis on traffic of the road section, making a traffic plan, continuously tracking the traffic plan implementation result, effectively improving the efficiency of processing the road traffic condition data, and improving the feasibility of making the road traffic plan.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic diagram of a device system of a method, a device and a storage medium for processing traffic big data information;
FIG. 2 is a schematic diagram of a data processing flow of a traffic big data information processing method, device and storage medium provided in the present application;
FIG. 3 is a schematic diagram of a data preprocessing flow of a traffic big data information processing method, device and storage medium provided by the present application;
FIG. 4 is a schematic diagram of a data acquisition system of a traffic big data information processing method, device and storage medium provided by the present application;
fig. 5 is a schematic diagram of a data processing platform system of a traffic big data information processing method, a device and a storage medium.
Detailed Description
The following detailed description of specific embodiments of the invention is provided in connection with the accompanying drawings and examples. The following examples are only illustrative of the present invention and are not intended to limit the scope of the invention.
The following detailed description of specific embodiments of the invention is provided in connection with the accompanying drawings and examples. The following examples are only illustrative of the present invention and are not intended to limit the scope of the invention.
As shown in fig. 1-5, the present embodiment provides a traffic big data information processing method, which includes the following steps:
s1, collecting traffic data of the passing number a of vehicles at an upstream intersection C and the passing number b of vehicles at a downstream intersection D of each road through a data collecting system, and uploading the traffic data to a data preprocessing platform to preprocess the collected data;
s2, transmitting the preprocessed data to a data model building module, modeling the average speed, the average traffic flow and the traffic density of the road in the data, analyzing the model, and judging the traffic condition of the road;
s3, planning road traffic according to the judgment result, sending the planning result to a monitoring center, splitting the result by the monitoring center, controlling the traffic command device, and arranging command personnel to command on site;
s4, after a period of time, acquiring planned road traffic data through a data acquisition system, executing the step S2 on the acquired planned road traffic data, establishing a new data model, and comparing the data model with the road traffic data model before planning through a data comparison module to judge whether the road traffic condition is improved;
s5, sending the processing result and the comparison result to a deep learning module for deep learning of the data, and sending the learning result to a traffic planning module;
in the step S2, the road upstream portTo the downstream port->At->Average vehicle speed in time period>Average traffic flow->Traffic density->The modeling calculation formula of (2) is as follows:
then->In the method, in the process of the invention,average speed for each vehicle in the road segment;
and->All representing the total number of vehicles;
and->Indicate time of day->Is a time period;
the section traffic flow of the road upstream intersection C;
is the section traffic flow of the road downstream intersection D.
In this embodiment, in the step S1, the data preprocessing platform preprocesses data, including the following steps:
s11, acquiring n data acquired by a data acquisition system through a data acquisition module, and combining the data through a data combining module to eliminate repeated data;
s12, establishing m data processing windows through a data processing window establishing module, splitting the combined data, preprocessing the data through the m windows,；
s13, the preprocessed data are integrated primarily through a data preprocessing calculation module, and an integration result is output through a data output module.
In this embodiment, in the step S4, if it is determined that the traffic situation is not improved, the process returns to the step S2, and the road upstream port is collected againTo the downstream port->At->Average vehicle speed in time period>Average traffic flow->Traffic density->And modeling, and executing the step S3 and the step S4 again.
In this embodiment, in the step S13, the traffic data integration calculation formula for the vehicle passing number a at the upstream intersection C and the vehicle passing number b at the downstream intersection D of each road is:
in (1) the->Is an upstream crossing->At->A vehicle speed collection of each vehicle passing through the time period;
downstream crossing->At->The speed of each vehicle passing through the time period is integrated.
In this embodiment, in the step S2,、/>and +.>The calculation formula of (2) is as follows: />In (1) the->Is the distance between C and D;
（/>) For vehicle->At the time of C (D) passage;
in (1) the->And->Respectively->And->The number of elements of the two sets.
The traffic big data information processing device is applied to the traffic big data information processing method, and comprises a data acquisition system, wherein the data acquisition system is connected with a data preprocessing platform through a data transmission technology and is used for preprocessing acquired data, and the data preprocessing platform is connected with a data processing analysis system through the data transmission technology and is used for modeling and analyzing the preprocessed data and making road traffic planning.
In this embodiment, the data processing analysis system is connected to the monitoring center through a data transmission technology, and is used for sending an analysis result and a formulated road traffic plan to the monitoring center, splitting the planning result, controlling the traffic commanding device, and arranging the commander to command on site, where the data processing analysis system includes a data model building module, a traffic planning module, a data comparison module and a data deep learning module, the data model building module is used for performing modeling analysis on the preprocessed data, the traffic planning module is used for formulating a road traffic plan according to the modeling analysis result, the data comparison module is used for collecting road traffic data after a period of time, comparing the road traffic data with the data before planning, and analyzing the condition of the road traffic after planning, and the data deep learning module is used for performing deep learning on the model built by the data model building module and the traffic plan.
In this embodiment, the data acquisition system includes, but is not limited to, a loop induction coil module, a video monitoring module, a signal lamp monitoring module, a road weather monitoring module, and a vehicle GPS information acquisition module, which is configured to acquire traffic on a road, and perform omnibearing monitoring on signal lamps and weather conditions.
In this embodiment, the data preprocessing platform includes a data acquisition module, where the data acquisition module is connected to the data merging module through a data transmission technology and is used to merge acquired data and screen out the same data, where the data merging module is connected to the data processing window building module through a data transmission technology and is used to build a window for processing data according to the size of the data and process the data, where the data processing window building module is connected to the data preprocessing integration module through a data transmission technology and is used to integrate all the data processed by the window, and where the data preprocessing integration module is connected to the data output module through a data transmission technology and is used to transmit the integrated data to the data processing analysis system and process and analyze the data.
A traffic big data information processing storage medium in which at least one program code is stored for loading and executing the steps of the method according to any of the preceding claims.
According to the invention, through carrying out data preprocessing on huge data collected by opposite ends in rush hour and rush hour, screening and reorganizing the data, required data are effectively obtained, repeated or useless data are screened out, and the accuracy of data acquisition is improved, so that the speed of subsequent data modeling analysis and traffic planning formulation is improved, and through a data deep learning module in a data processing analysis system, the deep learning is carried out on the formulated traffic planning, and the speed of traffic planning and control planning on rush hour road sections is improved;
according to the invention, the data model is built and analyzed on the preprocessed data, the traffic plan is formulated, the traffic data of the road section is collected again after a period of time, after modeling analysis, the traffic plan formulated before is compared with the modeling analysis result before, whether the traffic plan formulated before is effective or not is judged, the rapid modeling analysis on the traffic of the road section is realized, the traffic plan is formulated, the continuous tracking is carried out on the traffic plan implementation result, the road traffic condition data processing efficiency is effectively improved, and the feasibility of road traffic plan formulation is improved.
The above embodiments are only for illustrating the present invention, and are not limiting of the present invention. While the invention has been described in detail with reference to the embodiments, those skilled in the art will appreciate that various combinations, modifications, and substitutions can be made thereto without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. The traffic big data information processing method is characterized by comprising the following steps:
s1, collecting traffic data of the passing number a of vehicles at an upstream intersection C and the passing number b of vehicles at a downstream intersection D of each road through a data collecting system, and uploading the traffic data to a data preprocessing platform to preprocess the collected data;
s2, transmitting the preprocessed data to a data model building module, modeling the average speed, the average traffic flow and the traffic density of the road in the data, analyzing the model, and judging the traffic condition of the road;
s3, planning road traffic according to the judgment result, sending the planning result to a monitoring center, splitting the result by the monitoring center, controlling the traffic command device, and arranging command personnel to command on site;
s4, after a period of time, acquiring planned road traffic data through a data acquisition system, executing the step S2 on the acquired planned road traffic data, establishing a new data model, and comparing the data model with the road traffic data model before planning through a data comparison module to judge whether the road traffic condition is improved;
s5, sending the processing result and the comparison result to a deep learning module for deep learning of the data, and sending the learning result to a traffic planning module;
in the step S2, the road upstream portTo the downstream port->At->Average vehicle speed in time period>Average traffic flow->Traffic density->The modeling calculation formula of (2) is as follows:
then:
in (1) the->Average speed for each vehicle in the road segment;
and->All representing the total number of vehicles;
and->Indicate time of day->Is a time period;
is a road upstream crossing->Cross-section traffic flow of (2);
is a road downstream crossing->Cross-section traffic flow of (a).
2. The traffic big data information processing method according to claim 1, wherein in the step S1, the data preprocessing platform preprocesses the data, including the steps of:
s11, acquiring n data acquired by a data acquisition system through a data acquisition module, and combining the data through a data combining module to eliminate repeated data;
s12, establishing m data processing windows through a data processing window establishing module, splitting the combined data, preprocessing the data through the m windows,；
s13, the preprocessed data are integrated primarily through a data preprocessing calculation module, and an integration result is output through a data output module.
3. The traffic big data information processing method according to claim 1, wherein in the step S4, if it is determined that the traffic situation is not improved, the step S2 is returned to, and the road upstream port is collected againTo the downstream port->At->Average vehicle speed in time period>Average ofTraffic flow->Traffic density->And modeling, and executing the step S3 and the step S4 again.
4. The traffic big data information processing method according to claim 2, wherein in the step S13, for each road upstream intersectionNumber of passing vehicles a and downstream crossing +.>The traffic data integration calculation formula of the passing quantity b of the vehicles is as follows: /> In (1) the->Is an upstream crossing->At->A vehicle speed collection of each vehicle passing through the time period;
downstream crossing->At->The speed of each vehicle passing through the time period is integrated.
5. The traffic big data information processing method according to claim 1, wherein in the step S2,、/>and +.>The calculation formula of (2) is as follows: />In (1) the->Is the distance between C and D;
（/>) For vehicle->At the time of C (D) passage; /> In (1) the->And->Respectively->And->The number of elements of the two sets.
6. The traffic big data information processing device is applied to the traffic big data information processing method according to any one of claims 1-5, and is characterized by comprising a data acquisition system, wherein the data acquisition system is connected with a data preprocessing platform through a data transmission technology and is used for preprocessing acquired data, and the data preprocessing platform is connected with a data processing analysis system through the data transmission technology and is used for modeling and analyzing the preprocessed data and making road traffic planning.
7. The traffic big data information processing apparatus according to claim 6, wherein: the data processing analysis system is connected with the monitoring center through a data transmission technology and is used for sending an analysis result and a formulated road traffic plan to the monitoring center, splitting the planning result, controlling the traffic command device and arranging command personnel to command on site, the data processing analysis system comprises a data model building module, a traffic planning module, a data comparison module and a data deep learning module, the data model building module is used for carrying out modeling analysis on the preprocessed data, the traffic planning module is used for formulating a road traffic plan according to the modeling analysis result, the data comparison module is used for collecting road traffic data after a period of time, comparing the road traffic data with the data before planning and analyzing the condition of the road traffic after planning, and the data deep learning module is used for carrying out deep learning on the model built by the data model building module and the traffic plan.
8. The traffic big data information processing device of claim 6, wherein the data acquisition system comprises, but is not limited to, a loop induction coil module, a video monitoring module, a signal lamp monitoring module, a road weather monitoring module and a vehicle GPS information acquisition module for acquiring the traffic of the road, the signal lamp and the weather condition for omnibearing monitoring.
9. The traffic big data information processing device according to claim 6, wherein the data preprocessing platform comprises a data acquisition module, the data acquisition module is connected with a data merging module through a data transmission technology and is used for merging acquired data and screening out the same data, the data merging module is connected with a data processing window building module through the data transmission technology and is used for building a window for processing the data according to the size of the data, the data processing window building module is connected with a data preprocessing integration module through the data transmission technology and is used for integrating all the data processed by the window, and the data preprocessing integration module is connected with a data output module through the data transmission technology and is used for transmitting the integrated data to a data processing analysis system for processing and analyzing the data.
10. A traffic big data information processing storage medium, characterized in that at least one program code is stored in said storage medium, said program code being adapted to load and execute the steps of the method according to any of claims 1-5.
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