CN103559795A - Multi-strategy and multi-object self-adaptation traffic control method - Google Patents
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Abstract
The invention discloses a multi-strategy and multi-object self-adaptation traffic control method. The multi-strategy and multi-object self-adaptation traffic control method is characterized by comprising the following steps that (1), traffic state inspection equipment collects traffic flow data in real time, obtains the traffic state information and sends the traffic state information to an intersection signal machine, and the intersection signal machine uploads the traffic flow data to a signal center control system; (2), the intersection signal machine calculates the traffic intensity of an intersection, judges the traffic states of the intersection and adjusts the control plan of the current intersection in real time according to the different traffic states; (3), according to the intersection traffic flow data uploaded in real time, the signal center control system optimizes the intersection signal control scheme from the global angle of a road network. According to the control method, the road network grade global optimization self-adaptation signal control method is provided through judgment and analysis of the traffic states of the road network, and artery coordination control applicable to any traffic state is achieved.
Description
Technical field
The invention belongs to traffic automatic control technology field, specifically, relate to a kind of how tactful multiobject self-adaption traffic control method and system.
Background technology
Along with constantly riseing of city automobile recoverable amount, cause that transport need amount increases severely, yet the traffic that the road network that city reaches its maturity can provide supply is limited, imbalance of supply and demand, becomes one of inducement of urban traffic blocking; Traffic jam issue mainly concentrates on the node (grade crossing) of road network, forces and it should be noted that backward traffic control technology is also the main inducing of traffic problems.Along with the development of electronics, information and control technology and in the widespread use of transportation industry, the intelligentized traffic control technology that people are constantly making great efforts to seek by advanced person is improved traffic congestion.Wherein, the research of adaptive traffic signal control system and application, be one of intelligentized important achievement of traffic control.Adaptive traffic signal control system mainly comprises four unit: intersection signal control unit, road traffic data detection system, remote center's control module, communication unit.According to range of control, can be divided into single-point Adaptive Signal Control, main line Adaptive Signal Control, the Adaptive Signal Control of regional coordination.For single crossing single-point adaptive traffic signal control system, utilize crossing checkout equipment to obtain the traffic behavior parameter at crossing, signal timing plan at the automatic calculation optimization of crossing control module Huo remote center crossing, and download to teleseme and carry out, the control best results of single intersection of take is target; For the Trunk Road Coordination Adaptive Signal Control at a plurality of crossings, in optimization of road joints scheme, upgrade the coordination phase differential of Multiple Intersections, take that to realize that the green ripple of main line controls be target; The regional coordination adaptive control of facing area, is divided into Nei Ji sub-range, ， subarea, a plurality of traffic subarea region and coordinates to control, and the control best results of road network integral body in region of take is target.
Mainly there is following problem in existing self-adaptation control method: the adaptability 1) changing for traffic behavior is poor, lacks the detection method of the peak period congestion status that can be applicable to traffic signals control; The green ripple of single-point adaptive control, main line is controlled, demand for control that can not adaptive peak phase congestion status.2) road network with Dian,Xian Wei unit isolated be optimized control, effect of optimization is attended to one thing and lose sight of another, and is absorbed in the predicament of local optimum, causes the global optimization effect of road network poor.3), for modern city road network structure, traffic behavior, feature complicated and changeable, lacks clear and definite control target, the control strategy of system.
Based on this, how to invent a kind of how tactful multiobject self-adaption traffic control method and system, go for the system optimization method of the Arterial Coordination Control of any traffic behavior, the method is introduced affects the key parameter of Trunk Road Coordination effect (being that initial green light is queued up) modified basis phase differential, the traffic behavior of take is foundation with the corresponding relation of controlling target, providing the control method for coordinating that blocks up of main line, is the technical matters that the present invention mainly solves.
Summary of the invention
The present invention is in order to solve the problem that existing traffic control method is poor to the real-time change adaptability of traffic behavior, prioritization scheme can not be optimized for whole road network structure from the overall situation, a kind of how tactful multiobject adaptive traffic signal control system is provided, by differentiation and analysis to road network (comprising crossing, section, main line, region) traffic behavior, determine the corresponding control target of different traffic; Changing the mechanism of road network level, systematized control strategy and the control mode of foundation based on traffic state judging, provides a kind of global optimization Adaptive Signal Control method of road network level.
In order to solve the problems of the technologies described above, the present invention is achieved by the following technical solutions:
A multiobject self-adaption traffic control method, comprises the following steps:
(1), traffic behavior checkout equipment Real-time Collection traffic flow data obtains traffic state information, and transmits it to intersection annunciator, by intersection annunciator, traffic flow data is uploaded to signal center's control system;
(2), intersection annunciator calculates crossing traffic intensity according to the traffic flow data obtaining, take this traffic intensity value as condition discrimination index, the traffic behavior at judgement crossing, and automatically switch and control target according to different traffic behaviors, the control program at current crossing adjusted in real time;
(3), intersection annunciator is uploaded to signal center's control system by crossing traffic intensity simultaneously, signal center's control system is obtained road section traffic volume state, arterial traffic state and regional traffic state information according to crossing traffic flow data, the judgement of crossing traffic intensity, according to above-mentioned information, automatically switch and control target, generate real-time crossing traffic signal timing plan, and the control command of this control program is transferred to teleseme, the control program that the control program priority that described intersection annunciator generates generates lower than signal center's control system.
Further, divided lane flow, time headway, the time occupancy traffic flow data at entrance detector acquisition crossing in step (1), and transfer to intersection annunciator, outlet detector acquisition section queue length information, and transfer to intersection annunciator.Traffic flow data based on crossing entrance, outlet detects, from crossing, the traffic behavior of section, main line, the comprehensive perception road network of region various dimensions.Wherein, it is the basis that road net traffic state is differentiated that traffic state at road cross is differentiated, and usings crossing, section as the elementary cell of obtaining road grid traffic flow data, adopts traffic intensity parameter as condition discrimination index; Each traffic intensity value, characterizes the unique traffic behavior in crossing.
Further, in described step (2), if the queue length in section reaches maximum queue length L, sentencing this section is congestion status, otherwise this section is unimpeded state.
Further, in described step (2), when the positive and negative two-way green light initial queue length in the section of main line is all less than maximum queue length L, this main line is unimpeded state, otherwise this main line is congestion status.
Further, in described step (2), in region, all traffic intensities that presets key crossing all reach separately
position traffic intensity time, judge that this region is as congestion status, otherwise this region is non-congestion status,
The
the traffic intensity of position: the crossing traffic intensity of upper one week always sort the
bit data.
In described step (2), the traffic behavior at crossing comprises: unimpeded, slight crowding, crowded and serious crowded four kinds of states, when crossing is when unimpeded, take single spot optimization to control or induction control, also be that system changes according to real-time traffic intensity, the control cycle at calculation optimization crossing, optimal control in dynamic scheme.
Further, in described step (2), when crossing is in non-when unimpeded, if this place, crossing downstream road section is congestion status, bottleneck control is carried out at current crossing, and continue the congestion status in judgement section, place, until single-point optimal control, when non-congestion status, is carried out in section, place or induction is controlled.
Further, in described step (2), when crossing is in non-unimpeded, and this place, crossing downstream road section is while being non-congestion status, continues to judge whether this crossing belongs to arterial control crossing, if belong to arterial control crossing, judge that whether this main line is in congestion status, if congestion status, all crossings of main line executive system optimization-Multiple Intersections blocks up to link and controls, if non-congestion status, all crossings of main line executive system optimization-green wave coordination is controlled.
Further, in described step (2), if crossing does not belong to arterial control crossing, continue to judge whether this crossing belongs to Region control crossing, if belonging to Qie Gai region, Region control crossing is congestion status, the green time of the borderline control of constricted zone crossing control phase, carries out Current limited Control.
Further, in described step (2), described bottleneck control method is: that ends this current crossing enters downstream road section phase place green light.
Compared with prior art, advantage of the present invention and good effect are: a kind of how tactful multiobject Adaptive Signal Control method of the present invention, by differentiation and analysis to road network (crossing, section, main line, region) traffic behavior, determine the corresponding control target of different traffic; Changing the mechanism of road network level, systematized control strategy and the control mode of foundation based on traffic state judging, provides a kind of global optimization Adaptive Signal Control method of road network level; Be applicable to the Arterial Coordination Control of any traffic behavior, the method is introduced affects the key parameter of Trunk Road Coordination effect (being that initial green light is queued up) modified basis phase differential, the traffic behavior of take is foundation with the corresponding relation of controlling target, provides the control method for coordinating that blocks up of main line.
Read by reference to the accompanying drawings after the detailed description of embodiment of the present invention, it is clearer that the other features and advantages of the invention will become.
Accompanying drawing explanation
Fig. 1 is a kind of embodiment process flow diagram of the multiobject self-adaption traffic control method of many strategies proposed by the invention;
Fig. 2 is bottleneck control flow chart in section in Fig. 1;
Tu3Shi Tu1 Road mouthfeel is answered control flow chart;
Fig. 4 is single spot optimization control flow chart in crossing in Fig. 1;
Fig. 5 is arterial control system optimization process flow diagram in Fig. 1.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in more detail.
Embodiment mono-, and the present embodiment provides a kind of how tactful multiobject self-adaption traffic control method, comprises the following steps:
(1), traffic behavior checkout equipment Real-time Collection traffic flow data obtains traffic state information, and transmits it to intersection annunciator, by intersection annunciator, traffic flow data is uploaded to signal center's control system;
(2), intersection annunciator calculates crossing traffic intensity according to the traffic flow data obtaining, take this traffic intensity value as condition discrimination index, the traffic behavior at judgement crossing, and automatically switch and control target according to different traffic behaviors, the control program at current crossing adjusted in real time;
(3), intersection annunciator is uploaded to signal center's control system by crossing traffic intensity simultaneously, signal center's control system is obtained road section traffic volume state, arterial traffic state and regional traffic state information according to crossing traffic flow data, the judgement of crossing traffic intensity, according to above-mentioned information, automatically switch and control target, generate real-time crossing traffic signal timing plan, and the control command of this control program is transferred to teleseme, the control program that the control program priority that described intersection annunciator generates generates lower than signal center's control system.
Wherein, the computing method of crossing traffic intensity can adopt existing computing method, the object of the invention is to consider the traffic behavior in section, main line, region, when section, main line, region are during in congestion status, need implement to block up control for its feature separately, therefore,, for the traffic behavior in section, main line, region, only do the differentiation of non-congestion status and congestion status.Based on above-mentioned steps, the method of the present embodiment has realized including detection of dynamic and the differentiation of the multidimensional traffic behavior of crossing, section, main line, Regional Road Network, by the traffic behavior to road network various dimensions, detect and analyze, preferably control systematically target, dynamically switching control strategy and control mode, realize the overall adaptive optimization of whole road network (crossing, section, main line, region) and control.
Wherein, the system major equipment of realizing this method consists of: signal center's control system, is generally laid in traffic control center; The signal controller at crossing, hereinafter to be referred as teleseme, is laid in the crossing that needs signal controlling; Traffic behavior checkout equipment, is divided into two kinds of entrance detecting device and outlet detecting devices, is generally laid on crossing import, exit lane.
As a preferred embodiment, divided lane flow, time headway, the time occupancy traffic flow data at entrance detector acquisition crossing in step (1), and transfer to intersection annunciator, outlet detector acquisition section queue length information, and transferring to intersection annunciator, above-mentioned information is uploaded to signal center's control system by intersection annunciator.Wherein, conventional entrance detecting device comprise, Data mining device, geomagnetism detecting device, video detector, ultrasonic detector etc.Outlet detecting device can adopt overflow detector to realize, specific implementation is: the mode of obtaining section queue length information is specially: in section, far from crossing, upstream, in the middle of 0～100 meter of position, one group of (2) overflow detector is laid in a track, for detection of time occupancy, flow, velocity information: the rolling time occupation rate data according to outlet detecting device, judge whether section reaches maximum queue length.Traffic flow data based on crossing entrance, outlet detects, from crossing, the traffic behavior of section, main line, the comprehensive perception road network of region various dimensions.Wherein, it is the basis that road net traffic state is differentiated that traffic state at road cross is differentiated, and usings crossing, section as the elementary cell of obtaining road grid traffic flow data, adopts traffic intensity parameter as condition discrimination index; Each traffic intensity value, characterizes the unique traffic behavior in crossing.
In the step (2) of the present embodiment, by overflow detector, detect queue length, if the queue length in section reaches maximum queue length L, sentencing this section is congestion status, otherwise this section is unimpeded state, can certainly adopt other detection meanss to detect queue length.
In addition, in the step (2) of the present embodiment, the traffic behavior determination methods of main line is: when the positive and negative two-way green light initial queue length in the section of main line is all less than maximum queue length L, this main line is unimpeded state, otherwise this main line is congestion status.
And in the step (2) of the present embodiment, the traffic behavior determination methods in region is: in region, all traffic intensities that presets key crossing all reach separately
position traffic intensity time, judge that this region is as congestion status, otherwise this region is non-congestion status,
The
the traffic intensity of position: the bit data of the total sequence of crossing traffic intensity of upper a week.
In described step (2), when crossing is when unimpeded (being also non-congestion status), taking single spot optimization to control or induction is controlled, is also that system changes according to real-time traffic intensity, the control cycle at calculation optimization crossing, optimal control in dynamic scheme.The control target of its setting is to incur loss through delay minimum, vehicle mean delay minimum and traffic efficiency maximum with rolling stock, unimpeded unimpeded state, slight congestion status and the congestion status of comprising again, corresponding one by one with above-mentioned three kinds of control targets respectively, different according to controlling target, system is finally determined optimum control scheme, is also that single spot optimization is controlled or induction is controlled, and above-mentioned two kinds of control method prior aries solve, its process flow diagram, referring to shown in Fig. 3, Fig. 4, does not repeat them here.
Shown in Figure 1, in described step (2), when crossing is in non-when unimpeded, if this place, crossing downstream road section is congestion status, bottleneck control is carried out at current crossing, and continue the congestion status in judgement section, place, until single-point optimal control, when non-congestion status, is carried out in section, place or induction is controlled.The control object that current crossing execution bottleneck is controlled is to prevent to queue up and overflows, and reaches the technique effect that regulates this road section traffic volume state when blocking up appears in this section.Preferably, in described step (2), described bottleneck control method is: that ends this current crossing enters downstream road section phase place green light.Shown in Figure 2, end entering after downstream road section phase place green light of this current crossing, also need regularly to judge whether section state is removed, if so, recover normal control, otherwise, continue to carry out section bottleneck and control.
In described step (2), when crossing is in non-unimpeded, and this place, crossing downstream road section is while being non-congestion status, continue to judge whether this crossing belongs to arterial control crossing, if belong to arterial control crossing, judge that whether this main line is in congestion status, if the words of congestion status, the all crossings of main line executive system optimization-Multiple Intersections blocks up to link and controls, shown in Figure 5, also: when main line is congestion status, to prevent that section from queuing up, overflow, balanced each section queue length is for controlling target, by the mode of system optimization, carry out the coordination control strategy that blocks up of main line.If non-congestion status, it controls target for reducing main line stop frequency, and all crossings of main line executive system optimization-green wave coordination is controlled, and carries out the green ripple control strategy of main line by system optimization mode.
In described step (2), if crossing does not belong to arterial control crossing, continue to judge whether this crossing belongs to Region control crossing, if belong to Qie Gai region, Region control crossing, be congestion status, the green time of the borderline control of constricted zone crossing control phase, carries out Current limited Control.Under the congestion status of region, take and alleviate region and block up, prevent to queue up and overflow as target, by the control area transport need of demand control strategy, equilibrium traffic is supplied with.Under the non-congestion status in region, Region control is subordinated to crossing, section, arterial control.
In addition, also comprising that the dynamical state of the road network overall situation is differentiated and Optimization Steps, is also that road network self-adaptation is divided, and its method is: during road grid traffic is controlled, what take crossing is base control object; Take traffic subarea as basic optimal control unit.According to traffic behavior testing result, traffic subarea is merged and or fractionation adjustment.Need, according to actual site inspection result, initial division to be carried out in the optimization subarea of road network, region.Subarea initial division, divides and coordinates to control subarea according to category of roads, major flow trend etc., carries out and coordinate to control in subarea; Region initial division: the nucleus that some is easily blocked up maybe needs to adjust the region of stream to divide strategic control district into, by the split time at crossing, border, control area, alleviates the degree of blocking up in region, makes the certain unobstructed degree of driving of maintenance in region.
4) many policy control mode self-adaptation conversion
Road network status information based on the perception of traffic behavior detection module, system is adjusted control target automatically, preferred control strategy, optimization control scheme.Many tactful multi objective control mode self-adaptations are changed the mechanism.
According to preferred control strategy and control mode, optimization control scheme is also issued to teleseme execution.
Crossing control program generates and carries out
According to the crossing traffic intensity of dynamic calculation, take 5 minutes cycles as interval optimization control scheme, each phase place green time, carry out single-point optimal control; Traffic state at road cross, when free zone, also can sense that the arrival situation of vehicle is real-time according to real-time entrance detecting device, carries out induction and controls.Shown in Figure 3, induction control method, for to disclose ripe control program, is not repeating.Shown in Figure 4, single spot optimization control method, is applying for a patent, at this, is not repeating.Below only briefly introduce its green light distribution principle.
The split allocation strategy of single-point crossing is mainly according to waiting principle of traffic intensity to distribute.The distribution that refers to crossing phase place green time Deng traffic intensity principle is carried out according to the phase place traffic intensity calculating.
The control method of the present embodiment, by differentiation and analysis to road network (crossing, section, main line, region) traffic behavior, has been determined the corresponding control target of different traffic, for road network signal control strategy, formulates, and solid reference is provided; The control strategy of the road network system based on traffic state judging and changing the mechanism of control mode have been set up, the method has broken through Adaptive Signal Control can only take the local optimum drawback that point (crossing), line (main line) be unit, and a kind of global optimization Adaptive Signal Control method of road network level is provided; Simultaneously, a kind of system optimization method that is applicable to the Arterial Coordination Control of any traffic behavior has been studied in this motion, the method is introduced affects the key factor of Trunk Road Coordination effect (being that initial green light is queued up) modified basis phase differential, improved greatly and coordinated to control the adaptability changing for traffic behavior, the traffic behavior of take is foundation with the corresponding relation of controlling target, the breakthrough control method for coordinating that blocks up that puts forward main line.
Adaptive traffic signal control system in the present embodiment, the intelligent level of controlling by improving traffic signals, effectively reduces the complexity of urban traffic signal management and control, thereby has reduced the human and material resources resource input of urban transportation management and control; The dynamical state of the road network overall situation is differentiated and is optimized, and has improved the active prevention and control ability that control system is blocked up to road network, for the steady unimpeded operation of urban transportation provides powerful guarantee.
Certainly; above-mentioned explanation is not limitation of the present invention; the present invention is also not limited in above-mentioned giving an example, and the variation that those skilled in the art make in essential scope of the present invention, remodeling, interpolation or replacement, also should belong to protection scope of the present invention.
Claims (10)
1. more than, a tactful multiobject self-adaption traffic control method, is characterized in that, comprises the following steps:
(1), traffic behavior checkout equipment Real-time Collection traffic flow data obtains traffic state information, and transmits it to intersection annunciator, by intersection annunciator, traffic flow data is uploaded to signal center's control system;
(2), intersection annunciator calculates crossing traffic intensity according to the traffic flow data obtaining, take this traffic intensity value as condition discrimination index, the traffic behavior at judgement crossing, and automatically switch and control target according to different traffic behaviors, the control program at current crossing adjusted in real time;
(3), intersection annunciator is uploaded to signal center's control system by crossing traffic intensity simultaneously, signal center's control system is obtained road section traffic volume state, arterial traffic state and regional traffic state information according to crossing traffic flow data, the judgement of crossing traffic intensity, according to above-mentioned information, automatically switch and control target, generate real-time crossing traffic signal timing plan, and the control command of this control program is transferred to teleseme, the control program that the control program priority that described intersection annunciator generates generates lower than signal center's control system.
2. according to claim 1 how tactful multiobject self-adaption traffic control method, it is characterized in that, divided lane flow, time headway, the time occupancy traffic flow data at entrance detector acquisition crossing in step (1), and transfer to intersection annunciator, outlet detector acquisition section queue length information, and transfer to intersection annunciator.
3. according to claim 2 how tactful multiobject self-adaption traffic control method, is characterized in that, in described step (2), if the queue length in section reaches maximum queue length L, sentencing this section is congestion status, otherwise this section is unimpeded state.
4. according to claim 3 how tactful multiobject self-adaption traffic control method, is characterized in that, in described step (2), when the positive and negative two-way green light initial queue length in the section of main line is all less than maximum queue length L, this main line is unimpeded state, otherwise this main line is congestion status.
5. according to claim 4 how tactful multiobject self-adaption traffic control method, is characterized in that, in described step (2), in region, all traffic intensities that presets key crossing all reach separately
position traffic intensity time, judge that this region is as congestion status, otherwise this region is non-congestion status,
The
the traffic intensity of position: the crossing traffic intensity of upper one week always sort the
bit data.
6. according to claim 5 how tactful multiobject self-adaption traffic control method, it is characterized in that, in described step (2), the traffic behavior at crossing comprises: unimpeded, slight crowding, crowded and serious crowded four kinds of states, when crossing is when unimpeded, take single spot optimization to control or induction control, be also that system changes according to real-time traffic intensity, the control cycle at calculation optimization crossing, optimal control in dynamic scheme.
7. according to claim 6 how tactful multiobject self-adaption traffic control method, it is characterized in that, in described step (2), when crossing is during in non-unimpeded state, if this place, crossing downstream road section is congestion status, bottleneck control is carried out at current crossing, and continues the congestion status in judgement section, place, until single-point optimal control, when unimpeded state, is carried out in section, place or induction is controlled.
8. according to claim 7 how tactful multiobject self-adaption traffic control method, it is characterized in that, in described step (2), when crossing is during in non-unimpeded state, and this place, crossing downstream road section is while being non-congestion status, continue to judge whether this crossing belongs to arterial control crossing, if belong to arterial control crossing, judge that whether this main line is in congestion status, if the words of congestion status, the all crossings of main line executive system optimization-Multiple Intersections blocks up to link and controls, if the words of non-congestion status, the all crossings of main line executive system optimization-green wave coordination is controlled.
9. according to claim 7 how tactful multiobject self-adaption traffic control method, it is characterized in that, in described step (2), if crossing does not belong to arterial control crossing, continue to judge whether this crossing belongs to Region control crossing, if belonging to Qie Gai region, Region control crossing is congestion status, the green time of the borderline control of constricted zone crossing control phase, carries out Current limited Control.
10. according to claim 7 how tactful multiobject self-adaption traffic control method, is characterized in that, in described step (2), described bottleneck control method is: that ends this current crossing enters downstream road section phase place green light.
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