CN111145564A - Self-adaptive variable lane control method and system for signal control intersection - Google Patents
Self-adaptive variable lane control method and system for signal control intersection Download PDFInfo
- Publication number
- CN111145564A CN111145564A CN202010005695.8A CN202010005695A CN111145564A CN 111145564 A CN111145564 A CN 111145564A CN 202010005695 A CN202010005695 A CN 202010005695A CN 111145564 A CN111145564 A CN 111145564A
- Authority
- CN
- China
- Prior art keywords
- lane
- intersection
- traffic
- signal
- flow
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 33
- 230000006870 function Effects 0.000 claims abstract description 35
- 230000008859 change Effects 0.000 claims abstract description 14
- 238000006243 chemical reaction Methods 0.000 claims abstract description 14
- 230000003044 adaptive effect Effects 0.000 claims description 14
- 238000005457 optimization Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 8
- 230000000737 periodic effect Effects 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 description 5
- 238000012937 correction Methods 0.000 description 4
- 238000011144 upstream manufacturing Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000003111 delayed effect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000012508 change request Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a self-adaptive variable lane control method and a system for a signal control intersection, which comprise the following steps: collecting historical traffic data of the intersection, and determining the cycle of each conversion of lane functions according to the traffic change rule of the entrance; taking the traffic load degree index of the current intersection as a basis for lane function conversion; judging whether lane switching is carried out or not according to the switching period and the traffic load degree index of the current intersection; if so, switching the pre-signal, and optimizing the timing of the main signal; otherwise, keeping the original signal scheme; judging whether the optimized signal scheme is superior to the original scheme, if so, changing the current signal scheme into the optimized scheme; otherwise, the original signal scheme is maintained. The invention can adapt to the traffic flow of each traffic flow at the intersection changing along with time, and avoid the phenomenon that one traffic flow is crowded and the other traffic flow is vacant.
Description
Technical Field
The invention relates to the technical field of urban road signal control, in particular to a method and a system for controlling a self-adaptive variable lane of a signal control intersection.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The urban traffic jam becomes a ubiquitous international problem, intersections serve as key nodes of urban road networks, and different turning motor vehicle flows, non-motor vehicle flows and pedestrian flows are interwoven to seriously affect the traffic capacity of the intersections. The left-turn traffic flow has more conflict points generated at the intersection, higher accident rate and larger influence on the traffic capacity of the intersection. The temporal and spatial differences presented by the distribution of urban traffic flows on the road network make intersection resources still not well utilized.
At present, more research at home and abroad focuses on a method for setting a changeable lane on a tidal traffic flow road section, and less research on changing the lane function by tracking the road traffic demand in real time is carried out. The prior art provides a control method for determining variable lane attributes based on detector detection data, but the arrangement positions of the detectors mentioned in the description are harsher according to the conditions of arrangement, arrangement quantity and the like of traffic flow in an intersection canalization area, and the actual road conditions are often difficult to meet. In the prior art, the traffic volume of the next time period is predicted based on the current and historical traffic flow data and is used as an attribute judgment basis of the variable lane, but the time efficiency is poor because the correlation and the like are needed to be compared and analyzed with a large amount of data in a database, and the accuracy of the prediction result is difficult to ensure. In the prior art, the lane function and the signal timing of the variable guide lane are cooperatively optimized by taking the minimum delay as a target, the effect of the variable lane on reducing the delay of an intersection under the condition of known flow is analyzed, and a control conversion strategy of the variable lane is not provided. In the prior art, a dynamic lane function and signal phase combination model is established based on the analysis of the time-space relationship of the intersection, but the combination model has various constraint conditions and is not applicable to the intersection with short-time traffic demand change.
Disclosure of Invention
The invention aims to adapt to the traffic flow of each traffic flow of an intersection which changes constantly along with time, avoid the phenomena that a certain flow direction lane is crowded and the other flow direction lane is vacant, and provides a self-adaptive variable lane control method and a self-adaptive variable lane control system of a signal control intersection.
In some embodiments, the following technical scheme is adopted:
a self-adaptive variable lane control method for a signal control intersection comprises the following steps:
(1) collecting historical traffic data of the intersection, and determining the cycle of each conversion of lane functions according to the traffic change rule of the entrance;
(2) taking the traffic load degree index of the current intersection as a basis for lane function conversion;
(3) judging whether lane switching is carried out or not according to the switching period and the traffic load degree index of the current intersection; if yes, switching the pre-signal, optimizing the timing of the main signal, and entering the step (4); otherwise, keeping the original signal scheme;
(4) judging whether the optimized signal scheme is superior to the original scheme, if so, changing the current signal scheme into the optimized scheme; otherwise, keeping the original signal scheme;
(5) returning to the step (3), starting the judgment of the next period.
The method comprises the following steps of collecting historical traffic data of an intersection, and determining the cycle of each conversion of lane functions according to the traffic change rule of an entrance, wherein the method specifically comprises the following steps:
selecting a data segment space with the length of n as a sliding window, wherein n is the number of data contained in the sliding window;
setting the allowable deviation of single data in a sliding window, and setting a standard deviation threshold of n periodic flow data in the sliding window according to the allowable deviation;
calculating the standard deviation of the n flow data according to the first n calculated flow initial mean values of the flow data;
sliding a sliding window from a data starting point to a data end point, discarding the original starting point flow data and entering a window with a new period flow data every time the sliding window moves once, and calculating the mean value and the standard deviation of new n flow data;
if the total number of the N periodic flow data is N, obtaining N-N +1 standard deviation calculation values, and counting the number m of the standard deviations less than or equal to the standard deviation threshold valuen；
Changing the length of the sliding window, repeating the above steps, and comparing m under each sliding window lengthnValue, take mnAnd taking the length of the sliding window at the maximum as a function switching judgment period of the lane at the intersection.
In other embodiments, the following technical solutions are adopted:
a terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer readable storage medium is used for storing a plurality of instructions which are suitable for being loaded by a processor and executing the adaptive variable lane control method for the signal control intersection.
In other embodiments, the following technical solutions are adopted:
a computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute the above-described method of adaptive variable lane control at a signalized intersection.
Compared with the prior art, the invention has the beneficial effects that:
the invention can adapt to the traffic flow that each traffic flow of the intersection changes constantly along with time, avoid the phenomenon that a certain traffic flow lane is crowded, another traffic flow lane is vacant; the lane function is allowed to be coordinated according to the actual running condition of the road, and then signal timing optimization is carried out aiming at the change of the lane function, so that the aim of fully utilizing space resources in the intersection is fulfilled.
Drawings
FIG. 1 is a schematic diagram of traffic signal control according to a first embodiment of the present invention;
FIG. 2 is a flowchart illustrating the overall operation of an adaptive variable lane according to an embodiment of the present invention;
FIG. 3 is a schematic view illustrating a flow of controlling a lane function according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of intersection canalization in an embodiment of the invention;
FIG. 5 is a circuit diagram according to an embodiment of the present invention;
FIG. 6 is a comparison graph of average delay per vehicle for each flow direction lane before and after a variable lane is used in the embodiment of the present invention;
fig. 7 is a comparison graph of average delay of left-turning vehicles before and after a variable lane is adopted in the embodiment of the invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
The noun explains:
an inlet passage: refers to an intersection at an intersection where the road planes intersect.
Bayonet: and the vehicle monitoring system is arranged at the intersection or on the road section and is used for shooting, recording and processing all motor vehicles passing through the point.
Pre-signal: the pre-signal is a set of signal lights located upstream (about 30-50 meters) of the intersection to induce the driver to enter the variable lane.
Main signals: several groups of signal lamp devices are set at the crossing to distribute right of way to traffic flow in all directions in time.
Example one
In one or more embodiments, an adaptive variable lane control method based on bayonet detection data is disclosed, and it should be noted that not all intersections are suitable for setting a dynamic variable lane, and the following conditions and assumptions need to be satisfied in terms of road physical conditions, traffic states, and the like:
conditions are as follows:
(1) the number of the lanes at the inlet lane and the outlet lane is 4;
(2) setting a special left-turn phase for an entrance lane of the variable lane under the phase condition;
the basic assumption is that:
(1) influence of pedestrians crossing the street and non-motor vehicles is not considered;
(2) the case where right turn is controlled by a signal is not considered herein;
(3) is not suitable for a three-dimensional intersection ring intersection and the like;
(4) no consideration is given to special conditions such as traffic accidents.
The general workflow of the adaptive variable lane of the present embodiment is shown in fig. 2, and includes the following steps:
(1) collecting historical traffic data of the intersection, and determining the cycle of each conversion of lane functions according to the traffic change rule of the entrance;
(2) taking the traffic load degree index of the current intersection as a basis for lane function conversion;
(3) judging whether lane switching is carried out or not according to the switching period and the traffic load degree index of the current intersection; if so, switching the pre-signal (namely switching between left turn permission and straight going permission), optimizing the timing of the main signal, and entering the step (4); otherwise, keeping the original signal scheme;
(4) judging whether the optimized signal scheme is superior to the original scheme, if so, changing the current signal scheme into the optimized scheme; otherwise, keeping the original signal scheme;
(5) returning to the step (3), starting the judgment of the next period.
In particular, the amount of the solvent to be used,
1) determining time intervals of every two adjacent lane changes
If the time interval of the judgment is too long, the requirement of traffic flow in each direction of the road can not be met in real time, the space utilization efficiency is improved limitedly, and if the time interval of the judgment is too short, the coordination pressure between a driver and the road can be increased, and even the traffic order is disordered. Therefore, it is necessary to determine the time interval between each determination of whether the lane change function is required at the intersection through the historical rule analysis of the data collected at the actual intersection. The judgment method comprises the following steps:
the method comprises the steps of firstly, statistically analyzing the flow change characteristics of an entrance way according to a time sliding window with a period as a unit by using bayonet historical data, and determining the period of each conversion of lane functions according to the flow change rule. The time length of the lane function changing period is ensured to be shortened as much as possible under the condition that the fluctuation of the traffic flow in each flow direction is not large. The steps are as follows
(1) And selecting a data segment space with the length of n as a sliding window to judge the minimum time length of the stability of the flow data segment, wherein n is the number of data contained in the sliding window. Each data is a statistical value in a unit of one cycle
(2) Setting allowable deviation epsilon of single data in a sliding window, and setting a threshold sigma of standard deviation of n periodic flow data in the sliding window according to the allowable deviationn。
(3) Calculating the standard deviation sigma of the n flow data according to the first n calculated flow initial mean values E of the flow data0
(4) And in the process of sliding the window from the data starting point to the data ending point, the original starting point flow data is abandoned and a new period flow data enters the window every time the window is moved once, and the mean value and the standard deviation of the new n flow data are calculated. If the total N periodic flow data are obtained, obtaining N-N +1 standard deviation calculated values, and counting to satisfy the condition that the sigma is not more thannThe number of standard deviations of (a) is mn。
(5) Changing the length of the sliding window, repeating the above steps, and comparing m under each sliding window lengthnValue, take mnAnd taking the length of the sliding window at the maximum as a function switching judgment period of the lane at the intersection.
2) Basis of lane function conversion
The saturation is an important criterion for judging how the lane function should be changed, and is an index describing the traffic load degree of a road or an intersection by dividing the traffic flow of the road or the intersection by the traffic capacity of the road or the intersection.
When the left-turn traffic flow saturation is greater than the straight-going traffic flow saturation, the lane function is changed into left-turn;
when the left-turn traffic flow saturation is less than the straight traffic flow saturation, the lane function becomes straight.
The jth lane saturation calculation formula of each entrance lane is
C is the intersection signal period, qiIs the actual flow of the jth lane, SjIs the saturation flow rate of the jth lane, (pcu/h), giThe effective green time of the j-th lane traffic flow in the period,(s).
3) Signal switching scheme
In order to ensure that the traffic flow of the previous phase on the variable lane with the lane function changed is empty and the normal running of the vehicles facing to the entrance lane and the adjacent entrance lane is not influenced, the signal lamp group of the variable lane needs to ensure that the current traffic flow is closed earlier than the main signal lamp group, the vehicle of the next phase can enter the variable lane at the moment, if the average speed of the vehicle of the variable lane is v, the length of the variable lane is L, (the distance between a stop line and a variable sign) and the time length of closing the variable lane in advance is V
t2Time to drive off the intersection from the entrance lane stop line; in addition, in order to further ensure that the vehicle can be emptied, the releasing time of the variable lane can be delayed, and the delay time is not suitable to be too long.
With reference to figure 1 of the drawings,
phase of main signal turning left in north-south directionThe time of day is,
is the phase time of the main signal going straight in the north-south direction,
for the left-hand phase time of the main signal in the east-west direction,
is the straight-ahead phase time of the main signal in the east-west direction.
Common left-turn lane slave
When the vehicle starts to accumulate left-turning vehicles to pass in the next period, the variable lane needs to be delayed for a few times (the delay time is t)2) To avoid that too many vehicles accumulated on the variable lane cannot be drained in time during the left-turn phase, and the lane function is switched at t2When the time is finished, in order to ensure that the straight traffic flow on the lane before the left turn can be cleared in time when the lane changing function is switched, the pre-signal needs to be closed in advance (the advance time is t)1) Only the last straight-going vehicle entering the variable lane can be ensured to be in the state of closing the straight-going pre-signal
And driving away from the intersection before finishing.
End time to t2And finishing calculating the saturation index and the right-turn saturation index of the traffic flow on the left-turn lane of the road within the time period of the ending time.
Referring to fig. 3, in an initial state, the variable lane is straight, which is represented by α -0, α -1 represents that the variable lane is left-turned, i represents a cycle number, from the first cycle, the traffic flow of the left-turn lane and the traffic flow of the straight lane are input, the saturation of the left-turn lane and the saturation of the straight lane are calculated and compared, if the saturation of the left-turn lane is less than the saturation of the straight lane, α -0 is set, no action is performed, the lane function attribute remains unchanged, if the saturation of the left-turn lane is greater than the saturation of the straight lane, α -1 is set, N starts to count N-1, which represents that a lane function change request is received, and when the number of requests is accumulated to N times or more, the variable lane function attribute is changed to "left-turn", and the cycle count is increased by 1, and the next cycle is entered, and the above steps are repeated.
4) Main signal timing optimization
Because the number of each functional lane is continuously changed, the phase timing of each signal may need to be optimized in real time, and the optimization method is an optimization model with multiple constraint conditions.
① with average delay per car as optimization objective:
n is the number of the entrance lanes at the intersection, DiFor the average delay per car for the ith entrance lane, (s/pcu).
Wherein d isLAverage delay for left-turn traffic, qLFor left-turn traffic flow, dTIs the average delay of the straight-through traffic, qTIs a straight-going flow.
The control delay of the left-turn or straight-going traffic flow vehicles consists of three parts, namely control delay, random delay and initial queuing delay:
control delay calculation formula:
wherein λ isjIs the split green for the jth lane,
xjis the saturation of the jth lane.
Random delay calculation formula:
wherein x isjSaturation of jth lane, T duration of analysis period, (h), QjJ the traffic capacity of the first lane, (pcu/h), I the incremental delay correction factor for lane change and adjustment of the vehicle at the upstream signal, and K the delay correction factor for induction control.
Initial queuing delay calculation formula:
t' is the duration of the saturation state in the analysis period, (h), μ is the delay parameter, QbFor the number of queued vehicles at the beginning of the analysis period, Q when the chef queue length is 0b＝0。
② constraints of the signal optimization model:
a) the effective green time of each lane group must be not less than the minimum effective green time, giFor the effective green time of the ith phase,
then it indicates that the ith phase has right of way in the jth lane
The traffic capacity calculation formula is as follows:
b) the green time of each phase should also satisfy the minimum period and maximum period constraints
TlossIs the total loss time in the cycle, CminAnd CmaxThe minimum period and the maximum period allowed by the intersection are respectively, and C is satisfied because the green light time of each phase is balanced under the fixed periodmin＝Cmax。
c) Saturation constraint
After the functional attribute of the lane is changed, the saturation of the left-turn traffic flow and the straight traffic flow must be ensured to be within a certain range, and the condition that the saturation of a certain flow direction is too large is avoided
xi L≤ximax,xi T≤ximax
xi LAverage per lane saturation, x, for left-turn traffici TIs the average per lane saturation of the straight-ahead traffic.
In this embodiment, the south road is set to be a changeable lane by taking a ten-way young east road intersection in china, deng and china as an example, and the intersection canalization is as shown in fig. 4.
The intersection signal phase is shown in the following table:
assuming that the traffic flow at the intersection arrives randomly, adopting single-point preset signal control, referring to HCM2000, and setting the period C as 210 s; the distance between the intersection and the adjacent upstream intersection is more than or equal to 1.6km, so that the increment delay correction coefficient I for lane change and adjustment of the upstream signal lamp vehicle is 1.0; for a fixed period signal, the delay correction factor K for the inductive control is taken to be 0.5.
N is obtained by the lane attribute switching judgment methodp＝6。
Because the method can not be applied to an actual road, the road network is drawn in VISSIM traffic simulation software, and the simulation control is completed by a program through a python through a COM port. The road network graph is shown in fig. 5.
The simulation results are as follows: the average delay per vehicle comparison graph of the flow direction lanes before and after the variable lane is shown in fig. 6 (obtained by taking one sampling point every ten periods). The average delay of left turn vehicles before and after using a variable lane is shown in fig. 7.
Optimized lane change and signal timing times (starting at 6:00 and ending at 21:00)
Example two
In one or more embodiments, a terminal device is disclosed, which includes a server including a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements an adaptive variable lane control method for a signalized intersection in the first embodiment when executing the program. For brevity, no further description is provided herein.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include both read-only memory and random access memory, and may provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.
In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software.
The adaptive variable lane control method for the signal control intersection in the first embodiment may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, among other storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor. To avoid repetition, it is not described in detail here.
Those of ordinary skill in the art will appreciate that the various illustrative elements, i.e., algorithm steps, described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. A self-adaptive variable lane control method for a signal control intersection is characterized by comprising the following steps:
(1) collecting historical traffic data of the intersection, and determining the cycle of each conversion of lane functions according to the traffic change rule of the entrance;
(2) taking the traffic load degree index of the current intersection as a basis for lane function conversion;
(3) judging whether lane switching is carried out or not according to the switching period and the traffic load degree index of the current intersection; if yes, switching the pre-signal, optimizing the timing of the main signal, and entering the step (4); otherwise, keeping the original signal scheme;
(4) judging whether the optimized signal scheme is superior to the original scheme, if so, changing the current signal scheme into the optimized scheme; otherwise, keeping the original signal scheme;
(5) returning to the step (3), starting the judgment of the next period.
2. The self-adaptive variable lane control method for the signal control intersection as claimed in claim 1, characterized by collecting historical traffic data of the intersection and determining the cycle of each conversion of lane functions according to the traffic change rule of the entrance, specifically comprising the following steps:
selecting a data segment space with the length of n as a sliding window, wherein n is the number of data contained in the sliding window;
setting the allowable deviation of single data in a sliding window, and setting a standard deviation threshold of n periodic flow data in the sliding window according to the allowable deviation;
calculating the standard deviation of the n flow data according to the first n calculated flow initial mean values of the flow data;
sliding a sliding window from a data starting point to a data end point, discarding the original starting point flow data and entering a window with a new period flow data every time the sliding window moves once, and calculating the mean value and the standard deviation of new n flow data;
if the total number of the N periodic flow data is N, obtaining N-N +1 standard deviation calculation values, and counting the number m of the standard deviations less than or equal to the standard deviation threshold valuen；
Changing the length of the sliding window, repeating the above steps, and comparing m under each sliding window lengthnValue, take mnAnd taking the length of the sliding window at the maximum as a function switching judgment period of the lane at the intersection.
3. The adaptive variable lane control method for the signal control intersection as claimed in claim 1, wherein the traffic load degree index of the current intersection is used as a basis for lane function conversion, and specifically comprises the following steps:
taking the saturation as a traffic load degree index of the intersection, and when the saturation of the left-turning traffic flow is greater than the saturation of the straight traffic flow, changing the lane function into left-turning; when the left-turn traffic flow saturation is less than the straight traffic flow saturation, the lane function becomes straight.
4. The adaptive variable lane control method for the signalized intersection according to claim 3, wherein a j-th lane saturation calculation formula of each entrance lane is as follows:
wherein C is the intersection signal period, qiIs the actual flow of the jth lane, SjIs the saturation flow rate of the jth lane, giThe effective green time of the j-th lane traffic flow in the period.
5. The adaptive variable lane control method for the signalized intersection according to claim 1, wherein the variable lane signal lamp group closes the current traffic ahead of the main signal lamp group, and if the average vehicle speed of the variable lane is v and the length of the variable lane is L, the time period for closing the variable lane in advance is as follows:
t2is the time to drive off the intersection from the approach lane stop line.
6. The adaptive variable lane control method for the signal-controlled intersection according to claim 1, wherein the timing of the main signal is optimized, specifically:
and establishing a main signal timing optimization model by taking the minimum average delay of each vehicle as an optimization target and taking the minimum effective green light time constraint, the minimum green light time period constraint, the maximum green light time period constraint and the saturation constraint as constraint conditions.
7. The method for controlling the self-adaptive variable lane of the signal-controlled intersection according to claim 6, wherein the main signal timing optimization model is specifically as follows:
wherein n is the number of the entrance lanes of the intersection, DiDelay for average per car for the ith entrance lane; dLAverage delay for left-turn traffic, qLFor left-turn traffic flow, dTIs the average delay of the straight-through traffic, qTThe flow rate is straight-going;
respectively control delay, random delay and initial queuing delay.
8. The method for controlling the adaptive variable lane at the signalized intersection according to claim 6, wherein the constraint condition comprises:
a) the effective green light time of each lane group is not less than the minimum effective green light time;
b) the green time of each phase should also satisfy the minimum period and maximum period constraints;
c) after the functional attribute of the lane is changed, the saturation of the left-turn traffic flow and the straight traffic flow is ensured to be in a set range, and the condition that the saturation of a certain flow direction is too large is avoided.
9. A terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; a computer readable storage medium for storing a plurality of instructions adapted to be loaded by a processor and to perform the method of adaptive variable lane control at a signalized intersection according to any one of claims 1 to 8.
10. A computer readable storage medium having stored therein a plurality of instructions, characterized in that the instructions are adapted to be loaded by a processor of a terminal device and to perform the method of adaptive variable lane control at a signalized intersection according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010005695.8A CN111145564B (en) | 2020-01-03 | 2020-01-03 | Self-adaptive variable lane control method and system for signal control intersection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010005695.8A CN111145564B (en) | 2020-01-03 | 2020-01-03 | Self-adaptive variable lane control method and system for signal control intersection |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111145564A true CN111145564A (en) | 2020-05-12 |
| CN111145564B CN111145564B (en) | 2021-09-17 |
Family
ID=70523442
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010005695.8A Expired - Fee Related CN111145564B (en) | 2020-01-03 | 2020-01-03 | Self-adaptive variable lane control method and system for signal control intersection |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111145564B (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111915894A (en) * | 2020-08-06 | 2020-11-10 | 北京航空航天大学 | Variable lane and traffic signal cooperative control method based on deep reinforcement learning |
| CN112466113A (en) * | 2020-11-16 | 2021-03-09 | 南京莱斯信息技术股份有限公司 | Signal self-adaptive control method based on variable lane |
| CN112884194A (en) * | 2020-12-15 | 2021-06-01 | 苏州工业园区测绘地理信息有限公司 | Variable lane switching and signal timing method based on signalized intersection running condition |
| CN113570855A (en) * | 2021-06-22 | 2021-10-29 | 阿波罗智联(北京)科技有限公司 | Variable lane control method, device, equipment and storage medium |
| CN113823101A (en) * | 2021-09-22 | 2021-12-21 | 公安部交通管理科学研究所 | Inductive control interactive intersection signal iterative response control method and system |
| CN114038189A (en) * | 2021-11-05 | 2022-02-11 | 苏州工业园区测绘地理信息有限公司 | Self-adaptive variable lane switching method based on video analysis algorithm |
| CN114241768A (en) * | 2021-12-18 | 2022-03-25 | 擎翌(上海)智能科技有限公司 | Variable lane switching method and variable lane switching system |
| CN114360264A (en) * | 2022-01-18 | 2022-04-15 | 重庆大学 | Intelligent city traffic management method based on traffic flow regulation |
| CN115019506A (en) * | 2022-06-01 | 2022-09-06 | 山东衡昊信息技术有限公司 | Variable lane control method based on multi-process reinforcement learning |
| CN115691145A (en) * | 2023-01-04 | 2023-02-03 | 中国科学技术大学先进技术研究院 | Lane number adjusting method, device, equipment and storage medium |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040010371A1 (en) * | 2001-09-28 | 2004-01-15 | Shinji Matsumoto | Lane keep control apparatus and method for automotive vehicle |
| CN101650877A (en) * | 2009-08-31 | 2010-02-17 | 吉林大学 | Method for setting crossing self-adapting changeable driveway |
| CN104036645A (en) * | 2014-06-03 | 2014-09-10 | 东南大学 | Reversible-lane-based intersection signal control method |
| CN104074112A (en) * | 2014-07-11 | 2014-10-01 | 武汉理工大学 | Tidal lane of upstream and downstream intersection of urban road and design method of tidal lane |
| US9423266B2 (en) * | 2012-01-26 | 2016-08-23 | Telecommunication Systems, Inc. | Navigational lane guidance |
| CN106683405A (en) * | 2016-12-28 | 2017-05-17 | 安徽科力信息产业有限责任公司 | Road traffic state evaluation method based on road traffic flow density |
| CN106997391A (en) * | 2017-04-10 | 2017-08-01 | 华北电力大学（保定） | A kind of method of steady state condition data in quick screening large scale process data |
| CN107067764A (en) * | 2017-03-21 | 2017-08-18 | 东南大学 | A kind of variable guided vehicle road self-adaptation control method of urban intersection |
| CN107170257A (en) * | 2017-07-11 | 2017-09-15 | 山东理工大学 | A kind of reverse changeable driveway intelligent control method based on multi-source data |
| CN206921296U (en) * | 2017-07-10 | 2018-01-23 | 深圳市智能交通技术有限公司 | A kind of traffic signal controlling machine for possessing self-adapting changeable driveway control function |
| CN110097752A (en) * | 2019-03-27 | 2019-08-06 | 杭州远眺科技有限公司 | A kind of intelligent and variable guided vehicle road calculation method |
-
2020
- 2020-01-03 CN CN202010005695.8A patent/CN111145564B/en not_active Expired - Fee Related
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040010371A1 (en) * | 2001-09-28 | 2004-01-15 | Shinji Matsumoto | Lane keep control apparatus and method for automotive vehicle |
| CN101650877A (en) * | 2009-08-31 | 2010-02-17 | 吉林大学 | Method for setting crossing self-adapting changeable driveway |
| US9423266B2 (en) * | 2012-01-26 | 2016-08-23 | Telecommunication Systems, Inc. | Navigational lane guidance |
| CN104036645A (en) * | 2014-06-03 | 2014-09-10 | 东南大学 | Reversible-lane-based intersection signal control method |
| CN104074112A (en) * | 2014-07-11 | 2014-10-01 | 武汉理工大学 | Tidal lane of upstream and downstream intersection of urban road and design method of tidal lane |
| CN106683405A (en) * | 2016-12-28 | 2017-05-17 | 安徽科力信息产业有限责任公司 | Road traffic state evaluation method based on road traffic flow density |
| CN107067764A (en) * | 2017-03-21 | 2017-08-18 | 东南大学 | A kind of variable guided vehicle road self-adaptation control method of urban intersection |
| CN106997391A (en) * | 2017-04-10 | 2017-08-01 | 华北电力大学（保定） | A kind of method of steady state condition data in quick screening large scale process data |
| CN206921296U (en) * | 2017-07-10 | 2018-01-23 | 深圳市智能交通技术有限公司 | A kind of traffic signal controlling machine for possessing self-adapting changeable driveway control function |
| CN107170257A (en) * | 2017-07-11 | 2017-09-15 | 山东理工大学 | A kind of reverse changeable driveway intelligent control method based on multi-source data |
| CN110097752A (en) * | 2019-03-27 | 2019-08-06 | 杭州远眺科技有限公司 | A kind of intelligent and variable guided vehicle road calculation method |
Non-Patent Citations (6)
| Title |
|---|
| JINJUN TANG: ""A hierarchical prediction model for lane-changes based on combination of fuzzy C-means and adaptive neural network"", <EXPERT SYSTEMS WITH APPLICATIONS> * |
| MA QING: ""A New Control Strategy of Variable Lane Based on Video Detection "", <2014 FIFTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND ENGINEERING APPLICATIONS> * |
| 丁靖: ""信号控制交叉口可变导向车道的研究"", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 傅立骏: ""基于动态交通流量的可变车道自适应控制方法"", 《科技通报》 * |
| 刘昱岗: ""基于ＡＮＦＩＳ的可变导向车道智能控制系统"", 《交通运输工程学报》 * |
| 孙锋: ""交叉口逆向可变车道与信号配时协同优化方法"", 《公路交通科技》 * |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111915894B (en) * | 2020-08-06 | 2021-07-27 | 北京航空航天大学 | Variable lane and traffic signal cooperative control method based on deep reinforcement learning |
| CN111915894A (en) * | 2020-08-06 | 2020-11-10 | 北京航空航天大学 | Variable lane and traffic signal cooperative control method based on deep reinforcement learning |
| CN112466113A (en) * | 2020-11-16 | 2021-03-09 | 南京莱斯信息技术股份有限公司 | Signal self-adaptive control method based on variable lane |
| CN112884194A (en) * | 2020-12-15 | 2021-06-01 | 苏州工业园区测绘地理信息有限公司 | Variable lane switching and signal timing method based on signalized intersection running condition |
| CN112884194B (en) * | 2020-12-15 | 2024-04-02 | 园测信息科技股份有限公司 | Variable lane switching and signal timing method based on signal intersection operation condition |
| CN113570855A (en) * | 2021-06-22 | 2021-10-29 | 阿波罗智联(北京)科技有限公司 | Variable lane control method, device, equipment and storage medium |
| JP2022120022A (en) * | 2021-06-22 | 2022-08-17 | 阿波▲羅▼智▲聯▼（北京）科技有限公司 | Control method for variable lane, device, apparatus, and storage medium |
| CN113823101A (en) * | 2021-09-22 | 2021-12-21 | 公安部交通管理科学研究所 | Inductive control interactive intersection signal iterative response control method and system |
| CN113823101B (en) * | 2021-09-22 | 2022-06-21 | 公安部交通管理科学研究所 | Inductive control interactive intersection signal iterative response control method and system |
| CN114038189A (en) * | 2021-11-05 | 2022-02-11 | 苏州工业园区测绘地理信息有限公司 | Self-adaptive variable lane switching method based on video analysis algorithm |
| CN114241768B (en) * | 2021-12-18 | 2023-07-21 | 擎翌(上海)智能科技有限公司 | Variable lane switching method and variable lane switching system |
| CN114241768A (en) * | 2021-12-18 | 2022-03-25 | 擎翌(上海)智能科技有限公司 | Variable lane switching method and variable lane switching system |
| CN114360264A (en) * | 2022-01-18 | 2022-04-15 | 重庆大学 | Intelligent city traffic management method based on traffic flow regulation |
| CN115019506B (en) * | 2022-06-01 | 2024-03-01 | 北京百车宝科技有限公司 | Variable lane control method based on multi-process reinforcement learning |
| CN115019506A (en) * | 2022-06-01 | 2022-09-06 | 山东衡昊信息技术有限公司 | Variable lane control method based on multi-process reinforcement learning |
| CN115691145A (en) * | 2023-01-04 | 2023-02-03 | 中国科学技术大学先进技术研究院 | Lane number adjusting method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111145564B (en) | 2021-09-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111145564B (en) | Self-adaptive variable lane control method and system for signal control intersection | |
| CN108399759B (en) | Traffic design method for continuous flow intersection left-turn non-motor vehicles | |
| CN107016857B (en) | Signal control intersection left-turn traffic combination design optimization method | |
| CN103996289B (en) | A kind of flow-speeds match model and Travel Time Estimation Method and system | |
| CN103559795B (en) | Multi-strategy and multi-object self-adaptation traffic control method | |
| CN105788301B (en) | The pre- stop line in piggybacking left-hand rotation intersection and pre-signal method to set up | |
| CN112037507B (en) | Supersaturated traffic state trunk line adaptive signal coordination design method and device | |
| CN107067759B (en) | ACP-based parallel traffic signal lamp real-time control method | |
| CN104077919A (en) | Optimization method for combined phase position of needed lane | |
| CN107945539B (en) | Intersection signal control method | |
| CN111091722B (en) | Optimization method of intersection signal control parameters in man-machine hybrid driving environment | |
| CN109191847B (en) | Self-adaptive trunk line coordination control method and system based on city gate data | |
| CN110910662A (en) | Single-point self-adaptive traffic signal optimization control method under cooperative vehicle and road environment | |
| CN105405303A (en) | Traffic control method based on traffic flow | |
| CN105046990B (en) | Pedestrian walkway signals' control method between a kind of adjacent intersection based on particle cluster algorithm | |
| CN103337178A (en) | Traffic signal self-adaptive control method based on dynamic priority | |
| CN113538897B (en) | Urban traffic area iterative learning boundary control method considering disturbance | |
| CN111833619B (en) | Supersaturated traffic state trunk line bidirectional signal coordination design method and device | |
| CN106952484B (en) | Road network threshold control based on macroscopic basic graph | |
| CN114155724A (en) | Intersection traffic signal control method under Internet of vehicles environment | |
| WO2023035666A1 (en) | Urban road network traffic light control method based on expected reward estimation | |
| CN113763728B (en) | Traffic organization and signal timing collaborative optimization method, device and equipment | |
| CN109859475B (en) | Intersection signal control method, device and system based on DBSCAN density clustering | |
| Yao et al. | CTM-based traffic signal optimization of mixed traffic flow with connected automated vehicles and human-driven vehicles | |
| CN113470390B (en) | Multiphase dynamic coordination control method for short-link intersection edge node fusion |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210917 |