CN114550471A - Signal lamp control method and control system for intelligent traffic - Google Patents
Signal lamp control method and control system for intelligent traffic Download PDFInfo
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Abstract
The application relates to the field of traffic signal lamp control, and discloses a signal lamp control method and a signal lamp control system for intelligent traffic, wherein the method comprises the following steps: acquiring road section information; determining the flow of the incoming vehicles, the flow of the outgoing vehicles, the flow of the traveling vehicles in the section and whether a fork exists; if no fork exists, when a first congestion value obtained according to the traffic flow is larger than a preset congestion threshold value, controlling signal lamps through a signal lamp combined control strategy at a road section inlet and a road section outlet; if the fork exists, acquiring the traffic flow of the fork; when a second congestion value obtained according to the traffic flow is larger than a preset congestion threshold value, if no turnout signal lamp exists, the signal lamp is controlled through a signal lamp combined control strategy at a road section inlet and a road section outlet; and if the turnout signal lamp exists, controlling the signal lamp through a signal lamp combined control strategy of the turnout, the road section inlet and the road section outlet. The traffic jam condition is relieved through the joint control of the signal lamps.
Description
Technical Field
The application relates to the field of traffic signal lamp control, in particular to a signal lamp control method and a signal lamp control system for intelligent traffic.
Background
In places such as cities where the quantity of motor vehicles and non-motor vehicles is large, the road conditions are very complicated because the road construction has many intersections and road sections. The traffic jam often occurs, and the production and the life of people are affected. Therefore, under the condition that roads are not newly added, the utilization efficiency of the roads is improved, and the key point for solving the traffic jam problem is to improve the traffic efficiency.
The traffic control may be performed by a person, for example, at the morning and evening peak, the traffic control is performed at the intersection by a traffic police, in order to reduce the labor consumption, a signal lamp may be provided at the intersection, and the traffic duration is controlled by the two colors of red and green of a left turn lamp, a right turn lamp or a straight running lamp in the signal lamp. The traditional signal lamp control system respectively sets corresponding lighting modes aiming at signal lamps of a single intersection, if a plurality of vehicles on a straight lane exist, the green time of the straight lamp is prolonged, the traffic volume of the intersection is increased, and the traffic jam at the intersection is avoided.
However, the whole urban road network is a complex system with multiple intersections and road sections, the traffic flow at different intersections is mutually influenced, the traditional signal lamp control system only controls the signal lamp of a single intersection, and after the traffic flow at one intersection is increased, the traffic flow at the next intersection is inevitably increased, and even the traffic jam at the next intersection is avoided. Therefore, the traffic light control of a single intersection does not improve the traffic efficiency of the whole urban road network, and even can cause larger congestion.
Disclosure of Invention
In order to solve the problem of congestion of a traffic road section, the application provides a signal lamp control method and a signal lamp control system for intelligent traffic.
In a first aspect, the present application provides a signal lamp control method for intelligent traffic, which adopts the following technical scheme:
a signal lamp control method for intelligent traffic comprises the following steps:
obtaining road section information of a traffic road section in the intelligent traffic network based on a machine vision technology, wherein the road section information comprises road section in-information, road section inlet information and road section outlet information of the traffic road section, and both the road section inlet and the road section outlet are signal lamp intersections;
determining the traffic flow of the vehicle entering according to the entrance information of the road section, and determining the traffic flow of the vehicle leaving according to the exit information of the road section;
determining the traffic flow in the section and whether a fork exists according to the information in the road section;
if no intersection exists, calculating to obtain a first congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles and the flow of the traveling vehicles in the section based on an AI (automatic learning) algorithm;
when the first congestion value is larger than a preset congestion threshold, generating a signal lamp combined control strategy of a road section inlet and a road section outlet, and jointly controlling signal lamps of the road section inlet and the road section outlet through the signal lamp combined control strategy to enable the first congestion value to be adjusted to be not larger than the preset congestion threshold;
if the fork exists, the fork traffic flow of the fork is obtained;
based on an AI automatic learning algorithm, calculating to obtain a second congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles, the flow of the traveling vehicles in the section and the flow of the vehicles at the fork road;
when the second congestion value is larger than a preset congestion threshold value, judging whether a turnout signal lamp exists at the turnout;
if no turnout signal lamp exists, generating a signal lamp combined control strategy of a road section inlet and a road section outlet, and jointly controlling the signal lamps of the road section inlet and the road section outlet through the signal lamp combined control strategy to enable a second congestion value to be adjusted to be not more than a preset congestion threshold value;
and if the turnout signal lamps exist, generating a turnout signal lamp combined control strategy, a road section inlet and a road section outlet, and jointly controlling the signal lamps of the road section inlet and the road section outlet and the turnout signal lamps through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than the preset congestion threshold value.
Optionally, the road section information further includes lane information, and the method further includes:
judging whether the traffic road section is a bidirectional driving lane or a unidirectional driving lane according to the lane information;
if the traffic road section is a bidirectional driving lane, determining that the traffic road section comprises a first road section and a second road section, wherein the driving directions of the first road section and the second road section are opposite, and the first road section and the second road section are both provided with a road section inlet and a road section outlet;
and if the traffic road section is the one-way driving lane, determining that the traffic road section is the one-way road section.
Optionally, determining an incoming traffic flow according to the road section entrance information, and determining an outgoing traffic flow according to the road section exit information, includes:
analyzing according to the road section entrance information to obtain the number of vehicles entering through the road section entrance within a preset time period, and calculating to obtain the entering vehicle flow;
and analyzing according to the information of the road section exit to obtain the number of vehicles driving in through the road section entrance in a preset time period, and calculating to obtain the driving-out traffic flow.
Optionally, determining the traffic flow and whether there is a fork in the segment according to the information in the segment includes:
analyzing according to the information in the road section to obtain the number of vehicles running on the road section in a preset time period, and calculating to obtain the traffic flow in the section;
determining whether a branch for traffic flow entering or traffic flow exiting exists in the middle of the road section of the traffic road section according to the information in the road section;
if a branch for the incoming traffic flow and/or the outgoing traffic flow exists, a fork road exists;
if no branch for the incoming traffic flow and the outgoing traffic flow exists, no fork exists.
Optionally, obtaining the intersection traffic flow of the intersection includes:
acquiring map data near the fork road, and judging that the fork road is a parking lot entrance or a branch road according to the map data near the fork road;
if the intersection is a branch road intersection, detecting the number of vehicles passing through the branch road intersection in a preset time period by a vehicle detector arranged at the branch road intersection, and calculating to obtain the traffic flow of the branch road intersection;
if the current time point is at the entrance or exit of the parking lot, determining whether the current time point is in the peak time period of going on or off duty;
if the vehicle is not in the peak time period of going to and going from work, the number of passing vehicles in the preset time period is obtained through detection of the parking lot electronic barrier, and the vehicle flow at the fork road is obtained through calculation;
and if the traffic flow is in the on-duty peak time, calling a historical record table of the on-duty peak traffic flow of the parking lot to obtain the traffic flow of the fork.
Optionally, the traffic road section is a one-way road section, and a second congestion value is calculated based on an AI automatic learning algorithm according to the traffic flow entering, the traffic flow exiting, the traffic flow traveling in the section, and the traffic flow at the fork intersection, and the method includes:
based on an AI automatic learning algorithm, calculating to obtain an initial value according to the flow of the incoming traffic, the flow of the outgoing traffic and the flow of the traffic in the segment;
calculating to obtain a first congestion adjustment coefficient according to the vehicle flow at the fork;
and calculating to obtain a second congestion value according to the first congestion adjustment coefficient and the initial value.
Optionally, when the traffic road segment includes the first road segment and the second road segment, based on an AI automatic learning algorithm, the second congestion value is calculated according to the incoming traffic flow, the outgoing traffic flow, the traffic flow in the segment, and the vehicle flow at the intersection, and the second congestion value includes:
based on an AI (automatic learning) algorithm, calculating to obtain an initial value of the first road section according to the driving-in traffic flow, the driving-out traffic flow and the driving traffic flow in the section of the first road section;
based on an AI automatic learning algorithm, calculating to obtain an initial value of the second road section according to the driving-in traffic flow, the driving-out traffic flow and the driving traffic flow in the section of the second road section;
identifying that the fork road is connected with the first road section or the second road section;
if the intersection is connected with the first road section, calculating to obtain a second congestion adjustment coefficient of the first road section according to the traffic flow of the intersection, and calculating to obtain a second congestion value of the first road section according to the second congestion adjustment coefficient and the initial value of the first road section;
and if the intersection is connected with the second road section, calculating to obtain a third congestion adjustment coefficient of the second road section according to the traffic flow of the intersection, and calculating to obtain a second congestion value of the second road section according to the third congestion adjustment coefficient and the initial value of the second road section.
Optionally, the method further comprises:
judging whether a vehicle turning point exists between the first road section and the second road section;
if the vehicle turning points exist, acquiring a first turning vehicle number and a second turning vehicle number of the vehicle turning points in a preset time period, wherein the first turning vehicle number is the number of vehicles turning around from a first road section and driving into a second road section, the second turning vehicle number is the number of vehicles turning around from the second road section and driving into the first road section,
respectively calculating to obtain a first turning vehicle flow and a second turning vehicle flow according to the first turning vehicle number and the second turning vehicle number;
and adjusting the driving traffic flow in the sections of the first road section and the second road section according to the first turning traffic flow and the second turning traffic flow.
Optionally, generating a signal lamp joint control strategy for the road section entrance and the road section exit, and jointly controlling signal lamps for the road section entrance and the road section exit through the signal lamp joint control strategy, so that the second congestion value is adjusted to be not greater than the preset congestion threshold, further including:
and establishing communication connection with the parking lot electronic barrier gate, controlling the opening speed of the entrance barrier gate of the parking lot electronic barrier gate to be increased or the entrance barrier gate to be normally opened, and controlling the opening speed of the exit barrier gate of the parking lot electronic barrier gate to be reduced.
In a second aspect, the present application provides a signal lamp control system for intelligent traffic, which adopts the following technical scheme:
the system comprises an information acquisition module, an information processing module and a signal lamp control strategy module;
the information acquisition module is used for acquiring road section information of a traffic road section in the intelligent traffic network based on a machine vision technology, wherein the road section information comprises road section in-information, road section inlet information and road section outlet information of the traffic road section, and both the road section inlet and the road section outlet are signal lamp intersections;
the information processing module is used for determining the traffic flow of the vehicle entering according to the information of the entrance of the road section and determining the traffic flow of the vehicle leaving according to the information of the exit of the road section; determining the traffic flow in the section and whether a fork exists according to the information in the road section; if no turnout exists, calculating to obtain a first congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles and the flow of the traveling vehicles in the section based on an AI (automatic learning) algorithm;
the signal lamp control strategy module is used for generating a signal lamp combined control strategy of a road section inlet and a road section outlet when the first congestion value is larger than a preset congestion threshold value, and jointly controlling signal lamps of the road section inlet and the road section outlet through the signal lamp combined control strategy to enable the first congestion value to be adjusted to be not larger than the preset congestion threshold value;
the information processing module is also used for acquiring the turnout traffic flow of the turnout if the turnout exists; based on an AI automatic learning algorithm, calculating to obtain a second congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles, the flow of the traveling vehicles in the segment and the flow of the vehicles at the fork road;
the signal lamp control strategy module is also used for generating a signal lamp combined control strategy of the road section inlet and the road section outlet if no turnout signal lamp exists, and jointly controlling the signal lamps of the road section inlet and the road section outlet through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than a preset congestion threshold value; and if the turnout signal lamps exist, generating a turnout signal lamp combined control strategy, a road section inlet and a road section outlet, and jointly controlling the signal lamps of the road section inlet and the road section outlet and the turnout signal lamps through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than the preset congestion threshold value.
In summary, the present application includes the following advantageous technical effects:
aiming at the congestion problem of a traffic road section of two adjacent signal lamp intersections in an intelligent traffic network, when no intersection exists, calculating to obtain a first congestion value according to the flow of incoming vehicles, the flow of outgoing vehicles and the flow of running vehicles in a section based on an AI automatic learning algorithm, when the first congestion value is larger than a preset congestion threshold value, indicating that the congestion problem needs to be solved, generating a signal lamp combined control strategy of a road section inlet and a road section outlet, and further, jointly controlling signal lamps of the road section inlet and the road section outlet, and relieving the congestion condition of the traffic road section; when the turnout exists, calculating to obtain a second congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles, the flow of the traveling vehicles in the section and the flow of the vehicles at the turnout based on an AI automatic learning algorithm, wherein when the second congestion value is larger than a preset congestion threshold value, the problem of congestion is indicated to be solved, and if the turnout does not have a signal lamp, the signal lamps at the entrance and the exit of the road section are controlled in a combined manner, so that the congestion condition of the traffic road section is relieved; if the turnout signal lamp exists at the turnout, a signal lamp combined control strategy of the turnout, the road section inlet and the road section outlet is generated, and then the signal lamp of the road section inlet and the road section outlet and the turnout signal lamp are combined and controlled, so that the congestion condition of the traffic road section is relieved; compared with the traditional signal lamp control system which only controls a single intersection signal lamp, when the traffic jam occurs in the traffic road section, the signal lamps of adjacent signal lamp intersections in the traffic road section are jointly controlled, meanwhile, the influence of the traffic flow of the intersection on the jam condition is taken into consideration in the calculation process of the jam value, and for the intersection with the signal lamp, the signal lamp of the intersection signal lamp and the signal lamp intersection are all brought into a signal lamp joint control strategy, so that the traffic jam condition is relieved.
Drawings
Fig. 1 is a schematic flowchart of a signal lamp control method for intelligent traffic according to the present application.
Fig. 2 is a schematic flow chart of obtaining the traffic flow at the intersection according to the present application.
Fig. 3 is a schematic flow chart of a congestion value calculation process when a traffic road segment is a one-way road segment according to the present application.
Fig. 4 is a schematic flow chart of a congestion value calculation process when a traffic road segment of the present application is a bidirectional road segment.
Fig. 5 is a schematic structural diagram of a signal lamp control system of intelligent traffic according to the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The embodiment of the application discloses a signal lamp control method for intelligent traffic.
Referring to fig. 1, the method includes:
and S101, obtaining road section information of a traffic road section in the intelligent traffic network based on a machine vision technology.
Wherein, the constitution of intelligent transportation network includes: the traffic network consists of all roads for vehicles to run, and intelligent facilities are arranged on the roads and matched with the roads. In a traffic network, a traffic road section is formed between two adjacent signal lamp intersections, then a road section inlet and a road section outlet are both signal lamp intersections, and intelligent facilities matched with the traffic road section comprise a geomagnetic detector, a video camera and the like. The road information of the traffic road section can be obtained through detection of the intelligent facility, and the road information is divided into road section in-section information, road section entrance information and road section exit information of the traffic road section. The machine vision technology is a comprehensive technology, including image processing, mechanical engineering technology, control, electric light source illumination, optical imaging, sensors, analog and digital video technology, computer software and hardware technology and the like, and can be applied to an intelligent traffic network, especially to acquisition and processing of road section information of traffic road sections, so that the road section information of each traffic road section and information related to vehicles can be acquired.
S102, determining the traffic flow rate of the vehicle entering according to the entrance information of the road section, and determining the traffic flow rate of the vehicle leaving according to the exit information of the road section.
The road section entrance and the road section exit are signal lamp intersections of traffic road sections, and the road section entrance information and the road section exit information both include the fact that the vehicle is detected to enter or exit at a certain moment, and the specific process of calculating the traffic flow is as follows:
analyzing according to the road section entrance information to obtain the number of vehicles entering through the road section entrance within a preset time period, for example, the preset time period is 1 point integral to 1 point 02 minutes, the time period is 2 minutes, and the number of the vehicles entering is 20, dividing the number of the vehicles by the time period of the preset time period, and calculating to obtain the entering traffic flow of 10 vehicles/minute;
similarly, the same mode is adopted for calculating the outgoing traffic flow of the road section outlet, and in order to ensure the same time, the preset time period is also from 1 point to 1 point for 02 minutes.
And S103, determining the traffic flow in the section and whether a fork exists according to the information in the road section.
The information in the road section represents the information between the road section inlet and the road section outlet of the traffic road section, and the traffic flow in the middle driving section of the traffic road section can be obtained; in an actual traffic scene, traffic sections are divided into a closed type and an open type, the closed type means that no turnout exists in the middle of the traffic section, except that no other vehicle enters the section at the section entrance and the section exit, the open type means that the turnout exists in the middle of the traffic section, and other vehicles can drive in or out of the traffic section through the turnout, and the specific judgment process is as follows:
determining whether a branch for traffic flow entering or traffic flow exiting exists in the middle of the road section of the traffic road section according to the information in the road section;
if a branch for the incoming traffic flow and/or the outgoing traffic flow exists, a fork road exists;
if no branch for the incoming traffic flow and the outgoing traffic flow exists, no fork exists;
determining that no fork exists, and executing step S104; it is determined that there is an intersection, step S106 is executed.
And S104, calculating to obtain a first congestion value according to the incoming traffic flow, the outgoing traffic flow and the traffic flow in the section based on an AI (automatic learning) algorithm.
The Artificial Intelligence (AI) automatic learning algorithm is applied to the traffic field to calculate the congestion value, and the congestion model is constructed by counting the historical traffic jam data and the historical traffic flow, so that the AI-based automatic learning algorithm is used for calculating the congestion value substantially through the pre-constructed congestion model. Under the condition that no intersection exists, the traffic road section is closed, and a first congestion value is obtained by calculation only according to the flow of the incoming traffic, the flow of the outgoing traffic and the flow of the traffic in the section, namely on the basis of the known length of the traffic road section, the number of vehicles in the middle of the road section in a preset time period, the number of the incoming vehicles and the number of the outgoing vehicles are known, so that whether the traffic road section is congested or not can be determined, the congestion degree is represented by the first congestion value, the larger the first congestion value is, the higher the congestion degree is, and the smaller the congestion degree is.
And S105, when the first congestion value is larger than the preset congestion threshold, generating a signal lamp combined control strategy of the road section inlet and the road section outlet, and jointly controlling signal lamps of the road section inlet and the road section outlet through the signal lamp combined control strategy to enable the first congestion value to be adjusted to be not larger than the preset congestion threshold.
The first congestion value is greater than a preset congestion threshold value and indicates that the traffic congestion situation reaches a ground step needing to be improved, traffic lights at a road section entrance and a road section exit are alternated according to a preset period before the first congestion value is larger than the preset congestion threshold value, the first congestion value belongs to a single intersection to independently control the traffic lights, in order to relieve the congestion situation, the traffic lights at the road section entrance and the road section exit need to be controlled in a combined mode to generate a combined control strategy of the traffic lights at the road section entrance and the road section exit, and the combined control strategy of the traffic lights at the road section entrance and the road section exit is controlled through the combined control strategy of the traffic lights, for example, the red light time or the green light time of the road section entrance is controlled to be prolonged, so that the traffic flow is reduced; or the red light time of the exit of the control road section is shortened or the green light time is prolonged, so that the flow of the outgoing vehicles is increased; alternatively, the flow rate of the incoming traffic is reduced and the flow rate of the outgoing traffic is also increased. The objective is to adjust the first congestion value to be no greater than a preset congestion threshold.
And S106, acquiring the turnout traffic flow of the turnout.
When the fork exists, the vehicle detection equipment installed at the fork acquires the fork traffic flow of the fork.
And S107, calculating to obtain a second congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles, the flow of the vehicles in the section and the flow of the vehicles at the fork junction based on an AI (automatic learning) algorithm.
Under the condition that the traffic road section is not closed, a second congestion value needs to be calculated by combining the traffic flow of the intersection on the basis of the traffic flow of the entering traffic, the traffic flow of the exiting traffic and the traffic flow of the vehicles in the section, namely the number of vehicles in the middle of the road section, the number of entering vehicles and the number of exiting vehicles in a preset time period are known on the basis of the known length of the traffic road section, and the number of vehicles entering or exiting from the intersection is combined, so that whether the traffic road section is congested or not can be determined, the congestion degree is represented by the second congestion value, the larger the second congestion value is, the higher the congestion degree is, and the smaller the congestion degree is.
And S108, judging whether the turnout signal lamp exists at the turnout when the second congestion value is larger than the preset congestion threshold value.
The second congestion value is greater than the preset congestion threshold value, which indicates that the traffic congestion situation reaches a ground step to be improved, whether a signal lamp is installed at the turnout can be determined by inquiring information of the intelligent traffic network, and if the signal lamp is not installed at the turnout, the step S109 is executed; if there is a branch signal lamp, step S110 is executed.
And S109, generating a signal lamp combined control strategy of the road section inlet and the road section outlet, and jointly controlling signal lamps of the road section inlet and the road section outlet through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than a preset congestion threshold value.
Under the condition that no turnout signal lamp is provided, in order to relieve the congestion condition, signal lamps at a road section entrance and a road section exit need to be controlled in a combined mode, a signal lamp combined control strategy of the road section entrance and the road section exit is generated, the signal lamps at the road section entrance and the road section exit are controlled in a combined mode through the signal lamp combined control strategy, for example, the red light time of the road section entrance is controlled to be prolonged or the green light time of the road section entrance is controlled to be shortened, and therefore the traffic flow of the vehicle is reduced; or the red light time of the exit of the control road section is shortened or the green light time is prolonged, so that the flow of the outgoing vehicles is increased; alternatively, the flow rate of the incoming vehicle is reduced and the flow rate of the outgoing vehicle is also increased. The objective is to adjust the second congestion value to be no greater than a preset congestion threshold.
And S110, generating a signal lamp combined control strategy of the fork, the road section inlet and the road section outlet, and jointly controlling the signal lamps of the road section inlet and the road section outlet and the signal lamps of the fork through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than a preset congestion threshold value.
Under the condition of having a turnout signal lamp, in order to alleviate the congestion condition, the signal lamps at the road section entrance and the road section exit and the turnout signal lamp need to be controlled in a combined manner, and the mode of controlling each signal lamp comprises the following steps:
(1) the red light time of the entrance of the control road section is prolonged or the green light time of the entrance of the control road section is shortened, so that the driving traffic flow of the entrance of the control road section is reduced;
(2) the red light time of the exit of the control road section is shortened or the green light time of the exit of the control road section is prolonged, so that the flow of the outgoing vehicles at the exit of the control road section is increased;
(3) the turnout is driven out of the traffic road section, and the red light time or the green light time of a signal lamp of the turnout is controlled to be shortened or prolonged, so that the driving-out traffic flow of the turnout is increased;
(4) the turnout is driven into the traffic road section, and the red light time or the green light time of a signal lamp of the turnout is controlled to be prolonged or shortened, so that the driving traffic flow of the turnout is increased;
when the turnout is an outgoing traffic section, the signal lamp combined control strategy can be any one of (1), (2) and (3), can also be the combination of any two or the combination of any three;
when the intersection is a traffic road section, the signal lamp combination control strategy can be any one of (1), (2) and (4), or a combination of any two or three.
The principle of the embodiment of the present embodiment is as follows: aiming at the congestion problem of a traffic road section of two adjacent signal lamp intersections in an intelligent traffic network, when no intersection exists, calculating to obtain a first congestion value according to the flow of incoming vehicles, the flow of outgoing vehicles and the flow of running vehicles in a section based on an AI automatic learning algorithm, when the first congestion value is larger than a preset congestion threshold value, indicating that the congestion problem needs to be solved, generating a signal lamp combined control strategy of a road section inlet and a road section outlet, and further, jointly controlling signal lamps of the road section inlet and the road section outlet, and relieving the congestion condition of the traffic road section; when the fork exists, calculating to obtain a second congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles, the flow of the traveling vehicles in the section and the flow of the vehicles at the fork based on an AI automatic learning algorithm, when the second congestion value is larger than a preset congestion threshold value, indicating that the congestion problem needs to be solved, and if the fork does not have a signal lamp, jointly controlling the signal lamps at the entrance and the exit of the road section to relieve the congestion condition of the traffic road section; if the turnout signal lamp exists at the turnout, a signal lamp combined control strategy of the turnout, the road section inlet and the road section outlet is generated, and then the signal lamp of the road section inlet and the road section outlet and the turnout signal lamp are combined and controlled, so that the congestion condition of the traffic road section is relieved; compared with the traditional signal lamp control system only controlling a single intersection signal lamp, when the traffic jam occurs in the traffic road section, the signal lamps of the adjacent signal lamp intersections in the traffic road section are jointly controlled, meanwhile, the influence of the traffic flow of the turnout intersection on the jam condition is taken into consideration in the calculation process of the jam value, and for the turnout intersection with the signal lamp, the signal lamps of the turnout intersection signal lamp and the signal lamp intersection are all taken into a signal lamp joint control strategy, so that the traffic jam condition is relieved.
In the above embodiment shown in fig. 1, the road section information further includes lane information, and it can be determined whether the traffic road section is one-way or two-way through the lane information, the specific process is as follows:
judging whether the traffic road section is a bidirectional driving lane or a unidirectional driving lane according to the lane information, if so, determining that the traffic road section comprises a first road section and a second road section, wherein the driving directions of the first road section and the second road section are opposite, and the first road section and the second road section are both provided with a road section inlet and a road section outlet; and if the traffic road section is the one-way driving lane, determining that the traffic road section is the one-way road section.
In the above step S106 of the embodiment shown in fig. 1, as shown in fig. 2, the process of acquiring the traffic flow at the intersection includes the specific steps of:
s201, obtaining map data near the intersection, and judging the intersection to be a parking lot exit or a branch road intersection according to the map data near the intersection.
Wherein, under the condition that a fork exists, map data near the fork is obtained through a map database, so as to judge that the fork is a parking lot exit or a branch road intersection, and if the fork is a branch road intersection, the step S202 is executed; if it is the parking lot entrance, step S203 is performed.
S202, detecting and obtaining the number of vehicles passing through the branch road intersection in a preset time period through a vehicle detector arranged at the branch road intersection, and calculating to obtain the traffic flow of the branch road intersection.
If the fork road is the branch road intersection, the number of vehicles passing through the branch road intersection in a preset time period is detected through a vehicle detector arranged at the branch road intersection, and the traffic flow of the fork road is calculated.
And S203, determining whether the current time point is in the on-off peak period.
If the fork is a parking lot entrance and exit, because the parking lot is not in the peak time of going to and going out of work, the number of vehicles entering and exiting is small, the influence on the congestion of the traffic road section is weak, the traffic flow is high only in the peak time of going to and going out of work, and the influence on the congestion of the traffic road section is large, so that whether the current time point is in the peak time of going to and going out of work or not needs to be determined, and if the current time point is not in the peak time of going to and going out of work, the step S204 is executed; if so, step S205 is performed.
And S204, detecting through the parking lot electronic barrier to obtain the number of passing vehicles in a preset time period, and calculating to obtain the traffic flow at the fork.
If the vehicle is not in the peak time period of going to work or off work, the number of passing vehicles in the preset time period is detected through the parking lot electronic barrier, and the vehicle flow at the fork road is calculated.
And S205, if the traffic flow is in the peak time period of going to and going to duty, calling a historical record table of the traffic flow of the peak time of going to and going to duty in the parking lot to obtain the traffic flow of the fork.
If the parking lot is located at the peak time of going to work and going to work, because the parking groups facing the same parking lot are stable during the peak time of going to work and going to work, in order to save the detection overhead of the electronic barrier gate of the parking lot, only the historical record table of the traffic flow of the parking lot at the peak time of going to work and going to work needs to be called to obtain the traffic flow of the fork.
In conjunction with the above embodiments shown in fig. 1 and 2, for the calculation of the congestion value, it is not considered whether the traffic road section is one-way or two-way, and if the traffic road section is two-way, it is also considered which direction road section the intersection is connected to, and the following description will be made on the one-way road section and the two-way road section by using fig. 3 and 4, respectively.
As shown in fig. 3, the congestion value calculation process when the traffic road segment is a one-way road segment specifically includes the steps of:
s301, based on an AI automatic learning algorithm, calculating to obtain an initial value according to the flow of the incoming traffic, the flow of the outgoing traffic and the flow of the traffic in the segment.
And S302, calculating to obtain a first congestion adjustment coefficient according to the traffic flow at the fork.
If the fork road is driven in, dividing the traffic flow of the fork road by the driving traffic flow to obtain a first congestion adjustment coefficient;
if the fork road is driven out, dividing the traffic flow of the fork road by the driving traffic flow to obtain a first congestion adjustment coefficient;
if the fork road has the entrance and the exit, dividing the traffic flow of the entrance of the fork road by the entrance traffic flow, dividing the traffic flow of the exit of the fork road by the exit traffic flow, and adding to obtain a first congestion adjustment coefficient.
And S303, calculating to obtain a second congestion value according to the first congestion adjustment coefficient and the initial value.
And obtaining a second congestion value by using the (first congestion adjustment coefficient + 1) initial value.
As shown in fig. 4, the congestion value calculation process when the traffic road segment is a bidirectional road segment specifically includes the steps of:
s401, based on an AI automatic learning algorithm, calculating to obtain an initial value of the first road section according to the driving traffic flow, the driving traffic flow and the driving traffic flow in the section of the first road section.
S402, based on an AI automatic learning algorithm, calculating to obtain an initial value of the second road section according to the driving-in traffic flow, the driving-out traffic flow and the driving traffic flow in the section of the second road section.
And S403, identifying that the intersection is connected with the first road section or the second road section.
Wherein, for the bidirectional road section, the fork is connected with one of the road sections, if the road section is the first road section, the step S404 is executed; if the second link is the first link, step S405 is performed.
S404, calculating to obtain a second congestion adjustment coefficient of the first road section according to the vehicle flow at the intersection, and calculating to obtain a second congestion value of the first road section according to the second congestion adjustment coefficient and the initial value of the first road section.
When the intersection is connected with the first road section, only the congestion condition of the first road section is affected, so that the second congestion adjustment coefficient of the first road section is obtained through calculation according to the traffic flow of the intersection, and the second congestion value of the first road section is obtained through calculation according to the second congestion adjustment coefficient and the initial value of the first road section.
S405, calculating a third congestion adjustment coefficient of the second road section according to the traffic flow at the intersection, and calculating a second congestion value of the second road section according to the third congestion adjustment coefficient and the initial value of the second road section.
When the intersection is connected with the second road section, only the congestion condition of the second road section is influenced, so that a third congestion adjustment coefficient of the second road section is obtained through calculation according to the traffic flow of the intersection, and a second congestion value of the second road section is obtained through calculation according to the third congestion adjustment coefficient and the initial value of the second road section.
In the above embodiment shown in fig. 4, there may be a u-turn point between the bidirectional road segments, and then the traffic flow in the segments of the first road segment and the second road segment may be affected, before step 401 is implemented, the following steps are further performed:
judging whether a vehicle turning point exists between the first road section and the second road section;
if the vehicle turning points exist, acquiring a first turning vehicle number and a second turning vehicle number of the vehicle turning points in a preset time period, wherein the first turning vehicle number is the number of vehicles turning around from a first road section and driving into a second road section, the second turning vehicle number is the number of vehicles turning around from the second road section and driving into the first road section,
respectively calculating to obtain a first turning vehicle flow and a second turning vehicle flow according to the first turning vehicle number and the second turning vehicle number;
and adjusting the driving traffic flow in the sections of the first road section and the second road section according to the first turning traffic flow and the second turning traffic flow.
In the above embodiment shown in fig. 1, when it is determined that the intersection exists, but the intersection has no signal lamp, after the implementation process of the signal lamp combination control in step S109, the method further includes:
and establishing communication connection with the parking lot electronic barrier gate, controlling the opening speed of the entrance barrier gate of the parking lot electronic barrier gate to be increased or the entrance barrier gate to be normally opened, and controlling the opening speed of the exit barrier gate of the parking lot electronic barrier gate to be reduced.
The turnout junction without the signal lamp can be a branch road junction or a parking lot exit, but considering that the branch road junction has no signal lamp, the traffic flow cannot be controlled certainly, and the parking lot is provided with an electronic barrier, so that under the condition of congestion, after the signal lamps of the road section entrance and the road section exit are controlled jointly through a signal lamp joint control strategy, the communication connection with the parking lot electronic barrier is also established, the opening speed of the entrance barrier of the parking lot electronic barrier is controlled to be increased or the entrance barrier is controlled to be normally opened, and the opening speed of the exit barrier of the parking lot electronic barrier is controlled to be reduced. Thereby reducing traffic pressure on the traffic segment.
It should be noted that, when the intersection is a branch road intersection, but the branch road intersection has no signal lamp, there is a possibility that, on the branch road, when there is a toll station within a preset distance range from the branch road intersection, a connection with the control console of the toll station may be established, the control console of the toll station is intended to send a second congestion value, and the control console controls the passing speed of the vehicle according to the second congestion value, so as to reduce the traffic flow entering the traffic section and improve the traffic flow exiting the traffic section.
The above is an embodiment of the signal lamp control method for intelligent traffic according to the present application, and a signal lamp control system for intelligent traffic is described below with reference to the embodiment. As shown in fig. 5, the present application provides a signal lamp control system for intelligent traffic, including:
the system comprises an information acquisition module 501, an information processing module 502 and a signal lamp control strategy module 503;
the information acquisition module 501 is configured to obtain road segment information of a traffic road segment in an intelligent traffic network based on a machine vision technology, where the road segment information includes road segment in-information, road segment entrance information, and road segment exit information of the traffic road segment, and both the road segment entrance and the road segment exit are signal light intersections;
the information processing module 502 is configured to determine an incoming traffic flow according to the road section entrance information, and determine an outgoing traffic flow according to the road section exit information; determining the traffic flow in the section and whether a fork exists according to information in the road section based on an AI automatic learning algorithm; if no fork exists, calculating to obtain a first congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles and the flow of the traveling vehicles in the section;
the signal lamp control strategy module 503 is configured to generate a signal lamp combined control strategy for a road section entrance and a road section exit when the first congestion value is greater than a preset congestion threshold, and jointly control signal lamps for the road section entrance and the road section exit through the signal lamp combined control strategy, so that the first congestion value is adjusted to be not greater than the preset congestion threshold;
the information processing module 502 is further configured to, if there is a fork, obtain a fork traffic flow of the fork; based on an AI automatic learning algorithm, calculating to obtain a second congestion value according to the flow of the incoming vehicles, the flow of the outgoing vehicles, the flow of the traveling vehicles in the section and the flow of the vehicles at the fork road;
the signal lamp control strategy module 503 is further configured to generate a signal lamp combined control strategy for the road section entrance and the road section exit if no intersection signal lamp is available, and jointly control the signal lamps for the road section entrance and the road section exit through the signal lamp combined control strategy, so that the second congestion value is adjusted to be not greater than the preset congestion threshold; and if the turnout signal lamps exist, generating a turnout signal lamp combined control strategy, a road section inlet and a road section outlet, and jointly controlling the signal lamps of the road section inlet and the road section outlet and the turnout signal lamps through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than the preset congestion threshold value.
Compared with the traditional signal lamp control system which only controls a single intersection signal lamp, the signal lamp control system for intelligent traffic of the embodiment jointly controls the signal lamps of adjacent signal lamp intersections of a traffic road section when the traffic road section is congested, simultaneously considers the influence of traffic flow of the intersection on the congestion condition in the congestion value calculation process, brings the signal lamps of the signal lamps and the signal lamp intersections into a signal lamp joint control strategy for the intersection with the signal lamp, and relieves the traffic congestion condition.
The foregoing is a preferred embodiment of the present application and is not intended to limit the scope of the application in any way, and any features disclosed in this specification (including the abstract and drawings) may be replaced by alternative features serving equivalent or similar purposes, unless expressly stated otherwise. That is, unless expressly stated otherwise, each feature is only an example of a generic series of equivalent or similar features.
Claims (10)
1. A signal lamp control method for intelligent traffic is characterized by comprising the following steps:
obtaining road section information of a traffic road section in an intelligent traffic network based on a machine vision technology, wherein the road section information comprises road section in-information, road section inlet information and road section outlet information of the traffic road section, and both a road section inlet and a road section outlet are signal lamp intersections;
determining the traffic flow of the vehicle entering according to the road section entrance information, and determining the traffic flow of the vehicle leaving according to the road section exit information;
determining the traffic flow in the section and whether a fork exists according to the information in the section;
if no intersection exists, calculating to obtain a first congestion value according to the driving-in traffic flow, the driving-out traffic flow and the driving traffic flow in the section based on an AI (automatic learning) algorithm;
when the first congestion value is larger than a preset congestion threshold, generating a signal lamp combined control strategy of the road section entrance and the road section exit, and jointly controlling signal lamps of the road section entrance and the road section exit through the signal lamp combined control strategy to enable the first congestion value to be adjusted to be not larger than the preset congestion threshold;
if the fork exists, acquiring the fork traffic flow of the fork;
based on the AI automatic learning algorithm, calculating to obtain a second congestion value according to the incoming traffic flow, the outgoing traffic flow, the traffic flow in the section and the traffic flow at the fork;
when the second congestion value is larger than a preset congestion threshold value, judging whether the turnout has a turnout signal lamp;
if no turnout signal lamp exists, generating a signal lamp combined control strategy of the road section entrance and the road section exit, and jointly controlling the signal lamps of the road section entrance and the road section exit through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than the preset congestion threshold value;
and if the turnout signal lamp exists, generating a signal lamp combined control strategy of the turnout, the road section inlet and the road section outlet, and jointly controlling the signal lamps of the road section inlet and the road section outlet and the turnout signal lamp through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than the preset congestion threshold value.
2. The signal light control method of intelligent transportation according to claim 1, wherein the section information further includes lane information, the method further comprising:
judging whether the traffic road section is a bidirectional driving lane or a unidirectional driving lane according to the lane information;
if the traffic road section is the bidirectional driving lane, determining that the traffic road section comprises a first road section and a second road section, wherein the driving directions of the first road section and the second road section are opposite, and the first road section and the second road section are both provided with a road section inlet and a road section outlet;
and if the traffic road section is the one-way driving lane, determining that the traffic road section is the one-way road section.
3. The signal lamp control method for intelligent transportation according to claim 2, wherein the determining of the traffic flow rate based on the section entrance information and the determining of the traffic flow rate based on the section exit information comprises:
analyzing according to the road section entrance information to obtain the number of vehicles driven in through the road section entrance in a preset time period, and calculating to obtain the driving traffic flow;
and analyzing according to the road section exit information to obtain the number of vehicles entering through the road section entrance in the preset time period, and calculating to obtain the traffic flow of the vehicles leaving.
4. The signal lamp control method for intelligent transportation according to any one of claims 1-3, wherein the determining of the traffic flow in the segment and the existence of the intersection according to the information in the segment comprises:
analyzing according to the information in the road section to obtain the number of vehicles running on the road section within a preset time period, and calculating to obtain the traffic flow in the section;
determining whether a branch for traffic flow entering or traffic flow exiting exists in the middle of the road section of the traffic road section according to the information in the road section;
if a branch for the incoming traffic flow and/or the outgoing traffic flow exists, a fork road exists;
if no branch for the incoming traffic flow and the outgoing traffic flow exists, no fork exists.
5. The signal lamp control method for intelligent traffic of claim 4, wherein the obtaining of the intersection traffic flow of the intersection comprises:
acquiring map data near the fork road, and judging that the fork road is a parking lot exit or a branch road intersection according to the map data near the fork road;
if the road is a branch road intersection, detecting the number of vehicles passing through the branch road intersection in the preset time period by a vehicle detector arranged at the branch road intersection, and calculating to obtain the traffic flow of the branch road intersection;
if the current time point is at the entrance or exit of the parking lot, determining whether the current time point is in the peak time period of going on or off duty;
if the vehicle is not in the peak time period of going to and fro, the number of passing vehicles in the preset time period is obtained through detection of an electronic barrier gate of the parking lot, and the vehicle flow at the fork road is obtained through calculation;
and if the traffic flow is in the peak time period of going to and going to duty, calling a historical record table of the traffic flow of the peak time of going to and going to duty in the parking lot to obtain the traffic flow of the fork.
6. The signal light control method of intelligent traffic according to claim 5, wherein the traffic section is a one-way section,
the calculating, based on the AI automatic learning algorithm, a second congestion value according to the incoming traffic flow, the outgoing traffic flow, the traffic flow in the segment, and the intersection traffic flow includes:
based on the AI automatic learning algorithm, calculating to obtain an initial value according to the driving traffic flow, the driving traffic flow and the driving traffic flow in the segment;
calculating to obtain a first congestion adjustment coefficient according to the vehicle flow at the fork;
and calculating to obtain a second congestion value according to the first congestion adjustment coefficient and the initial value.
7. The signal light control method of intelligent traffic according to claim 5, wherein when the traffic section includes a first section and a second section,
the calculating, based on the AI automatic learning algorithm, a second congestion value according to the incoming traffic flow, the outgoing traffic flow, the traffic flow in the segment, and the intersection traffic flow includes:
based on the AI automatic learning algorithm, calculating to obtain an initial value of the first road section according to the driving-in traffic flow, the driving-out traffic flow and the driving traffic flow in the section of the first road section;
based on the AI automatic learning algorithm, calculating to obtain an initial value of the second road section according to the driving-in traffic flow, the driving-out traffic flow and the driving traffic flow in the section of the second road section;
identifying that the intersection meets the first road segment or the second road segment;
if the intersection is connected with the first road section, calculating a second congestion adjustment coefficient of the first road section according to the traffic flow of the intersection, and calculating a second congestion value of the first road section according to the second congestion adjustment coefficient and the initial value of the first road section;
if the intersection is connected with the second road section, calculating to obtain a third congestion adjustment coefficient of the second road section according to the traffic flow of the intersection, and calculating to obtain a second congestion value of the second road section according to the third congestion adjustment coefficient and the initial value of the second road section.
8. The signal lamp control method for intelligent transportation according to claim 7, further comprising:
judging whether a vehicle turning point exists between the first road section and the second road section;
if the vehicle turning points exist, acquiring a first turning vehicle number and a second turning vehicle number of the vehicle turning points in the preset time period, wherein the first turning vehicle number is the number of vehicles which enter the second road section by turning around from the first road section, the second turning vehicle number is the number of vehicles which enter the first road section by turning around from the second road section,
respectively calculating to obtain a first turning vehicle flow and a second turning vehicle flow according to the first turning vehicle number and the second turning vehicle number;
and adjusting the traffic flow of the running vehicles in the sections of the first road section and the second road section according to the first turning traffic flow and the second turning traffic flow.
9. The signal light control method for intelligent transportation according to claim 5, wherein the generating of the signal light joint control strategy for the section entrance and the section exit, and jointly controlling the signal lights for the section entrance and the section exit through the signal light joint control strategy so that the second congestion value is adjusted to be not greater than the preset congestion threshold value further comprises:
and establishing communication connection with the parking lot electronic barrier gate, controlling the opening speed of an entrance barrier gate of the parking lot electronic barrier gate to be increased or the entrance barrier gate to be normally opened, and controlling the opening speed of an exit barrier gate of the parking lot electronic barrier gate to be reduced.
10. The signal lamp control system of the intelligent traffic is characterized by comprising:
the system comprises an information acquisition module, an information processing module and a signal lamp control strategy module;
the information acquisition module is used for acquiring road section information of a traffic road section in an intelligent traffic network based on a machine vision technology, wherein the road section information comprises road section in-information, road section entrance information and road section exit information of the traffic road section, and both a road section entrance and a road section exit are signal lamp intersections;
the information processing module is used for determining the traffic flow of the vehicle entering according to the road section entrance information and determining the traffic flow of the vehicle leaving according to the road section exit information; determining the traffic flow in the section and whether a fork exists according to the information in the section; if no fork exists, calculating to obtain a first congestion value according to the driving traffic flow, the driving traffic flow and the driving traffic flow in the section based on an AI (automatic learning) algorithm;
the signal lamp control strategy module is used for generating a signal lamp combined control strategy of the road section entrance and the road section exit when the first congestion value is larger than a preset congestion threshold, and jointly controlling signal lamps of the road section entrance and the road section exit through the signal lamp combined control strategy to enable the first congestion value to be adjusted to be not larger than the preset congestion threshold;
the information processing module is also used for acquiring the turnout traffic flow of the turnout if the turnout exists; based on the AI automatic learning algorithm, calculating to obtain a second congestion value according to the incoming traffic flow, the outgoing traffic flow, the traffic flow in the section and the traffic flow at the fork;
the signal lamp control strategy module is further configured to generate a signal lamp combined control strategy for the road section inlet and the road section outlet if no intersection signal lamp is available, and jointly control the signal lamps at the road section inlet and the road section outlet through the signal lamp combined control strategy, so that the second congestion value is adjusted to be not greater than the preset congestion threshold; and if the turnout signal lamp exists, generating a signal lamp combined control strategy of the turnout, the road section inlet and the road section outlet, and jointly controlling the signal lamps of the road section inlet and the road section outlet and the turnout signal lamp through the signal lamp combined control strategy to enable the second congestion value to be adjusted to be not more than the preset congestion threshold value.
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