CN104766483A - Traffic control inducing coordination system and method based on cloud computing - Google Patents
Traffic control inducing coordination system and method based on cloud computing Download PDFInfo
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- 238000004458 analytical method Methods 0.000 claims description 23
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- 238000003064 k means clustering Methods 0.000 description 2
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- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
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Abstract
The invention discloses a traffic control inducing coordination system and method based on cloud computing. Cloud platform architecture is used as a foundation. The system comprises a traffic information collecting module, a traffic information processing module, a traffic state judging module, a traffic signal control optimization module, a traffic inducing scheme generating module and a displaying module. On the basis of a cloud computing platform, effective coordination of traffic control and inducing is achieved, and traffic control and inducing information is issued quickly and accurately.
Description
Technical field
The present invention relates to a kind of traffic coordinating system and method, particularly a kind of coordinating traffic control and traffic guidance system and method based on cloud computing.
Background technology
Coordinating traffic control and traffic guidance system is the important content of intelligent transportation system research.Traffic control system is optimized control by the timing scheme of the online traffic lights that satisfy the need, thus mandatory control is carried out to the behavior of vehicle, make the vehicle olderly flowage on road network, ensure that the road is clear by range of control, reduce the generation of traffic congestion, shorten hourage.System for traffic guiding is for core with real-time dynamic traffic theory of distribution, the modem technologies such as integrated use detection, communication, computing machine, control, satellite positioning tech and Geographic Information System, according to the traffic flow conditions of current road network and the destination of various vehicle, through optimizing the stroke route being calculated as vehicle and providing best, dynamically transport information and optimal path is provided to guide to driver.
In traditional traffic system, traffic control system and system for traffic guiding are two separate systems, incompatible between system, and transport information is difficult to even cannot share, and defines many " information island ".Traffic control system utilizes the transport information of crossing, uses corresponding traffic signals parameter optimization algorithm, take system optimal as target, generates traffic signal control scheme.System for traffic guiding is based on real-time transport information, optimum for target with user, for driver provides best driving path.System for traffic guiding provides corresponding induction information according to the time delay of crossing in controlled area, the information such as congestion and traffic events, induction information itself is obtained by the practical operation situation of current traffic signal control scheme and traffic flow, therefore current road conditions are reflected objectively, its route recommended allows vehicle avoid crowded section of highway as far as possible, from this some, induction information is all the driver being conducive to being about to enter this region.In addition, for user, when controlled area is for unimpeded state, traffic guidance is favourable for user; On the contrary, when controlled area be in traffic congestion even state of paralysis time, traffic guidance has been not just optimal path for user, and traffic behavior can be caused more to worsen.
From eighties of last century nineties, domestic and international experts and scholars expand research to Traffic Control and Guidance is collaborative, mainly contain four kinds of modes: data sharing formula, master-slave mode, pass rank cooperating type and integrated mode.In these four kinds of modes, effect is it is preferred that integrated mode, by control program and the induction scheme control variable as system, all state equations and the state equation retrained as system and the constraint of Comprehensive Control and induction, with the overall goal of road network for optimal objective, and solved by various optimization method, obtain the optimal strategy controlling induction.But, along with the continuous expansion of controlled area road network scale, amount of traffic information is also huge all the more, and the transport information processing mode of standalone and cooperation model derivation algorithm cannot meet the demand of user, therefore, have impact on the efficient issue of Traffic Control and Guidance strategy.
Summary of the invention
The object of the invention is to overcome the slow and inefficient problem of model solution of existing coordinating traffic control and traffic guidance system transport information processing speed, and coordinating traffic control and traffic guidance system and method when a kind of efficient real based on cloud computing is provided, and then improve the operational efficiency of traffic system.
A kind of coordinating traffic control and traffic guidance system based on cloud computing of the present invention comprises traffic information collection module, transport information processing module, traffic state analysis module, coordinating traffic control and traffic guidance module, traffic signalization module, traffic guidance schemes generation module and display module, wherein transport information processing module is connected with traffic information collection module, traffic state analysis module is connected with transport information processing module, coordinating traffic control and traffic guidance module is connected with traffic state analysis module, traffic signalization module is connected with display module with coordinating traffic control and traffic guidance module respectively with after traffic guidance schemes generation wired in parallel.
Traffic information collection module, for gathering multi-source traffic information;
Transport information processing module, for fast processing multi-source traffic information;
Traffic state analysis module, for real time discriminating traffic behavior;
Coordinating traffic control and traffic guidance module, for providing traffic signalization parameter and guidance information;
Traffic signalization module, for generating traffic control scheme;
Traffic guidance schemes generation module, for generating traffic guidance scheme;
Display module, for issuing traffic induction information.
Described transport information comprises flow, speed and time occupancy.
Described signal controling parameters comprises signal period and split.
A kind of coordinating traffic control and traffic guidance method based on cloud computing of the present invention is applied to the above-mentioned coordinating traffic control and traffic guidance system based on cloud computing, comprises the following steps:
One, multi-source traffic information is gathered;
Two, the multi-source traffic information gathered is processed;
Three, the transport information of described process is sent to traffic state analysis module, carries out traffic state analysis;
Four, solve coordinating traffic control and traffic guidance model, generate signal controling parameters;
Five, traffic signalization parameter and traffic state information are sent to traffic signal optimization control module and traffic guidance schemes generation module, generate traffic control scheme and traffic guidance scheme;
Six, traffic control and traffic guidance scheme and effect thereof is shown.
Described transport information comprises flow, speed and time occupancy.
Described signal controling parameters comprises signal period and split.
Described information processing method, traffic state analysis method and coordinating traffic control and traffic guidance model solution all adopt the parallel method based on cloud computing.
Beneficial effect of the present invention: the design proposal that the invention provides a kind of traffic control and traffic guidance based on cloud computing integration coherent system, to solve in traditional coherent system design proposal the slow and inefficient problem of model solution of multi-source traffic information processing speed, the adjustment of traffic flow is shortened reaction time, makes road more unimpeded.
Accompanying drawing explanation
Fig. 1 is the structural drawing of the embodiment of the present invention;
Fig. 2 is the process flow diagram of the embodiment of the present invention.
Embodiment
Refer to shown in Fig. 1 and Fig. 2, for embodiments of the invention, a kind of coordinating traffic control and traffic guidance system based on cloud computing described in the present embodiment comprises traffic information collection module 1, transport information processing module 2, traffic state analysis module 3, coordinating traffic control and traffic guidance module 4, traffic signalization module 5, traffic guidance schemes generation module 6 and display module 7, wherein transport information processing module 2 is connected with traffic information collection module 1, traffic state analysis module 3 is connected with transport information processing module 2, coordinating traffic control and traffic guidance module 4 is connected with traffic state analysis module 3, traffic signalization module 5 is connected with display module 7 with coordinating traffic control and traffic guidance module 4 respectively with after the parallel connection of traffic guidance schemes generation module 6.
Traffic information collection module 1, for gathering multi-source traffic information, the multi-source traffic information gathered comprises flow, speed and time occupancy;
Transport information processing module 2, for fast processing multi-source traffic information, processes the multi-source traffic information collected, and comprises traffic data pre-service, traffic data merges, traffic data is predicted and traffic data excavates;
Traffic state analysis module 3, for real time discriminating traffic behavior, analyzes the transport information after process, obtains the traffic state information of current time or future time instance;
Coordinating traffic control and traffic guidance module 4, solves traffic control and traffic guidance model, and for providing traffic signalization parameter and guidance information, described signal controling parameters comprises signal period and split;
Traffic signalization module 5, for generating traffic control scheme;
Traffic guidance schemes generation module 6, for generating traffic guidance scheme;
Display module 7, for issuing traffic induction information, the effect of display coordinating traffic control and traffic guidance scheme.
Described transport information comprises flow, speed and time occupancy.
A kind of coordinating traffic control and traffic guidance method based on cloud computing described in the present embodiment is applied to the above-mentioned coordinating traffic control and traffic guidance system based on cloud computing, comprises the following steps:
One, multi-source traffic information is gathered;
Two, the multi-source traffic information gathered is processed;
Three, the transport information of described process is sent to traffic state analysis module, carries out traffic state analysis;
Four, solve coordinating traffic control and traffic guidance model, generate signal controling parameters;
Five, induction scheme is generated;
Six, traffic control and traffic guidance scheme and effect thereof is shown.
Described transport information comprises flow, speed and time occupancy.
Described signal controling parameters comprises signal period and split.
Described information processing method, traffic state analysis method and coordinating traffic control and traffic guidance model solution all adopt the parallel method based on cloud computing.
Traffic information collection module 1 stores the traffic data coming from multiple checkout equipment and gather, the multi-source traffic data collected is sent to transport information processing module 2, and transport information processing module 2 is responsible for carrying out pre-service, data fusion and data prediction to multi-source traffic data.
The idiographic flow that traffic state analysis module 3 analyzes subsequent time traffic behavior is, first by the flow of current time after pre-service, speed, occupation rate equal time sequence inputting in parallel K-means clustering algorithm, calculate three kinds of traffic behaviors: unimpeded, crowded, serious congested traffic parameter threshold, then the traffic parameter of parallel support vector machines model to subsequent time is utilized to predict, obtain each traffic parameter value of subsequent time, again be input in K-means clustering algorithm, judge the traffic behavior in each section of subsequent time.
The expression formula of the average stroke speed of a motor vehicle is:
θ
i(t)＝L
i/T
i(t)
In formula, L
ifor road section length; T
it () is section formation time.
The expression formula of section saturation volume rate is as follows:
S＝V/C
In formula, V is the actual flow in section; C is road section capacity.
Time occupancy refers in observation time, and wagon detector detects the time of vehicle and the ratio detecting T.T., and expression is as follows:
occupy＝ΣΔt
i/T
i(t)
In formula, Δ t
iit is the time (s) that i-th car is detected; T
it () is detecting device detection T.T. (s).
Coordinating traffic control and traffic guidance module 4, according to the result of traffic state analysis module 3, performs coordinating traffic control and traffic guidance strategy.When traffic behavior is in unimpeded, even if there is unsaturation traffic congestion, Traffic Control and Guidance need not be coordinated just can solve; When traffic behavior is in crowded, traffic flow, close to state of saturation, needs to perform Traffic Control and Guidance coordination strategy; When traffic behavior is in seriously crowded, the traffic flow of all roads of road network is in blocked state, and Traffic Control and Guidance is coordinated to lose efficacy, and needs to add other traffic management measures, solves over-saturation traffic congestion.Coordinating traffic control and traffic guidance module 4 relates to the Solve problems of model, and the paralleling genetic algorithm that the present embodiment have employed based on cloud computing solves, and reaches object fast and accurately.
Traffic signalization module 5 and traffic guidance schemes generation module 6 receive and come from the traffic signals parameter and induction information that coordinating traffic control and traffic guidance module 4 sends, and generate traffic control strategy and traffic guidance strategy.
This embodiment, by refreshing in real time traffic behavior, determines the traffic behavior in each section of future time instance exactly, and performs coordinating traffic control and traffic guidance strategy for the traffic behavior in each section of future time instance.
Claims (7)
1. the coordinating traffic control and traffic guidance system based on cloud computing, it is characterized in that: comprise traffic information collection module (1), transport information processing module (2), traffic state analysis module (3), coordinating traffic control and traffic guidance module (4), traffic signalization module (5), traffic guidance schemes generation module (6) and display module (7), wherein transport information processing module (2) is connected with traffic information collection module (1), traffic state analysis module (3) is connected with transport information processing module (2), coordinating traffic control and traffic guidance module (4) is connected with traffic state analysis module (3), traffic signalization module (5) is connected with display module (7) with coordinating traffic control and traffic guidance module (4) respectively with after traffic guidance schemes generation module (6) parallel connection,
Traffic information collection module (1), for gathering multi-source traffic information;
Transport information processing module (2), for fast processing multi-source traffic information;
Traffic state analysis module (3), for real time discriminating traffic behavior;
Coordinating traffic control and traffic guidance module (4), for providing traffic signalization parameter and traffic guidance letter
Breath; Traffic signalization module (5), for generating traffic control scheme;
Traffic guidance schemes generation module (6), for generating traffic guidance scheme;
Display module (7), for issuing traffic induction information.
2. a kind of coordinating traffic control and traffic guidance system based on cloud computing according to claim 1, is characterized in that: described transport information comprises flow, speed and time occupancy.
3. a kind of coordinating traffic control and traffic guidance system based on cloud computing according to claim 1, is characterized in that: described signal controling parameters comprises signal period and split.
4., based on a coordinating traffic control and traffic guidance method for cloud computing, comprise the following steps:
One, multi-source traffic information is gathered;
Two, the multi-source traffic information gathered is processed;
Three, the transport information of described process is sent to traffic state analysis module, carries out traffic state analysis;
Four, solve coordinating traffic control and traffic guidance model, generate signal controling parameters;
Five, traffic signalization parameter and traffic state information are sent to traffic signal optimization control module and traffic guidance schemes generation module, generate traffic control scheme and traffic guidance scheme;
Six, traffic control and traffic guidance scheme and effect thereof is shown.
5. a kind of coordinating traffic control and traffic guidance method based on cloud computing according to claim 4, is characterized in that: described transport information comprises flow, speed and time occupancy.
6. a kind of coordinating traffic control and traffic guidance method based on cloud computing according to claim 4, is characterized in that: described signal controling parameters comprises signal period and split.
7. a kind of coordinating traffic control and traffic guidance method based on cloud computing according to claim 4, is characterized in that: described information processing method, traffic state analysis method and coordinating traffic control and traffic guidance model solution all adopt the parallel method based on cloud computing.
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| CN110264717A (en) * | 2019-06-25 | 2019-09-20 | 牡丹江师范学院 | A kind of municipal intelligent traffic regulator control system |
| CN111341107A (en) * | 2020-05-18 | 2020-06-26 | 成都信息工程大学 | Shared traffic control method based on cloud platform data |
| CN114463868A (en) * | 2022-02-08 | 2022-05-10 | 山东高速股份有限公司 | Toll station traffic flow combination prediction method and system for traffic flow management and control |
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Application publication date: 20150708 |