CN110111592B - Method for dynamically matching optimal signal timing scheme based on traffic signal controller - Google Patents
Method for dynamically matching optimal signal timing scheme based on traffic signal controller Download PDFInfo
- Publication number
- CN110111592B CN110111592B CN201910552516.XA CN201910552516A CN110111592B CN 110111592 B CN110111592 B CN 110111592B CN 201910552516 A CN201910552516 A CN 201910552516A CN 110111592 B CN110111592 B CN 110111592B
- Authority
- CN
- China
- Prior art keywords
- scheme
- signal
- traffic
- traffic flow
- sequence group
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000013439 planning Methods 0.000 claims abstract description 5
- 238000004806 packaging method and process Methods 0.000 claims abstract description 4
- 238000004422 calculation algorithm Methods 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 9
- 230000007704 transition Effects 0.000 claims description 9
- 230000006978 adaptation Effects 0.000 claims description 6
- 238000010587 phase diagram Methods 0.000 claims description 6
- 238000004088 simulation Methods 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 238000000819 phase cycle Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000011835 investigation Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000012384 transportation and delivery Methods 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
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
Abstract
The invention discloses a method for dynamically matching an optimal signal timing scheme based on a traffic signal controller, which belongs to the field of signal lamp control, and aims to solve the technical problems of acquiring traffic flow information on a road in real time, optimizing scheme timing, predicting congestion indexes, providing a corresponding signal timing scheme aiming at intersection traffic and adjusting traffic flow, wherein the adopted technical scheme is as follows: the method comprises the following specific steps: s1, planning and constructing a traffic flow-signal scheme database; s2, predicting a congestion coefficient; s3, the traffic signal scheme expert formulates a signal lamp timing scheme and stores the signal lamp timing scheme into a traffic flow-signal scheme database; s4, carrying out rule judgment on the real-time traffic flow in any time interval, and matching an optimal signal lamp timing scheme in the next time interval; and S5, packaging the acquired signal lamp timing schemes into a scheme which can be identified by the annunciator platform and sending the scheme to the annunciator platform, so as to realize real-time dynamic adjustment of the traffic signal lamps at the traffic intersection.
Description
Technical Field
The invention relates to the field of signal lamp control, in particular to a method for dynamically matching an optimal signal timing scheme based on a traffic signal controller.
Background
The traffic signal control machine is mostly used for controlling and managing the traffic signals at domestic intersections, and the amount of traffic signal control intersections in China is about 13 thousands according to statistics until 2018. The traffic signal controller is a well-set timing control scheme, and comprises single-stage timing control, multi-stage timing control and the like. The timing scheme used in the timing control method is formulated according to historical data of traffic investigation, and is kept unchanged until next traffic investigation after determination.
The traffic police is a direct manager for road traffic control, different timing schemes need to be set in the signal controller in advance by the traffic police according to traffic flow and pedestrian density at different times in a day, traffic lights are manually controlled at intersections, due to professional limitation, traffic management departments mainly perform control according to control experience when setting the timing schemes of the traffic lights, and adjust the timing schemes again according to traffic passing feedback conditions after the schemes are deployed. Obviously, the timing control mode of the traditional signal control machine has the problems of incapability of adapting to random change of traffic flow, lack of flexibility, poor timeliness and the like. At present, the content of a signal lamp timing scheme is single, and a large amount of manpower and material resources are consumed to maintain the signal scheme.
In recent years, the informatization construction of urban roads is carried out in China, so that the perception means and the perception mode of urban road traffic flow are greatly enriched. In the field of current intelligent traffic signal lamp research, more and more people propose to collect traffic flow information on roads in real time by means of videos and the like, perform scheme timing optimization, predict congestion indexes, provide a corresponding signal timing scheme aiming at intersection traffic and adjust traffic flow. Therefore, how to acquire traffic flow information on roads in real time, optimize scheme timing, predict congestion indexes, provide a corresponding signal timing scheme for intersection traffic, and adjust traffic flow is a technical problem which needs to be solved urgently.
Patent document No. CN108389403A discloses an intelligent traffic signal lamp and speed limit sign adjusting method based on traffic flow capture, which adopts a technical scheme that the intelligent traffic signal lamp and speed limit sign adjusting method includes a collecting camera for collecting road traffic flow information, a control computer equipped with traffic simulation software, and a cloud database server for storing traffic signal lamp and electronic speed limit sign adjusting schemes, wherein the collecting camera collects real-time road traffic information, the real-time road traffic information is processed and then synchronized into the control computer for simulation operation, and then an optimal traffic signal lamp and electronic speed limit sign adjusting scheme is matched according to real-time road traffic conditions, so as to dynamically adjust the traffic signal lamp and electronic speed limit sign. However, the technical scheme can not carry out scheme timing optimization according to the road traffic flow information acquired in real time, predict the congestion index, provide a corresponding signal timing scheme aiming at the intersection traffic and adjust the traffic flow.
Disclosure of Invention
The technical task of the invention is to provide a method for dynamically matching an optimal signal timing scheme based on a traffic signal controller, so as to solve the problems of how to acquire traffic flow information on roads in real time, optimize scheme timing, predict congestion indexes, propose a corresponding signal timing scheme for intersection traffic and adjust traffic flow.
The technical task of the invention is realized in the following way, the method for dynamically matching the optimal signal timing scheme based on the traffic signal controller is characterized in that a traffic signal scheme expert formulates a signal lamp timing scheme, each signal lamp timing scheme is provided with a corresponding rule judgment value, and the formulated signal lamp timing scheme is stored in a traffic flow-signal scheme database; real-time traffic flow of each lane is collected through a road camera or a vehicle-mounted GPS, traffic flow data is subjected to rule analysis and judgment, and an optimal signal lamp timing scheme is matched in a traffic flow-signal scheme database by using a dynamic programming algorithm; the method comprises the following specific steps:
s1, planning and constructing a traffic flow-signal scheme database;
s2, prediction congestion coefficient: acquiring traffic flow information in real time by using a road camera or a vehicle-mounted GPS, storing the traffic flow information into a traffic flow-signal scheme database, analyzing the congestion state of the intersection according to data in the traffic flow-signal scheme database, and predicting the congestion coefficient of the intersection at the next period;
s3, the traffic signal scheme expert formulates a signal lamp timing scheme and stores the signal lamp timing scheme into a traffic flow-signal scheme database;
s4, carrying out rule judgment on the real-time traffic flow in any time interval, and matching an optimal signal lamp timing scheme in the next time interval;
and S5, packaging the acquired signal lamp timing schemes into a scheme which can be identified by the annunciator platform and sending the scheme to the annunciator platform, so as to realize real-time dynamic adjustment of the traffic signal lamps at the traffic intersection.
Preferably, the traffic flow-signal scheme database includes a flow table (car _ flow), a timing scheme table (signal _ list), and a signal scheme delivery record table (send _ record);
the flow meter is used for recording the collected real-time traffic flow of each lane;
the timing scheme table is used for storing a signal lamp timing scheme;
the signal scheme issuing record table is used for recording a signal scheme issuing log.
Preferably, the traffic flow information in step S2 is stored in a flow meter in the traffic flow-signal pattern database.
Preferably, the specific steps of predicting the congestion coefficient in step S2 are as follows:
s201, redefining lanes on the road junction: the lanes are named according to the naming rule of intersection name, vehicle driving direction and lane number, so that the traffic flow information on the road can be collected conveniently;
s202, acquiring information of traffic flow and pedestrian flow on each road in real time by using a road camera and a vehicle-mounted GPS; the existing cameras on the road are used for information acquisition, the number of lanes, the number of vehicles on each lane and the number of pedestrians waiting at the intersection are sorted out, and time cost and price cost are saved.
Preferably, the concrete steps of redefining the lane at the intersection in step S201 are as follows:
s20101, direction division: dividing according to the driving direction of the vehicle; for example, if the uppermost vehicle runs from north to south, the direction of the lane where the vehicle is located is named as NTS;
s20102, lane number definition: according to the PTV vissim rule of a traffic simulation tool, when more than two lanes are on one road, observing the driving direction of the lanes, wherein the outermost side is a first lane, and the lanes are named from outside to inside in sequence; for example, the lane in which the vehicle is located is the first lane, and the lane in which the vehicle is located may be redefined as RoadName-NTS-01.
Preferably, in the step S3, the traffic signal plan expert formulates a traffic light timing plan and stores the traffic light timing plan into a timing plan table (signal _ list) in the traffic flow-signal plan database; the signal lamp timing scheme comprises a required period duration, a total effective green lamp duration, a green lamp duration of each sequence, a scheme optimal time interval and a scheme pre-selection judgment condition in the timing scheme.
Preferably, in step S4, the specific steps of performing rule judgment on the real-time traffic flow in any time interval and matching the optimal signal light timing scheme in the next time interval are as follows:
s401, setting an interval range (interval), preferably 15 minutes, and summarizing and counting the traffic flow of the current time interval from a flow table (car _ flow) of a traffic flow-signal scheme database according to lanes;
s402, calculating the congestion coefficient TPI of the current lane: summarizing the traffic flow according to the redefined lane classification in the step S2, counting the real-time vehicle passing number of each lane, the passing direction of the vehicle, the traffic light proportion of the lane and the speed limit condition of the lane, and calculating the congestion coefficient of the lane;
s403, matching an optimal timing scheme from a timing scheme table (signal _ list) of the traffic flow-signal scheme database, and realizing the process of matching the optimal signal lamp timing scheme by adopting a dynamic programming algorithm; the dynamic programming algorithm is to decompose the problem into a plurality of interconnected sub-problems, and obtain the solution of the original problem by solving the solutions of the sub-problems, which is essentially the divide-and-conquer idea and the solution of redundancy.
Preferably, the step S402 of calculating the congestion coefficient TPI of the current lane, summarizing the traffic flow according to the lane classification redefined in the step S2, and counting the number of real-time vehicle passing in each lane includes the following specific steps:
s40201, manufacturing a phase diagram of a four-phase sequence of the crossroad, wherein the phase diagram is respectively a sequence group I, a sequence group II, a sequence group III and a sequence group IV; the sequence group (i) comprises two lanes, and the statistical data are named as RoadName-WTE-01 and RoadName-WTE-02; the sequence group II comprises two lanes, and the counted data are named as RoadName-ETW-01 and RoadName-ETW-02; the sequence group III comprises two lanes, the counted data are named as RoadName-STN-01 and RoadName-STN-02, the sequence group IV comprises two lanes, and the counted data are named as RoadName-NTS-01 and RoadName-NTS-02; the sequence group (I) and the sequence group (II) form a relative sequence group (1), the sequence group (III) and the sequence group (IV) form a relative sequence group (2), and each relative sequence group corresponds to a standard single-phase maximum value (Std _ Uniphase _ Max _ sequence No) in a timing scheme table of a traffic flow-signal scheme database;
s40202, processing the traffic flow data of each lane counted in the step S40201 to obtain an actual single-phase maximum value (Ture _ Uniphase _ Max _ sequence No) of each relative sequence group; the calculation formula of the actual single-phase maximum value of the relative sequence group 1 is as follows:
wherein TPI-WTE represents a congestion coefficient in the west-east direction; TPI-ETW represents the congestion coefficient in the east-west direction;
the calculation formula of the actual single-phase maximum value of the relative sequence group 2 is as follows:
wherein, TPI-SN represents the congestion coefficient in the north-south direction; TPI-NS represents the congestion coefficient in the north-south direction.
Preferably, the dynamic programming algorithm in step S403 decomposes the problem into a plurality of interconnected sub-problems, and obtains the solution of the original problem by solving the solutions of the sub-problems, which is substantially a divide-and-conquer idea and solves redundancy, and the specific steps are as follows:
s40301, dividing the problem into 3 interrelated stages according to the space characteristic according to the problem condition;
s40302, solving the solutions of all relative sequence groups by adopting the calculation formula of the step S40202, and recording the solution as S (i);
s40303, transition from one state to the next state is called state transition, and according to the problem situation, the state transition equation is:
S(i)＝(tureMax1≤std1))∩(tureMax2≤std2)∩…∩(tureMaxi≤stdi)；
wherein, turmaxi represents the actual single-phase maximum value of the relative sequence group calculated in step S40202; stdi represents a pre-selection judgment condition of the timing scheme table (signal _ list) in step S1;
s40304, setting m signal lamp timing schemes in the traffic flow-signal scheme database, and performing the first relative sequence group comparison and then having n signal lamp timing schemes1The stripe adaptation scheme is analogized by the way that n is arranged after the t-th relative sequence group comparisontThe strip adaptation scheme, which uses dynamic programming to program the time complexity of the problem to O (m) + O (n)1)+…+O(nt) This greatly reduces the complexity of scheme matching.
Preferably, the sending record of the signal lamp timing scheme in the step S5 is stored in a signal scheme issuing record table (send _ record) of the traffic flow-signal scheme database, so as to compare and record whether the currently issued signal lamp timing scheme is the best.
The method for dynamically matching the optimal signal timing scheme based on the traffic signal controller has the following advantages that:
the invention issues the optimal signal timing scheme to the traffic signal controller of the intersection according to the real-time road condition of the road, thereby effectively avoiding traffic jam caused by unreasonable signal timing scheme; the method comprises the steps that a signal traffic flow-signal scheme database is established to carry out rule prejudgment on collected real-time traffic flow data, dynamic planning is used for matching, an optimal timing scheme is obtained, and the optimal timing scheme is issued to a traffic signal controller corresponding to an intersection, so that traffic jam is relieved;
by dynamically configuring a signal lamp timing scheme, the invention utilizes the existing resources to the maximum extent, reduces the waiting time cost, reduces the pressure of traffic police, provides road trip reminding for vehicle drivers and pedestrians in time, relieves the congestion pressure of road trip, and realizes the safety, rapidity and comfort of traffic flow;
the invention aims to solve the problems that the content of the existing signal lamp timing scheme is single, a large amount of manpower and material resources are consumed to maintain the signal scheme, and the like.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a schematic diagram of lane information redefinition;
fig. 2 is a phase illustration;
FIG. 3 is a diagram of an idea model of dynamic programming.
Detailed Description
The method for dynamically matching the optimal signal timing scheme based on the traffic signal control machine according to the present invention will be described in detail with reference to the drawings and the embodiments.
Example (b):
the invention relates to a method for dynamically matching an optimal signal timing scheme based on a traffic signal controller, which comprises the steps of formulating a signal lamp timing scheme by a traffic signal scheme expert, setting a corresponding rule judgment value in each signal lamp timing scheme, and storing the formulated signal lamp timing scheme into a traffic flow-signal scheme database; real-time traffic flow of each lane is collected through a road camera or a vehicle-mounted GPS, traffic flow data is subjected to rule analysis and judgment, and an optimal signal lamp timing scheme is matched in a traffic flow-signal scheme database by using a dynamic programming algorithm; the method comprises the following specific steps:
s1, planning and constructing a traffic flow-signal scheme database; the traffic flow-signal scheme database comprises a flow table (car _ flow), a timing scheme table (signal _ list) and a signal scheme issuing record table (send _ record); the flow meter is used for recording the collected real-time traffic flow of each lane; the timing scheme table is used for storing a signal lamp timing scheme; the signal scheme issuing recording table is used for recording a signal scheme issuing log;
s2, prediction congestion coefficient: acquiring traffic flow information in real time by using a road camera or a vehicle-mounted GPS, storing the traffic flow information into a flow meter of a traffic flow-signal scheme database, analyzing the congestion state of the intersection according to data in the traffic flow-signal scheme database, and predicting the congestion coefficient of the intersection at the next period; the method comprises the following specific steps:
s201, redefining lanes on the road junction: the lanes are named according to the naming rule of intersection name, vehicle driving direction and lane number, so that the traffic flow information on the road can be collected conveniently; as shown in the attached figure 1, the method comprises the following specific steps:
s20101, direction division: dividing according to the driving direction of the vehicle; for example, if the uppermost vehicle runs from north to south, the direction of the lane where the vehicle is located is named as NTS;
s20102, lane number definition: according to the PTV vissim rule of a traffic simulation tool, when more than two lanes are on one road, observing the driving direction of the lanes, wherein the outermost side is a first lane, and the lanes are named from outside to inside in sequence; for example, the lane in which the uppermost vehicle is located is the first lane, and the lane in which the uppermost vehicle is located in fig. 1 may be redefined as RoadName-NTS-01.
S202, acquiring information of traffic flow and pedestrian flow on each road in real time by using a road camera and a vehicle-mounted GPS; the existing cameras on the road are used for information acquisition, the number of lanes, the number of vehicles on each lane and the number of pedestrians waiting at the intersection are sorted out, and time cost and price cost are saved.
S3, the traffic signal scheme expert formulates a signal lamp timing scheme and stores the signal lamp timing scheme into a timing scheme table (signal _ list) of the traffic flow-signal scheme database; the signal lamp timing scheme comprises a required period duration, a total effective green lamp duration, a green lamp duration of each sequence, a scheme optimal time interval and a scheme pre-selection judgment condition in the timing scheme.
S4, carrying out rule judgment on the real-time traffic flow in any time interval, and matching an optimal signal lamp timing scheme in the next time interval; the method comprises the following specific steps:
s401, setting an interval range (interval), preferably 15 minutes, and summarizing and counting the traffic flow of the current time interval from a flow table (car _ flow) of a traffic flow-signal scheme database according to lanes;
s402, calculating the congestion coefficient TPI of the current lane: summarizing the traffic flow according to the redefined lane classification in the step S2, counting the real-time vehicle passing number of each lane, the passing direction of the vehicle, the traffic light proportion of the lane and the speed limit condition of the lane, and calculating the congestion coefficient of the lane; as shown in the attached figure 2, the specific steps are as follows:
s40201, manufacturing a phase diagram of a four-phase sequence of the crossroad, wherein the phase diagram is respectively a sequence group I, a sequence group II, a sequence group III and a sequence group IV; the sequence group (i) comprises two lanes, and the statistical data are named as RoadName-WTE-01 and RoadName-WTE-02; the sequence group II comprises two lanes, and the counted data are named as RoadName-ETW-01 and RoadName-ETW-02; the sequence group III comprises two lanes, the counted data are named as RoadName-STN-01 and RoadName-STN-02, the sequence group IV comprises two lanes, and the counted data are named as RoadName-NTS-01 and RoadName-NTS-02; the sequence group (I) and the sequence group (II) form a relative sequence group (1), the sequence group (III) and the sequence group (IV) form a relative sequence group (2), and each relative sequence group corresponds to a standard single-phase maximum value (Std _ Uniphase _ Max _ sequence No) in a timing scheme table of a traffic flow-signal scheme database;
s40202, processing the traffic flow data of each lane counted in the step S40201 to obtain an actual single-phase maximum value (Ture _ Uniphase _ Max _ sequence No) of each relative sequence group; the calculation formula of the actual single-phase maximum value of the relative sequence group 1 is as follows:
wherein TPI-WTE represents a congestion coefficient in the west-east direction; TPI-ETW represents the congestion coefficient in the east-west direction;
the calculation formula of the actual single-phase maximum value of the relative sequence group 2 is as follows:
wherein, TPI-SN represents the congestion coefficient in the north-south direction; TPI-NS represents the congestion coefficient in the north-south direction.
S403, matching an optimal timing scheme from a timing scheme table (signal _ list) of the traffic flow-signal scheme database, and realizing the process of matching the optimal signal lamp timing scheme by adopting a dynamic programming algorithm; the dynamic programming algorithm is used for decomposing the problem into a plurality of interconnected subproblems, and solving the subproblems to obtain the solution of the original problem, wherein the solution is essentially a divide-and-conquer idea and redundancy solution; the problem transformation model diagram is analyzed by using a dynamic programming algorithm thought, as shown in the attached figure 3, and the specific steps are as follows:
s40301, dividing the problem into 3 interrelated stages according to the space characteristic according to the problem condition;
s40302, solving the solutions of all relative sequence groups by adopting the calculation formula of the step S40202, and recording the solution as S (i);
s40303, transition from one state to the next state is called state transition, and according to the problem situation, the state transition equation is:
S(i)＝(tureMIax1≤std1)∩(tureMax2≤std2)∩…∩(tureMaxi≤stdi)；
wherein, turmaxi represents the actual single-phase maximum value of the relative sequence group calculated in step S40202; stdi represents a pre-selection judgment condition of the timing scheme table (signal _ list) in step S1;
s40304, setting m signal lamp timing schemes in the traffic flow-signal scheme database, and performing the first relative sequence group comparison and then having n signal lamp timing schemes1The stripe adaptation scheme is analogized by the way that n is arranged after the t-th relative sequence group comparisontThe strip adaptation scheme, which uses dynamic programming to program the time complexity of the problem to O (m) + O (n)1)+…+O(nt) This greatly reduces the complexity of scheme matching.
S5, packaging the acquired signal lamp timing schemes into a scheme which can be identified by the annunciator platform and sending the scheme to the annunciator platform, so as to realize real-time dynamic adjustment of the traffic signal lamps at the traffic intersection; the sending record of the signal lamp timing scheme is stored in a signal scheme issuing record table (send _ record) of the traffic flow-signal scheme database, so that whether the currently issued signal lamp timing scheme is optimal or not is conveniently compared and recorded.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. The method is characterized in that a traffic signal scheme expert formulates a signal lamp timing scheme, a corresponding rule judgment value is set in each signal lamp timing scheme, and the formulated signal lamp timing scheme is stored in a traffic flow-signal scheme database; real-time traffic flow of each lane is collected through a road camera or a vehicle-mounted GPS, traffic flow data is subjected to rule analysis and judgment, and an optimal signal lamp timing scheme is matched in a traffic flow-signal scheme database by using a dynamic programming algorithm; the method comprises the following specific steps:
s1, planning and constructing a traffic flow-signal scheme database;
s2, prediction congestion coefficient: acquiring traffic flow information in real time by using a road camera or a vehicle-mounted GPS, storing the traffic flow information into a traffic flow-signal scheme database, analyzing the congestion state of the intersection according to data in the traffic flow-signal scheme database, and predicting the congestion coefficient of the intersection at the next period;
s3, the traffic signal scheme expert formulates a signal lamp timing scheme and stores the signal lamp timing scheme into a traffic flow-signal scheme database;
s4, carrying out rule judgment on the real-time traffic flow in any time interval, and matching an optimal signal lamp timing scheme in the next time interval; the method comprises the following specific steps:
s401, setting a time interval range, and summarizing and counting the traffic flow of the current time interval from a flow meter of a traffic flow-signal scheme database according to lanes;
s402, calculating the congestion coefficient TPI of the current lane: summarizing the traffic flow according to the redefined lane classification in the step S2, counting the real-time vehicle passing number of each lane, the passing direction of the vehicle, the traffic light proportion of the lane and the speed limit condition of the lane, and calculating the congestion coefficient of the lane; the method comprises the following specific steps:
s40201, manufacturing a phase diagram of a four-phase sequence of the crossroad, wherein the phase diagram is respectively a sequence group I, a sequence group II, a sequence group III and a sequence group IV; the sequence group (i) comprises two lanes, and the statistical data are named as RoadName-WTE-01 and RoadName-WTE-02; the sequence group II comprises two lanes, and the counted data are named as RoadName-ETW-01 and RoadName-ETW-02; the sequence group III comprises two lanes, the counted data are named as RoadName-STN-01 and RoadName-STN-02, the sequence group IV comprises two lanes, and the counted data are named as RoadName-NTS-01 and RoadName-NTS-02; the sequence group I and the sequence group II form a relative sequence group 1, the sequence group III and the sequence group IV form a relative sequence group 2, and each relative sequence group corresponds to a standard single-phase maximum value in a timing scheme table of a traffic flow-signal scheme database;
s40202, processing the traffic flow data of each lane counted in the step S40201 to obtain the actual single-phase maximum value of each relative sequence group; the calculation formula of the actual single-phase maximum value of the relative sequence group 1 is as follows:
wherein TPI-WTE represents a congestion coefficient in the west-east direction; TPI-ETW represents the congestion coefficient in the east-west direction;
the calculation formula of the actual single-phase maximum value of the relative sequence group 2 is as follows:
wherein, TPI-SN represents the congestion coefficient in the north-south direction; TPI-NS represents the congestion coefficient in the north-south direction;
s403, matching an optimal timing scheme from a timing scheme table of the traffic flow-signal scheme database, and realizing a process of matching the optimal signal lamp timing scheme by adopting a dynamic programming algorithm; the dynamic programming algorithm is used for decomposing the problem into a plurality of interconnected subproblems, and solving the subproblems to obtain the solution of the original problem, wherein the solution is essentially a divide-and-conquer idea and redundancy solution;
and S5, packaging the acquired signal lamp timing schemes into a scheme which can be identified by the annunciator platform and sending the scheme to the annunciator platform, so as to realize real-time dynamic adjustment of the traffic signal lamps at the traffic intersection.
2. The method for dynamically matching an optimal signal timing scheme based on a traffic signal controller according to claim 1, wherein the traffic flow-signal scheme database comprises a flow table, a timing scheme table and a signal scheme issuing record table;
the flow meter is used for recording the collected real-time traffic flow of each lane;
the timing scheme table is used for storing a signal lamp timing scheme;
the signal scheme issuing record table is used for recording a signal scheme issuing log.
3. The method for dynamically matching an optimal signal timing scheme based on a traffic signal controller according to claim 1, wherein the traffic flow information in the step S2 is stored in a flow table in a traffic flow-signal scheme database.
4. The method for dynamically matching an optimal signal timing scheme based on a traffic signal controller according to claim 1 or 3, wherein the step of predicting the congestion coefficient in the step S2 comprises the following steps:
s201, redefining lanes on the road junction: naming lanes according to a naming rule of intersection name, vehicle driving direction and lane number;
s202, acquiring information of traffic flow and pedestrian flow on each road in real time by using a road camera and a vehicle-mounted GPS; and (3) acquiring information by using the existing cameras on the road, and sorting out the number of lanes, the number of vehicles in each lane and the number of pedestrians waiting at the intersection.
5. The method for dynamically matching an optimal signal timing scheme based on a traffic signal controller according to claim 4, wherein the step S201 of redefining the lanes on the intersection comprises the following steps:
s20101, direction division: dividing according to the driving direction of the vehicle;
s20102, lane number definition: according to the PTV vision rule of the traffic simulation tool, when more than two lanes are on one road, the driving direction of the lanes is observed, the first lane is on the outermost side, and the lanes are named from outside to inside in sequence.
6. The method for dynamically matching an optimal signal timing scheme based on a traffic signal controller according to claim 1, wherein the traffic signal scheme expert makes a traffic light timing scheme in the step S3 and stores the timing scheme in the traffic flow-signal scheme database; the signal lamp timing scheme comprises a required period duration, a total effective green lamp duration, a green lamp duration of each sequence, a scheme optimal time interval and a scheme pre-selection judgment condition in the timing scheme.
7. The method for dynamically matching an optimal signal timing scheme based on a traffic signal controller according to claim 1, wherein the dynamic programming algorithm in step S403 is to decompose a problem into a plurality of interconnected sub-problems, and obtain a solution of an original problem by solving the sub-problems, which is substantially a divide-and-conquer idea and solves redundancy, and comprises the following specific steps:
s40301, dividing the problem into 3 interrelated stages according to the space characteristic according to the problem condition;
s40302, solving the solutions of all relative sequence groups by adopting the calculation formula of the step S40202, and recording the solution as S (i);
s40303, transition from one state to the next state is called state transition, and according to the problem situation, the state transition equation is:
S(i)＝(tureMax1≤std1)∩(tureMax2≤std2)∩…∩(tureMaxi≤stdi)；
wherein, turmaxi represents the actual single-phase maximum value of the relative sequence group calculated in step S40202; stdi represents a pre-selection judgment condition of the timing scheme table in step S1;
s40304, setting m signal lamp timing schemes in the traffic flow-signal scheme database, and performing the first relative sequence group comparison and then having n signal lamp timing schemes1The stripe adaptation scheme is analogized by the way that n is arranged after the t-th relative sequence group comparisontThe strip adaptation scheme, which uses dynamic programming to program the time complexity of the problem to O (m) + O (n)1)+…+O(nt)。
8. The method for dynamically matching an optimal signal timing scheme based on a traffic signal controller according to claim 1, wherein the sending record of the signal light timing scheme in the step S5 is stored in a signal scheme issuing record table of a traffic flow-signal scheme database, so as to compare and record whether the currently issued signal light timing scheme is optimal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910552516.XA CN110111592B (en) | 2019-06-25 | 2019-06-25 | Method for dynamically matching optimal signal timing scheme based on traffic signal controller |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910552516.XA CN110111592B (en) | 2019-06-25 | 2019-06-25 | Method for dynamically matching optimal signal timing scheme based on traffic signal controller |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110111592A CN110111592A (en) | 2019-08-09 |
| CN110111592B true CN110111592B (en) | 2021-10-22 |
Family
ID=67495884
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910552516.XA Active CN110111592B (en) | 2019-06-25 | 2019-06-25 | Method for dynamically matching optimal signal timing scheme based on traffic signal controller |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110111592B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110930739A (en) * | 2019-11-14 | 2020-03-27 | 佛山科学技术学院 | Intelligent traffic signal lamp control system based on big data |
| CN111768638A (en) * | 2020-05-25 | 2020-10-13 | 同济大学 | Lane distribution method for single-point signalized intersection |
| CN112150800A (en) * | 2020-08-19 | 2020-12-29 | 上海图丽信息技术有限公司 | Method for maximizing road passing efficiency under multi-source data perception |
| CN111932894A (en) * | 2020-09-09 | 2020-11-13 | 安徽庐峰交通工程有限公司 | Multifunctional integrated road traffic signal system |
| CN113223303B (en) * | 2021-05-18 | 2023-09-26 | 华路易云科技有限公司 | Road traffic double-core signal controller and control system with same |
| CN113538938B (en) * | 2021-08-04 | 2022-04-29 | 深圳英飞拓科技股份有限公司 | Intelligent traffic monitoring method and device, computer equipment and storage medium |
| CN114550447A (en) * | 2022-02-09 | 2022-05-27 | 重庆长安汽车股份有限公司 | System and method for obtaining intersection information to realize real-time traffic light scheduling |
| CN114333361B (en) * | 2022-02-22 | 2022-06-28 | 南京慧尔视智能科技有限公司 | Signal lamp timing method and device |
| CN115798231A (en) * | 2022-10-17 | 2023-03-14 | 浪潮思科网络科技有限公司 | Traffic signal lamp control method, equipment and medium |
| CN116229740B (en) * | 2023-05-10 | 2023-10-10 | 湖北大学 | Traffic light timing control method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5444442A (en) * | 1992-11-05 | 1995-08-22 | Matsushita Electric Industrial Co., Ltd. | Method for predicting traffic space mean speed and traffic flow rate, and method and apparatus for controlling isolated traffic light signaling system through predicted traffic flow rate |
| CN104332058A (en) * | 2013-07-31 | 2015-02-04 | 南通大学 | Intelligent traffic light controlling method and system |
| CN104933876A (en) * | 2015-06-03 | 2015-09-23 | 浙江师范大学 | Control method of self-adaptive smart city intelligent traffic signals |
| CN105070073A (en) * | 2015-07-23 | 2015-11-18 | 合肥革绿信息科技有限公司 | Geomagnetism-based region self-optimization signal control method and device |
| CN108389403A (en) * | 2018-04-23 | 2018-08-10 | 白冰 | The traffic lights and speed(-)limit sign intelligent adjusting method captured based on vehicle flowrate |
-
2019
- 2019-06-25 CN CN201910552516.XA patent/CN110111592B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5444442A (en) * | 1992-11-05 | 1995-08-22 | Matsushita Electric Industrial Co., Ltd. | Method for predicting traffic space mean speed and traffic flow rate, and method and apparatus for controlling isolated traffic light signaling system through predicted traffic flow rate |
| CN104332058A (en) * | 2013-07-31 | 2015-02-04 | 南通大学 | Intelligent traffic light controlling method and system |
| CN104933876A (en) * | 2015-06-03 | 2015-09-23 | 浙江师范大学 | Control method of self-adaptive smart city intelligent traffic signals |
| CN105070073A (en) * | 2015-07-23 | 2015-11-18 | 合肥革绿信息科技有限公司 | Geomagnetism-based region self-optimization signal control method and device |
| CN108389403A (en) * | 2018-04-23 | 2018-08-10 | 白冰 | The traffic lights and speed(-)limit sign intelligent adjusting method captured based on vehicle flowrate |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110111592A (en) | 2019-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110111592B (en) | Method for dynamically matching optimal signal timing scheme based on traffic signal controller | |
| CN106297291B (en) | Urban expressway traffic information acquisition system | |
| CN110570658B (en) | Method for identifying and analyzing abnormal vehicle track at intersection based on hierarchical clustering | |
| CN106781592B (en) | A kind of traffic navigation system and method based on big data | |
| CN110349407B (en) | Regional traffic signal lamp control system and method based on deep learning | |
| CN104318324B (en) | Shuttle Bus website and route planning method based on taxi GPS records | |
| CN109191872B (en) | Intersection traffic flow characteristic parameter extraction method based on number plate data | |
| CN110969871B (en) | Intelligent traffic light control system and control method | |
| CN111951549B (en) | Self-adaptive traffic signal lamp control method and system in networked vehicle environment | |
| CN108417057A (en) | A kind of intelligent signal lamp timing system | |
| CN108389406B (en) | Automatic division method for signal control time interval | |
| CN108171998B (en) | Intersection self-adaptive traffic signal control system based on electric alarm data and working method thereof | |
| CN110379169B (en) | Saturated headway calculation method for lane to be transferred based on video number plate equipment | |
| CN109887289A (en) | A kind of network vehicle flowrate maximization approach of urban traffic network model | |
| CN112820108A (en) | Self-learning road network traffic state analysis and prediction method | |
| CN205665896U (en) | Intersection signal lamp state recognition device | |
| CN102024330A (en) | Intelligent traffic signal control system, method and equipment based on high-definition video technology | |
| CN109410574A (en) | A kind of timing parameter optimization method towards stage-phase signal control program | |
| CN109816978B (en) | Regional group traffic guidance system and method considering dynamic response behaviors of drivers | |
| CN109697867A (en) | A kind of traffic control method and system based on deep learning | |
| CN107665583B (en) | Method for calculating lane saturation flow rate under different weather conditions | |
| CN101540101A (en) | Method and system for detecting road traffic incidents | |
| CN111524345B (en) | Induction control method for multi-objective optimization under constraint of real-time queuing length of vehicle | |
| CN102024331A (en) | Intelligent traffic signal control system | |
| CN109584564B (en) | Method, system and device for implementing and optimizing multi-device communication control scheme |
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 | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210924 Address after: 271000 Langchao science and Technology Park, 527 Dongyue street, Tai'an City, Shandong Province Applicant after: INSPUR SOFTWARE Co.,Ltd. Address before: 250100 Ji'nan hi tech Zone No. 2877, Shandong Province Applicant before: INSPUR GROUP Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |