CN107808217A - A kind of Public Transport Transfer optimization method based on Big Dipper positioning with the volume of the flow of passengers - Google Patents
A kind of Public Transport Transfer optimization method based on Big Dipper positioning with the volume of the flow of passengers Download PDFInfo
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Abstract
The present invention relates to a kind of Public Transport Transfer optimization method based on Big Dipper positioning with the volume of the flow of passengers.The present invention measures public transport data using Beidou satellite navigation system, builds Urban Transit Network according to the basic theories of complex network and algorithm, optimal case is provided with reference to public traffic network.Basic ideas are：The each circuit of public transport and its site information data passed through are gathered first, distance between two websites, bus brushing card data, it is determined that there are related parameter and the weights on side, complex network model is established according to user's request respectively, according to adjacency matrix corresponding to different models, calculated using Floyd Algorithm Analysis and determine final riding scheme.
Description
Technical Field
The invention relates to a bus transfer optimization method based on Beidou positioning and passenger flow, and belongs to the technical field of bus transfer scheme optimization.
Background
The bus taking scheme is one of important subjects of a bus network system, and is of great significance to resident trip by providing an optimal bus taking scheme according to the demands of residents by analyzing the structure of the bus system in combination with a complex network. At present, the research of urban public transport riding schemes gradually tends to be networked and systematized; however, in the prior art, an accurate and effective bus taking scheme based on Beidou high-precision positioning and bus passenger flow is lacked, and the bus taking scheme in the prior art cannot effectively provide a proper optimization method according to the characteristics and the actual congestion state of the urban bus system network.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a bus transfer optimization method based on Beidou positioning and passenger flow.
Summary of the invention:
according to the invention, the Beidou satellite navigation system is used for measuring bus data, an urban bus network is constructed according to the basic theory and algorithm of a complex network, and an optimal scheme is given by combining the bus network. The basic idea is as follows: the method comprises the steps of firstly, collecting information data of all lines of the bus and stations passing through the lines, the distance between two stations and bus card swiping data, determining weights of relevant parameters and edges, respectively establishing complex network models according to user requirements, and analyzing and calculating to determine a final bus taking scheme by using a Floyd algorithm according to adjacent matrixes corresponding to different models.
Description of terms:
l space: in the L space, bus stops are taken as nodes, if two stops are adjacent on the same bus line, the two stops have connecting edges, and if the two stops are not adjacent, the two stops do not have connecting edges.
P space: in the P space, bus stops are taken as nodes, and if two stops have bus lines to pass through, namely two stops have direct bus lines, the two stops have connecting edges; if no direct bus route exists between two stations, no connecting edge exists.
Side: the method represents the connection relation of two adjacent nodes and is divided into an unweighted edge and a weighted edge.
Shortest path: the path with the shortest distance from the source node to the destination node is sharedAnd N is the number of nodes in the network.
The technical scheme of the invention is as follows:
a bus transfer optimization method based on Beidou positioning and passenger flow comprises the following steps:
1) Acquiring public transportation data:
collecting and recording public transportation data; the bus data comprises a bus route map, bus stop names, actual distances between two adjacent bus stops in the same bus route and bus card swiping times;
the bus lines and bus stops are used for establishing a complex network of a bus network system; the number of times of swiping the bus card can accurately reflect the passenger flow; the distance between the bus stops is used as a parameter for calculating the weight of the connected edges.
2) Data preprocessing:
sequentially numbering the bus stops in each bus line according to the bus advancing sequence;
calculating the number of bus routes passing through the same pair of adjacent bus stops; recording the number of different bus lines passing between two adjacent bus stops i and j as N ij (ii) a In reality, a plurality of different bus lines may pass through two adjacent bus stops simultaneously;
the distance between the adjacent bus stop i and the bus stop j is recorded as L ij (ii) a Calculating the total passenger flow F of the adjacent bus stop i and the adjacent bus stop j through the number of times of swiping the bus card ij ；
N ij 、F ij 、L ij All the weights are used for calculating the weight between two adjacent stations in the least-time-consumption riding scheme; distance L between adjacent bus stop i and bus stop j ij The measured result is obtained by measuring the Beidou high-precision vehicle-mounted positioning equipment;
3) Constructing a complex network of a public transport network system;
complex networks are usually formed by a huge number of nodes and intricate relationships among the nodes, and the network structure has complex topological structure characteristics. The urban public transport network topology model mainly adopts a P space model and an L space model which respectively correspond to a public transport transfer network and a public transport station network;
the invention utilizes pajek to construct and analyze the complex network, and pajek can provide visual network composition and is beneficial to analyzing the optimal riding scheme.
Bus taking scheme with least transfer times
A bus taking scheme with the least transfer times needs to use a P space method to construct an undirected and unauthorized bus network, in the P space, bus stops are used as nodes in the network, any two stops in the same bus line have connecting edges, and if no direct bus line exists between the two stops, no connecting edge exists between the two stops.
3.1.1 In pajek, data entry is performed by sequentially enumerating all edges in the complex network, and the basic format is as follows:
*Vertices N
*Edgeslist[i j c]
*Matrix
in the data structure, N represents the number of all nodes in the complex network, i and j represent the numbers of two bus stops corresponding to the edges respectively, c represents the weight, and when a bus line exists between the bus stop i and the bus stop j, c =0; c =1 when no bus line exists between the bus stop i and the bus stop j;
in pajek, the basic format of the data entry is:
*Vertices N
*Arcslist[i j c]
*Edgeslist[i j c]
*Matrix
* Only one of Arcslist [ ijc ] and Edgeslist [ ijc ] is selected, wherein the former represents that a directed network is to be constructed, and the latter represents that an undirected network is to be constructed; no empty row is left between each row of data, and the data are separated by a space or a Tab key; the invention constructs a non-directional network, so that Edgeslist is adopted;
3.1.2 Reading a net file of the public transportation network system by using pajek, and generating a complex network diagram of the public transportation transfer network by using a P space method; taking a bus stop as a node in a complex network;
3.1.3 Constructing an adjacency matrix of the urban public transportation network system according to the connection relation among all nodes in the complex network; element a in the adjacency matrix ij Is 0 or 1;1 represents that a bus route is arranged between stations with corresponding row number and column number; 0 represents that no bus line exists between the stations with the corresponding row number and column number;
3.1.4 According to the adjacency matrix, calculating the minimum transfer times between any two stations by using a Floyd algorithm; the method comprises the following specific steps:
a) Setting Dis (i, j) as the minimum transfer times from the bus stop i to the bus stop j;
b) For each bus stop k, checking whether Dis (i, k) + Dis (k, j) < Dis (i, j) is true, if true, judging that a path from i to k to j is shorter than a path from i to j directly, and setting Dis (i, j) = Dis (i, k) + Dis (k, j); wherein k is not equal to i, j;
c) Repeating the step B) until all bus stops k and Dis (i, j) are traversed, namely the minimum transfer times from the bus stop i to the bus stop j are obtained;
the Floyd algorithm is a classic dynamic programming algorithm. Finding the shortest path from bus stop i to bus stop j. From the perspective of dynamic planning, the shortest path from any bus stop i to any bus stop j is not more than 2 possibilities, namely, the shortest path is directly from the bus stop i to the bus stop j, and the shortest path is from the bus stop i to the bus stop j through a plurality of bus stops k.
Bus taking scheme with minimum time
In the scheme, the weight of the edge is not 1 any more, but W ij (ii) a The bus running efficiency of the road section is represented, the larger the weight is, the lower the bus running efficiency of the road section is, the time consumption is longer when the road section passes through the road section, the smaller the weight is, the bus running efficiency of the road section is represented, and the time when the road section passes through the road section is short.
3.2.1 In pajek, data entry is performed by sequentially enumerating all edges in the complex network, and the basic format is as follows:
*Vertices N
*Edgeslist[i j c]
*Matrix
step 3.2.1) is different from step 3.1.1) in that when data entry is performed, the connection relationship between the stations changes, and the sub-network formed by all stations in the same line is not a complete graph any more, but only adjacent stations in the bus line have the connection relationship.
3.2.2 Reading a net file of the public transportation network system by using pajek, and generating a complex network diagram of the public transportation station network by using an L space method; taking a bus stop as a node in a complex network; the weight of the connected edge
3.2.3 According to the connection relationship among all nodes in the complex network, constructing an L space adjacency matrix of the urban public transportation network; element a in the adjacency matrix ij Is 0 or 1;1 represents that a bus route is arranged between stations with corresponding row number and column number; 0 represents that no bus line exists between the stations with the corresponding row number and column number; and only two adjacent bus stops in the same bus line have a connection relation in the L space.
3.2.4 Computing a most time-saving bus riding scheme by using a Floyd algorithm; the method comprises the following specific steps:
a) Setting dis (i, j) as the minimum transfer times from the bus stop i to the bus stop j;
b) For each bus stop k, checking whether dis (i, k) + dis (k, j) < dis (i, j) is true, if true, judging that a path from i to k to j is shorter than a path from i to j directly, and setting dis (i, j) = dis (i, k) + dis (k, j); wherein k is not equal to i, j;
c) Repeating the step b) until all bus stops k and dis (i, j) are traversed, namely the minimum transfer times from the bus stop i to the bus stop j are obtained;
wherein the content of the first and second substances,the method is characterized in that the weight value of all edges between a bus stop i and a bus stop j is added, n is the number of times of bus transfer, T is the average waiting time of each time of transfer, and T is an empirical value.
Different from the step 3.1.4), when the minimum value comparison is carried out, the sum of the edges with the weight values passed by the paths between the two stations and the sum of the times of vehicle transfer multiplied by the waiting time are compared;
according to the optimization of the invention, the public transportation data is collected through a vehicle-mounted Beidou satellite navigation system; the actual distance between two adjacent bus stops in the same bus route is obtained through vehicle-mounted Beidou positioning equipment.
The invention has the beneficial effects that:
1. the bus transfer optimization method based on Beidou positioning and passenger flow realizes positioning and precision of bus data, can effectively construct an urban bus network system and analyze network characteristics of the urban bus network system, provides a targeted transfer scheme according to the requirements of users, reasonably goes out, avoids congestion, can improve the utilization rate of buses at the moment, and promotes smooth operation of urban traffic.
Drawings
FIG. 1 is a flow chart of the bus transfer optimization method of the present invention;
FIG. 2 is a screenshot of the data form entered in step 3.1.1) of example 1;
FIG. 3 is a bus network diagram of a 14-way bus constructed by the P-space method in embodiment 1;
fig. 4 is a screenshot of the data form entered in step 3.2.1) in embodiment 1;
fig. 5 is a network diagram of a bus stop of 14 buses constructed by using the L space method in embodiment 1.
Detailed Description
The invention is further described below, but not limited thereto, with reference to the following examples and the accompanying drawings.
Example 1
As shown in fig. 1.
A bus transfer optimization method based on Beidou positioning and passenger flow comprises the following steps:
1) Acquiring public transportation data:
collecting and recording public transportation data; the bus data comprises a bus route map, bus stop names, actual distances between two adjacent bus stops in the same bus route and bus card swiping times;
the public transport lines and the public transport stations are used for establishing a complex network of a public transport network system; the number of times of swiping the bus card can accurately reflect the passenger flow; the distance between the bus stops is used as a parameter for calculating the weight of the connected edges.
2) Data preprocessing:
sequentially numbering the bus stops in each bus line according to the bus advancing sequence; taking the bus network system in Jinan City as an example, the data of 1 to 217 bus routes are collected, and 1436 stops are counted.
Calculating the number of bus routes passing through the same pair of adjacent bus stops; recording the number of different bus lines passing between two adjacent bus stops i and j as N ij (ii) a In reality, a plurality of different bus lines may pass through two adjacent bus stops simultaneously;
the distance between the adjacent bus stop i and the bus stop j is recorded as L ij (ii) a Calculating the total passenger flow F of the adjacent bus stop i and the adjacent bus stop j through the times of bus card swiping ij (ii) a The number of times of swiping the bus is taken as the passenger flow F ij ；
N ij 、F ij 、L ij All the weights are used for calculating the weight between two adjacent stations in the least-time-consumption riding scheme; distance L between adjacent bus stop i and bus stop j ij The measured result is obtained by measuring the Beidou high-precision vehicle-mounted positioning equipment;
3) Constructing a complex network of a public transport network system;
complex networks are usually formed by a huge number of nodes and intricate relationships among the nodes, and the network structure has complex topological structure characteristics. The urban public transport network topology model mainly adopts a P space model and an L space model which respectively correspond to a public transport transfer network and a public transport station network;
the complex network is constructed and analyzed by utilizing the pajek, and the pajek can provide an intuitive network composition and is beneficial to analyzing an optimal riding scheme.
Bus taking scheme with least transfer times
A bus taking scheme with the least transfer times needs a method of P space to construct an undirected and unauthorized bus network, in the P space, bus stops are used as nodes in the network, any two stops in the same bus line have a connecting edge, and if no bus line is reached between the two stops, the connecting edge is not formed between the two stops.
3.1.1 In pajek, data entry is performed by sequentially enumerating all edges in the complex network, and the basic format is as follows:
*Vertices N
*Edgeslist[i j c]
*Matrix
in the data structure, N represents the number of all nodes in the complex network, i and j represent the numbers of two bus stops corresponding to the edges respectively, c represents weight, and when a bus line exists between the bus stop i and the bus stop j, c =0; c =1 when no bus line exists between the bus stop i and the bus stop j;
taking the route of 14 buses in the south of china as an example, data entry is shown in fig. 2, and a constructed network consists of 16 bus stops. The connection relationship between the sites is determined by the data below the Edges, such as the first 16 rows below the Edges: the site 1 and the site 2 have connecting edges, and the weight is 1; the site 1 and the site 3 have connecting edges, and the weight of the connecting edges is 1; 5363 site … … has a connecting edge with 16 sites, and its weight is 1.
3.1.2 Reading a net file of the public transportation network system by using pajek, and generating a complex network diagram of the public transportation transfer network by using a P space method; taking a bus stop as a node in a complex network; taking a 14-way bus in south of china as an example, a public transportation network constructed by using a P-space method is shown in fig. 3.
3.1.3 Constructing an adjacency matrix of the urban public transportation network system according to the connection relation among all nodes in the complex network; element a in the adjacency matrix ij Is 0 or 1;1 represents that a bus route is arranged between stations with corresponding row number and column number; 0 represents that no bus line exists between the stations with the corresponding row number and column number;
taking a 14-route bus in south China as an example, the constructed adjacency matrix is as follows:
from this matrix, it can be seen that any two stations in the same line have a connection relationship in P space.
3.1.4 According to the adjacency matrix, calculating the minimum transfer times between any two stations by using a Floyd algorithm; the method comprises the following specific steps:
a) Setting Dis (i, j) as the minimum transfer times from the bus stop i to the bus stop j;
b) For each bus stop k, checking whether Dis (i, k) + Dis (k, j) < Dis (i, j) is true, if true, judging that a path from i to k to j is shorter than a path from i to j directly, and setting Dis (i, j) = Dis (i, k) + Dis (k, j); wherein k is not equal to i, j;
c) Repeating the step B) until all bus stops k and Dis (i, j) are traversed, namely the minimum transfer times from the bus stop i to the bus stop j are obtained;
the Floyd algorithm is a classic dynamic programming algorithm. Finding the shortest path from bus stop i to bus stop j. From the perspective of dynamic planning, the shortest path from any bus stop i to any bus stop j is not more than 2 possibilities, namely, the shortest path is directly from the bus stop i to the bus stop j, and the shortest path is from the bus stop i to the bus stop j through a plurality of bus stops k.
The calculation shows that the average number of times of vehicle transfer between any two stations of the Jinan public transportation network is 1.6, and compared with 1.15 of Shanghai, 1.37 of Guangzhou and 1.56 of Beijing, the efficiency of vehicle transfer is lower than that of the above cities.
Bus taking scheme with minimum time consumption
In the scheme, the weight of the edge is not 1 any more, but W ij (ii) a The bus running efficiency of the road section is represented, the larger the weight is, the lower the bus running efficiency of the road section is, the time consumption is longer when the road section passes through the road section, the smaller the weight is, the bus running efficiency of the road section is represented, and the time when the road section passes through the road section is short.
3.2.1 In pajek, data entry is performed by sequentially enumerating all edges in the complex network, and the basic format is as follows:
*Vertices N
*Edgeslist[i j c]
*Matrix
the difference between step 3.2.1) and step 3.1.1) is that when data recording is performed, the connection relationship between stations changes, and the sub-networks formed by all stations in the same line are not complete diagrams any more, but only adjacent stations in the bus line have the connection relationship. Taking the south-economic 14-way vehicle as an example, assuming that the weight of each edge is 1 in this example, the data entry is as shown in fig. 4, and in Edges, adjacent stations have a connection relationship.
3.2.2 Reading a net file of the public transportation network system by using pajek, and generating a complex network diagram of the public transportation station network by using an L space method; taking a bus stop as a node in a complex network; the weight of the connected edge
Constructing an undirected and authorized public transportation network by an L space method; if a direct bus line passes between the two bus stops, a connecting edge is arranged between the two bus stops, and if no direct bus line passes between the two bus stops, no connecting edge is arranged between the two bus stops; a bus station network constructed by using the L space method is shown in fig. 5;
3.2.3 According to the connection relationship among all nodes in the complex network, constructing an L space adjacency matrix of the urban public transportation network(ii) a Element a in the adjacency matrix ij Is 0 or 1;1 represents that a bus route is arranged between stations with corresponding row number and column number; 0 represents that no bus line exists between the stations with the corresponding row number and column number; and only two adjacent bus stops in the same bus line have a connection relation in the L space. Taking the 14 paths of buses in the south of the province as an example, the constructed adjacency matrix is as follows:
3.2.4 Computing a most time-efficient bus taking scheme by using a Floyd algorithm; the method comprises the following specific steps:
a) Setting dis (i, j) as the minimum transfer times from the bus stop i to the bus stop j;
b) For each bus stop k, checking whether dis (i, k) + dis (k, j) < dis (i, j) is true, if true, judging that a path from i to k to j is shorter than a path from i to j directly, and setting dis (i, j) = dis (i, k) + dis (k, j); wherein k is not equal to i, j;
c) Repeating the step b) until all bus stops k and dis (i, j) are traversed, namely the minimum transfer times from the bus stop i to the bus stop j are obtained;
wherein, the first and the second end of the pipe are connected with each other,the method is characterized in that the weight value of all edges between a bus stop i and a bus stop j is added, n is the number of times of bus transfer, T is the average waiting time of each time of transfer, and T is an empirical value.
Different from the step 3.1.4), when the minimum value comparison is carried out, the sum of the edges with the weight values passed by the paths between the two stations and the sum of the times of vehicle transfer multiplied by the waiting time are compared;
example 2
The bus transfer optimization method based on Beidou positioning and passenger flow volume according to embodiment 1, further, the bus data is collected through a vehicle-mounted Beidou satellite navigation system; the actual distance between two adjacent bus stops in the same bus line is obtained through the vehicle-mounted Beidou positioning device.
Claims (2)
1. A bus transfer optimization method based on Beidou positioning and passenger flow is characterized by comprising the following steps:
1) Acquiring public transportation data:
collecting and recording public transportation data; the bus data comprises a bus route map, bus stop names, actual distances between two adjacent bus stops in the same bus route and bus card swiping times;
2) Data preprocessing:
sequentially numbering the bus stops in each bus line according to the bus advancing sequence;
calculating the number of bus routes passing through the same pair of adjacent bus stops; recording the number of different bus lines passing between two adjacent bus stops i and j as N ij ；
The distance between the adjacent bus stop i and the bus stop j is recorded as L ij (ii) a Calculating the total passenger flow F of the adjacent bus stop i and the adjacent bus stop j through the number of times of swiping the bus card ij ；
3) Constructing a complex network of a public transport network system;
bus taking scheme with least transfer times
3.1.1 In pajek, data entry is performed by sequentially enumerating all edges in the complex network, and the basic format is as follows:
*Vertices N
*Edgeslist[i j c]
*Matrix
in the data structure, N represents the number of all nodes in the complex network, i and j represent the numbers of two bus stops corresponding to the edges respectively, c represents the weight, and when a bus line exists between the bus stop i and the bus stop j, c =0; c =1 when no bus line exists between the bus stop i and the bus stop j;
3.1.2 Read the net file of the public transportation network system by pajek, and generate the complex network diagram of the public transportation transfer network by P space method; taking a bus stop as a node in a complex network;
3.1.3 Constructing an adjacency matrix of the urban public transportation network system according to the connection relation among all nodes in the complex network; element a in the adjacency matrix ij Is 0 or 1;1 represents that bus lines exist between stations with corresponding row numbers and column numbers; 0 represents that no bus line exists between the stations with the corresponding row number and column number;
3.1.4 According to the adjacency matrix, calculating the minimum transfer times between any two stations by using a Floyd algorithm; the method comprises the following specific steps:
a) Setting Dis (i, j) as the minimum transfer times from the bus stop i to the bus stop j;
b) For each bus stop k, checking whether Dis (i, k) + Dis (k, j) < Dis (i, j) is true, if true, judging that a path from i to k to j is shorter than a path from i to j directly, and setting Dis (i, j) = Dis (i, k) + Dis (k, j); wherein k is not equal to i, j;
c) Repeating the step B) until all bus stops k and Dis (i, j) are traversed, namely the minimum transfer times from the bus stop i to the bus stop j are obtained;
bus taking scheme with minimum time
3.2.1 In pajek, data entry is performed by sequentially enumerating all edges in the complex network, and the basic format is as follows:
*Vertices N
*Edgeslist[i j c]
*Matrix
3.2.2 Reading a net file of the public transportation network system by using pajek, and generating a complex network diagram of the public transportation station network by using an L space method; taking a bus stop as a node in a complex network; the weight of the connected edge
3.2.3 Based on the connection relationships between the nodes in the complex network,constructing an L space adjacency matrix of the urban public transport network; element a in the adjacency matrix ij Is 0 or 1;1 represents that a bus route is arranged between stations with corresponding row number and column number; 0 represents that no bus line exists between the stations with the corresponding row number and column number;
3.2.4 Computing a most time-saving bus riding scheme by using a Floyd algorithm; the method comprises the following specific steps:
a) Setting dis (i, j) as the minimum transfer times from the bus stop i to the bus stop j;
b) For each bus stop k, checking whether dis (i, k) + dis (k, j) < dis (i, j) is true, if true, judging that a path from i to k to j is shorter than a path from i to j directly, and setting dis (i, j) = dis (i, k) + dis (k, j); wherein k is not equal to i, j;
c) Repeating the step b) until all bus stops k, dis (i, j) are traversed, namely the minimum transfer times from the bus stop i to the bus stop j are obtained;
wherein, the first and the second end of the pipe are connected with each other,the method is characterized in that the weight value of all edges between a bus stop i and a bus stop j is added, n is the number of times of bus transfer, T is the average waiting time of each time of transfer, and T is an empirical value.
2. The Beidou positioning and passenger flow based bus transfer optimization method according to claim 1, wherein the bus data is collected through a vehicle-mounted Beidou satellite navigation system; the actual distance between two adjacent bus stops in the same bus line is obtained through the vehicle-mounted Beidou positioning device.
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| CN108509659A (en) * | 2018-05-22 | 2018-09-07 | 武汉轻工大学 | Recommendation method, apparatus, terminal device and the readable storage medium storing program for executing of riding scheme |
| CN109299813A (en) * | 2018-08-27 | 2019-02-01 | 华中科技大学 | A kind of public traffic network shortest path length calculation method under least bus change |
| CN110837919A (en) * | 2019-10-22 | 2020-02-25 | 武汉元光科技有限公司 | Bus supply condition judgment method and device |
| CN111191817A (en) * | 2019-12-12 | 2020-05-22 | 华侨大学 | Bus network topology division method based on transfer passenger flow |
| CN112529292A (en) * | 2020-12-11 | 2021-03-19 | 重庆邮电大学 | Traffic network line optimization method based on improved Floyd algorithm |
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