CN109359890B - Method for evaluating influence degree of rainfall weather on urban road traffic - Google Patents
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Abstract
The invention relates to an assessment method of influence degree of rainfall weather on urban road traffic speed, which comprises the steps of integrating and filtering data, and pre-estimating the influence degree of the urban road traffic speed of the rainfall weather in advance through a rainfall influence analysis model; according to the method, the time lag term of the road section passing speed is introduced as a control variable through a time sequence analysis method, the influence of other unknown factors is controlled, the higher-order term of the rainfall variable and the rainfall accumulation variable are introduced, the action rule of the whole rainfall process on road traffic is comprehensively considered, the model result is more general, and a sequencing model is constructed to analyze the rainfall influence level based on the rainfall action factor, so that the rainfall influence level is evaluated more objectively, the defect of artificial subjective grading is avoided, and the evaluation result is more reliable.
Description
Technical Field
The invention belongs to the technical field of urban traffic management, and particularly relates to an evaluation method for influence degree of rainfall weather on urban road traffic speed.
Background
The existing rainfall traffic influence analysis method comprises a linear regression model and a traffic flow parameter model. The regression model analyzes the influence of rainfall by establishing a regression equation between the rainfall and the speed, but the model usually only focuses on the influence of the current rainfall and ignores the effect of rainfall cumulant, and the model is lack of consideration on road traffic environment variables. The traffic flow parameter model mainly analyzes the effect of rainfall by constructing a functional relation among traffic flow parameters, but the model result is not suitable for other road sections due to the fact that the functional relation among the traffic flow parameters of different road sections is greatly different.
At present, research on rainfall weather traffic influence is mostly based on simple correlation analysis of real-time meteorological data and traffic flow characteristic data, the research focuses on researching the influence of current rainfall on traffic flow characteristics, and the influence of rainfall cumulant on road traffic flow is ignored, so that the analysis on the influence of rainfall on the traffic flow characteristics is not comprehensive enough, the analysis result is inaccurate, and the model is difficult to popularize.
Therefore, it is necessary to invent a method for evaluating the influence degree of rainfall weather on the urban road traffic speed.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method for evaluating the influence degree of rainfall weather on the urban road traffic speed is provided, and traffic flow change under traffic network change can be pre-estimated in advance by fitting parameters related to the pedestrian routing behavior.
The technical scheme adopted by the invention is as follows: the system comprises a computer, wherein the computer integrates and filters data, and pre-estimates the influence degree of urban road traffic speed in meteorological rainfall weather through a rainfall influence analysis model;
the method for evaluating the influence degree of the rainfall weather on the urban road traffic speed comprises the following steps:
s10, integrating data and filtering;
performing data matching according to the time-space attributes of the GPS data, the weather rainfall data and the road network data of the floating car to obtain a traffic speed sequence and a rainfall sequence with 5-minute time precision on different road sections, and performing noise reduction on the speed sequence and the rainfall sequence by adopting field filtering and median filtering;
s20, a rainfall influence rule analysis model;
constructing a multi-element time series analysis model (ARMAX) based on passing speed for different road sections, and estimating a regression coefficient and a significance level of a rainfall variable in the model and the goodness of fit (Adjusted R-Square) of the model;
s30, a rainfall influence level analysis model;
obtaining an initial road section rainfall influence grade sequence according to the significance level of the rainfall variable regression coefficient, constructing an Ordered Probit model by taking the road section rainfall influence grade as a dependent variable and the rainfall variable regression coefficient as an independent variable, and correcting the road section rainfall influence grade sequence according to a model result;
s40, a rainfall influence degree evaluation method;
estimating the descending amount of the traffic speed of different road sections under heavy rain (15mm/h) weather according to the regression coefficient of the rainfall variable, and determining the speed descending range corresponding to different rainfall influence levels corresponding to the rainfall influence levels of different road sections;
and S50, outputting a rainfall influence degree evaluation method.
The technical scheme provided by the embodiment of the invention has the following beneficial effects: according to the method, the time lag term of the road section passing speed is introduced as a control variable through a time sequence analysis method, the influence of other unknown factors is controlled, and the model result is more general. Secondly, the invention introduces a quadratic term (R) of the rainfall variables, taking into account the nonlinear effect of the rainfall influences5^2) and cubic term (R)5^3) so as to more accurately analyze the law of action of rainfall on the road traffic flow speed. Thirdly, the invention also introduces a rainfall accumulation variable (R)30，R60) Therefore, the effect of the whole rainfall process is accurately evaluated, and the influence analysis of rainfall is more comprehensive. Finally, the invention uses the acting factor (R) of rainfall5，R30，R60Regression coefficient of) to construct a ranking model to analyze the rainfall influence level, so that the rainfall influence level is evaluated more objectively, the defect of artificial subjective grading is avoided, the evaluation result is more reliable, and compared with the existing rainfall influence analysis method, the method has the following advantages:
1. a rainfall influence rule model (ARMAX model) introduces a time lag term of road section passing speed as a control variable to control the influence of other unknown factors, and the model result is more general;
2. a rainfall influence rule model (ARMAX model) introduces a secondary term and a tertiary term of rainfall, a nonlinear process of rainfall influence is analyzed, and the accuracy of a model result is higher;
3. a rainfall influence rule model (ARMAX model) introduces rainfall accumulation variables, the effect of the whole rainfall process on the road section traffic speed is comprehensively considered, and the model result is more comprehensive;
4. the rainfall influence grade evaluation model (Ordered Probit model) grades the rainfall sensitivity of different road sections, so that the defect of artificial subjective grading is avoided, and the reliability of the model result is higher.
Description of the drawings:
FIG. 1 is a schematic flow chart of the method for evaluating the influence degree of rainfall weather on the urban road traffic speed;
FIG. 2 is a timing diagram of the road segment traffic speed after data filtering in accordance with the present invention;
FIG. 3 is a scatter plot of the rainfall at the present time and the road section passing speed of the present invention;
FIG. 4 is a scatter plot of cumulative rainfall versus road segment traffic speed for the first 30 minutes of the present invention;
FIG. 5 is a scatter diagram of rainfall accumulation and road section passing speed in the first 30-60 minutes of the invention.
Detailed Description
In order to more fully understand the technical contents of the present invention, the technical solutions of the present invention will be further described and illustrated below with reference to the accompanying drawings and specific embodiments, but not limited thereto.
Referring to fig. 1 to 5, a method for evaluating influence degree of rainfall weather on urban road traffic speed includes a computer, the computer integrates and filters data, and the influence degree of the urban road traffic speed of the meteorological rainfall weather is pre-estimated through a rainfall influence analysis model;
referring to fig. 1, it is a flow chart of the method for evaluating the influence degree of rainfall weather on the urban road traffic speed.
As shown in fig. 1, in the process of the present invention, the method for evaluating the influence degree of rainfall weather on the urban road traffic speed includes the following steps:
and S10, integrating and filtering data, and performing data matching according to the floating car GPS data, the weather rainfall data and the time-space attributes of road network data to obtain a traffic speed sequence and a rainfall sequence of different road sections with 5-minute time precision. And performing noise reduction processing on the speed sequence and the rainfall sequence by adopting field filtering and median filtering.
Specifically, in step S10, the data integration and filtering process is as follows:
s11, importing floating car GPS data and meteorological rainfall data into a PostgreSQL database;
s12, performing space-time attribute matching on floating car GPS data, meteorological rainfall data and Shenzhen road network data through a PostGIS geographic information system;
s13, extracting a speed sequence of 5-minute time accuracy of the specific link according to the link ID;
s14, removing data noise of the speed sequence through neighborhood filtering and median filtering, wherein a time sequence diagram after road section passing speed filtering is shown in figure 2;
s15, extracting a rainfall sequence according to the ID of the weather monitoring station;
and S16, acquiring rainfall, the rainfall accumulation amount sequence of the first 30 minutes and the rainfall accumulation amount sequence of the first 30-60 minutes in 5 minutes according to the rainfall data time attribute.
In the step S20, rainfall influence rule analysis is performed, and a traffic speed sequence-based multivariate time sequence analysis model (ARMAX) is constructed for different road sections, so that the regression coefficient and the significance level of rainfall variables in the model and the goodness-of-fit (Adjusted R-Square) of the model are estimated.
Specifically, in step S20, the rainfall influence law analysis process is as follows:
s21, determining model variables, wherein the dependent variable sequence is a road section passing speed sequence, and the process of the road section passing speed affected by rainfall is shown in figures 3, 4 and 5; the sequence of independent variables includes: the rainfall sequence, rainfall accumulation sequence, morning and evening peak sequence, non-working day sequence, rainfall and morning and evening peak interaction item sequence at the current moment, and the specific model variables are as follows:
TABLE 1ARMAX model variables selection definition
And S22, performing correlation analysis on the road section passing speed sequence, and determining parameters p and q of an ARMA (p, q) model.
And S23, calculating the regression coefficient, the significance level and the goodness of fit of the model of the rainfall related variables of the different road section models by a least squares method (OLS).
In the step of S30, rainfall influence grade evaluation is carried out, an initial road section rainfall influence grade sequence is obtained according to the significance level of rainfall influence variables, an Ordered Probit model is constructed by taking the rainfall influence grade as a dependent variable and a rainfall variable regression coefficient as an independent variable, and the road section rainfall influence grade sequence is corrected according to a model result.
Specifically, in step S30, the procedure of the rainfall impact level evaluation is as follows:
s31, according to the ARMAX model result, all regression coefficients of rainfall related variables (R5, R30 and R60) are statistically significant, the rainfall influence level is 3, the rainfall influence level is not significant, the rainfall influence level is 0, and the like, so that a discrete-form road section rainfall influence level sequence is obtained.
S32, constructing an Ordered Probit model by taking the rainfall influence level of the initial road section as a dependent variable and the regression coefficient value as an independent variable, wherein the model variables are described as follows:
TABLE 2 sequencing model variable definitions
S33, calculating the value of the model parameter through Maximum Likelihood Estimation (MLE), and correcting the initial rainfall influence level sequence, wherein the rainfall influence level correction model is as follows:
and S40, evaluating the rainfall influence degree, estimating the descending amount of the passing speed of different road sections in heavy rain (15mm/h) weather according to the regression coefficient of the rainfall variable, corresponding to the rainfall influence levels of different road sections, and determining the speed descending range corresponding to the different rainfall influence levels.
Specifically, in step S40, the procedure of the rainfall influence degree evaluation is as follows:
and S41, calculating the speed reduction amount of different weather rainfall levels according to the rainfall related variable regression coefficients of the ARMAX models of different road sections.
S42, calculating the speed descending ranges of the road sections with different rainfall influence levels, wherein the results are as follows:
TABLE 4 speed reduction for different rainfall effect classes under heavy rain (15mm/h) conditions
S43, according to the speed reduction range of different rainfall influence grades, eliminating the influence of head and tail extreme values, and forming a rainfall influence degree evaluation method after rounding calibration, wherein the result is as follows:
when the rainfall traffic influence analysis model is constructed, the change rule of the speed of the road section under different traffic road conditions and the change rule of the speed of the road section under different traffic road conditions are consideredAnd under the action of other unknown factors, a time lag term of the road section passing speed is introduced as a control variable through a time sequence analysis method, the influence of other unknown factors is controlled, and the model result is more general. Secondly, the invention introduces a quadratic term (R) of the rainfall variables, taking into account the nonlinear effect of the rainfall influences5^2) and cubic term (R)5^3) so as to more accurately analyze the law of action of rainfall on the road traffic flow speed. Thirdly, the invention also introduces a rainfall accumulation variable (R)30，R60) Therefore, the effect of the whole rainfall process is accurately evaluated, and the influence analysis of rainfall is more comprehensive. Finally, the invention uses the acting factor (R) of rainfall5，R30，R60Regression coefficient of) to construct a ranking model to analyze the rainfall influence level, so that the evaluation of the rainfall influence level is more objective, the defect of artificial subjective grading is avoided, and the evaluation result is more reliable.
Compared with the existing rainfall influence analysis method, the rainfall influence analysis method has the following advantages:
1. a rainfall influence rule model (ARMAX model) introduces a time lag term of road section passing speed as a control variable to control the influence of other unknown factors, and the model result is more general;
2. a rainfall influence rule model (ARMAX model) introduces a secondary term and a tertiary term of rainfall, a nonlinear process of rainfall influence is analyzed, and the accuracy of a model result is higher;
3. a rainfall influence rule model (ARMAX model) introduces rainfall accumulation variables, the effect of the whole rainfall process on the road section traffic speed is comprehensively considered, and the model result is more comprehensive;
4. the rainfall influence grade evaluation model (Ordered Probit model) grades the rainfall sensitivity of different road sections, so that the defect of artificial subjective grading is avoided, and the reliability of the model result is higher.
The above description is only a preferred embodiment of the present patent, and not intended to limit the scope of the present patent, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the specification and the drawings, and which are directly or indirectly applied to other related technical fields, belong to the scope of the present patent protection.
Claims (4)
1. A method for evaluating influence degree of rainfall weather on urban road traffic speed is characterized by comprising the following steps: the system comprises a computer, a data acquisition module, a data processing module and a rainfall influence analysis module, wherein the computer integrates and filters data, and pre-estimates the influence degree of urban road traffic speed in meteorological rainfall weather;
the method for evaluating the influence degree of the rainfall weather on the urban road traffic speed comprises the following steps:
s10, integrating data and filtering;
performing data matching according to the time-space attributes of the GPS data, the weather rainfall data and the road network data of the floating car to obtain a traffic speed sequence and a rainfall sequence with 5-minute time precision on different road sections, and performing noise reduction on the speed sequence and the rainfall sequence by adopting field filtering and median filtering;
s20, a rainfall influence rule analysis model;
building a rainfall influence rule model based on a multi-element time sequence of traffic speed for different road sections, and estimating a regression coefficient and a significance level of rainfall variables in the model and the goodness of fit of the model;
s30, a rainfall influence level analysis model;
obtaining an initial road section rainfall influence grade sequence according to the significance level of the rainfall variable regression coefficient, constructing an Ordered Probit model by taking the road section rainfall influence grade as a dependent variable and the rainfall variable regression coefficient as an independent variable, and correcting the road section rainfall influence grade sequence according to a model result;
s40, a rainfall influence degree evaluation method;
estimating the descending amount of the passing speed of different road sections under heavy rain weather according to the regression coefficient of the rainfall variable, and determining the speed descending range corresponding to different rainfall influence levels corresponding to the rainfall influence levels of different road sections;
and S50, outputting a rainfall influence degree evaluation result.
2. The method for evaluating the degree of influence of rainfall weather on the traffic speed of urban roads according to claim 1, wherein: in the step S20, the calculation method of the rainfall influence law includes the following steps:
s21, determining model variables; the dependent variable sequence is a road section passing speed sequence, and the independent variable sequence comprises the following steps: a rainfall sequence, a rainfall accumulation sequence, a peak in the morning and at night, a non-working day sequence and a rainfall and peak in the morning and at night interaction item sequence at the current moment;
s22, carrying out correlation analysis on the road section passing speed sequence, and determining parameters p and q of an ARMAX (p, q) model;
s23, calculating regression coefficients, significance levels and goodness of fit of rainfall related variables of different road section models through a least square method, wherein the analysis models are as follows:
lnv denotes the log sequence of the average speed of 5 minutes passing through the road section, R5Representing a 5 minute rainfall sequence of the road section, R52 represents a quadratic term of a 5-minute rainfall sequence of a road segment, R5^3 represents a cubic term of a 5-minute rainfall sequence of a road section, R30Represents the cumulative amount of rainfall in the first 30 minutes, R60Representing the cumulative amount sequence of rainfall in the first 30-60 minutes, T1Indicating the early peak sequence, T2Representing an early peak sequence and D a non-weekday sequence.
3. The method for evaluating the degree of influence of rainfall weather on the traffic speed of urban roads according to claim 1, wherein: in the step S30, the rainfall influence level evaluation process is as follows:
s31, rainfall related variable (R) according to ARMAX model result5,R30,R60) If all regression coefficients are statistically significant, the influence level is 3, if all the regression coefficients are not significant, the influence level is 0, and so on, a discrete-form road section rainfall influence level sequence is obtained;
s32, constructing an Ordered Probit model by taking the rainfall influence level of the initial road section as a dependent variable and the rainfall variable regression coefficient value as an independent variable as follows:
latent model to be estimated:
Xiregression coefficient, X, representing a rainfall variable1Regression coefficient, X, representing 5 min rainfall2Regression coefficient, X, representing cumulative amount of rainfall in the first 30 minutes3A regression coefficient representing rainfall cumulant in the first 30-60 minutes;
s33, calculating the value of the model parameter through maximum likelihood estimation, and correcting the initial rainfall influence level sequence, wherein the rainfall influence level correction model comprises the following steps:
4. the method for evaluating the degree of influence of rainfall weather on the traffic speed of urban roads according to claim 1, wherein: in the step S40, the rainfall influence degree evaluation process is as follows:
s41, calculating the speed reduction amount of the road sections with different weather rainfall levels according to the rainfall related variable regression coefficients of the ARMAX models of the different road sections, wherein the calculation formula is as follows:
eta is the velocity decrease amount, R5Representing a 5 minute rainfall sequence of the road section, R52 represents a quadratic term of a 5-minute rainfall sequence of a road segment, R5^3 represents a cubic term of a 5-minute rainfall sequence of a road section, R30Represents the cumulative amount of rainfall in the first 30 minutes, R60Representing a rainfall accumulation sequence in the first 30-60 minutes;
s42, calculating speed descending ranges of road sections with different rainfall influence levels;
s43, according to the speed reduction ranges of different rainfall influence levels, eliminating the influence of head and tail extreme values, and obtaining the rainfall influence degree evaluation method after rounding calibration as follows:
y represents the rainfall impact rating.
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