CN107886720A - Interval two-type fuzzy set festival holiday-based urban traffic congestion transfer analysis method - Google Patents
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Abstract
The invention relates to an interval-based two-type fuzzy aggregation holiday-based urban traffic jam transfer analysis method. By collecting the data of the Shenzhen traffic police microblog 2014 year, the social media traffic data analysis has important significance for solving the urban traffic jam problem aiming at the fact that the conventional urban roads can not meet the normal traffic requirement gradually. The method comprises the following steps: the method comprises the following steps: selecting and analyzing main parameters influencing traffic jam according to the road traffic state; step two: performing congestion analysis on the Shenzhen road section by using interval two-type fuzzy aggregate fuzzy comprehensive evaluation according to the selected traffic parameters; step three: and obtaining a traffic jam transfer evaluation conclusion of the city on the holiday according to the analysis result, and visualizing the traffic jam condition. The invention has the following characteristics: according to the method, the Shenzhen traffic condition is known by analyzing the urban traffic jam transfer on the holiday, so that the traffic jam road condition information is provided for drivers and travelers, the real-time road section jam condition can be known conveniently, the waiting time is shortened, and the occurrence of accidents is reduced.
Description
Technical Field
The invention relates to the field of microblog extracted data and traffic flow analysis, in particular to an interval two-type fuzzy set festival holiday-based urban traffic jam transfer analysis method.
Background
Along with the development of social economy, the living standard of everyone is higher and higher. The number of automobiles is increased sharply, the existing roads can not meet the requirements of normal traffic gradually, and the traffic problems of congestion, blockage and the like are increased day by day. Meanwhile, with the development of networks, social media plays a bigger and bigger role. As a key technology of an urban traffic guidance system, data analysis based on social media has important significance for solving the problem of urban traffic jam transfer in holidays, and is one of the research hotspot problems in the field of intelligent traffic. In recent years, scholars at home and abroad mine traffic data through social media, and a large amount of analysis and research are carried out on traffic jam. In foreign countries, Mochamad et al extracts traffic condition data through social media, discusses grammars and semantics of natural languages, Sakkachin and Twitie analyze the assessment of road traffic congestion severity through Twitter, and Chihiromaru et al uses social information to perform traffic control network fault system detection of large-scale disasters. In China, Cui and the like extract traffic information from social media, discuss the method and carry out experiments, and Wanuncut and the like mainly research human traffic and traffic networks by utilizing big data of social media. However, the analysis cannot effectively analyze the traffic congestion state in holidays and festivals, and the analysis result is visualized. Mo Hong et al performed linguistic dynamics analysis on traffic flow by a social media-based method, and intuitively displayed road sections, reasons and time of traffic congestion by using a keyword picture wall.
The traffic jam information in the holidays is mainly from social media including WeChat, microblog, social network sites and the like, and is different from the source of the traffic jam information in the common cities. And such information is mainly expressed as language information, so how to analyze the characteristics of the urban traffic jam transfer on holidays becomes key. Because the language description has ambiguity, ambiguity and imperfection, the ambiguity set is one of the effective ways to solve the problem, and the two-type ambiguity set can better solve the problems of language ambiguity and data noise compared with the one-type ambiguity set, so that people can define a membership function with larger freedom degree, and the method has obvious superiority in the aspects of processing system uncertainty and the like.
Disclosure of Invention
Aiming at the problems, the technical problem solved by the invention is that according to the congestion situation from Shenzhen holiday to working day, an interval type fuzzy aggregation holiday urban traffic congestion transfer analysis method is provided, through acquiring data of Shenzhen police microblog about the congestion of Shenzhen road section, carrying out example analysis on the data, and analyzing the congestion transfer of the road section from the holiday to the working day by using graphic visualization; the method not only provides data basis for researchers, but also can acquire traffic information in real time, provides accurate road location and congestion degree for drivers, and solves a plurality of problems.
The technical scheme for solving the technical problems is as follows:
step S1: acquiring Shenzhen traffic police microblog congested road data, and selecting and analyzing main parameters influencing traffic congestion in the process of analyzing and judging according to the road traffic state;
in the process of analyzing and judging the road traffic jam state, the traffic jam parameter to be considered needs to be determined. Comprehensively considering the effectiveness of the parameters and the requirements on feasibility and economy of input data, the following three parameters are selected as the input parameters of the traffic state: the length of the queue; average driving speed; average delay time.
Further, the queuing length refers to the length of a road segment occupied by the queued vehicles at a traffic break point (intersection, accident occurrence point, etc.). The queuing length can be used as a measure of the degree of traffic congestion, and in general, the more severe the congestion causes the longer the queuing length.
The average driving speed refers to the average value of all the vehicle speeds passing through the road section in a certain time. The average driving speed index is an evaluation index which can most intuitively and simply reflect the running state of the road network.
The average delay time is an average time of time loss due to congestion when the vehicle travels on a certain road. For the road congestion condition, the congestion condition of the road can be intuitively obtained through the average delay time.
Step S2: performing congestion evaluation on the Shenzhen road section by using interval two-type fuzzy aggregate fuzzy comprehensive evaluation according to the selected traffic parameters; which comprises the following steps:
step S21: determining a factor set M of an evaluation object;
further, the method comprises the following steps of; is provided withM＝{m1,m2,m3Is a set of factors for evaluation of the object, m1For queue length, m2Is the average running speed, m3Is the average delay time.
Step S22: comment set C for determining evaluation objectj；
Further, the method comprises the following steps of; note Cj(j ═ 1,2,3,4) and indicates "clear", "light congestion", "moderate congestion", and "severe congestion", respectively.
Step S23: determining a weight set of evaluation factors
Further, the method comprises the following steps of;and isWherein a isiRepresents miThe weight of (c).
Step S24: performing single-factor fuzzy evaluation, and determining a fuzzy comprehensive evaluation matrix R;
the fuzzy comprehensive evaluation matrix R is M to CjA fuzzy relation of (a), thetaijIndicates that C is made for the ith factorjThe degree of evaluation.
Ri＝[ri1ri2ri3ri4]Represents a pair of miAnd (4) evaluating the single factor, and synthesizing all factors to obtain a fuzzy comprehensive evaluation matrix R.
According to the classified statistics and fuzzy membership matching of the scores of all the indexes, the object x can be obtainednFuzzy comprehensive matrix of satisfaction degree in both voting proportion and average scoreEquation 1 is expressed as:
wherein r isij(j-1, 2,3,4) is an index miThe degrees are respectively 'smooth', 'slight congestion', 'moderate congestion' and 'severe congestion', and the evaluation is given according to experts.
Step S25: and obtaining an evaluation result by comprehensive evaluation.
Index miFuzzy comprehensive evaluation matrixAnd corresponding weight vectorObtaining a two-type fuzzy comprehensive evaluation formula 2 by using a weighted average fuzzy synthesis operator:
wherein,represents a generalized fuzzy synthesis algorithm, here a weighted average synthesis operator M (·, V), equation 3:
and finally, carrying out congestion evaluation on the four road sections of Shenzhen through example analysis, and carrying out traffic congestion transfer graph visualization.
The invention provides an interval-based two-type fuzzy aggregation holiday-based urban traffic jam transfer analysis method, which has the advantages that: by collecting Shenzhen traffic police microblog data, language information on social media is effectively utilized, and traffic jam transfer in urban festivals and holidays is analyzed, so that a reference route is provided for travelers, and traffic pressure is relieved.
Drawings
FIG. 1 is a flow chart of traffic police microblog data collection and analysis;
FIG. 2 is a flowchart of step S2 of the present invention;
FIG. 3 is a visual diagram of congestion degree of a clay road section;
FIG. 4 is a visualization of congestion levels for highway segments;
fig. 5 is a visual map of the congestion degree of the meisha road section.
Detailed Description
The method for analyzing urban traffic congestion transfer based on the interval type two fuzzy aggregation holiday according to the invention is further described in detail with reference to the accompanying drawings and the embodiments of the invention.
As shown in fig. 1, the method comprises the following specific steps:
step S1: acquiring Shenzhen traffic police microblog congested road data, and selecting and analyzing main parameters influencing traffic congestion in the process of analyzing and judging according to the road traffic state;
the method includes detecting a congested road section and issuing microblog data according to Shenzhen traffic police, and collecting microblog data; processing, screening, classifying and drying the microblog data texts to obtain microblog data of congested road sections, and then selecting and analyzing main parameters influencing traffic congestion;
step S2: performing congestion evaluation on the Shenzhen road section by using interval two-type fuzzy aggregate fuzzy comprehensive evaluation according to the selected traffic parameters;
analyzing and calculating traffic jam microblog data, judging a jammed road section by using an interval two-type fuzzy set and fuzzy comprehensive judgment, analyzing traffic jam transfer in holidays of urban festivals to obtain a traffic jam data rule, and predicting;
step S3: and obtaining an evaluation conclusion of the traffic jam transfer in the city on the holiday according to the analysis result, and visualizing the traffic jam condition.
And the microblog data image visualization is carried out by using the javaweb, and the user can visually receive and read and then feed back traffic jam information (comment and forwarding).
The second graph is to further perform fuzzy comprehensive evaluation on the two-type fuzzy set of the analysis interval in the step S2:
performing interval two-type fuzzy comprehensive evaluation on the congestion degree of the Shenzhen four road sections on the working day, wherein the fuzzy comprehensive evaluation matrixes of the experts for the traffic congestion of the four road sections are respectively as follows:
according to expert experience, setting index weight vectors as follows:
A＝[0.4 0.2 0.4]
the comprehensive evaluation is carried out according to the formula (3) to obtain:
and (3) taking the expert experience result as a main membership degree, wherein the sub-membership degree is 1 to form 4 fuzzy sets for evaluating the congestion degree of the road section working day, and recording the fuzzy sets as:
from the maximum membership method, x2Is moderately congested, x4Is moderately congested, and x2Degree of (a) to x4Large, x3In light congestion, x1The smoothness is smooth. Therefore, the overall congestion degree of the four road sections is ranked as x from large to small2，x4，x3，x1。
Performing interval type two fuzzy comprehensive evaluation on the congestion degree of the Shenzhen four road sections on the holiday, wherein the fuzzy comprehensive evaluation matrixes of the expert for the traffic congestion of the four road sections respectively comprise:
according to expert experience, setting index weight vectors as follows:
A＝[0.4 0.2 0.4]
the comprehensive evaluation is carried out according to the formula (3) to obtain:
taking the expert experience result as a secondary membership degree which is 1 to form 4 fuzzy sets for evaluating the congestion degree of the road section working day,
from the maximum membership method, x3For severe congestion, x4、x1、x2Is lightly congested and the degree is from large to small x4＞x1＞x2. Therefore, the overall congestion degrees of the four road sections are ranked as x3，x4，x1，x2。
The interval two-type fuzzy comprehensive evaluation is used for comparing the congestion degrees of the four-large road section working day and the holiday of the Shenzhen, and the congestion degrees of the four-large road section working day and the holiday of the Shenzhen traffic police microblog data are compared.
For further analysis of the link congestion graphic visualization in step S3:
according to the method, through data collected from Shenzhen police micro blog, data of 9 months, 10 months, 11 months and 12 months of three road sections (mud post, Meisha and high speed) are selected, visual analysis is carried out on traffic jam transfer of a working day and a holiday of each month, the micro blog data is input by using a javaweb, and image processing is carried out by using a browser script file. The abscissa of the picture is from Monday to Sunday of four months, and the mid-autumn festival of holidays of 9 months and the national festival of holidays of 10 months, the ordinate divides one day into 24 time periods, the congestion times are divided into n grades, and different degrees of congestion are represented by the color depth.
And the third graph is the comparison of the congestion degree of the muddy road in four months and every day, and the degree grades are divided into 6 types. The figures show that the congestion times of the working days are obviously more than those of the holidays, the main congestion time periods of the working days are 7:00-9:00 and 17:00-19:00, the congestion on the weekends is dispersed in each time period of each day, the congestion is not generated during the holidays of the mud hills, and the congestion degree of the mud hills is reduced when the congestion of roads is transferred from the working days to the holidays.
The fourth graph is a comparison of congestion degrees in four months per day at high speed, and the degree grades are divided into 8 types. It can be seen from the figure that the congestion times of workdays are obviously less than those of holidays, the congestion time periods of the holidays are all 8:00-22:00, the high-speed congestion times are obviously increased due to the fact that the national celebration is long and false in 10 months, the high-speed congestion times of Tuesdays in 9 months are also obviously increased in the figure, the reason is that Tuesdays 9.30 are national celebration trips, the high-speed serious congestion occurs in Shenzhen days after 18:00 days, the congestion times are more than those of other workdays, and the congestion degree is increased when the high-speed congestion is transferred from the workdays to the holidays.
And the fifth graph is the comparison of the congestion degree of the Meisha on Monday to Sunday and holiday of four months, and the degree grades are divided into 6. It can be seen from the figure that the congestion times in the working day is 0, namely congestion occurs only in mid-autumn festival and national celebration in two months, because the meisha is the tourist attraction of Shenzhen, and more people drive in the holidays, so the congestion times in the holidays are obviously increased.
According to the method, a microblog text screening method is used, and classification is carried out, so that the problems of a specific congestion road section, duration, congestion intensity and the like can be reflected. The visualization of traffic data images can clearly assist in analyzing and predicting sections and reasons of traffic jam, and the real-time monitoring and analysis of road traffic states are key points of smart city construction.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A method for urban traffic jam transfer analysis based on interval type II fuzzy set holidays is characterized by comprising the following steps:
step S1: acquiring Shenzhen traffic police microblog congested road data, and selecting and analyzing main parameters influencing traffic congestion in the process of analyzing and judging according to the road traffic state;
step S2: according to the selected traffic parameters, performing congestion evaluation on the Shenzhen related road sections by using interval two-type fuzzy aggregate fuzzy comprehensive evaluation;
step S3: and obtaining an evaluation conclusion of the traffic jam transfer in the city on the holiday according to the analysis result, and visualizing the traffic jam condition.
2. The method for analyzing traffic congestion transition in a holiday city based on the interval type two fuzzy aggregation as claimed in claim 1, wherein in step S1:
before congestion evaluation, the main parameters of a road congestion evaluation index are determined; the method comprehensively considers the effectiveness of parameters and the requirements on feasibility and economy of input data, and selects the following three parameters as the input parameters of the traffic state: queuing length, average driving speed and average delay time;
the queuing length refers to the length of a road segment occupied by the queued vehicles at a traffic break point (an intersection, an accident occurrence point and the like); the queuing length can be used for measuring the traffic jam degree, and under the general condition, the more serious the jam is, the longer the queuing length is;
the average driving speed refers to the average value of the speeds of all vehicles passing through the road section within a certain time; the average driving speed index is an evaluation index which can most intuitively and simply reflect the running state of the road network;
the average delay time refers to the average time of time loss caused by congestion when a vehicle runs on a certain road; for the road congestion condition, the congestion condition of the road can be intuitively obtained through the average delay time.
3. The method for analyzing traffic congestion transition in a holiday city based on the interval type two fuzzy aggregation as claimed in claim 1, wherein in step S2:
according to the selected traffic parameters, the interval type fuzzy aggregate fuzzy comprehensive evaluation is used for carrying out congestion evaluation on the Shenzhen road section, and the method comprises the following steps:
step S21: determining a factor set M of an evaluation object;
step S22: comment set C for determining evaluation objectj；
Step S23: determining a weight set of evaluation factors
Step S24: performing single-factor fuzzy evaluation, and determining a fuzzy comprehensive evaluation matrix R;
step S25: and obtaining an evaluation result by comprehensive evaluation.
4. The interval-type two-model fuzzy aggregate comprehensive evaluation method for the degree of congestion in the Shenzhen road segment as claimed in claim 3, wherein the set of factors influencing the congestion evaluation object in step S21 includes { queue length, average driving speed, average delay time }, and is expressed as M ═ M { (M average driving speed, average delay time })1,m2,m3}。
5. The interval two-type fuzzy aggregate comprehensive evaluation method for the degree of congestion in the Shenzhen road segment as claimed in claim 3, wherein in step S22, the degree of congestion is divided into "smooth", "slightly congested", "moderately congested" and "severely congested", which are denoted as Cj(j＝1,2,3,4)。
6. The interval two-type fuzzy aggregate comprehensive evaluation method for the Shenzhen road segment congestion degree as claimed in claim 3, wherein in step S23, the weight of each factor in the factor set is expressed asAnd 0 is more than or equal to ai≤1，Wherein a isiRepresents miThe weight of (c).
7. The interval two-type fuzzy aggregate comprehensive evaluation method of the Shenzhen road segment congestion degree as claimed in claim 3, wherein in step S24, the fuzzy comprehensive evaluation matrix R is from M to CjA fuzzy relation of (a), thetaijIs to show toi factors make CjThe degree of evaluation;
Ri＝[ri1ri2ri3ri4]represents a pair of miThe fuzzy comprehensive evaluation matrix R can be obtained by integrating all the factors; according to the classified statistics and fuzzy membership matching of the scores of all the indexes, the object x can be obtainednFuzzy comprehensive matrix of satisfaction degree in both voting proportion and average scoreIs shown as
<mrow> <msub> <mi>R</mi> <msub> <mi>x</mi> <mi>n</mi> </msub> </msub> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>r</mi> <mn>11</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>12</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>13</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>14</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>r</mi> <mn>21</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>22</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>23</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>24</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>r</mi> <mn>31</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>32</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>33</mn> </msub> </mtd> <mtd> <msub> <mi>r</mi> <mn>34</mn> </msub> </mtd> </mtr> </mtable> </mfenced> </mrow>
Wherein r isij(j-1, 2,3,4) is an index miThe degrees are respectively 'smooth', 'slight congestion', 'moderate congestion' and 'severe congestion', and the evaluation is given according to experts.
8. The interval type two-type fuzzy aggregate comprehensive evaluation method for the Shenzhen road segment congestion degree as claimed in claim 3, wherein the index m in step S25iFuzzy comprehensive evaluation matrixAnd corresponding weight vectorObtaining a two-type fuzzy comprehensive judgment by utilizing a weighted average fuzzy synthesis operator:
wherein,represents a generalized fuzzy synthesis algorithm, here a weighted average synthesis operator M (·, V), i.e. V
<mrow> <msub> <mi>B</mi> <msub> <mi>x</mi> <mi>n</mi> </msub> </msub> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>4</mn> </munderover> <msub> <mi>a</mi> <mi>i</mi> </msub> <msub> <mi>r</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>3</mn> <mo>,</mo> <mn>4.</mn> </mrow>
9. The interval two-type fuzzy aggregate comprehensive evaluation method for the Shenzhen road section congestion degree as claimed in claim 3, wherein the four road sections of the Shenzhen are subjected to congestion evaluation, the festival and holiday traffic congestion transfer is analyzed, and the traffic congestion transfer condition is visualized.
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