CN106448199B - A kind of traffic control method based on text mining - Google Patents
A kind of traffic control method based on text mining Download PDFInfo
- Publication number
- CN106448199B CN106448199B CN201610836901.3A CN201610836901A CN106448199B CN 106448199 B CN106448199 B CN 106448199B CN 201610836901 A CN201610836901 A CN 201610836901A CN 106448199 B CN106448199 B CN 106448199B
- Authority
- CN
- China
- Prior art keywords
- crossroad
- traffic control
- msub
- determined
- road
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Traffic Control Systems (AREA)
Abstract
The present invention provides a kind of traffic control method based on text mining, including:Step 100, the text message of traffic control is obtained;Step 200, the radiation scope of crossroad is determined;Step 300, the keyword in the crossroad radiation scope is determined;Step 400, the keyword frequency of occurrences and number are counted;Step 500, the degree of Congestion of the crossroad is predicted;Step 600, the traffic control information of the crossroad is adjusted;Step 700, the cycle of epicycle traffic control adjustment is determined.The present invention can according in certain time with the relevant text message of traffic control, the following a period of time possible degree of Congestion in crossroad is specified in analysis, the traffic control information for specifying crossroad is adjusted based on degree of Congestion, avoid causing traffic congestion, people's trip quality is improved, is conducive to build low carbon society.
Description
Technical field
The present invention relates to field of traffic control, more particularly to a kind of traffic control method based on text mining.
Background technology
In recent years, Britain, Australia, Europe and the U.S. establish traffic control system in some cities.At these
It is most of that magnetic loop detector, and the control device by each crossing or work people are all installed near each crossing in system
Traffic control parameter by communication network input microprocessors such as telephone wire, cable, closed-circuit television lines, is used minicom by member
Carry out centralized Control.The urban traffic control of some existing independent developments domestic at present and management system, but in overall performance ratio
External homogeneous system still has larger gap, only obtains some applications in some small and medium-sized cities.Draw in domestic city especially big city
Into traffic system largely be import SCOOT and SCATS systems.Since China's traffic flow is mixed traffic flow, and it is external
Traffic flow differ widely, the using effect of external traffic control system at home is unsatisfactory.Compared with foreign countries, China's mesh
Preceding traffic is also relatively backward, is mainly manifested in:
(1) urban road unreasonable structure, most cities road space structure category plane traffic behavior, forms " people's car
Mixed row, speed car, which mixes, to be sailed " the characteristics of.Primary and secondary arterial highway and branch line are out of proportion, and joining relation is disorderly, makes arterial road be difficult to send out
Wave its function.For path area, domestic urban road area ratio is less than same size big city in the world.
(2) traffic trip unbalance of structure.Domestic urban transportation is mainly by various motor vehicles, non-motor vehicle and pedestrian's structure
Into forming special ternary mixed traffic structure.
(3) traffic management technology level is low, frequent accidents.Two quasi-representatives are presented the problem of Urban Transport at present
Phenomenon:Manage ineffective, disorder;There is no science, reasonable, effective City Traffic Monitor System.Thus the consequence day brought
Become serious.Show as that the road network traffic capacity is big significantly lower than design requirement and fluctuation, the travel time, it is difficult to predict, friendship occurred frequently
Interpreter's event, traffic environment deterioration, the easy fatigue of traveler etc..
The content of the invention
The present invention is to solve the above problems, provide a kind of traffic control method based on text mining, it is characterised in that
Comprise the following steps:
Step 100, the text message of traffic control is obtained;
Step 200, the radiation scope of crossroad is determined;
Step 300, the keyword in the crossroad radiation scope is determined;
Step 400, the keyword frequency of occurrences and number are counted;
Step 500, the degree of Congestion of the crossroad is predicted;
Step 600, the traffic control information of the crossroad is adjusted;
Step 700, the cycle of epicycle traffic control adjustment is determined.
The present invention can specify crossroad future according in certain time with the relevant text message of traffic control, analysis
Possible degree of Congestion for a period of time, is adjusted the traffic control information for specifying crossroad based on degree of Congestion, avoids causing
Traffic congestion, improves people's trip quality, is conducive to build low carbon society.
Embodiment
To make the object, technical solutions and advantages of the present invention clearer, below by the technology in the embodiment of the present invention
Scheme is clearly and completely described, it is clear that and described embodiment is part of the embodiment of the present invention, rather than whole
Embodiment.Based on the embodiments of the present invention, those of ordinary skill in the art are obtained without creative efforts
The every other embodiment obtained, belongs to the scope of protection of the invention.
The embodiment of the present invention one discloses a kind of traffic control method based on text mining, it is characterised in that including with
Lower step:
Step 100, the text message of traffic control is obtained;
Step 200, the radiation scope of crossroad is determined;
Step 300, the keyword in the crossroad radiation scope is determined;
Step 400, the keyword frequency of occurrences and number are counted;
Step 500, the degree of Congestion of the crossroad is calculated;
Step 600, the traffic control information of the crossroad is adjusted;
Step 700, the cycle of epicycle traffic control adjustment is determined.
The embodiment of the present invention two discloses a kind of traffic control method based on text mining, it is characterised in that including with
Lower step:
Step 100, the text message of traffic control is obtained;
The method that the text message of traffic control is obtained in the step 100 includes but are not limited to crawl short message,
Capture map software information and crawl internet information.
Step 200, the radiation scope of crossroad is determined;
The step 200 further comprises:
Step 220, the two road rank by the crossroad is determined;
The road grade criteria for classifying in the present invention is:Urban road ranking score through street, trunk roads, secondary distributor road, branch
Level Four, red line width control systems at different levels:Through street is not less than 40 meters, 30-40 meters of major trunk roads, 25-40 meters of subsidiary road, and branch 12-
25 meters.(according to《Urban road engineering design specification》(CJJ37-2012), the red line width for road is not made mandatory
It is required that only being required road width requirement, cross section composition and each functional bands minimum widith of road)
Level-one road is through street, value 1:Median strip is equipped with urban road, there are more than four car lanes,
It is all or part of to be come in and gone out using crossings on different level and control, the road travelled at a relatively high speed for automobile.Also known as parkway.It hurry up
The designed driving speed on fast road is 60-80km/h.
Second grade highway is trunk roads, value 2:The main line of each subregion in city is connected, based on communication function.Trunk roads are set
Meter road speed is 40-60km/h.
Tertiary road is secondary distributor road, value 3:The collecting and distributing effect of traffic of trunk roads and each by stages is undertaken, has service work(concurrently
Energy.The designed driving speed of secondary distributor road is 40km/h.
Level Four road is branch, value 4:Secondary distributor road and the connecting line on neighbour road (cell road), based on service function.Branch
The designed driving speed on road is 30km/h.
Step 240, the number of track-lines in the two road by the crossroad is determined;
Step 260, the heavy construction quantity between the crossroad and neighbouring crossroad is determined, it is big in the present invention
Type building refers to:The building engineering of more than 25 layers (containing, similarly hereinafter);Highly more than 100 meters of structures or building engineering;
The building engineering that more than 30,000 square metres of single building area;
The building engineering that more than 30 meters of single span;The residential quarters or building that more than 100,000 square metres of construction area
Group project;The building engineering of more than 100,000,000 yuan of contract amount of peace is built in individual event;
More than 15 meters of depth, and the Soft foundation treatment engineering of more than 10,000,000 yuan of individual works contract amount;Single pile is born
More than load 6000kN, and the ground and foundation engineering of more than 10,000,000 yuan of individual works contract amount;More than 11 meters of depth, and it is single
The Large and Deep Foundation Pit and earth and rock works of 10,000,000 yuan of item engineering contract volume;More than 1000 tons of steel construction weight, and steel construction
The structural steelwork that more than 20,000 square metres of construction area;More than 300 tons of grid structure weight, and grid structure construction area
More than 5000 square metres, and the rack engineering of more than 70 meters of the rack length of side;
Step 280, the radiation model of the crossroad is calculated according to the road grade, number of track-lines and heavy construction quantity
Enclose, the formula for calculating radiation scope is:
Wherein Rad be the crossroad radiation scope, L1And L2Respectively by first of the crossroad and
Article 2 road grade, N1And N2Respectively pass through first of the crossroad and the track quantity of Article 2 road, NcFor
Heavy construction quantity around the crossroad, α and β are respectively first and Article 2 road by the crossroad
Weight coefficient, have α, β ∈ [0,1], and alpha+beta=1, λ is radiation scope coefficient, can be adjusted according to city size, preferably
For 5.
Usually, the road grade value by a crossroad is smaller, illustrates that this crossroad is more important, if
Number of track-lines by a crossroad is more, illustrates that this crossroad is more important, if the heavy construction around crossroad
It is more, illustrate that this crossroad is more important.So the radiation scope calculation formula of the present invention can reflect different parameters to spoke
Influence and the significance level of scope are penetrated, and the use of radiation scope coefficient enables to city of this formula suitable for different scales
City, has further expanded the practicality.
Step 300, the keyword in the crossroad radiation scope is determined, the keyword in the step 300 includes
But address is not limited only to, street name, number, building name, organization, performs title, tournament names.
Step 400, the keyword frequency of occurrences and number are counted;
The step 400 further comprises:
Step 420, the keyword in text message is extracted;
Step 440, the total degree that each keyword occurs in text message is counted;
Step 450, the total degree N that all keywords occur in text message is calculated
Wherein wiThe total degree occurred for i-th of keyword, n are the quantity of keyword;
Step 460, the true number W that i-th of keyword occurs in text message is calculatedi,
Wherein wjThe total degree occurred for j-th of keyword, rijSimilar journey for j-th of keyword to i-th of keyword
Spend coefficient,
rij∈ [0,1], i, j ∈ [1, n], similarity degree coefficient calculation method can use the cosine based on space vector to calculate
Method;
The true number that so-called keyword occurs, is because a place name may have different form of presentation, different passes
Keyword is probably strong correlation, such as " State Intellectual Property Office " can be considered as same keyword with " office is known by state ", with address
" Xitucheng Lu 6 " is also strong correlation, and similarity degree coefficient is exactly the measurement for describing to contact between keyword, is had no associated
Similarity degree coefficient is 0 between keyword, and the similarity degree coefficient of keyword full name and abbreviation is 1.
Step 470, the frequency f that i-th of keyword occurs is calculatedi
Wherein Δ t is the time cycle of the keyword in statistics text message;
Step 480, the number and frequency that are occurred according to keyword calculate the temperature h of the crossroad
Wherein WkThe true number occurred for k-th of keyword in the crossroad radiation scope, fkFor the cross
The frequency that k-th of keyword in the radiation scope of crossing occurs, nradFor the keyword number in the crossroad radiation scope
Amount, γ are adjustment factor, γ ∈ [0,1].
Step 500, the degree of Congestion of the crossroad is predicted, specific method is:
Step 600, the traffic control information of the crossroad is adjusted, specific method is:
Given first threshold T, if degree of Congestion is more than first threshold, then report warning information to citywide automobile, carry
Show that the crossroad is likely to occur congestion, remind citizen to adjust traffic path;
Step 700, the cycle of epicycle traffic control adjustment is determined, the duration for adjusting the cycle is preferably 30 minutes.
This will not be repeated here with method something in common for other, and details refer to method declaratives.
The embodiment of the present invention can specify four crossway according in certain time with the relevant text message of traffic control, analysis
The following a period of time possible degree of Congestion of mouth, is adjusted the traffic control information for specifying crossroad according to degree of Congestion, keeps away
Exempt to cause traffic congestion, improve people's trip quality, be conducive to build low carbon society.
Finally it should be noted that:The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations;Although
The present invention is described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that:It still may be used
To modify to the technical solution described in foregoing embodiments, or equivalent substitution is carried out to which part technical characteristic;
And these modification or replace, do not make appropriate technical solution essence depart from various embodiments of the present invention technical solution spirit and
Scope.
Claims (2)
1. a kind of traffic control method based on text mining, it is characterised in that comprise the following steps:
Step 100, the text message of traffic control is obtained, the method for the text message for obtaining traffic control includes capturing short
Letter information, captures map software information and crawl internet information;
Step 200, the radiation scope of crossroad is determined;
Step 300, the keyword in the crossroad radiation scope is determined;
Step 400, the keyword frequency of occurrences and number are counted;
Step 500, the degree of Congestion of the crossroad is predicted;
Step 600, the traffic control information of the crossroad is adjusted;
Step 700, the cycle of epicycle traffic control adjustment is determined;
Wherein, the step 200 further comprises:
Step 220, the two road rank by the crossroad is determined;
Step 240, the number of track-lines in the two road by the crossroad is determined;
Step 260, the heavy construction quantity between the crossroad and neighbouring crossroad is determined;
Step 280, the radiation scope of the crossroad is calculated according to the road grade, number of track-lines and heavy construction quantity,
Calculate radiation scope formula be:
<mrow>
<mi>R</mi>
<mi>a</mi>
<mi>d</mi>
<mo>=</mo>
<mi>&lambda;</mi>
<mo>*</mo>
<msup>
<mi>e</mi>
<mfrac>
<mrow>
<mi>ln</mi>
<mi> </mi>
<msub>
<mi>N</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>ln</mi>
<mi> </mi>
<msub>
<mi>N</mi>
<mn>2</mn>
</msub>
</mrow>
<mrow>
<msub>
<mi>&alpha;L</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<msub>
<mi>&beta;L</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
</msup>
<mo>*</mo>
<msqrt>
<mrow>
<msub>
<mi>N</mi>
<mi>c</mi>
</msub>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msqrt>
<mo>;</mo>
</mrow>
Wherein Rad be the crossroad radiation scope, L1And L2Respectively pass through the crossroad first and second
Bar road grade, N1And N2Respectively pass through first of the crossroad and the track quantity of Article 2 road, NcTo be described
Heavy construction quantity around crossroad, α and β respectively pass through first of the crossroad and the power of Article 2 road
Weight coefficient, has α, β ∈ [0,1], and alpha+beta=1, λ is radiation scope coefficient.
2. the traffic control method according to claim 1 based on text mining, it is characterised in that in the step 300
Keyword include but are not limited to address, street name, number, building name, organization, performs title, match
Title.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610836901.3A CN106448199B (en) | 2016-09-21 | 2016-09-21 | A kind of traffic control method based on text mining |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610836901.3A CN106448199B (en) | 2016-09-21 | 2016-09-21 | A kind of traffic control method based on text mining |
Publications (2)
Publication Number | Publication Date |
---|---|
CN106448199A CN106448199A (en) | 2017-02-22 |
CN106448199B true CN106448199B (en) | 2018-05-08 |
Family
ID=58165885
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201610836901.3A Active CN106448199B (en) | 2016-09-21 | 2016-09-21 | A kind of traffic control method based on text mining |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106448199B (en) |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101887440B (en) * | 2009-05-13 | 2012-05-30 | 财团法人资讯工业策进会 | Hot spot analytic system and method |
CN103236163B (en) * | 2013-04-28 | 2015-01-07 | 北京航空航天大学 | Traffic jam avoiding prompting system based on collective intelligence network |
CN103942955A (en) * | 2014-03-24 | 2014-07-23 | 河北盛航通信科技有限公司 | Traffic road condition trend predicting and prompting system based on mobile network |
CN204256966U (en) * | 2014-12-11 | 2015-04-08 | 杨绍鹏 | Intelligence commander managing and control system |
CN105702058A (en) * | 2016-02-29 | 2016-06-22 | 宇龙计算机通信科技(深圳)有限公司 | Crossroad traffic light intelligent control method and system on the basis of vehicle positioning |
-
2016
- 2016-09-21 CN CN201610836901.3A patent/CN106448199B/en active Active
Also Published As
Publication number | Publication date |
---|---|
CN106448199A (en) | 2017-02-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN104318758B (en) | Based on multi-level multimodal Public transport network planning method | |
CN102819955B (en) | Road network operation evaluation method based on vehicle travel data | |
CN100541553C (en) | Road traffic accident data acquisition and processing (DAP) method | |
CN101930670B (en) | Method for predicting social vehicle running time on bus travel road section | |
CN103606266B (en) | Based on the road grid traffic improving countermeasure efficiency evaluation method of DEA | |
CN104778834A (en) | Urban road traffic jam judging method based on vehicle GPS data | |
CN102157064A (en) | Method for designing signal intersection of bus lanes | |
CN105023445A (en) | Regional traffic dynamic regulation-control method and system | |
CN109887289A (en) | A kind of network vehicle flowrate maximization approach of urban traffic network model | |
CN106710216A (en) | Expressway real-time traffic jam road condition detection method and system | |
Karlaftis et al. | Automobile ownership, households without automobiles, and urban traffic parameters: are they related? | |
Jian Daniel et al. | Research and analysis on causality and spatial-temporal evolution of urban traffic congestions—a case study on Shenzhen of China | |
CN104182633A (en) | Hierarchical traffic operation evaluation method | |
CN106448199B (en) | A kind of traffic control method based on text mining | |
CN106355913B (en) | A kind of traffic control method based on text mining | |
Fu et al. | Urban Parking Characteristic Investigation and Parking System Evaluation: A Case Study in Xi’an | |
Wang et al. | Smart traffic management with cyber-physical systems for scenic areas | |
Wang et al. | A Selection Parking Behavior Logit Model in Tourist Cities | |
Liu et al. | Mining Hub Nodes Based on Fast Brandes Betweenness Centrality in a Weighted Complex Transportation Network | |
Kong | Analysis of Traffic Carrying Capacity of Rail Transit TOD: A Case Study of Chongqing Bishan TOD Project | |
Hao et al. | A day-to-day invariant macroscopic fundamental diagrams for probe vehicles | |
Nogi et al. | Estimation of Level of Service for Urban Arterial Road of Ahmedabad City | |
Wang et al. | Empirical study on reversible lane in Beijing | |
Huang et al. | Research on the Influence and Optimization of Open Community on Road Traffic | |
Wang | Analysis of the traffic capacity of the entrance and exit of the commercial plaza parking lot |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |