CN112765753B - Public transport super network construction method - Google Patents
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Abstract
The invention discloses a construction method of a public transport super network, which comprises the following steps: s1: carrying out spatial correction and redundancy processing on the original data of the public transport network; s2: constructing a virtual connection arc of public transport, and simulating a real world travel path; s3: constructing a virtual connecting arc of the subway station and the road; s4: constructing road section impedance functions of all driving arcs and virtual connecting arcs; s5: constructing a public transport super network formed by fusing all driving arcs and virtual connecting arcs; and S6, constructing a public transport super network topological structure. The invention considers the defects brought by the time efficiency and the precision of constructing the public transportation network by utilizing the traditional GIS software, and provides a construction method of the public transportation super network based on GeoPandas.
Description
Technical Field
The invention relates to the field of traffic planning, in particular to a construction method of a public traffic super network.
Background
With the continuous enlargement of urban rail transit network scale and the continuous perfection of structure, conventional public transportation and rail transit are in a competitive and complementary state, the attraction of rail transit to public transit travelers is far stronger than that of conventional public transportation, but the accessibility of conventional public transportation is superior to rail transit, and public transit users often achieve the purpose of reducing generalized travel cost through the mixed use of conventional public transportation and rail transit.
However, in the research of the existing public transportation network, most of the public transportation networks aim at a single transportation mode, and the network structure is simple. With the development of technology and economy, a single-mode traffic network is no longer suitable, a traffic network mixing multiple traffic modes can reflect the urban traffic condition of the current society more truly, and the research on the multi-mode traffic network gradually becomes the research focus of urban traffic planning.
The super network is characterized in that various different networks are fused together in a virtual connection arc constructing mode, complex relations among the networks can be well expressed through mutual fusion of multiple layers of networks, mutual influences among sub-networks at all levels are expressed in a virtual connection constructing mode, abstract problems can be specified, and the complex problems are simplified.
If a technical means can be provided, the urban public transport super network can be quickly constructed and analyzed into a language which can be identified by a program, so that the timeliness and the precision of the traditional network construction can be improved, and a better input is provided for a traffic prediction model, thereby providing technical support for traffic decision.
Disclosure of Invention
The invention aims to solve the technical problem of providing a construction method of a public transport super network aiming at the defects of timeliness and precision existing in the prior art that a single traffic mode is adopted for modeling prediction and GIS software is adopted for constructing a network model, so that the precision of the prediction model can be improved in the aspect of traffic planning, and support is provided for traffic decision.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention provides a construction method of a public transport super network, which comprises the following steps:
s1: performing spatial correction and redundancy processing on GIS data of the public transport network, performing interruption processing on the processed public transport line, and taking the processed public transport line as a driving arc;
s2: constructing virtual connecting arcs of various travel paths in the simulated real public transport by using a geographic data visualization tool GeoPandas according to the broken public transport lines generated in the step S1;
s3: constructing a virtual connecting arc of the subway station and the road by utilizing a geographic data visualization tool GeoPandas;
s4: constructing road section impedance functions of all driving arcs and virtual connecting arcs;
s5: fusing all driving arcs and virtual connecting arcs generated in the steps S1-S3 into a public transport super network according to the road section impedance function obtained in the step S4;
and S6, constructing a public transport super network topological structure and establishing a public transport super network which can be identified by computer languages.
Further, in step S1 of the present invention, the processing of the GIS data of the public transportation network includes the specific steps of:
s1.1: acquiring GIS data of conventional public transport, rail transit, ferry, BRT, basic road network and traffic cell mass center;
s1.2: aiming at the problem of deviation of GIS data of conventional public transport, rail transit, ferry, BRT and basic road networks, the space correction is carried out on other networks on the basis of the conventional public transport network;
s1.3: processing redundant and disordered site GIS data;
s1.4: and (4) vertically breaking the line data of the same traffic mode by using the station data, and extracting breakpoint GIS data.
Further, the step S2 of the present invention includes constructing various virtual connecting arcs for simulating the traveling behavior of the traveler, that is, constructing virtual connecting arcs of the traffic cell centroid and the bus station, the cell centroid and the subway station, the bus station and the bus line, the bus station and the road, the subway station and the subway line, and the bus station and the subway station within a certain distance range, and the specific steps are as follows:
s2.1: based on a point at one end of a virtual connecting arc to be constructed, namely a reference point, searching a certain number of nearest break points or reference points, namely search points, and calculating coordinates of the points;
s2.2: the calculation formula for calculating the distance between the reference point and the search point is as follows:
wherein x is 1 、y 1 Is the horizontal and vertical coordinate of the reference point, x 2 、y 2 Horizontal and vertical coordinates of the search point are shown;
s2.3: screening search points within the specified distance range according to the result calculated in the step S2.2;
s2.4: constructing a virtual connecting arc according to the known coordinates;
s2.5: and according to the steps S2.1-S2.4, sequentially constructing different types of virtual connecting arcs according to the requirements of different types of virtual connecting arcs, including distance and number.
Further, the step S3 of the present invention includes:
the method comprises the following steps of (1) constructing a virtual connection arc of the subway station and the road, wherein the only difference from S2 is as follows: and searching a search point closest to the reference point in the S2.1, wherein the S3 is similar to the establishment of the centroid connecting rod, does not search the closest search point but randomly searches a road breakpoint in a certain range, and then builds a virtual connecting arc by using a geographic data visualization tool GeoPandas according to the steps S2.2-S2.4.
Further, in step S4 of the present invention, the geographic data visualization tool GeoPandas is used to construct impedance functions of various road segments, which is specifically as follows:
where C (i, j) is the combined impedance of an OD centering path; m is m road segments constituting the path; f k (i, j) is the cost of the kth road segment (i, j); t is a unit of k (i, j) is the time impedance of the kth link (i, j); e is the set of all road segments in one OD pair;
s4.1: constructing impedance functions of virtual connection arcs of a basic road network, a traffic cell mass center and a bus station, a cell mass center and a subway station, a subway station and a road, a bus station and a road, and a bus station and a subway station; the road section has no cost impedance and only contains time impedance, and the time impedance function is expressed as:
in the formula, T walk (i, j) is the time impedance of the segment (i, j) in the network; lambda [ alpha ] walk Converting coefficients for the time weights of the walking sections; l walk (i, j) is the length of the link (i, j), in km; v walk The walking speed is in km/h; e walk Is a collection of walking network edges;
s4.2: constructing an impedance function of a conventional bus section; transferring the monetary cost of a bus trip to a connection arc between a bus station and a bus line, no longer considering cost impedance in a bus network, only considering time impedance, expressed as:
in the formula, T bus (i, j) is the time impedance of the bus segment (i, j); lambda bus Converting the time weight of the bus section into a coefficient; l. the bus (i, j) is the length of the link (i, j), in km; v bus The unit is the travel speed of the bus section, namely km/h; rho ij A congestion degree coefficient for a conventional bus section (i, j); e bus Is a set of conventional public transport network edges;
s4.3: constructing an impedance function of a rail transit road section; the cost impedance calculation formula is as follows:
F sub (i，j)＝η sub ρ sub l sub (i，j)，(i，j)∈E sub
in the formula, F sub (i, j) a cost impedance of the rail transit section (i, j); eta sub Converting the cost weight into a coefficient for the track traffic section; rho sub Average cost per kilometer, unit/km; l sub (i, j) is the length of the link (i, j), in km; e sub A set of rail transit network edges;
the time impedance function is expressed as:
in the formula, T sub (i, j) is the time impedance of the rail transit section (i, j); lambda [ alpha ] sub Converting the time weight into a coefficient for the track traffic section; l sub (i, j) is the length of the track traffic section (i, j) in km; v sub The unit is the travel speed of the rail transit road section, namely km/h; rho ij A congestion degree coefficient of the track traffic section (i, j);
s4.4: constructing an impedance function of a bus station and a virtual connection arc of a bus line; the arc time impedance of the connection between the bus station and the bus line is mainly derived from the waiting time, and the cost impedance is derived from the bus taking cost of the bus; the connection arc impedance function calculation formula is as follows:
F bus_con (i，j)＝c bus_con n bus_con ，(i，j)∈E bus_con
T bus_con (i，j)＝λ bus_con T bus_con ，(i，j)∈E bus_con
in the formula, F bus_con (i, j) is the cost impedance of the bus stop and the bus line connection arc section (i, j); t is bus_con (i, j) is the time impedance of the bus stop and the bus line connection arc section (i, j); c. C bus_con In order to share the cost of the connecting arc of the bus for getting on and off, the fare is half of the fare; n is bus_con A cost weight conversion coefficient for a bus stop and a bus line connection arc section (i, j); lambda [ alpha ] bus_con Time weight conversion coefficient of the arc road section (i, j) connecting the bus station and the bus line; t is a unit of bus_con The average waiting time is the average waiting time; e bus_con Representing a set of connecting arcs between a conventional bus station and a bus line;
s4.5: constructing an impedance function of a virtual connection arc of a rail transit station and a rail transit line; the connecting arc does not have cost impedance, only has time impedance, the time impedance is divided into two parts, one part is the time from walking to waiting points of the rail transit stations, the solution is carried out according to walking distance, and the other part is waiting time;
in the formula, T sub_con (i, j) is the time impedance of the track traffic station and the track traffic line connection arc section (i, j); lambda walk Converting the time utility weight coefficient of the walking road section; l sub_con (i, j) is the length of a track traffic station and a track traffic line connection arc section (i, j), and the unit is km; v. of walk The walking speed is the unit km/h; lambda [ alpha ] sub_con Converting the weight of the waiting time of the rail transit into a coefficient; t is sub_con The average waiting time is taken; e sub_con And representing the set of the connection arcs of the rail transit station and the rail transit line.
Further, the step S5 of the present invention includes:
s5.1: processing the attributes of various driving arcs and connecting arcs, and giving specific attributes to the driving arcs and the connecting arcs, wherein the specific attributes comprise the following steps:
and kind =1: a base road network;
and kind =2: virtual connecting rods of the mass center and the bus station and the mass center and the subway station;
and kind =3: a subway line;
and kind =4: a virtual connecting arc of a subway station and a road;
and kind =5: the bus lines comprise conventional bus lines, ferries and BRT lines;
and king =6: a virtual connection arc of the bus station and the bus line;
and kind =7: virtual connection arcs of the bus station and the road;
and kind =8: a virtual connecting arc of the subway station and the subway line;
and kid =9: virtual connection arcs of the bus station and the subway station.
S5.2: and processing the attribute of the virtual connection arc with the kind =2 by using a geographic data visualization tool GeoPandas, and adding a TAZ field to enable the connection arc to inherit the serial number attribute of the traffic cell.
S5.3: and fusing the processed driving arc with the kind =1-kind =9 and the virtual connecting arc by using a geographic data visualization tool GeoPandas to construct a public transportation super network.
Further, the step S6 of the present invention includes:
and constructing a public transport super network topological structure, constructing an adjacency matrix, and establishing a public transport super network which can be identified by computer languages.
The invention provides a construction device of a public transport super network, which comprises the following modules:
the original data processing module is used for checking the public transport network and the basic road network by using a conventional public transport network as a reference; redundant sites are processed, only one site is reserved for the same site, and the sites are ensured not to be on line; breaking the corresponding public transportation line by using the processed station;
the virtual connecting arc module is used for searching a certain number of searching points which are closest to the station serving as a reference point; calculating coordinates of all points; constructing a virtual connecting arc according to the coordinates;
the virtual connection arc module of the subway station and the road searches for road breakpoints within a certain distance range by taking the subway station as a reference point, but the breakpoints are not necessarily the nearest breakpoints; calculating coordinates of all points; constructing a virtual connecting arc according to the coordinates;
the road section impedance function module is used for establishing a road section impedance function model and indicating that different types of lines have different costs;
the public transportation super network module performs fusion processing according to all processed running arcs and virtual connection arcs to construct a complete public transportation super network;
the public transport super network topological structure module is used for providing a computer language for identification and laying a foundation for path search and network distribution by using the computer language.
The invention has the following beneficial effects: the method for constructing the public transport super network fully considers the influence of all public transport modes, utilizes the rail transit data, the conventional public transport data, the ferry data and the BRT data to construct the method for constructing the public transport super network, simulates the trip behavior of a traveler by constructing various virtual connection arcs by utilizing GeoPandas, and finally constructs the public transport super network and the topological structure thereof, thereby greatly improving the time efficiency and the precision of the traditional construction method.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a method for constructing a public transportation super network according to an embodiment of the present invention;
fig. 2 is a technical route diagram of a processing site using GeoPandas according to an embodiment of the present invention.
Fig. 3 is a flowchart of constructing a virtual connection arc of a public transportation super network by using GeoPandas according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Fig. 1 is a schematic flow chart of a method for constructing a public transportation super network according to an embodiment of the present invention, which includes the following steps:
s1: carrying out spatial correction and redundancy processing on the public transport GIS network data, and carrying out interruption processing on the processed public transport lines;
in the embodiment of the present invention, in step S1, the processing of the original public transportation GIS data specifically includes the following steps:
s1.1: acquiring GIS data such as conventional public transport, rail transit, ferry, BRT, basic road network, mass center of a traffic cell and the like;
in the embodiment of the invention, 2019 data are selected as a model input end, and each public transport sub-mode has information such as lines, stations and the like; the traffic cell centroid should be generated using the traffic cell map layer.
Various public transport network information in the OSM webpage is acquired through a python technology; the traffic cell centroid is constructed by utilizing Geopandas technology.
S1.2: aiming at the problem of deviation of GIS data such as conventional public transport, rail transit, ferry, BRT and basic road network, and the like, the space correction is carried out on other networks on the basis of the conventional public transport network;
the embodiment of the invention selects the conventional public transport network as the basis to carry out spatial correction on the rail transit, the ferry, the BRT and the basic road network which may have the deviation.
By means of GIS technology, conventional public transport network is used as reference layer, and other networks may be corrected by adding proper correction points to the other networks to make the networks consistent in spatial position.
S1.3: processing redundant and disordered site GIS data;
there are n homonymous stations among the stations in the public transportation sub-network, but the form is disordered in spatial position, and n depends on the number of lines passing through a certain station. In fact, in real life, the physical location of most sites is only 1, and almost all lines passing through are connected. Therefore, the embodiment of the invention processes the disordered sites, and only 1 site is reserved in the same direction.
Fig. 2 shows a method for processing a cluttered and redundant site by using the GeoPandas technology.
According to the GeoPandas technology, firstly, based on site names, file data are sequenced, a variable temp is defined, the 1 st site is taken as the temp, and if the 1 st site is the same as the 2 nd site in name, the 2 nd site is deleted; if the 2 nd site is not the same as the 3 rd site in name, the (n + 2) th site is reserved and marked as temp, and the iterative judgment is carried out in sequence, and only 1 site is reserved for the same site name finally.
S1.4: line data of the same traffic mode are vertically interrupted by utilizing station data, and breakpoint GIS data are extracted;
in order to simulate the change of a traveler from one mode of transportation to another mode of transportation or get on or off a bus, a station needs to be connected to a road and a corresponding public line, and if the station is directly connected without interruption, the traveler cannot actually change from one mode of transportation to another mode of transportation or get on or off the bus in the model.
The method comprises the steps of inputting corresponding bus route layers or road network layers for interruption processing and extracting breakpoint layers by utilizing a GIS technology on the basis of stations.
S2: constructing virtual connecting arcs of various simulated real travel paths by using GeoPandas according to the broken public transport lines generated in the step 1;
fig. 3 shows a method for constructing a virtual connection arc by using GeoPandas technology.
In the embodiment of the present invention, step S2 includes constructing a virtual connection arc that simulates the trip behavior of a traveler, that is, constructing virtual connection arcs of a traffic cell centroid and a bus station (including a conventional bus, a ferry and a BRT), a cell centroid and a subway station, a bus station and a bus line, a bus station and a road, a subway station and a subway line, and a bus station and a subway station within a certain distance range, and specifically includes the following steps:
s2.1: based on the point at one end of the virtual connecting arc to be constructed (reference point), searching a certain number of nearest break points or reference points (search points), and calculating the coordinates of the points;
the rail transit station, the conventional bus station, the ferry station and the BRT station are used as reference points, and the rail transit line, the conventional bus line breakpoint, the ferry line breakpoint, the BRT line breakpoint, the road network breakpoint and the reference points can be used as search points.
Inputting a reference point and a search point layer to be searched by utilizing a python technology, and searching a certain number of search points closest to the reference point on the basis of the reference point; and respectively calculating the coordinates of the two and connecting the attributes of the search points to the reference point layer. In the embodiment of the invention, the number of the connected arcs is different.
S2.2: calculating the distance between the reference point and the search point;
and establishing a length field in the reference point layer, calculating the distance between the reference point and the search point and filling. The formula is as follows:
wherein x 1 、y 1 Is the horizontal and vertical coordinates of a reference point, x 2 、y 2 The horizontal and vertical coordinates of the search point are shown.
S2.3: screening search points within the specified distance range according to the result calculated in the S2.2;
and reading the reference point image layer by using a GeoPandas technology, taking out the reference point site name and the length result calculated in S2.2, and judging whether the length is within a specified distance range. If not, the piece of data is deleted. The embodiment of the invention sets different distance requirements for different virtual connecting arcs, so that the set specified distances are different during screening.
S2.4: constructing a virtual connecting arc according to the known coordinates;
and reading the reference point layer processed by S2.3 by utilizing a GeoPandas technology, and constructing a virtual connection arc according to coordinate information in the layer attribute. Firstly, calculating the data length of a reference point file, and then traversing the attribute data of the file, wherein the method specifically comprises the following steps: taking out the 1 st data and storing the data into a newly-built attribute table; coordinates of the reference point and the search point in the 1 st data are taken out, and a virtual connecting arc of the two points is established according to the coordinates; storing the constructed virtual connection arc into the newly-built geomList; and completing traversing to the last piece of data and creating a connecting arc. And constructing a geoDataFrame by using the created and filled attribute and the geoList, defining coordinates and outputting the file.
S2.5: and according to the steps S2.1-S2.4, sequentially constructing different types of virtual connecting arcs according to the requirements of different types of virtual connecting arcs, such as distance, quantity and the like.
S3: constructing a virtual connecting arc of the subway station and the road by utilizing GeoPandas;
in the embodiment of the invention, in the step S3, a virtual connection arc of the subway station and the road is constructed, and the only difference from the step S2 is that: the searching point closest to the reference point is searched in S2.1, S3 is similar to the creating of the traffic cell centroid connecting rod, the closest searching point is not searched, the road break point in a certain range is randomly searched, and then the virtual connecting arc is constructed according to S2.2-S2.4.
S4: constructing road section impedance functions of all driving arcs and virtual connecting arcs;
in the process of using public transport to travel by urban public transport travelers, the travelers generally need to comprehensively consider the time, cost and other factors of each feasible route from a travel starting point r to a travel ending point s. The impedance of each path section in the public transport super network is independent, and the impedance of one feasible path which can be selected by a public transport traveler can be expressed as the sum of the impedance of each path section, namely:
where C (i, j) is the combined impedance of an OD centering path; m is m road segments constituting the path; f k (i, j) is the cost of the kth road segment (i, j); t is k (i, j) is the time impedance of the kth link (i, j); e is the set of all segments in one OD pair.
S4.1: and constructing impedance functions of virtual connection arcs of a basic road network, a traffic cell mass center and a bus station, a cell mass center and a subway station, a subway station and a road, a bus station and a road and a bus station and a subway station. The road section has no cost impedance and only contains time impedance, the time impedance is related to the length of the road section and the walking speed, and the impedance function can be expressed as:
in the formula, T walk (i, j) is the time impedance of the segment (i, j) in the network; lambda walk Converting the time weight of the walking road section into a coefficient; l walk (i, j) is the length (km) of the road section (i, j); v walk Walking speed (km/h); e walk Is a collection of walking network edges.
S4.2: and constructing an impedance function of the conventional bus section. The monetary cost of bus travel is transferred to the connecting arc between the bus stop point and the bus line, and the fact that a certain cost is paid through the connecting arc when a bus is taken every time is more consistent with the practical situation, and the cost impedance is not considered in the bus network, and only the time impedance is considered. The time impedance function can be expressed as:
in the formula, T bus (i, j) is the time impedance of the bus segment (i, j); lambda [ alpha ] bus Converting the time weight of the bus section into a coefficient; l bus (i, j) is the length (km) of the link (i, j); v bus The travel speed (km/h) of the bus section; rho ij A congestion degree coefficient for a conventional bus section (i, j); e bus Is a collection of conventional public transportation network edges.
S4.3: and constructing an impedance function of the rail transit road section. The cost impedance calculation formula of the rail transit is as follows:
F sub (i，j)＝η sub ρ sub l sub (i，j)，(i，j)∈E sub
in the formula, F sub (i, j) a cost impedance of the rail transit section (i, j); eta sub Converting the cost weight into a coefficient for the track traffic section; rho sub Average cost per kilometer (yuan/km); l sub (i, j) is the length (km) of the link (i, j); e sub A set of rail transit network edges.
The time impedance function can be expressed as:
in the formula, T sub (i, j) is the time impedance of the rail transit section (i, j); lambda [ alpha ] sub Converting the time weight into a coefficient for the track traffic section; l sub (i, j) is the length (km) of the rail transit section (i, j); v sub The travel speed (km/h) of the rail transit road section; rho ij The congestion degree coefficient of the track traffic section (i, j);
s4.4: and constructing an impedance function of the bus station and the virtual connection arc of the bus line. The bus stop and the bus line connecting arc are used by travelers to transfer from the bus stop to a bus section, and have time impedance and cost impedance, wherein the time impedance mainly comes from waiting time, and the cost impedance comes from bus taking cost.
Based on the above analysis, the connection arc impedance function calculation formula is as follows:
F bus_con (i，j)＝c bus_con n bus_con ，(i，j)∈E bus_con
T bus_con (i，j)＝λ bus_con T bus_con ，(i，j)∈E bus_con
in the formula, F bus_con (i, j) is the cost impedance of the bus stop and the bus line connection arc section (i, j); t is bus_con (i, j) is the time impedance of the bus stop and the bus line connection arc section (i, j); c. C bus_con In order to share the cost of the connecting arc of the bus for getting on and off, the fare is half of the fare; n is bus_con A cost weight conversion coefficient for a bus stop and a bus line connection arc section (i, j); lambda bus_con Time weight conversion coefficient of the arc road section (i, j) connecting the bus station and the bus line; t is bus_con The average waiting time is the average waiting time; e bus_con And represents the set of the connecting arcs of the conventional bus station and the bus line.
S4.5: and constructing an impedance function of the virtual connection arc of the rail transit station and the rail transit line.
The rail transit station and the rail transit line are connected in an arc manner, so that travelers can transfer between the rail transit station and the rail transit line for use, the travelers do not have cost impedance and only have time impedance, the time impedance is divided into two parts, one part is the time from walking of the rail transit station to a waiting point, the solution is carried out according to the walking distance, and the other part is the waiting time.
Wherein, T sub_con (i, j) is the time impedance of the track traffic station and the track traffic line connection arc section (i, j); lambda [ alpha ] walk Converting the time utility weight coefficient of the walking road section; l sub_con (i, j) is the length (km) of the connection arc road section (i, j) of the rail transit station and the rail transit line; v. of walk Walking speed (km/h); lambda [ alpha ] sub_con For track trafficA vehicle time weight conversion coefficient; t is sub_con The average waiting time is taken; e sub_con Representing the set of connection arcs of the rail transit station and the rail transit line.
S5: fusing the driving arc and the connecting arc processed in the S4 into a public transportation super network;
s5.1: and (4) creating a kid field for each layer by utilizing a GeoPandas technology, and giving specific attributes to different types of road sections. The following were used:
and kind =1: representing a base road network;
and kind =2: virtual connecting rods representing the mass center and the bus station and the mass center and the subway station;
and kind =3: representing a subway line;
and king =4: representing a virtual connecting arc of the subway station and the road;
and kind =5: representing bus lines (including conventional bus lines, ferry and BRT lines)
And kind =6: a virtual connecting arc representing a bus station and a bus line;
and king =7: representing a virtual connection arc of the bus station and the road;
and kind =8: representing a virtual connecting arc of the subway station and the subway line;
and kid =9: representing a virtual connecting arc of a bus station and a subway station.
S5.2: and processing the attribute of the virtual connecting arc with the kid =2, and adding a TAZ field to enable the connecting arc to inherit the serial number attribute of the traffic cell.
S5.3: and fusing the processed driving arc with the kid = 1-kid =9 with the virtual connecting arc by using GeoPandas to construct a public transport super network.
S6: and constructing a public transport super network topological structure and establishing a public transport super network which can be identified by computer languages.
The public transportation super network topological structure is used for constructing an adjacency matrix and numbering all road sections. Firstly, numbering the public transportation super network constructed in S5 by utilizing a GIS technology; and acquiring all serial numbers and attribute information by using a GeoPandas technology, and transmitting the serial numbers and the attribute information to a MySQL database for computer language identification.
Fig. 4 is a schematic structural diagram of an apparatus provided in an embodiment of the present invention, including:
the original data processing module 401 is used for checking other public transportation networks and basic road networks by using a conventional public transportation network as a reference; processing redundant sites, and only one same site is reserved to ensure that the sites are not on line; and breaking the corresponding public transportation line by using the processed station.
A virtual connecting arc module 402, which searches a certain number of nearest search points with a site as a reference point; calculating coordinates of all points; constructing a virtual connecting arc according to the coordinates;
the virtual connection arc module 403 of the subway station and the road searches for a road breakpoint within a certain distance range with the subway station as a reference point, but not necessarily a closest breakpoint; calculating coordinates of all points; constructing a virtual connecting arc according to the coordinates;
a section impedance function module 404, configured to establish a section impedance function model, which indicates that different types of lines have different costs;
the public transportation super network module 405 performs fusion processing according to all processed driving arcs and virtual connection arcs to construct a complete public transportation super network;
the public transportation super network topology structure module 406 is used for providing a computer language for identification, and can lay a foundation for path search and network distribution by using the computer language.
The specific implementation of each module may refer to the description of the above method embodiment, and the embodiment of the present invention will not be repeated.
It should be noted that, according to the implementation requirement, each step/component described in the present application can be divided into more steps/components, and two or more steps/components or partial operations of the steps/components can be combined into new steps/components to achieve the purpose of the present invention.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (4)
1. A method for constructing a public transportation super network is characterized by comprising the following steps:
s1: performing spatial correction and redundancy processing on GIS data of the public transport network, performing interruption processing on the processed public transport line, and taking the processed public transport line as a driving arc;
s2: constructing virtual connecting arcs of various travel paths in the simulated real public transport by using a geographic data visualization tool GeoPandas according to the broken public transport lines generated in the step S1;
s3: constructing a virtual connecting arc of the subway station and the road by utilizing a geographic data visualization tool GeoPandas;
s4: constructing road section impedance functions of all driving arcs and virtual connecting arcs;
s5: fusing all driving arcs and virtual connecting arcs generated in the steps S1-S3 into a public transport super network according to the road section impedance function obtained in the step S4;
s6: constructing a public transport super network topological structure and establishing a public transport super network which can be identified by computer languages;
in the step S1, the GIS data of the public transportation network is processed, and the specific steps are as follows:
s1.1: acquiring GIS data of conventional public transport, rail transit, ferry, BRT, basic road network and traffic cell mass center;
s1.2: aiming at the problem of deviation of GIS data of conventional public transport, rail transit, ferry, BRT and basic road network, the space correction is carried out on other networks on the basis of the conventional public transport network;
s1.3: processing redundant and disordered site GIS data;
s1.4: the method comprises the steps that line data of the same traffic mode are vertically broken by using station data, and breakpoint GIS data are extracted;
in step S2, virtual connection arcs for simulating travel behaviors of various travelers are constructed, that is, virtual connection arcs for traffic cell centroids and bus stations, cell centroids and subway stations, bus stations and bus lines, bus stations and roads, subway stations and subway lines, and bus stations and subway stations within a certain distance range are constructed, and the specific steps are as follows:
s2.1: based on a point at one end of a virtual connecting arc to be constructed, namely a reference point, searching a certain number of nearest break points or reference points, namely search points, and calculating coordinates of the points;
s2.2: the calculation formula for calculating the distance between the reference point and the search point is as follows:
wherein x is 1 、y 1 Is the horizontal and vertical coordinates of a reference point, x 2 、y 2 Horizontal and vertical coordinates of the search point are obtained;
s2.3: screening search points within the specified distance range according to the result calculated in the step S2.2;
s2.4: constructing a virtual connecting arc according to the known coordinates;
s2.5: according to the steps S2.1-S2.4, different types of virtual connecting arcs are sequentially constructed according to the requirements of different types of virtual connecting arcs, including distance and number;
the step S3 includes:
the method comprises the following steps of (1) constructing a virtual connection arc of the subway station and the road, wherein the only difference from S2 is as follows: searching a search point closest to the reference point in S2.1, wherein S3 is similar to the establishment of a centroid connecting rod, a road breakpoint in a certain range is randomly searched instead of searching the closest search point, and then a virtual connecting arc is constructed by utilizing a geographic data visualization tool GeoPandas according to the steps S2.2-S2.4;
in the step S4, the geographic data visualization tool GeoPandas is used to construct impedance functions of various road segments, which specifically includes:
where C (i, j) is the combined impedance of an OD centering path; m is m road segments constituting the path; f k (i, j) is the cost of the kth road segment (i, j); t is k (i, j) is the time impedance of the kth link (i, j); e is the set of all road segments in one OD pair;
s4.1: constructing impedance functions of virtual connection arcs of a basic road network, a traffic cell mass center and a bus station, a cell mass center and a subway station, a subway station and a road, a bus station and a road, and a bus station and a subway station; the road section has no cost impedance and only contains time impedance, and the time impedance function is expressed as:
in the formula, T walk (i, j) is the time impedance of the segment (i, j) in the network; lambda walk Converting the time weight of the walking road section into a coefficient; l walk (i, j) is the length of the link (i, j), in km; v walk The walking speed is the unit km/h; e walk Is a collection of walking network edges;
s4.2: constructing an impedance function of a conventional bus section; transferring the monetary cost of a bus trip to a connection arc between a bus station and a bus line, no longer considering cost impedance in a bus network, only considering time impedance, expressed as:
in the formula, T bus (i, j) is the time impedance of the bus segment (i, j); lambda [ alpha ] bus Converting the time weight of the bus section into a coefficient; l bus (i, j) is the length of the road section (i, j), in km; v bus The unit is the travel speed of the bus section, namely km/h; rho ij A congestion degree coefficient for a conventional bus section (i, j); e bus Is a set of conventional public transport network edges;
s4.3: constructing an impedance function of a rail transit road section; the cost impedance calculation formula is as follows:
F sub (i，j)＝η sub ρ sub l sub (i，j)，(i，j)∈E sub
in the formula, F sub (i, j) a cost impedance of the rail transit section (i, j); eta sub Converting the cost weight into a coefficient for the track traffic section; rho sub Average cost per kilometer, unit/km; l sub (i, j) is the length of the link (i, j), in km; e sub A set of rail transit network edges;
the time impedance function is expressed as:
in the formula, T sub (i, j) is the time impedance of the rail transit section (i, j); lambda [ alpha ] sub Converting coefficients for the time weight of the rail transit sections; l sub (i, j) is the length of the track traffic section (i, j) in km; v sub The unit is the travel speed of the rail transit road section, namely km/h; rho ij The congestion degree coefficient of the track traffic section (i, j);
s4.4: constructing an impedance function of a bus station and a virtual connection arc of a bus line; the arc time impedance of the connection between the bus station and the bus line is mainly derived from the waiting time, and the cost impedance is derived from the bus taking cost of the bus; the connection arc impedance function calculation formula is as follows:
F bus_con (i，j)＝c bus_con n bus_con ，(i，j)∈E bus_con
T bus_con (i，j)＝λ bus_con T bus_con ，(i，j)∈E bus_con
in the formula, F bus_con (i, j) is the cost impedance of the bus stop and the bus line connection arc section (i, j); t is bus_con (i, j) arc road for connecting bus station with bus lineThe time impedance of segment (i, j); c. C bus_con In order to distribute the cost of the connecting arcs of the bus for getting on and off, the fare is half of the fare; n is bus_con A cost weight conversion coefficient for a bus stop and a bus line connection arc section (i, j); lambda [ alpha ] bus_con Time weight conversion coefficient of the arc road section (i, j) connecting the bus station and the bus line; t is bus_con The average waiting time is the average waiting time; e bus_con Representing a set of connecting arcs between a conventional bus station and a bus line;
s4.5: constructing an impedance function of a virtual connection arc of a rail transit station and a rail transit line; the connecting arc does not have cost impedance, only has time impedance, the time impedance is divided into two parts, one part is the time from walking to waiting points of the rail transit stations, the solution is carried out according to walking distance, and the other part is waiting time;
in the formula, T sub_con (i, j) is the time impedance of the track traffic station and the track traffic line connection arc section (i, j); lambda [ alpha ] walk Converting the time utility weight coefficient of the walking road section; l sub_con (i, j) is the length of a track traffic station and a track traffic line connection arc section (i, j), and the unit is km; v. of walk The walking speed is the unit km/h; lambda sub_con Converting the weight of the waiting time of the rail transit into a coefficient; t is sub_con The average waiting time is the average waiting time; e sub_con Representing the set of connection arcs of the rail transit station and the rail transit line.
2. The method for constructing a public transportation super network according to claim 1, wherein the step S5 comprises:
s5.1: the attributes of various driving arcs and connecting arcs are processed and given specific attributes, and the specific attributes are as follows:
and kind =1: a base road network;
and kind =2: virtual connecting rods of the mass center and the bus station and the mass center and the subway station;
and kid =3: a subway line;
and kind =4: a virtual connecting arc of a subway station and a road;
and kind =5: the bus lines comprise conventional bus lines, ferries and BRT lines;
and kind =6: a virtual connection arc of a bus station and a bus line;
and king =7: virtual connection arcs of the bus station and the road;
and kind =8: a virtual connecting arc of the subway station and the subway line;
and kind =9: virtual connection arcs of a bus station and a subway station;
s5.2: processing the attribute of the virtual connecting arc with the kind =2 by using a geographic data visualization tool GeoPandas, and adding a TAZ field to enable the connecting arc to inherit the serial number attribute of the traffic cell;
s5.3: and fusing the processed driving arc with the kind =1-kind =9 and the virtual connecting arc by using a geographic data visualization tool GeoPandas to construct a public transportation super network.
3. The method for constructing a public transportation super network according to claim 1, wherein the step S6 comprises:
and constructing a public transport super network topological structure, constructing an adjacency matrix, and establishing a public transport super network which can be identified by computer languages.
4. A device for constructing a public transportation super network is characterized by comprising the following modules:
the original data processing module is used for checking the public transport network and the basic road network by using a conventional public transport network as a reference; processing redundant sites, and only one same site is reserved to ensure that the sites are not on line; breaking the corresponding public transportation line by using the processed station;
the virtual connecting arc module is used for searching a certain number of searching points closest to the station serving as a reference point; calculating coordinates of all points; constructing a virtual connecting arc according to the coordinates;
a virtual connection arc module of the subway station and the road searches a road breakpoint in a certain distance range by taking the subway station as a reference point; calculating coordinates of all points; constructing a virtual connecting arc according to the coordinates;
the road section impedance function module is used for establishing a road section impedance function model and indicating that different types of lines have different costs;
the public transportation super network module performs fusion processing according to all processed running arcs and virtual connection arcs to construct a complete public transportation super network;
the public transport super network topological structure module is used for providing a computer language for identification and laying a foundation for path search and network distribution by using the computer language;
the original data processing module comprises the following specific steps:
s1.1: acquiring GIS data of conventional public transport, rail transit, ferry, BRT, basic road network and mass center of a traffic community;
s1.2: aiming at the problem of deviation of GIS data of conventional public transport, rail transit, ferry, BRT and basic road network, the space correction is carried out on other networks on the basis of the conventional public transport network;
s1.3: processing redundant and disordered site GIS data;
s1.4: the method comprises the steps that line data of the same traffic mode are vertically broken by using station data, and breakpoint GIS data are extracted;
in the virtual arc module of being connected of virtual arc module and subway station and road, including the virtual arc of being connected of the various simulation travelers' trip behaviors of founding, found the virtual arc of being connected of traffic district barycenter and bus station, district barycenter and subway station, bus station and bus line, bus station and road, subway station and subway line, bus station and subway station in the certain distance within range promptly, concrete step is:
s2.1: based on a point at one end of a virtual connecting arc to be constructed, namely a reference point, searching a certain number of nearest break points or reference points, namely search points, and calculating coordinates of the points;
s2.2: the calculation formula for calculating the distance between the reference point and the search point is as follows:
wherein x is 1 、y 1 Is the horizontal and vertical coordinates of a reference point, x 2 、y 2 Horizontal and vertical coordinates of the search point are shown;
s2.3: screening search points within the specified distance range according to the result calculated in the step S2.2;
s2.4: constructing a virtual connecting arc according to the known coordinates;
s2.5: according to the steps S2.1-S2.4, different types of virtual connecting arcs are sequentially constructed according to the requirements of different types of virtual connecting arcs, including distance and number;
among virtual connection arc module and subway station and the virtual connection arc module of road, include:
the method comprises the following steps of (1) constructing a virtual connection arc of the subway station and the road, wherein the only difference from S2 is as follows: searching a searching point closest to the reference point in S2.1, wherein S3 is similar to the establishment of a centroid connecting rod, a road breakpoint in a certain range is randomly searched instead of searching the closest searching point, and then a virtual connecting arc is constructed by utilizing a geographic data visualization tool GeoPandas according to the steps S2.2-S2.4;
the road section impedance function module comprises:
the method comprises the following steps of constructing impedance functions of various road sections by utilizing a geographic data visualization tool GeoPandas, and specifically comprising the following steps:
where C (i, j) is the combined impedance of an OD centering path; m is m road segments constituting the path; f k (i, j) is the cost of the kth road segment (i, j); t is k (i, j) is the time impedance of the kth link (i, j); e is the set of all road segments in one OD pair;
s4.1: constructing impedance functions of virtual connection arcs of a basic road network, a traffic cell mass center and a bus station, a cell mass center and a subway station, a subway station and a road, a bus station and a road, and a bus station and a subway station; the road section has no cost impedance and only contains time impedance, and the time impedance function is expressed as:
in the formula, T walk (i, j) is the time impedance of the segment (i, j) in the network; lambda [ alpha ] walk Converting the time weight of the walking road section into a coefficient; l walk (i, j) is the length unit km of the link (i, j); v walk The walking speed is the unit km/h; e walk Is a collection of walking network edges;
s4.2: constructing an impedance function of a conventional bus section; transferring the monetary cost of a bus trip to a connection arc between a bus station and a bus line, no longer considering cost impedance in a bus network, only considering time impedance, expressed as:
in the formula, T bus (i, j) is the time impedance of the bus section (i, j); lambda [ alpha ] bus Converting the time weight of the bus section into a coefficient; l. the bus (i, j) is the length of the link (i, j), in km; v bus The unit is the travel speed of the bus section, namely km/h; rho ij A congestion degree coefficient for a conventional bus section (i, j); e bus Is a set of conventional public transport network edges;
s4.3: constructing an impedance function of a rail transit road section; the cost impedance calculation formula is as follows:
F sub (i，j)＝η sub ρ sub l sub (i，j)，(i，j)∈E sub
in the formula, F sub (i, j) a cost impedance of the rail transit section (i, j); eta sub Converting the cost weight into a coefficient for the track traffic section; rho sub Average cost per kilometer, unit/km; l sub (i, j) is the length of the link (i, j), in km; e sub A set of rail transit network edges;
the time impedance function is expressed as:
in the formula, T sub (i, j) is the time impedance of the rail transit section (i, j); lambda [ alpha ] sub Converting the time weight into a coefficient for the track traffic section; l sub (i, j) is the length of the track traffic section (i, j) in km; v sub The unit is the travel speed of the rail transit road section, namely km/h; rho ij The congestion degree coefficient of the track traffic section (i, j);
s4.4: constructing an impedance function of a bus station and a virtual connection arc of a bus line; the arc time impedance of the connection between the bus station and the bus line is mainly derived from the waiting time, and the cost impedance is derived from the bus taking cost of the bus; the connection arc impedance function calculation formula is as follows:
F bus_con (i，j)＝c bus_con n bus_con ，(i，j)∈E bus_con
T bus_con (i，j)＝λ bus_con T bus_con ，(i，j)∈E bus_con
in the formula, F bus_con (i, j) is the cost impedance of the bus stop and the bus line connection arc section (i, j); t is bus_con (i, j) is the time impedance of the bus stop and the bus line connection arc section (i, j); c. C bus_con In order to share the cost of the connecting arc of the bus for getting on and off, the fare is half of the fare; n is bus_con A cost weight conversion coefficient for a bus stop and a bus line connection arc section (i, j); lambda bus_con Time weight conversion coefficient of the arc road section (i, j) connecting the bus station and the bus line; t is bus_con The average waiting time is the average waiting time; e bus_con Representing conventional bus stops and bus linesA set of connected arcs;
s4.5: constructing an impedance function of a virtual connection arc of a rail transit station and a rail transit line; the connecting arc does not have cost impedance, only has time impedance, the time impedance is divided into two parts, one part is the time from walking to waiting points of the rail transit stations, the solution is carried out according to walking distance, and the other part is waiting time;
in the formula, T sub_con (i, j) is the time impedance of the track traffic station and the track traffic line connection arc section (i, j); lambda [ alpha ] walk Converting the time utility weight coefficient of the walking road section; l sub_con (i, j) is the length of a track traffic station and a track traffic line connection arc section (i, j), and the unit is km; v. of walk The unit of the walking speed is km/h; lambda [ alpha ] sub_con Converting the weight of the waiting time of the rail transit into a coefficient; t is sub_con The average waiting time is the average waiting time; e sub_con Representing the set of connection arcs of the rail transit station and the rail transit line.
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