CN109544948A - A kind of traffic lights countdown prediction technique based on navigation system - Google Patents
A kind of traffic lights countdown prediction technique based on navigation system Download PDFInfo
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- CN109544948A CN109544948A CN201811238348.9A CN201811238348A CN109544948A CN 109544948 A CN109544948 A CN 109544948A CN 201811238348 A CN201811238348 A CN 201811238348A CN 109544948 A CN109544948 A CN 109544948A
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- traffic lights
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
Abstract
The traffic lights countdown prediction technique based on navigation system that the present invention relates to a kind of, comprising the following steps: 1: the traffic lights countdown casting of first traffic lights of automobile direction of advance is carried out；2: obtaining the time instant that more vehicles pass through the traffic lights respectively；3: multiple time instants that step 2 is got are included into data group D；4: three variables of setting, the respectively corresponding green light initial moment T of the signal lamp direction of advance0, green light duration Tg, red light duration Tr；5: generating N group Ti=(T0,Tg,Tr)；6: by the lack part formed without vehicle by crossing in vehicle is formed by crossing in a green time accumulation point part and a red light, finding optimal T0, TgAnd Tr.The duration of energy Accurate Prediction traffic lights red light and green light of the present invention and they replace at the time of, prompt driver in front of traffic lights respectively residue how many second, it enables a driver to be smoothly through traffic lights by count down information come regulation speed.
Description
Technical field
The present invention relates to the technical fields of traffic lights countdown prediction more particularly to a kind of based on navigation system
Traffic lights countdown prediction technique.
Background technique
Currently, having the position of display traffic lights on the navigation maps such as Amap, Baidu map and Tencent's map
Function, however, these maps cannot all show red light or green light remaining time in traffic lights.
If expecting red light or green light remaining time in traffic lights, need by with traffic police department cooperation, from it
The information of traffic lights switching moment is obtained in system.Which can accurately acquire traffic lights remaining time, however require that
The cooperation of traffic police department carries out data sharing.
For this purpose, this patent proposes a kind of prediction algorithm of traffic lights countdown, mainly pass through user on auto navigation
Red light in traffic lights, which is extrapolated, with the positional distance and vehicle speed information of traffic lights (considers asking for safety factor
Topic, amber light takes into account red light), the duration of green light, traffic lights alternating at the time of and red light and the remaining number of seconds of green light, make
User can be smoothly through traffic lights by count down information come regulation speed.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide it is a kind of can Accurate Prediction traffic lights red light and
The duration of green light and they at the time of replace, in front of prompt driver traffic lights respectively residue how many seconds based on leading
The traffic lights countdown prediction technique of boat system.
To achieve the above object, technical solution provided by the present invention are as follows:
A kind of traffic lights countdown prediction technique based on navigation system, comprising the following steps:
S1: the traffic lights countdown casting of first traffic lights B of automobile A direction of advance is carried out；
S2: the time instant that more vehicles pass through first traffic lights B respectively is obtained；
S3: multiple time instants that step S2 is got are included into data group D；
S4: three variables of setting, the respectively corresponding green light initial moment T of the signal lamp direction of advance0, green light continue when
Between Tg, red light duration Tr；
S5: N group T is generatedi=(T0,Tg,Tr)；
S6: by vehicle is formed by crossing in a green time accumulation point part and a red light without vehicle
By the lack part that crossing is formed, optimal T is found0, TgAnd Tr。
Further, specific step is as follows for the step S1 progress traffic lights countdown casting:
The location information of the running automobile A on road is obtained using the api interface of the GPS of navigation software offer, then
After automobile A chooses stroke, by the map api interface of navigation software, the driving information of automobile A is obtained, including automobile A's
Section where updating primary moment travel speed, driving direction, travel route in 0.5 second and automobile A the trip will by
Traffic lights list and will by the signal lamp crossing；Have according to the driving information of automobile, and in automobile A running section
When the section of first traffic lights, first traffic lights B information of traffic lights list is obtained, it is soft according to navigating
Part provide 2D map pai interface, we it is available to automobile A arrive the traffic lights actual travel distance, be arranged one away from
From error, in allowable range of error, take that automobile A has passed through traffic lights B as, then according to the moment traffic lights institute
Place's state plays corresponding voice prompting.Such as: if traffic lights are in red light phase, broadcasting red light remaining time；If traffic
Signal lamp is in green light phase, then broadcasts green light remaining time.
Further, the step S6 finds optimal T0, TgAnd TrSpecific step is as follows:
S6-1: random population initialization:
Population scale is set as Chrom, gene number is Nvars, and binary coding is coding mode, the value range of gene
It is 125 < 27, so digit after coding are as follows: Nvars*7, gen are genetic algebra, and the following are chromosomes:
Ti={ X1, X2, X3…Xnvars, I=1,2,3 ... Chrom；
S6-2: calculating fitness is carried out to random population using fitness function:
Select fitness function:
Wherein, f is adaptive value, and C is penalty factor, T0,TrAnd TgFor genotypic variance, mod (Di, T) it is available current when
Between be which in corresponding traffic light a cycle T in stage, T is time of traffic lights cycle Tg+Tr；
S6-3: using wheel disc stake algorithm, calculates Population adaptation value summation, and the adaptive value for calculating separately each chromosome is same
The ratio of group's adaptive value summation selects the chromosome for participating in breeding using random wheel disc；
S6-4: judge whether to reach termination condition according to genetic algebra and fitness variance；If reaching termination condition, tie
Beam iteration obtains optimal TgAnd Tr, otherwise, enter step S6-5；
S6-5: genetic algorithm is mated and is made a variation；
S6-6: return step S6-2.
Further, the step S6-5 genetic algorithm is mated and made a variation, and specific step is as follows:
S6-5-1: it mates:
Setting mating probability 0.8, thus at random to each chromosome generate one 0 to 1 at random between number, if the number is small
In mating probability, then homologue participates in mating, is otherwise not involved in mating；
Then, the natural number for carrying out 0 to Nvars*7-1 to the chromosome for participating in mating is used as mating position, according to mating position
Come determine exchange base because position；
S6-5-2: it makes a variation:
Assuming that mutation probability be 0.1, generate one 0 to 1 random number at random to each chromosome, if the number less than 0.1,
Then the gene participates in genetic mutation；
Then, the natural number for carrying out 0 to Nvars*7-1 to the chromosome for participating in mating is used as variation position, according to mating position
To determine the position of genetic mutation；And the value of genetic mutation randomly selects and becomes 0 or 1；
Genetic algebra gen adds 1.
Compared with prior art, the principle and advantage of this programme is as follows:
Using the api interface for the GPS that navigation software provides, to obtain the location information (longitude and latitude of the running automobile A on road
Degree), then after automobile A chooses stroke, by the map api interface of navigation software, obtain the driving information of automobile A, packet
Include the A of automobile updates primary moment travel speed, driving direction, travel route place section and automobile A the trip for 0.5 second
Will by traffic lights list and will by the signal lamp crossing.According to the driving information of automobile, and in automobile A
When running section has the section of first traffic lights, first traffic lights B letter of traffic lights list is obtained
Breath, according to the 2D map pai interface that navigation software provides, we are available to automobile A to the actual travel road of the traffic lights
A range error is arranged in journey, and distance d is in allowable range of error, and automobile A present speed is not that 0 (may be for 0
Stop), take that automobile A has passed through traffic lights B as；Then, the moment that multiple automobile A passes through traffic lights B is obtained
Moment, and multiple time instants are included into data group D.After obtaining enough data D, start to predict traffic lights countdown:
Random population is firstly generated, calculating fitness then is carried out to random population using fitness function；After fitness has been calculated, adopt
With wheel disc stake algorithm, population is selected to compete, after judging fitness variance and genetic algebra, selection is mated and is made a variation,
Or it completes to calculate, exit the program.
At the time of the duration and their alternatings of this programme energy Accurate Prediction traffic lights red light and green light, prompt
Traffic lights respective residue how many second, enable a driver to through count down information come regulation speed, successfully in front of driver
Pass through traffic lights.
Detailed description of the invention
Fig. 1 is time instant schematic diagram when more vehicles pass through traffic lights；
Fig. 2 is the time diagram (a) (b) that random parameter is formed.
Fig. 3 is a kind of flow chart of the traffic lights countdown prediction technique based on navigation system of the present invention.
Specific embodiment
The present invention is further explained in the light of specific embodiments:
It is shown in Figure 3, a kind of traffic lights countdown prediction technique based on navigation system described in the present embodiment,
The following steps are included:
S1: the traffic lights countdown casting for carrying out first traffic lights B of automobile A direction of advance (considers safety factor
The problem of, amber light takes into account red light), specific as follows:
The location information of the running automobile A on road is obtained using the api interface of the GPS of navigation software offer, then
After automobile A chooses stroke, by the map api interface of navigation software, the driving information of automobile A is obtained, including automobile A's
Section where updating primary moment travel speed, driving direction, travel route in 0.5 second and automobile A the trip will by
Traffic lights list and will by the signal lamp crossing；Have according to the driving information of automobile, and in automobile A running section
When the section of first traffic lights, first traffic lights B information of traffic lights list is obtained, it is soft according to navigating
Part provide 2D map pai interface, we it is available to automobile A arrive the traffic lights actual travel distance, be arranged one away from
From error, in allowable range of error, take that automobile A has passed through traffic lights B as, then according to the moment traffic lights institute
Place's state plays corresponding voice prompting.
Such as: if traffic lights are in red light phase, broadcasting red light remaining time；If traffic lights are in green light shape
State then broadcasts green light remaining time.
S2: the time instant that more vehicles pass through first traffic lights B respectively is obtained, as shown in Fig. 1.
In Fig. 1, horizontal axis is the actual change situation of first traffic lights continuously multiple period red lights and green light, t1,
t2,t3,t4……tn-1,tnFor the time instant for thering is vehicle to be recorded when passing through traffic lights.
S3: multiple time instants that step S2 is got are included into data group D, D={ t1,t2,t3,t4……tn-1,tn}；
S4: three variables of setting, the respectively corresponding green light initial moment T of the signal lamp direction of advance0, green light continue when
Between Tg, red light duration Tr；
S5: N group T is generatedi=(T0,Tg,Tr)；
According to TiThree parameters, a time diagram about traffic lights signal intensity is made, as shown in Fig. 2；
In figure, one group of producible time diagram of every group of random parameter；In time diagram 2 (a), TgFor green time, at this moment
Comparison diagram 1, it is assumed that point (at the time of vehicle is locating when passing through the traffic lights crossroad) major part in Fig. 1 falls in the time
T in Fig. 2 (a)gIn the range of, and largely point does not fall in the T in Fig. 2 (a) to Fig. 1rIn the range of, then judge that this group of parameter is
It is more conform with the solution of optimization problem (the fitness function f that the parameter obtains is comparatively smaller).As a same reason, in Fig. 1
Point only has fraction to fall in Fig. 2 (b) TgIn (in green light), and even there is partial dot to fall in TrIn (in red light), then judge the group
Than upper group random parameter of random parameter is farther (the fitness function f that the parameter obtains is comparatively bigger) apart from optimal solution.
Therefore, the present embodiment is converted into optimization problem after entering step S6:
S6: by vehicle is formed by crossing in a green time accumulation point part and a red light without vehicle
By the lack part that crossing is formed, optimal T is found0, TgAnd Tr.Specific step is as follows:
S6-1: random population initialization:
Population scale is set as Chrom, gene number is Nvars, and binary coding is coding mode, the value range of gene
It is 125 < 27, so digit after coding are as follows: Nvars*7, gen are genetic algebra, and the following are chromosomes:
Ti={ X1, X2, X3…Xnvars, I=1,2,3 ... Chrom；
In the present embodiment, Chrom=250, Nvars=3；
S6-2: calculating fitness is carried out to random population using fitness function:
Select fitness function:
Wherein, f is adaptive value, and C is penalty factor, T0,TrAnd TgFor genotypic variance, mod (Di, T) it is available current when
Between be which in corresponding traffic light a cycle T in stage, T is time of traffic lights cycle Tg+Tr；
S6-3: using wheel disc stake algorithm, calculates Population adaptation value summation, and the adaptive value for calculating separately each chromosome is same
The ratio of group's adaptive value summation selects the chromosome for participating in breeding using random wheel disc；
S6-4: judge whether to reach termination condition according to genetic algebra and fitness variance；
Termination condition are as follows:
Genetic algebra gen is greater than 2000 and fitness variance is less than 20；
If reaching termination condition, terminate iteration, obtains optimal TgAnd Tr, otherwise, enter step S6-5；
S6-5: genetic algorithm is mated and is made a variation, the specific steps are as follows:
S6-5-1: it mates:
Mating probability is set as 0.8, thus at random to each chromosome generate one 0 to 1 at random between number, if the number
Less than 0.8, then homologue participates in mating, is otherwise not involved in mating；
Then, the natural number for carrying out 0 to Nvars*7-1 to the chromosome for participating in mating is used as mating position, according to mating position
Come determine exchange base because position；
S6-5-2: it makes a variation:
Assuming that mutation probability be 0.1, generate one 0 to 1 random number at random to each chromosome, if the number less than 0.1,
Then the gene participates in genetic mutation；
Then, the natural number for carrying out 0 to Nvars*7-1 to the chromosome for participating in mating is used as variation position, according to mating position
To determine the position of genetic mutation；And the value of genetic mutation randomly selects and becomes 0 or 1；
Genetic algebra gen adds 1；
S6-6: return step S6-2.
The present embodiment mainly uses genetic algorithm to simulate the evolutionary process of an Artificial Population, passes through selection
(Selection), mate (Crossover) and make a variation mechanism such as (Mutation), all retains one group of time in each iteration
Choosing individual repeats this process, and population is after several generations evolve, and ideally its fitness reaches the state of near-optimization.
At the time of the duration and their alternatings of this programme energy Accurate Prediction traffic lights red light and green light, prompt
Traffic lights respective residue how many second, enable a driver to through count down information come regulation speed, successfully in front of driver
Pass through traffic lights.
The examples of implementation of the above are only the preferred embodiments of the invention, and implementation model of the invention is not limited with this
It encloses, therefore all shapes according to the present invention, changes made by principle, should all be included within the scope of protection of the present invention.
Claims (4)
1. a kind of traffic lights countdown prediction technique based on navigation system, which comprises the following steps:
S1: the traffic lights countdown casting of first traffic lights B of automobile A direction of advance is carried out；
S2: the time instant that more vehicles pass through first traffic lights B respectively is obtained；
S3: multiple time instants that step S2 is got are included into data group D；
S4: three variables of setting, respectively the green light initial moment T in some direction of signal lamp0, green light duration Tg, it is red
Lamp duration Tr；
S5: N group T is generatedi=(T0,Tg,Tr)；
S6: by passing through in vehicle is formed by crossing in a green time accumulation point part and a red light without vehicle
The lack part that crossing is formed, finds optimal T0, TgAnd Tr。
2. a kind of traffic lights countdown prediction technique based on navigation system according to claim 1, feature exist
In the step S1 carries out traffic lights countdown casting, and specific step is as follows:
The location information that the running automobile A on road is obtained using the api interface of the GPS of navigation software offer, then in vapour
Vehicle A, by the map api interface of navigation software, obtains the driving information of automobile A after navigation software chooses stroke, including
Section and automobile A the trip are wanted where 0.5 second of automobile A updates primary moment travel speed, driving direction, travel route
By traffic lights list and will by the signal lamp crossing；It is travelled according to the driving information of automobile, and in automobile A
When there is the section of first traffic lights in section, first traffic lights B information of traffic lights list is obtained, according to
Navigation software provide 2D map pai interface, we it is available to automobile A to the traffic lights actual travel distance, and
One range error is set, in allowable range of error, takes that automobile A has passed through traffic lights B as, is then handed over according to the moment
Ventilating signal lamp status plays corresponding voice prompting.
3. a kind of traffic lights countdown prediction technique based on navigation system according to claim 1, feature exist
In the step S6 finds optimal T0, TgAnd TrSpecific step is as follows:
S6-1: random population initialization:
Population scale is set as Chrom, gene number is Nvars, and binary coding is coding mode, and the value range of gene is
125<27, so digit after coding are as follows: Nvars*7, gen are genetic algebra, and the following are chromosomes:
Ti={ X1, X2, X3…Xnvars, I=1,2,3 ... Chrom；
S6-2: calculating fitness is carried out to random population using fitness function:
Select fitness function:
Wherein, f is adaptive value, and C is penalty factor, T0,TrAnd TgFor genotypic variance, mod (Di, T) and available current time is
Which in corresponding traffic light a cycle T, T are time of traffic lights cycle T in stageg+Tr；
S6-3: using wheel disc stake algorithm, calculates Population adaptation value summation, calculates separately the same group of adaptive value of each chromosome
The ratio of adaptive value summation selects the chromosome for participating in breeding using random wheel disc；
S6-4: judge whether to reach termination condition according to genetic algebra and fitness variance；If reaching termination condition, terminate to change
In generation, obtains optimal T0,TgAnd Tr, otherwise, enter step S6-5；
S6-5: genetic algorithm is mated and is made a variation；
S6-6: return step S6-2.
4. a kind of traffic lights countdown prediction technique based on navigation system according to claim 3, feature exist
In the step S6-5 genetic algorithm is mated and made a variation, and specific step is as follows:
S6-5-1: it mates:
Setting mating probability 0.8, thus at random to each chromosome generate one 0 to 1 at random between number, if the number be less than hand over
With probability, then homologue participates in mating, is otherwise not involved in mating；
Then, the natural number for carrying out 0 to Nvars*7-1 to the chromosome for participating in mating is used as mating position, is determined according to mating position
Determine exchange base because position；
S6-5-2: it makes a variation:
Assuming that mutation probability is 0.1, one 0 to 1 random number is generated at random to each chromosome, if the number less than 0.1, is somebody's turn to do
Gene participates in genetic mutation；
Then, the natural number for carrying out 0 to Nvars*7-1 to the chromosome for participating in mating is used as variation position, is determined according to mating position
Determine the position of genetic mutation；And the value of genetic mutation randomly selects and becomes 0 or 1；
Genetic algebra gen adds 1.
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| CN111721317A (en) * | 2020-06-30 | 2020-09-29 | 北京百度网讯科技有限公司 | Method and device for generating navigation information |
| CN112017425A (en) * | 2019-05-28 | 2020-12-01 | 上海擎感智能科技有限公司 | Navigation time calculation method |
| CN113840765A (en) * | 2019-05-29 | 2021-12-24 | 御眼视觉技术有限公司 | System and method for vehicle navigation |
| CN115331471A (en) * | 2022-08-10 | 2022-11-11 | 阿波罗智联(北京)科技有限公司 | Intelligent navigation scheduling method, device, equipment and storage medium based on V2X |
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