A regional public transport accessibility measurement method and device based on multi-source data fusion and a storage medium

Abstract

The application relates to the technical field of traffic planning and control, and particularly discloses a regional public transport accessibility measurement method and device based on multi-source data fusion and a storage medium. First, subway and bus site data is acquired; second, the travel modes of residents are divided according to whether transfer is needed; third, a transfer link between different traffic modes is established based on the travel mode of transfer; finally, indexes are extracted from the transfer link and a single travel link, the public transport site accessibility of single travel and transfer travel can be measured according to a model, and thus the measurement of the regional public transport accessibility can be completed by aggregating the site accessibility. The application classifies the travel modes based on multi-source data, considers the continuous transfer service between different traffic tools to establish the single travel and transfer link, and can measure the site accessibility of single travel and transfer travel modes simultaneously.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of traffic planning and control, and particularly relates to a regional public transport accessibility measurement method and device based on multi-source data fusion and a storage medium. BACKGROUND

[0002] With the acceleration of urbanization and the continuous growth of population, urban traffic problems have become increasingly prominent, and the efficiency and service quality of public transportation systems have become the focus of attention for city managers and residents. As the basic unit of public transportation networks, the accessibility of bus stops is directly related to the convenience of passengers' travel and the overall efficiency of public transportation systems. However, traditional bus stop accessibility measurement methods have many limitations and are difficult to meet the needs of modern urban traffic management.

[0003] Firstly, traditional methods often rely on a single data source. Traditional methods mainly rely on static and single data sources to evaluate the accessibility of public transportation. These data usually only include basic information such as the geographical location of bus lines, station settings, and operating hours. However, these information often cannot fully reflect the complexity of public transportation systems, especially the importance of transfer. Transfer is an indispensable part of public transportation systems, which relates to whether passengers can smoothly switch between different lines or different modes of transportation to reach their destination.

[0004] Secondly, a single data source often cannot provide complete transfer station information. This leads to the convenience of transfer being underestimated or ignored in accessibility measurement, thereby affecting the accuracy of measurement results. A single data source may also fail to accurately reflect changes in passenger travel demand. If passenger travel demand shifts from one area to another, but the single data source fails to capture this change, the measurement results may not match the actual demand.

[0005] In addition, with the rapid development of information technology, new technologies such as big data, cloud computing, and the Internet of Things have provided unprecedented opportunities for urban traffic management. The acquisition and processing of multi-source data have become more convenient and efficient, providing new ideas and methods for bus stop accessibility measurement.

[0006] In summary, it is urgent to develop a regional public transport accessibility measurement method based on multi-source data fusion, which has important practical significance and application value. Therefore, the regional bus station accessibility measurement method based on multi-source data fusion is born at the right moment. The method considers the transfer travel in the station accessibility measurement, not just the single travel in the traditional sense. By making full use of modern information technology means, the method integrates multiple data sources to realize the comprehensive and accurate measurement of the accessibility of bus stations. This not only helps to improve the overall efficiency and service quality of the public transportation system, but also helps to provide a scientific basis for urban traffic planning, bus network optimization and bus service improvement. SUMMARY

[0007] To solve the problems in the prior art, the present application provides a regional public transport accessibility measurement method based on multi-source data fusion, equipment and storage medium, which solves the problem of insufficient precision caused by only considering single travel and ignoring the combined effect of multi-transportation mode transfer in the calculation of accessibility in the traditional method, and ensures that the accessibility evaluation can more comprehensively reflect the diversified transportation strategies that individuals may adopt in actual travel, thereby solving the problems mentioned in the above background art.

[0008] To achieve the above object, the present application provides the following technical scheme: a regional public transport accessibility measurement method based on multi-source data fusion, comprising the following steps:

[0009] S1, obtaining bus station data and subway station data, preprocessing the data, and extracting effective information therefrom to establish a subway and bus database based on the survey results;

[0010] S2, dividing the travel mode of passengers into two categories: the first category is single bus or subway travel mode, and the second category is transfer travel, including pure bus or subway transfer travel and bus-subway mixed travel;

[0011] S3, establishing a transfer link for the transfer travel mode;

[0012] S4, extracting the required indicators for the model from the transfer link of single travel and transfer travel, and using different models for each travel mode to calculate the station accessibility of single travel and transfer travel;

[0013] S5, aggregating the station accessibility obtained in step S4 in the traffic cell to obtain the regional public transport accessibility.

[0014] Preferably, in step S1, the effective information includes: line number, site number, site name, site distance, site latitude and longitude, and the number of points of interest near each site obtained by Arcgis; wherein the points of interest include points of interest related to government agencies, shopping malls, work units, education and culture, and medical units.

[0015] Preferably, in step S3, a transfer link is established for transfer travel mode, specifically including the following:

[0016] S31, set a line as X, when the line site x1 to the line site x2, x2 is regarded as the first transfer site;

[0017] S32, introduce the concept of diffusion circle, take the site in the line as the diffusion center, and establish a diffusion circle of 1500 meters from the center site, collect the position information of the center site and other sites that may exist in the surrounding based on the diffusion circle as the service range of the site;

[0018] S33, search for other line sites within the service range of the diffusion circle of x2 as the center;

[0019] S34, repeat the operation of step S32-step S33 to find the next site, until the maximum transfer number 4 is reached or there is no site to search for, obtain the link between the sites, and the sites include bus sites and subway sites, and establish the transfer link of continuous transfer between public transportation sites according to the link.

[0020] Preferably, in step S4, the indicators required by the model are extracted from the transfer link of single travel and transfer travel, specifically including: two indicators required by the single travel model in single travel: site distance and number of points of interest, wherein the site distance is taken as the input variable of E kj , and the number of points of interest is taken as the input variable of C j ; the indicators required by the transfer travel model in the transfer link of transfer travel: the number of opportunities in the service range of the site, the site distance, the transfer mode penalty coefficient α, the transfer number penalty coefficient β, and the different site transfer penalty coefficient γ.

[0021] Preferably, the step of extracting the indicators required by the transfer travel model specifically includes:

[0022] 1) based on the bus and subway site data in step S1, the number of opportunities in the service range of the site is obtained according to the line site number to obtain the number of points of interest in the service range of the site;

[0023] 2) the Euclidean distance between the transfer sites is calculated by the latitude and longitude data of different sites, that is, the site distance, and the specific calculation formula is as follows:

[0024] d12 = 6368.16 x arccos(sinX + cosX)

[0025] wherein,

[0026] In the formula, long1, lat1, Long2, lat2 are the longitude and latitude data of the stations before and after transfer respectively;

[0027] 3) The transfer mode of each transfer link is counted, and the transfer mode penalty coefficient a is adjusted according to the transfer mode, specifically including: when the transfer mode is bus-bus, the transfer mode penalty coefficient a takes the value 1.8; when the transfer mode is subway-subway, the transfer mode penalty coefficient a takes the value 1.2; when the transfer mode is bus-subway, the transfer mode penalty coefficient a takes the value 1.5;

[0028] 4) The transfer times of each transfer link are counted, and the transfer times penalty coefficient β is adjusted according to the transfer times, specifically including: when the transfer is 1 time, the transfer times penalty coefficient β takes the value 1.2; when the transfer is 2 times, the transfer times penalty coefficient β takes the value 1.5; when the transfer is 3 times, the transfer times penalty coefficient β takes the value 2.0; when the transfer is 4 times, the transfer times penalty coefficient β takes the value 3.0;

[0029] 5) According to the walking speed and the distance between stations, the same and different station transfer penalty coefficient γ is uniformly taken as 1.85.

[0030] Preferably, in step S4, different models are used to calculate the station accessibility of single travel and transfer travel for each travel mode, specifically including:

[0031] The single travel model is a gravity model-based algorithm, and the station accessibility calculation formula of single travel mode is as follows:

[0032]

[0033] wherein, A k is the public transport accessibility of the kth station; E kj is the travel cost from station k to station j; C j is the number of opportunities within the service range of station j; m represents the total number of stations on the travel route of station k;

[0034] The transfer travel model is a weighted algorithm based on the single travel model, and the station accessibility calculation formula of transfer travel mode is as follows:

[0035]

[0036] wherein, a is the transfer mode penalty coefficient; β is the transfer times penalty coefficient; γ is the different station transfer penalty coefficient.

[0037] Preferably, the obtained station accessibility in step S4 is aggregated in a traffic zone according to the location relationship of the cell to which the station belongs, to obtain regional public transport accessibility.

[0038] In another aspect, to achieve the above object, the present application also provides the following technical scheme: an electronic device, comprising: a processor; and a memory for storing one or more programs;

[0039] When the one or more programs are executed by the processor, the processor executes the regional public transport accessibility measurement method based on multi-source data fusion.

[0040] In another aspect, to achieve the above object, the present application also provides the following technical scheme: a computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the regional public transport accessibility measurement method based on multi-source data fusion.

[0041] The beneficial effects of the present application are: the regional bus station accessibility measurement method based on multi-source data fusion proposed by the present application: first, the present application uses a multi-dimensional data source different from the single data source in the past, which can integrate data from different channels, and these data together provide more comprehensive information, which helps to more accurately evaluate the accessibility of the public transport system. Secondly, in the way of measuring accessibility, the present application measures based on single trip and transfer trip, which overcomes the problem that the traditional measurement method ignores the transfer problem, resulting in that the measurement result cannot accurately reflect the actual travel experience of passengers, thereby reducing the accuracy of accessibility measurement. By considering transfer trips, the actual travel process of passengers from the starting point to the destination can be more accurately evaluated, thereby obtaining more accurate accessibility results. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The flowchart of the regional public transport accessibility measurement method based on multi-source data fusion of the present application;

[0043] Figure 2 The structure diagram of the electronic device in the embodiment of the present application;

[0044] In the figure, 210 is a processor; 220 is a memory. DETAILED DESCRIPTION

[0045] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0046] With reference to Figure 1 The present application provides a technical solution: a regional public transport accessibility measurement method based on multi-source data fusion, characterized by comprising the following steps:

[0047] S1, obtain bus station data and subway station data, pre-process the data, and extract effective information therefrom to establish a subway and bus database based on survey results.

[0048] The effective information includes line number, station number, station name, station distance, station longitude and latitude, and the number of interest points near each station obtained by Arcgis; and includes interest points related to government units, shopping malls, work units, science and education and medical units.

[0049] The data used in the implementation of the present application is bus station data and subway station data of Hangzhou in November 2023, wherein the original data of the bus and the subway includes line number, station number, station name, station distance, station longitude and latitude, and then the data is pre-processed, and an example of the data structure is shown in Table 1.

[0050] Table 1 Station data structure

[0051]

[0052] Further, a buffer area is established by Arcgis with the station as the center and a radius of 500 meters as the unit, so as to count the number of service opportunities near each station, including the number of interest points related to government units, shopping malls, work units, science and education and medical units, and an example of the data structure is shown in Table 2.

[0053] Table 2 Station interest point data structure

[0054]

[0055] S2, divide the travel mode of passengers, specifically into two categories: the first category is single bus or subway travel mode, and the second category is transfer travel, including pure bus or subway transfer travel and bus-subway mixed travel.

[0056] In the analysis of the division of the travel mode of residents, whether the transfer can be taken in the travel and the linkability between different traffics are considered to divide the travel mode into single travel and transfer travel mode, and the specific analysis process includes:

[0057] ①The travel demand of residents is diverse, including long and short distances, different time periods, etc. Single public transport or subway travel mode is suitable for simple travel demand, while public transport transfer and mixed travel can better meet the complex and variable travel demand. By considering whether transfer can be taken in the travel mode, the travel demand and preference of residents can be more accurately reflected;

[0058] ②With the rapid development of modern transportation system, the link and coverage of transportation lines are continuously optimized, providing convenient travel for residents.

[0059] S3, a transfer link chain is established for the transfer travel mode. According to the service capacity of each station, other stations that match it are searched, which can connect the stations of different lines, realize the continuous link travel between different transportation tools, and thus establish the transfer link chain.

[0060] The transfer link chain is established for the transfer travel mode, which specifically includes the following:

[0061] S31, a line is set as X (including public transport and subway lines), when the line station x1 to the line station x2, x2 is regarded as the first transfer station;

[0062] S32, the concept of diffusion circle is introduced, the station in the line is regarded as the diffusion center, the diffusion circle of 1500 meters is established around the center station, and the position information of the center station and other stations that may exist around the center station is collected based on the diffusion circle as the service range of the station;

[0063] S33, other line stations within the service range of the diffusion circle of x2 are searched;

[0064] S34, the next station is searched by repeating the operation of step S32-step S33 until the maximum transfer number 4 is reached or there is no station to search, the link between the stations is obtained, and the stations include public transport stations and subway stations, and the transfer link chain of continuous transfer between public transport stations is established according to the link.

[0065] For example:

[0066] ①The concept of diffusion circle is introduced, the station in the line is regarded as the diffusion center, the diffusion circle of 1500 meters is established around the center station, and the position information of the center station and other stations that may exist around the center station is collected based on the diffusion circle as the service range of the station;

[0067] ②Take a station x1 in a line X (including bus and subway lines) as the starting station, and x1 can reach other stations x2, x3, etc. in the line. Take x2 as the first transfer station of the travel chain;

[0068] ③Take x2 as the first transfer station, and search for other stations y1, y2, z1, z1, etc. in the vicinity of x2 except for the line according to the diffusion circle established in ①. Select one of the stations y1 as the second transfer station;

[0069] ④Take y1 as the second transfer station, and continue to search for other stations q1, q2, p1, p2, etc. in the vicinity of y2 except for the line. Select one of the stations q1 as the third transfer station to repeat the above operation to find the next station. Stop the search operation when there is no station that can be searched or the maximum number of transfers 4 is reached. In order to prevent the lines from being mixed, it is stipulated that each line can only be used once;

[0070] ⑤Connect all the searched stations to form a travel chain about the station x1.

[0071] ⑥At the same time, when x2 is taken as the first transfer station, the second transfer station can be y2, z1, z1, etc. due to the uncertainty of the station. Similarly, the third and fourth transfer stations (if any) can also be other stations. According to this theory, multiple travel chains about x1 can be established;

[0072] ⑦At the same time, in the line X, the station x1 can reach not only x2 but also x3, x4, x5, etc. in the line, which can be taken as the second transfer station about x1. Therefore, multiple travel chains about x1 can also be established;

[0073] ⑧According to the above, all travel chains about x1 can be established;

[0074] ⑨Similarly, all travel chains about all stations can be established in this way, and the stations include bus stations and subway stations. Therefore, pure bus or subway transfer travel and bus-subway mixed transfer travel can be established.

[0075] S4, extract the indicators required by the model from the transfer link chain of single travel and transfer travel, and use different models for each travel mode to calculate the station accessibility of single travel and transfer travel.

[0076] Further, the indicators required by the model extracted from the transfer link chain of single travel and transfer travel include two indicators required by the single travel model: station distance and the number of interest points, wherein the station distance is taken as E kjthe input variable of the first embodiment, the number of POIs as C j the input variable of the first embodiment; the indicators required by the transfer trip model are extracted from the transfer link chain: the number of opportunities of the station service range, the station distance, the transfer mode penalty coefficient a, the transfer frequency penalty coefficient β, and the off-station transfer penalty coefficient γ.

[0077] Further, the station accessibility calculation of the transfer trip needs to extract the indicators required by the model from the transfer link chain. The steps of extracting the indicators required by the transfer trip model include:

[0078] 1) Based on the bus and subway station data in step S1, the number of opportunities of the station service range is obtained according to the line station number to obtain the POIs within the station service range to represent the number of opportunities of the station service range.

[0079] 2) The Euclidean distance between transfer stations, i.e., the station distance, is calculated through the latitude and longitude data of different stations. The specific calculation formula is as follows:

[0080] d 12 = 6368.16 * arccos (sinX + cosX)

[0081] wherein,

[0082] In the formula, long1, lat1, Long2, and lat2 are the latitude and longitude data of the stations before and after transfer.

[0083] 3) The transfer mode of each transfer link chain is counted, and the transfer mode penalty coefficient a is adjusted according to the transfer mode. Specifically, when the transfer mode is bus-bus, the transfer mode penalty coefficient a is 1.8; when the transfer mode is subway-subway, the transfer mode penalty coefficient a is 1.2; and when the transfer mode is bus-subway, the transfer mode penalty coefficient a is 1.5. As shown in Table 3.

[0084] Table 3 Adjustment mode table of transfer mode penalty coefficient

[0085] Transfer mode Conventional bus - conventional bus Rail transit - rail transit Conventional bus - rail transit Value 1.8 1.2 1.5

[0086] 4) The transfer frequency of each transfer link chain is counted, and the transfer frequency penalty coefficient β is adjusted according to the transfer frequency. Specifically, when the transfer frequency is 1, the transfer frequency penalty coefficient β is 1.2; when the transfer frequency is 2, the transfer frequency penalty coefficient β is 1.5; when the transfer frequency is 3, the transfer frequency penalty coefficient β is 2.0; and when the transfer frequency is 4, the transfer frequency penalty coefficient β is 3.0. As shown in Table 4.

[0087] Table 4 Adjustment mode table of transfer frequency penalty coefficient

[0088] Transfer times Transfer 1 time Transfer 2 times Transfer 3 times Transfer 4 times Value 1.2 1.5 2.0 3.0

[0089] 5) According to the walking speed of the person and the distance parameter of the station, the same and different station transfer penalty coefficient γ is uniformly taken as 1.85.

[0090] Further, different models are used for respective travel modes to calculate the station accessibility of single travel and transfer travel, specifically including:

[0091] The single travel model is a gravity model-based algorithm, and the station accessibility calculation formula of the single travel mode is as follows:

[0092]

[0093] Wherein, A k is the public transport accessibility of the kth station; E kj is the travel cost of the station k to the station j; C j is the number of opportunities within the service range of the station j; and m represents the total number of stations on the travel route of the station k.

[0094] The transfer travel model is a weighted algorithm based on the single travel model, and the station accessibility calculation formula of the transfer travel mode is as follows:

[0095]

[0096] Wherein, α is the transfer mode penalty coefficient; β is the transfer number penalty coefficient; and γ is the different station transfer penalty coefficient.

[0097] S5, aggregate the obtained station accessibility in step S4 in the traffic cell, to obtain the regional public transport accessibility.

[0098] According to the location relationship of the station belonging to the cell, the obtained station accessibility in step S4 is aggregated in the traffic cell to obtain the regional public transport accessibility.

[0099] The regional public transport accessibility is obtained by superimposing the accessibility of all public transport stations in the traffic cell. First, the traffic cell where all public transport stations are located is counted, and then the accessibility of the same type of interest points of the stations in each cell is accumulated to obtain the accessibility of the regional public transport, and an example of the data structure is shown in Table 5.

[0100] Table 5 Regional public transport accessibility

[0101]

[0102]

[0103] There is an inseparable close relationship between the regional public transport accessibility and the accessibility of nearby bus stations. The convenience of the nearby bus stations directly relates to the efficiency and comfort of the residents using public transport, and further has a profound impact on the convenience of the whole traffic zone to reach other important areas of the city. Both of them reflect the degree of perfection of the urban traffic network, the rationality of the planning layout, and the convenience and efficiency of the residents' travel, which are important aspects that cannot be ignored in the development of urban traffic.

[0104] Based on the same inventive concept as the above method embodiments, the embodiments of the present application also provide an electronic device, such as Figure 2 As shown, the device includes a processor 210 and a memory 220 for storing one or more programs.

[0105] When the one or more programs are executed by the processor 210, the processor performs the method of measuring the regional public transport accessibility based on multi-source data fusion.

[0106] The method of measuring the regional public transport accessibility based on multi-source data fusion specifically includes the following:

[0107] S1, obtain bus station data and subway station data, pre-process the data, and extract effective information therefrom to establish a subway and bus database based on the survey results;

[0108] S2, divide the travel mode of passengers into two categories: the first category is a single bus or subway travel mode, and the second category is a transfer travel mode, including pure bus or subway transfer travel and bus-subway mixed travel;

[0109] S3, establish a transfer link for the transfer travel mode;

[0110] S4, extract the required indicators for the model from the transfer link of the single travel and the transfer travel, and use different models for the respective travel modes to calculate the station accessibility of the single travel and the transfer travel;

[0111] S5, aggregate the station accessibility obtained in step S4 in the traffic zone to obtain the regional public transport accessibility.

[0112] Based on the same inventive concept as the above method embodiments, the embodiments of the present application also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program is executed by the processor 210 to implement the method of measuring the regional public transport accessibility based on multi-source data fusion.

[0113] The method of measuring the regional public transport accessibility based on multi-source data fusion specifically includes the following:

[0114] S1, obtain bus station data and subway station data, pre-process the data, and extract effective information therefrom to establish a subway and bus database based on the survey results;

[0115] S2, divide the travel mode of passengers, specifically into two categories: the first category is a single bus or subway travel mode, and the second category is a transfer travel mode, including pure bus or subway transfer travel and bus-subway mixed travel;

[0116] S3, establish a transfer link for the transfer travel mode;

[0117] S4, extract the required indicators for the model from the transfer link of the single travel and the transfer travel, and use different models for the respective travel modes to calculate the station accessibility of the single travel and the transfer travel;

[0118] S5, aggregate the station accessibility obtained in step S4 in a traffic cell to obtain the regional public transport accessibility.

[0119] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0120] If the functions are realized in the form of software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, an electronic device, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: 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 various media that can store program codes. It should be noted that in this document, the terms "include", "contain" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device that includes a series of elements not only includes those elements, but also includes other elements that are not explicitly listed, or includes elements inherent to the process, method, article or device. Without more limitations, the element defined by the statement "includes one" does not exclude the presence of another identical element in the process, method, article or device that includes the element.

[0121] The terminology used in the description of the embodiments herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the description of the embodiments and the appended claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0122] It should be understood that the term "and / or" as used herein merely describes associated objects, and can exist in three forms, for example, A and / or B can mean that A exists alone, A and B exist together, or B exists alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects.

[0123] Depending on context, the word "if" as used herein can be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined" or "if [a stated condition or event] is detected" can be interpreted to mean "upon determining" or "in response to determining" or "upon detecting [the stated condition or event]" or "in response to detecting [the stated condition or event]."

[0124] The "first\second" mentioned in the embodiments is only to distinguish similar objects, and does not represent a specific order of the objects. Understandably, the "first\second" can be interchanged in a specific order or sequence as allowed. It should be understood that the objects distinguished by "first\second" can be interchanged under appropriate circumstances, so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0125] Although the application has been described in detail with reference to the foregoing embodiments, the technical solutions recorded in the foregoing embodiments can be modified by those skilled in the art, or some technical features can be replaced by equivalents, and any modification, equivalent replacement, improvement, etc. within the spirit and principles of the application shall be included in the protection scope of the application.

Claims

1. A method for measuring regional public transportation accessibility based on multi-source data fusion, characterized by: The steps include: S1. Obtain bus stop data and subway station data, pre-process the data, extract effective information from it, and establish a subway and bus database based on the survey results; S2. Categorize passengers' travel modes into two categories: the first category is single bus or subway travel, and the second category is transfer travel, which includes pure bus, subway transfer travel, or bus-subway mixed travel; S3. Establish a transfer connection chain for transfer travel modes; specifically, it includes the following: S31. Let a line be X. When the line station x1 reaches the line station x2, x2 is regarded as the first transfer station. S32. Introducing the concept of diffusion circles, treating a station along the route as a diffusion center, establishing a diffusion circle with a radius of 1500 meters around this station. Using this diffusion circle as the station's service range, we collect location information for the central station and any other stations that may exist in its vicinity. S33, searching for other line stations within the service range of its diffusion circle with x2 as the center; S34. Repeat steps S32 to S33 to search for the next station until the maximum number of transfers reaches 4 or there are no more stations to search. Then, links between the station and other stations are obtained, and the stations include bus stations and subway stations. Based on these links, a transfer connection chain for continuous transfers between public transportation stations is established; S4. Extract the indicators required by the model from the transfer connection chain of single trips and transfer trips, and use different models for each travel mode to calculate the station accessibility of single trips and transfer trips; The indicators required for the model are extracted from the transfer connection chain between a single trip and a transfer trip. Specifically, two indicators required for the single trip model are extracted from a single trip: station distance and number of points of interest, where station distance is used as E kj The input variable is the number of interest points as C j The input variables of the transfer travel are: the number of opportunities in the station service range, the station distance, the transfer mode penalty coefficient α, the transfer number penalty coefficient β and the different station transfer penalty coefficient γ; Different models are used for each travel mode to calculate the station accessibility for single trips and transfer trips, including: The single travel model is an algorithm based on the gravity model. The formula for calculating the station accessibility of a single travel mode is as follows: Among them, A k is the public transportation accessibility of the k-th station; E kj is the travel cost from station k to station j; C j is the number of opportunities within the service range of station j; m is the total number of all stations on the travel route of station k; The transfer travel model is a weighted algorithm based on a single travel model. The calculation formula for station accessibility of transfer travel mode is as follows: Among them, α is the transfer mode penalty coefficient; β is the transfer number penalty coefficient; γ is the different station transfer penalty coefficient; S5. Based on the location relationship of the cells to which the stations belong, aggregate the station accessibility obtained in step S4 within the traffic cell to obtain regional public transportation accessibility.

2. The method for measuring regional public transportation accessibility based on multi-source data fusion according to claim 1 is characterized by: In step S1, the valid information includes: line number, station number, station name, station distance, station latitude and longitude, and the number of points of interest near each station obtained through Arcgis; including points of interest related to government agencies, shopping malls, workplaces, scientific and educational culture and medical institutions.

3. The method for measuring regional public transportation accessibility based on multi-source data fusion according to claim 1 is characterized by: The steps for extracting indicators required for the transfer travel model include: 1) Based on the bus and subway station data in step S1, obtain points of interest within the station service range according to the line station number to represent the number of opportunities within the station service range; 2) Calculate the Euclidean distance between transfer stations, i.e., station distance, using the latitude and longitude data of different stations. The specific calculation formula is as follows: d 12 =6368.16×arccos(sinX+cosX) in, Where, long1, lat1 are the longitude and latitude data of the station before the transfer; long2, lat2 are the longitude and latitude data of the station after the transfer; 3) Count the transfer modes of each transfer chain and adjust the transfer mode penalty coefficient α based on the transfer mode. Specifically, when the transfer mode is bus-bus, the transfer mode penalty coefficient α is 1.8; when the transfer mode is subway-subway, the transfer mode penalty coefficient α is 1.2; when the transfer mode is bus-subway, the transfer mode penalty coefficient α is 1.5; 4) Count the number of transfers for each transfer chain and adjust the transfer penalty coefficient β based on the number of transfers. Specifically, when there is one transfer, the transfer penalty coefficient β is 1.2; when there are two transfers, the transfer penalty coefficient β is 1.5; when there are three transfers, the transfer penalty coefficient β is 2.0; when there are four transfers, the transfer penalty coefficient β is 3.0; 5) Based on the walking speed and station distance parameters, the transfer penalty coefficient γ for the same or different stations is uniformly set to 1.

85.

4. An electronic device, characterized in that: The electronic device includes: a processor (210); and a memory (220) for storing one or more programs; When the one or more programs are executed by the processor (210), the processor is enabled to execute the regional public transportation accessibility measurement method based on multi-source data fusion as described in any one of claims 1 to 3.

5. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by the processor (210), the method for measuring regional public transportation accessibility based on multi-source data fusion as described in any one of claims 1 to 3 is implemented.

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