CN106297285B - Freeway traffic operating status fuzzy synthetic appraisement method based on changeable weight - Google Patents

Abstract

The invention discloses a fuzzy comprehensive evaluation method for expressway traffic running state based on dynamic weight. Firstly, the evaluation index value is calculated according to the collected vehicle detector data and toll data; then, the index weight vector is calculated according to the dynamic traffic data; finally, according to the weight vector Establish a dynamic fuzzy comprehensive evaluation model and calculate the comprehensive evaluation value of expressway traffic operation status: evaluate the expressway traffic operation status and output the evaluation results. The fuzzy comprehensive evaluation method of expressway traffic operation state based on dynamic weight proposed by the present invention is based on the existing expressway data source, uses dynamic traffic data to calculate the index weight in real time, and uses the fuzzy comprehensive evaluation method to evaluate the traffic operation state of the expressway section Evaluation, this method takes four parameters as evaluation indicators for highway sections: section saturation, occupancy rate, average travel speed, and average travel time delay, and realizes fuzzy comprehensive evaluation through dynamic weights.

Description

Fuzzy Comprehensive Evaluation Method of Expressway Traffic Operation State Based on Dynamic Weight

technical field

The invention relates to the field of expressway traffic operation evaluation, in particular to a dynamic weight-based fuzzy comprehensive evaluation method for expressway traffic operation state.

Background technique

The evaluation system of expressway traffic operation status can provide theoretical support for expressway control measures and operation strategies. In order to better propose expressway management strategies, improve operational efficiency, and maximize the role of expressways, it is necessary to evaluate the expressway traffic operation at different times in order to identify the period with the best operating conditions and use it as a future reference standards for practice

At present, the fuzzy comprehensive evaluation method is a common method in expressway operation evaluation. This method mainly selects one or more traffic indicators for traffic evaluation, and evaluates the expressway operation status qualitatively and quantitatively. However, in the evaluation process, the weight of each evaluation index is obtained by expert method, which is greatly affected by subjective factors, and different expressway sections and the same section at different times due to the dynamic changes of traffic data, the index has a great influence on the expressway section. The importance of health status reflection may vary.

Therefore, it is necessary to study the index weight calculation method based on dynamic traffic data, so as to make the evaluation of expressway traffic operation status more objective and reasonable.

Contents of the invention

The purpose of the present invention is to propose a fuzzy comprehensive evaluation method for expressway traffic operation state based on dynamic weight; it is used for reasonably evaluating the operation state of expressway sections.

The purpose of the present invention is achieved through the following technical solutions:

The fuzzy comprehensive evaluation method of expressway traffic operation state based on dynamic weight provided by the present invention comprises the following steps:

Step 1: collect highway data and preprocess the data; the data includes vehicle detector data and toll data;

Step 2: Calculate the evaluation index value according to the collected vehicle detector data and charging data; the evaluation index value includes calculating flow saturation, time occupancy rate, average travel speed and average travel time delay;

Step 3: According to the dynamic traffic data, use the difference-driven principle of data to calculate the index weight vector in real time;

Step 4: Establish a dynamic fuzzy comprehensive evaluation model according to the weight vector and calculate the comprehensive evaluation value of expressway traffic operation status:

Step 5: Evaluate the traffic operation state of the expressway according to the comprehensive evaluation value and output the evaluation result.

Further, the data preprocessing in step 1 is calculated according to the following steps:

(11) Use the threshold method to remove the abnormal data in the vehicle detector data, the specific steps are as follows:

Determine the flow threshold q according to the following formula:

0≤q≤f _c CT/60;

Among them: C is the traffic capacity of the road; T is the time interval of data collection; f _c is the correction coefficient of the flow rate;

Determine the velocity v according to the following formula:

0≤v≤f _v v ₀ ;

Among them: v ₀ is the speed limit of the high-speed section; f _v is the correction coefficient of the speed.

(12) Preprocessing of charging data, the specific steps are as follows:

Determine the preset threshold TE of travel time according to the following formula:

TE=[L/1.5*v ₀ ,24];

Among them, TE is the effective data interval; L is the length of the road section; v ₀ is the speed limit of the high-speed road section;

Judging whether the charging data is within the preset threshold TE, if yes, the charging data is correct data, if not, the charging data is abnormal data;

Eliminate abnormal data.

Further, the evaluation index value in the step 2 is calculated according to the following steps:

The evaluation index value is calculated according to the following formula:

(21) Use the vehicle detector data to calculate the flow saturation and occupancy rate:

Among them: S is the flow saturation of the road section; Q is the actual traffic flow; C ₀ is the design traffic flow of the road section; R _t is the time occupancy rate; _T is the length of observation time; i=1,2...n;

(22) Through the toll ID number of the expressway toll data, the time of entry and exit and the mileage of the road section, the mileage and travel time of each vehicle are obtained, and the average travel speed and average travel time delay are calculated:

Among them: D is the average travel speed; L _D is the total mileage of all vehicles on the evaluation section during the evaluation period; T _D is the total driving time of all vehicles during the evaluation period; n _D is the number of all vehicles on the evaluation section within the evaluation period; l _Di is the driving mileage of vehicle i in the evaluation period; t _Di is the driving time of vehicle i in the evaluation period; TD is the average travel time delay; l is the length of the road section; td _i is the travel time of the i-th vehicle, T _td is the total travel time, which can be obtained by calculating the toll data; v ₀ is the smooth speed, which is obtained according to the design speed of the road section; n is the total number of passing vehicles within the observation time;

Further, the weight vector in step 3 is calculated according to the following steps:

(31) Combined with the time series weighted average operator TOWA operator to establish a dynamic comprehensive evaluation model for expressways:

Among them: y(t _k ) is a linear function; w _j (t _k ) is the weight at time t _k (k=1,2,...n); x _j (t _k ) is the index observation value at time t _k ;

(32) Calculation of linear functions The maximum value of the sum of squared deviations;

(33) Construct the indicator matrix A according to the following formula:

Among them, m represents the number of items in the evaluation index system, and x _i (t _j ) represents the index of the evaluation index system;

(34) Calculate w according to the following formula to maximize the sum of squared deviations of the function y(t _k ):

(35) Take the eigenvector corresponding to the largest eigenvalue of H as the weight vector w.

Further, the comprehensive evaluation of motion blur in the step 4 is calculated according to the following steps:

(41) Establish the factor set U according to the following formula:

U＝{u ₁ , u ₂ , u ₃ , u ₄ }＝{flow saturation, average travel speed, occupancy rate, travel time delay};

(42) Establish the evaluation set V according to the following formula:

V＝{smooth, basic, general, crowded, jammed}＝{5,4,3,2,1};

(43) Establish weight set W according to the following formula:

where w={w ₁ ,w ₂ ,w ₃ ,w ₄ }, and the weights are summed

(44) Establish the evaluation matrix R according to the following formula:

Among them, r _j is the evaluation level of the indicator;

The following multi-dimensional evaluation matrix is constructed by constructing the evaluation grades of the traffic operation status at n moments:

Among them: R _1j , R _2j , R _3j , and R _4j respectively represent the flow saturation, evaluation travel speed, occupancy rate, and evaluation grade value of travel time delay at time j; j=1, 2,...n.

(45) Carry out fuzzy comprehensive evaluation according to the following formula, and obtain the comprehensive evaluation value according to the product of weight vector and evaluation matrix calculation matrix:

Among them, bn represents the comprehensive evaluation result value at time n.

Further, the evaluation result in step 5 is a comprehensive evaluation result obtained at a certain moment through the weight vector and the evaluation matrix, and the traffic operation status is determined through the numerical value of the evaluation result.

Owing to adopting above-mentioned technical scheme, the present invention has following advantage:

The fuzzy comprehensive evaluation method of expressway traffic operation state based on dynamic weight proposed by the present invention is based on the existing expressway data source, uses dynamic traffic data to calculate the index weight in real time, and uses the fuzzy comprehensive evaluation method to evaluate the traffic operation state of the expressway section Evaluation, a method to determine the traffic status of road sections. In this method, the four parameters of road section saturation, occupancy rate, average travel speed, and average travel time delay are used to establish evaluation indicators for expressway sections, and fuzzy comprehensive evaluation is realized through dynamic weights.

Other advantages, objects and features of the present invention will be set forth in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the investigation and research below, or can be obtained from It is taught in the practice of the present invention. The objects and other advantages of the invention may be realized and attained by the following specification.

Description of drawings

The accompanying drawings of the present invention are described as follows.

Fig. 1 is a flowchart of the present invention.

Fig. 2 is a weight calculation diagram of the present invention.

Detailed ways

The present invention will be further described below in conjunction with drawings and embodiments.

As shown in the figure, the fuzzy comprehensive evaluation method provided in this embodiment evaluates the traffic operation state of the expressway section, specifically through the following steps:

Step 1: Data Preprocessing

(1) First, use the threshold method to eliminate the abnormal data, and preprocess the data of the vehicle detector:

The reasonable range of flow threshold q is:

0≤q≤f _c CT/60

Among them: C is the road capacity (veh/h); T is the time interval of data collection (min); f _c is the correction coefficient of the flow rate, usually 1.1-1.3.

The reasonable range of velocity v is: 0≤v≤f _v v ₀

Among them: v ₀ is the speed limit of the high-speed section, and the speed limit of different sections is different, which is determined by the section itself; f _v is the correction coefficient of the speed, usually 1.3-1.5.

Reasonable value range of occupancy rate o: 0≤o≤100%.

(2) Charge data preprocessing:

The data whose travel time is within the interval TE=[L/1.5*v ₀ ,24] is regarded as correct data, and the data outside this interval is regarded as abnormal data and eliminated.

Among them, TE is the effective data interval; L is the length of the section; v ₀ is the speed limit of the high-speed section.

Step 2: Calculate indicator parameter values

Calculate the evaluation index value based on the collected vehicle detector data and charging data. The specific formula is as follows:

(1) Use the 5mim data of the vehicle detector to calculate the flow saturation and occupancy rate:

Among them: S is the flow saturation of the road section; Q is the actual traffic flow in 5 minutes; C ₀ is the design traffic flow of the road section; R _t is the time occupancy rate; T is the length of observation time; t _i is the time when the i-th vehicle occupies the detector , i=1,2...n;

(2) Through the toll ID number of the expressway toll data, the time of entry and exit, and the mileage of the road section, the mileage and travel time of each vehicle are obtained, and the average travel speed and average travel time delay are calculated:

Among them: D is the average travel speed; L _D is the total mileage of all vehicles on the evaluation section during the evaluation period; T _D is the total driving time of all vehicles during the evaluation period; n _D is the number of all vehicles on the evaluation section during the evaluation period; l _Di is the driving mileage of vehicle i in the evaluation period; t _Di is the driving time of vehicle i in the evaluation period. TD is the average travel time delay; l is the length of the road section; td _i is the travel time of the i-th vehicle, and T _td is the total travel time, which can be obtained by calculating the toll data; v ₀ is the smooth speed, which can be obtained according to the design speed of the road section ; n is the sum of the number of vehicles passing through during the observation time.

Step 3: Determine the index weight w

According to the dynamic traffic data, the index weight is calculated in real time by using the difference driving principle of the data:

(1) Since there is an implicit time series relationship between the weight w _j and time t, combined with the time series weighted average operator TOWA operator, the dynamic comprehensive evaluation of the expressway is expressed as:

Among them: y(t _k ) is a linear function; w _j (t _k ) is the weight at time t _k (k=1,2,...n); x _j (t _k ) is the index observation value at time t _k ;

(2) At the same time, in order to maximize the difference between the operating states of the system s at different times, it is necessary to let the linear function The sum of squared deviations is the largest.

(3) Assume that the evaluation index system has a total of m indicators, and push forward n-1 time units from the evaluation time t _n to the time t ₁ , all indicators can be expressed as x _i (t _j )(i=1,2, ...n;j=1,2...m)

Get the indicator matrix A:

w maximizes the sum of squared deviations of the function y(t _k ), then it can be transformed into a linear programming problem, which has the following formula:

but:

Take the eigenvector corresponding to the largest eigenvalue of H as the weight vector w.

Step 4: Implementation of dynamic fuzzy comprehensive evaluation

The general steps of fuzzy comprehensive evaluation are as follows:

(1) Establish the factor set U: The factor set refers to the set of factors of the evaluation object, also known as the parameter index,

U＝{u ₁ , u ₂ , u ₃ , u ₄ }＝{flow saturation, average travel speed, occupancy rate, travel time delay};

(2) Establish evaluation set V: it is the set of evaluation comments on the object. It is a collection of comments. Based on the principle of human readability and the evaluation requirements of expressway traffic, as well as the classification standard of expressway, the evaluation set

V＝{smooth, basic, general, crowded, jammed}＝{5,4,3,2,1};

(3) Establish weight set W: According to the weight vector w={w ₁ ,w ₂ ,w ₃ ,w ₄ } calculated in step 3, the weights are added It is necessary to use the principle of normalization to process and re-determine the weight set

(4) Establish the evaluation matrix R: evaluate from a single factor in the factor set U, and determine the evaluation level of each element in the evaluation object set; when the i-th factor is evaluated, the evaluation level of the index is r _j (r _j 's The values are 1, 2, 3, 4, 5), and the value of r _j is determined according to Table 1, then there is an evaluation matrix:

Table 1 Index evaluation grading standard table (design speed is 120km/h)

When evaluating the traffic operation status at n times at the same time, there is the following multi-dimensional evaluation matrix:

Among them: R _1j , R _2j , R _3j , and R _4j respectively represent the flow saturation, evaluation grade value of travel speed, occupancy, and travel time delay at time j; j=1, 2,...n.

(5) Fuzzy comprehensive evaluation: When the weight set and evaluation matrix are known, the product of the calculation matrix is calculated to obtain the comprehensive evaluation value:

Among them, bn represents the comprehensive evaluation result value at time n.

Step 5: Determine the evaluation result

It can be seen from step 4 that the comprehensive evaluation result at a certain moment is obtained through the weight vector and the evaluation matrix, and the result is a specific value between [0,5]. The traffic operation state is determined by the value of the value, and the specific state The interval classification table is as follows:

Table 2 Interval table of running status

Comprehensive evaluation results [0,1.5) [1.5,2.5) [2.5,3.5) [3.5,4.5) [4.5,5] state jam crowded generally Basic flow unimpeded

Finally, it is noted that the above embodiments are only used to illustrate the technical solutions of the present invention without limitation. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be carried out Modifications or equivalent replacements, without departing from the spirit and scope of the technical solution, should be included in the protection scope of the present invention.

Claims (5)

1. the freeway traffic operating status fuzzy synthetic appraisement method based on changeable weight, it is characterised in that：Including following Step：

Step 1：Acquisition highway data simultaneously pre-process data；The data include vehicle checker data and charge number According to；

Step 2：According to the vehicle checker data of acquisition and charge data Calculation Estimation index value；The evaluation index value includes calculating Flow saturation degree, time occupancy, average travel speed and average travel time delay；

Step 3：According to dynamic traffic data, the real-time parameter weight vectors of the variance drive principle of data are utilized；

Step 4：Dynamic-fuzzy-ovcrall evaluation model is established according to weight vectors and calculates the comprehensive of freeway traffic operating status Close evaluation of estimate：

Step 5：Freeway traffic operating status is evaluated according to comprehensive evaluation value and exports evaluation result；

Weight vectors in the step 3 calculate according to the following steps：

(31) sequential weighted average operator TOWA operators is combined to establish the Dynamic Comprehensive Evaluation model of highway：

Wherein：y(t_k) it is linear function；w_j(t_k) it is t_kThe weight at moment, k=1,2 ... n；x_j(t_k) it is t_kThe index at moment is seen Measured value；

(32) linear function is calculatedSum of squares of deviations maximum value；

(33) according to following formula structure index matrix A：

I=1,2 ... n；J=1,2...m

Wherein, m indicates assessment indicator system index item number, x_i(t_j) indicate assessment indicator system index；

(34) calculating w according to following formula makes function y (t_k) sum of squares of deviations it is maximum：

max{w^THw}

s.t.w^TW=1；

W ＞ 0

(35) the corresponding feature vector of the Maximum characteristic root of H is taken, as weight vectors w.

2. the freeway traffic operating status fuzzy synthetic appraisement method based on changeable weight as described in claim 1, It is characterized in that：The data prediction of the step 1 calculates according to the following steps：

(11) the extraordinary data in vehicle checker data are rejected using threshold method, is as follows：

Flow threshold q is determined according to following formula：

0≤q≤f_cCT/60；

Wherein：C is road passage capability；T is the time interval of data acquisition；f_cFor the correction factor of flow；

Speed v is determined according to following formula：

0≤v≤f_vv₀；

Wherein：v₀For the limitation speed of fastlink；f_vFor the correction factor of speed；

(12) it to the pretreatment of charge data, is as follows：

The predetermined threshold value TE of journey time is determined according to following formula：

TE=[L/1.5*v₀,24]；

Wherein, TE is effective data intervals；L is road section length；v₀For the limitation speed of fastlink；

Charge data is judged whether in predetermined threshold value TE, if it is, charge data is correct data, if it is not, then receiving It is extraordinary data to take data；

Reject extraordinary data.

3. the freeway traffic operating status fuzzy synthetic appraisement method based on changeable weight as described in claim 1, It is characterized in that：Evaluation index value in the step 2 calculates according to the following steps：

The evaluation index value is calculated according to following formula：

(21) vehicle checker data are used to calculate flow saturation degree and occupation rate：

Wherein：S is link flow saturation degree；Q is practical vehicle flowrate；C₀For the design vehicle flowrate in section；R_tFor time occupancy；T For observation interval；t_iThe time of detector, i=1,2 ... n are occupied for i-th vehicle；

(22) by the charge ID number of expressway tol lcollection data, go out station entrance time and section mileage, obtain the row of each car Mileage and journey time are sailed, average travel speed and average travel time delay are calculated：

Wherein：D is average stroke speed；L_DFor the total kilometrage of all drivings on evaluation period inner evaluation section；T_DTo evaluate the period The total time of interior all vehicle drivings；n_DFor all driving vehicle numbers on evaluation period inner evaluation section；l_DiFor in the evaluation period The mileage of driving vehicle i；t_DiFor the running time of driving vehicle i in the evaluation period；TD is delayed for average travel time；l For road section length；td_iFor the journey time of i-th vehicle, T_tdFor total travel time, it can be calculated and be obtained by charge data；v₀For Pass unimpeded speed, is obtained according to the design speed in section；N be observation time in by vehicle number summation.

4. the freeway traffic operating status fuzzy synthetic appraisement method based on changeable weight as described in claim 1, It is characterized in that：Dynamic-fuzzy-ovcrall evaluation in the step 4 calculates according to the following steps：

(41) set of factors U is established according to following formula：

U={ u₁,u₂,u₃,u₄}={ flow saturation degree, average stroke speed, occupation rate, journey time delay }；

(42) evaluate collection V is established according to following formula：

V=it is unimpeded, and it is substantially unimpeded, it is generally, crowded, block={ 5,4,3,2,1 }；

(43) weight sets W is established according to following formula：

Wherein, w={ w₁,w₂,w₃,w₄, and weight is added

(44) evaluations matrix R is established according to following formula：

Wherein, r_jFor the opinion rating of index；

The opinion rating of the traffic circulation state at n moment is built to following multidimensional evaluations matrix：

Wherein：R_1j, R_2j, R_3j, R_4jIndicate respectively flow saturation degree, evaluation travel speed, occupation rate, journey time delay when Carve the opinion rating value of j；J=1,2 ... n；

(45) fuzzy overall evaluation is carried out according to following formula, is obtained according to the product of weight vectors and evaluations matrix calculating matrix Comprehensive evaluation value：

Wherein, bn indicates the comprehensive evaluation result value of moment n.

5. the freeway traffic operating status fuzzy synthetic appraisement method based on changeable weight as described in claim 1, It is characterized in that：Evaluation result in the step 5 is the comprehensive evaluation result acquired by weight vectors and evaluations matrix, is passed through The numerical value of evaluation result determines traffic circulation state.