CN106846837A - A kind of traffic light intelligent control system, traffic lights intelligent control method and device - Google Patents
A kind of traffic light intelligent control system, traffic lights intelligent control method and device Download PDFInfo
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- G—PHYSICS
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- 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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Abstract
The invention discloses a kind of traffic light intelligent control system, including for gathering the ultrasound examination module of the information of vehicle flowrate in correspondence track, the image capture module of pedestrian image for gathering correspondence track crossing, for carrying out image analysis processing to pedestrian image to obtain pedestrian's quantity information and the traffic lights intelligent control module for being instructed according to pedestrian's quantity information and information of vehicle flowrate generation Traffic signal control and the traffic signals lamp module for the fluorescent lifetime according to the Traffic signal control instruction corresponding traffic lights of adjustment；Image capture module and the ultrasound examination module are connected with the traffic lights intelligent control module, and traffic lights intelligent control module is connected with corresponding traffic signals lamp module.The invention also discloses a kind of traffic lights intelligent control method and traffic lights intelligent controlling device.The present invention can effectively improve the vehicle pass-through efficiency of traffic intersection, so as to effectively alleviate urban traffic blocking.
Description
Technical field
The present invention relates to technical field of traffic control, more particularly to a kind of traffic light intelligent control system, traffic lights intelligence
Control method and device.
Background technology
Dependence increasingly with modern society to communications and transportation, traffic lights becomes indispensable during people live one
Point.Although the need for traditional traffic light control system can meet commander's crossing traffic to a certain extent, with motor-driven
The development of vehicle, the growth of population and urbanization, original traffic light control system has shown obvious shortcoming：Traffic lights
Time is relatively fixed, it is impossible to adjust traffic lights (red light, amber light and green light) with the change of vehicle flowrate and flow of the people
The display time, therefore existing traffic light control system can not well improve the vehicle pass-through efficiency of traffic intersection so that
Urban traffic blocking can not effectively be alleviated.
The content of the invention
Regarding to the issue above, it is an object of the invention to provide a kind of traffic light intelligent control system, it can be effectively
The vehicle pass-through efficiency of traffic intersection is improved, so as to effectively alleviate urban traffic blocking；The present invention also aims to carry
For a kind of traffic lights intelligent control method and a kind of traffic lights intelligent controlling device.
To achieve these goals, one aspect of the present invention provides a kind of traffic light intelligent control system, and it includes ultrasound
Ripple detection module, image capture module, traffic lights intelligent control module and traffic signals lamp module；Described image acquisition module
And the ultrasound examination module is connected with the traffic lights intelligent control module, the traffic lights intelligent control module with
Corresponding traffic signals lamp module connection；Wherein, the ultrasound examination module, the vehicle flowrate for gathering corresponding track is believed
Breath；Described image acquisition module, the pedestrian image for gathering corresponding track crossing；Wherein, the track crossing with it is described
Track is located at same traffic intersection；The traffic lights intelligent control module, for carrying out image point to the pedestrian image
Analysis is processed, and to obtain pedestrian's quantity information, and carries out data mould according to pedestrian's quantity information and the information of vehicle flowrate
Paste analysis, is instructed with the Traffic signal control for obtaining corresponding crossing；The traffic signals lamp module, for according to the friendship
The fluorescent lifetime of the corresponding traffic lights of ventilating signal lamp control instruction real-time adjustment.
Another aspect of the present invention provides a kind of traffic lights intelligent control method, and it is comprised the following steps：
The information of vehicle flowrate in the corresponding track that reception is gathered by ultrasound examination module, and receive by image capture module
The pedestrian image at the corresponding track crossing for collecting；
Image analysis processing is carried out to the pedestrian image, to obtain pedestrian's quantity information；
Data fuzzy analysis are carried out to pedestrian's quantity information and the information of vehicle flowrate, to generate corresponding intersection
Traffic signal control is instructed, and Signalized control instruction is sent into traffic signals lamp module, so that the traffic is believed
Signal lamp module instructs the fluorescent lifetime of the corresponding traffic lights of real-time adjustment according to the Traffic signal control.
Further, the step " image analysis processing being carried out to the pedestrian image, to obtain pedestrian's quantity information "
Specially：
The current pedestrian image is processed as current gray-scale map；
The current gray level figure is carried out into gray scale difference value with default image background model to compare, and according to comparative result pair
The current gray level figure carries out binary conversion treatment, to obtain corresponding binary image；
Denoising is carried out to the binary image, to obtain corresponding denoising image；
The object pixel connected domain of corresponding denoising image is obtained, according to the statistics of the object pixel connected domain to getting
Analysis, obtains pedestrian's quantity information.
Further, the step " the current pedestrian image is processed as into current gray-scale map " is specially：
The pedestrian image to currently getting cuts, to obtain the current cutting image of suitable size；
Gray processing treatment is carried out to the current cutting image, to obtain the current gray-scale map.
Further, the current gray level figure " is carried out gray scale difference value ratio by the step with default image background model
Compared with, and binary conversion treatment is carried out to the current gray level figure according to comparative result, and to obtain corresponding binary image " it is specific
For：
The pixel of the current gray level figure is carried out into gray scale with the corresponding pixel of described image background model one by one
Concrete value comparison analysis, to obtain all target pixel points in the current gray level figure；Wherein, the target pixel points are and institute
State the pixel of the gray difference value more than default threshold value of the corresponding pixel of image background model；
The gray value of the target pixel points in the current gray level figure that will be got is set to 0, and by the current gray level
The gray value of the rest of pixels point in figure is set to 255, to obtain corresponding binary image；Wherein, the target pixel points
Collection area is expressed as the object pixel connected domain.
Further, the step " denoising being carried out to the binary image, to obtain corresponding denoising image "
Specially：
Image enhancement processing is carried out to the binary image；
Image after processing enhancing is first expanded post-etching treatment, to obtain corresponding denoising image.
Further, state step and " the object pixel connected domain of corresponding denoising image is obtained, according to the target to getting
The statistical analysis of pixel connected domain, obtains pedestrian's quantity information " it is specially：
Obtain the object pixel connected domain of the denoising image；
Judge the provincial characteristics parameter values of each object pixel connected domain whether in default scope；Wherein,
Region area, the length and width of the provincial characteristics parameter including the pixel connected domain when valid pixel ratio；
The quantity of object pixel connected domain of the statistical regions characteristic parameter numerical value in default scope, and generated with this
Pedestrian's quantity information.
Further, described traffic lights intelligent control method is further comprising the steps of：
The background image of multiple to being collected in the range of the scheduled time carries out gray processing treatment, to obtain corresponding background
Gray level image；Wherein, there is no the image of pedestrian on the corresponding crossing that the background image is photographed for image capture module, it is described
Before the shooting time of background image is located at the shooting time of the current pedestrian image, and both shooting times are close；
Denoising is carried out to each background gray level image, to obtain pretreatment image；
The statistical analysis of pixel is carried out to each pretreatment image, and corresponding image is set up according to statistic analysis result
Background model；
Treatment is updated to described image background model according to the newest background image for getting.
Further, the step " carries out data to obscure according to pedestrian's quantity information and the information of vehicle flowrate
Analysis, is instructed with the Traffic signal control for generating corresponding intersection, and Signalized control instruction is sent into traffic signals
Lamp module, so that the traffic signals lamp module instructs the corresponding traffic signals of real-time adjustment according to the Traffic signal control
The fluorescent lifetime of lamp " is specially：
The information of vehicle flowrate and pedestrian's quantity information that will be received are analyzed calculating, are tied with obtaining corresponding calculating
Really；
The result of calculation is converted into corresponding traffic lights fuzzy quantity；
Corresponding traffic lights fuzzy control rule is set up according to the traffic lights fuzzy quantity；
Enter the resolving and reasoning of row information according to the traffic lights fuzzy control rule, believed with obtaining corresponding traffic
Signal lamp fuzzy control quantity；
The traffic lights fuzzy control quantity is carried out into sharpening conversion process, it is clear to obtain corresponding domain scope
Amount, and the clear change of variable of domain scope is processed as the actual controlled quentity controlled variable of traffic lights；
Corresponding Traffic signal control is generated according to the actual controlled quentity controlled variable of the traffic lights to instruct and described in being sent to
Traffic signals lamp module, so that the traffic signals lamp module instructs real-time adjustment corresponding according to the Traffic signal control
The fluorescent lifetime of traffic lights.
Still further aspect of the present invention additionally provides a kind of traffic lights intelligent controlling device, and it includes：
Receiving unit, for receiving the information of vehicle flowrate in the corresponding track gathered by ultrasound examination module, and receives
The pedestrian image at the corresponding track crossing collected by image capture module；
Graphics processing unit, for carrying out image analysis processing to the pedestrian image, to obtain pedestrian's quantity information；
Signaling control unit, for carrying out fuzzy point of data to pedestrian's quantity information and the information of vehicle flowrate
Analysis, is instructed with the Traffic signal control for generating corresponding intersection, and Signalized control instruction is sent into traffic lights
Module, so that the traffic signals lamp module instructs the corresponding traffic lights of real-time adjustment according to the Traffic signal control
Fluorescent lifetime.
The traffic light intelligent control system, the traffic intelligent control method and the traffic intelligent that the present invention is provided
Control device, the information of vehicle flowrate in corresponding track can be collected by the ultrasound examination module, by described image
Acquisition module can get the pedestrian image at correspondence track crossing, and can be right by the traffic lights intelligent control module
The pedestrian image carries out image analysis processing, to obtain the pedestrian's quantity information in the pedestrian image, it is possible to receiving
To pedestrian's quantity information and the information of vehicle flowrate carry out data fuzzy analysis, to obtain corresponding traffic lights
Control instruction, the traffic signals lamp module is according to the corresponding friendship of Traffic signal control instruction real-time adjustment for receiving
The fluorescent lifetime of ventilating signal lamp, to realize effective control of wagon flow and the stream of people to traffic intersection.As can be seen here, the present invention can be with
Vehicle flowrate and the fluorescent lifetime of flow of the people adjust automatically traffic lights according to traffic intersection, can effectively reduce each crossing car
The mean delay time such that it is able to effectively improve the vehicle pass-through efficiency of traffic intersection, and then can effectively alleviate city
City's traffic congestion.
Brief description of the drawings
In order to illustrate more clearly of technical scheme, the accompanying drawing to be used needed for implementation method will be made below
Simply introduce, it should be apparent that, drawings in the following description are only some embodiments of the present invention, general for this area
For logical technical staff, on the premise of not paying creative work, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is a kind of structural representation of traffic light intelligent control system provided in an embodiment of the present invention；
Fig. 2 is a kind of structural representation of traffic lights intelligent control module provided in an embodiment of the present invention；
Fig. 3 is the workflow diagram of the information of vehicle flowrate in the corresponding track of ultrasound examination module collection shown in Fig. 1；
Fig. 4 is a kind of flow chart of traffic lights intelligent control method provided in an embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
Fig. 1 and Fig. 2 is referred to, on the one hand the embodiment of the present invention provides a kind of traffic light intelligent control system, and it includes
Ultrasound examination module 1, image capture module 2, traffic lights intelligent control module 3 and traffic signals lamp module 4；Described image
Acquisition module 2 and the ultrasound examination module 1 are connected with the traffic lights intelligent control module 3, the traffic lights intelligence
Energy control module 3 is connected with corresponding traffic signals lamp module 4；Wherein,
The ultrasound examination module 1, the information of vehicle flowrate for gathering corresponding track, i.e. near traffic intersection
Each track is all correspondingly arranged at least one ultrasound examination module 1；
Described image acquisition module 2, the pedestrian image for gathering correspondence crossing, i.e. each crossing is to that should have
Individual image capture module 2 carries out the shooting, collecting of the pedestrian image at crossing；
The traffic lights intelligent control module 3, including for receiving connecing for the information of vehicle flowrate and the pedestrian image
Receive unit 30, for carrying out image analysis processing, the graphics processing unit to obtain pedestrian's quantity information to the pedestrian image
31, and for carrying out data fuzzy analysis to pedestrian's quantity information and the information of vehicle flowrate, to obtain accordingly
The signaling control unit 32 of the Traffic signal control instruction at crossing；
The traffic signals lamp module 4, for instructing the corresponding traffic of real-time adjustment according to the Traffic signal control
The fluorescent lifetime of signal lamp (green light, red light or amber light).
, it is necessary to explanation, the track crossing is respectively positioned on same traffic road with the track in the present invention is implemented
Mouth (for example, crossroad or T-shaped road junction) place, wherein, every road at traffic intersection is respectively provided with a plurality of track, and every
Road is to that should have track crossing.
, it is necessary to explanation, the signaling control unit 32 is by corresponding signal output interface in the present invention is implemented
Module is attached with corresponding traffic signals lamp module 4, and so described signaling control unit 32 can be by the traffic signals
Lamp control instruction gives corresponding traffic signals lamp module 4 by the signal output interface module transfer.
In embodiments of the present invention, it is preferable that the traffic light intelligent control system also includes that communication module (can be with
It is wire communication module or wireless communication module), the communication module is electrically connected with the traffic lights intelligent control module 3,
The communication module is used for the information of vehicle flowrate that will be collected and pedestrian's quantity information uploads to traffic control center platform, with
Facilitating traffic direction central platform is controlled decision-making (preferably by traffic according to the information of vehicle flowrate and pedestrian's quantity information
The staff of command centre's platform carries out Analysis of Policy Making, naturally it is also possible to be that the terminal of traffic control center platform is carried out independently
Analysis decision), after traffic control center platform makes a policy, the communication module will receive the control for issuing and refer to
Make, then the traffic lights intelligent control module 3 controls the traffic signals lamp module 4 to realize difference according to the control instruction
The luminous work of traffic lights, so as to complete the long-range control and scheduling to traffic, and also can for greater flexibility process burst thing
Part, while also improving the operational efficiency of traffic system.
In embodiments of the present invention, the ultrasound examination module 1, preferably by probe assembly and main controller
(main control part of Tiny6410 embedded boards) is constituted.Wherein, every top in track is correspondingly provided with a probe assembly.Institute
Stating probe assembly includes the transmitting probe for launching ultrasonic wave and the receiving transducer for receiving the ultrasonic wave for firing back.
Refer to figure, 3, the principle of the measurement of ultrasound examination module 1 vehicle flowrate is：Probe assembly is launched by track downwards
The ultrasonic wave that ultrasonic wave and reception are reflected, then the main controller measures the time difference between the two, and is calculated with this
Ultrasonic wave launch and receive passed by apart from h, now the main controller judging distance h whether less than probe assembly apart from road surface
Height H and default height of car H1 is (that is, it is judged that condition is：h<H-H1), if so, indicating that vehicle is just travelled in probe group
The lower section of part, then proceedes to judge whether subsequent time h is equal to H (that is, it is judged that condition is：H=H), if so, representing upper a period of time
Carve the vehicle below the probe assembly to have been moved off, now Current vehicle number is added one by the main controller, it is last described
Main controller carries out calculating analysis to the vehicle number measured in the predetermined time, to determine the average of each track in the unit interval
Vehicle flowrate.
In embodiments of the present invention, each described image acquisition module 2 includes that at least one is used to shoot pedestrian's figure
CCD (the Charged Coupled Device) imageing sensor (i.e. camera) of picture and for obtaining the pedestrian image
And the pedestrian image that will be got is sent to the field programmable gate array of described image processing unit 31
(Field-Programmable Gate Array, FPGA) module, wherein, ccd image sensor is arranged on corresponding track
The top at crossing；FPGA module includes CMOS controllers, sdram controller and SDRAM memory, wherein, CMOS controllers
Operation sequential for controlling ccd image sensor, and be efficiently sent to the pedestrian image that ccd image sensor is photographed
In SDARM controllers；Sdram controller is used to store the pedestrian image in SDRAM memory, when FPGA module needs
Can be transferred from SDRAM memory when the pedestrian image is sent into described image processing unit 31.
In embodiments of the present invention, described image processing unit 31 is preferably and uses TMS320C6748 development boards, the exploitation
Plate uses the high-end Floating-point DSP-TMS320C6748 of T I, and dominant frequency is up to 450MHZ, DDR internal memories 1Gbit, 1 64Mbit
Norflash, 1 1Gbit nandflash, 1 128Mbit SPI Flash, 1 video input utilizing camera interface, 2 road sounds
Frequency stream interface, 1 USB_OTG, 1 SD card, 1 100 m ethernet, (one of multiplexing RS485 connects 2 RS232 interfaces
Mouthful), 1 IIC EPROM, extend out EMIF parallel bus and GPIO bus extenders.Described image processing unit 31 will be corresponding
Image is converted into YUV forms by RGB forms, then extracts Y-component in YUV forms as monochrome information to obtain corresponding gray scale
Figure.
In embodiments of the present invention, the signaling control unit 32 is preferably and uses Tiny6410 embedded boards.As schemed
Show, Tiny6410 is a embedded core board using ARM11 chips (Samsung S3C6410) as primary processor, support to install
Linux system, the plate is with three LCD interfaces, 4 wire resistive touchscreen interfaces, 100M standard network interfaces, standard DB9 five in addition
Line serial ports, the interfaces of Mini USB 2.0 etc., conveniently carry out embedded system program exploitation and visualization debugging.Wherein, it is described
Tiny6410 embedded boards are ARM11-Linux architecture systems as depicted.The CPU of Tiny6410 is based on ARM1176JZF-S
Core is designed, and is integrated with 256M Mobile DDR RAM, 256M/1GB SLC Nand flash storages, is installed on this basis
Linux2.6.38+Qtopia2+QtE4.8.5 system development environments carry out the data fuzzy algorithmic approach program of the embodiment of the present invention
Exploitation.
In embodiments of the present invention, the vehicle flowrate in corresponding track can be collected by the ultrasound examination module 1
Information, the pedestrian image at correspondence crossing can be got by described image acquisition module 2, and by the traffic lights intelligence
Control module 3 can carry out image analysis processing to the pedestrian image, to obtain the letter of the pedestrian's quantity in the pedestrian image
Breath, it is possible to data fuzzy analysis are carried out to the pedestrian's quantity information for receiving and the information of vehicle flowrate, to obtain
Corresponding Traffic signal control instruction, the traffic signals lamp module 4 refers to according to the Traffic signal control for receiving
The fluorescent lifetime of the corresponding traffic lights of real-time adjustment is made, to realize effective control of wagon flow and the stream of people to traffic intersection.
As can be seen here, the embodiment of the present invention can be luminous with flow of the people adjust automatically traffic lights according to the vehicle flowrate of traffic intersection
Time, can effectively reduce the mean delay time of each crossing vehicle such that it is able to which the vehicle for effectively improving traffic intersection leads to
Line efficiency, and then can effectively alleviate urban traffic blocking.
Fig. 4 is referred to, on the other hand the embodiment of the present invention provides a kind of traffic lights intelligence for being applied to above-mentioned control system
Energy control method, it includes step S1 to step S3：
S1, the information of vehicle flowrate in the corresponding track that reception is gathered by ultrasound examination module 1, and receive by IMAQ
The pedestrian image at the corresponding track crossing that module 2 is collected.
S2, image analysis processing is carried out to the pedestrian image, to obtain pedestrian's quantity information.
S3, data fuzzy analysis are carried out to pedestrian's quantity information and the information of vehicle flowrate, to generate corresponding road
The Traffic signal control instruction of mouth, and Signalized control instruction is sent to traffic signals lamp module 4, so that the friendship
Ventilating signal lamp module 4 instructs the fluorescent lifetime of the corresponding traffic lights of real-time adjustment according to the Traffic signal control.
Further, the step S3 specifically includes step S30 to step S35, and the step S30 to step S35, this
A little steps are loaded in the fuzzy controller in the traffic lights intelligent control module 3, and by described in form of software programs
Fuzzy controller is run：
S30, the information of vehicle flowrate that will be received and pedestrian's quantity information are analyzed calculating, to be calculated accordingly
As a result.
That is, analysis obtains the concrete numerical value and pedestrian's quantity of the vehicle flowrate in the information of vehicle flowrate for receiving
The concrete numerical value of the pedestrian's quantity in information.
S31, corresponding traffic lights fuzzy quantity is converted into by the result of calculation.
Wherein, the detailed process of conversion is：The result of calculation that will be received first is processed to become fuzzy controller
It is required that input quantity, secondly the input quantity that will treat carry out change of scale, be transformed to corresponding input quantity respective
These input quantities for having transformed to domain scope are finally carried out Fuzzy Processing by domain scope, make original accurately input quantity
Become traffic lights fuzzy quantity, and represented with corresponding fuzzy set.The purpose of fuzzy quantization is that input variable is mapped
To a range for suitable corresponding domain, so, accurate input data is just transformed into appropriate Linguistic Value or fuzzy set
Identifier.
Typically in actual applications by precise volume discretization, continuously value amount several grades, each grade of correspondence one will be divided into
Fuzzy set.The actual range of deviation x and deviation variation rate Δ x in control system is called the basic domain of these variables, if partially
Difference x basic domain be [- x ,+x], the universe of a fuzzy set that deviation x is taken for (- n ,-n+1,, 0, n-1, n), you can be given
The quantizing factor k of the obfuscation of precise volume.In embodiments of the present invention, the fuzzy subset of deviation delta x has 7：Honest, center,
It is just small, zero, it is negative it is small, negative in, it is negative big, the basic domain of deviation x is [- 11,11], obscure domain for [- 4, -3, -2, -1,0 ,+1,
+ 2 ,+3 ,+4], quantizing factor is K2=4- (- 4)/11- (- 11)=4/11.Additionally, deviation variation rate Δ x fuzzy subsets are same
There are 7：Very long, long, more long, medium, shorter, short, very short, the basic domains of deviation variation rate Δ x are [0,22].
S32, corresponding traffic lights fuzzy control rule is set up according to the traffic lights fuzzy quantity.
Wherein, the fuzzy control rule includes database and fuzzy rule base two parts, and database is mainly included
Classification number of the membership function of linguistic variable, the change of scale factor and fuzzy space etc., fuzzy rule base is included
A series of reflections represented with Fuzzy Linguistic Variable control the control rule of the experience and knowledge of expert.Wherein fuzzy control rule
It is that, by a kind of language representation of the Intuitive inference of people, fuzzy rule is generally formed by connecting by a series of relative, such as If-
Then, else, also, and, or etc..
Wherein, in order to realize fuzzy control, the embodiment of the present invention is two parts lighting time T points of green light：First
It is divided into fixed basic time (preferably 10 seconds, can according to actual needs carry out setting and modifying), as crossing vehicle parameter
Acquisition time T1；Part II be according to different directions vehicle flow change carry out fuzzy decision with obtain green light time delay when
Between T2, i.e., final lighting time of corresponding green light is T：T=T1+T2；Camera module can described in this twice
To gather pedestrian's number of the waiting at correspondence crossing.Wherein, because the vehicle of the North and South direction of traffic intersection is essentially all same
When it is static with circulation, the east-west direction of traffic intersection is similarly；As long as therefore taking a side in the North and South direction of traffic intersection
Traffic intersection is not yet passed to one of direction of the vehicle number maximum X and east-west direction that not yet pass traffic intersection
Vehicle number maximum Y, in sending into the fuzzy controller after being gathered by the ultrasonic acquisition module during actual motion, Ran Housuo
It is " if A and B then C " etc. 49 by using fuzzy condition statement to state the fuzzy control rule unit in fuzzy controller
Bar fuzzy condition statement is based on the actual traffic situation of traffic intersection, draws corresponding fuzzy control rule, and according to fuzzy
Control rule is concluded to obtain corresponding fuzzy control state table.
S33, the resolving and reasoning of row information are entered according to the traffic lights fuzzy control rule, to be handed over accordingly
Ventilating signal lamp fuzzy control quantity.
Wherein, the step is the core of fuzzy controller, and it has the inferential capability based on fuzzy concept of simulation people, its
Reasoning process is carried out based on the implication relation and inference rule in fuzzy logic.
Traffic lights fuzzy control quantity refers to on basic acquisition time basis based on the analysis to Current vehicle quantity
Upper additional green light delay time fuzzy quantity t2, wherein, the domain of green light delay time fuzzy quantity t2 is (0~20), and it is used
Gravity model appoach computing formula：T2=(1/2 × 4+1/2 × 4+1/2 × 8+1/2 × 8)/(1/2+1/2+1/2+1/2).Need explanation
It is that green light delay time fuzzy quantity t2 can also be calculated using maximum membership degree method or weighted mean method lamp algorithm, herein not
It is specifically limited.
In embodiments of the present invention, because vehicle maximum X, Y that the crossing of different directions not yet passes traffic intersection is needed
Different green light delay time fuzzy quantity t2 are corresponded to, if each data conciliates blur method meeting with fuzzy reasoning above
It is very complicated, it is necessary to calculate very multiple.Therefore fuzzy polling list can be quickly generated using the function in MATLAB, with
Quickly obtain the green light delay time fuzzy quantity t2 at all correspondence crossings.
S34, sharpening conversion process is carried out by the traffic lights fuzzy control quantity, to obtain corresponding domain scope
Clear amount, and the clear change of variable of domain scope is processed as the actual controlled quentity controlled variable of traffic lights.
That is, the fuzzy control quantity is become to represent the clear amount of domain scope and is would indicate that in domain through sharpening
The clear amount of scope is through change of scale into actual controlled quentity controlled variable.For example, green light delay time fuzzy quantity t2 is converted into for reality
Border controls the green light delay time controlled quentity controlled variable of corresponding green light, and correspondence is then controlled according to the green light delay time controlled quentity controlled variable
Green light realize the lasting bright light of green light delay time T2.
S35, generates corresponding Traffic signal control and instructs and be sent to according to the actual controlled quentity controlled variable of the traffic lights
The traffic signals lamp module 4, so that the traffic signals lamp module 4 instructs real-time adjustment according to the Traffic signal control
The fluorescent lifetime of corresponding traffic lights.
In foregoing invention embodiment, the fuzzy controller, it is based on the realization of Tiny6410 embedded boards, is used for
Control variables is calculated, fuzzy quantization treatment is performed, fuzzy control rule is set and is performed fuzzy reasoning and sharpening treatment etc.
Operation.In fuzzy polling list is downloaded to the Embedded flash of Tiny6410 or SD card, online query is realized,
Fuzzy polling list regards 11 × 16 matrix as, is continuously put into storage area, is carried out using base address+offset side-play amounts
Addressing can complete work of tabling look-up.
Further, the step S2 specifically includes step S20 to step S23：
S20, current gray-scale map is processed as by the current pedestrian image.
Preferably, step S20 specifically includes step S200 to step S201：
S200, the pedestrian image to currently getting cuts, to obtain the current cutting image of suitable size.
That is, the purpose that above-mentioned 31 pairs of pedestrian images of graphics processing unit are cut is to reduce successive image treatment
Workload, such that it is able to accelerate to the pedestrian image treatment efficiency.Wherein, the pedestrian image is gathered from described image
Exported in module 2, it is RGB color image.
S201, carries out gray processing treatment, to obtain the current gray-scale map to the current cutting image.
When above-mentioned graphics processing unit 31 gets the current cutting image, 31 pairs of institutes of described image processing unit
Stating the current image (for RGB color figure) that cuts carries out image gray processing treatment, and the current cutting image is converted into YUV lattice
Formula, the Y-component extracted in the YUV forms of the current cutting figure after conversion obtains the current gray-scale map as monochrome information,
Wherein monochrome information is：Y=0.299XR+0.587XG+0.114XB.
S21, carries out the current gray level figure gray scale difference value and compares with default image background model, and according to comparing knot
Fruit carries out binary conversion treatment to the current gray level figure, to obtain corresponding binary image.Wherein, described image background model
It is just to be had built up before the current gray level figure.
Preferably, the step S21 specifically includes step S210 to step S211：
S210, the pixel of the current gray level figure is carried out with the corresponding pixel of described image background model one by one
Gray scale difference value comparative analysis, to obtain all target pixel points in the current gray level figure；Wherein, the target pixel points with
The gray difference value of the corresponding pixel of described image background model is more than default threshold value.
S211, the gray value of the target pixel points in the current gray level figure that will be got is set to 0, and will be described current
The gray value of the rest of pixels point in gray-scale map is set to 255, to obtain corresponding binary image；Wherein, the object pixel
Point collection area be expressed as the object pixel connected domain, i.e., described object pixel connected domain be with the background model
Same pixel point position has the pixel region of otherness.For example, there is pedestrian, luggage case and road in the pedestrian image
Mouthful other background objects, i.e. the pedestrian image and the difference of the background model are that had more pedestrian, luggage case this is different
Picture material, therefore, pedestrian's pixel connected region and luggage case pixel connected domain are two kinds and institute in the pedestrian image
Stating each self-corresponding pixel position in background model has the pixel region of otherness.
Wherein, it is black that gray value is set to 0 target pixel points color in the picture, and gray value is set to 255
Rest of pixels point color in the picture is white, that is, the image for finally obtaining is binary image.By the current gray level figure
Image binaryzation is carried out, is so conducive to the further treatment of image, and the image is become simple and image data amount
Reduce, the image outline region of target interested can be highlighted.
S22, denoising is carried out to the binary image, to obtain corresponding denoising image.
Preferably, the step S22 specifically includes step S220 to step S221：
S220, the binary image carries out image enhancement processing.That is, calculated by using 3X3 sliding windows medium filtering
Method carries out the preliminary denoising of image to the binary image, to strengthen the effect of image.It is, of course, also possible to pass through other correlations
Algorithm for image enhancement carries out enhancing treatment to the binary image.
S221, the image after processing enhancing is first expanded post-etching treatment, to obtain corresponding denoising image.
Wherein, processed by first being expanded post-etching to image, can be with minuscule hole in blank map picture, in connection figure picture
The effect of adjacent object and smooth image boundary.
S23, obtains the object pixel connected domain of corresponding denoising image, according to the object pixel connected domain to getting
Statistical analysis, obtains pedestrian's quantity information.
Preferably, the step S23 specifically includes step S230 to step S232：
S230, obtains the object pixel connected domain of the denoising image.
In the step s 21, obtain corresponding binary image, and analyze the binary image
Target pixel points, therefore by obtaining the collection area of the target pixel points in the denoising image, you can get described going
Make an uproar the object pixel connected domain of image.Wherein, above-mentioned pedestrian's pixel connected domain is the object pixel connected domain for needing to obtain
One of which.
Whether S231, judge the provincial characteristics parameter values of each object pixel connected domain in default scope；
Wherein, region area, the length and width of the provincial characteristics parameter including the pixel connected domain when valid pixel ratio.
It is to judge to be all mesh of pedestrian's pixel connected domain to the purpose that each object pixel connected domain is judged
Mark pixel connected domain.Wherein, in embodiments of the present invention, it is preferable that the predetermined threshold value of the region area is set to 800 pixels,
The preset range of the length-width ratio is set to 0.2 to 4.0, and the preset range of the valid pixel ratio is set to 0.2 to 0.9.As long as
Judge the provincial characteristics parameter values of corresponding object pixel connected domain in default scope, then the object pixel connects
Logical domain is pedestrian's pixel connected domain.
S232, the quantity of object pixel connected domain of the statistical regions characteristic parameter numerical value in default scope, and with
This generation pedestrian's quantity information.
In embodiments of the present invention, the traffic lights intelligent control module 3 is believed by obtaining the vehicle flowrate in corresponding track
The pedestrian image at correspondence crossing is ceased and got, and image analysis processing is carried out by the pedestrian image, to obtain
Pedestrian's quantity information in the pedestrian image；Then to the pedestrian's quantity information for receiving and the information of vehicle flowrate
Data fuzzy analysis are carried out, is instructed with obtaining corresponding Traffic signal control, and Signalized control instruction is sent to
Traffic signals lamp module 4, so that the traffic signals lamp module 4 instructs real-time adjustment correspondence according to the Traffic signal control
Traffic lights fluorescent lifetime, to realize effective control of wagon flow and the stream of people to traffic intersection.As can be seen here, the present invention
Embodiment can be reduced effectively according to the vehicle flowrate of traffic intersection and the fluorescent lifetime of flow of the people adjust automatically traffic lights
The mean delay time of each crossing vehicle such that it is able to effectively improve the vehicle pass-through efficiency of traffic intersection, and then can have
Alleviate urban traffic blocking in effect ground.
In foregoing invention embodiment, it is preferable that described traffic lights intelligent control method also includes step S100 to step
Rapid S103：
S100, the background image of multiple to being collected in the range of the scheduled time carries out gray processing treatment, to obtain correspondence
Background gray level image；Wherein, there is no the figure of pedestrian on the corresponding crossing that the background image is photographed for image capture module 2
Picture.Because over time, the light and weather environment of traffic intersection can change (such as because black clouds blocks sun
Light and cause the dim of traffic intersection), therefore, the shooting time for setting the background image is located at current pedestrian's figure
Before the shooting time of picture, and both shooting times are close, and it is not multiple very big backgrounds that can so get otherness
Image.
Wherein, it is to the mode that the background image carries out gray processing treatment：The background image is converted into YUV lattice
Formula, the Y-component extracted in the YUV forms of the background image after conversion obtains the current gray-scale map as monochrome information, its
Middle monochrome information is：Y=0.299XR+0.587XG+0.114XB.
S101, carries out denoising, to obtain pretreatment image to each background gray level image.
Wherein, denoising is carried out to the background gray level image using 3X3 sliding windows median filtering algorithm.Need
Bright, may also take on other Denoising Algorithms carries out denoising to the background gray-scale map, is not specifically limited herein.
S102, the statistical analysis of pixel is carried out to each pretreatment image, and set up correspondence according to statistic analysis result
Image background model.
That is, by the statistical analysis of the same position pixel to each pretreatment image, each pixel is drawn
Grey level histogram, the wherein pixel value of pixel in being just distributed very much, to the component of R, G, B pixel value of each pixel
Statistical analysis is carried out respectively, can obtain the probability-distribution function of the stochastic variable of the pixel value components of each pixel, from
And the value fluctuation situation of the pixel value of each pixel can be drawn, pixel value components according to each pixel it is general
Rate distribution function sets up described image background model, and (i.e. one is used to be carried out with reference to the Road Junction Background for comparing with the pedestrian image
Image).It should be noted that described image background model compares in the gray scale difference value for carrying out pixel with the current gray level figure
During analysis, the picture size size of described image background model is consistent with the size of the current gray level figure.Specific practice
Can be：Described image background model is made to be cut with the current gray level figure identical；Or can be institute to collecting
State background image to make to be cut with the current pedestrian image identical, then set up corresponding further according to the background image of gray processing
Image background model.
S103, treatment is updated according to the newest background image for getting to described image background model.
Over time, the illumination brightness in the monitoring scene of described image acquisition module 2 can be changed, and it is adopted
The brightness of the image for collecting can also change, it is therefore desirable to which the image background model to having built up is updated, to improve
The degree of accuracy of successive image treatment.Wherein, it is to the mode that described image background model updates：To the newest Background for getting
As the pixel value of the pixel for carrying out each same position with the background image collected in default time range is carried out
Statistical analysis, i.e., calculate analysis and foreground point ratiometer point counting by using the analysis of pixel value mean value computation, pixel value variance
The analysis modes such as analysis, come every with the background image collected in default time range to the newest background image for getting
The pixel value of one pixel of same position is analyzed, so as to set up the multidate information of the pixel of each same position
Window (can so obtain the fluctuation situation of the pixel value of each pixel), wherein, foreground point ratio refers in N number of pixel
The ratio shared by the number of times of foreground point is judged as in point sampling value, when the acquisition time of the image being analyzed is when default
Between in the range of when, the prospect ratio is judged more than default threshold value, at this moment just according to the N number of background image for collecting recently
In each pixel sampled value fluctuation situation, to be updated to described image background model.
This preferred embodiment can set up image background model and is updated to improve by image background model
The degree of accuracy of successive image treatment.
Refer to Fig. 2, embodiment of the present invention still further aspect additionally provide a kind of traffic lights intelligent controlling device (equivalent to
Above-mentioned traffic lights intelligent control module 3), it includes：Receiving unit 30, for receiving what is gathered by ultrasound examination module 1
The information of vehicle flowrate in corresponding track, and receive pedestrian's figure at the corresponding track crossing collected by image capture module 2
Picture；Graphics processing unit 31, for carrying out image analysis processing to the pedestrian image, to obtain pedestrian's quantity information；Signal
Control unit 32, for carrying out data fuzzy analysis to pedestrian's quantity information and the information of vehicle flowrate, to generate phase
Answer the Traffic signal control at crossing to instruct, and Signalized control instruction is sent to traffic signals lamp module 4, so that institute
State traffic signals lamp module 4 according to the Traffic signal control instruct the corresponding traffic lights of real-time adjustment it is luminous when
Between.
Further, described image processing unit 31 includes：Image gray processing subelement, for by the current pedestrian
Image procossing is current gray-scale map；Image binaryzation subelement, for by the current gray level figure and default image background
Model carries out gray scale difference value comparing, and carries out binary conversion treatment to the current gray level figure according to comparative result, to obtain correspondence
Binary image：Denoising subelement, for carrying out denoising to the binary image, to obtain corresponding denoising figure
Picture；Graphical analysis subelement, the object pixel connected domain for obtaining corresponding denoising image, according to the target picture to getting
The statistical analysis of plain connected domain, obtains pedestrian's quantity information.
Further, the figure gray processing subelement, including：Secondary units are cut, for the institute to currently getting
State pedestrian image to be cut, to obtain the current cutting image of suitable size；Gray processing processes secondary units, for described
The current image that cuts carries out gray processing treatment, to obtain the current gray-scale map.
Further, described image binaryzation subelement includes：Gray scale difference value compares secondary units, for will be described current
The pixel of gray-scale map carries out gray scale difference value comparative analysis with the corresponding pixel of described image background model one by one, to obtain
All target pixel points in the current gray level figure；Wherein, the target pixel points are corresponding with described image background model
Pixel gray difference value be more than default threshold value；Binaryzation secondary units, for the current gray level that will be got
The gray value of the target pixel points in figure is set to 0, and the gray value of the rest of pixels point in the current gray level figure is set to
255, to obtain corresponding binary image；Wherein, the collection area of the target pixel points is expressed as the object pixel company
Logical domain.
Further, the denoising subelement includes：Image enhaucament secondary units, for being carried out to the binary image
Image enhancement processing；Image expansion corrode secondary units, for processing enhancing after image first expanded post-etching treatment,
To obtain corresponding denoising image.
Further, described image analysis subelement includes：Obtain secondary units, for obtaining the denoising image in
Object pixel connected domain；Judge secondary units, the provincial characteristics parameter values for judging each object pixel connected domain are
It is no in default scope；Wherein, region area, the length and width of the provincial characteristics parameter including the pixel connected domain are when
Valid pixel ratio；Statistics secondary units, for object pixel of the statistical regions characteristic parameter numerical value in default scope
The quantity of connected domain, and pedestrian's quantity information is generated with this.
In embodiments of the present invention, by the receiving unit 30 can obtain corresponding track information of vehicle flowrate and
The pedestrian image at correspondence crossing is got, and image can be carried out to the pedestrian image by described image processing unit 31
Analyzing and processing, to obtain the pedestrian's quantity information in the pedestrian image；Then can be right by the signaling control unit 32
The pedestrian's quantity information for receiving and the information of vehicle flowrate carry out data fuzzy analysis, are believed with obtaining corresponding traffic
Signal lamp control instruction, and Signalized control instruction is sent to traffic signals lamp module 4, so that the traffic lights mould
Block 4 instructs the fluorescent lifetime of the corresponding traffic lights of real-time adjustment according to the Traffic signal control, to realize to traffic
The wagon flow at crossing and effective control of the stream of people.As can be seen here, the embodiment of the present invention can be according to the vehicle flowrate of traffic intersection and people
The fluorescent lifetime of flow adjust automatically traffic lights, can effectively reduce the mean delay time of each crossing vehicle, so as to
The vehicle pass-through efficiency of traffic intersection is enough effectively improved, and then can effectively alleviate urban traffic blocking.
In foregoing invention embodiment, it is preferable that described image processing unit 31 also includes：
Background image gray processing subelement, for carrying out ash to the background image of multiple collected in the range of the scheduled time
Degreeization treatment, to obtain corresponding background gray level image；Wherein, the background image be image capture module 2 photograph it is right
Answering does not have the image of pedestrian on crossing, the shooting time of the background image be located at the current pedestrian image shooting time it
Before, and both shooting times are close；
Background image denoising subelement, for carrying out denoising to each background gray level image, to be pre-processed
Image；
Image background model sets up subelement, the statistical analysis for carrying out pixel to each pretreatment image, and root
Analysis result sets up corresponding image background model according to statistics；
Image background model modification subelement, for according to the newest background image for getting to described image background model
It is updated treatment.
This preferred embodiment can set up image background model and is updated to improve by image background model
The degree of accuracy of successive image treatment.
Above disclosed is only some preferred embodiments of the invention, can not limit the power of the present invention with this certainly
Sharp scope, one of ordinary skill in the art will appreciate that realizing all or part of flow of above-described embodiment, and weighs according to the present invention
Profit requires made equivalent variations, still falls within the covered scope of invention.
One of ordinary skill in the art will appreciate that all or part of flow in realizing above-described embodiment method, can be
The hardware of correlation is instructed to complete by computer program, described program can be stored in a computer read/write memory medium
In, the program is upon execution, it may include such as the flow of the embodiment of above-mentioned each method.Wherein, described storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random Access
Memory, RAM) etc..
Claims (10)
1. a kind of traffic light intelligent control system, it is characterised in that including ultrasound examination module, image capture module, traffic
Lamp intelligent control module and traffic signals lamp module；Described image acquisition module and the ultrasound examination module are and institute
The connection of traffic lights intelligent control module is stated, the traffic lights intelligent control module is connected with corresponding traffic signals lamp module；Its
In,
The ultrasound examination module, the information of vehicle flowrate for gathering corresponding track；
Described image acquisition module, the pedestrian image for gathering corresponding track crossing；Wherein, the track crossing with it is described
Track is located at same traffic intersection；
The traffic lights intelligent control module, for carrying out image analysis processing to the pedestrian image, to obtain pedestrian's quantity
Information, and data fuzzy analysis are carried out according to pedestrian's quantity information and the information of vehicle flowrate, to obtain corresponding road
The Traffic signal control instruction of mouth；
The traffic signals lamp module, for instructing the corresponding traffic lights of real-time adjustment according to the Traffic signal control
Fluorescent lifetime.
2. a kind of traffic lights intelligent control method, it is characterised in that comprise the following steps：
Receive the information of vehicle flowrate in the corresponding track gathered by ultrasound examination module and collected by image capture module
Corresponding track crossing pedestrian image；
Image analysis processing is carried out to the pedestrian image, to obtain pedestrian's quantity information；
Data fuzzy analysis are carried out to pedestrian's quantity information and the information of vehicle flowrate, to generate the traffic of corresponding intersection
Signalized control is instructed, and Signalized control instruction is sent into traffic signals lamp module, so that the traffic lights
Module instructs the fluorescent lifetime of the corresponding traffic lights of real-time adjustment according to the Traffic signal control.
3. traffic lights intelligent control method according to claim 2, it is characterised in that the step " is schemed to the pedestrian
As carrying out image analysis processing, to obtain pedestrian's quantity information " it is specially：
The current pedestrian image is processed as current gray-scale map；
The current gray level figure is carried out into gray scale difference value with default image background model to compare, and according to comparative result to described
Current gray level figure carries out binary conversion treatment, to obtain corresponding binary image；
Denoising is carried out to the binary image, to obtain corresponding denoising image；
The object pixel connected domain of corresponding denoising image is obtained, according to the statistical of the object pixel connected domain to getting
Analysis, obtains pedestrian's quantity information.
4. traffic lights intelligent control method according to claim 3, it is characterised in that the step is " described in current
Pedestrian image is processed as current gray-scale map " it is specially：
The pedestrian image to currently getting cuts, to obtain the current cutting image of suitable size；
Gray processing treatment is carried out to the current cutting image, to obtain the current gray-scale map.
5. traffic lights intelligent control method according to claim 3, it is characterised in that the step is " by the current ash
Degree figure carries out gray scale difference value and compares with default image background model, and carries out two to the current gray level figure according to comparative result
Value is processed, to obtain corresponding binary image " it is specially：
The pixel of the current gray level figure is carried out into gray scale difference value with the corresponding pixel of described image background model one by one
Comparative analysis, to obtain all target pixel points in the current gray level figure；Wherein, the target pixel points are and the figure
As the pixel of the gray difference value more than default threshold value of the corresponding pixel of background model；
The gray value of the target pixel points in the current gray level figure that will be got is set to 0, and by the current gray level figure
The gray value of rest of pixels point be set to 255, to obtain corresponding binary image；Wherein, the set of the target pixel points
Region representation is the object pixel connected domain.
6. traffic lights intelligent control method according to claim 3, it is characterised in that the step is " to the binaryzation
Image carries out denoising, to obtain corresponding denoising image " it is specially：
Image enhancement processing is carried out to the binary image；
Image after processing enhancing is first expanded post-etching treatment, to obtain corresponding denoising image.
7. traffic lights intelligent control method according to claim 3, it is characterised in that the step " obtains corresponding going
Make an uproar the object pixel connected domain of image, according to the statistical analysis of the object pixel connected domain to getting, obtain pedestrian's quantity letter
Breath " is specially：
Obtain the object pixel connected domain of the denoising image；
Judge the provincial characteristics parameter values of each object pixel connected domain whether in default scope；Wherein, it is described
Region area, the length and width of provincial characteristics parameter including the pixel connected domain when valid pixel ratio；
The quantity of object pixel connected domain of the statistical regions characteristic parameter numerical value in default scope, and pedestrian is generated with this
Quantity information.
8. the traffic lights intelligent control method according to claim 3 to 6 any one, it is characterised in that also including following
Step：
The background image of multiple to being collected in the range of the scheduled time carries out gray processing treatment, to obtain corresponding background gray scale
Image；Wherein, there is no the image of pedestrian, the background on the corresponding crossing that the background image is photographed for image capture module
Before the shooting time of image is located at the shooting time of the current pedestrian image, and both shooting times are close；
Denoising is carried out to each background gray level image, to obtain pretreatment image；
The statistical analysis of pixel is carried out to each pretreatment image, and corresponding image background is set up according to statistic analysis result
Model；
Treatment is updated to described image background model according to the newest background image for getting.
9. traffic lights intelligent control method according to claim 2, it is characterised in that the step is " according to the pedestrian
Quantity information and the information of vehicle flowrate carry out data fuzzy analysis, are referred to the Traffic signal control for generating corresponding intersection
Order, and Signalized control instruction is sent to traffic signals lamp module, so that the traffic signals lamp module is according to
The fluorescent lifetime of the corresponding traffic lights of Traffic signal control instruction real-time adjustment " is specially：
The information of vehicle flowrate and pedestrian's quantity information that will be received are analyzed calculating, to obtain corresponding result of calculation；
The result of calculation is converted into corresponding traffic lights fuzzy quantity；
Corresponding traffic lights fuzzy control rule is set up according to the traffic lights fuzzy quantity；
Enter the resolving and reasoning of row information according to the traffic lights fuzzy control rule, to obtain corresponding traffic lights
Fuzzy control quantity；
The traffic lights fuzzy control quantity is carried out into sharpening conversion process, is clearly measured with obtaining corresponding domain scope,
And the clear change of variable of domain scope is processed as the actual controlled quentity controlled variable of traffic lights；
Corresponding Traffic signal control is generated according to the actual controlled quentity controlled variable of the traffic lights to instruct and be sent to the traffic
Signal lamp module, so that the traffic signals lamp module instructs the corresponding traffic of real-time adjustment according to the Traffic signal control
The fluorescent lifetime of signal lamp.
10. a kind of traffic lights intelligent controlling device, it is characterised in that including：
Receiving unit, the information of vehicle flowrate for receiving the corresponding track gathered by ultrasound examination module, and receive by scheming
As the pedestrian image at the corresponding track crossing that acquisition module is collected；
Graphics processing unit, for carrying out image analysis processing to the pedestrian image, to obtain pedestrian's quantity information；
Signaling control unit, for carrying out data fuzzy analysis to pedestrian's quantity information and the information of vehicle flowrate, with
The Traffic signal control instruction of corresponding intersection is generated, and Signalized control instruction is sent to traffic signals lamp module,
So that the traffic signals lamp module instructs the hair of the corresponding traffic lights of real-time adjustment according to the Traffic signal control
The light time.
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| CN112101272B (en) * | 2020-09-23 | 2024-05-14 | 阿波罗智联(北京)科技有限公司 | Traffic light detection method, device, computer storage medium and road side equipment |
| WO2021189970A1 (en) * | 2020-10-28 | 2021-09-30 | 平安科技（深圳）有限公司 | Intelligent control method and system for traffic light, and storage medium and computing device |
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| CN114373312A (en) * | 2022-01-13 | 2022-04-19 | 南京融才交通科技研究院有限公司 | Urban traffic intelligent control method and system based on traffic informatization |
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Application publication date: 20170613 |