CN116959275A - Urban traffic jam optimization method and system - Google Patents
Urban traffic jam optimization method and system Download PDFInfo
- Publication number
- CN116959275A CN116959275A CN202311212205.1A CN202311212205A CN116959275A CN 116959275 A CN116959275 A CN 116959275A CN 202311212205 A CN202311212205 A CN 202311212205A CN 116959275 A CN116959275 A CN 116959275A
- Authority
- CN
- China
- Prior art keywords
- lane
- length
- congestion
- traffic
- time length
- 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 41
- 238000005457 optimization Methods 0.000 title claims description 24
- 238000001514 detection method Methods 0.000 claims abstract description 66
- 238000012545 processing Methods 0.000 claims abstract description 30
- 238000004364 calculation method Methods 0.000 claims description 20
- 238000012937 correction Methods 0.000 claims description 18
- 239000006185 dispersion Substances 0.000 claims description 18
- 230000009471 action Effects 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 4
- 238000004458 analytical method Methods 0.000 description 14
- 206010021033 Hypomenorrhoea Diseases 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
Classifications
-
- 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
- G08G1/01—Detecting movement of traffic to be counted or controlled
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The application relates to a city traffic jam optimizing method and system, and relates to the field of traffic management technology, wherein the method comprises the steps of obtaining a detection road image and marking a detection road; determining a detection lane region according to the lane matching relationship; acquiring a traffic flow queuing length in a detection lane area; judging whether the traffic flow queuing length is greater than the congestion reference length; if the traffic is larger than the traffic jam, defining the traffic jam lane as a traffic jam lane, determining an associated lane corresponding to the traffic jam lane according to the intersection matching relation, and defining the vehicle queuing length of the associated lane as an associated length; determining a reference time length corresponding to the association length according to the time length matching relation; and determining the associated demand time according to all the reference time, determining the congestion and dredging time according to the signal lamp period time and the associated demand time, and controlling the signal lamps corresponding to the congestion traffic channels to pass by the green lamps according to the congestion and dredging time. The application has the effect of being convenient for processing the traffic jam condition.
Description
Technical Field
The application relates to the technical field of traffic management, in particular to a method and a system for optimizing urban traffic jam.
Background
Along with the development of the times, vehicles on roads are rapidly increased, and pressure is given to the roads, so that when most of the vehicles are on the same road, road congestion occurs, and at the moment, the speed of the vehicles is slow, so that people are influenced.
In the related art, when a road is congested, the current solution is generally directed by traffic control personnel at an intersection, so that traffic in all directions can normally travel until traffic is completely dredged.
In view of the above-mentioned related art, the inventor considers that the traffic congestion is dredged by traffic management personnel, the traffic management personnel is required to drop to each intersection, and more labor cost is required, so that the traffic congestion is not conveniently dredged, and there is still room for improvement.
Disclosure of Invention
In order to facilitate the processing of traffic congestion, the application provides a method and a system for optimizing urban traffic congestion.
In a first aspect, the present application provides a method for optimizing urban traffic congestion, which adopts the following technical scheme:
a city traffic jam optimizing method comprises the following steps:
acquiring a detection road image and a corresponding mark detection road;
determining a detection lane region corresponding to the marked detection road in the detection road image according to a preset lane matching relationship;
Performing feature recognition on the detection lane area to obtain the queuing length of the traffic flow;
judging whether the traffic flow queuing length is greater than a preset congestion reference length;
if the traffic flow queuing length is not greater than the congestion reference length, no action is performed;
if the traffic flow queuing length is greater than the congestion reference length, defining the lane as a congestion lane, determining an associated lane corresponding to the congestion lane according to a preset intersection matching relationship, and defining the vehicle queuing length of the associated lane as an associated length;
determining a reference time length corresponding to the association length according to a preset time length matching relation;
and carrying out summation calculation according to all the reference time lengths to determine the associated demand time length, carrying out difference calculation according to the preset signal lamp period time length and the associated demand time length to determine the congestion dredging time length, and controlling the signal lamps corresponding to the congestion traffic lanes to carry out green light passing according to the congestion dredging time length.
By adopting the technical scheme, whether the traffic jam occurs or not is determined by acquiring the traffic flow queuing length, when the traffic jam occurs, different time durations are matched according to the congestion degree to adjust the green light passing time length of the traffic lane, so that vehicles on the traffic lane with the traffic jam can relatively quickly leave the traffic lane, the situation that the vehicles gather on the traffic jam lane to further cause the traffic jam is reduced, and the traffic jam is conveniently processed.
Optionally, after the associated lane is determined, the urban traffic jam optimizing method further includes:
judging whether a congestion lane exists in the associated lanes or not;
if no congestion lane exists in the associated lane, calculating the associated demand time length to determine the congestion dispersion time length;
if the traffic jam lane exists in the associated lane, defining the corresponding associated lane and the current traffic jam lane as the affected lane, determining a reference time length according to the associated lane which does not affect the lane, and summing up and calculating an associated demand time length;
calculating a difference value according to the signal lamp period duration and the associated demand duration to determine an allocable duration;
establishing a detection interval with the width of a preset fixed duration on a preset time axis, enabling the rear end point of the detection interval to coincide with the current time point, and acquiring the average value moving speed affecting the lane in the detection interval;
calculating according to the average moving speed and the corresponding traffic flow queuing length to determine the lane load affecting the lane;
calculating according to all lane loads to determine the demand ratio of the single influencing lane, determining the congestion and dredging time length of the single influencing lane according to the demand ratio and the allocable time length, and controlling the signal lamps corresponding to the congestion and dredging time length to carry out green light traffic.
By adopting the technical scheme, the condition that a plurality of congestion lanes appear at one intersection is determined so as to adapt proper congestion dredging time length to optimize the congestion condition.
Optionally, after the congestion relief duration is determined, the urban traffic congestion optimization method further includes:
acquiring the original green light display time length of the congestion traffic lane;
calculating a difference value according to the congestion dispersion time length and the green light display time length to determine an adjustment time length;
judging whether the adjustment time length is longer than a preset reference demand time length or not;
if the adjusted time length is longer than the reference demand time length, controlling a signal lamp corresponding to the congestion traffic channel to pass through green light with the congestion dredging time length;
if the adjustment time length is not greater than the reference demand time length, determining an entering lane corresponding to the congestion lane according to a preset lane entering and exiting matching relationship, and acquiring the green light passing time length of the entering lane;
calculating a difference value according to the green light passing duration and a preset correction duration to determine the correction passing duration;
and controlling the signal lamps corresponding to the traffic jam lane to carry out green light passing by using the jam dredging time length, and controlling the signal lamps corresponding to the entering lane to correct the passing time length to carry out green light passing.
By adopting the technical scheme, when the adjusted green light passing duration is smaller than the original green light passing duration without larger change, the optimization effect on the current lane is poorer, and the traffic flow entering the lane is reduced at the moment so as to reduce the congestion to further aggravate.
Optionally, the method further comprises a step of determining a correction duration, the step comprising:
defining the queuing length of the traffic flow entering the lane as the entering length;
acquiring the cycle increment length and the cycle loss length of a entering lane in a detection interval;
calculating a difference value according to a preset early warning length and an entering length to determine the growth degree;
generating a variable duration with a variable value, and calculating according to the green light passing duration, the period loss length and the variable duration to determine the variable loss length;
calculating according to the period increment length and the variable loss length to determine the period net increment length, and calculating according to the increased length and the period net increment length to determine the number of up-to-standard periods;
and when the number of the up-to-standard periods is consistent with the preset fixed number, calculating a difference value according to the green light passing duration and the corresponding variable duration to determine the correction duration.
By adopting the technical scheme, the more proper correction time length can be determined so that the traffic jam condition is not easy to occur in the entering lane.
Optionally, the step of calculating according to the green light traffic duration, the period loss length and the variable duration to determine the variable loss length includes:
Defining a vehicle queuing length corresponding to the period loss length as a history length;
definition:
the green light passing duration is T 1 ；
Length of period loss L 1 ；
Variable duration is T 2 ；
Variable loss length L 2 ；
History length L 3 ；
Length of entry L 4 ；
The preset ratio coefficient is gamma;
then。
By adopting the technical scheme, the more accurate variable loss length can be calculated.
Optionally, if the adjustment time length is longer than the reference demand time length, the urban traffic jam optimizing method further includes:
determining an outgoing road corresponding to the congestion road according to the lane entrance-exit matching relationship, and defining the lane as an outgoing lane in the outgoing road;
defining the vehicle flow queuing length of the driving-out lane as the driving-out length;
calculating according to the driving-out length and a preset limited length to determine the lane pressure;
acquiring the driving-in distribution duty ratio of each driving-out lane in the driving-out road in the detection section;
calculating according to the driving-in distribution duty ratio, the average moving speed and the congestion dispersion duration to determine the increment pressure of the driving-in lane;
calculating according to the lane pressure, the increment pressure and the preset permission pressure to determine excess pressure;
determining the corresponding adjustment time length of excess pressure according to a preset pressure matching relation;
According to the adjustment time length, the congestion dispersion time length is corrected and updated, the signal lamps corresponding to the congestion traffic channels are controlled to pass through green lamps according to the updated congestion dispersion time length, and the adjustment time length is distributed in the signal lamps of the relevant lanes in the same intersection according to a preset distribution rule.
By adopting the technical scheme, the load pressure condition of the lane from which the vehicle exits can be analyzed, so that the condition that the exiting lane is jammed due to the fact that a large number of vehicles enter the current lane is reduced.
Optionally, the allocation rule includes:
judging whether a congestion lane exists in the related lanes or not;
if no congestion lane exists in the related lanes, calculating according to the traffic queuing lengths of the related lanes to determine the traffic ratio of the lanes, and calculating according to the traffic ratio of the lanes and the adjustment time length to determine the lane allocation time length;
if a congestion lane exists in the related lane, acquiring the upper limit time of the permission of the congestion lane, and defining the congestion dredging time length of the congestion lane as the actual dredging time length;
performing difference calculation according to the allowable upper limit duration and the actual dredging duration to determine a difference duration;
and preferentially distributing the adjustment time length to the lane corresponding to the difference time length with the largest value according to a preset sequencing rule, continuously determining the difference time length with the largest value in the remaining lanes when the difference time length remains after distribution until the congestion lane is distributed, determining the lane traffic flow ratio of the remaining lanes when the congestion lane is distributed, and determining the lane distribution time length when the congestion lane remains after the distribution is completed.
By adopting the technical scheme, the time length can be preferentially distributed to the most needed lanes, so that the congestion optimization effect is better.
In a second aspect, the application provides an urban traffic congestion optimization system, which adopts the following technical scheme:
an urban traffic congestion optimization system comprising:
the acquisition module is used for acquiring the detection road image and the corresponding mark detection road;
the processing module is connected with the acquisition module and the judging module and is used for storing and processing information;
the judging module is connected with the acquisition module and the processing module and is used for judging information;
the processing module determines a detection lane region corresponding to the marked detection road in the detection road image according to a preset lane matching relationship;
the processing module performs feature recognition on the detection lane area so that the acquisition module acquires the queuing length of the traffic flow;
the judging module judges whether the queuing length of the traffic flow is larger than a preset congestion reference length;
if the judging module judges that the traffic queuing length is not greater than the congestion reference length, no action is performed;
if the judging module judges that the traffic flow queuing length is greater than the congestion reference length, the processing module defines the traffic lane as a congestion traffic lane, determines an associated traffic lane corresponding to the congestion traffic lane according to a preset intersection matching relationship, and defines the traffic queuing length of the associated traffic lane as an associated length;
The processing module determines a reference time length corresponding to the association length according to a preset time length matching relation;
the processing module performs summation calculation according to all the reference time lengths to determine the associated demand time lengths, performs difference calculation according to the preset signal lamp period time lengths and the associated demand time lengths to determine the congestion dredging time lengths, and controls the signal lamps corresponding to the congestion traffic lanes to perform green light traffic according to the congestion dredging time lengths.
By adopting the technical scheme, the vehicle flow queuing length is acquired through the acquisition module so that the judgment module can determine whether the congestion situation possibly occurs, when the judgment module confirms that the congestion situation occurs, the processing module matches different time lengths according to the congestion degree so as to adjust the green light passing time length of the lane, so that vehicles on the lane with the congestion situation can relatively quickly exit the lane, the situation that the vehicles gather on the congested lane and further the congestion situation occurs is reduced, and the traffic congestion situation is conveniently processed.
In summary, the present application includes at least one of the following beneficial technical effects:
when the road is congested, the green light passing time length on the road can be corrected according to the congestion degree condition, so that vehicles in the congested lanes can be driven out in time, and effective treatment of traffic congestion is realized;
When the current traffic congestion situation cannot be optimized continuously, the driving-in vehicles can be limited, so that the occurrence of the situation that the traffic congestion is further aggravated is reduced;
and analyzing the road condition of the vehicle driving out of the lane in the congestion processing process so as to reduce the congestion condition of the driving out lane caused by the influence of the current congestion lane.
Drawings
Fig. 1 is a flow chart of a city traffic congestion optimization method.
Fig. 2 is a flow chart of a method of analyzing a multi-lane congestion situation.
Fig. 3 is a flow chart of an approach lane analysis method.
Fig. 4 is a schematic view of urban road traffic.
Fig. 5 is a flowchart of the correction duration determination method.
Fig. 6 is a flowchart of the outgoing lane analysis method.
Fig. 7 is a flow chart of an allocation rule determination method.
Fig. 8 is a block flow diagram of a city traffic congestion optimization method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings 1 to 8 and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Embodiments of the application are described in further detail below with reference to the drawings.
The embodiment of the application discloses an urban traffic jam optimizing method, which is used for analyzing the condition of each lane of an intersection and an associated intersection when a road is jammed, comprehensively analyzing each data to determine the green light time length required to be adjusted so as to enable the green light traffic time length of the jammed lane to be increased, thereby enabling vehicles on the jammed lane to exit on the lane and realizing effective treatment of the jammed condition.
Referring to fig. 1, the method flow of the urban traffic congestion optimization method includes the following steps:
step S100: and acquiring a detection road image and a corresponding mark detection road.
The detection road image is an image of each vehicle driving road, can be obtained through a camera arranged on the road, can be supplemented by law enforcement recorders worn on traffic control personnel, and is marked as the road corresponding to the detection road image.
Step S101: and determining a detection lane region corresponding to the marked detection road in the detection road image according to the preset lane matching relationship.
The detection lane area is an image area on the image of lanes in different directions on the same lane, such as a left-turn lane, a straight-turn lane, a right-turn lane and the like; the lane matching relation among the different marks, which are used for detecting the different positions of the lanes on the road and the different positions of the lanes on the detected road image, is recorded and stored in advance by a staff.
Step S102: and performing feature recognition on the detection lane area to obtain the queuing length of the traffic flow.
The vehicle flow queuing length is the actual vehicle queuing length on the lane corresponding to the detection lane region, the queuing length of the vehicle on the image can be determined by carrying out feature recognition on the vehicle on the detection lane region, then the vehicle flow queuing length is obtained by calculating parameters such as a camera angle, a shooting distance and the like, and the calculation method of the actual length by the length in the image is a conventional technical means of a person skilled in the art and is not repeated.
Step S103: and judging whether the queuing length of the traffic flow is larger than a preset congestion reference length.
The congestion reference length is the vehicle queuing length when the intersection set by the staff is congested, the congestion reference lengths corresponding to different roads are inconsistent, the congestion reference length can be determined by marking the determination of the detection road, and the relation between the congestion reference length and the congestion reference length is recorded and stored in advance by the staff; the purpose of the judgment is to know whether the traffic lane is congested.
Step S1031: if the traffic flow queuing length is not greater than the congestion reference length, no action is performed.
When the traffic flow queuing length is not greater than the congestion reference length, the traffic lane is indicated to be free from congestion, and special treatment is not needed at the moment.
Step S1032: if the traffic flow queuing length is greater than the congestion reference length, defining the lane as a congestion lane, determining an associated lane corresponding to the congestion lane according to a preset intersection matching relationship, and defining the vehicle queuing length of the associated lane as an associated length.
When the traffic flow queuing length is greater than the congestion reference length, indicating that the traffic lane is congested, and processing the congestion; defining a congestion lane to distinguish different lanes, facilitating subsequent analysis and control, wherein the associated lane is a lane in which the green light cannot be lightened simultaneously by the intersection and the congestion lane, and the intersection matching relationship between the two is determined in advance by a staff; the associated length is defined to distinguish the vehicle queuing lengths of different lanes for subsequent analysis.
Step S104: and determining the reference time length corresponding to the association length according to the preset time length matching relation.
The reference time length is the time length when the vehicle can normally run without congestion under the traffic flow of the correlation length, for example, only 2 vehicles are needed, at this time, only the green light is needed for 5 seconds, and the time length matching relation between the two is determined in advance by staff.
Step S105: and carrying out summation calculation according to all the reference time lengths to determine the associated demand time length, carrying out difference calculation according to the preset signal lamp period time length and the associated demand time length to determine the congestion dredging time length, and controlling the signal lamps corresponding to the congestion traffic lanes to carry out green light passing according to the congestion dredging time length.
The related demand time length is the time length occupied by other lanes in the current signal lamp period, the signal lamp period time length is the time length corresponding to the time length when the signal lamp corresponding to the traffic jam lane changes in one period, namely the time length between the time of the signal lamp being lighted up and the time of the next time of the signal lamp being lighted up, the traffic jam dredging time length is the time length for the traffic jam lane to travel under the condition that the basic traveling requirements of other related vehicles are met in the signal lamp period time length, the related demand time length is subtracted from the signal lamp period time length to determine, and the green light corresponding to the traffic jam lane is controlled by the traffic jam dredging time length, so that the vehicles of the traffic jam lane can travel out of the traffic jam lane more conveniently, and effective traffic jam processing is realized.
Referring to fig. 2, after the associated lane is determined, the city traffic congestion optimization method further includes:
step S200: and judging whether a congestion lane exists in the associated lanes.
The purpose of the judgment is to know whether the duration can be distributed on the signal lamp corresponding to one congestion channel or not.
Step S2001: if no congestion lane exists in the associated lane, calculating the associated demand time length to determine the congestion relief time length.
When no congestion lane exists in the associated lane, the indication can be used by moving the time length to a signal lamp of the congestion lane, and the congestion dredging time length is normally determined.
Step S2002: if the traffic jam lane exists in the associated lane, defining the corresponding associated lane and the current traffic jam lane as the affected lane, determining a reference time length according to the associated lane which does not affect the lane, and summing up and calculating the associated demand time length.
When a congestion lane exists in the associated lane, the fact that a plurality of congestion lanes need to be analyzed is indicated, at the moment, the reference time lengths of the associated lanes cannot be added to determine the reference time length needed to be used, the influence lanes are defined to identify and distinguish the traffic lanes with congestion at the same intersection, and the associated demand time length is the sum of the reference time lengths needed by the fact that the traffic lanes without congestion favor the traffic lanes under the condition of meeting the condition that the traffic lanes without congestion.
Step S201: and calculating a difference value according to the signal lamp period duration and the associated demand duration to determine the allocable duration.
The assignable duration is the green light passing duration which is more than the signal light period, and the signal light period duration minus the associated demand duration is used for determining.
Step S202: and establishing a detection interval with the width of a preset fixed duration on a preset time axis, enabling the rear end point of the detection interval to coincide with the current time point, and acquiring the average value moving speed affecting the lane in the detection interval.
The time axis is a coordinate axis formed by combining all time points, the fixed time length is the time length which is set by a worker and can be used for collecting and analyzing the vehicle running condition under a certain condition of a lane, and a detection interval is established so as to be convenient for analyzing the vehicle flow running condition on the lane; the average moving speed is the average speed affecting the movement of the vehicle in the detection section, and can be determined by analyzing the moving condition of the vehicle.
Step S203: and calculating according to the average moving speed and the corresponding traffic flow queuing length to determine the lane load affecting the lane.
The lane load is the pressure load of the current lane with congestion, the larger the value is, the more congestion is indicated, and the calculation formula isWhere Φ is the lane load, v 0 For the average speed of the normal running of the vehicle when the traffic lane is not congested, L 0 For the normal queuing length of the vehicle when the traffic lane is not jammed, the two are preset values, L' is the queuing length of the traffic flow, v 1 The mean moving speed.
Step S204: calculating according to all lane loads to determine the demand ratio of the single influencing lane, determining the congestion and dredging time length of the single influencing lane according to the demand ratio and the allocable time length, and controlling the signal lamps corresponding to the congestion and dredging time length to carry out green light traffic.
The demand ratio is the ratio of the time length to be allocated for influencing the lane, the larger the lane load is, the larger the congestion degree is, the larger the corresponding demand ratio is, and the demand ratio can be added through all lane loads and then the value of the ratio is determined through a single lane load; the allocable duration of each affected lane can be determined by multiplying the demand duty ratio by the allocable duration, and at the moment, the corresponding congestion traffic lane is controlled to pass through green light by the corresponding congestion dredging duration so that traffic congestion can be relieved.
Referring to fig. 3, after the congestion routing duration is determined, the city traffic congestion optimization method further includes:
step S300: and acquiring the original green light display time length of the congestion traffic lane.
The green light display time length is the green light time length displayed in the signal light period before the congestion lane re-congestion and dispersion time length is not determined.
Step S301: and calculating a difference value according to the congestion dispersion time length and the green light display time length to determine an adjustment time length.
The adjustment time length is the time length difference between the adjusted green light of the congestion lane and the time length before adjustment, and the time length of green light display is subtracted from the congestion dredging time length to determine
Step S302: judging whether the adjustment time length is longer than a preset reference demand time length.
The reference time length is the minimum adjustment time length set by the staff and used for recognizing that the green light time length of the congestion lane changes greatly, and the judgment purpose is to know whether the green light time length of the congestion lane changes greatly or not so as to determine whether the congestion situation can be effectively relieved or not.
Step S3021: and if the adjustment time length is longer than the reference demand time length, controlling a signal lamp corresponding to the congestion traffic channel to pass through green light with the congestion dredging time length.
When the adjustment time length is longer than the reference demand time length, the time length after the current congestion lane is adjusted is changed greatly, the congestion situation can be effectively relieved, and green light passing is normally carried out according to the congestion dredging time length.
Step S3022: if the adjustment time length is not greater than the reference demand time length, determining an entering lane corresponding to the traffic jam lane according to a preset lane entering and exiting matching relationship, and acquiring the green light passing time length of the entering lane.
When the adjustment time length is not greater than the reference demand time length, the time length after the adjustment of the current congestion lane is not changed greatly, the congestion situation can not be relieved only by adjusting the green light time length, and further analysis is needed; the entering lane is a lane in which a vehicle can enter a congestion lane, and referring to fig. 4, the green light passing duration is a duration in which a signal light corresponding to the entering lane is displayed as a green light in a signal light period.
Step S303: and calculating a difference value according to the green light traffic duration and the preset correction duration to determine the correction traffic duration.
The correction duration is the duration for reducing the green light entering the lane, and the value can be set by a worker according to the actual situation and can be determined according to the vehicle situation of the lane; the corrected traffic duration is the duration of green light traffic of the vehicles which can enter the lane after being corrected by the corrected duration, and the corrected duration is subtracted from the green light traffic duration to determine.
Step S304: and controlling the signal lamps corresponding to the traffic jam lane to carry out green light passing by using the jam dredging time length, and controlling the signal lamps corresponding to the entering lane to correct the passing time length to carry out green light passing.
The traffic lights corresponding to the traffic jam lanes are controlled to pass through green lights in the jam dredging time length so that vehicles on the jam lanes can leave the jam lanes as far as possible, and meanwhile, the traffic lights corresponding to the entering lanes are controlled to correct the passing time length to pass through green lights so that the vehicles entering the lanes enter the jam lanes as late as possible, so that the occurrence of the situation that the jam of the jam lanes is further aggravated is reduced.
Referring to fig. 5, the method further includes a step of determining a correction duration, including:
Step S400: the flow queuing length of the traffic entering the lane is defined as the entry length.
The entering length is defined to distinguish the queuing lengths of the traffic flow of different lanes, so that the subsequent analysis is convenient.
Step S401: and acquiring the cycle increment length and the cycle loss length of the entering lane in the detection interval.
The cycle increment length is the length formed by vehicles entering the lane in a single signal lamp period in the detection interval, and the cycle loss length is the length formed by vehicles exiting the lane in a single signal lamp period in the detection interval.
Step S402: and carrying out difference calculation according to the preset early warning length and the entering length to determine the growth degree.
The early warning length is the boundary length set by the staff and used for recognizing the situation that the traffic entering the lane is likely to be jammed, and the specific numerical value is set by the staff according to the road situation and other factors; the extendable length is the length of queuing vehicles which can be increased when entering the lane at present, and is determined by subtracting the entering length from the early warning length.
Step S403: and generating a variable duration with variable values, and calculating according to the green light traffic duration, the period loss length and the variable duration to determine the variable loss length.
The variable duration is a duration with a variable value, the variable loss length is a length value that a vehicle entering a lane can exit in the variable duration, and the calculation method is as follows: defining the vehicle queuing length corresponding to the period loss length as the history length, thenWherein T is 1 The green light passing duration is the green light passing duration; l (L) 1 Length for cycle loss; t (T) 2 Is of variable duration; l (L) 2 Is a variable loss length; l (L) 3 Is the history length; l (L) 4 For the entry length; gamma is a preset ratio coefficient, which is a fixed value.
Step S404: and calculating according to the period increment length and the variable loss length to determine the period net increment length, and calculating according to the increased length and the period net increment length to determine the number of up-to-standard periods.
The period net increase length is the length of the vehicle which is increased when entering the lane in a single signal lamp period, and the period increment length is determined by subtracting the variable loss length; the number of up-to-standard periods is the number of signal lamp periods required by a vehicle entering a lane to reach a condition where congestion may occur.
Step S405: and when the number of the up-to-standard periods is consistent with the preset fixed number, calculating a difference value according to the green light passing duration and the corresponding variable duration to determine the correction duration.
The fixed number is the period number when the entering lane is allowed to be jammed and set by the staff, the fixed number is the number after the front jammed traffic lane is not jammed in general, the condition that the entering lane passes the signal lamp period of the standard period number under the current condition is indicated to be jammed when the standard period number is consistent with the fixed number, and at the moment, the proper correction time can be obtained by subtracting the variable time length at the moment by the green lamp passing time length.
Referring to fig. 6, if the adjustment time period is longer than the reference demand time period, the city traffic congestion optimization method further includes:
step S500: and determining an outgoing road corresponding to the blocked traffic lane according to the lane entrance-exit matching relationship, and defining the lane as an outgoing lane in the outgoing road.
When the adjustment time length is longer than the reference demand time length, the method can enable the vehicle which is jammed in the lane to quickly drive out so as to relieve the traffic jam of the lane, but the condition that the traffic jam occurs in the lane which is driven in after the vehicle is driven out possibly exists, and further analysis is needed; the outgoing road is a road into which a vehicle that is a congested lane enters after exiting, and referring to fig. 4, the outgoing lane is a lane in each direction of the outgoing road, for example, a left-turn lane, a straight lane, or the like.
Step S501: the flow queuing length of the outgoing lane is defined as the outgoing length.
The driving-out length is defined to distinguish the queuing lengths of the traffic flows of different lanes, so that the subsequent analysis is convenient.
Step S502: and calculating according to the driving-out length and the preset limited length to determine the lane pressure.
The limited length is the vehicle queuing length when the output lane is crowded, the lane pressure is the current vehicle pressure of the lane, and the determination is made by dividing the driving-out length by the limited length.
Step S503: an entry allocation duty ratio of each of the outgoing lanes in the outgoing road is acquired in the detection section.
The driving-in allocation ratio is the ratio of the vehicles in the driving-out road to the driving-in/driving-out road in each lane, for example, 100 vehicles in the driving-in/driving-out road in the detection section, wherein the number of driving-in left lanes is 30, the number of driving-out lanes is 60, the number of driving-out lanes is 10, and the corresponding driving-in allocation ratios are 30%, 60% and 10%, respectively.
Step S504: and calculating according to the driving-in distribution duty ratio, the average moving speed and the congestion dispersion duration to determine the increment pressure of the driving-in lane.
The added pressure is the pressure brought to the driving-in lane when the traffic jam lane passes through green light in the traffic jam dredging time period, the average moving speed and the traffic jam dredging time period are utilized to obtain the condition of vehicles which can be driven in a single period, and the driving-in ratio is allocated to determine the pressure of each driving-in lane at the moment.
Step S505: and calculating according to the lane pressure, the increment pressure and the preset permission pressure to determine the excess pressure.
The allowable pressure is a lane pressure value set by a worker and used for identifying that the driving-in lane is at the boundary of the congestion condition, and the excess pressure is an excess pressure which is caused to the driving-in lane when the vehicle is driven under the congestion dredging time, and the excessive pressure is determined by adding the added pressure to the lane pressure and subtracting the allowable pressure.
Step S506: and determining the corresponding adjustment time length of the excess pressure according to the preset pressure matching relation.
The adjustment time length is the time length for reducing the congestion dredging time length of the congestion lane, when the excess pressure is not more than zero, the congestion dredging time length of the congestion lane is not greatly influenced, the adjustment time length at the moment is 0, different excess pressures have different adjustment time lengths, and the pressure matching relation between the two is determined by a plurality of experiments performed in advance by a worker.
Step S507: according to the adjustment time length, the congestion dispersion time length is corrected and updated, the signal lamps corresponding to the congestion traffic channels are controlled to pass through green lamps according to the updated congestion dispersion time length, and the adjustment time length is distributed in the signal lamps of the relevant lanes in the same intersection according to a preset distribution rule.
The original congestion dispersion time length is used for subtracting the adjustment time length to update the congestion dispersion time length, so that vehicles in a congested lane cannot rush into the driving lane at one time to cause congestion in the driving lane, meanwhile, the adjustment time length can be distributed in signal lamps of other lanes to realize rapid passing of the vehicles in the other lanes, and a method for distributing the time length set by a worker according to a distribution rule is described below.
Referring to fig. 7, the allocation rule includes:
step S600: and judging whether a congestion lane exists in the related lanes.
The purpose of the judgment is to know whether the congestion channel needs to be subjected to preferential allocation of the duration.
Step S6001: if no congestion lane exists in the related lanes, calculating according to the traffic queuing lengths of the related lanes to determine the traffic ratio of the lanes, and calculating according to the traffic ratio of the lanes and the adjustment time length to determine the lane allocation time length.
When no traffic jam channel exists in the related lanes, the fact that all the related lanes have no pressure of vehicle jam is indicated, the traffic flow ratio of the lanes is the ratio of vehicles of all the related lanes of the vehicle station on the lanes, and the queuing lengths of all the traffic flows are added and then calculated and determined by using the queuing length of a single traffic flow; the time length allocated to the single lane with the lane allocation time length in the adjustment time length is determined by multiplying the lane traffic flow ratio by the adjustment time length.
Step S6002: if a congestion lane exists in the related lane, acquiring the upper limit time of the permission of the congestion lane, and defining the congestion dredging time length of the congestion lane as the actual dredging time length.
When a congestion lane exists in the related lane, the condition that the congestion pressure exists in the lane is indicated, and further analysis is needed; the upper limit allowable duration is the maximum signal street lamp duration to which the congestion lane can be adjusted, the numerical value is determined by comprehensively considering the bearable degree of the front lane, and the real dredging duration is defined to distinguish the congestion dredging duration of the lane which is the congestion lane in the related lanes, so that the subsequent analysis is convenient.
Step S601: and carrying out difference calculation according to the allowable upper limit duration and the actual dispersion duration to determine a difference duration.
The difference time length is the time length of the green light when the green light of the congested lane reaches the upper limit of the permission, and the real dredging output is subtracted from the upper limit of the permission to determine.
Step S602: and preferentially distributing the adjustment time length to the lane corresponding to the difference time length with the largest value according to a preset sequencing rule, continuously determining the difference time length with the largest value in the remaining lanes when the difference time length remains after distribution until the congestion lane is distributed, determining the lane traffic flow ratio of the remaining lanes when the congestion lane is distributed, and determining the lane distribution time length when the congestion lane remains after the distribution is completed.
The sorting rule is a method which is set by staff and can sort the numerical values, and the sorting rule can be used for preferentially distributing the time length of the lane with the largest difference value, so that the lane needing to be dredged can be timely congestion dredged, and the effective treatment of the overall traffic congestion is improved.
Referring to fig. 8, based on the same inventive concept, an embodiment of the present invention provides an urban traffic congestion optimization system, including:
the acquisition module is used for acquiring the detection road image and the corresponding mark detection road;
the processing module is connected with the acquisition module and the judging module and is used for storing and processing information;
the judging module is connected with the acquisition module and the processing module and is used for judging information;
the processing module determines a detection lane region corresponding to the marked detection road in the detection road image according to a preset lane matching relationship;
the processing module performs feature recognition on the detection lane area so that the acquisition module acquires the queuing length of the traffic flow;
the judging module judges whether the queuing length of the traffic flow is larger than a preset congestion reference length;
if the judging module judges that the traffic queuing length is not greater than the congestion reference length, no action is performed;
if the judging module judges that the traffic flow queuing length is greater than the congestion reference length, the processing module defines the traffic lane as a congestion traffic lane, determines an associated traffic lane corresponding to the congestion traffic lane according to a preset intersection matching relationship, and defines the traffic queuing length of the associated traffic lane as an associated length;
The processing module determines a reference time length corresponding to the association length according to a preset time length matching relation;
the processing module performs summation calculation according to all the reference time lengths to determine the associated demand time length, performs difference calculation according to the preset signal lamp period time length and the associated demand time length to determine the congestion dredging time length, and controls the signal lamps corresponding to the congestion traffic lanes to perform green light traffic according to the congestion dredging time length;
the multi-congestion analysis module is used for analyzing the congestion of a plurality of lanes at a single intersection so as to realize effective allocation of time length;
the entering lane analysis module is used for carrying out analysis control on the entering lane so as to reduce the condition that the vehicles entering the lane drive into the congestion lane to aggravate the congestion condition;
the correction time length determining module is used for determining more accurate correction time length;
the variable loss length calculation module is used for calculating more accurate variable loss length;
the outgoing lane analysis module is used for analyzing an outgoing lane so as to reduce the situation that the pressure of vehicles on the outgoing lane is too high and congestion occurs;
and the allocation rule determining module is used for determining rules for allocating the adjustment time length.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above. The specific working processes of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which are not described herein.
Claims (8)
1. A method for optimizing urban traffic congestion, comprising:
acquiring a detection road image and a corresponding mark detection road;
determining a detection lane region corresponding to the marked detection road in the detection road image according to a preset lane matching relationship;
performing feature recognition on the detection lane area to obtain the queuing length of the traffic flow;
judging whether the traffic flow queuing length is greater than a preset congestion reference length;
if the traffic flow queuing length is not greater than the congestion reference length, no action is performed;
if the traffic flow queuing length is greater than the congestion reference length, defining the lane as a congestion lane, determining an associated lane corresponding to the congestion lane according to a preset intersection matching relationship, and defining the vehicle queuing length of the associated lane as an associated length;
determining a reference time length corresponding to the association length according to a preset time length matching relation;
and carrying out summation calculation according to all the reference time lengths to determine the associated demand time length, carrying out difference calculation according to the preset signal lamp period time length and the associated demand time length to determine the congestion dredging time length, and controlling the signal lamps corresponding to the congestion traffic lanes to carry out green light passing according to the congestion dredging time length.
2. The urban traffic congestion optimization method according to claim 1, characterized in that after the associated lane determination, the urban traffic congestion optimization method further comprises:
judging whether a congestion lane exists in the associated lanes or not;
if no congestion lane exists in the associated lane, calculating the associated demand time length to determine the congestion dispersion time length;
if the traffic jam lane exists in the associated lane, defining the corresponding associated lane and the current traffic jam lane as the affected lane, determining a reference time length according to the associated lane which does not affect the lane, and summing up and calculating an associated demand time length;
calculating a difference value according to the signal lamp period duration and the associated demand duration to determine an allocable duration;
establishing a detection interval with the width of a preset fixed duration on a preset time axis, enabling the rear end point of the detection interval to coincide with the current time point, and acquiring the average value moving speed affecting the lane in the detection interval;
calculating according to the average moving speed and the corresponding traffic flow queuing length to determine the lane load affecting the lane;
calculating according to all lane loads to determine the demand ratio of the single influencing lane, determining the congestion and dredging time length of the single influencing lane according to the demand ratio and the allocable time length, and controlling the signal lamps corresponding to the congestion and dredging time length to carry out green light traffic.
3. The urban traffic congestion optimization method according to claim 2, characterized in that after the congestion relief time period is determined, the urban traffic congestion optimization method further comprises:
acquiring the original green light display time length of the congestion traffic lane;
calculating a difference value according to the congestion dispersion time length and the green light display time length to determine an adjustment time length;
judging whether the adjustment time length is longer than a preset reference demand time length or not;
if the adjusted time length is longer than the reference demand time length, controlling a signal lamp corresponding to the congestion traffic channel to pass through green light with the congestion dredging time length;
if the adjustment time length is not greater than the reference demand time length, determining an entering lane corresponding to the congestion lane according to a preset lane entering and exiting matching relationship, and acquiring the green light passing time length of the entering lane;
calculating a difference value according to the green light passing duration and a preset correction duration to determine the correction passing duration;
and controlling the signal lamps corresponding to the traffic jam lane to carry out green light passing by using the jam dredging time length, and controlling the signal lamps corresponding to the entering lane to correct the passing time length to carry out green light passing.
4. The urban traffic congestion optimization method according to claim 3, further comprising a step of determining a correction duration, the step comprising:
Defining the queuing length of the traffic flow entering the lane as the entering length;
acquiring the cycle increment length and the cycle loss length of a entering lane in a detection interval;
calculating a difference value according to a preset early warning length and an entering length to determine the growth degree;
generating a variable duration with a variable value, and calculating according to the green light passing duration, the period loss length and the variable duration to determine the variable loss length;
calculating according to the period increment length and the variable loss length to determine the period net increment length, and calculating according to the increased length and the period net increment length to determine the number of up-to-standard periods;
and when the number of the up-to-standard periods is consistent with the preset fixed number, calculating a difference value according to the green light passing duration and the corresponding variable duration to determine the correction duration.
5. The urban traffic congestion optimization method according to claim 4, wherein the step of calculating to determine the variable loss length based on the green light traffic duration, the period loss length, and the variable duration comprises:
defining a vehicle queuing length corresponding to the period loss length as a history length;
definition: the green light passing duration is T 1 ；
Length of period loss L 1 ；
Variable duration is T 2 ；
Variable loss length L 2 ；
History length L 3 ；
Length of entry L 4 ；
The preset ratio coefficient is gamma;
then。
6. The urban traffic congestion optimization method according to claim 3, wherein if the adjustment time period is longer than the reference demand time period, the urban traffic congestion optimization method further comprises:
determining an outgoing road corresponding to the congestion road according to the lane entrance-exit matching relationship, and defining the lane as an outgoing lane in the outgoing road;
defining the vehicle flow queuing length of the driving-out lane as the driving-out length;
calculating according to the driving-out length and a preset limited length to determine the lane pressure;
acquiring the driving-in distribution duty ratio of each driving-out lane in the driving-out road in the detection section;
calculating according to the driving-in distribution duty ratio, the average moving speed and the congestion dispersion duration to determine the increment pressure of the driving-in lane;
calculating according to the lane pressure, the increment pressure and the preset permission pressure to determine excess pressure;
determining the corresponding adjustment time length of excess pressure according to a preset pressure matching relation;
according to the adjustment time length, the congestion dispersion time length is corrected and updated, the signal lamps corresponding to the congestion traffic channels are controlled to pass through green lamps according to the updated congestion dispersion time length, and the adjustment time length is distributed in the signal lamps of the relevant lanes in the same intersection according to a preset distribution rule.
7. The urban traffic congestion optimization method according to claim 6, wherein the allocation rule comprises:
judging whether a congestion lane exists in the related lanes or not;
if no congestion lane exists in the related lanes, calculating according to the traffic queuing lengths of the related lanes to determine the traffic ratio of the lanes, and calculating according to the traffic ratio of the lanes and the adjustment time length to determine the lane allocation time length;
if a congestion lane exists in the related lane, acquiring the upper limit time of the permission of the congestion lane, and defining the congestion dredging time length of the congestion lane as the actual dredging time length;
performing difference calculation according to the allowable upper limit duration and the actual dredging duration to determine a difference duration;
and preferentially distributing the adjustment time length to the lane corresponding to the difference time length with the largest value according to a preset sequencing rule, continuously determining the difference time length with the largest value in the remaining lanes when the difference time length remains after distribution until the congestion lane is distributed, determining the lane traffic flow ratio of the remaining lanes when the congestion lane is distributed, and determining the lane distribution time length when the congestion lane remains after the distribution is completed.
8. A city traffic congestion optimization system, comprising:
The acquisition module is used for acquiring the detection road image and the corresponding mark detection road;
the processing module is connected with the acquisition module and the judging module and is used for storing and processing information;
the judging module is connected with the acquisition module and the processing module and is used for judging information;
the processing module determines a detection lane region corresponding to the marked detection road in the detection road image according to a preset lane matching relationship;
the processing module performs feature recognition on the detection lane area so that the acquisition module acquires the queuing length of the traffic flow;
the judging module judges whether the queuing length of the traffic flow is larger than a preset congestion reference length;
if the judging module judges that the traffic queuing length is not greater than the congestion reference length, no action is performed;
if the judging module judges that the traffic flow queuing length is greater than the congestion reference length, the processing module defines the traffic lane as a congestion traffic lane, determines an associated traffic lane corresponding to the congestion traffic lane according to a preset intersection matching relationship, and defines the traffic queuing length of the associated traffic lane as an associated length;
the processing module determines a reference time length corresponding to the association length according to a preset time length matching relation;
the processing module performs summation calculation according to all the reference time lengths to determine the associated demand time lengths, performs difference calculation according to the preset signal lamp period time lengths and the associated demand time lengths to determine the congestion dredging time lengths, and controls the signal lamps corresponding to the congestion traffic lanes to perform green light traffic according to the congestion dredging time lengths.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311212205.1A CN116959275B (en) | 2023-09-20 | 2023-09-20 | Urban traffic jam optimization method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311212205.1A CN116959275B (en) | 2023-09-20 | 2023-09-20 | Urban traffic jam optimization method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116959275A true CN116959275A (en) | 2023-10-27 |
| CN116959275B CN116959275B (en) | 2023-12-26 |
Family
ID=88449561
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311212205.1A Active CN116959275B (en) | 2023-09-20 | 2023-09-20 | Urban traffic jam optimization method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116959275B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117831293A (en) * | 2024-01-09 | 2024-04-05 | 西安市政设计研究院有限公司 | Intelligent traffic control method and system |
| CN118447694A (en) * | 2024-04-26 | 2024-08-06 | 西安文爱电子科技有限公司 | Road traffic control system and traffic signal indicator lamp |
| CN118470992A (en) * | 2024-07-10 | 2024-08-09 | 江苏点创信息科技有限公司 | Vehicle-road cooperation method and device based on monitoring |
| CN118609370A (en) * | 2024-07-12 | 2024-09-06 | 南京信息工程大学 | A traffic diversion and control method based on cloud computing |
| CN118711375A (en) * | 2024-08-27 | 2024-09-27 | 广东车卫士信息科技有限公司 | A data analysis method and system for vehicle-mounted OBU |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH076898U (en) * | 1993-06-30 | 1995-01-31 | 日本サミコン株式会社 | One side traffic signal |
| CN103473935A (en) * | 2013-09-03 | 2013-12-25 | 青岛海信网络科技股份有限公司 | Crossing traffic jam judging and control method and system based on sensing detectors |
| WO2018149308A1 (en) * | 2017-02-15 | 2018-08-23 | 阿里巴巴集团控股有限公司 | Road traffic optimization method and device and electronic apparatus |
| CN109035814A (en) * | 2018-07-02 | 2018-12-18 | 福建榕基软件股份有限公司 | A kind of turn-on interval time automatic adjusting method and system |
| CN112562361A (en) * | 2020-11-30 | 2021-03-26 | 重庆电子工程职业学院 | Traffic signal lamp control method and system for smart city |
| CN112767719A (en) * | 2021-02-23 | 2021-05-07 | 上海慈航建设发展有限公司 | Efficient traffic signal lamp control system and control method |
| CN114299729A (en) * | 2021-12-06 | 2022-04-08 | 江苏航天大为科技股份有限公司 | Signal control method, system and computer storage medium based on intelligent traffic |
| CN115188199A (en) * | 2022-09-13 | 2022-10-14 | 深圳市城市交通规划设计研究中心股份有限公司 | Traffic guidance and signal control collaborative optimization method, electronic device and storage medium |
| WO2023035666A1 (en) * | 2021-09-10 | 2023-03-16 | 之江实验室 | Urban road network traffic light control method based on expected reward estimation |
-
2023
- 2023-09-20 CN CN202311212205.1A patent/CN116959275B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH076898U (en) * | 1993-06-30 | 1995-01-31 | 日本サミコン株式会社 | One side traffic signal |
| CN103473935A (en) * | 2013-09-03 | 2013-12-25 | 青岛海信网络科技股份有限公司 | Crossing traffic jam judging and control method and system based on sensing detectors |
| WO2018149308A1 (en) * | 2017-02-15 | 2018-08-23 | 阿里巴巴集团控股有限公司 | Road traffic optimization method and device and electronic apparatus |
| CN109035814A (en) * | 2018-07-02 | 2018-12-18 | 福建榕基软件股份有限公司 | A kind of turn-on interval time automatic adjusting method and system |
| CN112562361A (en) * | 2020-11-30 | 2021-03-26 | 重庆电子工程职业学院 | Traffic signal lamp control method and system for smart city |
| CN112767719A (en) * | 2021-02-23 | 2021-05-07 | 上海慈航建设发展有限公司 | Efficient traffic signal lamp control system and control method |
| WO2023035666A1 (en) * | 2021-09-10 | 2023-03-16 | 之江实验室 | Urban road network traffic light control method based on expected reward estimation |
| CN114299729A (en) * | 2021-12-06 | 2022-04-08 | 江苏航天大为科技股份有限公司 | Signal control method, system and computer storage medium based on intelligent traffic |
| CN115188199A (en) * | 2022-09-13 | 2022-10-14 | 深圳市城市交通规划设计研究中心股份有限公司 | Traffic guidance and signal control collaborative optimization method, electronic device and storage medium |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117831293A (en) * | 2024-01-09 | 2024-04-05 | 西安市政设计研究院有限公司 | Intelligent traffic control method and system |
| CN117831293B (en) * | 2024-01-09 | 2024-06-07 | 西安市政设计研究院有限公司 | Intelligent traffic control method and system |
| CN118447694A (en) * | 2024-04-26 | 2024-08-06 | 西安文爱电子科技有限公司 | Road traffic control system and traffic signal indicator lamp |
| CN118447694B (en) * | 2024-04-26 | 2024-12-24 | 西安文爱电子科技有限公司 | Road traffic control system and traffic signal indicator lamp |
| CN118470992A (en) * | 2024-07-10 | 2024-08-09 | 江苏点创信息科技有限公司 | Vehicle-road cooperation method and device based on monitoring |
| CN118609370A (en) * | 2024-07-12 | 2024-09-06 | 南京信息工程大学 | A traffic diversion and control method based on cloud computing |
| CN118711375A (en) * | 2024-08-27 | 2024-09-27 | 广东车卫士信息科技有限公司 | A data analysis method and system for vehicle-mounted OBU |
| CN118711375B (en) * | 2024-08-27 | 2024-12-10 | 广东车卫士信息科技有限公司 | A data analysis method and system for vehicle-mounted OBU |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116959275B (en) | 2023-12-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116959275B (en) | Urban traffic jam optimization method and system | |
| CN108806291B (en) | Method and system for vehicle merging guidance on high saturation ramp based on roadside equipment | |
| CN111613070B (en) | Traffic signal lamp control method, traffic signal lamp control device, electronic equipment and computer storage medium | |
| CN112069944A (en) | Road congestion level determination method | |
| CN114973661B (en) | Traffic signal lamp with intelligent control and traffic flow data storage | |
| CN117831293B (en) | Intelligent traffic control method and system | |
| CN112382102A (en) | Intelligent control system of urban traffic signal lamp | |
| CN116913108B (en) | Urban traffic monitoring and scheduling method and system | |
| CN112037538A (en) | Traffic signal lamp control method, temporary traffic command system and device | |
| CN113505346A (en) | Urban street lamp data processing and combined regulation and control system based on artificial intelligence | |
| CN117523840B (en) | Intelligent lane information management system and method based on digital analysis | |
| CN113053142A (en) | Bus priority control system based on vehicle-mounted positioning and bus path cooperation technology | |
| CN117746636A (en) | A smart city traffic command and monitoring system | |
| CN114049760A (en) | Traffic control method, device and system based on intersection | |
| CN120279734A (en) | Traffic signal lamp intelligent regulation and control system based on big data | |
| CN116740966A (en) | Automatic traffic management system based on digital twinning | |
| CN118736886B (en) | Parking lot service system based on intelligent allocation | |
| WO2022179321A1 (en) | Method and apparatus for arranging road detection device, and storage medium | |
| CN116631176B (en) | Control method and system for station passenger flow distribution state | |
| CN117172454A (en) | Intelligent meeting scheduling method and system for separate repair tunnel | |
| CN112148598A (en) | Traffic algorithm verification system based on migration simulation | |
| CN115620535B (en) | Traffic signal lamp management method and system based on big data | |
| CN115423868B (en) | Space positioning linkage calibration method for video monitoring camera | |
| CN117058877B (en) | Urban traffic intelligent monitoring method and system | |
| CN116824863A (en) | Intelligent road network monitoring 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 | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A method and system for optimizing urban traffic congestion Granted publication date: 20231226 Pledgee: Bank of Beijing Co.,Ltd. Jinan Branch Pledgor: CHINA ZE ELECTRONIC CO.,LTD. Registration number: Y2024370000029 |
|
| PE01 | Entry into force of the registration of the contract for pledge of patent right |