A method, device, equipment and medium for daily monitoring of commercial highway passenger volume

Abstract

The present invention relates to the technical field of highway passenger transport statistics, and discloses a daily monitoring method, device, equipment and medium for commercial highway passenger volume. The method comprises: calculating the base month commercial highway passenger volume based on the highway transport passenger volume range, the intercity and urban and rural public bus and tram passenger volume range, and the intercity and urban and rural taxi passenger volume range; obtaining optimized highway bus traffic data and optimized national and provincial highway bus traffic data; calculating the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, optimized highway bus traffic data, and optimized national and provincial highway bus traffic data; calculating the key holiday adjustment coefficient through website attendance data, and obtaining the final daily commercial highway passenger volume based on the key holiday adjustment coefficient and the initial daily commercial highway passenger volume. The present application improves the monitoring accuracy and data reliability by integrating multiple data sources and using the fluctuation coefficient method to calculate the daily commercial highway passenger volume.

Description

Technical Field

[0001] The present invention relates to the technical field of highway passenger transport statistics, and in particular to a method, device, equipment and medium for daily monitoring of commercial highway passenger transport volume. Background Art

[0002] Currently, national commercial highway passenger volume is calculated monthly. Each month, highway passenger transport companies submit their monthly figures to the transportation authorities through the "Transportation Enterprise One-Stop Online Reporting System." These figures are then aggregated to produce the national commercial highway passenger volume. During key holidays (such as New Year's Day and Spring Festival) each year, transportation authorities estimate national commercial highway passenger volume by collecting daily figures and trends from a sample of typical companies.

[0003] The shortcomings of existing technologies are as follows: the statistical method for daily passenger volume during key holidays is cumbersome and labor-intensive, there are errors when estimating passenger volume through typical enterprises, big data resources are not fully utilized, and the statistical scope is limited. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to overcome the deficiencies in the prior art and to provide a method, device, equipment and medium for daily monitoring of commercial highway passenger traffic.

[0005] The present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present disclosure provides a method for daily monitoring of commercial highway passenger volume, the method comprising:

[0007] Obtain the range of highway transport passenger volume, inter-city and urban-rural public bus and tram passenger volume, and inter-city and urban-rural taxi passenger volume;

[0008] Calculate the base month's commercial highway passenger volume based on the highway passenger volume range, the inter-city and urban-rural public bus and tram passenger volume range, and the inter-city and urban-rural taxi passenger volume range;

[0009] Obtaining original expressway bus traffic data and original national and provincial highway bus traffic data, and preprocessing the original expressway bus traffic data and the original national and provincial highway bus traffic data to obtain optimized expressway bus traffic data and optimized national and provincial highway bus traffic data;

[0010] Calculate the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized highway bus traffic data, and the optimized national and provincial highway bus traffic data using the fluctuation coefficient method;

[0011] The website attendance data is collected, a key holiday adjustment coefficient is calculated based on the website attendance data, and the initial daily commercial highway passenger volume is corrected according to the key holiday adjustment coefficient to obtain the final daily commercial highway passenger volume.

[0012] Optionally, the calculation of the base month's commercial highway passenger volume based on the highway transport passenger volume range, the intercity and urban-rural public bus and tram passenger volume range, and the intercity and urban-rural taxi passenger volume range includes:

[0013] Calculate the base month highway transport passenger volume according to the highway transport passenger volume range, wherein the base month highway transport passenger volume includes the base month regular bus passenger volume and the base month tourist chartered bus passenger volume;

[0014] Calculate the base month's intercity and urban and rural public bus and tram passenger volume based on the intercity and urban and rural public bus and tram passenger volume range;

[0015] The intercity and rural taxi passenger volume in the base month is calculated based on the intercity and rural taxi passenger volume range, wherein the intercity and rural taxi passenger volume in the base month includes the intercity and rural cruising bus passenger volume in the base month and the intercity and rural online taxi passenger volume in the base month;

[0016] The sum of the base month's highway passenger volume, the base month's intercity and urban-rural public bus and tram passenger volume, and the base month's intercity and urban-rural taxi passenger volume is taken as the base month's commercial highway passenger volume.

[0017] Optionally, the preprocessing of the original expressway bus traffic data and the original national and provincial highway bus traffic data to obtain optimized expressway bus traffic data and optimized national and provincial highway bus traffic data includes:

[0018] The original expressway bus traffic data and the original national and provincial highway bus traffic data are normalized using a preset positive indicator formula to obtain the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data;

[0019] Among them, the preset positive indicator formula is:

[0020]

[0021] Where, X ij is the original bus traffic data on the jth evaluation index in the i-th month, min(X j) and max(X j ) are the minimum and maximum values ​​of the jth evaluation index in all months, X i ， jOptimize the bus traffic data for the jth evaluation index in the i-th month.

[0022] Optionally, after obtaining the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data, the method further includes:

[0023] Calculating the fluctuation value between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data;

[0024] Calculating a conflict value between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data;

[0025] Calculating a first product of the fluctuation value and the conflict value of the optimized highway bus traffic data, and using the first product as the information volume of the optimized highway bus traffic data; calculating a second product of the fluctuation value and the conflict value of the optimized national and provincial highway bus traffic data, and using the second product as the information volume of the optimized national and provincial highway bus traffic data;

[0026] According to the information volume of the optimized expressway bus traffic data and the information volume of the optimized national and provincial highway bus traffic data, a first fluctuation weight of the optimized expressway bus traffic data and a second fluctuation weight of the optimized national and provincial highway bus traffic data are obtained.

[0027] Optionally, the calculation of the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized expressway bus traffic data, and the optimized national and provincial highway bus traffic data using a fluctuation coefficient method includes:

[0028] Obtain the number of days in a base month, calculate the average daily passenger volume of scheduled buses in the base month based on the passenger volume of scheduled buses in the base month and the number of days in the base month, and calculate the average daily passenger volume of chartered tourist buses in the base month based on the passenger volume of chartered tourist buses in the base month and the number of days in the base month;

[0029] Calculate the average daily passenger volume of intercity and urban and rural public buses and trams in the base month based on the passenger volume of intercity and urban and rural public buses and trams in the base month and the number of days in the base month;

[0030] Calculate the average daily passenger volume of intercity and urban-rural cruising buses in the base month based on the intercity and urban-rural cruising bus passenger volume in the base month and the number of days in the base month, and obtain the average daily passenger volume of intercity and urban-rural online-hailing taxis in the base month through the online-hailing taxi supervision information interaction system;

[0031] According to the optimized highway bus traffic data, the optimized national and provincial highway bus traffic data, the first fluctuation weight, and the second fluctuation weight, respectively calculate a first scheduled bus fluctuation coefficient, a second tourist chartered bus fluctuation coefficient, a third intercity urban and rural public bus and tram fluctuation coefficient, and a fourth intercity urban and rural touring bus fluctuation coefficient;

[0032] Calculate the third product of the average daily passenger volume of scheduled buses in the base month and the fluctuation coefficient of the first scheduled buses, calculate the fourth product of the average daily passenger volume of tourist chartered buses in the base month and the fluctuation coefficient of the second tourist chartered buses, calculate the fifth product of the average daily passenger volume of intercity and urban and rural public buses and trams in the base month and the third fluctuation coefficient of intercity and urban and rural public buses and trams, calculate the sixth product of the average daily passenger volume of intercity and urban and rural cruising cars in the base month and the fourth fluctuation coefficient of intercity and urban and rural cruising cars, and take the sum of the third product, the fourth product, the fifth product, the sixth product and the average daily passenger volume of intercity and urban and rural online taxis in the base month as the initial daily commercial highway passenger volume.

[0033] Optionally, the website attendance data includes the number of tickets sold on holidays, the number of tickets sold on non-holidays, and the total number of seats. Calculating the key holiday adjustment coefficient based on the website attendance data includes:

[0034] The quotient of the number of tickets sold during holidays and the total number of seats is used as the holiday attendance rate, and the quotient of the number of tickets sold during non-holidays and the total number of seats is used as the non-holiday attendance rate;

[0035] The average value of the non-holiday attendance rate is calculated, and the quotient of the holiday attendance rate and the average value of the non-holiday attendance rate is used as the key holiday adjustment coefficient.

[0036] Optionally, after obtaining the final daily commercial highway passenger volume, the method further includes:

[0037] Obtaining the actual monthly commercial highway passenger volume and the number of days in the month, and calculating the theoretical monthly commercial highway passenger volume based on the number of days in the month and the final daily commercial highway passenger volume;

[0038] Determining whether the error between the theoretical monthly commercial highway passenger volume and the actual monthly commercial highway passenger volume is greater than a preset error threshold;

[0039] If the error between the theoretical monthly commercial highway passenger volume and the actual monthly commercial highway passenger volume is greater than the preset error threshold, the abnormal influencing factors are determined and the abnormal influencing factors are adjusted until the error between the theoretical monthly commercial highway passenger volume and the actual monthly commercial highway passenger volume is less than or equal to the preset error threshold.

[0040] In a second aspect, an embodiment of the present disclosure provides a device for monitoring daily passenger volume on commercial highways, the device comprising:

[0041] An acquisition module is used to obtain the range of highway transport passenger volume, the range of inter-city and urban-rural public bus and tram passenger volume, and the range of inter-city and urban-rural taxi passenger volume;

[0042] A first calculation module is used to calculate the base month commercial highway passenger volume based on the highway transport passenger volume range, the inter-city and urban-rural public bus and tram passenger volume range, and the inter-city and urban-rural taxi passenger volume range;

[0043] A preprocessing module is used to obtain original highway bus traffic data and original national and provincial highway bus traffic data, and preprocess the original highway bus traffic data and the original national and provincial highway bus traffic data to obtain optimized highway bus traffic data and optimized national and provincial highway bus traffic data;

[0044] A second calculation module is configured to calculate the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized highway bus traffic data, and the optimized national and provincial highway bus traffic data using a fluctuation coefficient method;

[0045] The correction module is used to collect website attendance data, calculate the key holiday adjustment coefficient based on the website attendance data, and correct the initial daily commercial highway passenger volume according to the key holiday adjustment coefficient to obtain the final daily commercial highway passenger volume.

[0046] In a third aspect, a computer device is provided in an embodiment of the present disclosure, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the daily monitoring method for commercial highway passenger volume described in the first aspect when executing the computer program.

[0047] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the daily monitoring method for commercial highway passenger volume described in the first aspect are implemented.

[0048] Beneficial effects of this application:

[0049] The daily monitoring method for commercial highway passenger volume provided in the embodiment of the present application integrates multiple data sources and calculates the daily commercial highway passenger volume using the fluctuation coefficient method, thereby improving the monitoring accuracy and data reliability.

[0050] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort. Similar components are numbered similarly in the various drawings.

[0052] Figure 1 A flowchart of a method for daily monitoring of commercial highway passenger volume provided by an embodiment of the present application is shown;

[0053] Figure 2 A flowchart of another method for daily monitoring of commercial highway passenger volume provided by an embodiment of the present application is shown;

[0054] Figure 3 A schematic structural diagram of a daily monitoring device for commercial highway passenger volume provided by an embodiment of the present application is shown;

[0055] Figure 4 A structural diagram of a computer device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0056] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0057] Example 1

[0058] like Figure 1 FIG. 1 is a flow chart of a method for daily monitoring of commercial highway passenger volume in an embodiment of the present application. The method for daily monitoring of commercial highway passenger volume provided in an embodiment of the present application includes the following steps:

[0059] Step S110, obtaining the range of highway transport passenger volume, the range of inter-city and urban-rural public bus and tram passenger volume, and the range of inter-city and urban-rural taxi passenger volume.

[0060] It should be noted that before obtaining the range of each transportation volume, it is necessary to first divide all district and county-level administrative units into urban and non-urban areas: 1) Clarify the scope of urban areas: urban areas refer to the urban districts and county towns of prefecture-level cities and above in the country, and the remaining areas are defined as non-urban areas. For each municipality directly under the central government and each city with a regional city, the urban area refers to the central urban area designated in its urban planning, and the remaining areas are non-urban areas; 2) Clarify the scope of county towns: city refers to the town, township or street office area where the county government is located. According to this definition, the street area in each county is identified as the county town of the county. If there is no street but only town in the county's statistical division code and urban-rural division code, the area belonging to the Chengguan Town or the town that ranks first in the administrative division code of the county is defined as the county town.

[0061] Furthermore, the scope of highway transport passenger volume, the scope of inter-city and urban-rural public bus and tram passenger volume, and the scope of inter-city and urban-rural taxi passenger volume are clarified: 1) Clarify the scope of highway transport passenger volume: The scope of highway transport passenger volume refers to the passenger volume actually transported by highway transport enterprises and other units or individuals organized by them within a certain period of time; 2) The passenger volume of public buses and taxis between different provincial administrative regions is regarded as cross-provincial passenger volume, travel between different prefecture-level administrative regions is regarded as cross-city passenger volume, and travel from urban areas to non-urban areas and from non-urban areas to non-urban areas within the same prefecture-level administrative region is regarded as urban-rural passenger volume. The above three situations are included in the scope of inter-city and urban-rural public bus and tram passenger volume and the scope of inter-city and urban-rural taxi passenger volume (travel from urban area to urban area within the same prefecture-level administrative region is regarded as urban road travel, which belongs to the city's public bus and taxi passenger volume and does not belong to the inter-city and urban-rural scope).

[0062] The above method provides strong data support for the subsequent calculation of highway transport passenger volume, intercity and urban and rural public bus and tram passenger volume, and intercity and urban and rural taxi passenger volume by clarifying the scope of highway transport passenger volume, intercity and urban and rural public bus and tram passenger volume, and intercity and urban and rural taxi passenger volume. It comprehensively reflects the actual situation of commercial highway passenger transport and improves the accuracy of monitoring.

[0063] Step S120, calculating the base month's commercial highway passenger volume based on the highway transport passenger volume range, the inter-city and urban-rural public bus and tram passenger volume range, and the inter-city and urban-rural taxi passenger volume range.

[0064] In this example, commercial highway passenger volume refers to the total commercial passenger volume carried out by road transport during a given period, provided by various types of road transport enterprises (e.g., passenger and freight transport enterprises). Non-commercial highway passenger volume refers to passenger volume carried by non-commercial vehicles that is not primarily for remuneration. In this example, according to the passenger transport statistics reform work plan, commercial highway passenger volume is composed of three components: highway passenger volume, intercity and urban / rural public bus and tram passenger volume, and intercity and urban / rural taxi passenger volume.

[0065] First, calculate the highway passenger volume based on the highway passenger volume range, where the highway passenger volume includes the passenger volume of scheduled buses and the passenger volume of tourist chartered buses:

[0066] 1) The passenger volume of scheduled buses is usually divided into the following four levels: ① The passenger volume of first-level scheduled buses: refers to the passenger volume generated by highway passenger bus routes connecting large cities or between large cities and medium-sized cities, as well as those with more passing places (generally small cities, medium-sized cities, and suburbs of large cities) or longer mileage, and more stable or dense passenger sources; ② The passenger volume of second-level scheduled buses: refers to the passenger volume generated by highway passenger bus routes connecting medium-sized cities or between large cities and counties, county-level cities, as well as those with fewer passing places or shorter mileage, and more stable passenger sources; ③ The passenger volume of third-level scheduled buses: refers to the passenger volume generated by highway passenger bus routes connecting counties and counties, county-level cities, county towns and larger towns, larger towns or larger factories and mines, as well as those with fewer passing places, shorter mileage, and more stable passenger sources; ④ The passenger volume of fourth-level scheduled buses: refers to the passenger volume generated by highway passenger bus routes connecting townships and townships, townships and administrative villages, and administrative villages and administrative villages;

[0067] 2) Tourist charter passenger volume: refers to the passenger volume generated by the special transportation services provided by tourist charter companies to meet the transportation needs of tourists during their travels.

[0068] Understandably, in another optional implementation, depending on the data collection target, highway passenger volume can also be composed of two parts: enterprise highway passenger volume and individual highway passenger volume: 1) Enterprise highway passenger volume: All passenger transport enterprises engaged in passenger transport business submit their own passenger volume monthly through the online direct reporting system; 2) Individual highway passenger volume: This is calculated by multiplying the average passenger volume per seat of similar enterprises' vehicles by the number of seats per vehicle. Similar enterprises can be prioritized for consideration: highway passenger transport enterprises with similar frequency of departures and occupancy rates. The average passenger volume per seat of similar enterprises' vehicles is calculated by dividing the total passenger volume completed by the total number of seats in the enterprise's vehicles during the reporting period, with preference given to passenger transport enterprises using online ticketing.

[0069] Secondly, the intercity and urban and rural public bus and tram passenger volume is calculated based on the intercity and urban and rural public bus and tram passenger volume range. The specific calculation method is selected from the following three methods (only as examples and not limited to the following three methods) according to the difficulty of data collection.

[0070] 1) Scenario 1: For enterprises that have detailed data on passenger boarding and alighting stations, the data is divided into intercity and urban / rural data based on whether the boarding and alighting stations are located within the jurisdiction of the same prefecture-level administrative region or the same county, and the data is included in the urban public bus and tram passenger volume; the rest are included in the intercity and urban / rural public bus and tram passenger volume;

[0071] 2) Scenario 2: For companies that only have detailed data on passenger boarding stations, the data is divided into intercity and urban-rural bus passenger volume based on whether the boarding station is located within the city or county. Boarding stations within the city or county are included in the urban public bus and tram passenger volume, while the rest are included in the intercity and urban-rural public bus and tram passenger volume;

[0072] 3) Scenario 3: The company does not have detailed data on passengers getting on and off the bus, and splits the data based on the location of the bus stations on the operating routes. The proportion of the number of stations within the municipal district or county town is multiplied by the public bus and tram passenger volume, and the resulting value is included in the public bus and tram passenger volume within the city, and the rest is included in the intercity and urban-rural public bus and tram passenger volume.

[0073] Next, the inter-city and urban-rural taxi passenger volume is calculated based on the inter-city and urban-rural taxi passenger volume range. The inter-city and urban-rural taxi passenger volume consists of two parts: the inter-city and urban-rural cruising car passenger volume and the inter-city and urban-rural online taxi passenger volume:

[0074] 1) Intercity and rural cruising bus passenger volume: ① Collect cruising bus order data during the reporting period through each municipal transportation authority; ② Calculate the average occupancy rate based on the occupancy rate of cruising taxis in the region; ③ Multiply the order data by the occupancy rate to obtain the total cruising bus passenger volume; ④ Decompose the total cruising taxi passenger volume in equal proportions based on the split of online ride-hailing services to obtain the intercity and rural cruising taxi passenger volume;

[0075] 2) Intercity and urban-rural online taxi passenger volume: ① Based on the online taxi regulatory information interaction system, use big data technology to sort out the information of each online taxi order, including the order starting and ending locations. When the order starting and ending information is missing, it is supplemented according to the longitude and latitude trajectory; ② According to the online taxi occupancy rate in the region, the average occupancy rate is obtained; ③ The order data is multiplied by the occupancy rate to obtain the total online taxi passenger volume; ④ For boarding and alighting locations within the same prefecture-level administrative region or the same county, it is included in the urban online taxi passenger volume, and the rest is included in the intercity and urban-rural online taxi passenger volume.

[0076] Understandably, considering the different difficulties and timeliness of relevant data collection, based on actual conditions, this embodiment recommends selecting T-2 as the base month for daily monitoring of commercial highway passenger volume. For example, if the National Day Golden Week is monitored, the commercial highway passenger volume in August is used as the base month.

[0077] Calculate the values ​​of the above passenger volumes in the base month, and add the values ​​of the base month's highway transport passenger volume, the base month's intercity and urban and rural public bus and tram passenger volume, and the base month's intercity and urban and rural taxi passenger volume to obtain the base month's commercial highway passenger volume.

[0078] By integrating multiple data sources, this method avoids the difficulty of manual daily statistical compilation, reduces human interference, and reduces the burden on personnel. It also maximizes the use of passenger transport administrative records, providing a more comprehensive picture of the actual commercial highway passenger transport volume. This multi-source data integration not only improves the richness and accuracy of the data but also enhances the effectiveness of monitoring.

[0079] Step S130, obtaining original highway bus traffic data and original national and provincial highway bus traffic data, and preprocessing the original highway bus traffic data and original national and provincial highway bus traffic data to obtain optimized highway bus traffic data and optimized national and provincial highway bus traffic data.

[0080] Specifically, since commercial highway passenger volume is mainly generated by buses, we first obtain the original highway bus traffic data from the highway traffic big data system, including but not limited to: the summary number of cross-provincial highway bus traffic, the summary number of cross-city highway bus traffic, the summary number of cross-county highway bus traffic within the city, the summary number of county highway bus traffic, the summary number of tourist chartered vehicles traveling on the highway, the summary number of public buses and trams traveling on the highway, and the summary number of cruising taxis traveling on the highway.

[0081] Similarly, based on the national and provincial highway traffic volume survey big data system, original national and provincial highway bus traffic data is obtained, including but not limited to the average cross-sectional traffic volume data of buses traveling on national and provincial highways with observation stations across the country.

[0082] It should be noted that after collecting the original highway bus traffic data and the original national and provincial highway bus traffic data, the original data matrix X is first constructed:

[0083]

[0084] In the formula, m represents the evaluation object, and n represents the evaluation index. In this embodiment, m represents the month involved in the calculation, and n represents the national, provincial, or expressway. For example, X 11 It represents the original highway bus traffic data in January, X 22 It represents the original national and provincial highway bus traffic data in February.

[0085] Since the number of buses on highways and national and provincial roads are both positive indicators for commercial highway passenger volume, we then use the preset positive indicator formula to standardize the original highway bus traffic data and the original national and provincial road bus traffic data to obtain the standardized optimized highway bus traffic data and the optimized national and provincial road bus traffic data. The formula is as follows:

[0086]

[0087] Where, X ij is the original bus traffic data on the jth evaluation index (highway or national and provincial road) in the i-th month, min(X j) and max(X j ) are the minimum and maximum values ​​of the jth evaluation index in all months, X i ， j Optimize the bus traffic data for the jth evaluation index in the i-th month.

[0088] In a preferred embodiment, Figure 2 As shown, after step S130, the following steps are further included:

[0089] Step S131, calculating the fluctuation value between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data;

[0090] Step S132, calculating the conflict value between the optimized highway bus traffic data and the optimized national and provincial highway bus traffic data;

[0091] Step S133, calculating a first product of the fluctuation value and the conflict value of the optimized highway bus traffic data, using the first product as the information content of the optimized highway bus traffic data, calculating a second product of the fluctuation value and the conflict value of the optimized national and provincial highway bus traffic data, using the second product as the information content of the optimized national and provincial highway bus traffic data;

[0092] Step S134, obtaining a first fluctuation weight for optimizing the expressway bus traffic data and a second fluctuation weight for optimizing the national and provincial highway bus traffic data based on the information volume of the optimized expressway bus traffic data and the information volume of the optimized national and provincial highway bus traffic data.

[0093] Understandably, after obtaining optimized data on large-scale passenger bus traffic on expressways and national and provincial highways, it is necessary to analyze the degree of impact of the two on various types of commercial passenger vehicles. This embodiment first uses a two-round Delphi method from a subjective perspective, targeting experts in research related to national and provincial highways and expressways, as well as representatives of commercial highway passenger operating companies such as buses and taxis: the first survey is mainly conducted by experts with a long history of research in related fields such as national and provincial highways and expressways, and the main content of the survey is the proportion and number of commercial highway passenger vehicles on national and provincial highways and expressways; the second survey is mainly conducted by companies that own intercity and urban and rural buses and companies involved in intercity and urban and rural taxi operations, and the main content of the survey is whether the company's passenger traffic mainly occurs on expressways or national and provincial highways. Based on the results of the two questionnaires, it is subjectively judged that national and provincial highways have a greater impact on commercial highway passenger traffic.

[0094] To verify the above results, we used the CRITIC (Criteria Importance Through Intercrieria Correlation) method to verify the accuracy of the above results from an objective perspective and calculated the specific weight ratios according to the following steps:

[0095] 1) Calculate the fluctuation value between the optimized highway bus traffic data and the optimized national and provincial highway bus traffic data. Volatility is used to measure the degree of dispersion of each evaluation indicator. The formula is as follows:

[0096]

[0097] Where, represents the average of the bus traffic data on national, provincial or expressways, n represents the number of months (number of evaluation objects), S j Represents the fluctuation value of each evaluation indicator and other evaluation indicators;

[0098] 2) Calculate the conflict value between the optimized highway bus traffic data and the optimized national and provincial highway bus traffic data. The formula is as follows:

[0099]

[0100] Where r ij Represents the elements of the correlation coefficient matrix of each evaluation index, A j Represents the conflict value between each evaluation indicator and other evaluation indicators;

[0101] 3) Calculate the information content of each evaluation indicator. The formula is as follows:

[0102] C j =S j ×A j

[0103] Where C j Represents the amount of information for each evaluation indicator;

[0104] 4) Calculate the fluctuation weights of optimized highway bus traffic data and optimized national and provincial highway bus traffic data using the following formula:

[0105]

[0106] Where W j Represents the fluctuation weight of each evaluation indicator.

[0107] It should be noted that the weights of national, provincial and expressways calculated by the CRITIC method are highly consistent with the Delphi method and are consistent with the logic.

[0108] This method utilizes big data processing and analysis, rationally cleans data, and uses highway and national and provincial highway data. This not only improves monitoring accuracy but also reduces the impact of human factors on the results. The Delphi and CRITIC methods, using subjective and objective methods, respectively, determine the fluctuation weights of highway and national and provincial highway traffic data, laying an accurate data foundation for subsequent calculations using the fluctuation coefficient method.

[0109] Step S140, calculating the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, optimized highway bus traffic data, and optimized national and provincial highway bus traffic data, and using the fluctuation coefficient method.

[0110] Understandably, the fluctuation coefficient method uses equivalent data from a certain historical period (month T-2) as the base month. The changes in one or more factors influencing passenger volume between the base month and the daily monitoring period are used as time series variation characteristics. Substituting these into the formula yields the average daily passenger volume. When multiple factors are selected as fluctuation coefficients, it is necessary to determine the weights assigned to the different fluctuation coefficients.

[0111] Furthermore, the number of days in the base month is obtained, and the average daily passenger volume of the base month's scheduled bus is calculated based on the passenger volume of the base month's scheduled bus and the number of days in the base month, that is: the average daily passenger volume of the base month's Class 1 scheduled bus = the passenger volume of the base month's Class 1 scheduled bus / the number of days in the base month; the average daily passenger volume of the base month's Class 2 scheduled bus = the passenger volume of the base month's Class 2 scheduled bus / the number of days in the base month; the average daily passenger volume of the base month's Class 3 scheduled bus = the passenger volume of the base month's Class 3 scheduled bus / the number of days in the base month; the average daily passenger volume of the base month's Class 4 scheduled bus = the passenger volume of the base month's Class 4 scheduled bus / the number of days in the base month.

[0112] The average daily passenger volume of chartered tourist buses in the base month is calculated based on the passenger volume of chartered tourist buses in the base month and the number of days in the base month, that is: the average daily passenger volume of chartered tourist buses in the base month = the passenger volume of chartered tourist buses in the base month / the number of days in the base month.

[0113] The average daily passenger volume of intercity and urban-rural public buses and trams in the base month is calculated based on the intercity and urban-rural public bus and tram passenger volume in the base month and the number of days in the base month, that is: the average daily passenger volume of intercity and urban-rural public buses and trams in the base month = the intercity and urban-rural public bus and tram passenger volume in the base month / the number of days in the base month.

[0114] The average daily passenger volume of intercity and rural cruising buses in the base month is calculated based on the passenger volume of intercity and rural cruising buses in the base month and the number of days in the base month, that is: the average daily passenger volume of intercity and rural cruising buses in the base month = the passenger volume of intercity and rural cruising buses in the base month / the number of days in the base month.

[0115] It should be noted that the average daily passenger volume of intercity and urban and rural online taxis in the base month can be directly calculated through the big data of the online taxi regulatory information interaction system.

[0116] Furthermore, the fluctuation coefficient method is used to separately fluctuate different passenger transport modes:

[0117] 1) Fluctuation coefficient of first-class bus routes: Fluctuation coefficient of first-class bus routes = inter-provincial expressway bus volume in the current month / inter-provincial expressway bus volume in the base month × first fluctuation weight + national and provincial highway bus volume in the current month / national and provincial highway bus volume in the base month × second fluctuation weight; Fluctuation coefficient of second-class bus routes = inter-city expressway bus volume in the current month / inter-city expressway bus volume in the base month × first fluctuation weight + national and provincial highway bus volume in the current month / national and provincial highway bus volume in the base month × second fluctuation weight; Fluctuation coefficient of third-class bus routes = inter-county expressway bus volume in the current month / inter-county expressway bus volume in the base month × first fluctuation weight + national and provincial highway bus volume in the current month / national and provincial highway bus volume in the base month × second fluctuation weight; Fluctuation coefficient of fourth-class bus routes = intra-county expressway bus volume in the current month / intra-county expressway bus volume in the base month × first fluctuation weight + national and provincial highway bus volume in the current month / national and provincial highway bus volume in the base month × second fluctuation weight;

[0118] 2) Second tourist charter bus fluctuation coefficient = the volume of tourist charter buses on the highway in the current month / the volume of tourist charter buses on the highway in the base month × the first fluctuation weight + the volume of large passenger buses on national and provincial highways in the current month / the volume of large passenger buses on national and provincial highways in the base month × the second fluctuation weight;

[0119] 3) The third intercity and rural public bus and tram fluctuation coefficient = the volume of intercity and rural public buses and trams on highways in the current month / the volume of intercity and rural public buses and trams on highways in the base month × the first fluctuation weight + the volume of national and provincial highway buses in the current month / the volume of national and provincial highway buses in the base month × the second fluctuation weight;

[0120] 4) The fourth intercity and rural cruising car fluctuation coefficient = the volume of intercity and rural cruising cars on highways in the current month / the volume of intercity and rural cruising cars on highways in the base month × the first fluctuation weight + the volume of taxis on national and provincial highways in the current month / the volume of taxis on national and provincial highways in the base month × the second fluctuation weight.

[0121] Based on the above data, the initial daily commercial highway passenger volume is calculated, namely: Initial daily commercial highway passenger volume = Average daily passenger volume of Class I scheduled buses in the base month × Fluctuation coefficient of Class I scheduled buses + Average daily passenger volume of Class II scheduled buses in the base month × Fluctuation coefficient of Class II scheduled buses + Average daily passenger volume of Class III scheduled buses in the base month × Fluctuation coefficient of Class III scheduled buses + Average daily passenger volume of Class IV scheduled buses in the base month × Fluctuation coefficient of Class IV scheduled buses + Average daily passenger volume of tourist chartered buses in the base month × Fluctuation coefficient of the second tourist chartered bus + Average daily passenger volume of intercity and urban-rural public buses and trams in the base month × Fluctuation coefficient of the third intercity and urban-rural public buses and trams + Average daily passenger volume of intercity and urban-rural cruising cars in the base month × Fluctuation coefficient of the fourth intercity and urban-rural cruising cars + Average daily passenger volume of intercity and urban-rural online taxis in the base month

[0122] This method, through a "base period + fluctuation" approach, ensures consistency between daily and monthly passenger volume data, reducing the problem of mismatched results due to significant differences in data sources. Furthermore, using multi-source big data as a fluctuation coefficient, passenger volume results for the previous day are available each morning, improving the timeliness and stability of data collection. This provides managers and the public with more timely and accurate passenger traffic monitoring services during key holidays, better reflecting the actual development of road transportation and supporting GDP accounting and industry management decisions.

[0123] Step S150: collect website attendance data, calculate key holiday adjustment coefficients based on the website attendance data, and correct the initial daily commercial highway passenger volume based on the key holiday adjustment coefficients to obtain the final daily commercial highway passenger volume.

[0124] Understandably, first, collect occupancy data from websites (e.g., 100 Cities and 100 Stations) during holidays (such as Spring Festival and National Day) and non-holiday periods, including ticket sales and seat data, i.e., daily ticket sales and total seat counts, and clean the data to remove outliers and missing values. Regular bus occupancy data can be obtained through the "Road Passenger Transport Electronic Ticketing System," chartered tourist bus occupancy data can be obtained through the "Provincial and Municipal Chartered Bus Passenger Transport Management Information Filing System," intercity and urban / rural public bus occupancy data can be obtained through the "Typical Public Bus and Tram Passenger Transport Enterprise Dispatching and Management System," and intercity and urban / rural taxi occupancy data can be obtained through the "Online Car-hailing Supervision Information Interaction System" and the "One-Form Online Direct Reporting System."

[0125] Next, the calculation formula for the attendance rate is: Attendance rate = number of tickets sold / total number of seats. Therefore, the quotient of the number of tickets sold on holidays and the total number of seats is used as the holiday attendance rate, and the number of tickets sold on non-holidays and the total number of seats is used as the non-holiday attendance rate. Attendance rate = number of tickets sold / total number of seats.

[0126] In this embodiment, the difference between holiday attendance rate and non-holiday attendance rate can be analyzed, that is, the mean, median, standard deviation and other statistics of holiday attendance rate and non-holiday attendance rate are calculated respectively, and charts (such as box plots and histograms) are used to intuitively display the distribution of holiday and non-holiday attendance rates.

[0127] Finally, calculate the key holiday adjustment coefficient. The key holiday adjustment coefficient is intended to reflect the changes in attendance during holidays relative to non-holidays. The formula is as follows: key holiday adjustment coefficient = holiday attendance rate / average non-holiday attendance rate.

[0128] The key holiday adjustment coefficient is applied to the initial daily commercial highway passenger volume. For example, the correction formula could be: Final daily commercial highway passenger volume = Initial daily commercial highway passenger volume × Key Holiday Adjustment Coefficient. This correction process aims to more accurately reflect the actual highway passenger volume during holidays, as passenger volume during holidays is often affected by a variety of factors, such as increased travel demand and traffic congestion.

[0129] It should be noted that the above correction formula is only used as a reference. The specific correction method can be determined according to actual conditions, and the embodiments of the present application do not limit this.

[0130] This method can more comprehensively consider the impact of holidays on highway passenger volume, thereby generating more accurate and reliable daily commercial highway passenger volume data. This is of great reference value for highway passenger transport companies' operational decisions, government departments' traffic management, and the public's travel choices.

[0131] In an optional implementation manner, after step S150, the following steps are further included:

[0132] After calculating the final daily commercial highway passenger volume, calculate the product of the number of days in the month and the final daily commercial highway passenger volume to obtain the theoretical monthly commercial highway passenger volume, and then obtain the actual monthly commercial highway passenger volume from the commercial highway passenger volume big data system.

[0133] Further analyze the error between the theoretical and actual monthly commercial highway passenger volume and verify whether the error is greater than the preset error threshold. If it is less than or equal to the preset error threshold, there is no need to optimize the entire process. If it is greater than the preset error threshold, all indicators and parameters in the above process are checked one by one, analyzing the reasons for the increase in data error, identifying abnormal influencing factors, and adjusting these abnormal influencing factors until the error between the theoretical and actual monthly commercial highway passenger volume is less than or equal to the preset error threshold.

[0134] The above methods help to discover deviations or errors in the data, so that timely corrections can be made and the reliability and accuracy of the data can be improved.

[0135] The daily monitoring method for commercial highway passenger volume provided in the embodiment of the present application integrates multiple data sources and calculates the daily commercial highway passenger volume using the fluctuation coefficient method, thereby improving the monitoring accuracy and data reliability.

[0136] Example 2

[0137] like Figure 3FIG. 1 is a schematic diagram of a daily monitoring device 300 for commercial highway passenger traffic in an embodiment of the present application, which includes:

[0138] An acquisition module 310 is used to acquire the range of highway transport passenger volume, the range of inter-city and urban-rural public bus and tram passenger volume, and the range of inter-city and urban-rural taxi passenger volume;

[0139] The first calculation module 320 is used to calculate the base month's commercial highway passenger volume based on the highway passenger volume range, the inter-city and urban-rural public bus and tram passenger volume range, and the inter-city and urban-rural taxi passenger volume range;

[0140] A preprocessing module 330 is used to obtain original highway bus traffic data and original national and provincial highway bus traffic data, and preprocess the original highway bus traffic data and original national and provincial highway bus traffic data to obtain optimized highway bus traffic data and optimized national and provincial highway bus traffic data;

[0141] The second calculation module 340 is used to calculate the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized highway bus traffic data, and the optimized national and provincial highway bus traffic data, and using the fluctuation coefficient method;

[0142] The correction module 350 is used to collect website attendance data, calculate the key holiday adjustment coefficient based on the website attendance data, and correct the initial daily commercial highway passenger volume based on the key holiday adjustment coefficient to obtain the final daily commercial highway passenger volume.

[0143] The daily monitoring device for commercial highway passenger volume provided in the embodiment of the present application integrates multiple data sources and calculates the daily commercial highway passenger volume using the fluctuation coefficient method, thereby improving the monitoring accuracy and data reliability.

[0144] Example 3

[0145] The present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0146] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with a memory 41, a processor 42, and a network interface 43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0147] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0148] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or D slot compatibility test memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for the slot compatibility test method. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0149] In some embodiments, the processor 42 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other commercial highway passenger volume daily monitoring chip. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions or process data stored in the memory 41, such as computer-readable instructions for executing the slot compatibility testing method.

[0150] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0151] The computer device provided in this embodiment can execute the above-mentioned daily monitoring method for commercial highway passenger volume.

[0152] Example 4

[0153] This embodiment further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for daily monitoring of commercial highway passenger volume in the embodiment are implemented.

[0154] In this embodiment, the computer-readable storage medium includes flash memory, hard disks, multimedia cards, card-type memories (e.g., SD or DX memories), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disks, optical disks, etc. In some embodiments, the computer-readable storage medium may be an internal storage unit of a computer device, such as the hard disk or memory of the computer device. In other embodiments, the computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk equipped with the computer device, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Of course, the computer-readable storage medium may also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the computer-readable storage medium is generally used to store the operating system and various application software installed on the computer device. In addition, the computer-readable storage medium may also be used to temporarily store various types of data that have been output or are about to be output.

[0155] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should be noted that each box in the structure diagram and / or flowchart, and the combination of boxes in the structure diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0156] In addition, the functional modules or units in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0157] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium can be a non-volatile storage medium or a volatile storage medium. For example, the storage medium can be: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and other media that can store program codes.

[0158] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered by the scope of protection of the present invention.

Claims

1. A method for daily monitoring of commercial highway passenger volume, characterized in that: The method comprises: Obtain the range of highway transport passenger volume, inter-city and urban-rural public bus and tram passenger volume, and inter-city and urban-rural taxi passenger volume; Calculate the base month's commercial highway passenger volume based on the highway passenger volume range, the inter-city and urban-rural public bus and tram passenger volume range, and the inter-city and urban-rural taxi passenger volume range; Obtaining original expressway bus traffic data and original national and provincial highway bus traffic data, and preprocessing the original expressway bus traffic data and the original national and provincial highway bus traffic data to obtain optimized expressway bus traffic data and optimized national and provincial highway bus traffic data; Calculate the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized highway bus traffic data, and the optimized national and provincial highway bus traffic data using the fluctuation coefficient method; Collecting website attendance data, calculating a key holiday adjustment coefficient based on the website attendance data, and revising the initial daily commercial highway passenger volume based on the key holiday adjustment coefficient to obtain a final daily commercial highway passenger volume, wherein the key holiday adjustment coefficient reflects the change in attendance during holidays relative to non-holiday attendance; The calculation of the base month's commercial highway passenger volume based on the highway passenger volume range, the intercity and urban-rural public bus and tram passenger volume range, and the intercity and urban-rural taxi passenger volume range includes: Calculate the base month highway transport passenger volume according to the highway transport passenger volume range, wherein the base month highway transport passenger volume includes the base month regular bus passenger volume and the base month tourist chartered bus passenger volume; Calculate the base month's intercity and urban and rural public bus and tram passenger volume based on the intercity and urban and rural public bus and tram passenger volume range; The intercity and rural taxi passenger volume in the base month is calculated based on the intercity and rural taxi passenger volume range, wherein the intercity and rural taxi passenger volume in the base month includes the intercity and rural cruising bus passenger volume in the base month and the intercity and rural online taxi passenger volume in the base month; The sum of the base month's highway passenger volume, the base month's intercity and urban and rural public bus and tram passenger volume, and the base month's intercity and urban and rural taxi passenger volume is taken as the base month's commercial highway passenger volume; After obtaining the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data, the method further includes: Calculating a fluctuation value between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data, wherein the fluctuation value represents a degree of dispersion between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data; Calculating a conflict value between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data, wherein the conflict value represents a degree of non-correlation between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data; Calculating a first product of a fluctuation value and a conflict value of the optimized highway bus traffic data, using the first product as the information volume of the optimized highway bus traffic data, and obtaining a first fluctuation weight of the optimized highway bus traffic data according to the information volume of the optimized highway bus traffic data; Calculating a second product of the fluctuation value and the conflict value of the optimized national and provincial highway bus traffic data, using the second product as the information volume of the optimized national and provincial highway bus traffic data, and obtaining a second fluctuation weight of the optimized national and provincial highway bus traffic data according to the information volume of the optimized national and provincial highway bus traffic data; The calculation of the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized expressway bus traffic data, and the optimized national and provincial highway bus traffic data using the fluctuation coefficient method includes: Obtain the number of days in a base month, calculate the average daily passenger volume of scheduled buses in the base month based on the passenger volume of scheduled buses in the base month and the number of days in the base month, and calculate the average daily passenger volume of chartered tourist buses in the base month based on the passenger volume of chartered tourist buses in the base month and the number of days in the base month; Calculate the average daily passenger volume of intercity and urban and rural public buses and trams in the base month based on the passenger volume of intercity and urban and rural public buses and trams in the base month and the number of days in the base month; Calculate the average daily passenger volume of intercity and urban-rural cruising buses in the base month based on the intercity and urban-rural cruising bus passenger volume in the base month and the number of days in the base month, and obtain the average daily passenger volume of intercity and urban-rural online-hailing taxis in the base month through the online-hailing taxi supervision information interaction system; According to the optimized highway bus traffic data, the optimized national and provincial highway bus traffic data, the first fluctuation weight, and the second fluctuation weight, respectively calculate a first scheduled bus fluctuation coefficient, a second tourist chartered bus fluctuation coefficient, a third intercity urban and rural public bus and tram fluctuation coefficient, and a fourth intercity urban and rural touring bus fluctuation coefficient; Calculate the third product of the average daily passenger volume of scheduled buses in the base month and the fluctuation coefficient of the first scheduled buses, calculate the fourth product of the average daily passenger volume of tourist chartered buses in the base month and the fluctuation coefficient of the second tourist chartered buses, calculate the fifth product of the average daily passenger volume of intercity and urban and rural public buses and trams in the base month and the third fluctuation coefficient of intercity and urban and rural public buses and trams, calculate the sixth product of the average daily passenger volume of intercity and urban and rural cruising cars in the base month and the fourth fluctuation coefficient of intercity and urban and rural cruising cars, and take the sum of the third product, the fourth product, the fifth product, the sixth product and the average daily passenger volume of intercity and urban and rural online taxis in the base month as the initial daily commercial highway passenger volume.

2. The method for daily monitoring of commercial highway passenger volume according to claim 1, characterized in that: The preprocessing of the original expressway bus traffic data and the original national and provincial highway bus traffic data to obtain optimized expressway bus traffic data and optimized national and provincial highway bus traffic data includes: The original expressway bus traffic data and the original national and provincial highway bus traffic data are normalized using a preset positive indicator formula to obtain the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data; Among them, the preset positive indicator formula is: Where, For the In the month The original bus traffic data on the evaluation indicators, and Respectively The minimum and maximum values ​​of the evaluation indicators in all months, For the In the month Optimize bus traffic data based on three evaluation indicators.

3. The method for daily monitoring of commercial highway passenger volume according to claim 1, characterized in that: The website attendance data includes the number of tickets sold on holidays, the number of tickets sold on non-holidays, and the total number of seats. The calculation of the key holiday adjustment coefficient based on the website attendance data includes: The quotient of the number of tickets sold on holidays and the total number of seats is used as the holiday attendance rate, and the quotient of the number of tickets sold on non-holidays and the total number of seats is used as the non-holiday attendance rate; The average value of the non-holiday attendance rate is calculated, and the quotient of the holiday attendance rate and the average value of the non-holiday attendance rate is used as the key holiday adjustment coefficient.

4. The method for daily monitoring of commercial highway passenger volume according to claim 1, characterized in that: After obtaining the final daily commercial highway passenger volume, the following is also included: Obtaining the actual monthly commercial highway passenger volume and the number of days in the month, and calculating the theoretical monthly commercial highway passenger volume based on the number of days in the month and the final daily commercial highway passenger volume; Determining whether the error between the theoretical monthly commercial highway passenger volume and the actual monthly commercial highway passenger volume is greater than a preset error threshold; If the error between the theoretical monthly commercial highway passenger volume and the actual monthly commercial highway passenger volume is greater than the preset error threshold, the abnormal influencing factors are determined and the abnormal influencing factors are adjusted until the error between the theoretical monthly commercial highway passenger volume and the actual monthly commercial highway passenger volume is less than or equal to the preset error threshold.

5. A daily monitoring device for commercial highway passenger traffic, characterized in that: The device comprises: An acquisition module is used to obtain the range of highway transport passenger volume, the range of inter-city and urban-rural public bus and tram passenger volume, and the range of inter-city and urban-rural taxi passenger volume; A first calculation module is used to calculate the base month commercial highway passenger volume based on the highway transport passenger volume range, the inter-city and urban-rural public bus and tram passenger volume range, and the inter-city and urban-rural taxi passenger volume range; A preprocessing module is used to obtain original highway bus traffic data and original national and provincial highway bus traffic data, and preprocess the original highway bus traffic data and the original national and provincial highway bus traffic data to obtain optimized highway bus traffic data and optimized national and provincial highway bus traffic data; A second calculation module is configured to calculate the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized highway bus traffic data, and the optimized national and provincial highway bus traffic data using a fluctuation coefficient method; a correction module, configured to collect website attendance data, calculate a key holiday adjustment coefficient based on the website attendance data, and correct the initial daily commercial highway passenger volume based on the key holiday adjustment coefficient to obtain a final daily commercial highway passenger volume, wherein the key holiday adjustment coefficient reflects the change in attendance rate during holidays relative to non-holiday attendance rate; The calculation of the base month's commercial highway passenger volume based on the highway passenger volume range, the intercity and urban-rural public bus and tram passenger volume range, and the intercity and urban-rural taxi passenger volume range includes: Calculate the base month highway transport passenger volume according to the highway transport passenger volume range, wherein the base month highway transport passenger volume includes the base month regular bus passenger volume and the base month tourist chartered bus passenger volume; Calculate the base month's intercity and urban and rural public bus and tram passenger volume based on the intercity and urban and rural public bus and tram passenger volume range; The intercity and rural taxi passenger volume in the base month is calculated based on the intercity and rural taxi passenger volume range, wherein the intercity and rural taxi passenger volume in the base month includes the intercity and rural cruising bus passenger volume in the base month and the intercity and rural online taxi passenger volume in the base month; The sum of the base month's highway passenger volume, the base month's intercity and urban and rural public bus and tram passenger volume, and the base month's intercity and urban and rural taxi passenger volume is taken as the base month's commercial highway passenger volume; After obtaining the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data, the method further includes: Calculating a fluctuation value between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data, wherein the fluctuation value represents a degree of dispersion between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data; Calculating a conflict value between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data, wherein the conflict value represents a degree of non-correlation between the optimized expressway bus traffic data and the optimized national and provincial highway bus traffic data; Calculating a first product of a fluctuation value and a conflict value of the optimized highway bus traffic data, using the first product as the information volume of the optimized highway bus traffic data, and obtaining a first fluctuation weight of the optimized highway bus traffic data according to the information volume of the optimized highway bus traffic data; Calculating a second product of the fluctuation value and the conflict value of the optimized national and provincial highway bus traffic data, using the second product as the information volume of the optimized national and provincial highway bus traffic data, and obtaining a second fluctuation weight of the optimized national and provincial highway bus traffic data according to the information volume of the optimized national and provincial highway bus traffic data; The calculation of the initial daily commercial highway passenger volume based on the base month commercial highway passenger volume, the optimized expressway bus traffic data, and the optimized national and provincial highway bus traffic data using the fluctuation coefficient method includes: Obtain the number of days in a base month, calculate the average daily passenger volume of scheduled buses in the base month based on the passenger volume of scheduled buses in the base month and the number of days in the base month, and calculate the average daily passenger volume of chartered tourist buses in the base month based on the passenger volume of chartered tourist buses in the base month and the number of days in the base month; Calculate the average daily passenger volume of intercity and urban and rural public buses and trams in the base month based on the passenger volume of intercity and urban and rural public buses and trams in the base month and the number of days in the base month; Calculate the average daily passenger volume of intercity and urban-rural cruising buses in the base month based on the intercity and urban-rural cruising bus passenger volume in the base month and the number of days in the base month, and obtain the average daily passenger volume of intercity and urban-rural online-hailing taxis in the base month through the online-hailing taxi supervision information interaction system; According to the optimized highway bus traffic data, the optimized national and provincial highway bus traffic data, the first fluctuation weight, and the second fluctuation weight, respectively calculate a first scheduled bus fluctuation coefficient, a second tourist chartered bus fluctuation coefficient, a third intercity urban and rural public bus and tram fluctuation coefficient, and a fourth intercity urban and rural touring bus fluctuation coefficient; Calculate the third product of the average daily passenger volume of scheduled buses in the base month and the fluctuation coefficient of the first scheduled buses, calculate the fourth product of the average daily passenger volume of tourist chartered buses in the base month and the fluctuation coefficient of the second tourist chartered buses, calculate the fifth product of the average daily passenger volume of intercity and urban and rural public buses and trams in the base month and the third fluctuation coefficient of intercity and urban and rural public buses and trams, calculate the sixth product of the average daily passenger volume of intercity and urban and rural cruising cars in the base month and the fourth fluctuation coefficient of intercity and urban and rural cruising cars, and take the sum of the third product, the fourth product, the fifth product, the sixth product and the average daily passenger volume of intercity and urban and rural online taxis in the base month as the initial daily commercial highway passenger volume.

6. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the daily monitoring method for commercial highway passenger volume according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the daily monitoring method for commercial highway passenger traffic volume according to any one of claims 1 to 4 are implemented.

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