A micro-circulation bus station site selection method based on station attractive index

Abstract

The application discloses a micro-circulation bus station site selection method based on station attractive index, which comprises basic input data requirement specification, micro-circulation bus candidate station determination, station attractive index quantification method, micro-circulation bus station site selection model construction based on station attractive index, and the use of internet open platform data and survey data. The actual walking distance of residents from their residence to the micro-circulation bus station is considered, so that the bus station site selection can attract all residents in the layout area to take the micro-circulation bus, and the willingness of passengers to use the bus is improved. Meanwhile, the number of stations is considered to reduce the operation cost of public companies and improve the service convenience and accessibility of the micro-circulation bus. The application can merge the candidate stations before reaching the minimum threshold of the station attractive index that can attract passengers, so as to ensure that the micro-circulation travel demand of all residents is met with the least number of stations, and then competitive micro-circulation bus services are provided.

Description

Technical Field

[0001] This invention belongs to the field of public transportation planning and management, specifically involving a micro-circulation bus stop site selection method based on the station gravity index. Background Technology

[0002] Micro-circulation bus service is a concept within urban public transportation systems. It's a form of public transportation designed to meet short-distance travel needs at the micro-level, addressing the "first mile" and "last mile" of a passenger's journey. Unlike traditional bus routes, micro-circulation bus services need to offer greater convenience to gain a competitive advantage over shared bicycles and other modes of transportation during peak hours. Too many stops within the designated area can lead to excessively circuitous bus routes; too few stops result in long walking distances for residents, causing them to abandon micro-circulation bus services altogether. Traditional bus stop location methods often prioritize passenger accessibility, limiting factors like stop density and spacing, but these methods struggle to guarantee the micro-circulation bus travel needs of all residents within the designated area. Summary of the Invention

[0003] Objective: To address the aforementioned problems, this invention provides a micro-circulation bus stop location selection method that can meet the travel needs of all residents within the deployment area and improve the operational efficiency and save costs of micro-circulation buses by controlling the number of stops. Unlike traditional bus routes, micro-circulation bus services need to provide more convenient services to gain a competitive advantage over shared bicycles and other modes of transportation during peak hours. This invention considers that the attractiveness of micro-circulation buses is closely related to the walking distance from residents to bus stops and the actual operational efficiency and cost of the buses. In this context, it utilizes an open network platform to obtain the travel needs of residents within the deployment area and considers the station attraction index to allocate station locations.

[0004] Technical Solution: To solve the above technical problems, this invention provides a micro-circulation bus stop site selection method based on the station gravity index, which includes the following steps:

[0005] S1. Basic Input Data Requirements and Specifications, used to standardize the basic input data of the model;

[0006] S2. Determine candidate stops for micro-circulation bus routes;

[0007] S3. Obtain the gravitational index of each candidate station on each residential building, and use it as input data for the micro-circulation bus stop location selection model based on the station gravitational index.

[0008] S4. Construction of a micro-circulation bus stop location model based on station gravity index. The optimization objective is to maximize the sum of the gravity indices of micro-circulation bus stops to all residents in the deployment area. Constraints are established from aspects such as the number of stops and station gravity index. The bus stop location scheme is calculated and obtained under the premise of meeting the requirements of residents of each residential building for micro-circulation bus stops.

[0009] Furthermore, in step S1, the basic input data includes location data, resident data, and distance data within the deployment area. The standardization requirements for these three types of data are as follows:

[0010] Location data within the deployment area is obtained from the corresponding information source network open platform for each residential building, each entrance and exit of the community, and existing bus stops. The data is then encoded and summarized to obtain their geographical latitude and longitude coordinates.

[0011] Resident data within the deployment area is collected from the corresponding information source network open platform for each residential building in the community, and the community and number of households to which it belongs are obtained by encoding and summarizing.

[0012] Distance data within the deployment area is obtained by acquiring actual walking distance information from each residential building to each community entrance and existing bus stop from the corresponding information source network open platform, and then encoding and summarizing it to obtain the OD table.

[0013] Furthermore, in step S2, the set of candidate micro-circulation bus stops within the deployment area consists of a set of entrances and exits of residential communities and a set of existing bus stops.

[0014] Furthermore, in step S3, the station gravity index is characterized using a piecewise function of station gravity index - walking distance to station, as shown in the following formula:

[0015]

[0016] In the formula, S ij Let d be the station gravitational index of station j for residents of building i. ij Let θ be the walking distance from residents of building i to station j. When the walking distance is within θ, the gravitational attraction index of the micro-circulation bus station to residents remains unchanged. When the walking distance exceeds θ, the gravitational attraction index of the micro-circulation bus station to residents gradually decreases with the increase of walking distance. When the walking distance reaches the maximum walking distance κ, the micro-circulation bus service loses its attraction to residents, that is, the station gravitational attraction index is 0.

[0017] Furthermore, the specific process of step S4 is as follows:

[0018] S4-a1, The optimization objective is to maximize the sum of the gravitational indices of the micro-circulation bus stops within the deployment area for all residents:

[0019]

[0020] In the formula, Z represents the sum of the gravitational indices of the stations; H i M represents the number of households living in apartment building i. i The maximum value is taken as the gravitational index of all candidate stations in set N to residential building i, where N is the set of candidate bus stations in the deployment area;

[0021] S4-a2. Establish constraints based on two aspects: the gravitational index of the site and the number of sites.

[0022] M i =max{Z j ·S ij} (3)

[0023] Equation (3) is the maximum value of the gravitational index of all candidate sites in set N for residential building i;

[0024]

[0025] Equation (4) ensures that the maximum value of the gravitational index of the station near residential building i is greater than the threshold, and ensures that there is at least one station near each residential building that meets the requirements of the station gravitational index.

[0026]

[0027] Equation (5) ensures that only one value of k is determined as the final number of stations selected, and that value is within a set range, i.e., between β1 and β2;

[0028]

[0029] Equation (6) establishes the variable R that indicates the retention of k sites, including site j. jk And indicating the variable U that retains k sites k The logical relationship between the two;

[0030]

[0031] Equation (7) is Z j and U k Connecting these equations, both sides equal the final number of selected sites;

[0032] 0<β1≤β2≤δ (8)

[0033] Equation (8) is a constraint on the number of sites, ensuring that the number of sites in the final preferred site set is within a certain limit;

[0034]

[0035] Equation (9) represents the domain constraints of the model decision variables, indicating that Z j U k R jk It is a binary variable;

[0036] In the formula, I represents the set of residential buildings within the deployment area; N represents the set of candidate bus stops within the deployment area; α represents the minimum station attraction index within the deployment area that can attract residents to choose the micro-circulation bus service; β1 represents the minimum number of bus stops within the deployment area in the final scheme; β2 represents the maximum number of bus stops within the deployment area in the final scheme; δ represents the total number of candidate bus stops within the deployment area, δ=|N|; S ij M represents the station gravitational index of station j for residents of building i; i H represents the result of maximizing the gravitational exponent of all candidate sites in set N for residential building i; i Z represents the number of families living in apartment building i; j For a binary variable, it is 1 when candidate site j is retained, and 0 otherwise; U k For a binary variable, R is 1 if the plan determines to retain k bus stops, and 0 otherwise; jk To retain k bus stops in the final solution, the value is 1 if candidate stop j is included, and 0 otherwise.

[0037] S4-a3. Solve the location model consisting of the optimization objective in step S4-a1 and the constraints in step S4-a2. If a solution exists, the location scheme for the micro-circulation bus stop in the deployment area is obtained.

[0038] Beneficial effects: Compared with the prior art, the present invention, by adopting the above technical solution, has the following technical effects:

[0039] 1. This invention can meet the acceptable actual walking distance of passengers from their residence to the station, making the provided micro-circulation bus service attractive enough to all residents, and ensuring the competitiveness of micro-circulation buses and the fairness of bus services from the station level.

[0040] 2. This invention is applicable to relatively large residential communities with centralized management, providing corresponding reference and methodological support for the site selection aspect of the current community micro-circulation bus system planning;

[0041] 3. This invention effectively utilizes web crawler technology to obtain demand data to determine the number of stations. While meeting the station attraction requirements, it minimizes the number of stations, avoids waste, saves construction and operation costs, and improves the convenience and accessibility of micro-circulation bus services.

[0042] 4. This invention is based on the quantification of the site gravity index and a single-objective mixed integer linear programming model. The method is reasonable and the calculation is simple, which ensures the scientific nature and accuracy of subsequent work. Attached Figure Description

[0043] Figure 1 This is an overall logic flowchart of an embodiment of the present invention;

[0044] Figure 2 This is a distribution map of candidate sites in the deployment area according to an embodiment of the present invention;

[0045] Figure 3 This is the result of site selection for the regional micro-circulation bus stop in this embodiment of the invention. Detailed Implementation

[0046] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings:

[0047] This invention proposes a micro-circulation bus stop site selection method based on the station gravity index, such as... Figure 1 As shown, the specific implementation steps are as follows:

[0048] S1. Basic Input Data Requirements and Specifications, used to standardize the basic input data of the model;

[0049] S2. Determine candidate stops for micro-circulation bus routes;

[0050] S3. Obtain the gravitational index of each candidate station on each residential building, and use it as input data for the micro-circulation bus stop location selection model based on the station gravitational index.

[0051] S4. Construction of a micro-circulation bus stop location model based on station gravity index. The optimization objective is to maximize the sum of the gravity indices of micro-circulation bus stops to all residents in the deployment area. Constraints are established from aspects such as the number of stops and station gravity index. The bus stop location scheme is calculated and obtained under the premise of meeting the requirements of residents of each residential building for micro-circulation bus stops.

[0052] Furthermore, in step S1, location data within the area is deployed by crawling data from the corresponding information source network open platform for each residential building, each entrance and exit of the community, and existing bus stops, and encoding and summarizing them to obtain their geographical latitude and longitude coordinates. Taking a certain residential building in Fengwuyuan Community (118.857545, 32.123161) as an example, let it be numbered 1; taking a certain entrance and exit of Fengwuyuan Community (118.849692, 32.120594) as an example, let it be numbered 1; taking the existing bus stop—Dingjiazhuang West (North) (118.850074, 32.116206) as an example, let it be numbered 2;

[0053] Resident data within the deployment area is collected by crawling data from the corresponding information source network open platform for each residential building in the community, and the codes are summarized to obtain the community and number of households to which it belongs. Taking Building No. 1 in Fengwuyuan Community as an example, it has 194 households;

[0054] Distance data within the deployment area was collected by crawling data from the corresponding information source network open platform. The actual walking distance information from each residential building to each community entrance and existing bus stop was encoded and summarized to obtain the OD table. Taking the starting point numbered 1 to 3 as an example, the row number O is 1 and the column number D is 3 in the OD table, indicating that the actual walking distance from point 1 to point 3 is 269 meters.

[0055] In this embodiment, detailed data of 129 residential buildings within the deployment area were obtained.

[0056] Furthermore, in step S2, the candidate station set for micro-circulation buses within the deployment area consists of a set of residential community entrances and exits and a set of existing regular bus stops. In this embodiment, detailed data for 58 candidate stations within the deployment area are obtained, and the layout of the candidate stations is as follows: Figure 2 As shown.

[0057] Furthermore, in step S3, the station gravity index is characterized using a piecewise function of station gravity index - walking distance to station, as shown in the following formula:

[0058]

[0059] In the formula, S ij The station gravitational index of station j for residents of building i; d ij Let θ be the walking distance from residents of building i to station j. When the walking distance is within θ, the gravitational attraction index of the micro-circulation bus station to residents remains unchanged. When the walking distance exceeds θ, the gravitational attraction index of the micro-circulation bus station to residents gradually decreases with the increase of walking distance. When the walking distance reaches the maximum walking distance κ, the micro-circulation bus service loses its attraction to residents, that is, the station gravitational attraction index is 0.

[0060] The values ​​of θ and κ within the deployment area are determined by field visits and survey statistics. In this embodiment, θ is 300 meters and κ is 800 meters. The station gravity index - walking distance to the station piecewise function is Equation (2). Then, the gravity index of each candidate station to the residents of each residential building is calculated.

[0061]

[0062] Furthermore, the specific process of step S4 is as follows:

[0063] S4-a1, The optimization objective is to maximize the sum of the gravitational indices of the micro-circulation bus stops within the deployment area for all residents:

[0064]

[0065] In the formula, Z represents the sum of the gravitational indices of the stations; H i M represents the number of households residing in apartment building i; i The result is the maximum value of the gravitational index of all candidate stations in set N for residential building i; N is the set of candidate bus stations in the deployment area.

[0066] S4-a2. Establish constraints based on two aspects: the gravitational index of the site and the number of sites.

[0067]

[0068] Equation (4) is the maximum value of the gravitational index of all candidate sites in set N for residential building i;

[0069]

[0070] Equation (5) ensures that the maximum value of the gravitational index of the station near residential building i is greater than the threshold, and ensures that there is at least one station near each residential building that meets the requirements of the station gravitational index;

[0071]

[0072] Equation (6) ensures that only one value of k is determined as the final number of stations selected, and that value is within a set range, i.e., between β1 and β2;

[0073]

[0074] Equation (7) establishes the variable R that indicates the retention of k sites, including site j. jk And indicating the variable U that retains k sites k The logical relationship between the two;

[0075]

[0076] Equation (8) is Z j and U k Connecting these equations, both sides equal the final number of selected sites;

[0077]

[0078] Equation (9) is a constraint on the number of sites, ensuring that the number of sites in the final preferred site set is within a certain limit;

[0079]

[0080] Equation (10) represents the domain constraints of the model decision variables, indicating that Zj U k R jk It is a binary variable;

[0081] In the formula, I represents the set of residential buildings within the deployment area; N represents the set of candidate bus stops within the deployment area; α represents the minimum station attraction index within the deployment area that can attract residents to choose the micro-circulation bus service; β1 represents the minimum number of bus stops within the deployment area in the final scheme; β2 represents the maximum number of bus stops within the deployment area in the final scheme; δ represents the total number of candidate bus stops within the deployment area, δ=|N|; S ij M represents the station gravitational index of station j for residents of building i; i H represents the result of maximizing the gravitational exponent of all candidate sites in set N for residential building i; i Z represents the number of families living in apartment building i; j For a binary variable, it is 1 when candidate site j is retained, and 0 otherwise; U k For a binary variable, R is 1 if the plan determines to retain k bus stops, and 0 otherwise; jk To retain k bus stops in the final solution, the value is 1 if candidate stop j is included, and 0 otherwise.

[0082] S4-a3. In the embodiment, the minimum number of bus stops β1 in the final layout area is 10, the maximum number of bus stops β2 is 20, and the minimum station attraction index α that can attract residents to choose the micro-circulation bus service is 0.9.

[0083] Solving the location model formed by the optimization objective in step S4-a1 and the constraints in step S4-a2 yields the location scheme for micro-circulation bus stops within the deployment area, such as... Figure 3 As shown, there are a total of 17 preferred sites.

[0084] The above embodiments are merely illustrative of the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solutions based on the technical concept proposed in this invention shall fall within the scope of protection of this invention.

Claims

1. A micro-circulation bus stop site selection method based on station gravity index, characterized in that, The method includes the following steps: S1. Obtain the basic input data of the model and perform normalization processing on the basic input data of the model; S2. Determine candidate stops for micro-circulation bus routes; S3. Obtain the gravitational index of each candidate station on each residential building, and use it as input data for the micro-circulation bus stop location selection model based on the station gravitational index. S4. Construction of a micro-circulation bus stop location model based on station gravity index. The optimization objective is to maximize the sum of the gravity indices of micro-circulation bus stops to all residents in the deployment area. Constraints are established from the number of stations and the station gravity index. The bus stop location scheme is calculated and obtained under the premise of meeting the requirements of residents of each building for micro-circulation bus stops. In step S3, the station gravity index is characterized using a piecewise function of station gravity index - walking distance to station, as shown in the following formula: （1） In the formula, S ij Let d be the station gravitational index of station j for residents of building i. ij Let θ be the walking distance from residents of building i to station j. When the walking distance is within θ, the gravitational attraction index of the micro-circulation bus station to residents remains unchanged. When the walking distance exceeds θ, the gravitational attraction index of the micro-circulation bus station to residents gradually decreases as the walking distance increases. When the walking distance reaches the maximum walking distance κ, the micro-circulation bus service loses its appeal to residents, that is, the station gravitational attraction index is 0. The specific process of step S4 is as follows: S4-a1, The optimization objective is to maximize the sum of the gravitational indices of the micro-circulation bus stops within the deployment area for all residents: （2） In the formula, Z represents the sum of the gravitational indices of the stations; H i M represents the number of households living in apartment building i. i The maximum value is taken as the gravitational index of all candidate stations in set N to residential building i, where N is the set of candidate bus stations in the deployment area; S4-a2. Establish constraints based on two aspects: the gravitational index of the site and the number of sites. （3） Equation (3) is the maximum value of the gravitational index of all candidate sites in set N for residential building i; （4） Equation (4) ensures that the maximum value of the gravitational index of the station near residential building i is greater than the threshold, and ensures that there is at least one station near each residential building that meets the requirements of the station gravitational index; （5） Equation (5) ensures that only one value of k is determined as the final number of stations selected, and that the value is within a set range, i.e., between β1 and β2; （6） Equation (6) establishes the variable R that indicates the retention of k sites, including site j. jk And indicating the variable U that retains k sites k The logical relationship between the two; （7） Equation (7) is Z j and U k Connecting these equations, both sides equal the final number of selected sites; （8） Equation (8) is a constraint on the number of sites, ensuring that the number of sites in the final preferred site set is within a certain limit; （9） Equation (9) represents the domain constraints of the model decision variables, indicating that Z j U k R jk It is a binary variable; In the formula, I represents the set of residential buildings within the deployment area; N represents the set of candidate bus stops within the deployment area; α represents the minimum station attraction index within the deployment area that can attract residents to choose the micro-circulation bus service; β1 represents the minimum number of bus stops within the deployment area in the final scheme; β2 represents the maximum number of bus stops within the deployment area in the final scheme; δ represents the total number of candidate bus stops within the deployment area, δ=|N|; S ij M represents the station gravitational index of station j for residents of building i; i H represents the result of maximizing the gravitational exponent of all candidate sites in set N for residential building i; i Z represents the number of families living in apartment building i; j For a binary variable, it is 1 when candidate site j is retained, and 0 otherwise; U k For a binary variable, R is 1 if the plan determines to retain k bus stops, and 0 otherwise; jk To retain k bus stops in the final solution, the value is 1 if candidate stop j is included, and 0 otherwise. S4-a3. Solve the location model consisting of the optimization objective in step S4-a1 and the constraints in step S4-a2. If a solution exists, the location scheme of the micro-circulation bus station in the deployment area is obtained.

2. The micro-circulation bus stop site selection method based on the station gravity index according to claim 1, characterized in that, In step S1, the basic input data includes location data, resident data, and distance data within the deployment area. The standardization requirements for these three types of data are as follows: Location data within the deployment area is obtained from the corresponding information source network open platform for each residential building, each entrance and exit of the community, and existing bus stops. The data is then encoded and summarized to obtain their geographical latitude and longitude coordinates. Resident data within the deployment area is collected from the corresponding information source network open platform for each residential building in the community, and the community and number of households to which it belongs are obtained by encoding and summarizing. Distance data within the deployment area is obtained by acquiring actual walking distance information from each residential building to each community entrance and existing bus stop from the corresponding information source network open platform, and then encoding and summarizing it to obtain the OD table.

3. The micro-circulation bus stop site selection method based on the station gravity index according to claim 1, characterized in that, In step S2, the set of candidate micro-circulation bus stops within the deployment area consists of the set of entrances and exits of residential communities and the set of existing bus stops.

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