CN111028519B - Self-adaptive control method based on video flow detector - Google Patents
Self-adaptive control method based on video flow detector Download PDFInfo
- Publication number
- CN111028519B CN111028519B CN201911383246.0A CN201911383246A CN111028519B CN 111028519 B CN111028519 B CN 111028519B CN 201911383246 A CN201911383246 A CN 201911383246A CN 111028519 B CN111028519 B CN 111028519B
- Authority
- CN
- China
- Prior art keywords
- release
- moving direction
- north
- south
- vehicles
- 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
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
-
- 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
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
Abstract
The invention relates to a self-adaptive control method based on a video flow detector, which comprises the following steps: step 1, selecting M release periods as reference standards, wherein the release modes of each period are the same, and determining transition release time of each moving direction according to the selected reference standards; step 2, counting the release duration of each moving direction of the selected reference standard by using a video flow detector to obtain the average release duration of each moving direction; and 3, judging the release phase according to the transition release time of each moving direction in the step 1 and the average release time of each moving direction in the step 2 so as to obtain the release state of M predicted release periods. The invention can be used for dealing with the influence of real-time change of vehicles at the intersection on the dynamic clearance selection and improving the passing efficiency of the vehicles at the intersection.
Description
Technical Field
The invention relates to a self-adaptive control method, in particular to a self-adaptive control method based on a video flow detector, and belongs to the technical field of intelligent traffic.
Background
The traffic signal lamp is an important display tool in traffic safety products, can effectively release the traffic signal lamp, can strengthen the management of vehicles at the road junction, improve the utilization rate of road resources, reduce the waiting time of the vehicles, and more importantly, can pull the rapid development of economy. In recent years, optimization service engineering for road traffic release has become an important field of research, and higher requirements are also put forward on precision of traffic data, real-time monitoring of traffic states and prediction release of selection schemes. The application of bayonet big data technology is going into the field of vision of researchers, and how to realize the maximization of the utilization of the data is urgent.
At present, the video flow detection technology is applied to road traffic, and reliable and effective dynamic traffic data can be provided in real time. In early work, a traffic light detection algorithm based on vision is provided for identifying red light running behaviors. Other signal lamp detection algorithms are based on different technologies, such as a markov random field, a neural network, a mathematical form and the like, more empirical models are introduced to improve the performance of the algorithms, but the efficiency is different from the real-time performance. Later, according to different conditions, different emphasis targets are required, and the problem of the importance of manually determining the indexes combined with a fuzzy analysis method is solved. In the immune clone algorithm, the environment variation clone selection algorithm is integrated into signal timing optimization, the actual traffic condition of the intersection is met, and the traffic jam problem is effectively relieved.
In foreign countries, the Australian scholars Aksai Ke proposes a parking compensation coefficient on the basis of the Webster theory to evaluate the crossing traffic efficiency. The TRAF-NETSIM traffic simulation system developed in the United states simulates the movement of a single vehicle and plays an important role in traffic optimization management. In China, Longqiong and other people establish a multi-objective optimization model based on queuing length, delay time and parking times, and introduce traffic strategies, fuzzy analysis methods and the like to determine optimization index weight coefficients. The Wang palace sea establishes a multi-objective optimization model according to the mixed traffic condition and provides a corresponding isolated intersection signal lamp control method. And selecting delay time and parking times of the motor vehicle by Malying and the like, and solving by using an ant colony algorithm in combination with rainy and snowy weather.
The intelligent traffic control system is the key point of the current development of China, the traffic detector is used for calculating and applying the acquired data, and the traffic research tends to be performed by combining the traffic conditions of the actual intersection. The traffic information acquisition, the intersection release mode prediction and the effective lane release control have certain innovative significance, the effective discrimination of traffic flow is realized through the organic integration with a traffic signal control system, the reasonable timing of a signal control lamp promotes the continuous forward development of the modern society in the traffic field, and the existing traffic control method is difficult to meet the development requirement of intelligent traffic.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides an adaptive control method based on a video flow detector, which can be used for responding to the influence of real-time change of vehicles at an intersection on dynamic release selection and improving the passing efficiency of the vehicles at the intersection.
According to the technical scheme provided by the invention, the self-adaptive control method based on the video flow detector comprises the following steps:
and 3, judging the release phase according to the transition release time of each moving direction in the step 1 and the average release time of each moving direction in the step 2 so as to obtain the release state of M predicted release periods.
In step 3, in the release period, the release phase in the north-south direction is judged, specifically:
step 3.1, setting a north-south left-turn comparison value A and a north-south straight comparison value B, wherein
Wherein n1 is the transition release time of turning left from north to south, and n2 is the transition release time of straight going from north to south; u1, u 1-t2, u2, t3-t4, wherein t1 is the average releasing duration of the north-left turn, t2 is the average releasing duration of the south-left turn, t3 is the average releasing duration of the north-straight run, and t4 is the average releasing duration of the south-straight run;
step 3.2, if a × B >0, there are two cases to release the mode selection, and the release mode one is: turning left north and passing right north; the second release mode is: turning left, and passing through the south;
if A is B is 0, the release mode is south-north straight and south-north left turn.
The method also comprises a dynamic elimination step, wherein the dynamic elimination step comprises the following steps:
dt1, for the release mode of the current phase, obtaining the release duration t of the current moving direction by using a video flow detector, and when t is less than Tmin, continuing releasing the current phase; when t is greater than Tmax, the current moving direction is eliminated, the next phase release mode is executed, and when Tmin is greater than t and less than Tmax, the step dt2 is executed;
dt2, counting all upward vehicles in the counting unit for the counting unit p by taking the stop line as the space position for counting the vehicles;
step dt3, obtaining the number of vehicles in each dynamic upward counting unit time in the 0 th running period, the 1 st running period, the 2 nd running period, … and the S th running period according to the statistical mode of the step dt2, and selecting the maximum number of vehicles as the static load of the current running period from the 1 st running period by counting the number of vehicles in each dynamic upward counting unit time in the current running period and the last adjacent running period;
step dt4, calculating a dynamic load using the static load as described above, the dynamic load W being
Wherein C is the maximum green time, and A' is the total number of the passing static load vehicles;
step dt5, selecting any time interval f, and counting the number R of passing traffic flows in the time interval f;
step dt6, when the dynamic load W is smaller than Emin or larger than Emax, jumping to step dt7, otherwise, jumping to step dt 9; emin is the minimum traffic number, and Emax is the maximum traffic number;
step dt7, when the traffic flow quantity R is smaller than the minimum traffic flow quantity Emin, eliminating the current moving direction, otherwise, jumping to step dt 8;
step dt8, when the traffic flow quantity R is larger than the maximum traffic flow quantity Emax, the current phase is released continuously, otherwise, the dynamic current moving direction is eliminated;
step dt9 setting threshold criteria G to
When the minimum traffic volume Emin is less than G and less than the maximum traffic volume Emax, jumping to step dt10, otherwise, jumping to step dt 7;
and step dt10, when the traffic flow quantity R is smaller than the threshold value standard G, eliminating the current moving direction, otherwise, continuing to move the current moving direction.
The invention has the advantages that:
1. the limitations of passing programming, untimely information acquisition, mistaken vehicle elimination and the like are effectively avoided. When the video flow detector is used for acquiring real-time data, the release mode in the previous periods is fully considered, the release mode prediction is made, release is implemented, and the methods of the crossing moving direction prediction release mode, the vehicle number moving direction elimination criterion, the vehicle number mistaken elimination judgment criterion and the like are effectively implemented. The vehicle passing smoothness, the accurate judgment of the vehicle number and the maximum utilization rate of the signal lamp are guaranteed. The method is a method for judging and predicting the phase release of the next period by using the existing data, avoiding the overlong waiting time of vehicles and using the number of the vehicles to carry out dynamic elimination. The signaler system and the data of the gate are eliminated and efficiently matched with each other, so that intelligent release of intersection traffic is realized.
2. The defects of insufficient and untimely information acquisition and limitations of low data information utilization rate, single-target tracking, programmed release mode and the like are effectively avoided. On the basis of fully considering the dynamic traffic flow information of the road intersection, the advantages of the intelligent traffic self-adaptive releasing method are exerted, and the lane structure of the intersection is effectively judged, the moving direction and releasing mode of the intersection are set, the real-time traffic flow eliminating releasing principle is adopted, and the like. The lane is ensured to pass smoothly, the utilization rate of the intelligent signal control lamp is improved, and the waiting time of the vehicle is reduced. And a timely and accurate release scheme is given according to the real-time changing traffic flow state, and the detection technology information acquisition, the self-adaptive release method, the intelligent signal system and the like are efficiently matched and combined.
Drawings
FIG. 1 is a flow chart of the predictive release mode of the present invention.
FIG. 2 is a flow chart of vehicle statistics of the present invention.
FIG. 3 is a flow chart of the present invention for dynamic elimination.
Detailed Description
The invention is further illustrated by the following specific figures and examples.
As shown in fig. 1: in order to be used for dealing with the influence of real-time change of vehicles at the intersection on dynamic release selection and improve the passing efficiency of the vehicles at the intersection, the self-adaptive control method comprises the following steps:
specifically, M may take 3, i.e., predict the release for the next three cycles based on the selected 3 release cycles. The specific determination of the transition release time for each direction is well known in the art and will not be described herein.
specifically, the video traffic detector may adopt the existing common equipment, and the process of obtaining the release duration of each movement of the selected reference standard by using the radio frequency traffic detector is well known to those skilled in the art. After the release duration of each movement direction of the selected reference standard is obtained, the average release duration of each movement direction can be obtained by using a mode of calculating the arithmetic mean.
And 3, judging the release phase according to the transition release time of each moving direction in the step 1 and the average release time of each moving direction in the step 2 so as to obtain the release state of M predicted release periods.
Specifically, in the release period, taking the release phase determination in the north-south direction as an example, the release phase determination in the east-west direction is consistent with the limit determination in the north-south direction, and reference may be made to corresponding descriptions. When the release phase in the north-south direction is judged, the following steps are specifically performed:
step 3.1, setting a north-south left-turn comparison value A and a north-south straight comparison value B, wherein
Wherein n1 is the transition release time of turning left from north to south, and n2 is the transition release time of straight going from north to south; u1, u 1-t2, u2, t3-t4, wherein t1 is the average releasing duration of the north-left turn, t2 is the average releasing duration of the south-left turn, t3 is the average releasing duration of the north-straight run, and t4 is the average releasing duration of the south-straight run;
step 3.2, if a × B >0, there are two cases to release the mode selection, and the release mode one is: turning left north and passing right north; the second release mode is: turning left, and passing through the south;
if A is B is 0, the release mode is south-north straight and south-north left turn.
In the embodiment of the present invention, for the first release mode, specifically: north-south straight going, north left turning, north straight going, and north-south left turning. For the second release mode, specifically: north-south straight going, south left turning, south straight going and north-south left turning.
As shown in fig. 3, the method further includes a dynamic elimination step, and the dynamic elimination step includes:
dt1, for the release mode of the current phase, obtaining the release duration t of the current moving direction by using a video flow detector, and when t is less than Tmin, continuing releasing the current phase; when t is greater than Tmax, the current moving direction is eliminated, the next phase release mode is executed, and when Tmin is greater than t and less than Tmax, the step dt2 is executed;
specifically, Tmin and Tmax are the minimum release duration and the maximum release duration of each moving direction configured by the parameter configuration personnel, and the function is to set upper and lower limits for each moving direction release. And comparing the release duration t with Tmin and Tminx to serve as a judgment standard for judging whether the moving direction is to continue releasing or to terminate releasing. When t < Tmin, the phase continues to be released. And when t is greater than Tmax, eliminating the motion direction and executing next phase judgment.
Dt2, counting all upward vehicles in the counting unit for the counting unit p by taking the stop line as the space position for counting the vehicles;
specifically, the video detector counts the number of vehicles passing through the stop line, and counts 1 vehicle from the head of the vehicle passing through the stop line to the tail of the vehicle passing through the stop line. And setting a detection time period counting unit p, wherein the counting unit p is generally 5s, for example, 0-5 s is a first unit counting period, 5-10 s is a second unit counting period, and 10-15s is a third unit counting period, the number of passing vehicles in the 0 th running period of the moving direction is set as a minimum value X, that is, the number of lanes in the moving direction is multiplied by 2, and X is 2 lanes.
Step dt3, setting S as the number of cycles that the traffic signal machine is electrified and started to actually run, obtaining the number of vehicles in the unit time counted in the 0 th running cycle, the 1 st running cycle, the 2 nd running cycle, … and each moving direction in the S th running cycle according to the statistical mode of the step dt2, starting from the 1 st running cycle, counting the number of vehicles in the unit time counted in the current running cycle and each moving direction in the previous adjacent running cycle, and selecting the maximum number of vehicles as the static load of the current running cycle;
as shown in fig. 2, when counting the number of vehicles, the specific counting process includes the following steps:
and step s1, setting the minimum passing time of the unit vehicle moving inwards initially as Dmin, the maximum passing time as Dmax, the actual passing time of the vehicle as D and the number of the vehicles as H. If D < Dmin, H is 0; if D > Dmax, H is 0. If Dmin < D < Dmax, then proceed to step s 2.
Step s2, calculating the unit vehicle passing time: the video flow detector counts the total time J for each vehicle to move to pass through the stop line, and the total number F of vehicles to move to pass through the stop line in the last period. The calculation formula of the unit vehicle passing time E is as follows:
the unit vehicle passing time period is the total time period of the moving-direction released vehicle/the total number of vehicles passing through the stop line, i.e., E is F/J.
Step s3, vehicle number judgment: defining a parameter value Q-2E, counting the time length of a unit vehicle passing through a stop line as D, and if D is greater than Q, H-2; if D < Q, then H ═ 1;
step s4, counting the number of vehicles: and respectively counting the total number of the vehicles in the 0-5 s and 5-10 s.
Specifically, according to the statistical steps, the total number of vehicles passing through the first operation period of the dynamic direction is recorded as N [1, 1], N [1,2], and if the total number is the unit counting period of the second operation period of the dynamic direction, the total number is recorded as N [2,1], N [2,2]. And according to statistical methods, the table is as follows:
| 0 |
0—5s | 5-10s | 10-15s | ..... | |
| Marking | N[0,1] | N[0,2] | N[0,3] | ..... | |
| 1 st cycle of |
0—5s | 5-10s | 10-15s | ..... | |
| Marking | N[1,1] | N[1,2] | N[1,3] | ..... | |
| |
| A2 | A3 | ||
| 2 |
0—5s | 5-10s | 10-15s | ..... | |
| Marking | N[2,1] | N[2,2] | N[2,3] | ..... | |
| |
B1 | B2 | B3 | ||
| ..... | ..... | ..... | ..... | ..... |
Static load: and comparing the number of vehicles in the unit counting period of the 0 th running period and the 1 st running period, and taking the maximum value in each unit counting period as the load number. And then comparing the number of vehicles in the unit counting period of the second period with the number of loads respectively, and obtaining the maximum value as the number of loads of the next period, and so on.
Step dt4, calculating a dynamic load using the static load as described above, the dynamic load W being
Wherein C is the maximum green time, and A' is the total number of the passing static load vehicles; for the 1 st operation period, the total number A' of the passing static loads is A1+ A2+ A3+ … …, namely the total of all the loads in the 1 st operation period.
Step dt5, selecting any time interval f, and counting the number R of passing traffic flows in the time interval f; typically, the time interval f is chosen to be 5 seconds.
Step dt6, when the dynamic load W is smaller than Emin or larger than Emax, jumping to step dt7, otherwise, jumping to step dt 9; emin is the minimum traffic number, and Emax is the maximum traffic number;
specifically, the minimum traffic volume Emin is the current moving lane number × 2, and the maximum traffic volume Emax is the current moving lane number × 3.
Step dt7, when the traffic flow quantity R is smaller than the minimum traffic flow quantity Emin, eliminating the current moving direction, otherwise, jumping to step dt 8;
step dt8, when the traffic flow quantity R is larger than the maximum traffic flow quantity Emax, the current phase is released continuously, otherwise, the dynamic current moving direction is eliminated;
step dt9 setting threshold criteria G to
When the minimum traffic volume Emin is less than G and less than the maximum traffic volume Emax, jumping to step dt10, otherwise, jumping to step dt 7;
and step dt10, when the traffic flow quantity R is smaller than the threshold value standard G, eliminating the current moving direction, otherwise, continuing to move the current moving direction.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to examples, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (2)
1. An adaptive control method based on a video flow detector is characterized by comprising the following steps:
step 1, selecting M release periods as reference standards, wherein the release modes of each period are the same, and determining transition release time of each moving direction according to the selected reference standards;
step 2, counting the release duration of each moving direction of the selected reference standard by using a video flow detector to obtain the average release duration of each moving direction;
step 3, judging a release phase according to the transition release time of each moving direction in the step 1 and the average release duration of each moving direction in the step 2 so as to obtain the release states of M predicted release periods;
in step 3, in the release period, the release phase in the north-south direction is judged, specifically:
step 3.1, setting a north-south left-turn comparison value A and a north-south straight comparison value B, wherein
Wherein n1 is the transition release time of turning left from north to south, and n2 is the transition release time of straight going from north to south; u1, u 1-t2, u2, t3-t4, wherein t1 is the average releasing duration of the north-left turn, t2 is the average releasing duration of the south-left turn, t3 is the average releasing duration of the north-straight run, and t4 is the average releasing duration of the south-straight run;
step 3.2, if a × B >0, there are two cases to release the mode selection, and the release mode one is: turning left north and passing right north; the second release mode is: turning left, and passing through the south;
if A is B is 0, the release mode is south-north straight and south-north left turn.
2. The adaptive control method based on the video flow detector according to claim 1, further comprising a dynamic elimination step, wherein the dynamic elimination step comprises:
dt1, for the release mode of the current phase, obtaining the release duration t of the current moving direction by using a video flow detector, and when t is less than Tmin, continuing releasing the current phase; when t is greater than Tmax, the current moving direction is eliminated, the next phase release mode is executed, and when Tmin is greater than t and less than Tmax, the step dt2 is executed;
dt2, counting all upward vehicles in the counting unit for the counting unit p by taking the stop line as the space position for counting the vehicles;
step dt3, obtaining the number of vehicles in each dynamic upward counting unit time in the 0 th running period, the 1 st running period, the 2 nd running period, … and the S th running period according to the statistical mode of the step dt2, comparing the current running period with the number of vehicles in each dynamic upward counting unit time in the previous adjacent running period from the 1 st running period, and selecting the maximum number of vehicles as the static load of the current running period;
step dt4, calculating a dynamic load using the static load as described above, the dynamic load W being
Wherein C is the maximum green time, and A' is the total number of the passing static load vehicles;
step dt5, selecting any time interval f, and counting the number R of passing traffic flows in the time interval f;
step dt6, when the dynamic load W is smaller than Emin or larger than Emax, jumping to step dt7, otherwise, jumping to step dt 9; emin is the minimum traffic number, and Emax is the maximum traffic number;
step dt7, when the traffic flow quantity R is smaller than the minimum traffic flow quantity Emin, eliminating the current moving direction, otherwise, jumping to step dt 8;
step dt8, when the traffic flow quantity R is larger than the maximum traffic flow quantity Emax, the current phase is released continuously, otherwise, the dynamic current moving direction is eliminated;
step dt9 setting threshold criteria G to
When the minimum traffic volume Emin is less than G and less than the maximum traffic volume Emax, jumping to step dt10, otherwise, jumping to step dt 7;
and step dt10, when the traffic flow quantity R is smaller than the threshold value standard G, eliminating the current moving direction, otherwise, continuing to release the current moving direction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911383246.0A CN111028519B (en) | 2019-12-28 | 2019-12-28 | Self-adaptive control method based on video flow detector |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911383246.0A CN111028519B (en) | 2019-12-28 | 2019-12-28 | Self-adaptive control method based on video flow detector |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111028519A CN111028519A (en) | 2020-04-17 |
| CN111028519B true CN111028519B (en) | 2021-01-12 |
Family
ID=70194600
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911383246.0A Active CN111028519B (en) | 2019-12-28 | 2019-12-28 | Self-adaptive control method based on video flow detector |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111028519B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112735153A (en) * | 2020-10-23 | 2021-04-30 | 南京理工大学 | Intelligent traffic self-adaptive releasing method based on microwave radar |
| CN113516854B (en) * | 2021-03-25 | 2022-07-08 | 江苏航天大为科技股份有限公司 | Multi-interface coordination self-adaptive control method based on police card and video detector |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101021975A (en) * | 2007-03-14 | 2007-08-22 | 吉林大学 | Smooth transition method of coordination signal time distributing conception in city traffic control system |
| CN101251953A (en) * | 2008-04-03 | 2008-08-27 | 同济大学 | Unsymmetrical space-time optimizing control method for rotary intersection |
| CN101968930A (en) * | 2010-11-02 | 2011-02-09 | 徐笑晓 | Crossing signal light control method |
| CN102005125A (en) * | 2010-12-10 | 2011-04-06 | 东南大学 | Discharging method of vehicles passing intersection and related design method and control system |
| US8610596B2 (en) * | 2010-02-11 | 2013-12-17 | Global Traffic Technologies, Llc | Monitoring and diagnostics of traffic signal preemption controllers |
| US9881499B1 (en) * | 2017-03-02 | 2018-01-30 | Robert C. Tom | Traffic light devices and methods of use |
Family Cites Families (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3416130A (en) * | 1965-11-01 | 1968-12-10 | Lab For Electronics Inc | Traffic actuated control system |
| CN101923783B (en) * | 2010-08-30 | 2013-04-17 | 大连理工大学 | Four-way ring intersection traffic response control method |
| CN103280113B (en) * | 2013-05-08 | 2014-12-24 | 长安大学 | Self-adaptive intersection signal control method |
| CN104751647B (en) * | 2015-04-16 | 2017-06-20 | 无锡物联网产业研究院 | A kind of traffic control method and system |
| CN107221159A (en) * | 2016-03-22 | 2017-09-29 | 深圳市以捷创新科技有限公司 | The peccancy detection method of smart electronicses police's system for detecting regulation violation |
| CN107862876A (en) * | 2017-03-27 | 2018-03-30 | 平安科技（深圳）有限公司 | Traffic lamp control method and device |
| CN107038878B (en) * | 2017-06-06 | 2020-04-24 | 广东振业优控科技股份有限公司 | Traffic signal phase design method based on integer programming model |
| CN107331167B (en) * | 2017-08-07 | 2019-09-17 | 青岛海信网络科技股份有限公司 | A kind of traffic lights feedback adjustment methods and device |
| CN109872544A (en) * | 2017-12-05 | 2019-06-11 | 杭州海康威视数字技术股份有限公司 | A kind of control method and device of traffic signals |
| CN108564795A (en) * | 2018-03-30 | 2018-09-21 | 江苏智通交通科技有限公司 | Phase sequence selects and the Signal phase configuration method and system of schemes generation formula |
| CN208781403U (en) * | 2018-09-03 | 2019-04-23 | 福建泉州星蓝信息科技有限公司 | A kind of intelligent traffic lamp control machine |
| CN109345839A (en) * | 2018-10-19 | 2019-02-15 | 江苏智通交通科技有限公司 | Combinatorial phase flexible configuration method based on conventional phase sequence |
| CN109637160B (en) * | 2018-11-29 | 2021-02-02 | 浙江海康智联科技有限公司 | Single-point control method under dynamic traffic condition |
| CN109544945B (en) * | 2018-11-30 | 2021-06-01 | 江苏智通交通科技有限公司 | Regional control phase timing optimization method based on lane saturation |
| CN111429721B (en) * | 2020-03-27 | 2021-11-09 | 江苏智通交通科技有限公司 | Intersection traffic signal scheme optimization method based on queuing dissipation time |
-
2019
- 2019-12-28 CN CN201911383246.0A patent/CN111028519B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101021975A (en) * | 2007-03-14 | 2007-08-22 | 吉林大学 | Smooth transition method of coordination signal time distributing conception in city traffic control system |
| CN101251953A (en) * | 2008-04-03 | 2008-08-27 | 同济大学 | Unsymmetrical space-time optimizing control method for rotary intersection |
| US8610596B2 (en) * | 2010-02-11 | 2013-12-17 | Global Traffic Technologies, Llc | Monitoring and diagnostics of traffic signal preemption controllers |
| CN101968930A (en) * | 2010-11-02 | 2011-02-09 | 徐笑晓 | Crossing signal light control method |
| CN102005125A (en) * | 2010-12-10 | 2011-04-06 | 东南大学 | Discharging method of vehicles passing intersection and related design method and control system |
| US9881499B1 (en) * | 2017-03-02 | 2018-01-30 | Robert C. Tom | Traffic light devices and methods of use |
Non-Patent Citations (1)
| Title |
|---|
| 数据驱动交通响应绿波协调信号控制;李永强 等;《控制理论与应用》;20160531;正文第1-11页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111028519A (en) | 2020-04-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109598950B (en) | Ramp cooperative convergence control method and system for intelligent networked vehicles | |
| CN111028519B (en) | Self-adaptive control method based on video flow detector | |
| CN107274672B (en) | Signal intersection single vehicle delay time estimation method based on GPS data | |
| CN113327416A (en) | Urban area traffic signal control method based on short-term traffic flow prediction | |
| CN105046990A (en) | Pavement signal lamp control method between adjacent intersections based on particle swarm algorithm | |
| CN113516854B (en) | Multi-interface coordination self-adaptive control method based on police card and video detector | |
| CN102087788A (en) | Method for estimating traffic state parameter based on confidence of speed of float car | |
| CN106920403A (en) | A kind of single-point self-adaptation control method based on array radar | |
| CN110232821A (en) | A kind of peak period bay bus stop closes on lane capacity calculation method | |
| CN107393319B (en) | Signal optimization control method for preventing single cross port queuing overflow | |
| CN111524345B (en) | Induction control method for multi-objective optimization under constraint of real-time queuing length of vehicle | |
| CN111445700B (en) | Regional running and stopping vehicle monitoring method based on license plate identification data | |
| CN109859475B (en) | Intersection signal control method, device and system based on DBSCAN density clustering | |
| CN106875681B (en) | A kind of traffic congestion tendency prediction technique and system | |
| CN106846891B (en) | A kind of Public Parking berth multistep forecasting method decomposed based on sequence | |
| CN109816978B (en) | Regional group traffic guidance system and method considering dynamic response behaviors of drivers | |
| CN109658731B (en) | Control method for three-dimensional parking lot | |
| CN111754790B (en) | Ramp entrance traffic control system and method based on radar | |
| Yi-Fei et al. | Research on polling based traffic signal control strategy with fuzzy control | |
| CN108873696B (en) | Urban road supersaturation prevention control modeling method based on vehicle-mounted data | |
| CN205527128U (en) | Intelligence elevator management system based on flow of people statistics | |
| CN112669628B (en) | Intersection signal design method based on demand-supply dual fluctuation | |
| CN109615898A (en) | The output method and device of guidance path | |
| Ma et al. | Method of spillover identification in urban street networks using loop detector outputs | |
| Guo et al. | An improved actuated signal control of intersection based on VISVAP |
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 |