CN110992684B - Active prediction type signal control method and system based on video detection - Google Patents
Active prediction type signal control method and system based on video detection Download PDFInfo
- Publication number
- CN110992684B CN110992684B CN201911054990.6A CN201911054990A CN110992684B CN 110992684 B CN110992684 B CN 110992684B CN 201911054990 A CN201911054990 A CN 201911054990A CN 110992684 B CN110992684 B CN 110992684B
- Authority
- CN
- China
- Prior art keywords
- time
- video
- phase
- video information
- vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
-
- 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
-
- 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
- G08G1/015—Detecting movement of traffic to be counted or controlled with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/087—Override of traffic control, e.g. by signal transmitted by an emergency vehicle
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses an active prediction type signal control method and system based on video detection, which are used for simultaneously acquiring signal lamp information in a road passing direction and video information of three sections of a road, wherein the three sections comprise a front section, a middle section and a rear section of a stop line, each section comprises vehicle information in each passing direction, and the vehicle information in the front section, the middle section and the rear section is optimized and controlled respectively, so that the problem that the traditional mode of polling monitoring video time is solved, the video monitoring of multiple sections provides comprehensive road vehicle running conditions, an optimization control strategy of the current period can be directly calculated, the optimization control strategy acts on the current period, and the timeliness requirement of traffic flow condition response is met.
Description
Technical Field
The invention relates to the technical field of video detection control, in particular to an active prediction type signal control method and system based on video detection.
Background
The urban vehicles are more and more, and how to relieve traffic jam, reduce environmental pollution and improve traffic management efficiency under the premise of ensuring traffic safety in the existing road environment is a problem which needs to be solved urgently in each city.
At present, real-time dynamic optimization of traffic lights according to traffic flow is an important means for relieving urban traffic jam, and many companies try to make some signal optimization control systems to relieve the jam, but the implementation effect is poor. There are mainly the following reasons:
the existing video detection basically uses one camera, so that more video blind areas can be seen, and the running condition of the road vehicles at the intersection can not be provided comprehensively.
2. Most of the existing video vehicle detectors are installed on an electronic police rod, a virtual detection frame is drawn at a position 40 meters away from a stop line, and actual detection is carried out in a small-range area, similar to a coil or geomagnetic point detection mode.
3. Most of the so-called adaptive signal control in the market at present is a passive adjustment type control strategy, that is, currently detected traffic flow information is used for adjusting the time and period of the next phase. Thus, the current traffic flow condition cannot be responded in time.
4. At present, signal optimization mainly takes a vehicle as a main part, and the number of passengers on the vehicle is not the same, so that a plurality of vehicles pass through a green light period, but the total number of passing passengers is not always large, the time of all people is not reduced, and the optimal control effect cannot be achieved.
Therefore, it is an urgent need to solve the above-mentioned problems by those skilled in the art to provide an active predictive signal control method and system based on video detection, which can actively optimize the signal timing in real time.
Disclosure of Invention
In view of the above, the present invention provides an active predictive signal control method and system based on video detection. The multi-view video monitoring solves the problem that the traditional mode of polling the monitoring video time is solved, the multi-section video monitoring provides comprehensive road vehicle running conditions, the optimization control strategy of the current period can be directly calculated, and the optimization control strategy acts on the current period to meet the timeliness requirement of traffic flow condition response.
In order to achieve the purpose, the invention adopts the following technical scheme:
an active prediction type signal control method based on video detection comprises the following steps:
s1, simultaneously acquiring signal light information of the road passing direction and video information of three sections of the road, wherein the three sections comprise a front area, a middle area and a rear area of a stop line, and each section comprises vehicle information of each passing direction;
s2, judging whether the rear video information contains a motorcade/group image, if so, entering a third step, otherwise, controlling a signal lamp according to an initial timing mode;
s3, judging whether the number of waiting vehicles in the video information in the middle area and the number of passenger flows of the unit vehicle exceed a threshold value F2, if not, judging whether the time is predicted when time allocation needs to be optimized, if so, entering the step four, and if not, controlling a signal lamp according to an initial time allocation mode;
and S4, judging whether the front zone video information has vehicle congestion, and if so, controlling the current direction signal lamp to be red.
Preferably, the front area in S1 includes a region where the stopping line extends 0-80 m toward the crossing; the middle area comprises an area with a stopping line extending to the rear of the intersection for 0-80 m; the rear zone comprises a range area which extends to the rear of the intersection by 80-150 m from the stop line.
Preferably, the step S2 further includes detecting position information of a head and a tail of the fleet of vehicles, and predicting a time when the fleet of vehicles passes through the stop line, so as to control the extension duration of the corresponding phase signal lamp street lamp signal, the early turn-off time of the red lamp, and the duration of the phase-superimposed green lamp signal. The phase refers to the combination of the light colors of the signal cycle of the lane in the current direction, the phase is divided according to the time sequence of obtaining signal display of the traffic flow, and the signal phases are arranged in different time sequences. In the traffic signal, there is a phase control for each traffic stream. For example, when the intersection is released in a bidirectional left-turn four-phase symmetric manner, eight traffic flows of east straight traffic, east left-turn traffic, west straight traffic, west left-turn traffic, south straight traffic, south left-turn traffic, north straight traffic and north left-turn traffic correspond to one phase respectively, so that 8 phases exist, and only four phase stages exist.
Preferably, the method further comprises the following steps after S3:
s5, if the number of the waiting vehicles in the middle area video information exceeds a threshold value F2, further judging whether the number of the waiting vehicles in the middle area video information and the number of the passenger flow of the unit vehicle exceed a threshold value F1, wherein F1 is larger than F2, and when the number of the waiting vehicles exceeds a threshold value F1, entering S6;
s6, judging whether the current phase is a green light, if so, entering S7;
and S7, judging whether the residual time of the green light in the current phase exceeds a threshold G1, if so, ending the phase control process, otherwise, prolonging the green light time in the phase, and returning to S6.
Preferably, the method further comprises the following steps after S6:
s8, if the current phase is not the green light, executing the early-off operation of the red light, and entering S9;
and S9, superposing the current phase time and the green time of the next phase, judging whether the superposed time exceeds preset time, if so, ending the phase control flow, and otherwise, returning to S5.
It should be noted that, S4-S9 all belong to specific methods for optimizing the timing prediction time. The comparison with the booking time is made in consideration of the fact that the signal light cycle time length of the whole intersection cannot be too large or too small, otherwise the signal light cycle of the next intersection is affected. For S8 when the red light is early off and the green light is performed, the collision phase will necessarily end the green light, and the red light phase is performed, and the overlap time is: the green time of the conflict phase that has been performed plus the green time of the current phase.
Preferably, the method further comprises a multi-level priority control method: the green light is given a right of passage in a priority order, wherein,
when a public rescue vehicle is detected in the video information, giving a first priority to a current direction signal lamp;
when the public transportation vehicle is detected in the video information, giving a second priority to the signal lamp in the current direction;
giving a third priority to the current direction signal lamp when the number of passengers in the vehicle detected in the video information is more than two;
the remaining cases belong to a fourth priority, performed according to the video detection based active predictive type signal control method as claimed in claim 1.
An active predictive type signal control system based on video detection, comprising: a multi-view camera mechanism, a video detector and a signal machine, wherein,
the multi-view camera shooting mechanism is used for acquiring video information of three sections of the current intersection, wherein the three sections comprise a front area, a middle area and a rear area of a stop line; each section comprises vehicle information of each passing direction;
the video detector is used for detecting the signal lamp state of each passing direction of the current intersection;
and the signaler executes the active prediction type signal control method based on the video detection on the current period according to the signal lamp state detected by the video detector and the video information acquired by the multi-view camera mechanism, wherein the period refers to the time of 4 direction signal lamps circulating for one circle.
Preferably, the multi-view camera shooting mechanism comprises a shell and a plurality of video acquisition boards arranged in the shell, and the plurality of video acquisition boards are uniformly distributed along different directions; the video acquisition boards are connected to the video fusion processing board, and the video fusion processing board is connected with the wireless communication board; the video fusion processing board is further connected with a neural network acceleration board and used for carrying out vehicle contour recognition on the fusion spliced video, the video fusion processing board is connected with the wireless communication board, and the wireless communication board is connected with a command center platform or/and an LED large screen.
Through the technical scheme, the invention discloses and provides an active prediction type signal control method and system based on video detection. Compared with the prior art, the method has the following advantages:
1. firstly, splicing and fusing videos of a plurality of lenses together to form a large scene video picture; the process videos of the vehicle at the front, middle and rear of the camera installation site can be viewed simultaneously. The detection range can obtain the range of 80 meters in the forward direction, 80 meters in the middle direction and 80 meters in the backward direction, and the total range is 240 meters.
2. By adopting an optimized deep learning algorithm, the accurate detection of the video information of multiple sections is realized, the real-time output of the fleet/group conditions, the traffic flow information and the intersection congestion information of the front area, the middle area and the rear area of the road is realized, the running condition of road vehicles can be comprehensively reflected, and thus, data support is provided for the active optimization of signal timing.
3. The current detected traffic flow information directly acts on the signal lamp control of the current phase, and can timely respond to the current traffic flow condition.
4. Based on a multi-level priority control strategy, the problem that the current signal optimization mode mainly takes vehicles instead of passenger carrying number as main is effectively solved, and the optimal time for the people to pass through the intersection is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic flow chart of an active predictive signal control method based on video detection according to the present invention.
Fig. 2 is a field schematic diagram of an active predictive signal control method based on video detection according to the present invention.
Fig. 3 is a diagram of the tissue architecture of an active predictive signal control system based on video detection according to the present invention;
FIG. 4 is a block diagram of a multi-view camera mechanism provided by the present invention;
fig. 5 is an exploded view of the multi-view camera shooting mechanism structure provided by the invention.
Detailed Description
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, and not all of the embodiments. 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.
The embodiment of the invention discloses an active prediction type signal control method based on video detection, which is shown in the attached figures 1-2 and comprises the following steps:
s1, simultaneously acquiring signal light information of the road passing direction and video information of three sections of the road, wherein the three sections comprise a front area, a middle area and a rear area of a stop line, and each section comprises vehicle information of each passing direction;
s2, judging whether the rear video information contains a motorcade/group image, if so, entering a third step, otherwise, controlling a signal lamp according to an initial timing mode;
s3, judging whether the number of waiting vehicles in the video information in the middle area and the number of passenger flows of the unit vehicle exceed a threshold value F2, if so, entering S5, otherwise, judging whether the time prediction needs to be optimized, if so, entering a step four, and if not, controlling a signal lamp according to an initial time distribution mode;
and S4, judging whether the front zone video information has vehicle congestion, and if so, controlling the current direction signal lamp to be red. And if the current video information contains a plurality of still vehicle images, judging that the vehicle is in a congestion state.
In order to further optimize the above technical solution, in S1,
the front area comprises a stop line extending to the direction of the intersection for 0-80 m, and is mainly used for detecting whether a congested vehicle exists at the intersection in the direction;
the middle area comprises a range area of 0-80 m extending from the stop line to the rear of the intersection, and is mainly used for detecting whether vehicles exist or not and how many vehicles exist;
the rear area comprises a range area which extends to the rear of the intersection by 80-150 m from the stop line, and is mainly used for detecting whether a fleet group, the head of the fleet, the tail of the fleet and the like exist.
As shown in fig. 2, the current intersection has 4 directions, and the detection of the signal light information and the video information of three sections of the road in the current direction is performed respectively, and the optimal control strategy of the current period is comprehensively calculated according to the detection result of 3 section areas in each direction, so that no matter how many vehicles are in the whole intersection, a relatively high passing efficiency can be achieved, for example: the rear zone has a group of vehicles coming, and the green light is initially set at 15 seconds, but if the middle zone vehicle does not exceed the threshold F2, the green light duration is controlled to be reduced to 10 seconds.
S5, if the number of waiting vehicles in the middle area video information and the number of passenger flow people of the unit vehicle exceed a threshold value F2, further judging whether the number of waiting vehicles in the middle area video information exceeds a threshold value F1, wherein F1 is greater than F2, and when the number of waiting vehicles exceeds a threshold value F1, entering S6;
s6, judging whether the current phase is a green light, if so, entering S7, and if not, entering S8;
and S7, judging whether the residual time of the green light in the current phase exceeds a threshold G1, if so, ending the phase control process, otherwise, prolonging the green light time in the phase, and returning to S6.
S8, if the current phase is not the green light, executing the early-off operation of the red light, and entering S9; the red light early-off operation includes, for example, an initial timing of 30 seconds for a red light, and a control to 20 seconds for a red light timing after the early-off operation, i.e., a change to a green light.
And S9, superposing the current phase time and the green time of the next phase, judging whether the superposed time exceeds preset time, if so, ending the phase control flow, and otherwise, returning to S5.
In order to further optimize the technical scheme, S2 further includes detecting position information of a head and a tail of the fleet of vehicles, and predicting a time when the fleet of vehicles passes through the stop line, so as to control the extension duration of the signal lamp street lamp signal of the corresponding phase, the early turn-off time of the red lamp, and the duration of the signal lamp signal of the green lamp after the phase is superimposed.
The passenger loading of the vehicle is controlled in the highest priority, and the purpose is to minimize the per-person travel time. The following multi-level priority control can be classified: the green light is given a right of passage in a priority order, wherein,
when a public rescue vehicle is detected in the video information, giving a first priority to a current direction signal lamp;
when the public transportation vehicle is detected in the video information, giving a second priority to the signal lamp in the current direction;
giving a third priority to the current direction signal lamp when the number of passengers in the vehicle detected in the video information is more than two;
the remaining cases belonging to the fourth priority, are performed according to the video detection based active predictive type signal control method of claim 1.
In a specific embodiment, the priority screening is used for predicting the passenger capacity according to the passenger capacity borne by different vehicle types, and the priority screening is divided into several vehicle type grades to predict the passenger capacity:
the highest priority: the method comprises the following steps of detecting that vehicles such as an ambulance, a fire truck, a school bus and the like can pass through the ambulance, the fire truck, the school bus and the like in the highest priority, and calculating according to 50 persons in each vehicle;
the second priority is: bus vehicles, calculated by 30 persons per vehicle;
third priority: the number of the middle bus and the large truck is converted into 4 persons in each truck for calculation;
the fourth priority: the method comprises the following steps that (1) vehicles with people on a passenger seat are converted into 2 people on each vehicle for calculation;
the lowest priority: the other social vehicles were calculated for 1 person per vehicle.
The vehicle type can be detected through the video information, the vehicle type is converted into the number of people in the specific passenger flow, and then the timing of the phase signal lamp is calculated according to the passenger flow.
The embodiment also provides an active prediction type signal control system based on video detection, which includes: a multi-view camera 1, a video detector 2 and a signal machine 3, wherein,
the multi-view camera mechanism 1 is used for acquiring video information of three sections of a current intersection, wherein the three sections comprise a front area, a middle area and a rear area of a stop line; each section comprises vehicle information of each passing direction; the multi-view camera shooting mechanism 1 comprises a shell 11 and a plurality of video acquisition boards 12 arranged in the shell 11, wherein the video acquisition boards 12 are uniformly distributed along different directions; the video acquisition boards 12 are connected to a video fusion processing board 13, and the video fusion processing board 13 is connected with a wireless communication board 14; the video fusion processing board 13 is further connected with a neural network acceleration board 15 for vehicle contour recognition of the fusion spliced video, the video fusion processing board 13 is connected with a wireless communication board 14, and the wireless communication board 14 is connected with a command center platform or/and an LED large screen.
The video detector 2 is used for detecting the signal lamp state of each passing direction of the current intersection;
the traffic signal 3 executes the active prediction type signal control method described in S1 to S9 of the current cycle based on the traffic light state detected by the video detector 2 and the video information acquired by the multi-view imaging means 1.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (5)
1. An active prediction type signal control method based on video detection is characterized by comprising the following steps:
s1, simultaneously acquiring signal light information of the road passing direction and video information of three sections of the road, wherein the three sections comprise a front area, a middle area and a rear area of a stop line, and each section comprises vehicle information of each passing direction; the front area comprises a range area of which the stopping line extends to the intersection direction by 0-80 m; the middle area comprises an area with a stopping line extending to the rear of the intersection for 0-80 m; the rear area comprises an area which extends to the rear of the intersection by 80-150 m from the stop line;
s2, judging whether the rear video information contains a motorcade/group image, if so, entering a third step, otherwise, controlling a signal lamp according to an initial timing mode;
s3, judging whether the number of waiting vehicles in the video information in the middle area and the number of passenger flows of the unit vehicle exceed a threshold value F2, if not, judging whether the time is predicted when time allocation needs to be optimized, if so, entering the step four, and if not, controlling a signal lamp according to an initial time allocation mode;
and S4, judging whether the front zone video information has vehicle congestion, and if so, controlling the current direction signal lamp to be red.
2. The active predictive signal control method of claim 1, wherein the step S2 further comprises detecting position information of a head and a tail of the fleet of vehicles, and predicting a time when the fleet of vehicles passes a stop line, so as to control the time length of the phase signal lamp street lamp signal, the time length of the red light early turn-off, and the time length of the phase superimposed green light signal.
3. The method according to claim 1, further comprising the following steps after said S3:
s5, if the number of waiting vehicles in the middle area video information and the number of passenger flow people of the unit vehicle exceed a threshold value F2, further judging whether the number of waiting vehicles in the middle area video information exceeds a threshold value F1, wherein F1 is greater than F2, and when the number of waiting vehicles exceeds a threshold value F1, entering S6;
s6, judging whether the current phase is a green light, if so, entering S7;
and S7, judging whether the residual time of the green light in the current phase exceeds a threshold G1, if so, ending the phase control process, otherwise, prolonging the green light time in the phase, and returning to S6.
4. The active predictive type signal control method according to claim 3, wherein said step S6 is followed by the steps of:
s8, if the current phase is not the green light, executing the early-off operation of the red light, and entering S9;
and S9, superposing the current phase time and the green time of the next phase, judging whether the superposed time exceeds preset time, if so, ending the phase control flow, and otherwise, returning to S5.
5. The active predictive signal control method based on video detection according to claim 1, further comprising a multi-level priority control method: the green light is given a right of passage in a priority order, wherein,
when a public rescue vehicle is detected in the video information, giving a first priority to a current direction signal lamp;
when the public transportation vehicle is detected in the video information, giving a second priority to the signal lamp in the current direction;
giving a third priority to the current direction signal lamp when the number of passengers in the vehicle detected in the video information is more than two;
the remaining cases belong to a fourth priority, performed according to the video detection based active predictive type signal control method as claimed in claim 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911054990.6A CN110992684B (en) | 2019-10-31 | 2019-10-31 | Active prediction type signal control method and system based on video detection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911054990.6A CN110992684B (en) | 2019-10-31 | 2019-10-31 | Active prediction type signal control method and system based on video detection |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110992684A CN110992684A (en) | 2020-04-10 |
| CN110992684B true CN110992684B (en) | 2021-04-30 |
Family
ID=70082885
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911054990.6A Active CN110992684B (en) | 2019-10-31 | 2019-10-31 | Active prediction type signal control method and system based on video detection |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110992684B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113053143A (en) * | 2021-03-31 | 2021-06-29 | 联想(北京)有限公司 | Signal lamp timing optimization method and device and electronic equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104157153A (en) * | 2014-08-15 | 2014-11-19 | 北京航空航天大学 | Separated left turn lane design and related intersection channelization, signal phase and timing setting method |
| CN109410606A (en) * | 2018-03-22 | 2019-03-01 | 合肥革绿信息科技有限公司 | A kind of trunk roads synergistic signal machine control method based on video |
| CN109410601A (en) * | 2018-12-04 | 2019-03-01 | 北京英泰智科技股份有限公司 | Method for controlling traffic signal lights, device, electronic equipment and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10691957B2 (en) * | 2018-02-12 | 2020-06-23 | ITS Plus, Inc. | Method for increasing the accuracy of traffic cameras using optical masking technology |
-
2019
- 2019-10-31 CN CN201911054990.6A patent/CN110992684B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104157153A (en) * | 2014-08-15 | 2014-11-19 | 北京航空航天大学 | Separated left turn lane design and related intersection channelization, signal phase and timing setting method |
| CN109410606A (en) * | 2018-03-22 | 2019-03-01 | 合肥革绿信息科技有限公司 | A kind of trunk roads synergistic signal machine control method based on video |
| CN109410601A (en) * | 2018-12-04 | 2019-03-01 | 北京英泰智科技股份有限公司 | Method for controlling traffic signal lights, device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110992684A (en) | 2020-04-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110728844B (en) | Traffic light self-adaptive control method and device, traffic control equipment and storage medium | |
| CN101833863B (en) | Method and device for detecting vehicle flow speed, as well as method and system for controlling traffic lights | |
| CN115297595B (en) | Intelligent city street lamp intelligent control method and system based on Internet of things | |
| CN108615378A (en) | A kind of traffic light time regulation and control method at two-way multilane zebra stripes crossing | |
| CN109410601A (en) | Method for controlling traffic signal lights, device, electronic equipment and storage medium | |
| CN111462497A (en) | Traffic data issuing method, system, terminal and storage medium | |
| CN108109403B (en) | Adaptive traffic light control system and method based on traffic flow | |
| CN110782681B (en) | Traffic indicator lamp self-adaptive control method, device, terminal and storage medium | |
| CN107730926A (en) | A kind of intellectual traffic control method, apparatus and system | |
| JP5526788B2 (en) | Traffic signal control system, traffic signal controller, central device and program | |
| CN111882894A (en) | Intelligent traffic signal lamp control method and system | |
| CN114141021B (en) | Smart city traffic signal lamp control system and control method thereof | |
| CN106530772A (en) | Intelligent traffic signal lamp, control system of the same and emergency control method of the same | |
| CN111028523A (en) | Signal lamp control method, device and equipment | |
| CN109584583B (en) | Intelligent refined control system and method for same-phase right-turn vehicles and street-crossing pedestrians | |
| CN105139671B (en) | Limit the intelligent traffic control system and its control method of viewing area | |
| CN110264651A (en) | Railway platform pedestrian gets over line monitoring method, device, terminal and storage medium | |
| KR102134393B1 (en) | Signal control system for bus-only lane | |
| CN111540219B (en) | Bidirectional bus signal priority coordination method based on artificial intelligence bus-road coordination | |
| CN110992684B (en) | Active prediction type signal control method and system based on video detection | |
| CN104794909B (en) | The prevention of intersection traffic obstruction and automatic emergency processing system and its processing method | |
| Zeng et al. | Intelligent transport management system for urban traffic hubs based on an integration of multiple technologies | |
| CN115953908B (en) | Traffic light control method and system and traffic light | |
| KR102605101B1 (en) | Smart signal apparatus for non-signalized intersection and control method thereof | |
| CN112489465A (en) | Efficient intelligent traffic light control method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: 210000 third floor, Beidou building, No. 6, Huida Road, Jiangbei new area, Nanjing, Jiangsu Patentee after: Hualui Cloud Technology Co.,Ltd. Address before: Shihua Road, Beijing 1000165 Patentee before: Hua Lu Yun Technology Co.,Ltd. |