CN105243856B - The self-organizing construction method of urban traffic signal intelligent control rule - Google Patents
The self-organizing construction method of urban traffic signal intelligent control rule Download PDFInfo
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Abstract
A kind of self-organizing construction method of urban traffic signal intelligent control rule, intersection all in traffic network is localized by interconnection effect, it is abstracted by the hydrodynamics with road network and traffic parameter, the real-time regular expression that internal system is act as between complicated traffic flow is converted, controls traffic flow to realize the purpose of intellectual traffic control on demand or automatically.The features of the present invention includes：Influence of the Road form to traffic flow is taken into full account, so as to ensure the popularity and stability of this method application；Transit time is intelligently distributed, reduces parking waiting, improves traffic efficiency；The signal switching mode of intelligence, can use different switching modes according to different traffics, more effectively improve road passage capability；The effective operand that system is greatly decreased, solve current control strategy and lead to not meet the real time problems for being uniformly controlled global road network because amount of calculation is excessive.
Description
Technical field
The invention belongs to traffic intelligent control technical field, is related to the regular self-organizing structure of urban traffic signal intelligent control
Construction method.
Technical background
Be made up of roadnet, flow system and management system one of Traffic Systems is typical, open to be answered
Miscellaneous system, it is any by the central controlled method of traditional " from top to bottom " big system, be difficult to untie it is such have hard real-time,
The control problem of isomery big data feature.Current a variety of intelligentized traffic signal control systems existing at home and abroad, its core
The heart is all to employ the strategy passively controlled, and its method is evaded to system complexity in fact；When its system scale is little,
There is certain applicability in the case of traffic flow fluctuation less；As system environments is constantly complicated, traffic flow change frequency adds
Play, its control performance accelerate to decline because priori controls the incompleteness of regular objective reality and non real-time nature.Question essence
It is that each road junction does not possess the first study responding ability to scene change, while have ignored each road and hand over
The effect of intercoupling between cross road mouth so that response of the whole system to localized variation is partially slow, and its build-up effect is more obvious.
And its rule is dynamic, changeable in actual Traffic Systems, different local dynamic stations need to use different local rules.
Therefore, for the deficiency of traditional cities traffic control signal " from top to bottom " centralized Control principle, objectively it is necessary research and development one
The self-organizing construction method of the new urban traffic signal intelligent control rule of kind " from bottom to top ".
The content of the invention
In view of the above-mentioned deficiencies in the prior art, it is an object of the present invention to propose that one kind is based on city road network parameter and fluid dynamic
The self-organizing construction method of urban traffic signal intelligent control rule, passes through the intelligence of urban transportation single intersection signal phase
Change switchover policy and realize urban traffic intersection signal self-organization control function, reduce congested in traffic and current delay, improve city
Road rate.
Its core be by intersection all in traffic network by interconnection effect is localized, by with
The hydrodynamics of road network and traffic parameter is abstracted, and is converted the real-time regular expression that internal system is act as between complicated traffic flow, is pressed
Need or automatically control traffic flow to realize the purpose of intellectual traffic control.
The present invention substance be：For the urban traffic signal real-time control problem with complexity features, propose
A kind of new self-organizing based on city road network parameter and fluid dynamic urban traffic signal intelligent control rule is built
Method, i.e., hydrodynamics is introduced on the basis of cellular automata to establish the balance model of traffic flow, it is each by assigning
The autonomous decision-making capability in independent intersection, the interaction between adjacent intersection is evolution power, formation from bottom to top
Local crossing and the Self-organizing Science rule of global road network, and the phase judgment rule by formulating traffic intersection realizes traffic system
The Real-time Decision of system signal mode, is effectively greatly decreased the operand of system, solves current control strategy because of amount of calculation mistake
Lead to not greatly meet the real time problems for being uniformly controlled global road network, reach the purpose of intellectual traffic control.
To achieve the above object, the present invention uses following technical scheme：
1st, the city road network parameter described in this method is the length in single track, width, curvature, allows current phase
Several, maximum speed limit, the preferred number of lane and adjacent lane interphase interaction influence seven parameters such as coefficient.This method
Using road and pipeline, traffic flow and the similitude between flowing naturally, hydrodynamics is introduced to establish the balance model of traffic flow
With the rule model of signal switching.This method is using urban traffic signal control system as transportation network processing, each crossroad
Mouth has the ability of independent information gathering and decision-making treatment to realize the function of control traffic lights conversion.Each crossroad
Mouthful it is that the right-angled intersection that forms, while each intersection and adjacent connection around it are mutually perpendicular to by 1-5 bars track
Intersection carries out data interaction, and basic model is set as that each crossing 4 crossings adjacent thereto are connected and reciprocation
(it may also indicate that a crossing is connected and interacted with 2,3,5 or more crossings by the simplification or extension of basic model
The situation of effect), thus under the weighted value of smart allocation crossing intersection data carry out data operation and decision signal switching
Enabled (containing whether carrying out signal switching and how to carry out signal switching).Each track allows current phase acquisition green at it
The magnitude of traffic flow that can be let pass during signal, determined by the corresponding lane traffic density that can be driven into downstream, while the track is certainly
Body traffic density will determine the magnitude of traffic flow of letting pass in its upstream corresponding phase track.There are 12 vehicle travelings each intersection
Effective control direction, respectively：
With numeral 1 represent from west to drive into intersection and turn left drive towards the north to control direction；
With numeral 2 represent from west to drive into intersection and directly to drive towards east to control direction；
With numeral 3 represent from west to drive into intersection and turn right drive towards south to control direction；
With numeral 4 represent from south orientation drive into intersection and turn left drive towards west to control direction；
With numeral 5 represent from south orientation drive into intersection and directly to drive towards the north to control direction；
With numeral 6 represent from south orientation drive into intersection and turn right drive towards east to control direction；
With numeral 7 represent from east orientation drive into intersection and turn left drive towards south to control direction；
With numeral 8 represent from east orientation drive into intersection and directly to drive towards west to control direction；
With numeral 9 represent from east orientation drive into intersection right turn drive towards the north to control direction；
With numeral 10 represent from north orientation drive into intersection and turn left drive towards east to control direction；
With numeral 11 represent from north orientation drive into intersection and directly to drive towards south to control direction；
With numeral 12 represent from north orientation drive into intersection right turn drive towards west to control direction；
Above-mentioned 12 control directions correspond to 12 control phases, its phase mark sequence and above-mentioned mark sequence respectively in control rule
It is corresponding.Each phase assigns a switching threshold, carries out Phase-switching when next phase decision value reaches threshold value, threshold value is by this
The relevant track critical density of phase institute calculates gained.
2nd, realize steps of the method are：
1) multiple sensors are installed on the entering of each track in intersection, at mouth and track maximum queue flag bit, passed
Sensor sends the data collected in real time to the signal controlling machine of each intersection, and signal controlling machine is according to the information control of collection
The state change of signal lamp processed.
2) the maximal density ρ in the track is calculated according to the road network parameter in each trackmax, critical crowded density pjam, it is maximum
Flow Qmax, maximum transit time Tmax, minimum passing time Tmin：
ρmax=L/S
L is the lane length and reference length obtained by curvature weighting in formula；S is that kart average length is pacified with two workshops
Full distance sum, generally 6.5m.
ρjam=iintρmax
I in formulaintInteracted response coefficient for the track and adjacent lane, be divided into no adjacent lane, have one it is adjacent
Track, there are two adjacent lanes, adjacent lane is more, and its value is bigger, span (0.5,1).
Qmax=Vmaxρmax
V in formulamaxAllow current maximum speed per hour for the track.
Minimum passing time determines by the current speed per hour of maximum, quick decision when maximum transit time is as corresponding to whole team's row density
It is fixed.
3) dynamic track density p, track flow Q, track inflow flow Q are calculated according to the information of collectionin, track outflow
Flow Qout, track demand transit time T：
ρ=(Nin-Nout+N)/ρmax
N in formulain、NoutThe vehicle number for entering, rolling away from the track in time step t is represented respectively, and N represents a upper time step
The vehicle number of clearing in long t, the extra computation that left turn lane needs turn around car number N1。
Flow into, outflow flow is detected by road crossing both ends sensor and obtained.
WhereinT is unit time step.(t ' is it is merely meant that definite value integrates
Lower and t difference)
4) signal controlling machine the phase combination according to designed by system, distributes each phase according to resulting dynamic parameter
The minimax cycle, when single time step is settled accounts to current phase state value compared with threshold value, it is determined whether carry out
Phase-switching, if switching over, communicated with adjacent intersection, and calculate the phase difference of adjacent intersection.
3rd, in order to realize the correlation between same-phase order track, so that it is determined that the parameter in arbitrary phase rule
Number, the now combination to 12 phases in intersection divides, as follows：
1) track of a current phase is only allowed
2) track of two colleague's phases is allowed
3) track of three current phases is allowed
Wherein, f () represents any track for allowing current number comprising the phase, and left-hand rotation+right-hand rotation combination is defaulted as trident
Crossing.
4th, by the introducing of Fluid Mechanics rule, traffic flow equilibrium process is established, it is final the methods of using difference equation
Show that the step of controlling regular equation is as follows：
To receive dimension-RANS (abbreviation N-S equations) vector form represent it is as follows：
In formulaReferred to as Laplace operator.
Introduce traffic flow dynamic viscosity coefficientIt is (whole for the proportionality coefficient of various vehicles in whole traffic flow for sign
Which kind vehicle is individual wagon flow be aided with again based on any vehicle), way situation (number of track-lines), vehicle in whole traffic flow
The change of vehicle density, Na Wei-RANS that traffic flow is rebuild in analogy are as follows：
Vehicle flow can be construed to one kind with car in the characteristic that crossing is shifted from high-density region to density regions
It is bidimensional " diffusion " phenomenon of unit, the diffusion equation of its two-dimensional space is：
(corresponding with active spread condition)
(corresponding with the spread condition converged)
Wherein, situation function f (x, y, t) isWherein δ (x, y) is unit impulse function, i.e.,
∫ ∫ ∫ δ (x, y) dxdy=1, ((xi,yi) be point source position coordinate), for characterizing the position of point source, g (t) is
By source stream δ (x, y)=0, (x, y) ≠ (xi,yi)
Go out or by conflux into the function that changes over time of amount.Source actual crossing model corresponding with remittance in diffusion equation
Middle vehicle flows in and out.
It is followed successively by for the vector equation wherein four of reconstruction and acts on the inertia force of unit mass fluidQuality
Power (fb), pressure gradient powerAnd viscous forceBecause so-called single " molecule " in traffic flow is car
, and vehicle is the energy that is sent by engine to overcome gravity to travel.That is the motion relative to vehicle in itself
For, the effect of mass force is can be by completely ignored.
With the method for time discretization being handled in Self-organizing Science, can effectively reduce the excessive high-order fortune of system
Calculate.Independent network division is carried out by orthogonal direction to two-dimentional transportation network and obtains control rule such as using finite difference calculus
Under：
In formula The forecast and decision value of phase i subsequent times is represented, is used
Compare in the threshold value with default, so as to decide whether to carry out commutation；N, n-1, n+1 represent local crossing, downstream road respectively
Mouth, upstream crossing；∑αn、∑βn、∑ηnRepresent the respective priority pass parameter in corresponding track.
5th, the predicting traffic flow density in the phase track is calculated by such scheme, the operation result is converted into reality
The step of signal control form on border, is as follows：
(1) the control rule based on assignment of traffic, track is during downstream track is driven towards corresponding to arbitrary phase, meeting
Other associate the phenomenon that tracks of phase produce interflow in downstream entrance with local intersection, at the same the flow of its own and its
The flow of adjacent lane will determine that upstream crossing associates the assignment of traffic that phase is driven into, therefore assignment of traffic reasonable in design rule
The traffic demand in all directions can be ensured, avoid a direction upstream and downstream pressure is excessive from causing traffic flow to be difficult to effective flowing
Rough sledding, the principle of its assignment of traffic is：
Three kinds of situations are respectively in formula：When track influx is more than discharge, in the ratio clearance traffic flow of influx；
When track can let pass maximum discharge, let pass with maximum discharge；When downstream road junction limits local each crossing discharge,
Let pass on the basis of the track of downstream road junction minimum traffic volume discharge.
(2) in order to avoid traffic flow is frequently impacted or a certain flow direction can not obtain right-of-way, it is necessary to appointing for a long time
The green signal period length of meaning phase enters row constraint, assigns each phase minimum and maximum green two parameters of signal period length
Value, parameter value are determined by the inherent parameters of road；Meanwhile next phase decision value is in the phase green signal period minimum green signal
Phase threshold is arrived between long and maximum green Chief Signal Boatswain；That is, minimum period length of the green phase duration of current demand signal in not up to setting
When, Phase-switching will not be carried out；Current demand signal is in the minimum progress dynamic decision between maximum cycle of its green phase, if a certain phase
The state decision-making of gained has reached the phase threshold of itself after the time step clearing in office of position, then forces to carry out Phase-switching；
Reach the phase threshold of itself without any phase when the green phase duration of current demand signal has reached maximum cycle length and in whole cycle
Need to switch, then automatically into next phase.
(3) phase order of whole signal period is followed successively by f (2) or f (8), f (1) or f (7), f (3) or f (9), f (5)
Or f (11), f (4) or f (10), f (6) or f (12), if turning right allows a direct line, cancel right-hand rotation Phase-switching order；
If signal allows multiple phases of letting pass successively, cancel the queue order of the phase in rear number, the phase in rear order
If position is included in the track phase of preceding order, cancel the Phase-switching sequence of the rear order.
Due to using above-mentioned technical proposal, the beneficial effects of the invention are as follows：Under existing intelligent transportation system framework, with
It is point of penetration to solve urban traffic signal control problem, establishes and supports that the Self-organizing Science towards urban transportation big data is theoretical,
Effectively solve current control strategy and lead to not real-time control of the realization to traffic because global road network amount of calculation is excessive
Problem, inherently proposes the improved route that control method for coordinating deficiency is concentrated to current " from top to bottom " formula, and the present invention is logical
The expression of traffic flow internal relations effect is crossed, imparts the autonomous decision-making capability in each independent crossing, each independent crossing made
The calculating of the volume of traffic need to be only carried out by minimum correlation model, the amount of calculation of whole road network is effectively reduced, so as to realize to whole
The real-time control of individual road network and the pressure for effectively reducing service centre.The present invention not only enriches current city traffic control strategy
System, also provide the theoretical support with technology to develop new urban transportation Self-organizing Science equipment.
Brief description of the drawings
Fig. 1 is the schematic diagram of phase sequence number in illustrated embodiment of the present invention.
Fig. 2 is city localized road network topology result schematic diagram.
Fig. 3 is the schematic diagram of certain association phase under minimum decision model.
Fig. 4 is the Self-organizing Science process schematic of urban traffic signal.
Embodiment
The present invention will be further described with reference to the accompanying drawings.
Fig. 1 represents 12 phases corresponding to intersection, and the whole signal period presses f (2) or f (8), f (1) or f (7), f
(3) or f (9), f (5) or f (11), f (4) or f (10), f (6) or f (12) carry out Phase-switching, if turning right allows one to lead directly to
OK, then right-hand rotation Phase-switching order is cancelled；If the phase in rear order is included in the phase of preceding order, after cancelling this
The Phase-switching sequence of order, if there is two or more tracks to possess same current phase simultaneously, its parameter includes this
Phase decision-making equation, if track possesses two or more current phases simultaneously, its parameter is involved in being included each
The decision-making equation of phase.
Fig. 2 represents, by the road network figure after some city regional area road network form progress network topology, to be easy to simulation calculating.
Any Xrds crossing is chosen in Fig. 3 expressions, and it passes through four intersections adjacent with surrounding and carries out data communication
With phase association, the cellular Automation Model of minimum is formed, the track for possessing the 2nd phase of dark signs is decision-making car in figure
Road, the track of remaining light color mark is track associated by the phase, and wherein n is that this road intersection associates track, under n+1 is
Intersection association track is swum, n-1 is that upstream intersection associates track, and density, flow, the speed in all mark tracks are received
Enter the phase decision-making equation to be calculated.
It realizes that the step of control rule is as follows：
1) in advance urban road network handle by phase classification, that is, the number of the current phase allowed, by dividing
Each track Signal Phase Design at the crossing of certain selected crossing four direction adjacent thereto is analysed, the phase bit class at local crossing is combined, builds
The decision model of each phase is found, the current phase in current crossing is participated in track track related to the current phase of adjacent intersection and carries out
Integration expression, that is, select a certain crossing, according to adjacent intersection information, design the phase combination at the crossing, and distribute to each phase
The information of all roads associated by position.
2) parameter in each track in road network is integrated, and by the morphological parameters General Office in its upstream and downstream track in the same direction
Reason, assigns each track phase saturation degree critical value, the value mutually fades to interphase (saturation degree 0.35) and crowded phase based on traffic flow
(saturation degree 0.5) is modified；Interflow coefficient (such as Fig. 1 things when assigning each track master phase and dependent phase simultaneously
Through Lane is master phase in 2,8 phases, and 1,4,6,10 be dependent phase), so as to finally determine each track in each phase bit decisions
Parameter algebraic value in model, wherein in default parameter meeting writing controller.
3) detected in real time according to the traffic flow that is travelled on road, the flow that will collect on correspondence road, density,
The storage of the information such as speed, queue length in the unit of corresponding phase bit decisions, each phase bit decisions by the information of collection temporally
Step-length carries out sliding-model control, and settles accounts a decision parameters, and the decision parameters of all phases are compared, by decision table point
Situation is carried out judging whether to Phase-switching, or which phase to switch over operation to, and decision table is gathered around by low crowded, moderate
Squeeze, the function division that highly crowded progress is different.
4) after Phase-switching is carried out, according to the assignment of traffic rule at upstream and downstream crossing, change is dynamically adjusted according to Fig. 4
The time length of clearance, improves the utilization rate of road, and waits the Phase-switching application of next phase.If in practical application due to
The damage of detector or human factor cause road to be returned for a long time without data, then system can be according to the digital simulation of adjacent road
The magnitude of traffic flow corresponding to generation carries out decision-making.The parameters such as default road critical saturation can be in the certain limit of preset value
Dynamically fluctuated according to the change of environment, if it find that its some section has carried out the human activities such as the reconstruction on road,
New parameter preset need to be re-write.
5) the step of repeating 1-4.
Fig. 4 represents the Self-organizing Science process of urban traffic signal.In figure, at the beginning of GBegin represents green light phase
Carve, minimum, the maximum of each phase are respectively Gmin, Gmax when green.When each step that develops starts, system is by the vehicle flowrate of acquisition
Information N (vehicle number) is converted to status information CS, so as to participate in road network each crossing by the parallel evolutionary of self-organization rule,
From time shaft, when Phase Duration be less than it is minimum it is green constantly, without intervening phase, and enters " elastic green
When " after, it is required for being made regarding whether the phase state at local crossing the differentiation of switching at the end of each time step, directly
The new state CS of generation of developing in certain time step meets certain rule in signal control strategy, realizes the belisha beacon
Phase-switching.
It can be seen that the inventive method is using road and pipeline, traffic flow and the similitude between stream naturally, in cellular automata
On the basis of introduce hydrodynamics and establish the balance model of traffic flow, pass through assign each independent intersection it is autonomous certainly
Plan ability, the interaction between adjacent intersection as evolution power, the local crossing of formation from bottom to top and global road network from
Organizational controls is regular, and the Real-time Decision of traffic system signal mode is realized by formulating the phase judgment rule of traffic intersection,
Reach the purpose of intellectual traffic control.The features of the present invention includes：Influence of the Road form to traffic flow has been taken into full account, so as to
Ensure the popularity and stability of this method application, it is more actually active to solve different traffic problems；Intelligently distribution is logical
The row time, parking waiting is reduced, improve traffic efficiency；The signal switching mode of intelligence, this method can flexible designed phase
Number and phase combination, can meet the design requirement of 2-8 phases, can use different switching sides according to different traffics
Formula, more effectively improve road passage capability；The effective operand that system is greatly decreased, solve current control strategy because
Amount of calculation is excessive and leads to not meet the real time problems for being uniformly controlled global road network.
The above-mentioned description to embodiment is understood that for ease of those skilled in the art and using this hair
It is bright.Person skilled in the art obviously easily can make various modifications to these embodiments, and described herein
General Principle is applied in other embodiment without by performing creative labour.Therefore, the invention is not restricted to implementation here
Example, for those skilled in the art according to the announcement of the present invention, the improvement made for the present invention and modification all should be the present invention's
Within protection domain.
Claims (8)
- A kind of 1. self-organizing construction method of urban traffic signal intelligent control rule, it is characterised in that：By institute in traffic network Some intersections are localized by interconnection effect, are abstracted by the hydrodynamics with road network and traffic parameter, are turned Change the real-time regular expression that internal system is act as between complicated traffic flow, control traffic flow to realize intelligent friendship on demand or automatically The purpose of logical control；Comprise the following steps：1) multiple sensors are installed on to entrance, exit and the track maximum queue flag bit in each track in intersection, passed Sensor sends the data collected in real time to the signal controlling machine of each intersection, and signal controlling machine is according to the information control of collection The state change of signal lamp processed；2) the maximal density ρ in the track is calculated according to the road network parameter in each trackmax, critical crowded density pjam, maximum stream flow Qmax, maximum transit time Tmax, minimum passing time Tmin：ρmax=L/SL is the lane length and reference length obtained by curvature weighting in formula；S be kart average length and two shop safeties away from From sum；ρjam=iintρmaxI in formulaintFor the track and adjacent lane interaction response coefficient, it is divided into no adjacent lane, there is an adjacent car Road, there are two adjacent lanes, adjacent lane is more, and its value is bigger；Qmax=VmaxρmaxV in formulamaxAllow current maximum speed per hour for the track；Minimum passing time determines that maximum transit time speed per hour corresponding to whole team's row density determines by the current speed per hour of maximum；3) dynamic track density p, track flow Q, track inflow flow Q are calculated according to the information of collectionin, track outflow flow Qout, track demand transit time T：ρ=(Nin-Nout+N)/ρmaxN in formulain、NoutThe vehicle number for entering, rolling away from the track in time step t is represented respectively, and N is represented in upper time step t The vehicle number of clearing, the extra computation that left turn lane needs turn around car number N1；Flow into, outflow flow is detected by road crossing both ends sensor and obtained；<mrow> <mi>T</mi> <mo>=</mo> <mfrac> <mn>1</mn> <mi>t</mi> </mfrac> <munderover> <mo>&Sigma;</mo> <mn>1</mn> <mi>t</mi> </munderover> <mrow> <mo>(</mo> <mfrac> <mi>L</mi> <msup> <mi>v</mi> <mo>&prime;</mo> </msup> </mfrac> <mo>)</mo> </mrow> </mrow>WhereinT is unit time step；4) signal controlling machine is according to resulting dynamic parameter, the phase combination according to designed by system, and it is maximum to distribute each phase Minimum period, when single time step is settled accounts to current phase state value compared with threshold value, it is determined whether carry out phase Switching, if switching over, is communicated, and calculate the phase difference of adjacent intersection with adjacent intersection.
- 2. the self-organizing construction method of urban traffic signal intelligent control rule according to claim 1, it is characterised in that： I in formulaintSpan (0.5,1).
- 3. the self-organizing construction method of urban traffic signal intelligent control rule according to claim 1, it is characterised in that： Hydrodynamics is introduced on the basis of cellular automata to establish the balance model of traffic flow, by assigning each independent friendship The autonomous decision-making capability of cross road mouth, the interaction between adjacent intersection is evolution power, formation part crossing from bottom to top It is regular with the Self-organizing Science of global road network, and the phase judgment rule by formulating traffic intersection realizes traffic system signal mode The Real-time Decision of formula is to reduce the operand of system.
- 4. the self-organizing construction method of urban traffic signal intelligent control rule according to claim 1, it is characterised in that： The length of described city road network parameter including single track, width, curvature, allow current number of phases, maximum speed limit, track Current preferred number and adjacent lane interphase interaction influence coefficient；For this method using road and pipeline, traffic flow and the similitude between flowing naturally, introduction hydrodynamics establishes traffic flow The switching of balance model and signal rule model；Using urban traffic signal control system as transportation network processing, Mei Gejiao Cross road mouth has the ability of independent information gathering and decision-making treatment to realize the function of control traffic lights conversion.
- 5. the self-organizing construction method of urban traffic signal intelligent control rule according to claim 4, it is characterised in that： Each intersection is to be mutually perpendicular to the right-angled intersection that forms by 1-5 bars track, while each intersection is with being connected 4 intersections carry out data interaction, under the weighted value of 5 crossing intersection datas of smart allocation carry out data operation and certainly The switching of plan signal enables；The magnitude of traffic flow that each track can let pass when it allows the current phase green signal of acquisition, by The corresponding lane traffic density that can be driven into downstream is determined, while itself traffic density of the track will determine that its upstream corresponds to phase The magnitude of traffic flow of letting pass in position track.
- 6. the self-organizing construction method of urban traffic signal intelligent control rule according to claim 4, it is characterised in that： There is effective control direction of 12 vehicle travelings each intersection, sets respectively as follows：With numeral 1 represent from west to drive into intersection and turn left drive towards the north to control direction；With numeral 2 represent from west to drive into intersection and directly to drive towards east to control direction；With numeral 3 represent from west to drive into intersection and turn right drive towards south to control direction；With numeral 4 represent from south orientation drive into intersection and turn left drive towards west to control direction；With numeral 5 represent from south orientation drive into intersection and directly to drive towards the north to control direction；With numeral 6 represent from south orientation drive into intersection and turn right drive towards east to control direction；With numeral 7 represent from east orientation drive into intersection and turn left drive towards south to control direction；With numeral 8 represent from east orientation drive into intersection and directly to drive towards west to control direction；With numeral 9 represent from east orientation drive into intersection right turn drive towards the north to control direction；With numeral 10 represent from north orientation drive into intersection and turn left drive towards east to control direction；With numeral 11 represent from north orientation drive into intersection and directly to drive towards south to control direction；With numeral 12 represent from north orientation drive into intersection right turn drive towards west to control direction；Above-mentioned 12 control directions correspond to 12 control phases, its phase mark sequence and above-mentioned mark ordered pair respectively in control rule Should；Each phase assigns a switching threshold, carries out Phase-switching when next phase decision value reaches threshold value, threshold value is by the phase The relevant track critical density of position institute calculates gained.
- 7. the self-organizing construction method of urban traffic signal intelligent control rule according to claim 6, it is characterised in that： For allowing its combination of current number of phases to be on different tracks：1) track of a current phase is only allowed2) track of two colleague's phases is allowed3) track of three current phases is allowedWherein, f () represents any track for allowing current number comprising the phase, and left-hand rotation+right-hand rotation combination is defaulted as fork in the road；By the associative combination of phase, the 2-8 phase combinations in the signal controlling cycle of intersection one are set, only need to be according to right The phase association answered carries out decision-making.
- 8. the self-organizing construction method of the urban traffic signal intelligent control rule according to any in claim 1 to 7, its It is characterised by：Based on receive dimension-RANS to traffic flow campaign carry out math equation reconstruct, Na Wei-Stokes The vector form of equation is as follows：<mrow> <mfrac> <mrow> <mi>d</mi> <mi>u</mi> </mrow> <mrow> <mi>d</mi> <mi>t</mi> </mrow> </mfrac> <mo>=</mo> <msub> <mi>f</mi> <mi>b</mi> </msub> <mo>-</mo> <mfrac> <mn>1</mn> <mi>&rho;</mi> </mfrac> <mo>&dtri;</mo> <mi>p</mi> <mo>+</mo> <mi>&mu;</mi> <msup> <mo>&dtri;</mo> <mn>2</mn> </msup> <mi>u</mi> </mrow>In formulaReferred to as Laplace operator；Wherein four are followed successively by and act on unit mass The inertia force of fluidMass force fb, pressure gradient powerAnd viscous forceThe effect of mass force is ignored rear whole Reason obtains the reduced form of Na Wei-RANS for traffic flow：<mrow> <mfrac> <mrow> <mi>d</mi> <mi>u</mi> </mrow> <mrow> <mi>d</mi> <mi>t</mi> </mrow> </mfrac> <mo>=</mo> <mo>-</mo> <mfrac> <mn>1</mn> <mi>&rho;</mi> </mfrac> <mo>&dtri;</mo> <mi>p</mi> <mo>+</mo> <mover> <mi>&mu;</mi> <mo>~</mo> </mover> <msup> <mo>&dtri;</mo> <mn>2</mn> </msup> <mi>u</mi> </mrow>In formulaFor traffic flow dynamic viscosity coefficient.
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| CN107038878B (en) * | 2017-06-06 | 2020-04-24 | 广东振业优控科技股份有限公司 | Traffic signal phase design method based on integer programming model |
| CN108091146A (en) * | 2017-12-12 | 2018-05-29 | 常州大学 | A kind of traffic lights based on artificial intelligence it is non-wait whens manage system |
| CN108428356B (en) * | 2018-03-21 | 2020-06-02 | 东南大学 | Road condition map display and driving assistance application method based on fluid density field |
| CN109376920A (en) * | 2018-10-12 | 2019-02-22 | 国网浙江省电力有限公司温州供电公司 | Traffic route trend prediction method based on minute transfer matrix |
| CN112967502B (en) * | 2021-02-25 | 2022-02-11 | 大连东软信息学院 | Traffic flow control method for crossroad |
| CN113643529B (en) * | 2021-07-02 | 2022-09-20 | 厦门路桥信息股份有限公司 | Parking lot lane congestion prediction method and system based on big data analysis |
| CN113781768B (en) * | 2021-08-09 | 2023-02-10 | 同济大学 | Hot spot district traffic organization control cooperation method based on reserve traffic capacity |
| CN114067558A (en) * | 2021-08-22 | 2022-02-18 | 刘智和 | Intelligent network for controlling traffic of each intersection in city by adopting internet |
| CN114120670B (en) * | 2021-11-25 | 2024-03-26 | 支付宝(杭州)信息技术有限公司 | Method and system for traffic signal control |
| CN117041303B (en) * | 2023-10-09 | 2023-12-15 | 睿兴科技(天津)有限公司 | Data transmission method and system for intelligent diagnosis of water pump |
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