CN113380044B - Overflow control signal optimization method and device and storage medium - Google Patents
Overflow control signal optimization method and device and storage medium Download PDFInfo
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- CN113380044B CN113380044B CN202110923894.1A CN202110923894A CN113380044B CN 113380044 B CN113380044 B CN 113380044B CN 202110923894 A CN202110923894 A CN 202110923894A CN 113380044 B CN113380044 B CN 113380044B
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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Abstract
The invention provides an overflow control signal optimization method, an overflow control signal optimization device and a storage medium, wherein the method comprises the following steps: acquiring vehicle data and road network data in each intersection entrance road in a calibration area; judging whether queuing overflow or overflow risk exists at each intersection entrance road according to the vehicle data, and determining an overflow road section according to the judgment result; screening paths associated with the overflow path sections in the path set of the calibration area to obtain overflow paths, and screening existing sub-areas associated with the overflow paths in the sub-area set of the calibration area to obtain an overflow-preventing area; establishing a relationship between intersections according to the control type and road network data of each intersection in a preset anti-overflow area, and establishing a storage and forwarding model for each intersection in the anti-overflow area according to the relationship between intersections and preset signal timing data; and solving each store-and-forward model to obtain the control parameters of each intersection. The technical scheme of the invention can effectively solve the traffic overflow problem.
Description
Technical Field
The invention relates to the technical field of traffic control, in particular to an overflow control signal optimization method, an overflow control signal optimization device and a storage medium.
Background
Traffic overflow refers to a traffic phenomenon that vehicles on a road section queue beyond the length of the road section due to the bottleneck effect of a downstream intersection, so that part of the vehicles occupy an upstream intersection. After traffic overflow occurs, if the diversion is not performed in time, the congestion phenomenon will spread from a single intersection to the periphery, and large-area traffic paralysis will occur in the road network.
At present, the problem of traffic overflow is solved by manually dredging or controlling an intersection signal lamp. On the one hand, however, manual dredging is time-consuming and labor-consuming, and the dredging effect is poor. On the other hand, the existing intersection signal lamp control method only controls the individual intersection control signals, and cannot solve the problem of large-range traffic overflow.
Disclosure of Invention
The invention solves the problem of how to improve the capability of solving the traffic overflow problem.
In order to solve the problems, the invention provides an overflow control signal optimization method, an overflow control signal optimization device and a storage medium.
In a first aspect, the present invention provides an overflow control signal optimization method, including:
and acquiring vehicle data and road network data in each intersection entrance road in the calibration area.
And judging whether each intersection entrance lane is queued to overflow or has overflow risk according to the vehicle data, and determining an overflow road section according to a judgment result.
Screening the paths associated with the overflow path sections in the path set of the calibration area to obtain overflow paths, and screening the existing sub-areas associated with the overflow paths in the sub-area set of the calibration area to obtain overflow-preventing areas.
And establishing a relationship between intersections according to the preset control type of each intersection in the anti-overflow area and the road network data, and establishing a storage and forwarding model for each intersection in the anti-overflow area according to the relationship between intersections and preset signal timing data.
And solving each store-and-forward model by adopting a genetic algorithm to obtain the control parameters of each intersection.
Optionally, the vehicle data includes a vehicle queue length of each intersection entrance lane obtained by performing real-time online traffic simulation on the calibration area.
The judging whether each intersection approach is queued to overflow or has overflow risks according to the vehicle data, and the determining the overflow road section according to the judging result comprises the following steps:
for any intersection entrance lane, comparing the difference value between the length of the intersection entrance lane and the corresponding vehicle queuing length with a first preset threshold value;
when the difference value is smaller than or equal to the first preset threshold value, the inlet lane is indicated to be in queue overflow or overflow risks exist, and the intersection inlet lane is determined to be the overflow road section.
Optionally, the vehicle data includes vehicle data detected by vehicle detection devices disposed on respective intersection approach roads, wherein for any one of the intersections, the vehicle detection devices are disposed on the respective corresponding intersection approach road at a calibrated distance from the intersection.
The judging whether each intersection approach is queued to overflow or has overflow risks according to the vehicle data, and the determining the overflow road section according to the judging result comprises the following steps:
for any intersection entrance lane, when the corresponding vehicle detection device detects the vehicle data and the corresponding intersection entrance lane is continuously at least calibrated for a long time, the intersection entrance lane where the vehicle detection device is located is indicated to be in queue overflow or has overflow risk, and the intersection entrance lane is determined to be the overflow road section.
Optionally, after obtaining the overflow path, the method further comprises:
acquiring the length of a road section between every two adjacent intersections in the overflow path, and comparing the length of the road section with a first preset threshold value;
when the length of the road section is greater than or equal to the first preset threshold value, disconnecting the overflow path from the middle of the two intersections to form two new overflow paths;
and filtering out paths which do not comprise the overflow road section in all the overflow paths.
Optionally, after obtaining the overflow path, the method further comprises:
acquiring the flow of each overflow path, and calculating the average flow value according to the flow of all the overflow paths;
and comparing the flow of each overflow path with the average flow, and screening the overflow paths of which the flow is greater than or equal to the average flow according to the comparison result.
Optionally, after the spill prevention zone is obtained, the method further comprises:
acquiring the traffic state of the calibration area in the current time period, and generating a new subarea according to the traffic state;
screening out new sub-areas associated with the overflow path from all the new sub-areas generated;
judging whether the screened existing sub-areas and the screened new sub-areas have intersections or not, merging the existing sub-areas and the new sub-areas with the intersections according to a judgment result, and updating the anti-overflow area.
Optionally, the establishing of the intersection relationship according to the preset control type of each intersection in the anti-overflow area and the road network data includes:
judging whether a control subarea with separated space exists in the anti-overflow area or not according to the road network data;
and if the intersection data exist, establishing the inter-intersection relation in each control subarea according to the road network data and the control type of each intersection for each control subarea.
Optionally, the constructing a store-and-forward model according to the intersection relationship and preset signal timing data includes:
and for any intersection entrance lane in the control subarea, constructing a storage and forwarding model based on steering according to the signal timing data and the intersection relation, wherein an objective function of the storage and forwarding model comprises a minimum two-norm value of a queuing ratio of the intersection entrance lane.
Optionally, the constraints of the store-and-forward model include:
the signal period and the phase structure of the intersection where the intersection entrance lane is located are kept unchanged; releasing vehicles in the intersection entrance lane only when the intersection entrance lane is at a green light in each signal period; the number of vehicles flowing out of the intersection entrance lane does not exceed the maximum outflow at the intersection entrance lane saturation flow rate; the number of the vehicles flowing out of the intersection entrance road does not exceed the required quantity; outflow from the same exit lane of the intersection does not exceed the downstream capacity of the intersection; the number of vehicles flowing into the intersection approach lane is equal to the sum of the number of vehicles flowing out of all upstream intersections into the intersection approach lane; and the number of the queued vehicles at the intersection entrance lane is equal to the sum of the number of the queued vehicles in the previous period and the number of the vehicles flowing in the current period, and the number of the vehicles flowing out in the current period is subtracted.
Optionally, the solving each store-and-forward model by using a genetic algorithm includes:
and performing iterative search on the control parameters of each intersection under the given constraint condition by taking the optimal objective function as a convergence condition.
In a second aspect, the present invention provides an overflow control signal optimizing device, comprising:
and the acquisition module is used for acquiring vehicle data and road network data in each intersection entrance road in the calibration area.
And the judging module is used for judging whether each intersection entrance lane is in queuing overflow or has overflow risk according to the vehicle data and determining an overflow road section according to the judgment result.
And the screening module is used for screening the paths associated with the overflow road sections in the path set of the calibration area to obtain overflow paths, and screening the existing sub-areas associated with the overflow paths in the sub-area set of the calibration area to obtain an overflow-preventing area.
And the construction module is used for establishing the relationship between intersections according to the preset control type of each intersection in the anti-overflow area and the road network data, and constructing a storage and forwarding model aiming at each intersection in the anti-overflow area according to the relationship between intersections and preset signal timing data.
And the analysis module is used for solving each store-and-forward model by adopting a genetic algorithm to obtain the control parameters of each intersection.
In a third aspect, the present invention provides an overflow control signal optimization device, comprising a storage medium and a processor;
the storage medium for storing a computer program;
the processor is configured to implement the overflow prevention control signal optimization method as described above when executing the computer program.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the overflow control signal optimization method as described above.
The overflow prevention control signal optimization method, the overflow prevention control signal optimization device and the storage medium have the beneficial effects that: according to the vehicle data in each intersection entrance lane, whether queuing overflow occurs or overflow risks exist in each intersection entrance lane is judged, the vehicle data can be obtained through real-time online traffic simulation, traffic dispersion can be timely carried out when the overflow risks exist or queuing overflow just occurs, and further deterioration of traffic conditions is avoided. Searching a path including the overflow road section in a path set in the calibration area according to the overflow road section, then searching a related sub-area in a sub-area set of the calibration area according to the searched path to obtain an anti-overflow area, wherein the calibration area is a preset control area, and an area which has strong relevance with the current overflow road section in the calibration area can be found through screening. The method comprises the steps of establishing a relation among intersections in an anti-overflow area according to road network data, for example, determining a connection relation among the intersections, and the like, establishing a store-and-forward model of each intersection according to the relation among the intersections and preset signal timing data, for example, respectively modeling according to traffic flow directions and the like among the intersections, and solving the store-and-forward model of each intersection in the anti-overflow area by using a genetic algorithm to obtain control parameters of each intersection. According to the technical scheme, the overflow-preventing area with strong relevance to the overflow road section is found according to the upward tracing of the overflow road section with queuing overflow or overflow risk, the control parameters of each intersection in the overflow-preventing area are integrally optimized, the coupling influence among a plurality of intersections caused by optimizing a single intersection is avoided, and the traffic overflow dredging effect is improved.
Drawings
Fig. 1 is a schematic flow chart of an overflow control signal optimization method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an overflow control signal optimization device according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
The traffic network consists of intersections and road sections, and for two adjacent intersections in the traffic flow direction, the intersection which is positioned in the front of the traffic flow direction is a downstream intersection, and the intersection which is positioned in the back of the traffic flow direction is an upstream intersection. The intersection includes an entrance lane, which is a lane where vehicles flow into the intersection, and an exit lane, which is a lane where vehicles flow out of the intersection. Each inlet passage corresponds to a vehicle steering indication, including left turn, straight run, right turn, and the like, namely the types of the inlet passages include a left turn inlet passage, a straight run inlet passage, a right turn inlet passage, and the like.
As shown in fig. 1, an overflow control signal optimization method provided by an embodiment of the present invention includes:
and step S110, acquiring vehicle data and road network data in each intersection approach road in the calibration area.
Specifically, the calibration area comprises at least one intersection, each intersection comprises at least three entrance roads, and vehicle data in each entrance road of each intersection and road network data of the calibration area are obtained.
And step S120, judging whether each intersection entrance lane generates queuing overflow or has overflow risk according to the vehicle data, and determining an overflow road section according to the judgment result.
Step S130, screening the paths associated with the overflow path sections in the path set of the calibration area to obtain overflow paths, and screening the existing sub-areas associated with the overflow paths in the sub-area set of the calibration area to obtain overflow-preventing areas.
Specifically, the path set includes all paths within the calibration region, and the sub-region set includes all existing sub-regions within the calibration region. The path of the calibration area can be obtained by carrying out traffic simulation on the calibration area, the path including the overflow road section is screened out from the path set, and the screened path is the overflow path. The sub-areas of the calibration area can be obtained by dividing the calibration area in advance, the existing sub-areas comprising the overflow paths are screened out from the sub-area set, and the screened existing sub-areas are the overflow-preventing areas.
And step S140, establishing a relationship between intersections according to the preset control type of each intersection in the anti-overflow area and the road network data, and establishing a store-and-forward model for each intersection in the anti-overflow area according to the relationship between intersections and preset signal timing data.
Specifically, the control types of the intersections include area coordination control and single-point control, the area coordination control indicates that the intersections are uniformly controlled with other intersections, the single-point control indicates that the intersections need to be controlled individually, and the relationships among the intersections are established for the intersections of which the control types are area coordination control in the anti-overflow area.
And S150, solving the store-and-forward model by adopting a genetic algorithm to obtain the control parameters of each intersection.
In the embodiment, whether queuing overflow occurs or overflow risks exist in each intersection entrance lane is judged according to the vehicle data in each intersection entrance lane, the vehicle data can be obtained through real-time online traffic simulation, traffic dispersion can be timely carried out when the overflow risks exist or queuing overflow just occurs, and further deterioration of traffic conditions is avoided. Searching a path including the overflow road section in a path set in the calibration area according to the overflow road section, then searching a related sub-area in a sub-area set of the calibration area according to the searched path to obtain an anti-overflow area, wherein the calibration area is a preset control area, and an area which has strong relevance with the current overflow road section in the calibration area can be found through screening. The method comprises the steps of establishing a relation among intersections in an anti-overflow area according to road network data, for example, determining a connection relation among the intersections, and the like, establishing a store-and-forward model of each intersection according to the relation among the intersections and preset signal timing data, for example, respectively modeling according to traffic flow directions and the like among the intersections, and solving the store-and-forward model of each intersection in the anti-overflow area by using a genetic algorithm to obtain control parameters of each intersection. According to the technical scheme, the overflow-preventing area with strong relevance to the overflow road section is found according to the upward tracing of the overflow road section with queuing overflow or overflow risk, the control parameters of each intersection in the overflow-preventing area are integrally optimized, the coupling influence among a plurality of intersections caused by optimizing a single intersection is avoided, and the traffic overflow dredging effect is improved.
Optionally, the vehicle data includes a vehicle queue length of each intersection entrance lane obtained by performing real-time online traffic simulation on the calibration area.
Specifically, the simulation verification data of the previous time slice or the simulation prediction data of the current time slice can be obtained, and the simulation verification data and the simulation prediction data both include the vehicle queue length in each intersection entrance lane of the current time slice.
In the optional embodiment, the vehicle data of the intersection entrance lane is simulated through real-time online traffic simulation, detection equipment does not need to be additionally arranged, simplicity and high efficiency are achieved, and cost can be saved.
The judging whether each intersection approach is queued to overflow or has overflow risks according to the vehicle data, and the determining the overflow road section according to the judging result comprises the following steps:
and for any intersection entrance lane, comparing the difference value between the length of the intersection entrance lane and the corresponding vehicle queuing length with a first preset threshold value.
When the difference value is smaller than or equal to the first preset threshold value, the inlet lane is indicated to be in queue overflow or overflow risks exist, and the intersection inlet lane is determined to be the overflow road section.
Specifically, assuming that the first preset threshold is 15 meters, when the length of an intersection entrance lane, namely the queuing length of vehicles in the entrance lane, is less than or equal to 15, it is determined that queuing overflow occurs or overflow risk exists in the intersection entrance lane, and the intersection entrance lane is determined to be an overflow road section, and the difference is an absolute difference.
In this optional embodiment, the difference between the length of the intersection entrance lane and the corresponding vehicle queuing length is compared with a first preset threshold, the first preset threshold may be specifically set according to an actual situation, and according to a comparison result, it may be quickly determined whether queuing overflow has occurred or whether queuing overflow has not occurred but overflow risk exists, for example, if the first preset threshold is 0, if the difference is greater than 0, it indicates that queuing overflow has not occurred, and if the difference is less than 0, it indicates that queuing overflow has occurred, which is simple and convenient.
Optionally, the vehicle data includes vehicle data detected by vehicle detection devices disposed on respective intersection approach roads, wherein for any one of the intersections, the vehicle detection devices are disposed on the respective corresponding intersection approach road at a calibrated distance from the intersection.
Specifically, vehicle detection equipment is arranged on each intersection entrance lane at a calibration distance from the intersection in advance, the calibration distance can be specifically set according to actual conditions, for example, assuming that the calibration distance is 50 meters, for each intersection, vehicle detection equipment is arranged on each left-turn entrance lane, straight-going entrance lane and right-turn entrance lane at a distance of 50 meters from the intersection, and the vehicle detection equipment can comprise section flow detection equipment such as a ground coil, geomagnetic and microwave radar and vehicle identity sensing detection equipment such as an electric alarm, a bayonet and an RFID.
The judging whether each intersection approach is queued to overflow or has overflow risks according to the vehicle data, and the determining the overflow road section according to the judging result comprises the following steps:
for any intersection entrance lane, when the corresponding vehicle detection device detects the vehicle data and the corresponding intersection entrance lane is continuously at least calibrated for a long time, the intersection entrance lane where the vehicle detection device is located is indicated to be in queue overflow or has overflow risk, and the intersection entrance lane is determined to be the overflow road section.
Specifically, assuming that the calibration time is 3 minutes, if the vehicle detection device continuously detects the vehicle data for 3 minutes or longer without interruption in the middle, it is considered that the intersection entrance lane where the vehicle detection device is located is in queue overflow or has overflow risk.
In the optional embodiment, whether queuing overflow or overflow risk exists at the intersection entrance road is judged according to the vehicle data detected by the vehicle detection device, so that the accuracy is higher.
Optionally, after obtaining the overflow path, the method further comprises:
acquiring the length of a road section between every two adjacent intersections in the overflow path, and comparing the length of the road section with a first preset threshold value;
and when the length of the road section is greater than or equal to the first preset threshold value, disconnecting the overflow path from the middle of the two intersections to form two new overflow paths.
And filtering out paths which do not comprise the overflow road section in all the overflow paths.
Specifically, each overflow path p is represented by the intersections and their turns arranged in order, i.e.: p = { S1, S2, …, Si, … and SI }, wherein I is the serial number of the intersection, I is more than or equal to 1 and less than or equal to I, I is the number of the intersection, and Si represents the turn of the ith intersection.
If F1(Si, Si +1) =0 in path p = { S1, S2, …, Si, …, Si }, split path p is path { S1, S2, …, Si } and path { Si +1, Si +2, …, Si }, wherein,
the first preset threshold may be set according to actual conditions, and preferably, may be set to 1000 meters.
In this optional embodiment, when the road section between two adjacent intersections is long, for example, greater than the first preset threshold, it indicates that the road section has sufficient vehicle storage space, and it is not easy to queue and overflow, and the correlation between the control signal of the upstream intersection and the overflow road section is weak, and by splitting and filtering the overflow path, a path with strong correlation with the overflow road section can be obtained, so that the processing amount is reduced, and the processing speed is improved.
Optionally, after obtaining the overflow path, the method further comprises:
and acquiring the flow of each overflow path, and calculating the average flow value according to the flow of all the overflow paths.
And comparing the flow of each overflow path with the average flow, and screening the overflow paths of which the flow is greater than or equal to the average flow according to the comparison result.
Specifically, because there may be a plurality of overflow paths with similar flows passing through the same overflow section, the difference between the flows of these overflow paths is small, if a preset threshold value is adopted for screening, the overflow paths are all filtered out due to an excessively large preset threshold value, and a plurality of paths with low flow ratios are left after screening due to an excessively small preset threshold value.
In this optional embodiment, the overflow paths are screened by using the average flow value of each overflow path, and a path having strong correlation with the overflow section can be found in all the overflow paths, so that the overflow control is performed in a targeted manner, and a path having weak correlation is filtered, so that the processing amount can be reduced, and the processing speed can be increased.
Optionally, after the spill prevention zone is obtained, the method further comprises:
and acquiring the traffic state of the calibration area in the current time period, and generating a new subarea according to the traffic state.
And screening out new subareas associated with the overflow path from all the generated new subareas.
Judging whether the screened existing sub-areas and the screened new sub-areas have intersections or not, merging the existing sub-areas and the new sub-areas with the intersections according to a judgment result, and updating the anti-overflow area.
Specifically, for an area, the traffic state of the area changes with time, in order to avoid the influence of random fluctuation of the traffic flow, the subareas are divided again at intervals, and a subarea division algorithm can be adopted to divide the calibration area according to the traffic state to generate new subareas. The sub-region division algorithm is the prior art and is not described herein.
The generated new sub-area is valid for the whole control period, which should not be set too short in order for the surface sub-area to end without completing the transition, preferably the control period may be set to 60 min.
In this optional embodiment, in all the new sub-areas generated according to the current traffic state, the new sub-area associated with the overflow path is screened out, the new sub-area and the existing sub-area having the association are merged, the overflow prevention area is updated in real time in the time dimension, the influence of the traffic state change on the overflow prevention control can be avoided, and the accuracy of the overflow prevention control is improved.
Optionally, the establishing of the intersection relationship according to the preset control type of each intersection in the anti-overflow area and the road network data includes:
and judging whether a spatially separated control subarea exists in the anti-overflow area or not according to the road network data.
And if the intersection data exist, establishing the inter-intersection relation in each control subarea according to the road network data and the control type of each intersection for each control subarea.
Specifically, the road network data includes road network connection relations, and whether spatially separated control subregions exist is determined according to the road network connection relations. Since the spill-proof zone comprises a plurality of partial zones associated with the overflow path, there may also be more than one overflow path, so that there may be a plurality of control partial zones which are not connected to one another. For example, the spill-proof area comprises two sub-areas a and B, a comprises an overflow path a, B comprises an overflow path B, and there is no intersection between a and B, then a and B are two spatially separated control sub-areas. If present, each control sub-area may be treated separately.
Optionally, the constructing a store-and-forward model according to the intersection relationship and preset signal timing data includes:
and for any intersection entrance lane in the control subarea, constructing a storage and forwarding model based on steering according to the signal timing data and the intersection relation, wherein an objective function of the storage and forwarding model comprises a minimum two-norm value of a queuing ratio of the intersection entrance lane.
Optionally, the constraints of the store-and-forward model include:
the signal period and the phase structure of the intersection where the intersection entrance lane is located are kept unchanged; releasing vehicles in the intersection entrance lane only when the intersection entrance lane is at a green light in each signal period; the number of vehicles flowing out of the intersection entrance lane does not exceed the maximum outflow under the saturated flow rate; the number of the vehicles flowing out of the intersection entrance road does not exceed the required quantity; the outflow of the same exit lane of the intersection does not exceed the downstream capacity of the intersection; the number of vehicles flowing into the intersection approach lane is equal to the sum of the number of vehicles flowing out of all upstream intersections into the intersection approach lane; and the number of the vehicles in the turn queue at the intersection entrance lane is equal to the sum of the number of the vehicles in the queue in the previous period and the number of the vehicles flowing in the current period, and the number of the vehicles flowing out in the current period is subtracted.
In particular, for any intersection
Inlet channel of
The signal timing data includes fixed variables and state variables as shown in tables one and two.
Fixed variables in table-signal timing data
State variables in table two signal timing data
The control variables include: crossing point
Time of phase
。
The control parameters include: controlling duration
Control scheme update interval
。
The global variables include: absolute time
Control step length
Maximum value
。
Settable intersection
The signal of (2) is adjusted in amplitude per cycle
The inlet passage thereof
Queue reduction factor of
。
The constraints of the store-and-forward model include:
(1) because the cycle start times are not consistent, the current time may be at any time within the signal cycle, and thus the current cycle is maintained unchanged.
(2) The phase structure is kept unchanged.
(3) For crossing
Inlet channel of
In the inlet duct only
The vehicle was released when on the green light.
Inlet channel
Time of starting traffic flow
，
Inlet channel
End time of traffic flow
，
(4) For crossing
Inlet channel of
The vehicle outflow does not exceed the maximum outflow at the saturation flow rate.
(5) For crossing
Inlet channel of
The vehicle outflow does not exceed the demand.
Demand is inlet channel
The sum of the vehicle inflow and the number of vehicles in line for the current cycle.
(6) For crossing
And the vehicle outflow of the same outlet channel does not exceed the downstream flow.
When in use
When the constraint (4) is equal, when
When the constraint (5) is equal, when
Then, constraint (6) is taken, etc. At least one of the above three constraints is equal, thus
。
(7) For crossing
Inlet channel of
The number of vehicles flowing in is equal to the number of vehicles flowing out from the upstream crossing to the entrance lane
The sum of the number of vehicles (c).
(8) For crossing
Inlet channel of
The number of vehicles in line is equal to the number of vehicles in line in the last cycle + the number of vehicles flowing into the current cycle-the number of vehicles flowing out of the current cycle.
The objective function of the store-and-forward model includes:
In this optional embodiment, for any intersection entrance lane in the control sub-area, a storage-forwarding model based on steering is constructed according to the signal timing data and the intersection-to-intersection relationship, so that the anti-overflow control of the steering stage can be realized, and each steering entrance lane of each intersection is used as a control unit, thereby improving the anti-overflow control accuracy.
Optionally, the solving each store-and-forward model by using a genetic algorithm includes:
and performing iterative search on the control parameters of each intersection under the given constraint condition by taking the optimal objective function as a convergence condition.
Specifically, for the control subarea, intersection samples in the control subarea are generated based on a genetic algorithm, for each sample, the maximum queue of each intersection in each period is calculated according to the store-and-forward model of each intersection, the average maximum queue and the standard deviation thereof in the control subarea are further calculated, and iteration is performed by minimizing the maximum queue in one standard deviation. The control parameters include phase time and phase difference.
In the optional embodiment, the phase difference is introduced as an optimization variable, the phase difference of each intersection in the anti-overflow area is solved through a genetic algorithm, the anti-overflow control of the whole anti-overflow area can be realized, the anti-overflow control is performed on the anti-overflow area in comparison with the independent control of each intersection, the coupling influence between a plurality of intersections caused by the fact that a single intersection is controlled respectively can be avoided, and the traffic overflow problem solving effect is improved.
As shown in fig. 2, an overflow control signal optimizing device provided by an embodiment of the present invention includes:
and the acquisition module is used for acquiring vehicle data and road network data in each intersection entrance road in the calibration area.
And the judging module is used for judging whether each intersection entrance lane is in queuing overflow or has overflow risk according to the vehicle data and determining an overflow road section according to the judgment result.
And the screening module is used for screening the paths associated with the overflow road sections in the path set of the calibration area to obtain overflow paths, and screening the existing sub-areas associated with the overflow paths in the sub-area set of the calibration area to obtain an overflow-preventing area.
And the construction module is used for establishing the relationship between intersections according to the preset control type of each intersection in the anti-overflow area and the road network data, and constructing a storage and forwarding model aiming at each intersection in the anti-overflow area according to the relationship between intersections and preset signal timing data.
And the analysis module is used for solving each store-and-forward model by adopting a genetic algorithm to obtain the control parameters of each intersection.
Another embodiment of the present invention provides an overflow control signal optimizing device comprising a storage medium and a processor; the storage medium for storing a computer program; the processor is configured to implement the overflow prevention control signal optimization method as described above when executing the computer program. The device may comprise a computer, a server, etc.
A further embodiment of the invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the overflow control signal optimization method as described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like. In this application, the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
Although the present disclosure has been described above, the scope of the present disclosure is not limited thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present disclosure, and these changes and modifications are intended to be within the scope of the present disclosure.
Claims (13)
1. An overflow control signal optimization method, comprising:
acquiring vehicle data and road network data in each intersection entrance road in a calibration area;
judging whether each intersection entrance lane is queued to overflow or has overflow risk according to the vehicle data, and determining an overflow road section according to a judgment result;
screening paths associated with the overflow path sections in the path set of the calibration area to obtain overflow paths, and screening existing sub-areas associated with the overflow paths in the sub-area set of the calibration area to obtain overflow-preventing areas;
establishing a relationship between intersections according to a preset control type of each intersection in the anti-overflow area and the road network data, and establishing a storage and forwarding model for each intersection in the anti-overflow area according to the relationship between intersections and preset signal timing data; the control type comprises single-point control and area coordination control, and the objective function of the storage and forwarding model comprises a minimum two-norm value of a queuing ratio of an intersection entrance lane;
and solving each storage and forwarding model by adopting a genetic algorithm to obtain the control parameters of each intersection.
2. The overflow control signal optimization method according to claim 1, wherein the vehicle data includes a vehicle queue length of each intersection approach obtained by performing real-time online traffic simulation on the calibration area;
the judging whether each intersection approach is queued to overflow or has overflow risks according to the vehicle data, and the determining the overflow road section according to the judging result comprises the following steps:
for any intersection entrance lane, comparing the difference value between the length of the intersection entrance lane and the corresponding vehicle queuing length with a first preset threshold value;
when the difference value is smaller than or equal to the first preset threshold value, the intersection approach is indicated to be over-queued or has an overflow risk, and the intersection approach is determined to be the overflow road section.
3. The method of claim 1, wherein the vehicle data comprises vehicle data detected by vehicle detection devices disposed on respective intersection entry lanes, wherein for any one of the intersections the vehicle detection devices are disposed on the respective intersection entry lane at a calibrated distance from the intersection;
the judging whether each intersection approach is queued to overflow or has overflow risks according to the vehicle data, and the determining the overflow road section according to the judging result comprises the following steps:
for any intersection entrance lane, when the corresponding vehicle detection device detects the vehicle data and the corresponding intersection entrance lane is continuously at least calibrated for a long time, the intersection entrance lane where the vehicle detection device is located is indicated to be in queue overflow or has overflow risk, and the intersection entrance lane is determined to be the overflow road section.
4. The overflow control signal optimization method of claim 1, further comprising, after obtaining the overflow path:
acquiring the length of a road section between every two adjacent intersections in the overflow path, and comparing the length of the road section with a first preset threshold value;
when the length of the road section is greater than or equal to the first preset threshold value, disconnecting the overflow path from the middle of the two intersections to form two new overflow paths;
and filtering out paths which do not comprise the overflow road section in all the overflow paths.
5. The overflow control signal optimization method according to any one of claims 1 to 4, further comprising, after obtaining the overflow path:
acquiring the flow of each overflow path, and calculating the average flow value according to the flow of all the overflow paths;
and comparing the flow of each overflow path with the average flow, and screening the overflow paths of which the flow is greater than or equal to the average flow according to the comparison result.
6. The overflow prevention control signal optimization method according to any one of claims 1 to 4, further comprising, after the obtaining the overflow prevention area:
acquiring the traffic state of the calibration area in the current time period, and generating a new subarea according to the traffic state;
screening out new sub-areas associated with the overflow path from all the new sub-areas generated;
judging whether the screened existing sub-areas and the screened new sub-areas have intersections or not, merging the existing sub-areas and the new sub-areas with the intersections according to a judgment result, and updating the anti-overflow area.
7. The method for optimizing the overflow prevention control signal according to any one of claims 1 to 4, wherein the establishing of the intersection-to-intersection relationship according to the preset control types of the intersections in the overflow prevention area and the road network data comprises:
judging whether a control subarea with separated space exists in the anti-overflow area or not according to the road network data;
and if the intersection data exist, establishing the inter-intersection relation in each control subarea according to the road network data and the control type of each intersection for each control subarea.
8. The method for optimizing the overflow control signal according to claim 7, wherein the constructing a store-and-forward model according to the intersection relationship and preset signal timing data comprises:
and for any intersection entrance lane in the control subarea, constructing a storage and forwarding model based on steering according to the signal timing data and the intersection relation, wherein an objective function of the storage and forwarding model comprises a minimum two-norm value of a queuing ratio of the intersection entrance lane.
9. The overflow control signal optimization method of claim 8, wherein the constraints of the store-and-forward model comprise:
the signal period and the phase structure of the intersection where the intersection entrance lane is located are kept unchanged; releasing vehicles in the intersection entrance lane only when the intersection entrance lane is at a green light in each signal period; the number of vehicles flowing out of the intersection entrance lane does not exceed the maximum outflow at the intersection entrance lane saturation flow rate; the number of the vehicles flowing out of the intersection entrance road does not exceed the required quantity; outflow from the same exit lane of the intersection does not exceed the downstream capacity of the intersection; the number of vehicles flowing into the intersection approach lane is equal to the sum of the number of vehicles flowing out of all upstream intersections into the intersection approach lane; and the number of the queued vehicles at the intersection entrance lane is equal to the sum of the number of the queued vehicles in the previous period and the number of the vehicles flowing in the current period, and the number of the vehicles flowing out in the current period is subtracted.
10. The method for optimizing an overflow control signal according to claim 9, wherein solving each of the store-and-forward models using a genetic algorithm comprises:
and performing iterative search on the control parameters of each intersection under the given constraint condition by taking the optimal objective function as a convergence condition.
11. An overflow control signal optimizing device, comprising:
the acquisition module is used for acquiring vehicle data and road network data in each intersection entrance road in the calibration area;
the judging module is used for judging whether each intersection entrance lane is in queuing overflow or has overflow risk according to the vehicle data and determining an overflow road section according to a judgment result;
the screening module is used for screening paths associated with the overflow road sections in the path set of the calibration area to obtain overflow paths, and screening existing sub-areas associated with the overflow paths in the sub-area set of the calibration area to obtain overflow-preventing areas;
the construction module is used for establishing a relationship between intersections according to the preset control type of each intersection in the anti-overflow area and the road network data, and constructing a storage and forwarding model for each intersection in the anti-overflow area according to the relationship between intersections and preset signal timing data; the control type comprises single-point control and coordination control, and the objective function of the store-and-forward model comprises a minimum two-norm value of a queuing ratio of the intersection entrance lane;
and the analysis module is used for solving each store-and-forward model by adopting a genetic algorithm to obtain the control parameters of each intersection.
12. An overflow control signal optimizing device comprising a storage medium and a processor;
the storage medium for storing a computer program;
the processor, when executing the computer program, is configured to implement the overflow control signal optimization method according to any of claims 1 to 10.
13. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the overflow control signal optimization method according to any one of claims 1 to 10.
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| CN115691172B (en) * | 2022-10-26 | 2024-04-26 | 山东理工大学 | Chain type anti-blocking control phase difference optimization method for high-load state strong-correlation intersection group |
| CN115424447A (en) * | 2022-11-04 | 2022-12-02 | 华路易云科技有限公司 | Signal control method and signal control platform supporting autonomous configuration threshold |
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