CN112017455A - Intelligent traffic light coordination control method applied to intelligent traffic - Google Patents
Intelligent traffic light coordination control method applied to intelligent traffic Download PDFInfo
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- CN112017455A CN112017455A CN202010973618.1A CN202010973618A CN112017455A CN 112017455 A CN112017455 A CN 112017455A CN 202010973618 A CN202010973618 A CN 202010973618A CN 112017455 A CN112017455 A CN 112017455A
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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
- G08G1/081—Plural intersections under common control
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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
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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
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/095—Traffic lights
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Abstract
The invention relates to an intelligent traffic light coordination control method applied to intelligent traffic, and belongs to the technical field of intelligent traffic. Firstly, counting vehicle queuing lengths when red lights of all roads of a traffic channel intersection are obtained, and storing a main road mark and the corresponding queuing length into a main road intersection state table; the method comprises the following steps of collecting images through a camera, and measuring the queuing length of a vehicle by a vehicle queuing length measuring module; if the queuing length of any road is greater than a preset maximum threshold, inquiring a main road intersection state table, and acquiring a main road identifier and an allowable identifier of an adjacent intersection on the upper and lower reaches of the main road identifier; and if the permission flag is '1', performing coordinated linkage control, and finishing linkage control when the A, B, C queue lengths are all smaller than a minimum threshold value. The invention can quickly monitor vehicle congestion, dredge road vehicles and avoid traffic paralysis.
Description
Technical Field
The invention relates to an intelligent traffic light coordination control method applied to intelligent traffic, and belongs to the technical field of intelligent traffic.
Background
With the rapid increase of the number of urban vehicles, the contradiction between the vehicles and roads is increasingly prominent, and the bottleneck effect of intersections is more prominent. The traffic lights are arranged at the crossroad, so that traffic can be effectively dredged, and favorable guarantee is provided for the safety of pedestrians. Traffic light control is therefore becoming increasingly important in everyday life. Conventional traffic signal control schemes suffer from significant drawbacks. Because the control time is preset, the automatic regulation can not be carried out no matter the real-time traffic flow condition. This weakness has led to a failure to intelligently address traffic congestion problems. In the prior art, traffic lights at one intersection are generally controlled individually, and in the current urban traffic, the traffic conditions of each adjacent road are generally correlated and influenced with each other, and the individual control only considers the traffic conditions of one road and wants to relieve the traffic jam or the waggon of the whole city.
Disclosure of Invention
The invention aims to solve the technical problem of providing an intelligent traffic light coordination control method applied to intelligent traffic, which can ensure the current duration, give priority to certain lanes according to real-time traffic conditions, adjust the time length of traffic lights by the queuing length of each road vehicle when detecting red light, effectively relieve the traffic conditions at congested intersections and solve the problems.
The technical scheme of the invention is as follows: an intelligent traffic light coordination control method applied to intelligent traffic comprises the following specific steps:
step 1: and counting and acquiring the queuing length of each road adjacent to one road intersection at the time of red light, and storing the queuing length corresponding to the main road into a main road intersection state table according to the main road identification.
Step 2: preprocessing, extracting ROI, acquiring vehicle information, and calculating to obtain vehicle queuing length, specifically:
step2.1: intercepting images from a video captured by a camera by using a processor, and performing a series of preprocessing, wherein the preprocessing comprises the following steps: graying processing, image smoothing processing and image registration processing.
Step2.2: the method comprises the steps of obtaining an ROI (region of interest), wherein the region is to contain an image to be processed and only contains one lane, setting a vehicle stop line as a starting point, and setting a maximum threshold as an end point. The obtained ROI may not contain white lane lines due to large variation of the gray gradient at the edges of the lane lines, otherwise the pixel statistics are affected.
Step2.3: the vehicle queuing length detection module is used for determining the queuing length, and after the vehicle queuing end point is determined, the queuing length on the two-dimensional image can be obtained, so that the actual vehicle queuing length can be calculated.
Step 3: comparing the queuing length of each road with a maximum threshold value respectively, judging that the intersection of the road is congested when the acquired queuing length of any road of the intersection is greater than the maximum threshold value, inquiring a main road intersection state table of the intersection to acquire the identifier of the main road and the allowed identifiers of adjacent intersections of the upper and lower streams, and determining that the main road and the intersections of the upper and lower streams are allowed to coordinate and link control when the logic values of the allowed identifiers of the adjacent intersections of the main road and the upper and lower streams of the intersection are all '1'.
Preferably, the maximum threshold is set to be 75 meters, and this value range can avoid that the traffic light time is adjusted when the road is not very congested, and can also adjust the traffic light time in time when the road is congested, so as to avoid the deterioration of the traffic condition.
Step 4: the method comprises the steps of obtaining the A-type queuing length and the A-type green light duration corresponding to a main road identifier by inquiring a state table of a main road intersection of the road intersection, obtaining the B-type queuing length and the B-type green light duration of an adjacent intersection at the upstream of the main road, and obtaining the C-type queuing length and the C-type green light duration of an adjacent intersection at the downstream of the main road, and carrying out coordinated linkage control on traffic lights according to the determined A, B, C-type queuing length pair and A, B, C-type green light duration.
Wherein, the content recorded in the main road intersection state table comprises: the serial number of each road connected with the road port; whether each road connected with the intersection is the mark of the main road or not; the mark of the upstream and downstream crossing adjacent to the main road and the allowable mark whether to allow coordinated linkage control or not; the A, B, C class green time at the intersection.
The Step4 is specifically as follows:
calculating the green light passing time T of the congested road traffic intersection on the main road according to the formula (1):
in the formula (1), L1 is a class a queuing length, L2 is a class B queuing length, L3 is a class C queuing length, L is a congestion critical queuing length, t1 is the original class a green light duration on the main road at the determined congested road traffic intersection, t2 is the original class B green light duration at the upstream adjacent intersection of the main road, and t3 is the original class C green light duration at the downstream adjacent intersection of the main road.
And controlling the green light time length of the main road of the adjacent crossroads at the upstream and the downstream of the congested traffic intersection according to the determined green light time length.
After completing the coordinated linkage control of the green light time length of the road intersection, the upstream adjacent intersection and the downstream adjacent intersection in the main road direction, if the queue length of each road is less than the minimum threshold value, ending the coordinated linkage control, wherein the minimum threshold value is 25 meters.
The congestion critical queuing length L is 50 meters.
The invention has the beneficial effects that: when congestion occurs when one road intersection is queued for too long, the green light duration of three adjacent intersections on the main road can be adjusted according to the queuing length of the road intersection and the queuing lengths of the adjacent upstream and downstream intersections of the main road, so that the vehicle passing and queuing time is greatly reduced, the potential possibility of large-scale vehicle congestion is reduced, and the traffic pressure is effectively relieved.
Drawings
FIG. 1 is a schematic structural diagram of a signal lamp control device according to an embodiment of the present invention;
FIG. 2 is a flow chart of the steps of the present invention;
fig. 3 is a schematic diagram of the identification of a road intersection in the embodiment of the invention.
Detailed Description
The invention is further described with reference to the following drawings and detailed description.
Example 1: firstly, a signal lamp control device is arranged at a traffic intersection, and as shown in fig. 1, the signal lamp control device comprises a vehicle queuing length detection module 10, a signal lamp adjusting module 20 and a storage unit 30 in which a main road intersection state table is stored.
The vehicle queue length detection module 10 receives image information transmitted from a camera mounted on a road. The detection module 10 calculates the queue length by image information measurement, and stores the queue length of the road into the main road state table 30 according to the serial number of the road. When the obtained queuing length of any one road is greater than the preset maximum threshold, it is determined that the road is congested, the queuing length is sent to the signal lamp adjusting module 20, and the signal lamp adjusting module 20 queries the road junction state table 30 to obtain the main road identifier and the allowed identifiers of the adjacent upstream and downstream junctions. If the traffic light adjusting module 20 allows, the traffic light adjusting module 20 queries the road junction status table 30, and obtains the class a queuing length and the class a green light duration corresponding to the main road identifier of the road junction, the class B queuing length and the class B green light duration of the upstream adjacent junction, and the class C queuing length and the class C green light duration of the downstream adjacent junction for coordinated linkage control. When the queue lengths of all roads are less than the minimum threshold, the signal light adjustment module adjusts the A, B, C-type green light time to the original value.
As shown in fig. 2, an intelligent traffic light coordination control method applied to intelligent traffic includes the following specific steps:
step 1: and counting and acquiring the queuing length of each road adjacent to one road intersection at the time of red light, and storing the queuing length corresponding to the main road into a main road intersection state table according to the main road identification.
Step 2: and (4) carrying out a series of preprocessing, extracting the ROI, acquiring vehicle information, and calculating to obtain the vehicle queuing length.
Step 3: and comparing the queuing length of each road with the maximum threshold value respectively, if the queuing length of any road is greater than the maximum threshold value, determining that the intersection of the road is congested, and continuing Step4, otherwise, returning to Step 1. Preferably, the maximum threshold is set to be 75 meters, and this value range can avoid that the traffic light time is adjusted when the road is not very congested, and can also adjust the traffic light time in time when the road is congested, so as to avoid the deterioration of the traffic condition.
Step 4: and inquiring a main road intersection state table of the road intersection to obtain a main road identifier and allowed identifiers of upstream and downstream intersections adjacent to the main road identifier.
Step 5: and judging whether the coordinated linkage control is allowed according to the acquired permission identifier. If the acquired logical value is "1", the process is determined as allowable, and the process proceeds to Step6, whereas if the acquired logical value is "0", the process is determined as not allowable, and the process returns to Step 1.
And performing coordinated linkage control according to the determined A-type queuing length and A-type green light duration corresponding to the main road identifier, the B-type queuing length and B-type green light duration of an upstream adjacent intersection of the main road, and the C-type queuing length and C-type green light duration of a downstream adjacent intersection.
Step 6: and after the coordinated linkage control of Step5 is finished, judging whether the queuing length of each road is smaller than a minimum threshold value, if so, adjusting the green time of each road to be an original value, and finishing the coordinated linkage control. Otherwise, go back to Step 1.
As shown in fig. 3, the road junction of the present invention is schematically illustrated. The main road intersection is A, the upstream intersection is B, and the downstream intersection is C (from east to west to go to the vehicle).
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes can be made without departing from the spirit and scope of the present invention.
Claims (4)
1. An intelligent traffic light coordination control method applied to intelligent traffic is characterized by comprising the following steps:
step 1: counting and acquiring the queuing length of each road adjacent to one road intersection when the road is red, and storing the queuing length corresponding to the main road into a main road intersection state table according to the main road identification;
step 2: preprocessing, extracting ROI, obtaining vehicle information and obtaining vehicle queuing length;
step 3: comparing the queuing length of each road with a maximum threshold value respectively, judging that the intersection of the road is congested when the queuing length of any one road of the acquired road is greater than the maximum threshold value, inquiring a main road intersection state table of the intersection to acquire an identifier of the main road and an allowable identifier of an intersection adjacent to the main road and the upstream and downstream, and determining that the main road and the intersection adjacent to the upstream and downstream are allowed to coordinate and link control when the logic values of the allowable identifiers of the intersections adjacent to the main road and the upstream and downstream of the intersection are all '1';
step 4: the method comprises the steps of obtaining the A-type queuing length and the A-type green light duration corresponding to a main road identifier by inquiring a state table of a main road intersection of the road intersection, obtaining the B-type queuing length and the B-type green light duration of an adjacent intersection at the upstream of the main road, and obtaining the C-type queuing length and the C-type green light duration of an adjacent intersection at the downstream of the main road, and carrying out coordinated linkage control on traffic lights according to the determined A, B, C-type queuing length pair and A, B, C-type green light duration.
2. The method as claimed in claim 1, wherein Step4 is specifically comprised of:
calculating the green light passing time T of the congested road traffic intersection on the main road according to the formula (1):
in the formula (1), L1 is the A-type queuing length, L2 is the B-type queuing length, L3 is the C-type queuing length, L is the congestion critical queuing length, t1 is the original A-type green light duration on the main road of the determined congested road traffic intersection, t2 is the original B-type green light duration of the upstream adjacent intersection of the main road, and t3 is the original C-type green light duration of the downstream adjacent intersection of the main road;
controlling the green light time length of the main road of the adjacent crossroads at the upstream and the downstream of the congested traffic intersection according to the determined green light time length;
after completing the coordinated linkage control of the green light time length of the road intersection, the upstream adjacent intersection and the downstream adjacent intersection in the main road direction, if the queue length of each road is less than the minimum threshold value, ending the coordinated linkage control, wherein the minimum threshold value is 25 meters.
3. The intelligent traffic light coordination control method applied to intelligent traffic as claimed in claim 1, wherein: the maximum threshold is 75 meters.
4. The intelligent traffic light coordination control method applied to intelligent traffic as claimed in claim 2, wherein: the congestion critical queuing length L is 50 meters.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113112824A (en) * | 2021-03-19 | 2021-07-13 | 杭州航弘建设科技有限公司 | Road regulation and control method and device, intelligent terminal and storage medium |
| CN113593267A (en) * | 2021-06-25 | 2021-11-02 | 青岛海尔科技有限公司 | Traffic light control method and traffic light control device |
| CN114067573A (en) * | 2022-01-11 | 2022-02-18 | 成都宜泊信息科技有限公司 | Parking lot guarding method and system, storage medium and electronic equipment |
| CN117912271A (en) * | 2024-01-02 | 2024-04-19 | 浙江中控信息产业股份有限公司 | Green wave period coordination control method based on intersection group |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103985254A (en) * | 2014-05-29 | 2014-08-13 | 四川川大智胜软件股份有限公司 | Multi-view video fusion and traffic parameter collecting method for large-scale scene traffic monitoring |
| CN104123849A (en) * | 2014-07-14 | 2014-10-29 | 昆明理工大学 | Adjacent intersection bidirectional linkage control method in consideration of dynamic queuing length |
| CN105303850A (en) * | 2015-10-20 | 2016-02-03 | 北京长峰金鼎科技有限公司 | Control method for traffic signal lamp of crossing |
| CN105390001A (en) * | 2015-10-20 | 2016-03-09 | 北京长峰金鼎科技有限公司 | Dynamic control method of traffic signal lamps |
| CN105551269A (en) * | 2015-12-15 | 2016-05-04 | 邹晓虎 | Intelligent traffic control method for traffic signal lamps of smart city |
| CN105608911A (en) * | 2016-01-19 | 2016-05-25 | 邹晓虎 | Intelligent control method of traffic light of urban main road |
| CN109410608A (en) * | 2018-11-07 | 2019-03-01 | 泽交通工程咨询（上海）有限公司 | Picture self study traffic signal control method based on convolutional neural networks |
-
2020
- 2020-09-16 CN CN202010973618.1A patent/CN112017455A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103985254A (en) * | 2014-05-29 | 2014-08-13 | 四川川大智胜软件股份有限公司 | Multi-view video fusion and traffic parameter collecting method for large-scale scene traffic monitoring |
| CN104123849A (en) * | 2014-07-14 | 2014-10-29 | 昆明理工大学 | Adjacent intersection bidirectional linkage control method in consideration of dynamic queuing length |
| CN105303850A (en) * | 2015-10-20 | 2016-02-03 | 北京长峰金鼎科技有限公司 | Control method for traffic signal lamp of crossing |
| CN105390001A (en) * | 2015-10-20 | 2016-03-09 | 北京长峰金鼎科技有限公司 | Dynamic control method of traffic signal lamps |
| CN105551269A (en) * | 2015-12-15 | 2016-05-04 | 邹晓虎 | Intelligent traffic control method for traffic signal lamps of smart city |
| CN105608911A (en) * | 2016-01-19 | 2016-05-25 | 邹晓虎 | Intelligent control method of traffic light of urban main road |
| CN109410608A (en) * | 2018-11-07 | 2019-03-01 | 泽交通工程咨询（上海）有限公司 | Picture self study traffic signal control method based on convolutional neural networks |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113112824A (en) * | 2021-03-19 | 2021-07-13 | 杭州航弘建设科技有限公司 | Road regulation and control method and device, intelligent terminal and storage medium |
| CN113593267A (en) * | 2021-06-25 | 2021-11-02 | 青岛海尔科技有限公司 | Traffic light control method and traffic light control device |
| CN114067573A (en) * | 2022-01-11 | 2022-02-18 | 成都宜泊信息科技有限公司 | Parking lot guarding method and system, storage medium and electronic equipment |
| CN114067573B (en) * | 2022-01-11 | 2022-04-12 | 成都宜泊信息科技有限公司 | Parking lot guarding method and system, storage medium and electronic equipment |
| CN117912271A (en) * | 2024-01-02 | 2024-04-19 | 浙江中控信息产业股份有限公司 | Green wave period coordination control method based on intersection group |
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