CN106600990A - Dynamic signal lamp assessment method and system based on genetic algorithm - Google Patents
Dynamic signal lamp assessment method and system based on genetic algorithm Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
Abstract
The invention provides a dynamic signal lamp assessment method based on a genetic algorithm, and the method comprises the steps: carrying out the initialization, and obtaining related information through an intersection number; defining a lane group, wherein all lanes with the passing right at one phase at the same segment are defined as one lane group; finding a core permission lane group at a current phase, wherein the lane is removed from the lane group if the lane has the passing right at all phases; finding the key lane at the phase; determining a theoretical minimum period and a theoretical maximum period; determining the saturation of the lane at each phase; determining a punishment function for the period; determining a programming function at a non-oversaturation phase, carrying out the call of a genetic function to solve an optimal solution of the programming function. The invention also proposes a dynamic signal lamp assessment system based on the genetic algorithm.
Description
Technical field
The present invention relates to public transport technical field, comments in particular to a kind of Dynamic Signal lamp based on genetic algorithm
Estimate method and system.
Background technology
In intelligent transportation system (ITS), city traffic signal lamp control is a particularly important part.City vehicle is fast
Speed increases, and path resource is limited so that traditional traffic lights control is difficult to obtain satisfied effect.Traditional traffic lights control is main
Control when having solid and sense control.Gu when the mode that controls can not make respective reaction to the vehicle flowrate of real-time change.
For city intersection signal lighties, the vehicle average latency is reduced as target, taking into account pedestrian's driving peace
On the premise of complete, a kind of traffic lights real-time time-mixed algorithm in prior art, is also proposed, it is according to the vehicle number of video real-time detection, right
Traffic lights timing real-time monitoring.Algorithm includes two-step evolution:One-level control is based on fuzzy control theory, according to rate and the vehicle of being open to traffic
Waiting time chooses the initial timing of appropriate level；Two grades of real-time control calculating simulations are open to traffic number, to initial timing real-time monitoring
And control phase transition.Under identical transportation condition, relative to it is solid when control and fuzzy control, traffic lights real-time time-mixed algorithm makes
The vehicle average latency is reduced.Meanwhile, when each phase place traffic density differs greatly, it is to avoid waiting time polarization.But
The calculating of the algorithm is complicated, and the requirement to data processing is higher.
The content of the invention
Present invention aim at providing a kind of Dynamic Signal lamp appraisal procedure and system based on genetic algorithm, overcome existing
Problem in technology.
To reach above-mentioned purpose, the present invention proposes a kind of Dynamic Signal lamp appraisal procedure based on genetic algorithm, including：
Step 1, initialization, obtain following information by crossing numbering：The phase configuration at crossing, the corresponding car of each phase place
Road, the identifier marking in track, the saturation volume rate in each track, the traffic capacity in each track, 15 minutes flows in each track,
Each phase place key track packet, peak hour factor, delay and parking weight, incremental delay correction factor, upstream and downstream linkage
Correction factor, the minimax green time of each phase place, the minimax cycle time of each phase place and each phase place
Lost time；
Step 2, definition track group, all tracks definition for wherein under some phase place, possessing right-of-way on same section
For a track group；
Step 3, the core clearance track group for finding out current phase place, if wherein：Track all possesses current in all phase places
In the case of power, the track in the group of track, is removed；
Step 4, the crucial track for finding out phase place；
Step 5, decision theory minimum period and maximum cycle；
Step 6, the saturation for judging each phase place key track；
Step 7, determination are for the penalty in cycle；
Step 8, the planning function determined under non-supersaturation phase place, and call genetic function to solve the optimum of the planning function
Solution.
In further embodiment, in abovementioned steps 2, the decision condition of track group is：
1st, obtain all of track for possessing right-of-way under phase place A；
2nd, these tracks are grouped according to section, possess same road segment ID for one group.
In further embodiment, in abovementioned steps 4, find out phase place crucial track implement including：
1st, after core track group completes track screening, can there are two kinds of situations in each section
Situation 1：There is track group in phase place, then execution step：
1) find out v/s in the group of track and, than maximum track, define the crucial track that the track is the section；
2) find out in all track groups of phase place, v/s defines the crucial track that the track is phase place than maximum track；
Situation 2：There is no track group in phase place, then execution step：
1) v/s of the crucial track group of the phase place is set to into 0.1；
2nd, there is the situation of at least one track group in the section corresponding to phase place；Directly maximum flow is chosen from the group of track
Track, the track is defined as into crucial track；
3rd, certain phase place does not possess crucial track, because only that a track, then the phase place directly runs minimum green light.
In further embodiment, in abovementioned steps 5, decision theory minimum period and maximum cycle implement as
Under：
Theoretical according to Robert Webster delay, the theoretical minimum period is：
If：Y >=1, then the cycle is equal to the Cmin in data；
The theoretical maximum cycle is：
If：Y >=1, then the cycle is equal to the Cmax in data；
Wherein Y be the V/S of all phase places than sum, L is multiplied by 9 for phase place number.
In further embodiment, abovementioned steps 6 judge the computing formula of the saturation in each phase place key track as：
As long as it should be appreciated that all combinations of aforementioned concepts and the extra design for describing in greater detail below are at this
A part for the subject matter of the disclosure is can be viewed as in the case that the design of sample is not conflicting.In addition, required guarantor
All combinations of the theme of shield are considered as a part for the subject matter of the disclosure.
Can be more fully appreciated with reference to accompanying drawing from the following description present invention teach that foregoing and other aspect, reality
Apply example and feature.The feature and/or beneficial effect of other additional aspects such as illustrative embodiments of the present invention will be below
Description in it is obvious, or by according to present invention teach that specific embodiment practice in learn.
Description of the drawings
Accompanying drawing is not intended to drawn to scale.In the accompanying drawings, identical or approximately uniform group of each for illustrating in each figure
Can be indicated by the same numeral into part.For clarity, in each figure, not each ingredient is labeled.
Now, by example and the embodiment of various aspects of the invention will be described in reference to the drawings, wherein：
Fig. 1 is that the flow process of the Dynamic Signal lamp appraisal procedure based on genetic algorithm according to certain embodiments of the invention is illustrated
Figure.
Fig. 2 is the schematic flow sheet of real-valued genetic algorithm universal model.
Specific embodiment
In order to know more about the technology contents of the present invention, especially exemplified by specific embodiment and institute's accompanying drawings are coordinated to be described as follows.
Each side with reference to the accompanying drawings to describe the present invention in the disclosure, shown in the drawings of the embodiment of many explanations.
Embodiment of the disclosure must not be intended to include all aspects of the invention.It should be appreciated that various designs presented hereinbefore and reality
Apply example, and those designs for describing in more detail below and embodiment can in many ways in any one come real
Apply, this is because design disclosed in this invention and embodiment are not limited to any embodiment.In addition, disclosed by the invention one
A little aspects can be used alone, or otherwise any appropriately combined using with disclosed by the invention.
With reference to shown in Fig. 1, Fig. 2, embodiments in accordance with the present invention, a kind of Dynamic Signal lamp assessment side based on genetic algorithm
Method, including following implement step：
The first step：Initialization data
Following information is obtained respectively by crossing numbering
| The phase configuration at crossing | MD_PHASE_GROUP | Data base obtains automatically |
| The corresponding track of each phase place | Data base obtains automatically | |
| The identifier marking in track | Data base obtains automatically | |
| The saturation volume rate in each track | Data base obtains automatically, and the page can be changed | |
| The traffic capacity in each track | Data base obtains automatically, and the page can be changed | |
| 15 minutes flows in each track | Obtain in data base | |
| Each phase place key track packet | System-computed, the page can be changed | |
| Peak hour factor | Data base reads, and the page can be changed | |
| Delay and parking weight | Data base reads, and the page can be changed | |
| Incremental delay correction factor | Data base reads, and the page can be changed | |
| Upstream and downstream linkage correction factor | Data base reads silently and takes, and the page can be changed | |
| The minimax green time of each phase place | Data base reads silently and takes, and the page can be changed | |
| Minimax cycle time of each phase place | The minimax green time of each phase place | |
| The lost time of each phase place | 3 | Data base reads silently and takes, and the page can be changed |
Second step：Define track group
Under some phase place, all tracks for possessing right-of-way on same section are defined as a track group.Decision condition
For,
1st, obtain all of track for possessing right-of-way under phase place A.
2nd, these tracks are grouped according to section, possess same road segment ID for one group.
3rd step：Find out the core clearance track group of current phase place
If：Track removes the track in the case where all phase places all possess right-of-way in the group of track.
4th step：Find out the crucial track of phase place
After core track group completes track screening, can there are two kinds of situations in each section
Situation 1：There is track group in phase place
Execution step：
1st, find out v/s in the group of track and, than maximum track, define the crucial track that the track is the section.
2nd, find out in all track groups of phase place, v/s defines the crucial track that the track is phase place than maximum track.
Situation 2：There is no track group in phase place
Execution step：
● the v/s of the crucial track group of the phase place is set to into 0.1.
● there is the situation of at least one track group in the section corresponding to phase place
This situation is more common scenario, and the track of maximum flow is directly chosen from the group of track.The track is defined
For crucial track.
● certain phase place does not possess crucial track, because only that a track
This situation is more rare situation, the situation occurs, and the phase place directly runs minimum green light.
5th step：Decision theory minimum period and maximum cycle
Theoretical according to Robert Webster delay, the theoretical minimum period is
If：Y >=1, then the cycle be equal to data in Cmin,.
The theoretical maximum cycle is
If：Y >=1, then the cycle be equal to data in Cmax,.
Wherein Y be the V/S of all phase places than sum, L is multiplied by 9 for phase place number.
6th step：Judge the saturation in each phase place key track
The computing formula of saturation is
7th step：It is determined that for the penalty in cycle
Penalty logic as implied above is as follows：
If saturation>1
Then mean delay be equal to=original mean delay+| saturation -1 | squares * 2500；
If saturation<0.8
Then mean delay be equal to=original mean delay+| saturation -1 | squares * 5000；
8th step：Determine the planning function under non-supersaturation phase place
Wherein
Numbers of the n for phase place
C, gkFor unknown number, if target phase is locked out, its corresponding gkFor datum.
K represents the track group of a certain phase place, and A, B, C are phase bit number.
T：Value analyzes the period, it is proposed that be worth for 0.25.
k：Incremental delay amendment, it is proposed that value 0.5.
I：Upstream and downstream coordinated signals amendment, it is proposed that value 1.
λk：Table MD_UTC_PRORITY is stored in, can be obtained according to section numbering+phase place group #.Default value is 1.
Call genetic algorithm (shown in Fig. 2) to cry for help and the planning function export optimal solution.
Parameter and interface relationship in preceding method and it is defined as follows：
, in implementation process, the theoretical basic thought of timing is as follows for the present invention：
There are three kinds of situations in practical application based on the Traffic Signal Timing of flow, be respectively
1. when saturation is between 0～0.3
The now timing of signal lighties is limited by minimum green light.Its reason is because, although the green time of signal lighties
There is a waste, but be in order at the consideration of safety and pedestrian's street crossing, be both have waste shorten its green time.
2. when saturation is between 0.6～0.9
The now timing of signal lighties can improve efficiency by optimizing, and the method for optimization is using classical Robert Webster method
The method for then combining weighting carries out optimization.
3. when saturation is more than 0.9
The now timing of signal lighties is limited by maximum green light.Its reason is, the green time of signal lighties can not be after
Continue increase, because the excessive cycle may cause downstream traffic bottlenecks occur.
| Automatically calculate |
Module was run once per 1 minute, only obtained flow, and other numerical value are the buffering for obtaining for the first time.To calculate
Result be stored in AY_RESULT_UTC_BESTREGARDS tables.
| Request is calculated |
Module receive the page it is incoming below form data, if some items are not transmitted, then acquiescence use data base
In data.Result of calculation is generated according to user's request.And it is stored in AY_RESULT_UTC_BESTREGARDS.
Term is introduced：
| Term | Introduce |
| Controlled drug-release d | Due to the control of signal lighties, cause road produce vehicle stop or can not normal through time. |
| Uniform delay d1 | Assume that vehicle is averagely reached, but be the failure to the delay produced by crossing with average speed. |
| Incremental delay d2 | With the uneven and caused delay that saturation, the increase of density, vehicle are presented. |
| Saturation volume rate sa | Crossing no signal lamp, vehicle is with the intensive quantity queued up by crossing of desin speed. |
Fig. 2 show an exemplary algorithm of genetic algorithm, is real-valued genetic algorithm universal model.
With reference to shown in Fig. 2, the algorithm some steps and process explain.
3rd step：Judge end condition
End condition is a set, is combined together by multiple end conditions, as long as any one condition meets
Just stop interative computation.
End condition one：Genetic algebra
If genetic algebra is 1000, an end condition is often judged, algebraically increases by 1. and works as more than 1000, returns true.
End condition two：Individual adaptation degree tends to be steady.
4th step：Call competition operator
Competitive Algorithms are divided into two parts, and Part I is the solution for calling competition operator to obtain fitness.
Judge whether the Competitive Algorithms have penalty term,
Penalty is then called to solve again the value of competition operator if there is penalty term.
If there is no the penalty term then direct value of output competition operator.
5th step：Call penalty
System provides the interface of penalty, and the input of the interface is an individual for population.Output is modified
It is individual.
6th step：Write selection algorithm
Selection algorithm is divided into 2 parts, calls selection opertor to ask for the fitness of individuality.Fitness function should be towards mesh
The favourable direction of scalar functions is developed.I.e. fitness is bigger, and object function is the closer to target.
If each individual fitness is fi, a total of n is individual, then fitness wheel disc can use following ordered series of numbers to represent.
This probability number biography is entered into probability wheel disc algorithm, n individual subscript is tried to achieve.Choose generation new this n individuality
Population.
7th step：Call Crossover Operator
If probability of crossover is [ρ, 1- ρ], probability wheel disc is called, if hit, calls Crossover Operator, if miss,
Crossover Operator is never called then.
The input of Crossover Operator is an individual, is output as the new individual through hybridizing.For real-valued genetic algorithm, hybridization
Operator is used uniformly across the mode of arithmetic hybridization.
8th step：Call mutation operator
If mutation probability is [σ, 1- σ], probability wheel disc is called, if hit, calls mutation operator, if miss,
Mutation operator is never called then.
The input of Crossover Operator is an individual, is output as the new individual through hybridizing.Crossover Operator is needed according to concrete
Problem is specifically defined.
9th step：Select optimal solution
Individuality is ranked up according to individual fitness, chooses the solution of fitness highest, and output result.
Real number chromosome coding
System provides a kind of coding method and decoding algorithm of gene locus based on cipher table.Encryption algorithm is known objective
Knowledge is converted into mathematical knowledge, and decoding algorithm is for being simply reduced into objective knowledge by mathematics.Gene code is addressable port, i.e. root
Call the different coded methods just can be with according to different business demands.
The cipher table of real coding
The gene locus of real coding
An objective knowledge is represented with item chromosome, chromosome arranges genomic constitution according to certain order by multiple, no
Same gene has different data types, but unification is encoded according to real number, what gene was ordered into.
xn=z, bool ... enum }
Wherein xnFor chromosome, that is, an objective fact.Z, bool ... enum is to arrange according to certain order
Gene.
The generation of gene locus is very simple, it is assumed that the problem of solution has n known variables, it is only necessary to press n variable
According to sequential organization into a gene vectors.
xn={ x1, x2... xn}
Encoded adaptor and decoding adapter
Under conditions of gene locus, real coding is carried out according to cipher table and referred to as encode module.And enter to encoding module
Row inversionization referred to as decodes module.The supporting appearance of encoding and decoding adapter, is realized by way of interface definition.
Produce real number initial population
Initial population is the combination of feasibility solution and infeasible solution, quantity of only investigating, accuracy of not investigating.But preferably
Initial population possesses more preferable popularity, and can avoid the local convergence of genetic algorithm.Therefore the system is using uniform point
The random algorithm of cloth generates initial population.
Random call encryption algorithm generates several chromosomes,
1. each gene on chromosome, in its span, draws its correspondence using the stochastic variable of Homogeneous Analysis
Real number value.
2. the genic value for calculating is combined into into chromosome according to gene locus.
3. chromosome as several is continuously generated, population is constituted.The number of chromosome is defaulted as 80.
Selection opertor and penalty
Selection opertor includes disjunctive programming function and penalty,
1:Planning function is planning function chapters and sections herein.
2:Penalty, is punished by the way of R functionals by force.
One is eliminated by equality constraint therein to constraints, following constraint is obtained：
1.vscWhen≤0.6, it is constrained to following
gi-gmax≤0
gmin-gi≤0
For the penalty function of constraints it is：
For each gi, i=1,2,3 ..., n are defined as follows penalty function：
Then total penalty function：
2.vscDuring ＞ 0.6, it is constrained to following
gi-gmax≤0
gmin-gi≤0
For each gi, i=1,2,3 ..., n are defined as follows penalty function：
Then total penalty function：
Although the present invention is disclosed above with preferred embodiment, so which is not limited to the present invention.Skill belonging to of the invention
Has usually intellectual in art field, without departing from the spirit and scope of the present invention, when can be used for a variety of modifications and variations.Cause
This, protection scope of the present invention ought be defined depending on those as defined in claim.
Claims (6)
1. a kind of Dynamic Signal lamp appraisal procedure based on genetic algorithm, it is characterised in that include：
Step 1, initialization, obtain following information by crossing numbering：The phase configuration at crossing, the corresponding track of each phase place,
It is the identifier marking in track, the saturation volume rate in each track, the traffic capacity in each track, 15 minutes flows in each track, every
Individual phase place key track packet, peak hour factor, delay and parking weight, incremental delay correction factor, upstream and downstream linkage are repaiied
Positive coefficient, the minimax green time of each phase place, the minimax cycle time of each phase place and the damage of each phase place
The mistake time；
Step 2, definition track group, wherein under some phase place, all tracks for possessing right-of-way on same section are defined as one
Individual track group；
Step 3, the core clearance track group for finding out current phase place, if wherein：Track all possesses right-of-way in all phase places
In the case of, the track is removed in the group of track；
Step 4, the crucial track for finding out phase place；
Step 5, decision theory minimum period and maximum cycle；
Step 6, the saturation for judging each phase place key track；
Step 7, determination are for the penalty in cycle；
Step 8, the planning function determined under non-supersaturation phase place, and call genetic function to solve the optimal solution of the planning function.
2. the Dynamic Signal lamp appraisal procedure based on genetic algorithm according to claim 1, it is characterised in that abovementioned steps
In 2, the decision condition of track group is：
1st, obtain all of track for possessing right-of-way under phase place A；
2nd, these tracks are grouped according to section, possess same road segment ID for one group.
3. the Dynamic Signal lamp appraisal procedure based on genetic algorithm according to claim 1, it is characterised in that abovementioned steps
In 4, find out phase place crucial track implement including：
1st, after core track group completes track screening, can there are two kinds of situations in each section
Situation 1：There is track group in phase place, then execution step：
1) find out v/s in the group of track and, than maximum track, define the crucial track that the track is the section；
2) find out in all track groups of phase place, v/s defines the crucial track that the track is phase place than maximum track；
Situation 2：There is no track group in phase place, then execution step：
1) v/s of the crucial track group of the phase place is set to into 0.1；
2nd, there is the situation of at least one track group in the section corresponding to phase place；The car of maximum flow is chosen from the group of track directly
The track is defined as crucial track by road；
3rd, certain phase place does not possess crucial track, because only that a track, then the phase place directly runs minimum green light.
4. the Dynamic Signal lamp appraisal procedure based on genetic algorithm according to claim 1, it is characterised in that abovementioned steps
In 5, decision theory minimum period and maximum cycle are implemented as follows：
Theoretical according to Robert Webster delay, the theoretical minimum period is：
If：Y >=1, then the cycle is equal to the Cmin in data；
The theoretical maximum cycle is：
If：Y >=1, then the cycle is equal to the Cmax in data；
Wherein Y be the V/S of all phase places than sum, L is multiplied by 9 for phase place number.
5. the Dynamic Signal lamp appraisal procedure based on genetic algorithm according to claim 1, it is characterised in that abovementioned steps
The computing formula of 6 saturations for judging each phase place key track as：
6. a kind of Dynamic Signal lamp assessment system based on genetic algorithm, it is characterised in that include：At least one processor；
Memorizer；
Wherein, the memorizer is arranged for depositing data and the program module used for processor, described program module bag
Include for performing the programmed instruction of the method for any one in aforementioned claim 1-5.
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| CN106971566A (en) * | 2017-05-04 | 2017-07-21 | 无锡安邦电气股份有限公司 | Self-adaptation control method based on genetic algorithm |
| CN107393319A (en) * | 2017-08-31 | 2017-11-24 | 长安大学 | It is a kind of to prevent Single Intersection to be lined up the signal optimal control method overflowed |
| CN107393319B (en) * | 2017-08-31 | 2020-06-19 | 长安大学 | Signal optimization control method for preventing single cross port queuing overflow |
| CN111597700A (en) * | 2020-05-09 | 2020-08-28 | 北京百度网讯科技有限公司 | Signal control algorithm evaluation method and device, electronic equipment and readable storage medium |
| CN111597700B (en) * | 2020-05-09 | 2023-08-15 | 北京百度网讯科技有限公司 | Signal control algorithm evaluation method and device, electronic equipment and readable storage medium |
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