CN109993974B - Intelligent traffic-induced chain type progressive network construction method based on sliding window - Google Patents
Intelligent traffic-induced chain type progressive network construction method based on sliding window Download PDFInfo
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- CN109993974B CN109993974B CN201910280201.4A CN201910280201A CN109993974B CN 109993974 B CN109993974 B CN 109993974B CN 201910280201 A CN201910280201 A CN 201910280201A CN 109993974 B CN109993974 B CN 109993974B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
- G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
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Abstract
The invention discloses a sliding window-based intelligent traffic-induced chain type progressive network construction method. The method comprises the following steps: first, the present invention detects, describes and stores the traffic status information of vehicles in connected blocks of a highway by constructing a chain progressive network. And secondly, forming a chain type progressive network of the vehicles on the highway, and realizing real-time traffic state modeling, instantiation description, chain storage and iterative analysis of dynamic traffic flow. Thirdly, the GNSS system is used for carrying out synchronous time service on each block, and the synchronism and the accuracy of the information of each block are guaranteed. The invention constructs the intelligent traffic-induced chain type progressive network based on the sliding window principle, realizes the dynamic monitoring of vehicles and the real-time updating of the induction mode, and has wide application prospect.
Description
Technical Field
The invention belongs to the field of intelligent traffic, and particularly relates to a sliding window-based intelligent traffic guidance chain type Progressive network construction method.
Background
The existing vehicle flow detection mostly counts vehicles through a full-automatic traffic flow observation instrument which is generally arranged at a key intersection, but the accurate and dynamic monitoring is often difficult to carry out due to the complexity of road conditions and the complexity of roads. This may cause a situation that the traffic flow in a certain section is large and cannot be fed back to the rear vehicle, thereby causing traffic jam. Therefore, it is very necessary to establish an intelligent traffic guidance chain type progressive network construction method based on a sliding window by combining a radar block technology, so as to dynamically monitor traffic flow and realize intelligent guidance.
Disclosure of Invention
In order to overcome the shortages in the prior art, the invention provides an intelligent traffic guidance chain type progressive network construction method based on a sliding window.
The invention is realized by adopting the following technical scheme:
a method for constructing an intelligent traffic-induced chain type progressive network based on a sliding window comprises the following steps:
In the formula, WNFor the general information state of the radar block N, WiIs the general information state, P, of the radar block iiThe comprehensive information influence factor is the radar block i;
The further improvement of the invention is characterized in that the specific implementation method of the step 1 is as follows:
101) collecting weather six-element information and uploading the weather six-element information to a cloud platform;
102) determining the size of a sliding window based on weather conditions, wherein if the vehicle speed is generally slow and the vehicle condition in unit length is complex under the weather conditions that the visibility is less than 100 meters, the size of the selected window is 2-4 and the actual distance is 40-80 m in order to accurately and effectively describe the traffic flow information; on the contrary, if the weather condition that the visibility is larger than 100 meters occurs, the size of the selected window is 5-8, and the actual distance is 100-160 m.
The further improvement of the invention is that the specific implementation method of the step 2 is as follows:
201) numbering different radar blocks, establishing a chained database structure, and defining the name of each database according to the number so as to facilitate external access;
202) and determining the name, type and size of data in each radar block database, and finishing initialization configuration.
The further improvement of the invention is that the specific implementation method of the step 4 is as follows:
401) based on the traffic data information of different radar blocks, accessing the database according to the name, and updating the database of the chain type progressive network;
402) and according to the data information of different databases, the modeling and instantiation description of the real-time traffic state is completed by combining the GIS technology.
The further improvement of the invention is that the specific implementation method of the step 5 is as follows:
501) automatically adjusting induction modes of different radar blocks based on data information of the chain type progressive network;
502) when the traffic flow of a certain radar block is too large and congestion occurs, prompt information is sent to other adjacent radar block vehicles.
The invention has the following beneficial technical effects:
according to the intelligent traffic guidance chain type progressive network construction method based on the sliding window, provided by the invention, a traffic road is divided into a plurality of radar blocks, the detection, description and storage of vehicle traffic state information of the radar blocks connected with the expressway are realized, an information access platform is realized, and the traffic management capability is improved. Meanwhile, a chain type progressive network of the vehicles on the highway is formed, real-time traffic state modeling, instantiation description, chain type storage and iterative analysis of dynamic traffic flow are achieved, and reasonable traffic planning is facilitated.
Furthermore, the induction system (radar, induction lamp) and the like can wake up and update the chain type progressive network in real time, and the GPS and the Beidou are adopted to carry out synchronous time service on each block, so that the synchronism and the accuracy of information of each block are ensured.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a schematic diagram of the physical layer construction of the chained gradual network structure of the present invention when the weather conditions are poor.
Fig. 3 is a schematic diagram of the physical layer construction of the chain type progressive network structure of the present invention when the weather condition is good.
FIG. 4 is a schematic diagram of the physical layer and application layer structure models of the chained progressive network of the present invention.
Description of reference numerals:
1 is a radar block N +1, 2 is a radar block N, 3 is a radar block N-1, 4 is a radar and a camera, and 6 is a radar block.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments, and are not intended to limit the scope of the present disclosure. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Various schematic diagrams in accordance with the disclosed embodiments of the invention are shown in the figures. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are merely exemplary, and deviations may occur in practice due to manufacturing tolerances or technical limitations, and a person skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions, according to actual needs.
The invention is further elucidated with reference to the drawings and examples:
examples
Referring to fig. 2, 1 is a radar network block N +1, 2 is a radar network block N, 3 is a radar network block N-1, 4 is a radar and a camera, and 5 is an automobile. Since the number of radar pairs within each block is 2, the size of the sliding window is 2. The traffic flow state at a certain moment is shown in the figure, the number of vehicles in the radar network block N +1 is 2, the number of vehicles in the radar network block N is 0, and the number of vehicles in the radar network block N-1 is 1. And the radar and the camera in each block upload the information of the number, the speed and the license plate number of the vehicles to a database of corresponding block names through comprehensive judgment. Since the physical layer is arranged in a ring-like manner like a bicycle chain, the structure of the invention is called a chain progressive network.
Referring to fig. 3, if the weather condition becomes better, the traffic department does not limit the speed any more, the number of vehicles in the same length will decrease, at this time, the size of the sliding window can be increased appropriately, the number of radar pairs becomes 6, at this time, the chain type progressive network will complete updating, and data will be recorded according to the new sliding window.
Referring to fig. 4, the inventive physical layer and application layer structure model of the chained progressive network. The radar blocks 1, 2 and 3 ….. N based on weather conditions are constructed on a physical layer, and information interaction with an application layer is completed through a transmission protocol of a network layer and a transmission layer. The application layer is based on a B/S structure server, and a database list of each radar block is constructed through a database to realize dynamic modification and real-time access to the radar blocks.
Referring to table 1 and table 2, the vehicle speed information and the speed limit information can be stored for a part of a certain block of the cloud platform database by establishing the database, so that calling and instantiation analysis are facilitated. In the construction process of the chain type progressive network, the information such as license plate numbers, vehicle quantity and the like can be added, and the dynamic monitoring of the traffic flow is realized.
Table 1 is a database of the cloud platform chained progressive network of the present invention.
Table 2 shows data type information of the cloud platform chained gradual network according to the present invention.
Claims (5)
1. A method for constructing an intelligent traffic-induced chain type progressive network based on a sliding window is characterized by comprising the following steps:
step 1, initializing the size of a sliding window: a pair of radars which are opposite to each other on two sides of a road is defined as a radar pair, and the number of the continuous and adjacent radar pairs is defined as the size of a sliding window, namely the size of a radar block; in the intelligent induction process, the number of the radar pairs is initialized according to the actual environment condition, and the radar block numbering is completed, so that the radar block induction is facilitated;
step 2, initializing a chain type progressive network structure: initializing a database structure of the cloud platform according to the defined size of the sliding window to form a dynamic chained progressive network structure based on the current traffic flow state, wherein the chained progressive network structure meets the relational expression
In the formula, WNFor the general information state of the radar block N, WiIs the general information state, P, of the radar block iiThe comprehensive information influence factor is the radar block i;
step 3, the radar block captures vehicle information: the radar in each sliding window counts the number of vehicles, license plates and running speed in the radar block and uploads information to the cloud platform;
step 4, updating the chained progressive network: updating a database of the chain type progressive network based on data information of the radar block to realize real-time traffic state modeling, instantiation description, chain storage and iterative analysis of dynamic traffic flow;
step 5, intelligent induction: and intelligently inducing the vehicles in different radar blocks according to the database information of the chain type progressive network.
2. The method for constructing the intelligent traffic-induced chain-type progressive network based on the sliding window according to claim 1, wherein the specific implementation method of the step 1 is as follows:
101) collecting weather six-element information and uploading the weather six-element information to a cloud platform;
102) determining the size of a sliding window based on weather conditions, wherein if the vehicle speed is generally slow and the vehicle condition in unit length is complex under the weather conditions that the visibility is less than 100 meters, the size of the selected window is 2-4 and the actual distance is 40-80 m in order to accurately and effectively describe the traffic flow information; on the contrary, if the weather condition that the visibility is larger than 100 meters occurs, the size of the selected window is 5-8, and the actual distance is 100-160 m.
3. The method for constructing the intelligent traffic-induced chain-type progressive network based on the sliding window according to claim 2, wherein the specific implementation method of the step 2 is as follows:
201) numbering different radar blocks, establishing a chained database structure, and defining the name of each database according to the number so as to facilitate external access;
202) and determining the name, type and size of data in each radar block database, and finishing initialization configuration.
4. The method for constructing the intelligent traffic-induced chain-type progressive network based on the sliding window according to claim 3, wherein the specific implementation method of the step 4 is as follows:
401) based on the traffic data information of different radar blocks, accessing the database according to the name, and updating the database of the chain type progressive network;
402) and according to the data information of different databases, the modeling and instantiation description of the real-time traffic state is completed by combining the GIS technology.
5. The method for constructing the intelligent traffic-induced chain-type progressive network based on the sliding window according to claim 4, wherein the concrete implementation method of the step 5 is as follows:
501) automatically adjusting induction modes of different radar blocks based on data information of the chain type progressive network;
502) when the traffic flow of a certain radar block is too large and congestion occurs, prompt information is sent to other adjacent radar block vehicles.
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