CN115311865A - Method for acquiring traffic volume survey data based on ETC portal frame and charging data - Google Patents
Method for acquiring traffic volume survey data based on ETC portal frame and charging data Download PDFInfo
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Abstract
The invention provides a method for acquiring traffic volume survey data based on an ETC portal frame and charging data, which comprises the following steps: s1, ETC portal frame passing data, toll car flow detail data and a portal frame basic information table in a target area are obtained; s2, preprocessing the ETC portal passing data collected in the step S1; and S3, calculating road traffic volume survey data through the traffic data preprocessed in the step S2. The method for acquiring traffic volume survey data based on the ETC portal frame and the charging data has the advantages of high efficiency and rapidness in data entry and processing, higher practical value, capability of calculating various indexes required by highway traffic volume survey and capability of providing data support for planning, designing and operating management of a highway network.
Description
Technical Field
The invention belongs to the technical field of traffic informatization, and particularly relates to a method for acquiring traffic volume survey data based on an ETC portal frame and charging data.
Background
The traffic volume survey is an important parameter for describing traffic flow characteristics, and is an observation and recording work for various traffic unit quantities of a certain section of a passing road in a certain time, a certain period or a continuous period. The traffic volume survey aims to collect traffic volume data through long-term continuous observation or short-term interval and temporary observation, know the change and distribution rule of the traffic volume in time and space, and provide necessary data for traffic planning, road network construction, traffic control and management, engineering economic analysis and the like.
At present, a manual survey method and a dispatching station survey method are commonly used in highway traffic volume survey. The manual survey method needs to arrange technical personnel for fixed-point survey in advance, needs to invest a large amount of time and energy, has large workload of data entry, is easy to make mistakes, and is not an efficient data acquisition method. Compared with the prior art, the data acquisition method based on the automatic traffic dispatching station has high data quality and high input speed, and is convenient for subsequent data analysis work, but the method is influenced by the arrangement position of the survey station and cannot acquire the traffic volume condition of the whole road network.
After the provincial toll station is completely cancelled, the analysis and application based on ETC portal data becomes one of the popular directions in the field of highway big data research. The ETC portal frame system installed in the interchange of the expressway can obtain massive vehicle passing data including vehicle types, passing time, entrance time and the like, compared with the conventional toll data of the entrance and exit of the expressway obtained through the CPC composite passing card, the data volume of the vehicle passing on the section of the expressway is greatly increased, and the data volume is a good data source for highway traffic volume investigation. The existing journal 'highway traffic volume transformation exploration based on ETC portal data' analyzes the problem that the shapes of trucks in ETC portal data and traffic survey data are inconsistent, but does not research other data indexes, and has limitation.
Disclosure of Invention
In view of this, the present invention aims to provide a method for acquiring traffic volume survey data based on an ETC portal and charging data, and aims to solve the problems of low data entry efficiency, poor quality, single output data, high cost and limitation in the existing method.
In order to achieve the aim, the invention provides a method for acquiring traffic volume survey data based on an ETC portal frame and charging data, which comprises the following steps:
s1, ETC portal frame passing data, toll car flow detail data and a portal frame basic information table in a target area are obtained;
s2, preprocessing the ETC portal passing data acquired in the step S1;
s3, converting vehicle types based on the traffic data preprocessed in the step S2, and then calculating road traffic volume survey data;
vehicle type conversion: according to the charging vehicle type code, performing vehicle type conversion according to the inter-dispatching vehicle type to obtain a corresponding conversion coefficient;
the highway traffic volume survey data comprises: calculating section traffic volume, section vehicle type composition, OD traffic volume and interval average vehicle speed V in the period S A peak hour coefficient PHF and a traffic direction imbalance coefficient K D And a monthly change coefficient K of traffic volume Moon cake And coefficient of cyclic variation K Week (week) 。
Further, in step S2, the step of the ETC portal passage data preprocessing is as follows:
s2.1, deleting the record with the code value of the billing vehicle type of 0;
s2.2, deleting the record of which the charging mileage is a null value.
Because ETC portal traffic data may be influenced by factors such as transmission line faults, opposite portal mistaken shooting and the like, abnormal records may exist in data returned by the settlement center. The method can further improve the accuracy of the research result through the pretreatment step.
Further, in the step S3, the calculating step of the cross-sectional traffic volume within the statistical time period is as follows:
a. calculating the number of various types of vehicles with the same label in a statistical time period by taking the number of the gate frames in the ETC gate frame passing data as the label to obtain the section traffic volume of each vehicle type in a single direction;
b. b, indexing the opposite gantry numbers through the gantry numbers in the step a to obtain the traffic volume of the sections of the opposite vehicle types, wherein the sum of the uplink traffic volume and the downlink traffic volume is the actual section traffic volume;
c. according to the conversion coefficient, calculating the traffic volume T of the standard vehicle with equivalent cross section Sign board The calculation expression is as follows:
in the formula, T i,u I-type vehicle natural traffic volume, T, in upward direction i,d I-type vehicle natural traffic quantity alpha in the downward direction i The conversion coefficient of the ith vehicle; i belongs to { small and medium-sized passenger cars, large buses, minivans, medium-sized trucks, large trucks and oversize trucks }.
Further, in the step S3, the composition of the cross-section vehicle type is calculated as follows:
in the formula, i belongs to { middle and small passenger car, large passenger car, small truck, medium truck, large truck and super large truck }.
Further, in step S3, the calculating step of the OD running amount in the statistical time period is as follows:
A. extracting detailed toll vehicle flow data and a portal basic information table in a statistical time period, and writing 'license plate number', 'starting time', 'ending time', 'end point number', 'end point name', 'end point region, a' starting point number ',' starting point name 'and' starting point region according to the extracted field data;
B. and extracting the traffic of each vehicle type passing through the same starting point and the same end point in one day, namely counting the natural vehicle OD traffic between the starting point and the end point in a time period, and then performing vehicle type conversion according to the intermodule vehicle type to obtain the intermodule vehicle type and the standard vehicle OD traffic.
Further, in step S3, the step of calculating the section average vehicle speed is as follows:
(1) counting the length s of a road section between the portal j and the portal k;
(2) extracting all vehicle portal passing data passing through a road section between the portal j and the portal k in the statistical time period so as to obtain the time t of the ith vehicle passing through the road section i The calculation expression is as follows:
t i ＝passtime k -passtime j
in the formula, passtime j Time to pass portal j, past k The time of the last portal k is elapsed;
(3) calculating the section average vehicle speed V s The calculation expression is as follows:
in the formula, n is the total number of vehicles passing through a road section between the portal j and the portal k in the statistical time period.
Further, in step S3, the calculating step of the imbalance coefficient in the traffic volume direction is as follows:
i, calculating the section traffic volume of the up and down directions of the same road section, and recording the larger traffic volume in the two directions as T Max ；
Calculating the average value of the section traffic in the two directions, wherein the calculation expression is as follows:
in the formula, T ave Representing the average traffic in both directions, T u Representing cross-sectional traffic in the up direction, T d Representing the section traffic volume in the descending direction;
III, calculating the direction imbalance coefficient K D The calculation expression is as follows:
the invention has the beneficial effects that:
1. the source data used by the method come from ETC portal equipment installed on the highway, and compared with an inter-dispatching station investigation method, the method does not need to install other data acquisition equipment, has wide coverage range and is not influenced by the installation position of the inter-dispatching equipment; compared with a manual investigation method, the method does not need technical personnel to carry out field investigation, is efficient and rapid in data input and processing, is low in cost and has higher practical value.
2. The invention provides a vehicle type conversion method, which can convert the traffic volume in ETC portal data into the type required by the traffic dispatching data through a conversion coefficient, realize effective conversion of the data and solve the problem that the classification requirements of the ETC portal data and the traffic dispatching data on vehicle types are inconsistent.
3. The invention provides a method for acquiring highway traffic volume survey data based on an ETC portal and toll data, which comprises the steps of cleaning and analyzing the data on the basis of extracting the ETC portal data, then calculating indexes required by highway traffic volume survey by combining the toll data, wherein the calculated indexes comprise section traffic volume, OD (origin-destination) running volume, interval average vehicle speed, traffic composition, traffic volume direction unbalance coefficient, peak hour coefficient, traffic volume weekly-varying coefficient and monthly-varying coefficient, and the important data indexes which need to be referred to for highway planning, construction and scheduling are basically covered.
4. The invention provides a method for acquiring highway traffic volume survey data based on an ETC portal frame and toll data, which can realize short-time update according to the return frequency of the ETC portal frame data and provide support for real-time traffic running state analysis.
Drawings
FIG. 1 is a flow chart of a method for obtaining highway traffic volume survey data according to the present invention.
Detailed Description
In order to make the technical solutions, advantages and objects of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. It should be apparent that the described embodiments are only some of the embodiments of the present invention, and not all of them. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention without any inventive step, are within the scope of protection of the present application.
As shown in fig. 1, the present invention provides a method for obtaining traffic volume survey data based on an ETC portal and charging data, comprising the following steps:
s1, ETC portal frame passing data, toll vehicle flow detail data and a portal frame basic information table in a target area are obtained;
s2, preprocessing the ETC portal passing data acquired in the step S1;
and S3, converting the vehicle type based on the traffic data preprocessed in the step S2, and then calculating traffic volume survey data of the expressway.
The ETC portal passage data and the toll collection vehicle flow detail data are vehicle record information transmitted back by the toll collection equipment, and the field names and the descriptions are shown in tables 1 and 2. The portal basic information table records the Chinese name corresponding to the toll station code, the district and county where the toll station is located, the Chinese name corresponding to the portal number code, and the name of the road where the toll station belongs, as shown in table 3.
TABLE 1 ETC transaction data Table field
TABLE 2 charging data table fields
TABLE 3 Portal basic information table
| Serial number | Name of field | Description of field | Serial number | Name of field | Description of field |
| 1 | STATION_TAX_CODE | Toll station code | 4 | MJCODEHEX | Portal number code |
| 2 | STATION_NAME | Toll station Chinese name | 5 | ROAD | Name of road to which portal belongs |
| 3 | REGION_NAME | The district of | 6 | MJNAME | Chinese name of portal |
In the step S2, the ETC portal passing data preprocessing step is as follows:
s2.1, deleting a record with the code value of the billing vehicle type being 0, namely ENVEHCLASS =0;
the field content of the billing vehicle type code (envehcrass) is a discrete value, the normal value and the meaning thereof are shown in table 4, therefore, the value of 0 represents a toll-free vehicle type, and the analysis shows that the time interval between the data of the vehicle type code 0 and the transaction record under the normal vehicle type code is very short, generally within 2-3 seconds, obviously, the data is invalid data for the transaction and needs to be cleaned.
S2.2, deleting the record of the charging mileage as a null value.
The field content of the charging mileage (DISTANCE) is a continuous value, which indicates that the transaction time interval is not more than 2-3 seconds through the DISTANCE between two charging units, therefore, when the value is 0, a plurality of transaction data are indicated under the portal at the same time, and the data are invalid data and need to be cleaned.
Vehicle type conversion: and according to the charging vehicle type code (ENVEHCLASS), performing vehicle type conversion according to the inter-dispatching vehicle type corresponding to the table 4 to obtain a corresponding conversion coefficient.
The method comprises the following steps that vehicles with codes of 1, 2, 3, 4, 13, 14, 15, 16, 23, 24, 25 and 26 can directly correspond to the intermodal vehicle types, and vehicles with codes of 11, 12, 21 and 22 cannot directly correspond to the intermodal vehicle types, and the splitting method comprises the following steps: the total weight of the entrance cargos (ENALLLIUP) in the portal frame passing data table is taken as p,
if p-4.5 is more than or equal to 2or0 and more than or equal to 4.5, the intermodal vehicle model = small truck, and the conversion coefficient α =1;
if else 2 < p-4.5 < 7, intermodal vehicle model = medium truck, and the conversion coefficient α =1.5.
TABLE 4 conversion of toll car type into interchange car type and standard car type coefficient
The highway traffic volume survey data comprises: calculating section traffic volume, section vehicle type composition, OD traffic volume and interval average vehicle speed V in the period S A peak hour coefficient PHF and a traffic direction imbalance coefficient K D And the monthly coefficient of traffic volume K Moon cake And coefficient of cyclic variation K Week (week) 。
(1) The calculation steps of the section traffic volume in the statistical time period are as follows:
a. calculating the number of various vehicle types (ENVEHCLASS) with the same label in a statistical time period (hours and days) by taking a portal number (MJCODE) field in ETC portal passing data as a label to obtain the section traffic volume of each vehicle type in a single direction;
b. b, indexing the opposite portal numbers through the portal numbers in the step a to obtain the cross section traffic volume of each opposite vehicle type, and summing up the uplink traffic volume and the downlink traffic volume to obtain the actual cross section traffic volume;
c. calculating the traffic volume T of the standard vehicle according to the conversion coefficient of the standard vehicle Sign board The calculation expression is as follows:
in the formula, T i,u I-type vehicle natural traffic volume, T, in upward direction i,d I-type vehicle natural traffic volume alpha in downward direction i For conversion of i-th vehicleA coefficient; i belongs to { middle and small passenger car, large passenger car, small truck, medium truck, large truck and super large truck }.
(2) The composition of the section vehicle type is calculated as follows:
in the formula, i belongs to { middle and small passenger car, large passenger car, small truck, medium truck, large truck and super large truck }.
(3) The calculation steps of the OD output in the statistical time period are as follows:
A. and extracting the toll vehicle flow detail table and the portal basic information table in the corresponding statistical time interval. Extracting all field data in the statistical time interval in the charging vehicle flow list one by one, and writing 'charging license plate number (envehpulate)'; writing "entry time (entry)" into "start time", and "exit time (exit)" into "end time"; writing the exit number (exit) into the end point number, using an exit HEX character string (exit HEX) as a label, inquiring the exit name and the district in the portal basic information table, and writing the end point name into the end point district; "entry number (entry)" is written in "start number", and "entry HEX string (entry)" is used as a tag to inquire the entry name and the prefecture where the entry is located in the portal basic information table and to write in "start name" and "start prefecture".
B. And extracting the traffic of each vehicle type passing through the same starting point and the same end point on a certain day, namely counting the natural vehicle OD traffic between the starting point and the end point in a period of time, and then performing vehicle type conversion according to the intermodule vehicle type to obtain the intermodule vehicle type and the standard vehicle OD traffic.
(4) Average vehicle speed V in interval S The calculation steps of (2) are as follows:
(1) counting the length s of a road section between a portal j and a portal k;
(2) extracting all vehicle portal passing data passing through a road section between the portal j and the portal k in the statistical time period so as to obtain the time t of the ith vehicle passing through the road section i The calculation expression is as follows：
t i ＝passtime k -passtime j
In the formula, passtime j Past time to portal j k The time of the last portal k is elapsed;
(3) calculating the section average vehicle speed V s The calculation expression is as follows:
in the formula, n is the total number of vehicles passing through a road section between the door frame j and the door frame k in the statistical time period.
(5) The high peak hour coefficient PHF is calculated as follows:
counting the section traffic volume of the road section in each hour all day (calculated according to a standard vehicle), recording the maximum time period of the traffic volume in each hour all day as peak hour, and recording the traffic volume in the hour as the peak hour traffic volume;
II, extracting and counting the maximum traffic volume (calculated according to a standard vehicle) within 15 minutes continuously in the peak hour;
III high Peak hour factor PHF 15 The calculation expression of (c) is as follows:
(6) Coefficient of imbalance in traffic direction K D The calculation steps are as follows:
i, calculating the section traffic volume of the up and down directions of the same road section, and recording the larger traffic volume in the two directions as T Max ；
And II, calculating the average value of the section traffic in the two directions, wherein the calculation expression is as follows:
in the formula, T ave Representing the average traffic in both directions, T u Representing cross-sectional traffic in the up direction, T d Representing the section traffic volume in the descending direction;
III, calculating the direction imbalance coefficient K D The calculation expression is as follows:
(7) Monthly coefficient of traffic K Moon cake Coefficient of variation K Week (week) The calculating steps are as follows:
calculating annual average daily traffic AADT, monthly average daily traffic MADT and weekly average daily traffic WADT, wherein the calculation expression is as follows:
in the formula, Q i Representing the total daily traffic in each specified time period, and n represents the number of days of the month.
Coefficient of lunar variation K Moon cake The calculation expression is as follows:
III, coefficient of cyclic variation K Week (week) The calculation expression is as follows:
example 1
In the embodiment, the ETC portal traffic data, the toll collection vehicle flow detail data and the portal basic information table in a city all day are used as the basis, the data are cleaned and analyzed, and indexes required by highway traffic volume investigation are calculated.
Data cleaning: and deleting records of ENVEHCLASS =0 and DISTANCE =0 in ETC portal passage data to obtain cleaned data.
As shown in table 5, 14 pieces of data were obtained by extracting the vehicle track with the brand "yuee 6 × 2_1" from the ETC portal raw data. Firstly, the record with the charging vehicle type code of 0 is removed, 10 pieces of data are remained, as can be seen from table 6, the vehicle continuously passes through the same portal frame '581405' for 2 times, the passing time interval is 2 seconds, the vehicle type code has two types of records of 4 and 14, one piece of data is preliminarily judged to have errors, the trading DISTANCE (DISTANCE) field is checked, 5 pieces of records with 0 are judged to be invalid data, and the invalid data is removed. The data after cleaning is shown in table 7, the vehicle types are all 14, the situation that the vehicle continuously passes through the same gantry for 2 times does not exist, the running track is continuous, and the time interval is reasonable.
TABLE 5 ETC Portal transaction data before data cleansing
| MJCODEHEX | PASSTIME | ENVEHPLATE | ENVEHCLASS | DISTANCE | JYQLJLC | JYHLJLC |
| 5A1401 | 2021/*/**0:04 | Yu EE6 star 2 u 1 | 4 | 0 | 0 | 0 |
| 5A1401 | 2021/*/**0:04 | Yu EE6 star 2 u 1 | 14 | 2800 | 0 | 2800 |
| 5A1401 | 2021/*/**0:04 | Yu EE6 star 2 u 1 | 0 | 0 | 0 | 0 |
| 5A1401 | 2021/*/**0:04 | Yuee 6 star 2' 1 | 0 | 0 | 0 | 0 |
| 581402 | 2021/*/**0:17 | Yuee 6 star 2' 1 | 14 | 14520 | 2800 | 17320 |
| 581402 | 2021/*/**0:17 | Yu EE6 star 2 u 1 | 4 | 0 | 0 | 0 |
| 591402 | 2021/*/**0:17 | Yu EE6 star 2 u 1 | 0 | 0 | 0 | 0 |
| 581403 | 2021/*/**0:21 | Yuee 6 star 2' 1 | 4 | 0 | 0 | 0 |
| 581403 | 2021/*/**0:21 | Yu EE6 star 2 u 1 | 14 | 5780 | 17320 | 23100 |
| 591403 | 2021/*/**0:21 | Yu EE6 star 2 u 1 | 0 | 0 | 0 | 0 |
| 581404 | 2021/*/**0:31 | Yu EE6 star 2 u 1 | 4 | 0 | 0 | 0 |
| 581404 | 2021/*/**0:31 | Yu EE6 star 2 u 1 | 14 | 12320 | 23100 | 35420 |
| 581405 | 2021/*/**0:33 | Yuee 6 star 2' 1 | 4 | 0 | 0 | 0 |
| 581405 | 2021/*/**0:33 | Yuee 6 star 2' 1 | 14 | 2230 | 35420 | 37650 |
TABLE 6 transaction record after eliminating billing vehicle type code as 0
Table 7 transaction records after data has been completely purged
| MJCODEHEX | PASSTIME | ENVEHPLATE | ENVEHCLASS | DISTANCE | JYQLJLC | JYHLJLC |
| 5A1401 | 2021/*/**0:04 | Yuee 6 star 2' 1 | 14 | 2800 | 0 | 2800 |
| 581402 | 2021/*/**0:17 | Yuee 6 star 2' 1 | 14 | 14520 | 2800 | 17320 |
| 581403 | 2021/*/**0:21 | Yu EE6 star 2 u 1 | 14 | 5780 | 17320 | 23100 |
| 581404 | 2021/*/**0:31 | Yuee 6 star 2' 1 | 14 | 12320 | 23100 | 35420 |
| 581405 | 2021/*/**0:33 | Yuee 6 star 2' 1 | 14 | 2230 | 35420 | 37650 |
Calculating road traffic volume survey data including section traffic volume, section vehicle type composition, OD traffic volume and interval average vehicle speed V S A peak hour coefficient PHF and a traffic direction imbalance coefficient K D And the monthly coefficient of traffic volume K Moon cake And coefficient of cyclic variation K Week (week) 。
(1) Calculating the cross section traffic volume and the cross section vehicle type composition in the statistical time period: and (3) calculating the number of fields of various types of vehicles (ENVEHCLASS) in the whole day by taking a door frame number (MJCODE) field in a door frame passing data table as a label, namely the section traffic volume in one direction, and further judging the types of the trucks according to the total weight (ENELLUP) of the inlet trucks, wherein the types are shown in a table 8. The opposite gantry number is indexed through the gantry number, the sum of the uplink flow and the downlink flow is the natural cross section traffic volume in the statistical time period, the cross section traffic volume and the cross section vehicle type composition counted by the cross-dispatching vehicle type are obtained through vehicle type conversion, and the result is output in a form of a table 9.
TABLE 8 truck model determination
TABLE 9 calculation results of traffic volume and percentage of cross section
(2) Calculating the OD output in the statistical time period: the calculation procedure was as above and the results are output in the format of table 10.
Table 10 trip origin-destination statistics
And extracting the traffic flow of the vehicle type passing through the same starting point and the same end point on a certain day, namely the natural vehicle OD traffic flow between the starting point and the end point, obtaining the standard vehicle OD traffic flow through vehicle type conversion, and outputting the result in a format shown in a table 11.
TABLE 11 OD output
(3) Based on the ETC portal traffic data, the toll vehicle flow detail data and the portal basic information table of the embodiment, the method for analyzing and calculating the ETC portal traffic data calculates the average speed of the interval, the peak hour coefficient, the traffic direction unbalance coefficient, the traffic monthly change coefficient and the traffic weekly change coefficient according to the analysis and calculation method of the invention.
Finally, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that various changes, modifications and equivalents may be made therein without departing from the spirit and scope of the present invention.
Claims (7)
1. A method for obtaining traffic volume investigation data based on ETC portal frame and charging data is characterized by comprising the following steps:
s1, ETC portal frame passing data, toll vehicle flow detail data and a portal frame basic information table in a target area are obtained;
s2, preprocessing the ETC portal passing data acquired in the step S1;
s3, converting vehicle types based on the traffic data preprocessed in the step S2, and then calculating road traffic volume survey data;
vehicle type conversion: according to the charging vehicle type code, performing vehicle type conversion according to the inter-dispatching vehicle type to obtain a corresponding conversion coefficient;
the highway traffic volume survey data comprises: calculating section traffic volume, section vehicle type composition, OD traffic volume and interval average vehicle speed V in the period S Peak hourCoefficient PHF, coefficient of imbalance in traffic direction K D And the monthly coefficient of traffic volume K Moon cake And coefficient of cyclic variation K Week (week) 。
2. The method for acquiring traffic volume survey data based on the ETC portal and the toll data according to claim 1, wherein in the step S2, the ETC portal traffic data is preprocessed by the following steps:
s2.1, deleting the record with the code value of the billing vehicle type being 0;
s2.2, deleting the record of the charging mileage as a null value.
3. The method for obtaining traffic volume survey data based on the ETC portal frame and the charging data according to claim 2, wherein in the step S3, the calculation of the section traffic volume in the statistical time period comprises the following steps:
a. calculating various vehicle types of the same label in a statistical time period by taking the portal number in the ETC portal passing data as a label to obtain the section traffic volume of each vehicle type in a single direction;
b. b, indexing the opposite gantry numbers through the gantry numbers in the step a to obtain the traffic volume of the sections of the opposite vehicle types, wherein the sum of the uplink traffic volume and the downlink traffic volume is the actual section traffic volume;
c. calculating the traffic volume T of the standard vehicle with equivalent cross section according to the conversion coefficient Sign board The calculation expression is as follows:
in the formula, T i,u I-type vehicle natural traffic volume, T, in upward direction i,d I-type vehicle natural traffic volume alpha in downward direction i The conversion coefficient of the ith vehicle; i belongs to { small and medium-sized passenger cars, large buses, minivans, medium-sized trucks, large trucks and oversize trucks }.
4. The method according to claim 3, wherein in the step S3, the calculation of the composition of the section vehicle type is as follows:
in the formula, i belongs to { middle and small passenger car, large passenger car, small truck, medium truck, large truck and super large truck }.
5. The method according to claim 4, wherein in the step S3, the calculation of the OD traffic in the statistical period is as follows:
A. extracting detailed toll vehicle flow data and a portal basic information table in a statistical time period, and writing 'license plate number', 'starting time', 'ending time', 'end point number', 'end point name', 'end point region, a' starting point number ',' starting point name 'and' starting point region according to the extracted field data;
B. and extracting the traffic of each vehicle type passing through the same starting point and the same end point in one day, namely counting the natural vehicle OD traffic between the starting point and the end point in a time period, and then performing vehicle type conversion according to the intermodule vehicle type to obtain the intermodule vehicle type and the standard vehicle OD traffic.
6. The method for obtaining traffic volume survey data based on the ETC portal frame and the toll collection data according to claim 5, wherein in the step S3, the calculation of the interval average vehicle speed comprises the following steps:
(1) counting the length s of a road section between the portal j and the portal k;
(2) extracting all vehicle portal passing data passing through a road section between the portal j and the portal k in the statistical time period so as to obtain the time t of the ith vehicle passing through the road section i The calculation expression is as follows:
t i ＝passtime k -passtime j
in the formula, passtime j Time to pass portal j, pastime k The time of the last portal k is elapsed;
(3) calculating the section average vehicle speed V s The calculation expression is as follows:
in the formula, n is the total number of vehicles passing through a road section between the portal j and the portal k in the statistical time period.
7. The method according to claim 3, wherein in the step S3, the calculation of the traffic direction imbalance coefficient comprises:
i, calculating the section traffic volume of the up and down directions of the same road section, and recording the large traffic volume in the two directions as T Max ；
Calculating the average value of the section traffic in the two directions, wherein the calculation expression is as follows:
in the formula, T ave Representing the average traffic in both directions, T u Representing cross-sectional traffic in the up direction, T d Representing the cross-section traffic volume in the downlink direction;
III, calculating the direction imbalance coefficient K D The calculation expression is as follows:
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