Public transport potential opportunity accessibility analysis method and device and medium

Abstract

The invention relates to the field of urban traffic planning and management, in particular to a public traffic potential opportunity accessibility assessment method and device and a medium, and the method comprises the steps: building a public traffic topology network, and estimating the travel time between stations in the public traffic topology network; calculating potential opportunity accessibility by taking travel time as a measure based on the potential activity person number of the grid and considering distance attenuation; and carrying out matching degree grading on the visitor demand quantity and the potential opportunity accessibility calculation result, and evaluating the public transport supply and demand suitability. Compared with the prior art, the method comprehensively considers the actual service range, distance attenuation and geographical differentiation of the public transport, can accurately evaluate the adaptation degree of the public transport to the travel demands of the passengers in different lengths, and has high application value for public transport supply and demand matching analysis, public transport network planning, public transport resource allocation and the like.

Description

Technical Field

[0001] The present invention relates to the field of urban traffic planning and management, and particularly to a method for analyzing the accessibility of potential opportunities in public transportation. Background Art

[0002] The measurement of accessibility includes methods based on spatial barriers, opportunity accumulation, and spatial interaction, etc. The method based on spatial barriers defines accessibility as the degree of difficulty in overcoming spatial barriers. The shorter the average travel time to reach other areas, the better the accessibility. The method based on cumulative opportunities means that under the premise of setting a certain travel cost, the number of opportunities that can be obtained starting from a certain location is used as a quantitative indicator of accessibility. The method based on spatial interaction is to evaluate the accessibility by comprehensively applying the potential energy of all attraction points outside a certain location to that location, and considering the distance decay factor. This method comprehensively considers traffic resistance, the attractiveness of attraction points, and the intensity of spatial interaction. The more representative ones are the gravity model method and the two-step floating catchment area method.

[0003] In recent years, some literatures have also begun to use accessibility indicators such as "bus accessible area" and "accessible range" to measure the supply of the transportation system, that is, the location-based accessibility evaluation. At this time, the supply indicator considers the actual accessible range of the transportation system, but this logic regards all regions as having equal opportunities and measures the amount of opportunities by the size of the area, which actually violates the consistency of evaluation: under the same accessible range, the accessibility at different spatial positions is different. For example, within 30 minutes, 300 grids can be reached equally, but the opportunities available in the suburbs and the central city are different.

[0004] As the solutions disclosed in Chinese patent applications CN201310462387.8 and CN202311109471.1, for the public transportation accessibility of a certain location in the city (represented by a 500m×500m grid for its location), existing research mainly measures it from the perspective of the supply capacity of bus facilities and calculates the accessibility based on the distance between the demand location and the departure location. However, this method only considers the distance between the population point and the surrounding bus stops and the number of surrounding bus stops, and does not include the actual accessible space range and the opportunities that can be obtained starting from the population point. The accessibility calculated using the disclosed solutions also shows no difference in different regions. Therefore, it neither considers the actual service capacity range of the transportation system nor the geographical differentiation of regional user travel activities; in addition, it also ignores the impact of passenger travel demand on bus services. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned existing technologies and provide a method for evaluating the accessibility of potential opportunities in public transportation.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] As a first aspect of the present invention, a method for evaluating the accessibility of potential opportunities in public transportation is provided. The steps of the method include:

[0008] Establish a public transportation topological network and estimate the travel time between stations in the public transportation topological network;

[0009] Based on the potential number of activity person-times in grids and considering distance attenuation, with travel time as a measure, calculate the potential opportunity accessibility;

[0010] Perform matching degree grading on the high and low levels of visitor demand and the calculation results of potential opportunity accessibility, and evaluate the adaptability of public transportation supply and demand.

[0011] As a preferred technical solution, the establishment of the public transportation topological network and the estimation of travel time are specifically as follows:

[0012] Project the public transportation stations onto the public transportation lines where the stations are located. According to the projection order on the public transportation lines, successively cut the lines at adjacent projected stations to form line segments. The starting point and ending point of the line segment are two adjacent projected stations. Calculate the length and travel time of the line segment to form a set of line segments ls;

[0013] Traverse all public transportation stations, set a transfer distance threshold d, establish a buffer zone with a radius of transfer distance threshold d centered on the station, extract all other stations that are not on the same line and are within the buffer zone, construct transfer edges from the central station to other stations, set the transfer speed and transfer waiting time, and calculate the transfer time to form a set of transfer edges lc;

[0014] Take the union of the set of line segments ls and the set of transfer edges lc as the edges of the network. The weight of the edge is the travel time or transfer time of the road segment. Take the set of stations as the nodes of the network to construct a public transportation topological network G;

[0015] Using the shortest path algorithm, obtain the travel time from station i to station j in the public transportation topological network G.

[0016] As a preferred technical solution, the calculation of the potential opportunity accessibility is specifically as follows:

[0017] Use the attenuation function f to fit the travel distance distribution;

[0018] Based on the attenuation function and the number of activity person-times reaching the grid, calculate the supply degree, that is, the accessibility, of the grid under the time threshold T;

[0019] Calculate the potential number of activity person-times from the departure grid to other grids with a travel duration less than the time threshold T, that is, the demand index;

[0020] Calculate the ratio of the supply degree to the demand index as the supply-demand matching index.

[0021] As a preferred technical solution, the calculation of the accessibility is specifically as follows:

[0022]

[0023] In the formula, S i (t) is the supply degree of grid i under the time threshold T; N(t) is the number of grids whose travel time using the public transportation system from grid i is less than or equal to T; j is the grid whose travel time using the public transportation system from grid i is less than or equal to T; f(t ij ) is the distance decay function; t ij is the travel duration between grids i and j; p j is the number of activity person-times of grid j.

[0024] As a preferred technical solution, the calculation of the demand index is specifically as follows:

[0025] D i (t) = ∫0 T f(t)p i dt

[0026] In the formula, f(t) is the distance decay function, representing the probability of traveling from grid i to a grid with a travel duration of t; p i is the number of activity person-times of grid i.

[0027] As a preferred technical solution, the ratio of the supply degree to the demand index is the logarithm of the travel demand within time t to the number of people that can be contacted within time t:

[0028]

[0029] In the formula, β is the theoretical fixed ratio of the supply index S and the demand index D of the grid, that is, the constant term obtained by fitting lnD = β + lnS.

[0030] As a preferred technical solution, the distance decay function satisfies ∫ t f(t)dt = 1, and the travel distance distribution uses existing resident travel survey data to represent the probability / ratio when the travel duration is t.

[0031] As a preferred technical solution, the matching degree classification is specifically divided into 6 levels, including: HH, LH, M(+), M(–), LH, LL, and HL;

[0032] Among them, the first letter is the high or low visitor demand defined according to the relative level of the demand index in the cluster center. H indicates high visitor demand, and L indicates low visitor demand;

[0033] The second letter represents the supply-demand matching status, which is divided based on the ratio of the supply degree to the demand index. H indicates oversupply, M(+) indicates potential oversupply, M(–) indicates potential shortage of supply, and L indicates shortage of supply.

[0034] As a second aspect of the present invention, there is provided an evaluation device for the accessibility of potential opportunities for public transportation, including a memory, a processor, and a program stored in the memory. When the processor executes the program, the above-mentioned method for evaluating the accessibility of potential opportunities for public transportation is implemented.

[0035] As a third aspect of the present invention, there is provided a storage medium, on which a program is stored. When the program is executed, the above-mentioned method for evaluating the accessibility of potential opportunities for public transportation is implemented.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention constructs a method for establishing a public transportation topological network based on public transportation geographic information data, realizes the rapid estimation of travel time, further comprehensively considers the actual service range of public transportation, distance attenuation and geographical differentiation, uses travel time as a measure, and determines potential travel opportunities based on the number of activity person-times in the grid obtained by statistics to calculate and evaluate the accessibility of public transportation. Compared with the prior art, the bus network is used to estimate the bus travel time, considering the actual bus service capacity starting from the grid. Based on the travel distance distribution, the supply degree of the grid is obtained by summing the potential activity person-times of the grids where the travel time is less than or equal to T; and for the activity person-times of the departure grid, the demand index is obtained by integrating with the travel time; finally, the logarithm of the ratio of the number of accessible people calculated from the two is used as the supply-demand matching index. The definition of potential activity person-times reflects the actual accessible spatial range starting from the grid, and thus can accurately evaluate the public transportation and passenger demand. Determining potential travel opportunities based on the number of activity person-times in the grid obtained by statistics to further calculate the accessibility can reflect the supply and demand requirements and travel characteristics of different regional passenger groups, and can analyze the traffic accessibility at different travel times through comparison. The solution of the present invention can accurately evaluate the adaptability of public transportation to the travel demands of different lengths of passengers, and has high application value for public transportation supply-demand matching analysis, public transportation network planning, and public transportation resource allocation, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flowchart of a method for evaluating the accessibility of potential opportunities for public transportation according to the present invention;

[0039] Figure 2 is a schematic diagram of the fitting of the travel duration distribution in one specific embodiment of the present invention; 2a) is a travel duration distribution diagram, and 2b) is a schematic diagram of the fitting of the lognormal distribution;

[0040] Figure 3 This is the spatial distribution diagram of the accessibility index in one specific embodiment of the present invention. 3a) shows the 15-minute accessibility, 3b) shows the 30-minute accessibility, 3c) shows the 45-minute accessibility, 3d) shows the 60-minute accessibility, 3e) shows the 90-minute accessibility, and 3f) shows the 120-minute accessibility;

[0041] Figure 4 This is the scatter plot of the supply-demand index in one specific embodiment of the present invention;

[0042] Figure 5 This is the cross-classification result diagram of the visitor grid matching degree and the visitor activity volume in one specific embodiment of the present invention. 5a) shows the 15-minute matching degree classification, 5b) shows the 30-minute matching degree classification, 5c) shows the 45-minute matching degree classification, 5d) shows the 60-minute matching degree classification, 5e) shows the 90-minute matching degree classification, and 5f) shows the 120-minute matching degree classification. Specific Embodiments

[0043] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented on the premise of the technical solution of the present invention, and gives the detailed implementation manner and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0044] Embodiment 1

[0045] The present invention proposes a method for establishing a public transportation topological network based on public transportation geographic information data. By establishing a public transportation topological network based on public transportation geographic information data, the rapid estimation of travel time is realized. Further, considering the actual service range of public transportation, distance decay, and geographical differentiation, the evaluation of the potential opportunity accessibility of public transportation is realized. The method flow is as Figure 1 shown:

[0046] Step 1: Establishment of the public transportation topological network and estimation of travel time

[0047] Step 1.1: Segmentation of line segments

[0048] Project the public transportation stations onto the public transportation lines where the stations are located. According to the projection order on the public transportation lines, the lines are segmented at adjacent projected stations in sequence to form line segments. The starting point and the ending point of the line segment are two adjacent projected stations. Calculate the length and travel time of the line segment to form a set of line segments ls;

[0049] Step 1.2: Setting of transfer edges

[0050] Traverse all public transportation stations, set the transfer distance threshold d, establish a buffer zone with a radius of d centered on the station, extract all other stations that are not on the same line and are within the buffer zone, construct transfer edges from the central station to other stations, set the transfer speed, calculate the transfer time, and form a set of transfer edges lc;

[0051] Step 1.3: Establishment of the topological network

[0052] Take the union of the set of line segments ls and the set of transfer edges lc as the edges of the network. The weight of the edge is the travel time of the road segment or the transfer time. Take the set of stations s as the nodes of the network to construct a public transportation topological network G;

[0053] Step 1.4: Estimation of travel time

[0054] Use the shortest path algorithm to obtain the travel time from station i to station j in the public transportation topological network G.

[0055] Step 2: Calculation of potential opportunity accessibility

[0056] Step 2.1: Setting of the distance decay function

[0057] Use the function f to fit the travel distance distribution, which satisfies ∫ t f(t)dt = 1. The travel distance distribution can also use existing resident travel survey data to represent the probability / ratio when the travel duration is t;

[0058] Step 2.2: Calculation of accessibility

[0059] Calculate the accessibility according to the following formula:

[0060]

[0061] In the formula, S i (t) is the supply degree of grid i under the time threshold T, in person-times; N(t) is the number of grids whose travel time using the public transportation system from grid i is ≤ T; j is the grid whose travel time using the public transportation system from grid i is ≤ T; f(t ij ) is the distance decay function, which satisfies ∫ t f(t)dt = 1; t ij is the travel duration between grid i and j; p j is the number of activity person-times of grid j.

[0062] Step 2.3: Calculation of demand indicators

[0063] Calculate the demand indicator, the potential number of activity person-times from grid i to other grids with a travel duration less than T, according to the following formula:

[0064] Di (t) = ∫0 T f(t)p i dt (2)

[0065] Wherein, f(t) is the distance decay function, representing the probability of traveling from grid i to the grid with a travel time of t.

[0066] Step 2.4: Calculation of supply-demand matching index

[0067] Calculate the ratio of the supply index to the demand index (Supply-Demand Ratio, SDR) according to the following formula, that is, the logarithm of the ratio of the travel demand within time t to the number of people who can be contacted within time t:

[0068]

[0069] Wherein, β is the theoretical fixed ratio of S and D, that is, the constant term obtained by fitting lnD = β + lnS. By dividing by this fixed ratio and then taking the logarithm, the supply-demand matching degree can be transformed into a measure centered on 0.

[0070] Example 2

[0071] In this example, the method described in Example 1 above is adopted to conduct an accessibility analysis on the public transportation subway and bus line networks in XX City in 2019, as well as the activity demands of visitors (out-of-town tourists coming to Shanghai) and non-visitors (local residents) in May 2019 extracted from mobile phone signaling data. The specific steps are as follows:

[0072] Step 1: Establishment of public transportation topological network and estimation of travel time

[0073] 1.1: Segmentation of line segments

[0074] Project the public transportation stations onto the public transportation lines where they are located. According to the projection order on the public transportation lines, segment the lines successively at adjacent projected stations to form line segments. The starting point and ending point of the line segment are two adjacent projected stations. Set the subway travel speed at 35 km / h and the bus travel speed at 17.5 km / h, and calculate the length and travel time of the line segments to form a line segment set ls;

[0075] 1.2: Setting of transfer edges

[0076] Traverse all public transportation stations, set the transfer distance threshold d = 500 m, establish a buffer zone with a radius of d centered on the station, extract all other stations that are not on the same line and are within the buffer zone, construct transfer edges from the central station to other stations, set the transfer speed v = 0.8 m / s, the average waiting time after transfer is 7.5 min for buses and 2.5 min for subways, calculate the transfer time, and form a transfer edge set lc;

[0077] 1.3: Establishment of Topological Network

[0078] Take the union of the line segment set ls and the transfer edge set lc as the edges of the network. The weight of the edge is the travel time of the road segment or the transfer time. Take the station set s as the nodes of the network to construct the public transportation topological network G;

[0079] 1.4: Estimation of Travel Time

[0080] Using the shortest path algorithm, obtain the travel time from station i to station j in the public transportation topological network G, as shown in Table 3.

[0081] Table 3 Estimation Results of Travel Duration

[0082]

[0083] Step 2: Calculation of Potential Opportunity Accessibility

[0084] 2.1: Setting of distance decay function, use the function f to fit the travel distance distribution. After analysis, the travel duration distribution follows a lognormal distribution with a mean of 2.929 and a standard deviation of 0.7771. The distribution is shown in Figure 2 .

[0085] 2.2: Calculate accessibility. The spatial distribution of accessibility is shown in Figure 3 .

[0086] 2.3: Calculate the demand index: The potential number of activity person-times from grid i to other grids with a travel duration less than t.

[0087] 2.4: Calculation of supply-demand matching index

[0088] Calculate the ratio of the supply index to the demand index (Supply-Demand Ratio, SDR). The scatter plot of the supply and demand indexes is shown in Figure 4 , and the fixed ratio of the two is e –6.41 .

[0089] With the above accessibility analysis method, taking the difference in the adaptation of public transportation supply and demand between visitors and non-visitors as an example, the following perspectives of evaluation can be carried out (Table 4).

[0090] Table 4 Applicability of Evaluation Framework

[0091]

[0092]

[0093] Taking the optimization of the public transportation system for the visitor population as an example, the accessibility evaluation of the present invention can be analyzed as follows:

[0094] The calculated matching degree evaluation results for visitors and non-visitors are shown in the figure. The matching degree is classified according to the high or low demand of visitors and the high or low of visitor SDR. The classification criteria are shown in Table 5 and are divided into 6 levels: A-HH, B-LH, C-M(+), D-M(–), E-LL, and F-HL. The first letter after the dash is the high or low demand of visitors defined according to the relative high or low of the demand index in the clustering center, and the second letter represents the supply-demand matching status, including H for oversupply, M(+) for potential oversupply, M(–) for potential shortage of supply, and L for shortage of supply. According to the data distribution, the cut-off points are set at –2, 0, and 2. For example, C-HM(+) means high demand and potential oversupply, and the grid evaluated as C level. Figure 5 Stratified coloring is carried out according to different demand levels. Red indicates high demand, and blue indicates low demand. The lighter the color, the better the supply-demand degree:

[0095] Spatially, from the central city outwards, the matching degree first increases and then decreases (M-H-M-L). The areas with higher matching degrees are concentrated near subway stations in the suburbs (outside the inner ring), and the areas with low matching degrees are widely distributed in the suburbs, especially in the northwestern Jiading District and the south. There are also areas with low matching degrees in the hot spots of visitor activities in the central city, such as People's Square, Disneyland, and Pudong Airport. From the central city outwards, the number of visitor activities gradually decreases (H-L). Therefore, the overall supply-demand matching pattern of public transportation on the grid can be described as a state of high supply and high demand - high supply and low demand - low supply and low demand.

[0096] Temporally, with the increase in the accessibility evaluation time, the inter-regional differences in the supply-demand matching degree weaken. Under the accessibility measure of less than 30 minutes, the central city shows a better matching pattern, while the suburbs are generally weaker. Under the accessibility measure of more than 90 minutes, the regions are relatively balanced. This shows that in the suburbs, the adaptability of public transportation to the short-distance travel needs of visitors is weaker.

[0097] As shown in Table 5, for different levels, the following public transportation concerns and improvement suggestions for the visitor population can be put forward:

[0098] Table 5 Public transportation concerns and improvement suggestions for the visitor population

[0099]

[0100]

[0101] Example 2

[0102] As a second aspect of the present invention, the present application further provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned public transportation potential opportunity accessibility analysis method. In addition to the above-mentioned processors, memory, and interfaces, any device with data processing capabilities where the device in the embodiment is located may generally include other hardware according to the actual functions of the device with data processing capabilities, which will not be elaborated here.

[0103] Embodiment 3

[0104] As a third aspect of the present invention, the present application further provides a computer-readable storage medium, on which computer instructions are stored, and when the instructions are executed by a processor, the above-mentioned public transportation potential opportunity accessibility analysis method is implemented. The computer-readable storage medium may be an internal storage unit of any device with data processing capabilities described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium may also be an external storage device, such as a plug-in hard disk, a Smart Media Card (SMC), an SD card, a Flash Card, etc. equipped on the device. Further, the computer-readable storage medium may also include both an internal storage unit of any device with data processing capabilities and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and may also be used to temporarily store data that has been output or will be output.

[0105] The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations based on the concept of the present invention without creative work. Therefore, any technical solutions that can be obtained by those skilled in the art in the technical field of the present invention through logical analysis, reasoning, or limited experiments based on the concept of the present invention on the basis of the prior art should be within the protection scope determined by the claims.

Claims

1. A method for evaluating the accessibility of potential opportunities in public transportation, characterized in that the steps Including: Establish a public transportation topological network and estimate the travel time between stations in the public transportation topological network; Based on the potential number of active people in the grid and considering distance decay, using the travel time as a measure, calculate the potential opportunity accessibility; Perform a matching degree grading on the high and low levels of visitor demand and the calculation results of potential opportunity accessibility, and evaluate the adaptability of public transportation supply and demand.

2. The public transport potential opportunity accessibility evaluation method according to claim 1, wherein The establishment of the public transportation topological network and the estimation of travel time are specifically as follows: Project the public transportation stations onto the public transportation lines where the stations are located. According to the projection order on the public transportation lines, sequentially cut the lines at adjacent projected stations to form line segments. The starting point and ending point of the line segment are two adjacent projected stations. Calculate the length and travel time of the line segment to form a set of line segments ls; Traverse all public transportation stations, set a transfer distance threshold d, establish a buffer zone with a radius of the transfer distance threshold d centered on the station, extract all other stations that are not on the same line and are within the buffer zone, construct transfer edges from the central station to other stations, set the transfer speed and transfer waiting time, calculate the transfer time, and form a set of transfer edges lc; Take the union of the set of line segments ls and the set of transfer edges lc as the edges of the network. The weight of the edge is the travel time or transfer time of the road section. Take the set of stations as the nodes of the network to construct a public transportation topological network G; Using the shortest path algorithm, obtain the travel time from station i to station j in the public transportation topological network G.

3. A method for evaluating the accessibility of potential opportunities in public transportation according to claim 1, characterized in that, The calculation of the potential opportunity accessibility is specifically as follows: Use the attenuation function f to fit the travel distance distribution; Based on the attenuation function and the number of active people reaching the grid, calculate the supply degree of the grid under the time threshold T, that is, the accessibility; Calculate the potential number of active people from the departure grid to other grids with a travel duration less than the time threshold T, that is, the demand index; Calculate the ratio of the supply degree to the demand index as the supply-demand matching index.

4. The public transportation potential opportunity accessibility evaluation method according to claim 3, characterized in that The calculation of the accessibility is specifically as follows: Where S i (t) is the supply degree of grid i under the time threshold T; N(t) is the number of grids whose travel time using the public transportation system starting from grid i is less than or equal to T; j is the grid whose travel time using the public transportation system starting from grid i is less than or equal to T; f(t ij ) is the distance decay function; t ij is the travel duration between grids i and j; p j is the number of activity people in grid j.

5. The method for evaluating the accessibility of potential opportunities in public transportation according to claim 3, wherein, The calculation of the demand index is specifically as follows: D i (t) = ∫0 T f(t)p i dt where f(t) is the distance attenuation function, representing the probability of traveling from grid i to a grid with a duration of t; p i is the number of active people in grid i.

6. The method for evaluating the accessibility of potential opportunities for public transportation according to claim 3, wherein The ratio of the supply degree to the demand index is the logarithm of the ratio of the travel demand within time t to the number of people that can be contacted within time t: In the formula, β is the theoretical fixed ratio of the supply index S and the demand index D of the grid, that is, the constant term obtained by fitting lnD = β + lnS.

7. A method for evaluating the accessibility of potential opportunities in public transportation according to any one of claims 3-6, characterized in that The described distance decay function satisfies ∫ t f(t)dt = 1, and the trip distance distribution uses existing household travel survey data to represent the probability / share when the travel time is t.

8. A method for evaluating the accessibility of potential opportunities in public transportation according to claim 1, characterized in that, The matching degree grading is specifically divided into 6 levels, including: HH, LH, M(+), M(–), LH, LL, and HL; Among them, the first letter is the high and low level of visitor demand defined according to the relative level of the demand index in the cluster center. H represents high visitor demand, and L represents low visitor demand; The second letter represents the supply-demand matching situation, which is divided based on the ratio of the supply degree to the demand index. H represents oversupply, M(+) represents potential oversupply, M(–) represents potential supply shortage, and L represents supply shortage.

9. A public transportation potential opportunity accessibility evaluation device, comprising a memory, a processor, and a program stored in the memory, characterized in that, When the processor executes the program, it implements the public transportation potential opportunity accessibility evaluation method as described in any one of claims 1-8.

10. A storage medium, on which a program is stored, characterized in that, When the program is executed, it implements the public transportation potential opportunity accessibility evaluation method as described in any one of claims 1-8.

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