CN111583672A - Intelligent traffic light control method, system and device - Google Patents
Intelligent traffic light control method, system and device Download PDFInfo
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Abstract
The invention discloses an intelligent traffic light control method, a system and a device, which adopt a multi-stage fuzzy algorithm, calculate the total urgency of a waiting phase based on the traffic density and the residence time of the waiting phase, calculate the delay time based on the current traffic density and the total urgency of the waiting phase, and make final judgment according to a preset decision, can adjust the phase green-to-green ratio in real time to meet different traffic demands of traffic flow at peak and low valley periods, reduce the average delay time of vehicles, improve the road traffic capacity of the existing traffic facilities, and automatically adjust a timing scheme along with the changed traffic flow, thereby ensuring that the control effect can reach the optimum no matter how the environment changes.
Description
Technical Field
The invention relates to an intelligent traffic light control method, system and device, and belongs to the technical field of intelligent traffic.
Background
The traffic jam problem is increasingly severe due to the development of the automobile industry and the acceleration of the urbanization process, and the road jam prolongs the on-road time of the automobile on one hand, and on the other hand, the exhaust emission of the automobile is aggravated by frequent starting and acceleration, so that the urban life quality is seriously influenced. The intelligent traffic light control system is used as a key component of the intelligent traffic system, can reasonably guide road traffic flow to a certain extent, reduces tail gas emission, noise pollution and energy consumption, and has important practical significance for improving urban traffic conditions.
Research on intelligent traffic light control systems mainly focuses on the following two aspects: optimizing a traffic control strategy of the crossroad and detecting traffic information. Most of the existing commonly used intelligent traffic lights adopt fixed timing control, namely, a relatively reasonable fixed timing scheme is distributed according to the counted historical traffic flow data of each intersection, so that the flexibility is poor, dynamic adjustment can not be carried out according to the actual traffic flow of a road network, and the optimal control effect can not be ensured.
Disclosure of Invention
The invention provides an intelligent traffic light control method, system and device, which solve the problems disclosed in the background technology.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
an intelligent traffic light control method comprises the steps of,
collecting traffic flow information, calculating the number of vehicles to be passed and the length of a vehicle queue to be passed in the current passing phase, and calculating the number of vehicles to be passed, the length of the vehicle queue to be passed and the residence time of the vehicles to be passed in each waiting phase;
calculating the traffic density of the current passing phase according to the number of the vehicles to be passed in the current passing phase and the length of the vehicle queue to be passed in the current passing phase, and calculating the traffic density of each waiting phase according to the number of the vehicles to be passed in the waiting phase and the length of the vehicle queue to be passed in the waiting phase;
calculating the total urgency of the waiting phases according to the traffic flow density of each waiting phase, the residence time of the vehicles to be passed of each waiting phase and a preset first-level fuzzy algorithm;
calculating the delay time of the traffic light of the current passing phase according to the total urgency of the waiting phase, the current passing phase traffic density and a preset secondary fuzzy algorithm;
obtaining the final traffic light delay time according to the traffic light delay time of the current passing phase, the total urgency of the waiting phase and a preset decision;
and sending out corresponding traffic light and timer control instructions according to the final traffic light delay time length.
The control principle of the first-level fuzzy algorithm is that the residence time of the vehicle to be passed in the waiting phase is in direct proportion to the total urgency of the waiting phase, and the traffic density of the waiting phase is in direct proportion to the total urgency of the waiting phase.
The control principle of the two-stage fuzzy algorithm is that the current traffic flow density of the passing phase is in direct proportion to the delay time of the traffic light, and the total urgency of the waiting phase is in inverse proportion to the delay time of the traffic light.
The pre-set decision is that,
in response to the fact that the total urgency of the waiting phase is greater than or equal to the urgency threshold and the delay time of the traffic light in the current passing phase is smaller than the time threshold, passing right conversion is carried out according to the minimum preset traffic light time, and finally the delay time of the traffic light is the minimum preset traffic light time;
in response to the fact that the total urgency of the waiting phase is smaller than the urgency threshold and the delay time of the traffic light in the current passing phase is larger than or equal to the time threshold, passing right conversion is carried out according to the maximum preset traffic light time, and finally the delay time of the traffic light is the maximum preset traffic light time;
and under other conditions, the right of way is converted according to the delay time of the traffic light in the current passing phase, and finally the delay time of the traffic light is the delay time of the traffic light in the current passing phase.
And carrying out right-of-way conversion according to the degree of urgency of each waiting phase, wherein the degree of urgency of the waiting phases is obtained by calculation according to the traffic density, the residence time of the vehicles to be passed and a preset first-level fuzzy algorithm.
An intelligent traffic light control system, which comprises,
the acquisition and calculation module: collecting traffic flow information, calculating the number of vehicles to be passed and the length of a vehicle queue to be passed in the current passing phase, and calculating the number of vehicles to be passed, the length of the vehicle queue to be passed and the residence time of the vehicles to be passed in each waiting phase;
the traffic density module: calculating the traffic density of the current passing phase according to the number of the vehicles to be passed in the current passing phase and the length of the vehicle queue to be passed in the current passing phase, and calculating the traffic density of each waiting phase according to the number of the vehicles to be passed in the waiting phase and the length of the vehicle queue to be passed in the waiting phase;
a first-level fuzzy control module: calculating the total urgency of the waiting phases according to the traffic flow density of each waiting phase, the residence time of the vehicles to be passed of each waiting phase and a preset first-level fuzzy algorithm;
a secondary fuzzy control module: calculating the delay time of the traffic light of the current passing phase according to the total urgency of the waiting phase, the current passing phase traffic density and a preset secondary fuzzy algorithm;
a final duration obtaining module: obtaining the final traffic light delay time according to the traffic light delay time of the current passing phase, the total urgency of the waiting phase and a preset decision;
a control instruction module: and sending out corresponding traffic light and timer control instructions according to the final traffic light delay time length.
An intelligent traffic light control device comprises a controller, a plurality of composite traffic flow detection devices, a plurality of timers and a plurality of traffic lights;
the composite traffic flow detection equipment collects traffic flow information of the phase and sends the traffic flow information to the controller; the controller is internally provided with an intelligent traffic light control system for controlling traffic lights and a timer.
Along the advancing direction of a vehicle, each guide lane is sequentially provided with a composite traffic flow detection device A, a composite traffic flow detection device B and a composite traffic flow detection device C, the composite traffic flow detection device A is arranged at the front end of a stop line, a distance is reserved between the composite traffic flow detection device B and the composite traffic flow detection device A, a traffic flow detection area is arranged between the composite traffic flow detection device B and the composite traffic flow detection device A, and the composite traffic flow detection device C is close to the composite traffic flow detection device B.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform a smart traffic light control method.
A computing device comprising one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing a smart traffic light control method.
The invention achieves the following beneficial effects: the invention adopts a multi-stage fuzzy algorithm, calculates the total urgency of the waiting phase based on the traffic density and the residence time of the waiting phase, calculates the delay time based on the traffic density of the current phase and the total urgency of the waiting phase, and makes a final judgment according to a preset decision, can adjust the phase green-to-green ratio in real time to meet the traffic demands of different traffic flows in peak periods and low valley periods, reduces the average delay time of vehicles, improves the road traffic capacity of the existing traffic facilities, can automatically adjust the timing scheme along with the changed traffic flow, thereby ensuring that the control effect can reach the optimum no matter how the environment changes.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a block diagram of the apparatus of the present invention;
FIG. 3 is an installation layout diagram of the composite traffic flow detecting device;
FIG. 4 is a diagram of a multi-stage fuzzy control architecture;
FIG. 5 is a basic block diagram of a fuzzy algorithm;
FIG. 6 is a four-phase setup of the intelligent traffic light;
FIG. 7 illustrates a traffic light on/off scheme for a signal period;
fig. 8 is a flow chart of the apparatus.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, a method for controlling an intelligent traffic light includes the following steps:
step 1, collecting traffic flow information including traffic flow, speed, occupied time, head time interval and the like, calculating the number of vehicles to be passed and the length of a vehicle queue to be passed in a current passing phase, and calculating the number of vehicles to be passed, the length of the vehicle queue to be passed and the residence time of the vehicles to be passed in each waiting phase.
And 2, calculating the traffic density of the current passing phase according to the number of the vehicles to be passed in the current passing phase and the length of the vehicle queue to be passed in the current passing phase, and calculating the traffic density of each waiting phase according to the number of the vehicles to be passed in the waiting phase and the length of the vehicle queue to be passed in the waiting phase.
And 3, calculating the urgency of each waiting phase according to the traffic density of each waiting phase, the residence time of the vehicles to be passed in each waiting phase and a preset first-level fuzzy algorithm, and calculating the total urgency of the waiting phases according to the urgency of each waiting phase.
The total urgency of the waiting phases is the sum or mean of all the urgency of the waiting phases, which depends on whether the preset urgency threshold is the sum or the mean.
The control principle of the first-level fuzzy algorithm is as follows: the residence time of the vehicles waiting for passing in the waiting phase is in direct proportion to the total urgency of the waiting phase, and the traffic density of the waiting phase is in direct proportion to the total urgency of the waiting phase.
And 4, calculating the traffic light delay time (generally the delay time of a green light) of the current traffic phase according to the total urgency of the waiting phase, the current traffic phase traffic density and a preset two-stage fuzzy algorithm.
The control principle of the secondary fuzzy algorithm is as follows: the traffic density of the current passing phase is in direct proportion to the delay time of the traffic light, and the total urgency of the waiting phase is in inverse proportion to the delay time of the traffic light.
And 5, obtaining the final traffic light delay time according to the traffic light delay time of the current passing phase, the total urgency of the waiting phase and a preset decision.
The preset decision is as follows:
1) in response to the fact that the total urgency of the waiting phase is greater than or equal to the urgency threshold and the delay time of the traffic light in the current passing phase is smaller than the time threshold, passing right conversion is carried out according to the minimum preset traffic light time, and finally the delay time of the traffic light is the minimum preset traffic light time;
the right of way conversion is specifically carried out according to the urgency level of each waiting phase, namely the right of way is obtained by priority when the urgency level of the waiting phase is high;
2) in response to the fact that the total urgency of the waiting phase is smaller than the urgency threshold and the delay time of the traffic light in the current passing phase is larger than or equal to the time threshold, passing right conversion is carried out according to the maximum preset traffic light time, and finally the delay time of the traffic light is the maximum preset traffic light time;
3) and under other conditions, the right of way is converted according to the delay time of the traffic light in the current passing phase, and finally the delay time of the traffic light is the delay time of the traffic light in the current passing phase.
Step 5, corresponding traffic light and timer control instructions are sent out according to the final traffic light delay time length
The software system corresponding to the method comprises,
the acquisition and calculation module: collecting traffic flow information, calculating the number of vehicles to be passed and the length of a vehicle queue to be passed in the current passing phase, and calculating the number of vehicles to be passed, the length of the vehicle queue to be passed and the residence time of the vehicles to be passed in each waiting phase;
the traffic density module: calculating the traffic density of the current passing phase according to the number of the vehicles to be passed in the current passing phase and the length of the vehicle queue to be passed in the current passing phase, and calculating the traffic density of each waiting phase according to the number of the vehicles to be passed in the waiting phase and the length of the vehicle queue to be passed in the waiting phase;
a first-level fuzzy control module: calculating the total urgency of the waiting phases according to the traffic flow density of each waiting phase, the residence time of the vehicles to be passed of each waiting phase and a preset first-level fuzzy algorithm;
a secondary fuzzy control module: calculating the delay time of the traffic light of the current passing phase according to the total urgency of the waiting phase, the current passing phase traffic density and a preset secondary fuzzy algorithm;
a final duration obtaining module: obtaining the final traffic light delay time according to the traffic light delay time of the current passing phase, the total urgency of the waiting phase and a preset decision;
a control instruction module: and sending out corresponding traffic light and timer control instructions according to the final traffic light delay time length.
The method and the system adopt a multi-stage fuzzy algorithm, calculate the total urgency of the waiting phase based on the traffic density and the residence time of the waiting phase, calculate the delay time based on the traffic density of the current phase and the total urgency of the waiting phase, make final judgment according to a preset decision, adjust the phase green-to-letter ratio in real time to meet different traffic demands of traffic flows at peak and low valley periods, reduce the average delay time of vehicles, improve the road traffic capacity of the existing traffic facilities, and simultaneously, the method and the system are in a continuous measurement state and can automatically adjust a timing scheme along with the changed traffic flow, thereby ensuring that the control effect can be optimal no matter how the environment changes.
As shown in fig. 2, an intelligent traffic light control device includes a controller, an input button, a plurality of composite traffic flow detection devices, a plurality of timers, and a plurality of traffic lights. The input keys, all the composite traffic flow detection devices, all the timers and all the traffic lights are in communication with the controller.
The signal is transmitted by adopting the latest narrowband Internet of things NB-IoT, the NB-IoT technology supports cellular data connection of low-power consumption equipment in a wide area network, the advantages of wide coverage, low power consumption, large connection, low cost and the like are integrated, the signal is directly transmitted through an operator base station during working, the installation and maintenance cost of a gateway is saved, and the signal transmission is more stable, so that the signal transmission is more suitable for vehicle flow detection than the traditional gateway transmission.
The composite traffic flow detection equipment is used for acquiring traffic flow information of the phase and sending the traffic flow information to the controller. The composite vehicle flow detection equipment comprises a plurality of sensors connected with a CPU (Central processing Unit), and generally comprises a geomagnetic sensor and a microwave radar sensor, a vehicle is detected through the plurality of sensors, the CPU judges whether the vehicle passes through the sensors through a fusion algorithm, the limitation of the single geomagnetic sensor on anti-interference performance and sensitivity is broken through, the detection accuracy can reach more than 99%, the equipment adopts a mode of being buried in the ground, a battery is arranged in the equipment, the cost is low, the size is small, the installation and the maintenance are convenient, the detection range is adjustable, and the destructiveness to the road surface is greatly reduced.
The composite traffic flow detection equipment is installed as follows: along the advancing direction of a vehicle, each guide lane is sequentially provided with a composite traffic flow detection device A, a composite traffic flow detection device B and a composite traffic flow detection device C, the composite traffic flow detection device A is arranged at the front end of a stop line, a distance is reserved between the composite traffic flow detection device B and the composite traffic flow detection device A, a traffic flow detection area is arranged between the composite traffic flow detection device B and the composite traffic flow detection device A, and the composite traffic flow detection device C is close to the composite traffic flow detection device B.
Specifically referring to fig. 3, three composite traffic flow detection devices are respectively installed on four guiding lanes in the east, the west, the south and the north, a is located at the front end of a stop line, the distance between B and C is close, the area between a and B is regarded as a traffic flow detection area, C provides an auxiliary effect and is convenient for measuring parameters such as vehicle speed, and the like.
The controller is internally provided with an intelligent traffic light control system, namely the controller outputs a traffic light and timer control instruction according to an intelligent traffic light control method, so that the control of on and off of the traffic light and the control of timer display are realized.
The controller adopts STC89C52 singlechip as the main controller, contains power supply circuit, Reset circuit and crystal oscillator circuit triplex, and power supply circuit provides the power, and Reset circuit realizes the initialization to the singlechip, presses the Reset key and can get back to original state, and crystal oscillator circuit is also called clock circuit, and 12 clock cycles are a machine cycle, adopt internal clock alright make whole device steady operation.
After the traffic flow information is collected, the traffic flow information is processed by utilizing an interrupt interface and a timer of the single chip microcomputer to obtain the number of the vehicles to be passed and the length of a vehicle queue to be passed in the current passing phase, and the number of the vehicles to be passed, the length of the vehicle queue to be passed and the residence time of the vehicles to be passed in each phase.
The residence time of the vehicle to be passed is the time when the phase distance is the last green light end; the number of the vehicles to be passed in the traffic flow detection areas in two directions is accumulated in a certain phase, A is subjected to subtraction operation, B is subjected to addition operation, and data obtained in the traffic flow detection areas at any moment is the number of the vehicles to be passed in a certain direction; the length of the vehicle queue to be passed comprises the length of the vehicle and the distance between the vehicles, and the distance between B and C is set asLRecording the time when the vehicle arrives at C ast c The time of arrival at B ist b Then the speed of the vehicle is:
if the vehicle occupies the time of the composite traffic flow detection equipment, the time ist o Then, the vehicle length of the vehicle is:
suppose there is a vehicle in the traffic flow detection zone
The headway is respectively
The vehicle queue length may be defined as:
wherein,
as is the speed of the vehicle,
the length of the last vehicle.
If the distance of the detection area isNThen the traffic density can be described as:
a first-level fuzzy algorithm and a second-level fuzzy algorithm in the intelligent traffic light control system form a multi-level fuzzy controller structure shown in fig. 4, wherein the first-level fuzzy algorithm and the second-level fuzzy algorithm are both of a double-input single-output structure, input variables of the first-level fuzzy algorithm are the residence time and the traffic flow density of a waiting phase, and output variables are the total urgency; the input variables of the secondary fuzzy algorithm are total urgency and traffic flow density of a passing phase, and the output variable is green light delay time of the current passing phase.
The fuzzy algorithm is an intelligent algorithm, has obvious superiority to the complex and dynamic uncertain intelligent traffic lights, does not need to establish an accurate mathematical model, and can improve the accuracy of results while simplifying the operation difficulty. Fig. 5 is a basic structure diagram of the fuzzy algorithm, which is mainly composed of four parts of fuzzification, fuzzy reasoning, clarification and knowledge base. The fuzzification is used for mapping the input value of the physical domain into the linguistic value of the fuzzy domain, the output of the fuzzification is the membership value of each linguistic variable value corresponding to the input value, taking a one-level fuzzy algorithm in fig. 4 as an example, the retention time domain of the input variable waiting phase is T = {15,30,45,60,75,90,105,120,135,150,165}, the traffic density domain of the waiting phase is X = {0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0}, the linguistic variable of the total urgency degree is controlled to be U, and the linguistic values corresponding to the fuzzy subset on the domain are consistent with the input variable and are { positive large (PB), Positive Small (PS), Zero (ZE), Negative Small (NS), Negative Medium (NM), negative large (NB) }. Fuzzy reasoning is the core of a fuzzy algorithm, a fuzzy mathematical theory is used for carrying out logical reasoning operation on a fuzzy control rule, and the function of clarification is to convert a fuzzy vector after fuzzy reasoning into an accurate control quantity, wherein the method adopts the Mamdani reasoning and the maximum membership method. The knowledge base comprises a database and a rule base, wherein the database provides the partition of an input space, the definition of a membership function and the like, the rule base refers to a control rule and determines a system control mode, and a fuzzy condition sentence 'If-Then' is used for establishing the relation between an input variable and an output variable.
The fuzzy algorithm here must follow the following control principles: the control principle of the first-level fuzzy algorithm is as follows: the residence time of the vehicles to be passed in the waiting phase is in direct proportion to the total urgency of the waiting phase, and the traffic density of the waiting phase is in direct proportion to the total urgency of the waiting phase; the control principle of the secondary fuzzy algorithm is as follows: the traffic density of the current passing phase is in direct proportion to the delay time of the traffic light, and the total urgency of the waiting phase is in inverse proportion to the delay time of the traffic light. And obtaining the fuzzy control rule according to the membership function of each variable.
The input key is used for setting a system mode, the K1 key is a normal mode, when the K1 key is pressed, the passing time and the waiting time of the traffic lights are adjusted in real time according to traffic information, the key can also be set manually through the keys K3 and K4, the key K3 or the key K4 respectively increases or reduces the existing passing time manually, and the lighting time of the traffic lights is changed through forced intervention so as to adapt to special traffic conditions. The K2 key is in emergency mode, when the police car, the fire truck and the ambulance go out, the emergency program is started, the signal lights in four directions are all changed into red and in normally bright state, the other vehicles are emergently braked and stopped on the roadside, and after the special vehicle preferentially passes through, the K1 key can be pressed to recover to normal mode.
The timer and the traffic light form a display module for displaying the remaining time of the traffic light state and reminding the driver of paying attention to the conversion of the traffic light, and the driver can make 'stop' or 'pass' selection according to the remaining time. As shown in fig. 6, it is assumed that the intersection has a main road (north-south direction) and an auxiliary road (east-west direction), each direction needs to be provided with a group of red, yellow, green lights and turn lights, a four-phase signal control mode is adopted, the first phase is left turn of the traffic flow in the north-south direction, the second phase is straight run of the traffic flow in the north-south direction, the third phase is left turn of the traffic flow in the east-west direction, the fourth phase is straight run of the traffic flow in the east-west direction, and the passing duration and waiting duration of the four phases are determined by the analysis and comparison result of the traffic flow by the single chip microcomputer. And a short-time yellow lamp is adopted between the traffic lights for buffering warning, when the green lamp countdown of a certain phase is left for 5s, the yellow lamp flickers for warning, the countdown is finished, the traffic direction is changed, the green lamp countdown of another phase is started, and the steps are repeated. The timer adopts 7 sections of LED nixie tubes as display equipment, different light and dark combinations form different fonts, the minimum green light duration and the maximum green light duration need to be set, the minimum green light duration aims to ensure that the traffic time cannot be avoided due to the fact that the traffic flow is too small in each direction, the maximum green light duration aims to ensure that the traffic right cannot be occupied for a long time in a certain direction, and the vehicle delay time in other directions is increased. Assuming that four-phase traffic lights are alternately turned on once as a signal period, fig. 7 is a traffic light on-off scheme in one signal period, the south-north left turn and the straight line of the main trunk road are respectively turned on according to the sequence of green-yellow-red, red-green-yellow-red, the east-west left turn and the straight line of the auxiliary trunk road are respectively turned on according to the sequence of red-green-yellow, red-green-yellow-red, and the time length of the traffic lights in the above cases is determined by the single chip microcomputer according to the vehicle staying scale.
The control flow of the above device is shown in fig. 8:
s1), switching on the power supply, and initializing the device by the single chip microcomputer;
s2) setting the system to a normal mode or an emergency mode by an input key; the red light is normally on in the emergency mode, and two functions of manual control and automatic control can be realized in the normal mode;
s3), during manual control, the switch between the east and west directions and the north and south directions of the traffic lights is forcibly intervened through a key K3 or K4, and the lighting time of the traffic lights is manually set;
s4), when automatic control is carried out, composite type vehicle flow detection equipment is adopted to detect vehicle flows in the east-west direction and the south-north direction of the crossroad, and received vehicle flow information is transmitted to the single chip microcomputer through the advanced Internet of things NB-IoT communication technology;
s6) the singlechip calculates the time delay of the traffic light according to the intelligent traffic light control method, and controls the on and off of the traffic light and the display of the timer.
S7), the composite traffic flow detection equipment collects the traffic flow information of the next round, and the steps are repeated in a circulating mode.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform a smart traffic light control method.
A computing device comprising one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing a smart traffic light control method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.
Claims (10)
1. An intelligent traffic light control method is characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
collecting traffic flow information, calculating the number of vehicles to be passed and the length of a vehicle queue to be passed in the current passing phase, and calculating the number of vehicles to be passed, the length of the vehicle queue to be passed and the residence time of the vehicles to be passed in each waiting phase;
calculating the traffic density of the current passing phase according to the number of the vehicles to be passed in the current passing phase and the length of the vehicle queue to be passed in the current passing phase, and calculating the traffic density of each waiting phase according to the number of the vehicles to be passed in the waiting phase and the length of the vehicle queue to be passed in the waiting phase;
calculating the total urgency of the waiting phases according to the traffic flow density of each waiting phase, the residence time of the vehicles to be passed of each waiting phase and a preset first-level fuzzy algorithm;
calculating the delay time of the traffic light of the current passing phase according to the total urgency of the waiting phase, the current passing phase traffic density and a preset secondary fuzzy algorithm;
obtaining the final traffic light delay time according to the traffic light delay time of the current passing phase, the total urgency of the waiting phase and a preset decision;
and sending out corresponding traffic light and timer control instructions according to the final traffic light delay time length.
2. The intelligent traffic light control method according to claim 1, wherein: the control principle of the first-level fuzzy algorithm is that the residence time of the vehicle to be passed in the waiting phase is in direct proportion to the total urgency of the waiting phase, and the traffic density of the waiting phase is in direct proportion to the total urgency of the waiting phase.
3. The intelligent traffic light control method according to claim 1, wherein: the control principle of the two-stage fuzzy algorithm is that the current traffic flow density of the passing phase is in direct proportion to the delay time of the traffic light, and the total urgency of the waiting phase is in inverse proportion to the delay time of the traffic light.
4. The intelligent traffic light control method according to claim 1, wherein: the pre-set decision is that,
in response to the fact that the total urgency of the waiting phase is greater than or equal to the urgency threshold and the delay time of the traffic light in the current passing phase is smaller than the time threshold, passing right conversion is carried out according to the minimum preset traffic light time, and finally the delay time of the traffic light is the minimum preset traffic light time;
in response to the fact that the total urgency of the waiting phase is smaller than the urgency threshold and the delay time of the traffic light in the current passing phase is larger than or equal to the time threshold, passing right conversion is carried out according to the maximum preset traffic light time, and finally the delay time of the traffic light is the maximum preset traffic light time;
and under other conditions, the right of way is converted according to the delay time of the traffic light in the current passing phase, and finally the delay time of the traffic light is the delay time of the traffic light in the current passing phase.
5. The intelligent traffic light control method according to claim 4, wherein: and carrying out right-of-way conversion according to the degree of urgency of each waiting phase, wherein the degree of urgency of the waiting phases is obtained by calculation according to the traffic density, the residence time of the vehicles to be passed and a preset first-level fuzzy algorithm.
6. The utility model provides a wisdom traffic light control system which characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
the acquisition and calculation module: collecting traffic flow information, calculating the number of vehicles to be passed and the length of a vehicle queue to be passed in the current passing phase, and calculating the number of vehicles to be passed, the length of the vehicle queue to be passed and the residence time of the vehicles to be passed in each waiting phase;
the traffic density module: calculating the traffic density of the current passing phase according to the number of the vehicles to be passed in the current passing phase and the length of the vehicle queue to be passed in the current passing phase, and calculating the traffic density of each waiting phase according to the number of the vehicles to be passed in the waiting phase and the length of the vehicle queue to be passed in the waiting phase;
a first-level fuzzy control module: calculating the total urgency of the waiting phases according to the traffic flow density of each waiting phase, the residence time of the vehicles to be passed of each waiting phase and a preset first-level fuzzy algorithm;
a secondary fuzzy control module: calculating the delay time of the traffic light of the current passing phase according to the total urgency of the waiting phase, the current passing phase traffic density and a preset secondary fuzzy algorithm;
a final duration obtaining module: obtaining the final traffic light delay time according to the traffic light delay time of the current passing phase, the total urgency of the waiting phase and a preset decision;
a control instruction module: and sending out corresponding traffic light and timer control instructions according to the final traffic light delay time length.
7. An intelligent traffic light control device is characterized in that: the traffic light comprises a controller, a plurality of composite traffic flow detection devices, a plurality of timers and a plurality of traffic lights;
the composite traffic flow detection equipment collects traffic flow information of the phase and sends the traffic flow information to the controller; the controller is loaded with the intelligent traffic light control system of any one of claim 6, controlling traffic lights and timers.
8. The intelligent traffic light control device of claim 7, wherein: along the advancing direction of a vehicle, each guide lane is sequentially provided with a composite traffic flow detection device A, a composite traffic flow detection device B and a composite traffic flow detection device C, the composite traffic flow detection device A is arranged at the front end of a stop line, a distance is reserved between the composite traffic flow detection device B and the composite traffic flow detection device A, a traffic flow detection area is arranged between the composite traffic flow detection device B and the composite traffic flow detection device A, and the composite traffic flow detection device C is close to the composite traffic flow detection device B.
9. A computer readable storage medium storing one or more programs, characterized in that: the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods of claims 1-5.
10. A computing device, characterized by: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-5.
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