Method for calculating urban radiation index based on commercial vehicle and passenger vehicle traffic data

Abstract

The present invention discloses a method for calculating the city radiation power index based on commercial vehicle and passenger vehicle traffic data. The present invention provides strong data result support for the city's radiation power, and this result can be used as the basis for constructing other indicators such as the radiation power of urban agglomerations and the radiation power of the top 100 districts and counties. The application of this indicator can realize rolling calculation and evaluation, and can evaluate the city's external economic connections once a month or once a year. In the past, the external radiation power of cities was calculated using methods such as statistical data and gravity models, and there was no direct and intuitive method to evaluate the radiation power.

Description

Technical Field

[0001] The present invention belongs to the field of economic indicator research, and in particular, relates to a method for calculating a city radiation index based on commercial vehicle and passenger vehicle traffic data. Background Art

[0002] In the study of regional economy and urban development, the radiation power of a city is an important indicator to measure its economic impact on the surrounding regions. The radiation power of a city mainly refers to the influence of a city on other regions in terms of transportation, economy, culture, etc. It reflects the status and role of the city in the region. Traditionally, the measurement of urban radiation power usually relies on statistical economic data (such as GDP, population, number of enterprises) or estimates based on the flow data of specific commodities (such as logistics volume, trade volume), but these methods have some limitations. For example, economic statistics are relatively lagging and it is difficult to reflect real-time urban connections; and the flow data based on specific commodities can only represent local economic activities and lack extensiveness.

[0003] With the development of transportation and information technology, vehicle network data (including commercial vehicle and passenger vehicle data) provides a new tool for the analysis of regional economic connections. Commercial vehicle flow data can reflect the actual situation of inter-city cargo circulation and reveal the strength of logistics connections between different cities; passenger vehicle flow data can reflect the mobility of inter-city people flow and reflect the city's attractiveness to population activities. These data can present the transportation and economic connections between cities in a more comprehensive and real-time manner, providing an objective basis for the measurement of urban radiation power.

[0004] In view of this, the present invention is proposed. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a method for calculating the urban radiation index based on commercial vehicle and passenger vehicle traffic data, thereby solving the problems raised in the above-mentioned background technology.

[0006] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:

[0007] A method for calculating a city radiation index based on commercial vehicle and passenger vehicle traffic data comprises the following steps:

[0008] Step 1: Obtain the trip data of commercial vehicles and passenger vehicles through the Internet of Vehicles, where the trip data includes the vehicle license plate number, trip number, start time, starting longitude and latitude, and end longitude and latitude of the vehicle;

[0009] Step 2: Based on the trip data obtained in step 1, analyze and extract the starting point, end point and travel distance of the vehicle, and filter each trip to eliminate invalid data with a travel distance of less than 500 meters;

[0010] Step 3: Using the feature data extracted in step 2, calculate the city radiation index of commercial vehicles and passenger vehicles respectively;

[0011] Step 4: Use the extreme value normalization method to process the sub-index calculated in step 3 to obtain the standardized index;

[0012] Step 5: The standardized commercial vehicle and passenger vehicle sub-indices in step 4 are weighted according to the set weights a and b to finally generate a comprehensive index of urban radiation power, which is used to evaluate the intensity of economic ties between cities.

[0013] Optionally, the city radiation index in step 2 includes an urban radiation sub-index S1 considering traffic flow and an urban radiation sub-index S2 considering traffic flow and distance; the passenger car city radiation index includes an urban radiation sub-index C1 considering traffic flow, an urban radiation sub-index C2 considering traffic flow and distance, an urban radiation sub-index C3 considering the number of radiated cities, and an urban radiation sub-index C4 considering the number of radiated cities and distance.

[0014] Optionally, the radiation index S1 of city i is calculated based on the commercial vehicle traffic data. The formula is: Where n is the number of other cities related to city i. The radiation index S2 of city i is calculated using the formula:

[0015]

[0016] Optionally, calculate the radiation index C1 of city i using the formula: Calculate the radiation index C2 of city i using the formula:

[0017] Calculate the radiation index C3 of city i using the formula: Among them, D1 and D2 are the marker variables of traffic flow between cities. If there is traffic flow between city i and city j, D1 and D2 are recorded as 1, otherwise they are 0.

[0018] Calculate the radiation index C4 of city i using the formula:

[0019] Optionally, after obtaining S1 and S2, S1 and S2 are standardized. After S1 and S2 are standardized, SS1 and SS2 are obtained. Then, the obtained SS1 and SS2 are summed up to form the commercial vehicle city radiation index, which is expressed as follows:

[0020] Optionally, after obtaining the city radiation index C1 considering traffic flow, the city radiation index C2 considering traffic flow and distance, the city radiation index C3 considering the number of radiated cities, and the city radiation index C4 considering the number of radiated cities and distance, the formula The index is standardized, and then the standardized city radiation indexes C1, C2, C3, and C4 are recorded as SC1, SC2, SC3, and SC4. Then, after completing the standardization of the city radiation indexes C1, C2, C3, and C4, the passenger car city radiation index is obtained through the formula city radiation index = a*commercial vehicle city radiation index SSF+b*passenger car city radiation index SCF.

[0021] Optionally, the acquired Internet of Vehicles characteristic data is based on the time when the Internet of Vehicles data is reported, so as to obtain the vehicle's travel data and satellite positioning data for one year, and analyze the acquired satellite positioning data, mainly analyzing the satellite positioning time and satellite positioning longitude and latitude of the data points.

[0022] Optionally, the final expression for generating the comprehensive city radiation index is city radiation index = a*commercial vehicle city radiation index SSF+b*passenger vehicle city radiation index SCF, where a and b are weights, b=1-a, then the city radiation index range is (0,1), and a is adjusted based on the evaluation of the importance of passenger and cargo flows.

[0023] After adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art. Of course, any product implementing the present invention does not necessarily need to achieve all the advantages described below at the same time:

[0024] 1. The present invention provides strong data support for the radiation power of cities, and this result can be used as the basis for constructing other indicators such as the radiation power of urban agglomerations and the radiation power of the top 100 districts and counties. This indicator can be used to implement rolling calculation and evaluation, and can evaluate the external economic connections of cities once a month or once a year. In the past, the external radiation power of cities was calculated using statistical data and gravity models, and there was no direct and intuitive method to evaluate the radiation power.

[0025] 2. This invention uses "flow" data representing economic connections between cities, integrates the traffic data of commercial vehicles and passenger vehicles entering and leaving the city, and considers indicators such as the number of cities, traffic between cities, and the distance between the starting and ending points, to provide an indicator that more scientifically calculates economic connections between cities and represents the radiation power of cities. This indicator can be used as a reference for the development of similar indicators, and can also be scientifically applied to various scenarios to achieve dynamic monitoring.

[0026] 3. The present invention uses traffic data of commercial vehicles and passenger cars to not only accurately describe the flow of goods and people in the city, but also to combine factors such as distance and the number of radiated cities to quantify the radiation power of the city to the surrounding areas by building a scientific radiation power index model. Commercial vehicle flow data can reflect the strength of regional economic ties, while passenger vehicle flow data provides information about human activities such as life, consumption and tourism. Therefore, the method of calculating the city radiation power index based on commercial vehicle and passenger vehicle traffic data can overcome the shortcomings of traditional methods, more comprehensively reflect the radiation power of the city in the region, and provide strong data support for government decision-making, regional planning and market research.

[0027] The specific implementation modes of the present invention are further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings described below are only some embodiments. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0029] In the figure:

[0030] Figure 1 Flowchart of the method for calculating the urban radiation index for the data;

[0031] Figure 2 This is a schematic diagram of the structure of the total index of urban radiation power;

[0032] Figure 3 This is a schematic diagram of travel distribution in Shanghai 10 days before and after the Spring Festival;

[0033] Figure 4 Schematic diagram of the travel distribution structure in Shanghai 10 days before and 10 days after the Spring Festival.

[0034] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but are intended to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0035] The present invention will now be described in further detail with reference to the accompanying drawings.

[0036] See also Figure 1-4 As shown, in this embodiment, a method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data is provided, comprising the following steps:

[0037] Step 1: Obtain the trip data of commercial vehicles and passenger vehicles through the Internet of Vehicles, where the trip data includes the vehicle license plate number, trip number, start time, starting longitude and latitude, and end longitude and latitude of the vehicle;

[0038] Step 2: Based on the trip data obtained in step 1, analyze and extract the starting point, end point and travel distance of the vehicle, and filter each trip to eliminate invalid data with a travel distance of less than 500 meters;

[0039] Step 3: Using the feature data extracted in step 2, calculate the city radiation index of commercial vehicles and passenger vehicles respectively;

[0040] Step 4: Use the extreme value normalization method to process the sub-index calculated in step 3 to obtain the standardized index;

[0041] Step 5: The standardized commercial vehicle and passenger vehicle sub-indices in step 4 are weighted according to the set weights a and b to finally generate a comprehensive index of urban radiation power, which is used to evaluate the intensity of economic ties between cities.

[0042] As a further solution of the present invention: in the step one, the obtained Internet of Vehicles data includes: in order to provide better and faster services, only necessary data needs to be provided, which should include license plate number, trip number, start time, starting longitude, starting latitude, end longitude, and end latitude.

[0043] As a further solution of the present invention: in the step 2, the obtained Internet of Vehicles data includes: in order to provide better and faster services, only necessary data needs to be provided, which should include license plate number, trip number, start time, starting longitude, starting latitude, end longitude, and end latitude.

[0044] As a further solution of the present invention: in the step one, the vehicle network characteristic data obtained according to the reported data is: according to the time when the vehicle network data is reported, the vehicle's travel data and satellite positioning data for one year are obtained, and the obtained satellite positioning data is analyzed, mainly analyzing the satellite positioning time, satellite positioning longitude and latitude of the data points.

[0045] As a further solution of the present invention: in the step 2, the vehicle network characteristic data obtained according to the reported data is: according to the time when the vehicle network data is reported, the vehicle's travel data and satellite positioning data for one year are obtained, and the obtained satellite positioning data is analyzed, mainly analyzing the satellite positioning time, satellite positioning longitude and latitude of the data points.

[0046] As a further solution of the present invention: in the step 1, the extracted event features analyzed refer to the features that can represent the driving behavior of a passenger car extracted from satellite positioning data for at least one consecutive year.

[0047] As a further solution of the present invention: in the step 2, the extracted event features analyzed refer to the features that can represent the driving behavior of a passenger car extracted from satellite positioning data for at least one consecutive year.

[0048] As a further solution of the present invention: in the step 1, the behavioral event features analyzed include: the features of the trip mark, the starting point of the major trip, the end point of the major trip and the positioning of the starting and ending cities.

[0049] As a further solution of the present invention: in the step 2, the behavioral event features analyzed include: the features of the trip mark, the starting point of the major trip, the end point of the major trip and the positioning of the starting and ending cities.

[0050] As a further solution of the present invention: in the step 1, when performing data screening processing, according to the satellite positioning data, the trips with "distance (driving distance) <= 500 meters" and other unnecessary indicators are deleted, and the starting and ending points of all large trips are defined.

[0051] As a further solution of the present invention: in the step 2, when performing data screening processing, according to the satellite positioning data, the trips with "distance (driving distance) <= 500 meters" and other unnecessary indicators are deleted, and the starting and ending points of all large trips are defined.

[0052] In this embodiment, the city radiation power index in step 2 includes the city radiation power sub-index S1 considering traffic flow and the city radiation power sub-index S2 considering traffic flow and distance, and the passenger car city radiation power index includes the city radiation power sub-index C1 considering traffic flow, the city radiation power sub-index C2 considering traffic flow and distance, the city radiation power sub-index C3 considering the number of radiated cities, and the city radiation power sub-index C4 considering the number of radiated cities and distance. The city radiation power index is subdivided into multiple sub-indices, including the radiation power considering traffic flow, the radiation power of traffic flow and distance, the number of radiated cities, and the number of radiated cities and distance, so that the evaluation of the city radiation power is more comprehensive. This decomposition method can effectively reflect the economic and transportation radiation capacity of the city in the region, thereby more accurately portraying the scope of influence of the city.

[0053] In this embodiment, the radiation index S1 of city i is calculated based on the commercial vehicle traffic data, and the formula is: Where n is the number of other cities related to city i. The radiation index S2 of city i is calculated using the formula: The radiation power index of a city is calculated through commercial vehicle traffic data to reflect the actual connection between freight and logistics between cities. This method ensures the objectivity and representativeness of the calculation, making the radiation power index not only a theoretical derivation, but also a measurement based on actual traffic data, which can more truly reflect the economic connection between cities.

[0054] In this embodiment, the radiation index C1 of city i is calculated using the formula: Calculate the radiation index C2 of city i using the formula: The labeling of inter-city traffic data simplifies the complexity of data analysis by marking city pairs with traffic as 1 and city pairs without traffic as 0. This provides a clear data basis for subsequent calculations. This processing method can more quickly quantify traffic connections between cities.

[0055] Calculate the radiation index C3 of city i using the formula: Among them, D1 and D2 are marker variables for traffic between cities. If there is traffic between city i and city j, D1 and D2 are recorded as 1, otherwise they are 0. By standardizing the city radiation index, the comparability of different indicators is guaranteed. The standardized index reflects the relative level of urban radiation, provides a scientific basis for horizontal comparison of radiation power of different cities, and also lays the foundation for the calculation of the comprehensive index.

[0056] Calculate the radiation index C4 of city i using the formula:

[0057] In this embodiment, after obtaining S1 and S2, S1 and S2 are standardized. After S1 and S2 are standardized, SS1 and SS2 are obtained. Then, SS1 and SS2 are added together to form the commercial vehicle city radiation index, which is expressed as: Commercial vehicle city radiation index

[0058] In this embodiment, after obtaining the city radiation power sub-index C1 considering traffic flow, the city radiation power sub-index C2 considering traffic flow and distance, the city radiation power sub-index C3 considering the number of radiated cities, and the city radiation power sub-index C4 considering the number of radiated cities and distance, the formula The index is standardized, and then the standardized city radiation indexes C1, C2, C3, and C4 are recorded as SC1, SC2, SC3, and SC4. Then, after completing the standardization of the city radiation indexes C1, C2, C3, and C4, the passenger car city radiation index is obtained through the formula city radiation index = a*commercial vehicle city radiation index SSF+b*passenger car city radiation index SCF. When calculating the passenger car city radiation index, multiple factors such as traffic flow, distance, and the number of radiated cities are taken into account, which further improves the comprehensiveness of the index. This index not only takes into account the breadth of urban radiation (the number of radiated cities), but also combines the distance factor, which can more accurately reflect the city's attractiveness and influence on passenger car travel.

[0059] In this embodiment, the vehicle networking characteristic data obtained is based on the time when the vehicle networking data is reported, so as to obtain the vehicle travel data and satellite positioning data for one year, and analyze the obtained satellite positioning data, mainly analyzing the satellite positioning time and satellite positioning longitude and latitude of the data point. Using vehicle networking data for analysis ensures the integrity and representativeness of the data, and the data covers a whole year and can reflect the connection between cities in different seasons and at different times. This data processing method can fully reflect the radiation characteristics of the city and help to derive a more representative index.

[0060] In this embodiment, the final expression for generating the comprehensive index of urban radiation power is urban radiation power index = α * commercial vehicle urban radiation power index SSF + b * passenger car urban radiation power index SCF, where a and b are weights, b = 1-a, then the range of the urban radiation power index is (0,1), and a is adjusted according to the evaluation of the importance of passenger and cargo flows. The generation of the final comprehensive index combines the weights of passenger and cargo flows, so that the index can be flexibly adjusted to adapt to different analysis scenarios. The comprehensive index ranges from 0 to 1, providing an easy-to-interpret standard for evaluating the strength of urban radiation power. This method enhances the applicability of the index, giving it a higher explanatory power in different application scenarios.

[0061] The present invention is not limited to the above-mentioned embodiments. Anyone should be aware that any structural changes made under the enlightenment of the present invention, and any technical solutions that are the same or similar to the present invention, fall within the protection scope of the present invention. The technology, shape, and structural parts not described in detail in the present invention are all well-known technologies.

Claims

1. A method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data, characterized in that: The following steps are involved: Step 1: Obtain the trip data of commercial vehicles and passenger vehicles through the Internet of Vehicles, where the trip data includes the vehicle license plate number, trip number, start time, starting longitude and latitude, and end longitude and latitude of the vehicle; Step 2: Based on the trip data obtained in step 1, analyze and extract the starting point, end point and travel distance of the vehicle, and filter each trip to eliminate invalid data with a travel distance of less than 500 meters; Step 3: Using the feature data extracted in step 2, calculate the city radiation index of commercial vehicles and passenger vehicles respectively; Step 4: Use the extreme value normalization method to process the sub-index calculated in step 3 to obtain the normalized index; Step 5: The standardized commercial vehicle and passenger vehicle sub-indices in step 4 are weighted according to the set weights a and b to finally generate a comprehensive index of urban radiation power, which is used to evaluate the intensity of economic ties between cities.

2. The method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data according to claim 1, characterized in that: The urban radiation index in step 2 includes the urban radiation index S1 considering traffic flow and the urban radiation index S2 considering traffic flow and distance. The passenger car urban radiation index includes the urban radiation index C1 considering traffic flow, the urban radiation index C2 considering traffic flow and distance, the urban radiation index C3 considering the number of radiated cities, and the urban radiation index C4 considering the number of radiated cities and distance.

3. The method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data according to claim 2, characterized in that: According to the commercial vehicle traffic data, the radiation index S1 of city i is calculated as follows: Where n is the number of other cities related to city i. The radiation index S2 of city i is calculated as follows:

4. The method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data according to claim 3 is characterized in that: Calculate the radiation index C1 of city i using the formula: Calculate the radiation index C2 of city i using the formula: Calculate the radiation index C3 of city i using the formula: Among them, D1 and D2 are the marker variables of traffic flow between cities. If there is traffic flow between city i and city j, D1 and D2 are recorded as 1, otherwise they are 0; Calculate the radiation index C4 of city i using the formula:

5. The method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data according to claim 4 is characterized in that: After obtaining S1 and S2, S1 and S2 are standardized. After S1 and S2 are standardized, SS1 and SS2 are obtained. Then, the obtained SS1 and SS2 are summed up to form the commercial vehicle city radiation index, which is expressed as follows:

6. The method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data according to claim 5, characterized in that: After obtaining the city radiation index C1 considering traffic flow, the city radiation index C2 considering traffic flow and distance, the city radiation index C3 considering the number of radiated cities, and the city radiation index C4 considering the number of radiated cities and distance, the formula is used. The index is standardized, and then the standardized city radiation indexes C1, C2, C3, and C4 are recorded as SC1, SC2, SC3, and SC4. Then, after completing the standardization of the city radiation indexes C1, C2, C3, and C4, the passenger car city radiation index is obtained through the formula city radiation index = a*commercial vehicle city radiation index SSF+b*passenger car city radiation index SCF.

7. The method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data according to claim 6, characterized in that: The obtained Internet of Vehicles characteristic data is based on the time when the Internet of Vehicles data is reported, so as to obtain the vehicle's travel data and satellite positioning data for one year, and analyze the obtained satellite positioning data, mainly analyzing the satellite positioning time and satellite positioning longitude and latitude of the data points.

8. The method for calculating the city radiation index based on commercial vehicle and passenger vehicle traffic data according to claim 7, characterized in that: The final expression for the comprehensive urban radiation index is: Urban Radiation Index = a*Commercial Vehicle Urban Radiation Index SSF+b*Passenger Vehicle Urban Radiation Index SCF, where a and b are weights, b=1-a, then the urban radiation index range is (0,1), and a is adjusted based on the evaluation of the importance of passenger and freight flows.

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