CN117831293A - Intelligent traffic control method and system - Google Patents
Intelligent traffic control method and system Download PDFInfo
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- CN117831293A CN117831293A CN202410030300.8A CN202410030300A CN117831293A CN 117831293 A CN117831293 A CN 117831293A CN 202410030300 A CN202410030300 A CN 202410030300A CN 117831293 A CN117831293 A CN 117831293A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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- G—PHYSICS
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Abstract
The invention relates to the technical field of traffic control, in particular to an intelligent traffic control method and system, comprising the steps of collecting traffic information to obtain traffic data; analyzing the traffic data to identify a congested node; acquiring adjacent shunting nodes of the congestion node to prompt shunting in advance; calculating the passing speed of each direction of the congestion node, and dividing the congestion direction and the non-congestion direction; generating waiting time based on the traffic speed of the non-congestion direction and the number of waiting vehicles, and passing the non-congestion direction in the waiting time; according to the reserved space on the congested road section in the waiting time, sequentially controlling the traffic of vehicles according to each direction of entering the congested road section; adjusting the traffic time proportion based on queuing lengths in all directions of entering the congested road section; and monitoring and recording the running condition of the vehicle. Therefore, the road use efficiency can be improved, the traffic safety can be ensured, and the occurrence of illegal behaviors can be reduced.
Description
Technical Field
The invention relates to the technical field of traffic control, in particular to an intelligent traffic control method and system.
Background
Traffic management refers to the management and control of traffic and other traffic related activities by vehicles and pedestrians on roads as prescribed by law. Such management typically includes diverting, restricting or prohibiting traffic for a particular period of time to ensure that road traffic is safe, orderly and clear.
Traffic control aims to prevent and reduce traffic accidents, relieve traffic pressure and ensure smooth progress of special events or activities by controlling traffic flow. For example, traffic management may help maintain traffic order around the scene in the case of large gatherings, sporting events, road construction, emergency rescue, or the like.
In an actual traffic scene, roads are very crowded on certain dates, and on certain dates, the roads are smooth, and the existing main mode for adjusting is to send out traffic police for manual control, so that the workload is increased, and the working efficiency is reduced.
Disclosure of Invention
The invention aims to provide an intelligent traffic control method and system, which aim to automatically control roads, improve the use efficiency of the roads, ensure traffic safety and reduce the occurrence of illegal behaviors.
In order to achieve the above object, in a first aspect, the present invention provides a method for intelligent traffic control, including collecting traffic information to obtain traffic data;
analyzing the traffic data to identify a congested node;
acquiring adjacent shunting nodes of the congestion node to prompt shunting in advance;
calculating the passing speed of each direction of the congestion node, and dividing the congestion direction and the non-congestion direction;
generating waiting time based on the traffic speed of the non-congestion direction and the number of waiting vehicles, and passing the non-congestion direction in the waiting time;
according to the reserved space on the congested road section in the waiting time, sequentially controlling the traffic of vehicles according to each direction of entering the congested road section;
adjusting the traffic time proportion based on queuing lengths in all directions of entering the congested road section;
and monitoring and recording the running condition of the vehicle.
After the monitoring and recording of the running light condition of the vehicle, the intelligent traffic control method further comprises the step of carrying out data mining on traffic light control data based on the congestion nodes so as to generate traffic light control rules.
The specific steps of acquiring traffic information and obtaining traffic data comprise:
collecting traffic data in real time through deployed monitoring equipment;
transmitting the collected traffic information to a central processing system through a network;
and in the central processing system, preprocessing the acquired data to obtain traffic data.
The specific steps of processing and analyzing the traffic data to identify the congestion node include:
acquiring a traffic intersection node;
identifying the speed of all lanes based on the traffic intersection nodes;
and generating a congestion node when the minimum vehicle speed is lower than a preset value.
The specific step of acquiring the shunting nodes adjacent to the congestion node to prompt shunting in advance comprises the following steps:
retrieving traffic nodes adjacent to the target map based on the congestion nodes;
and prompting forward congestion proposal diversion through signal lamps of traffic nodes.
The specific steps of calculating the passing speed of each direction of the congestion node and dividing the congestion direction and the non-congestion direction comprise the following steps:
for each directional lane or road, calculating an average journey speed within a preset time interval;
setting a congestion speed threshold;
when the average travel speed in a certain direction is lower than the congestion speed threshold value, setting the congestion direction, otherwise, setting the congestion direction as a non-congestion direction.
The specific step of generating waiting time based on the traffic speed in the non-congestion direction and the number of waiting vehicles, and passing in the non-congestion direction within the waiting time comprises the following steps:
acquiring the traffic speed in the non-congestion direction;
identifying the number of waiting vehicles based on the monitoring image;
a waiting time is calculated based on the passing speed and the number of vehicles, and the vehicles in this direction pass during the waiting time.
The specific step of sequentially controlling the vehicle to pass in each direction of the congestion road section according to the preset waiting time comprises the following steps:
calculating the moving length of the traffic flow based on the waiting time and the traffic speed of the congested road section;
calculating the number of receivable vehicles based on the movement length;
and sequentially controlling the traffic lights to be communicated at the same time according to all directions entering the congested road section based on the number of vehicles.
In a second aspect, the invention also provides an intelligent traffic control system, which comprises an information acquisition module, a congestion node identification module, a diversion module, a direction distinguishing module, a non-congestion traffic module, a congestion traffic module, an adjustment module and a monitoring module;
the information acquisition module is used for acquiring traffic information to obtain traffic data;
the congestion node identification module is used for analyzing traffic data to identify congestion nodes;
the shunting module is used for acquiring shunting nodes adjacent to the congestion node so as to prompt shunting in advance;
the direction distinguishing module is used for calculating the passing speed of each direction of the congestion node and dividing the congestion direction and the non-congestion direction;
the non-congestion passing module is used for generating waiting time based on the passing speed of the non-congestion direction and the number of waiting vehicles, and passing in the non-congestion direction within the waiting time;
the congestion passing module is used for sequentially controlling the passing of vehicles according to the directions of the congestion road sections according to the reserved space on the congestion road sections in the waiting time;
the adjusting module is used for adjusting the traffic time proportion based on the queuing lengths in all directions of the entering congestion road section;
the monitoring module is used for monitoring and recording the running light condition of the vehicle.
The intelligent traffic control method and system comprise the steps of collecting traffic information to obtain traffic data; analyzing the traffic data to identify a congested node; acquiring adjacent shunting nodes of the congestion node to prompt shunting in advance; calculating the passing speed of each direction of the congestion node, and dividing the congestion direction and the non-congestion direction; generating waiting time based on the traffic speed of the non-congestion direction and the number of waiting vehicles, and passing the non-congestion direction in the waiting time; according to the reserved space on the congested road section in the waiting time, sequentially controlling the traffic of vehicles according to each direction of entering the congested road section; adjusting the traffic time proportion based on queuing lengths in all directions of entering the congested road section; and monitoring and recording the running condition of the vehicle. The congestion nodes can be identified through deep analysis of mass traffic data. Congestion nodes refer to those road segments where severe traffic congestion occurs during peak hours or under certain conditions. The system will acquire its neighboring shunting nodes for advanced shunting management if necessary. The shunting nodes refer to nodes which are adjacent to the congestion node and can play a role in shunting. By reasonably guiding the vehicle to these nodes, traffic pressure on congested road segments can be effectively relieved. In addition, the traffic speed of each direction of the congestion node can be calculated, and the congestion direction and the non-congestion direction can be distinguished according to the traffic speed. In the non-congestion direction, the system generates a reasonable waiting time according to the current road condition and the number of vehicles. During this waiting time, vehicles in a non-congestion direction can normally pass without any restriction. In the congestion direction, the system sequentially controls the traffic of vehicles in each direction of the congestion road section according to the space reserved in the waiting time. The orderly traffic mode can greatly relieve the congestion condition and improve the road use efficiency. In addition, the traffic time proportion can be dynamically adjusted according to the queuing lengths in all directions of the entering congestion road sections. In order to ensure traffic safety, the system also monitors and records the running light condition of the vehicle. The running of the red light is one of common illegal behaviors, and not only damages the safety of the driver, but also seriously influences the traffic order. By monitoring and recording red light running behaviors in real time, the system provides powerful evidence for law enforcement departments and is beneficial to restraining the occurrence of the non-civilized driving behaviors. In summary, the intelligent traffic control method and the intelligent traffic control system realize intelligent traffic management. The traffic jam control system not only can effectively solve the problem of traffic jam and improve the road use efficiency, but also can ensure traffic safety and reduce the occurrence of illegal behaviors.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for intelligent traffic control according to a first embodiment of the present invention.
Fig. 2 is a flowchart of acquiring traffic information to obtain traffic data according to a first embodiment of the present invention.
Fig. 3 is a flow chart of analyzing traffic data to identify congested nodes in accordance with a first embodiment of the present invention.
Fig. 4 is a flow chart of acquiring a split node adjacent to a congestion node to prompt the split in advance according to the first embodiment of the present invention.
Fig. 5 is a flowchart for calculating the traffic speed of each direction of a congested node and dividing the congested direction and the uncongested direction according to the first embodiment of the present invention.
Fig. 6 is a flow chart of the non-congestion-direction traffic in the waiting time generated based on the speed of the non-congestion-direction traffic and the number of waiting vehicles according to the first embodiment of the present invention.
Fig. 7 is a flowchart for sequentially controlling the traffic of vehicles in various directions into a congested road segment according to a space left on the congested road segment during a waiting time according to a first embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention.
First embodiment
Referring to fig. 1 to 7, the present invention provides a smart traffic control method, which includes:
s101, collecting traffic information to obtain traffic data;
the method comprises the following specific steps:
s201, collecting traffic data in real time through deployed monitoring equipment;
by means of monitoring equipment deployed at each important traffic node, various traffic data including traffic flow, speed, road conditions and the like can be collected in real time.
S202, transmitting the collected traffic information to a central processing system through a network;
these collected traffic information then needs to be transmitted over a network to a central processing system. The speed and quality of network transmission is critical to the processing of real-time data. Therefore, we need to ensure that the stability and bandwidth of the network are sufficient.
S203, preprocessing the acquired data in a central processing system to obtain traffic data.
In a central processing system, preprocessing of the collected data is required, including data cleaning, format conversion, etc., in order to obtain traffic data that can be used for analysis and decision.
S102, analyzing traffic data to identify congestion nodes;
the system plays a vital role in traffic data analysis, and aims to identify the congestion node and optimize traffic flow. The method comprises the following specific steps:
s301, acquiring a traffic intersection node;
information of the traffic intersection node can be obtained from the traffic map.
S302, identifying the speed of all lanes based on the traffic intersection node;
the vehicle of each lane can be tracked and measured in speed by high-precision radar, cameras and other devices, so that the accuracy and reliability of data are ensured, or the average speed of the running vehicle on the lane is calculated.
S303 generates a congestion node when the minimum vehicle speed is lower than a preset value.
S103, acquiring adjacent shunting nodes of the congestion node to prompt shunting in advance;
the step is used for prompting diversion in advance when traffic is jammed, so that the road pressure is reduced, and the traffic efficiency is improved. The method comprises the following specific steps:
s401, searching traffic nodes adjacent to a target map based on the congestion nodes;
the system needs to retrieve traffic nodes adjacent to the target map based on the congested nodes. This process may be accomplished using advanced map matching techniques and algorithms. For example, algorithms similar to Breadth First Search (BFS) or Depth First Search (DFS) may be employed to search for its neighbors, starting from known congested nodes, until a sufficiently large area is covered or a target node is found. In addition, in order to improve the searching efficiency, a heuristic searching algorithm, such as an a-algorithm, may be used, which can search according to a certain rule and priority, so as to find the target node in a shorter time.
S402 prompts forward congestion advice diversion through traffic node signaling lights.
This step may be accomplished by communicating with traffic lights. For example, vehicle networking (V2X) technology may be used to enable vehicles to communicate with surrounding traffic infrastructure to obtain status and information of traffic lights. When the vehicle passes a congestion node, if the node is connected with a signal lamp, the system can predict the congestion condition of the road section ahead through the received signal lamp information and send a diversion suggestion to a driver.
S104, calculating the passing speed of each direction of the congestion node, and dividing the congestion direction and the non-congestion direction;
in order to more fully understand and address traffic congestion problems, an in-depth analysis of traffic speeds in various directions is required. This process involves two key steps: firstly, calculating the average travel speed of lanes or roads in each direction in a preset time interval; next, the congestion direction and the non-congestion direction are further divided based on these speed data. The method comprises the following specific steps:
s501, calculating the average journey speed in a preset time interval for the lanes or roads in each direction;
s502, setting a congestion speed threshold;
this threshold should be based on a combination of historical data and actual conditions to distinguish between normal traffic speeds and speeds in case of congestion.
S503 sets the congestion direction when the average travel speed in a certain direction is lower than the congestion speed threshold, otherwise, sets the congestion direction.
Specifically, if the average trip speed in a certain direction is lower than the congestion speed threshold set by us, we can determine it as the congestion direction. Such partitioning helps us better understand and address traffic congestion issues, providing a powerful basis for subsequent traffic management and optimization.
S105, generating waiting time based on the traffic speed in the non-congestion direction and the number of waiting vehicles, and passing in the non-congestion direction within the waiting time;
the method comprises the following specific steps:
s601, acquiring a traffic speed in a non-congestion direction;
such information may be from cameras, radar, GPS, etc. on the road or obtained by exchanging data with traffic management centers in neighboring areas. These devices are capable of monitoring road conditions, including traffic flow, speed, etc., in real-time.
S602, identifying the number of waiting vehicles based on the monitoring image;
the monitoring image can be obtained by a camera on the road, and then the vehicles in the image are counted and analyzed by utilizing the image processing and recognition technology. This step is critical for accurate determination of traffic conditions and calculation of latency.
S603 calculates a waiting time in which the vehicle in this direction passes based on the passing speed and the number of vehicles.
The time for passing through a single automobile can be calculated based on the passing speed and the distance of the intersection, then the time for passing through all automobiles can be calculated by combining the number of the automobiles, and then the automobiles can normally pass in the corresponding direction in the time period.
S106, sequentially controlling the traffic of vehicles according to the directions of the congestion road sections according to the reserved space on the congestion road sections in the waiting time;
the method comprises the following specific steps:
s701, calculating the moving length of the traffic flow based on the waiting time and the traffic speed of the congested road section;
the traffic of the congested road segment is also continuously moving during the waiting time to obtain a movement length of the traffic, which indicates the number of vehicles that can enter.
S702, calculating the number of the receivable vehicles based on the moving length;
the number of accommodated vehicles can be calculated by the average length and the moving length of the vehicles.
S703 sequentially controls traffic lights to be communicated at the same time in each direction of entering the congested road section based on the number of vehicles.
The corresponding lane may then be controlled to pass a specified number of vehicles in a clockwise or counterclockwise order according to the number of vehicles. Therefore, the normal traffic of the non-congested road section can be prevented from being influenced by the congested road section.
S107, adjusting the traffic time proportion based on the queuing lengths in all directions of the entering congestion road section;
the method specifically comprises the steps of monitoring the queuing lengths of vehicles on lanes in all directions in real time by using equipment such as video detection, induction coils, radars, microwaves and the like; according to the queuing lengths in all directions and the arrival rate of vehicles, calculating the proportion of the actual traffic demand in each direction to the total traffic demand of the whole intersection; and combining the actual traffic demand proportion with the theoretical traffic capacity, and dynamically adjusting the duration of the green light in each direction.
S108, monitoring and recording the running light condition of the vehicle.
The real-time video stream analysis can be performed by utilizing the computer vision technology, the states of license plate numbers and traffic lights can be accurately identified, then the snap-shot vehicle pictures are compared with the vehicle information in the database, and the related information of the owners, the vehicle types and the like of the vehicles is verified; then according to the road traffic safety regulation, after confirming the illegal action of the vehicle, recording the illegal record into the electronic police system
S109, data mining is conducted based on traffic light control data of the congestion nodes to generate traffic light control rules.
The specific steps include collecting traffic light control data of the road junction; converting the original traffic light control data into a transaction data format, wherein each transaction represents a specific time period or intersection state combination (for example, the green light duration of each direction of an intersection in a certain time period); according to actual requirements and data analysis purposes, determining a threshold value of minimum support (frequency of occurrence of one item set) and minimum confidence (probability of occurrence of a back part after occurrence of the front part in a rule); grouping analysis is carried out on the data according to the corresponding days of each week, such as a workday mode from Monday to Friday and a holiday mode from Saturday; starting from a single element, finding out all frequent item sets meeting the minimum support requirement; using Apriori properties (i.e. "if one item set is frequent, then all non-empty subsets thereof are frequent"), generating new candidate item sets and verifying whether the candidate item sets reach minimum support by scanning the data set; for all the frequent item sets found in the previous step, generating a higher-order candidate frequent item set by applying the Apriori property again; for each found frequent item set, all possible association rules are generated (each rule consists of two parts: front piece and back piece, such as { workday, peak in the morning } - > { east-west green light longer }).
Based on the association rule, a corresponding traffic light control rule can be generated to better adjust the duration of the traffic light, and the traffic efficiency is improved.
Second embodiment
The invention provides an intelligent traffic control system which comprises an information acquisition module, a congestion node identification module, a diversion module, a direction distinguishing module, a non-congestion traffic module, a congestion traffic module, an adjusting module and a monitoring module, wherein the information acquisition module is used for acquiring information of a congestion node; the information acquisition module is used for acquiring traffic information to obtain traffic data; the congestion node identification module is used for analyzing traffic data to identify congestion nodes; the shunting module is used for acquiring shunting nodes adjacent to the congestion node so as to prompt shunting in advance; the direction distinguishing module is used for calculating the passing speed of each direction of the congestion node and dividing the congestion direction and the non-congestion direction; the non-congestion passing module is used for generating waiting time based on the passing speed of the non-congestion direction and the number of waiting vehicles, and passing in the non-congestion direction within the waiting time; the congestion passing module is used for sequentially controlling the passing of vehicles according to the directions of the congestion road sections according to the reserved space on the congestion road sections in the waiting time; the adjusting module is used for adjusting the traffic time proportion based on the queuing lengths in all directions of the entering congestion road section; the monitoring module is used for monitoring and recording the running light condition of the vehicle.
In the present embodiment, the key points of traffic congestion can be clearly identified by further analysis of a large amount of traffic information. These congestion points typically occur during periods of high traffic flow or under certain conditions. The system automatically detects the adjacent congested nodes at these points to effect traffic diversion when needed. Congestion nodes are nodes that are located near the point of congestion and that are effective in dispersing traffic. By properly guiding the vehicle to these points, the pressure of the congested road segment can be significantly relieved. The system can also estimate the driving speeds of the congestion points in different directions and divide the directions of congestion and non-congestion based on the data. For the uncongested direction, the system can provide a reasonable waiting time according to the real-time road condition and the number of vehicles, so that the vehicles can pass without restriction. In the congestion direction, the system sequentially controls the vehicles to enter the congestion road section according to the space in the waiting time. The management mode is beneficial to relieving the congestion and improving the road passing efficiency. In addition, the system can dynamically adjust the traffic time proportion of each direction and is based on the queuing length of vehicles in each direction. To maintain traffic order, the system also monitors and records vehicle violations, such as red light running. Running the red light not only endangers traffic safety, but also destroys traffic order. The real-time monitoring and recording function of the system provides powerful support for law enforcement agencies and helps to reduce such bad driving behavior. In general, the intelligent traffic management system realizes the intellectualization of traffic management through scientific means, effectively solves the problem of traffic jam, improves the road use efficiency, ensures the traffic safety and reduces the illegal behaviors.
The above disclosure is only a preferred embodiment of the present invention, and it should be understood that the scope of the invention is not limited thereto, and those skilled in the art will appreciate that all or part of the procedures described above can be performed according to the equivalent changes of the claims, and still fall within the scope of the present invention.
Claims (9)
1. An intelligent traffic control method is characterized in that,
the method comprises the steps of collecting traffic information to obtain traffic data;
analyzing the traffic data to identify a congested node;
acquiring adjacent shunting nodes of the congestion node to prompt shunting in advance;
calculating the passing speed of each direction of the congestion node, and dividing the congestion direction and the non-congestion direction;
generating waiting time based on the traffic speed of the non-congestion direction and the number of waiting vehicles, and passing the non-congestion direction in the waiting time;
according to the reserved space on the congested road section in the waiting time, sequentially controlling the traffic of vehicles according to each direction of entering the congested road section;
adjusting the traffic time proportion based on queuing lengths in all directions of entering the congested road section;
and monitoring and recording the running condition of the vehicle.
2. The intelligent traffic control method according to claim 1, wherein,
after the monitoring and recording of the running light condition of the vehicle, the intelligent traffic control method further comprises the step of carrying out data mining on the basis of traffic light control data of the congestion nodes so as to generate traffic light control rules.
3. The intelligent traffic control method according to claim 2, wherein,
the specific steps of acquiring traffic information and obtaining traffic data comprise:
collecting traffic data in real time through deployed monitoring equipment;
transmitting the collected traffic information to a central processing system through a network;
and in the central processing system, preprocessing the acquired data to obtain traffic data.
4. The intelligent traffic control method according to claim 3, wherein,
the specific steps of processing and analyzing the traffic data to identify the congestion node include:
acquiring a traffic intersection node;
identifying the speed of all lanes based on the traffic intersection nodes;
and generating a congestion node when the minimum vehicle speed is lower than a preset value.
5. The intelligent traffic control method according to claim 4, wherein,
the specific step of acquiring the shunting nodes adjacent to the congestion node to prompt shunting in advance comprises the following steps:
retrieving traffic nodes adjacent to the target map based on the congestion nodes;
and prompting forward congestion proposal diversion through signal lamps of traffic nodes.
6. The intelligent traffic control method according to claim 5, wherein,
the specific steps of calculating the passing speed of each direction of the congestion node and dividing the congestion direction and the non-congestion direction comprise the following steps:
for each directional lane or road, calculating an average journey speed within a preset time interval;
setting a congestion speed threshold;
when the average travel speed in a certain direction is lower than the congestion speed threshold value, setting the congestion direction, otherwise, setting the congestion direction as a non-congestion direction.
7. The intelligent traffic control method according to claim 6, wherein,
the specific steps of generating waiting time based on the traffic speed in the non-congestion direction and the number of waiting vehicles, and passing in the non-congestion direction within the waiting time include:
acquiring the traffic speed in the non-congestion direction;
identifying the number of waiting vehicles based on the monitoring image;
a waiting time is calculated based on the passing speed and the number of vehicles, and the vehicles in this direction pass during the waiting time.
8. The intelligent traffic control method according to claim 7, wherein,
the specific steps of sequentially controlling the traffic of the vehicles according to the preset waiting time and all directions entering the congested road section comprise the following steps:
calculating the moving length of the traffic flow based on the waiting time and the traffic speed of the congested road section;
calculating the number of receivable vehicles based on the movement length;
and sequentially controlling the traffic lights to be communicated at the same time according to all directions entering the congested road section based on the number of vehicles.
9. An intelligent traffic control system is characterized in that,
the system comprises an information acquisition module, a congestion node identification module, a diversion module, a direction distinguishing module, a non-congestion passing module, a congestion passing module, an adjusting module and a monitoring module;
the information acquisition module is used for acquiring traffic information to obtain traffic data;
the congestion node identification module is used for analyzing traffic data to identify congestion nodes;
the shunting module is used for acquiring shunting nodes adjacent to the congestion node so as to prompt shunting in advance;
the direction distinguishing module is used for calculating the passing speed of each direction of the congestion node and dividing the congestion direction and the non-congestion direction;
the non-congestion passing module is used for generating waiting time based on the passing speed of the non-congestion direction and the number of waiting vehicles, and passing in the non-congestion direction within the waiting time;
the congestion passing module is used for sequentially controlling the passing of vehicles according to the directions of the congestion road sections according to the reserved space on the congestion road sections in the waiting time;
the adjusting module is used for adjusting the traffic time proportion based on the queuing lengths in all directions of the entering congestion road section;
the monitoring module is used for monitoring and recording the running light condition of the vehicle.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118587912A (en) * | 2024-06-04 | 2024-09-03 | 重庆市工程管理有限公司 | A method for monitoring traffic flow on municipal roads based on the Internet of Things |
| CN119252034A (en) * | 2024-12-05 | 2025-01-03 | 山东科技大学 | A multi-lane diversion control method, device and medium |
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