CN113380056A - Intelligent regional traffic coordination control method - Google Patents
Intelligent regional traffic coordination control method Download PDFInfo
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- CN113380056A CN113380056A CN202110650326.9A CN202110650326A CN113380056A CN 113380056 A CN113380056 A CN 113380056A CN 202110650326 A CN202110650326 A CN 202110650326A CN 113380056 A CN113380056 A CN 113380056A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/081—Plural intersections under common control
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
Abstract
The invention discloses an intelligent regional traffic coordination control method, which adopts a mobile navigation application to obtain a travel destination, the system obtains a vehicle identification number, a geographic coordinate and travel destination basic information through the mobile navigation application, the system returns a traffic profile of the whole region, n travel schemes and corresponding electronic integral values to the mobile navigation application, an intelligent agent selects a certain travel scheme according to the self condition, and the system adds the electronic integral values corresponding to the schemes to an electronic account of the intelligent agent. According to the invention, through a modern artificial intelligence information technology, people and vehicles, vehicles and vehicles, and vehicles and road intelligent networks are constructed, real-time traffic road conditions are continuously acquired, data are transmitted and processed, information is timely transmitted to traffic participants, vehicles are effectively distributed on a proper road network, and further the road and vehicle operation efficiency is improved.
Description
Technical Field
The invention relates to a control method, in particular to an intelligent regional traffic coordination control method.
Background
The traffic signal control system is a regional traffic signal real-time networking control system integrating modern computers, communication and control technologies. The traffic signal control system goes through four stages of mechanical control, electric control and computer control from the initial manual control. The control range is also developed from the initial single-point intersection signal control system to the coordination control system of the main line or even the regional control system of the whole traffic network.
With the continuous and rapid development of social economy, the quantity of motor vehicles kept is continuously improved, and the urban traffic problem is increasingly serious. Due to the fact that planning of road early conditions is insufficient, traffic jam is increasingly prominent, and road basic conditions are limited by a plurality of factors and cannot be expanded infinitely, it is important to scientifically optimize travel routes of drivers and vehicles and give full play to the traffic efficiency of a road network.
Disclosure of Invention
The present invention is directed to a method for controlling traffic coordination in an intelligent area, so as to solve the problems set forth in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
an intelligent regional traffic coordination control method comprises the following steps:
step 1: the method comprises the steps that a mobile navigation application acquires a travel destination, a system acquires a vehicle identification number, a geographic coordinate and travel destination basic information through the mobile navigation application, the system returns a traffic profile of the whole area, n travel schemes and corresponding electronic integral values to the mobile navigation application, an intelligent agent selects a certain travel scheme according to the condition of the intelligent agent, and the system adds the electronic integral values corresponding to the schemes to an electronic account of the intelligent agent;
step 2: the intelligent agent selects a regional traffic coordination control strategy, the system counts the congestion conditions of different roads and sections in real time, collects the current geographic coordinates of each intelligent agent in real time, the system sends a new travel scheme and a corresponding electronic integral value to part of intelligent agents going to the congested roads or sections, the intelligent agent is prompted to change a travel route through a mobile navigation application, and the intelligent agent selects the travel scheme;
and step 3: the intelligent agent executes a regional traffic coordination control strategy;
and 4, step 4: the agent earns rewards or deducts electronic points;
and 5: upgrading a regional traffic coordination control strategy by an agent;
and continuously iterating the 5 steps by the system and the intelligent agent until the system generates an optimal regional traffic coordination control strategy.
As a further scheme of the invention: step 3, the intelligent agent executes the regional traffic coordination control strategy and is divided into three conditions: firstly, executing a new travel scheme; secondly, the method is executed according to the original scheme; and thirdly, executing according to other schemes, collecting the condition that the intelligent agent executes the regional traffic coordination control strategy, feeding back a traffic flow index to a signal lamp control system of a congested road or a section, and dynamically adjusting the phase or a phase timing scheme by the signal lamp control system in combination with the actual condition.
As a further scheme of the invention: in step 4, if the agent executes the new travel scheme in step 3, the system adds the electronic integral value corresponding to the new travel scheme to the electronic account of the agent, otherwise, the system deducts the electronic integral value corresponding to the travel scheme from the electronic account of the agent, and the system feeds back the electronic integral change condition to the agent in real time through the mobile navigation application.
As a further scheme of the invention: in the step 5, the intelligent agent learns the regional traffic coordination control strategy from the situation that the points are changed, and after the intelligent agent travels to the destination, the system stores the situation of the execution of the current travel scheme of the intelligent agent into the cloud platform as a historical basis.
As a still further scheme of the invention: the intelligent agent is a vehicle and a driver.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, through a modern artificial intelligence information technology, intelligent networks of people and vehicles, vehicles and roads are constructed, real-time traffic road conditions are continuously acquired, data are transmitted and processed, information is timely transmitted to traffic participants, vehicles are effectively distributed to a proper road network, and further the operation efficiency of the roads and vehicles is improved; the method comprehensively judges the traffic flow and the traffic situation of the road, processes various traffic emergencies, scientifically and real-timely adjusts the traffic light conversion of each control intersection, and can effectively reduce the parking times and delay of the vehicles, thereby relieving the vehicle congestion phenomenon to a certain extent; the method is beneficial to adjusting the active and passive relations between the two, and plays a certain role in relieving traffic jam.
Drawings
Fig. 1 is a flowchart of a traffic coordination control method in an intelligent area.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the embodiment of the invention, an intelligent regional traffic coordination control method is shown in fig. 1, and comprises the following steps:
step 1: the intelligent agent observes the traffic environment. And the intelligent agent inputs a travel destination in the mobile navigation application. The system obtains basic information such as vehicle identification numbers, geographic coordinates, travel destinations and the like of the intelligent agents through the mobile navigation application. The system balances and calculates from the angles of space-time, fairness, history and the like, and returns the traffic general profile, n travel schemes and corresponding electronic integral values to the whole area of the intelligent agent in sequence. The intelligent agent selects a certain travel scheme according to the self condition, and the system adds the electronic integral value corresponding to the scheme to the electronic account of the intelligent agent.
Step 2: and the intelligent agent selects a regional traffic coordination control strategy. The system counts the congestion conditions of different roads and sections in real time and collects the current geographic coordinates of each intelligent agent in real time. The system balances and calculates from the angles of space-time, fairness, history and the like, forwards sends a new travel scheme and a corresponding electronic integral value to some intelligent agents on congested roads or sections, and prompts the intelligent agents to change a driving route through a mobile navigation application. The agent makes a selection of a travel plan.
And step 3: and the intelligent agent executes the regional traffic coordination control strategy. The intelligent execution strategy is divided into three cases: firstly, executing a new travel scheme; secondly, the method is executed according to the original scheme; and thirdly, executing according to other schemes. The intelligent system collects the condition that the intelligent agent executes the regional traffic coordination control strategy, the system feeds back the traffic flow index to the signal lamp control system of the congested road or the district, and the signal lamp control system dynamically adjusts the phase or the phase timing scheme by combining the actual condition.
And 4, step 4: the agent receives a reward or deducts an electronic credit. If the agent executes the new travel plan in step 3, the system adds the electronic integral value corresponding to the new travel plan to the electronic account of the agent. And conversely, the system deducts the electronic integral value corresponding to the trip scheme from the electronic account of the agent. The system feeds the electronic integral change condition back to the intelligent agent in real time through the mobile navigation application.
And 5: and upgrading the regional traffic coordination control strategy by the intelligent agent. And the intelligent agent learns the regional traffic coordination control strategy from the situation of integral change. After the intelligent agent travels to the destination, the system stores the execution situation of the current travel scheme of the intelligent agent into the cloud platform as a historical basis.
And continuously iterating the 5 steps by the system and the intelligent agent until the system generates an optimal regional traffic coordination control strategy.
In the invention, the traffic participants are divided into drivers, pedestrians, traffic law enforcement, motor vehicles, non-motor vehicles, roads, signal control facilities, mobile navigation applications and the like.
In the invention, the system adopts an artificial intelligence algorithm for reinforcement learning to guide a driver or an unmanned vehicle to run. Reinforcement learning has five core components, which are agent, goal, environment, action, reward, respectively. Wherein the agent represents a driver and a vehicle; the target represents a destination for travel; the environment represents a traffic environment; the action represents the travel of the vehicle; the reward represents an electronic point that the system gives the driver or the unmanned vehicle an electronic point for a certain driving, and the electronic point is exchanged into a mental and physical reward. The system adopts the angles of space-time, fairness, history and the like to balance and calculate the regional traffic coordination control strategy, and the specific rule is as follows:
(1) space-time angle: the method is divided into two aspects of time and space. Generally speaking, the intelligent agent pays attention to the fact that driving time is as short as possible, and travel distance is as short as possible. The system dynamically adjusts the space-time ratio of the intelligent agent travel scheme by combining the congestion condition of the road or the district, and the regional traffic coordination control strategy is optimized as much as possible.
(2) Fairness angle: the system acquires the condition of the vehicle according to the vehicle identification number of the intelligent agent and judges whether the vehicle is a business vehicle, a special vehicle, a common vehicle and the like. When the system forwards issues a new travel scheme to some intelligent agents on congested roads or sections, the intelligent agents are randomly selected according to the conditions of vehicles.
(3) Historical angle: the system dynamically adjusts the electronic integral value corresponding to the newly generated travel scheme according to the historical situation of the intelligent agent execution region traffic coordination control strategy and the principle of reward as main part and penalty as auxiliary part so as to induce the intelligent agent to execute the travel scheme recommended by the system.
In conclusion, the invention constructs intelligent networks of people and vehicles, vehicles and roads through the modern artificial intelligence information technology, continuously collects real-time traffic road conditions, transmits and processes the data, and timely transmits the information to traffic participants, thereby realizing the effective distribution of vehicles to a proper road network and further improving the operation efficiency of roads and vehicles.
The method comprehensively judges the traffic flow and the traffic situation of the road, processes various traffic emergencies, scientifically and real-timely adjusts the traffic light conversion of each control intersection, and can effectively reduce the parking times and delay of the vehicles, thereby relieving the vehicle congestion phenomenon to a certain extent.
The urban traffic supply and demand balance problem is a fundamental problem of solving urban traffic jam, the traffic supply and the traffic demand are interactive and mutually influenced, and the intelligent regional traffic dispatching control is helpful for adjusting the active and passive relations between the traffic supply and the traffic demand and plays a certain role in relieving the traffic jam.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (5)
1. An intelligent regional traffic coordination control method is characterized by comprising the following steps:
step 1: the method comprises the steps that a mobile navigation application acquires a travel destination, a system acquires a vehicle identification number, a geographic coordinate and travel destination basic information through the mobile navigation application, the system returns a traffic profile of the whole area, n travel schemes and corresponding electronic integral values to the mobile navigation application, an intelligent agent selects a certain travel scheme according to the condition of the intelligent agent, and the system adds the electronic integral values corresponding to the schemes to an electronic account of the intelligent agent;
step 2: the intelligent agent selects a regional traffic coordination control strategy, the system counts the congestion conditions of different roads and sections in real time, collects the current geographic coordinates of each intelligent agent in real time, the system sends a new travel scheme and a corresponding electronic integral value to part of intelligent agents going to the congested roads or sections, the intelligent agent is prompted to change a travel route through a mobile navigation application, and the intelligent agent selects the travel scheme;
and step 3: the intelligent agent executes a regional traffic coordination control strategy;
and 4, step 4: the agent earns rewards or deducts electronic points;
and 5: upgrading a regional traffic coordination control strategy by an agent;
and continuously iterating the 5 steps by the system and the intelligent agent until the system generates an optimal regional traffic coordination control strategy.
2. The intelligent regional traffic coordination control method according to claim 1, wherein said step 3 intelligent agent executing regional traffic coordination control strategy is divided into three cases: firstly, executing a new travel scheme; secondly, the method is executed according to the original scheme; and thirdly, executing according to other schemes, collecting the condition that the intelligent agent executes the regional traffic coordination control strategy, feeding back a traffic flow index to a signal lamp control system of a congested road or a section, and dynamically adjusting the phase or a phase timing scheme by the signal lamp control system in combination with the actual condition.
3. The intelligent regional traffic coordination control method according to claim 1, wherein in step 4, if the agent executes the new travel scheme in step 3, the system adds the electronic integral value corresponding to the new travel scheme to the electronic account of the agent, otherwise, the system deducts the electronic integral value corresponding to the travel scheme from the electronic account of the agent, and the system feeds back the electronic integral change situation to the agent in real time through the mobile navigation application.
4. The intelligent regional traffic coordination control method according to claim 1, wherein in the step 5, the intelligent agent learns the regional traffic coordination control strategy from the situation that the points are changed, and after the intelligent agent travels to the destination, the system stores the situation that the current travel scheme of the intelligent agent is executed in the cloud platform as a historical basis.
5. The intelligent regional traffic coordination control method according to claim 1, wherein said agents are vehicles and drivers.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115083175A (en) * | 2022-06-23 | 2022-09-20 | 北京百度网讯科技有限公司 | Signal control method based on vehicle-road cooperation, related device and program product |
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