CN115760520B - Bus connection optimization method and device at subway new line opening stage - Google Patents
Bus connection optimization method and device at subway new line opening stage Download PDFInfo
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Abstract
The invention relates to the technical field of traffic and discloses a method and a device for optimizing bus connection in a new subway line opening stage, wherein the method comprises the steps of firstly collecting data, and specifically comprises overall supply data of bus service stations, lines and line plans, and longitude and latitude of bus, subway stations and line geographic information and vector diagram data; analyzing the bus connection state of the subway at the new line opening stage, and carrying out two-stage screening according to the acceptable walking transfer range of urban residents; determining a subway service coverage range lambda and a primary bus connection service coverage range omega; determining the passenger flow range of the bus connection optimizing service; performing standard data sample format and data conversion; performing bus service supply angle index evaluation; performing angle index evaluation on the effect of the connected bus passenger flow; and finally, optimizing the docking bus line. The invention can expand the effective attraction range of public transportation system and guide the traveling habit of resident buses by improving the accuracy and the effectiveness of the optimization of the bus connection service.
Description
Technical Field
The invention relates to the technical field of public transportation, in particular to a method and a device for optimizing bus connection in a new subway line opening stage.
Background
The public transportation is particularly in the integral non-networking stage, the problem of gradual adjustment and optimization of the connection public transportation service exists, the data volume of the public transportation line is large, the data is complex, the invalid data duty ratio is large, and the data mining and analysis level is particularly tested. The actual transfer distance, transfer time, connection distance, connection time, waiting time and other service effect indexes of passengers are key data of public transportation and subway connection, are used for analyzing the service effect of bus connection service passenger flow and have main problems so as to play a role in optimizing connection bus service lines, and therefore a new subway line opening stage bus connection optimizing method and device are needed.
Disclosure of Invention
The invention aims to provide a method and a device for optimizing bus connection in a subway new line opening stage, which can expand the effective attraction range of a public transportation system and guide the traveling habit of residents in buses by improving the accuracy and the effectiveness of bus connection service optimization.
The invention is realized in the following way:
within the subway service coverage range, a bus stop capable of providing bus connection service for a subway station is a connection bus stop; the bus line capable of providing bus connection service for the subway station is a connection bus line.
The travel behavior between the subway station and the connected bus station is called transfer, the shortest walking path is the transfer distance, and the walking time is the transfer time.
The travel behavior of a connected bus line from an origin bus stop to a connected bus stop or from the connected bus stop to a destination bus stop is called connection, the travel distance of the bus is the connection distance, and the consumed time is the connection time.
Bus connection optimization method and device at subway new line opening stage; the method is specifically carried out according to the following steps of;
S 1 collecting data, namely collecting general supply data of bus service stations, lines and bus line plans, bus, subway stations and line geographic information longitude and latitude, vector diagram data, and collecting all-purpose card/IC card swiping data and taxi/network taxi operation data, wherein reserved fields comprise bus stations, bus station longitude and latitude, subway stations, subway station longitude and latitude, bus lines, transit stations and departure frequency;
S 2 analyzing the bus connection state of the subway at the new line opening stage, and carrying out two-stage screening according to the acceptable walking transfer range of urban residents; according to the acceptable walking transfer range of urban residents, adopting a range of 500m to carry out two-stage screening;
S 2.1 according to the longitude and latitude of the bus station, calculating the bus station crossing with the 500m buffer zone around the subway station in the first stage;
S 2.2 calculating the shortest path between the bus station and the corresponding subway station in the second stage, specifically using a network analysis tool of the ArcGIS to calculate the shortest path, calculating the shortest transfer distance field-total_path between each connected bus station and the corresponding subway station, screening the bus station with the field value less than or equal to 500m, and taking the bus station screened in the two stages as the current subway connected station; the bus line passing through the bus stop is a connection bus line; the departure frequency of the line is the departure frequency of the bus.
S 3 Determining a subway service coverage range lambda and a bus connection service coverage range omega at one time;
specifically, according to the urban resident traveling habit, a direct coverage range Λ (generally, a range of a peripheral straight line distance 1000m of a subway station) of subway service is determined, according to the basic condition of the primary bus connection service of the subway, a coverage range Ω (generally, a range of a peripheral straight line distance 500m of all bus stations where a bus line is connected) of the previous bus connection service is determined and optimized, and the surface ranges Λ and Ω are combined to obtain the coverage range phi of the subway and the bus connection service thereof.
S 4 Determining the passenger flow range of the bus connection optimizing service; the bus connection optimizing service passenger flow range comprises residents in a bus and subway travel mode and residents in other subway travel modes.
S 5 Standard data sample format and data conversion are carried out;
taking the card swiping data of the passengers in the type I as a standard data sample format, and reserving fields comprises: (1) from the assigned ID, (2) departure place bus card swiping time, (3) departure place bus station, (4) bus line number 1, (5) connection subway bus station, (6) connection bus station card swiping time 1, (7) initial subway station, (8) subway station card swiping time, (9) stop subway station, subway station card swiping time, and,Subway junction bus stop, < >>Card swiping time 2, < >>Bus route number 2, & gt>Destination bus stop, < > and >>The card swiping time of the destination bus stop;
data conversion one: the passengers inconvenient to connect and not taking the long-distance buses of the subway are compared with the actual bus taking time through a formula 1, and whether the passengers are likely to be converted into a bus and subway travel mode at the stage is judged;
wherein: t (T) Theory of After assuming that the sample is transferred to the subway main channelThe required travel theoretical time;
OH 1 -departure bus stop to nearest subway station H 1 Is a manhattan distance of (a);
DH 2 -destination bus stop to nearest subway station H 2 Is a manhattan distance of (a);
v—average speed of peak section (flat peak/peak) where the urban bus is located at the card swiping time;
T sub -subway station H 1 To H 2 Operating time at peak section (peak/flat) where the card swiping time is located;
-average of absolute values of swipe time differences of standard sample fields (6) and (8);
standard sample field (d) and (d)>An average value of absolute values of card swiping time differences;
T actual practice is that of -the card swiping time difference of the departure bus stop and the destination bus stop;
data conversion II: judging whether passengers who are inconvenient to select private car and subway or network taxi and subway travel have transfer conditions or not.
S 6 Performing bus service supply angle index evaluation;
respectively carrying out table pairwise association on the connection bus station, the corresponding subway station, the transit bus line, all transit bus stations of the transit bus line and the longitude and latitude of each station; with the association table as an input, a supply angle index value is calculated, the specific index including: the related indexes of the connection sites, namely the number N of the connection sites and the transfer distance L; connection line related index: transfer line number, connection distance D, connection coverage; the relevant index of the opening frequency, namely the opening frequency;
the transfer distance L is calculated only by the average value of the transfer distances between each connection bus station and the subway according to the supply angle, and the specific formula is shown in the formula (2);
wherein: l (L) i The average transfer distance of the bus station connected with each entrance and exit of the subway station i;
N i the total number of bus stops connected with each entrance and exit of the subway station i;
then calculating the number of connection lines, connection distance data, connection coverage, bus line broken line coefficient and running frequency F r And carrying out evaluation calculation on the bus service supply angle index.
S 7 The method comprises the following steps of evaluating the angle index of the effect of the bus passenger flow;
respectively carrying out association processing on standardized and summarized transfer IC card swiping data, network bus/taxi conversion data, bus trip conversion data and supply data, wherein association fields are key fields of subway stations, bus stations and bus lines;
calculating a passenger flow service effect angle index value by taking the association table as input, wherein the specific index comprises a connection site related index, namely a weighted transfer distance and a transfer time; connection line related index: weighting the connection distance and the connection time; running frequency related index-waiting time; the average number of the indexes, the upper and lower quartiles 85% fraction and the 95% fraction of the overall sample are calculated,
and (3) carrying out three processing stages of data cleaning, outlier elimination, key index calculation and service pain point mining on each index data.
S 8 Optimizing the docking bus line by adding or extending the line, adding stations, increasing the driving frequency and improving the conventional bus traffic environment.
Further, the invention provides a bus connection optimizing device in a subway new line opening stage, which comprises a storage unit, wherein a computer program is stored on the storage unit, and the program is executed by a main controller to realize the method according to any one of the above.
Compared with the prior art, the invention has the beneficial effects that:
the bus connection service optimization accuracy and effectiveness can be improved, so that the effective attraction range of a public transportation system is enlarged, and the bus travel habits of residents are guided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some examples of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a transfer schematic of the present invention;
FIG. 3 is a schematic representation of the passenger type of the present invention;
fig. 4 is an optimization flow chart of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, based on the embodiments of the invention, which are apparent to those of ordinary skill in the art without inventive faculty, are intended to be within the scope of the invention. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, based on the embodiments of the invention, which are apparent to those of ordinary skill in the art without inventive faculty, are intended to be within the scope of the invention.
Referring to fig. 1, the method and the device for optimizing bus connection in the new subway line opening stage are specifically implemented according to the following steps;
in this embodiment, as shown in fig. 2, a bus station capable of providing bus connection service for a subway station is a connection bus station within the coverage area of the subway service; the bus line capable of providing bus connection service for the subway station is a connection bus line.
The travel behavior between the subway station and the connected bus station is called transfer, the shortest walking path is the transfer distance, and the walking time is the transfer time.
The travel behavior of a connected bus line from an origin bus stop to a connected bus stop or from the connected bus stop to a destination bus stop is called connection, the travel distance of the bus is the connection distance, and the consumed time is the connection time.
In the embodiment, a bus connection optimization method and device at a new subway line opening stage; the method is specifically carried out according to the following steps of;
S 1 collecting data, namely collecting general supply data of bus service stations, lines and bus line plans, bus, subway stations and line geographic information longitude and latitude, vector diagram data, and collecting all-purpose card/IC card swiping data and taxi/network taxi operation data, wherein reserved fields comprise bus stations, bus station longitude and latitude, subway stations, subway station longitude and latitude, bus lines, transit stations and departure frequency;
S 2 analyzing the bus connection state of the subway at the new line opening stage, and carrying out two-stage screening according to the acceptable walking transfer range of urban residents; according to the acceptable walking transfer range of urban residents, adopting a range of 500m to carry out two-stage screening;
S 2.1 according to the longitude and latitude of the bus station, calculating the bus station crossing with the 500m buffer zone around the subway station in the first stage;
S 2.2 the second stage calculates the shortest path between the bus station and the subway stationSpecifically, a network analysis tool of the ArcGIS is used for calculating the shortest path, the shortest transfer distance field-total_path between each connected bus station and the corresponding subway station is calculated, the bus station with the value of the field being less than or equal to 500m is screened, and the bus station screened in two stages is used as the current subway connected station; the bus line passing through the bus stop is a connection bus line; the departure frequency of the line is the departure frequency of the bus.
S 3 Determining a subway service coverage range lambda and a bus connection service coverage range omega at one time;
specifically, according to the urban resident traveling habit, a direct coverage range Λ (generally, a range of a peripheral straight line distance 1000m of a subway station) of subway service is determined, according to the basic condition of the primary bus connection service of the subway, a coverage range Ω (generally, a range of a peripheral straight line distance 500m of all bus stations where a bus line is connected) of the previous bus connection service is determined and optimized, and the surface ranges Λ and Ω are combined to obtain the coverage range phi of the subway and the bus connection service thereof.
S 4 Determining the passenger flow range of the bus connection optimizing service; the bus connection optimizing service passenger flow range comprises residents in a bus and subway travel mode and residents in other modes and subway travel modes.
The optimization of the connection bus of the subway is not only to serve residents who currently adopt the travel mode of 'bus+subway', such as type I in fig. 3, but also to consider serving residents who do not take the subway due to inconvenient connection and residents who select the travel mode of 'other modes+subway' due to inconvenient connection.
The residents inconvenient to connect and not taking subways can select modes in long-distance travel: the residents of buses, private cars, taxis/network buses and motorcycles/non-motor vehicles, only part of long-distance bus passengers with the same subway service direction can be transferred to the service range more, namely, the traveling efficiency of the passengers is improved by improving bus connection conditions, and the passengers are guided to be transferred to a main channel, such as type II and type III in fig. 3. The residents selecting to drive or drive in long-distance travel are mostly time sensitive, comfort sensitive or price insensitive, the residents are difficult to transfer to a public transportation system in short term, particularly in the subway non-network-forming stage, the passengers selecting motorcycles/non-motor vehicles in long-distance travel are mostly personal samples to select autonomously, and the passengers cannot be converted into buses to travel. The residents who inconvenient to select the "other modes and subways" for traveling are the important consideration range in the optimization process of the bus for the traveling, and the "other modes" comprise private cars, network taxi/taxis, non-motor vehicles, motorcycles/electric vehicles and the like, wherein only the important consideration is that whether the residents traveling in the modes of the private cars and subways and the network taxi/taxis and subways can be taken into consideration, and the residents traveling in the modes of the private cars and subways and the network taxi/taxis and subways can be taken into consideration according to the city development requirements (such as whether the non-motor vehicles are encouraged to travel and the like) are as shown in the type IV and the type V in the figure 3.
S 5 Standard data sample format and data conversion are carried out;
taking the card swiping data of the passengers in the type I as a standard data sample format, and reserving fields comprises: (1) from the assigned ID, (2) departure place bus card swiping time, (3) departure place bus station, (4) bus line number 1, (5) connection subway bus station, (6) connection bus station card swiping time 1, (7) initial subway station, (8) subway station card swiping time, (9) stop subway station, subway station card swiping time, and,Subway junction bus stop, < >>Card swiping time 2, < >>Bus route number 2, & gt>Destination bus stop, < > and >>The card swiping time of the destination bus stop;
the condition for identifying one trip of bus and subway is at least (1) to figureThe segment data is not null or at least (1) andthe field data value is not null, and the transfer card swiping time is not more than 30 minutes (generally, the walking transfer time is within 10 minutes, the space is optimized in consideration of individual difference and transfer convenience, the standard sample collection condition is controlled within 30 minutes, and if the selection is too long, larger sample deviation can exist). When the above condition is met and part of the fields are empty, the flag is empty (if the flag is 0, the statistical analysis software will incorporate it into the average, quartile statistics).
Data conversion one: the passengers (passengers of type II and type III) which are inconvenient to connect and do not take the subway and have long-distance buses are compared with the actual bus taking time through a formula 1, and whether the possibility of converting into a bus and subway travel mode exists at the stage is judged; the identification condition of passengers of the type III is that the transfer card swiping time of two bus stops is not more than 30 minutes (the general walking transfer time is within 10 minutes, the individual difference and the transfer convenience optimization space are considered, the standard sample collection condition is controlled within 30 minutes, and larger sample deviation possibly exists if the selection is overlong);
wherein: t (T) Theory of -assuming the travel theoretical time required after the sample is transferred to the subway main channel;
OH 1 -departure bus stop to nearest subway station H 1 Is a manhattan distance of (a);
DH 2 -destination bus stop to nearest subway station H 2 Is a manhattan distance of (a);
v—average speed of peak section (flat peak/peak) where the urban bus is located at the card swiping time;
T sub -subway station H 1 To H 2 Operating time at peak section (peak/flat) where the card swiping time is located;
-average of absolute values of swipe time differences of standard sample fields (6) and (8);
standard sample field (d) and (d)>An average value of absolute values of card swiping time differences;
T actual practice is that of -the card swiping time difference of the departure bus stop and the destination bus stop;
when T is Theory of ≤T Actual practice is that of The travel can be converted into a theoretical path (O-H1-H2-D) to be incorporated into a standard sample and marked with a type number, wherein fields (1) and (2) adopt automatic assignment and actual values, other fields assign theoretical values, namely theoretical stations and theoretical card swiping time of superimposed theoretical time, and transfer time of each stage assigns an average value of the actual sample.
Data conversion II: judging whether passengers who are inconvenient to select private car and subway or network taxi and subway travel have transfer conditions or not.
The passengers who go out by 'private car + subway' or 'net taxi + subway' are inconvenient to select due to connection, the data of the passengers are difficult to acquire, and whether the passengers have transfer conditions is judged based on the GPS data of the destination of the freight list of the passengers. When one end of the start point E or the end point F of a certain piece of operation data is in the subway service coverage range Λ (namely, the type IV and the type V), whether the passenger transfers subways or not is the object range which should be considered by optimizing the connected public transportation service.
For type IV, its endpoint F ε Λ: as the starting pointConsider data conversion; as the starting pointIn the eighth step, whether to add lines or adjust lines is considered in combination with passenger flow requirements.
For type V, its starting point E ε Λ: when the end point is reachedConsider data conversion; when the end point is reachedIn the eighth step, whether to add lines or adjust lines is considered in combination with passenger flow requirements.
The data conversion means that the operation data is converted into a theoretical sample to be included in a standard sample for analysis and optimization. Time of boarding (2) orOther fields give theoretical values, i.e. theoretical sites and theoretical card swiping time superimposed with theoretical time.
S 6 Performing bus service supply angle index evaluation;
respectively carrying out table pairwise association on the connection bus station, the corresponding subway station, the transit bus line, all transit bus stations of the transit bus line and the longitude and latitude of each station; with the association table as an input, a supply angle index value is calculated, the specific index including: the related indexes of the connection sites, namely the number N of the connection sites and the transfer distance L; connection line related index: transfer line number, connection distance D, connection coverage; the relevant index of the opening frequency, namely the opening frequency;
the transfer distance L is calculated only by the average value of the transfer distances between each connection bus station and the subway according to the supply angle, and the specific formula is shown in the formula (2);
wherein: l (L) i The average transfer distance of the bus station connected with each entrance and exit of the subway station i;
N i -is the groundThe total number of bus stops connected with each entrance and exit of the iron station i;
in the embodiment, the number of the connection lines, the connection distance data, the connection coverage, the bus line broken line coefficient and the running frequency F are calculated r And carrying out evaluation calculation on the bus service supply angle index.
The specific calculation is as follows: and counting the number of the transit lines according to the number of the transit stations of the connection bus stations, namely deleting repeated lines such as uplink and downlink, collinear multi-phase stations and the like, and counting the number of the non-repeated transit lines connected with each subway station.
Docking distance D: in the association tables of subway stations, connection bus lines and primary connection bus stations, the shortest path between the primary connection bus stations and the corresponding subway stations is calculated by means of a network analysis tool of an ArcGIS, the impedance is set to be the path (meter), the iteration range is the total elements of the primary connection bus stations, and the theoretical connection distance of the force of each primary connection bus station is calculated. At this time, the problem of the large probability of the many-to-many exists, namely that the names of a plurality of stations in the field of the bus station to be connected at one time are the same, but the subway station to be connected is different, and the connection direction and the scheme are different. In order to ensure the uniqueness of the connection direction of each primary connection bus station, a subway station with the smallest theoretical connection distance is selected as a connection scheme for reaching a subway network at the primary connection bus station. Ensuring that each one-time connection bus station corresponds to a unique subway station, wherein connection lines can be non-unique and are reserved in addition, and the connection lines are shown in the formula (4);
d=min (total_distance) 1 Total_distance 2 Total_distance 3 … Total_distance i ) (4)
Wherein: d-is a theoretical value of the connection distance from the bus connection station to the corresponding unique connection subway station;
total_distance i -is the shortest path calculation for the one-time docking bus station with subway station i.
In this embodiment, according to the actual running situation of each connection line, the actual connection distance of the connection bus station for connecting different lines at one time is reserved as the connection distance-total_distance of the connection bus station for connecting different lines at one time.
Docking coverage: according to the distribution condition of the bus stops at one time, calculating the Thiessen polygon covered by the connection, analyzing the service area of each connection stop responsible for covering, and ensuring that the smaller the area is, the more perfect the service is. If a large area is connected only by depending on one station, the bus station and line service are added in the eighth step in consideration of passenger flow demand.
Bus route broken line coefficient: calculating the discount coefficient of the bus line connected with the subway station, storing the discount coefficient as a new field, combining the weighted connection distance field in the eighth step, and considering the bus rapid line or the peak rapid line connected by increasing and opening.
Frequency of operation F r : in actual bus running, common bus types include conventional bus, peak bus, bus microcirculation, timing bus, rapid bus and the like, and in order to ensure to reflect the actual situation of the switching bus switching frequency, the switching frequency is subjected to statistical average according to the types and the time periods: the driving frequencies of various buses in the working day peak/flat peak and non-working day three periods are calculated, and the subway station is used as a key field for classification, summarization and averaging. Because of more types and difficult statistics of bus shifts, the proposal is to carry out statistics by stages and types: the first stage excludes timing bus, calculates the average value of the departure frequency of each subway station in three periods through the bus line; and (3) in the second stage, checking the primary bus connection station with the empty departure frequency field calculated in the first stage, and calculating the departure frequency average value of the timing bus line in three periods, wherein the departure frequency average value is shown in the formula (5).
F ri weekday/peak ＝∑ Workday day (∑ Early peak Num Early stage +∑ Peak in noon Num Noon +∑ Peak at night Num Late time +…)/∑T Peak (5)
Wherein: f (F) ri weekday/peak -is a subway station i; the average running frequency of the connected bus line in the working day peak time;
Nnm n -total departure of bus routes through subway stations during the peak hours;
T Peak -the peak time period
The automatic output index is the general supply level condition of the bus connected without considering the service passenger flow condition, and is used for describing the outline of the bus connected service of the city of the study object in the subway new line opening stage.
In this embodiment, the standardized and integrated transfer IC card swiping data, network bus/taxi conversion data, bus trip conversion data and supply data are respectively associated with each other, and the associated fields are key fields such as subway stations, bus lines, etc.
Taking the association table as input, calculating the angle index value of the passenger flow service effect, wherein the specific indexes comprise: weighted transfer distance of relevant indexes of connection siteTransfer time I t The method comprises the steps of carrying out a first treatment on the surface of the Connection line related index: weighted docking distance->Connection time F t The method comprises the steps of carrying out a first treatment on the surface of the Running frequency related index-waiting time W t The method comprises the steps of carrying out a first treatment on the surface of the The average number, upper and lower quartiles, 85% fraction and 95% fraction of the index of the total sample are calculated.
In this embodiment, since the sample data has a certain data error, each index data needs to be subjected to three processing stages of data cleaning (outlier removal), key index calculation and service pain point mining.
Data cleaning is mainly based on the following ranges: [ Q 1 -1.5(Q 3 -Q 1 )，Q 3 +1.5(Q 3 -Q 1 )]
Wherein Q is 1 And Q 3 Is the upper and lower quartile of index X. If the sample is not within the above range, it can be determined that the outlier is determined to be independent, if there is an abnormality (such as a transfer distance of 100m, a transfer time of 25 minutes, etc.), an outlier can be marked in the index (the transfer time outlier is marked in the above example), and the index optimization step is not participatedAnd (5) carrying out statistical calculation on the segments.
And calculating a key index, namely calculating an average number, upper and lower quartiles, 85% fraction and 95% fraction of the index after abnormal values are removed. The average value is used for judging the overall service effect of the index of the city; the 85% fraction and the 95% fraction are used for judging the overall acceptable, tolerable and equivalent extent of the city to the index; the upper quartile and the lower quartile are used for calculating outlier calculation after outlier removal, and searching for a service pain point.
And (3) mining a service pain point, combining 95% of fractional numbers and a second round of outlier calculation, searching samples with poor index response, and labeling sample characteristics for overall optimization in the eighth step.
Weighted transfer distanceThe passenger flow sample total set after data identification and conversion is connected with the supply data according to (5) subway bus station and +.>After the two fields of the subway connection bus station are respectively associated in a table, two connection distance (total_path) fields are obtained. Because the transfer distance has no obvious directivity, two fields of one sample can be counted as two samples for two trips of one person, an ID assignment field is newly established, and the subway bus stop and the +.>Subway connection bus station fields, namely connection bus station fields, combining corresponding (7) initial subway station fields and (9) termination subway station fields, namely subway station fields, and reserving total_path fields to obtain calculation weighted transfer distance->Is a new sample set of (a). The SPSS is used for carrying out descriptive statistics on the finished samples, and the distribution (judging whether the samples are normally distributed) and the average, the upper and lower quartiles, the 85 percent fraction and the 95 percent fraction are observed, becauseIs a full sample average, corresponding to an average weighted passenger flow, as in equations (6) - (7).
Wherein:the average transfer distance of passengers taking a 'subway-bus' travel mode is counted by the current IC card swiping information and taken over and down at a subway station i (from the combined subway station field).
-total number of samples with bus transfer behavior or transfer potential at subway station i.
The average transfer distance from the bus transfer station j to the subway station i is the classified and summarized main ID of the passengers who are counted through the IC card swiping information and adopt the subway-bus travel mode.
-total number of samples with transfer behaviour or transfer potential at bus stop j of subway station i.
Transfer time I t : calculating two card swiping time differences of card swiping time 1 of a fifth-step field (6) connection bus station and card swiping time of field (8) subway arrival to obtain a transfer time field of bus connection station to subway-bus subway transfer time, wherein the reserved field comprises (5) connection subway bus station, (7) initial subway station and bus subway transfer timeThe multiplication time is three, and the calculated transfer time I is obtained t New samples. The sample distribution (to determine whether normal distribution) and average, upper and lower quartiles, 85% fraction and 95% fraction are analyzed, and the average of the passenger flows is weighted by the whole sample average, as in the formulas (8) - (9).
Wherein: i ti The passengers get on the bus from the subway station i, the average transfer time of the passengers in the subway station i is adopted by a 'subway-bus' traveling mode, and the subway station field is a classified summary main ID.
-total number of samples with bus transfer behavior or transfer potential at subway station i.
I tj The passengers get off from the bus connection station j and get on from the subway station i, the average transfer time of the passengers in a subway-bus travel mode is adopted, and the bus connection station field is a classified summary main ID.
-total number of samples with transfer behaviour or transfer potential at bus stop j of subway station i.
Weighted docking distanceThe passenger flow sample total set after data identification and conversion and the supply data are based on (3) departure bus stop and +.>Two fields of destination bus stop correspond onceAfter the connection bus station performs table association, two connection distance (total_distance) fields are obtained. Because the connection distance has no obvious directivity, for two trips of a person, two fields of one sample are counted into two samples to be considered, corresponding fields of (7) an initial subway station and (9) a stop subway station, which are collectively called as subway station fields, are combined, the respective connection time fields are reserved, and (3) a departure bus station and +.>Destination bus stop field, collectively called one-time connection bus stop field, merging phase (4) bus line number 1 and +.>Bus line number 2 field, collectively called bus line number field, reserves respective total_distance field, and obtains calculated weighted connection distance +.>Is a new sample set of (a). The SPSS is used for carrying out descriptive statistics on the samples after the arrangement, and the distribution (judging whether the samples are normally distributed) and the average, the upper and lower quartiles, the 85% fraction and the 95% fraction of the samples are observed, and the average is equal to the average weighted passenger flow because of the whole sample, as shown in the formula (10) -formula (12);
wherein:-currently passing through an IC cardThe card swiping information is used for counting the average connection distance of passengers taking a subway-bus travel mode in a subway station i (from the combined subway station fields), wherein the subway station is a classified summary master ID;
-the total number of samples with bus transfer behavior or transfer potential at subway station i;
the statistics is carried out currently through IC card swiping information, passengers taking advantage of and falling at a subway station i and adopting a subway-bus travel mode are carried out at average connection distances (multi-line selection exists) of a primary connection bus station k (connection bus stations including departure places and destination), and the primary connection bus station is a classified summary main ID;
-the total number of samples to be docked or having docking potential at subway station i by one docking bus station k;
the current statistics is carried out through the information of IC card swiping, the average connection distance (multi-line selection) of all passengers taking a bridge at a subway station i and connecting through a bus line r in a subway-bus travel mode is adopted, and the bus line numbers are classified and summarized main IDs;
-total number of passenger samples connected via bus route r at subway station i.
Connection time F t : calculating transfer time by SPSS (SPSS) -calculating card swiping time 1 of bus station connected with field (6) and card swiping time of departure place of field (2), and fieldCard swiping time 2 and field +.>And obtaining a connection time field by the absolute value of the card swiping time difference of the card swiping time of the destination bus station. Because the connection time has no obvious directivity, for two trips of a person, two fields of one sample can be counted as two samples to be considered, corresponding fields of (7) an initial subway station and (9) a stop subway station, which are collectively called as subway station fields, are combined, the respective connection time fields are reserved, and (3) a departure bus station and->Destination bus stop field, commonly called one-time connection bus stop field, reserves respective connection time data, and obtains calculated weighted connection distance F t Is a new sample set of (a). The SPSS is used for carrying out descriptive statistics on the samples after the arrangement, and the distribution (judging whether the samples are normally distributed) and the average, the upper and lower quartiles, the 85% fraction and the 95% fraction of the samples are observed, and the average is equal to the average weighted passenger flow because of the whole sample, as shown in the formula (13) -formula (14);
wherein: f (F) ti The average connection time from the subway station i to all the bus stations connected at one time is the average connection time, and the subway stations are the main IDs which are classified and summarized;
-the total number of samples with bus transfer behavior or transfer potential at subway station i;
F tk the statistics is carried out currently through IC card swiping information, passengers taking advantage of and falling at a subway station i and adopting a subway-bus travel mode take average connection time at a primary connection bus station k (connection bus stations including departure places and destination), and the primary connection bus stations are classified and summarized with main IDs;
-total number of samples to or with docking potential to be docked at subway station i by one docking bus station k.
Waiting time W t : the waiting time cannot be counted directly through the card swiping time, and the subway outbound card swiping time and the field need to be counted according to the field in the fifth stepAnd calculating the absolute value of the card swiping time difference of the card swiping time 2 of the bus station, and calculating the total transfer and waiting time field of the subway-bus station, thereby subtracting the average transfer time. The passenger flow sample total set after data identification and conversion and the calculated transfer time I t New samples according to the former->The subway connection bus stop field is connected with the reserved (5) connection subway bus stop field to obtain the calculated transfer time I t The new sample is reserved (5) the subway station of the connection, and (7) the three fields of the initial subway station and the transfer time of the subway station of the bus (the updated fields are named as the bus station, the subway station and the transfer time), the transfer and waiting total time field calculated in the total passenger flow sample set after data identification and conversion, and the total passenger flow sample set after data identification and conversion is reserved>Bus line number 2 field (updated field name is bus line number) for a total of five fields. Screening samples with non-empty transfer time and waiting time of bus and subway to form calculation waiting time W t Is a new sample of (a). And adding new sample field waiting time, wherein the calculation method is that the two fields of the total waiting time and the transit subway transfer time are different.
Analysis of W t The sample distribution (judging whether normal distribution is carried out) of the field, the average, the upper and lower quartiles, the 85% quantile and the 95% quantile are all the average samples, which is equivalent to the average weighted passenger flow, as shown in the formulas (15) - (16);
wherein: w (W) ti The passengers get off from the subway station i in a 'subway-bus' traveling mode, the average waiting time of the passengers at the subway station i corresponding to each connected bus station is calculated, and the subway station field is a classified summary main ID.
-the total number of samples with transfer behaviour or transfer potential at subway station i.
W tr The weighted average waiting time of passenger flow of a bus line r connected with a subway station i is obtained, and a bus line number field is a classified summary main ID;
-total number of passenger samples connected via bus route r at subway station i.
S 7 The method comprises the following steps of evaluating the angle index of the effect of the bus passenger flow;
respectively carrying out association processing on standardized and summarized transfer IC card swiping data, network bus/taxi conversion data, bus trip conversion data and supply data, wherein association fields are key fields of subway stations, bus stations and bus lines;
calculating a passenger flow service effect angle index value by taking the association table as input, wherein the specific index comprises a connection site related index, namely a weighted transfer distance and a transfer time; connection line related index: weighting the connection distance and the connection time; running frequency related index-waiting time; the average number of the indexes, the upper and lower quartiles 85% fraction and the 95% fraction of the overall sample are calculated,
and (3) carrying out three processing stages of data cleaning, outlier elimination, key index calculation and service pain point mining on each index data.
S 8 Optimizing the docking bus line by adding or extending the line, adding stations, increasing the driving frequency and improving the conventional bus traffic environment.
For step S 5 In the two cases of data conversion, when one end E of a starting end point of a network taxi or a taxi order falls within a subway service direct coverage range lambda, the other end F does not fall within a primary bus connection service coverage range omega nor within the lambda range, the orders are clustered according to one end of a subway station, the other end F is used for making 500m buffers, and when more than 3 buffers are intersected, custom buses are considered to be opened or existing lines are prolonged.
According to step S 6 And carrying out statistical description on the calculated Thiessen polygons according to the area, carrying out passenger flow statistics on the area exceeding 95% quantile, and considering increasing or prolonging the line when the radiation range of a certain station is overlarge (a large area is connected by only one station) and the daily passenger flow exceeds 10 persons.
Weighted connection distance for one-time connection bus station kAnd carrying out statistical description, namely, if the bus line of the bus station is connected, the tortuosity coefficient is larger than 1.5, and the trend of the original bus line is considered to be adjusted or the line is increased in the subway connection direction, so that the curve coefficient is reduced.
(2) Additional station
Aiming at subway station transfer service indexAnd I ti If the transfer distance and transfer time of a certain station are both greater than 95% quantile, the addition or translation of peripheral bus docking stations is considered.
Weighted average transfer distance index for transfer from bus station j to subway station iAnd carrying out statistical description, namely considering translation stations or addition stations at bus connection stations with transfer distances exceeding 95% quantile.
Counting weighted average transfer time index-I of passengers getting off from bus connection station j and getting on from subway station I in a subway-bus travel mode tj And carrying out statistical description, namely, improving transfer walking conditions of the bus docking station with more than 95% quantile transfer, and adding a three-dimensional street crossing facility according to land conditions and traffic road grades.
(3) Increasing the frequency of opening
Weighted passenger flow average waiting time index W for statistically describing bus route r tr For the bus lines with the quantile waiting time of more than 95%, the waiting time of the connected bus lines is reduced by opening timing shift lines or adding opening frequency and the like.
(4) Improving conventional public transportation environment
Weighted connection time for one-time connection bus station kCarrying out statistical description, namely, one-time connection bus station exceeding 95% quantile connection time, and if the one-time connection bus station is weighted connection distance +.>The number of quantiles is also larger than the corresponding 95%, and the optimized line is comprehensively considered; if it weights the docking distance +.>Less than 95% quantiles, consider improving the conventional public transportation environment, and preferentially ensure the public transportation right.
In this embodiment, the invention provides a bus connection optimizing device in a new subway line opening stage, which comprises a storage unit, wherein a computer program is stored on the storage unit, and the program is executed by a main controller to realize the method according to any one of the above methods.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, and various modifications and variations may be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (2)
1. The bus connection optimizing method for the subway new line opening stage is characterized by comprising the following steps:
S 1 collecting data, namely collecting general supply data of bus service stations, lines and bus line plans, bus, subway stations and line geographic information longitude and latitude, vector diagram data, and collecting all-purpose card/IC card swiping data and taxi/network taxi operation data, wherein reserved fields comprise bus stations, bus station longitude and latitude, subway stations, subway station longitude and latitude, bus lines, transit stations and departure frequency;
S 2 analyzing the bus connection state of the subway at the new line opening stage, and carrying out two-stage screening according to the acceptable walking transfer range of urban residents; according to the acceptable walking transfer range of urban residents, adopting a range of 500m to carry out two-stage screening;
S 2.1 according to the longitude and latitude of the bus station, calculating the bus station crossing with the 500m buffer zone around the subway station in the first stage;
S 2.2 in the second stage, calculating the shortest paths of the bus stations and the corresponding subway stations, specifically using a Network analysis tool of an ArcGIS to calculate the shortest paths, and calculating the connected bus stationsScreening bus stops with the value of the field less than or equal to 500m from the shortest transfer distance field-total_distance of the subway station corresponding to the bus stops;
S 3 determining a subway service coverage range lambda and a bus connection service coverage range omega at one time;
S 4 determining the passenger flow range of the bus connection optimizing service; the bus connection optimizing service passenger flow range comprises residents in a bus and subway travel mode and residents in other modes and subway travel modes;
S 5 standard data sample format and data conversion are carried out; taking the card swiping data of the passengers in the type I as a standard data sample format, and reserving fields comprises: (1) from the assigned ID, (2) departure place bus card swiping time, (3) departure place bus station, (4) bus line number 1, (5) connection subway bus station, (6) connection bus station card swiping time 1, (7) initial subway station, (8) subway station card swiping time, (9) stop subway station, subway station card swiping time, and,Subway junction bus stop, < >>Card swiping time 2, < >>Bus route number 2, & gt>Destination bus stop, < > and >>The card swiping time of the destination bus stop;
data conversion one: the passengers inconvenient to connect and not taking the long-distance buses of the subway are compared with the actual bus taking time through a formula 1, and whether the passengers are likely to be converted into a bus and subway travel mode at the stage is judged;
wherein: t (T) Theory of -assuming the travel theoretical time required after the sample is transferred to the subway main channel;
OH 1 -departure bus stop to nearest subway station H 1 Is a manhattan distance of (a);
DH 2 -destination bus stop to nearest subway station H 2 Is a manhattan distance of (a);
v—average speed of peak section (flat peak/peak) where the urban bus is located at the card swiping time;
T sub -subway station H 1 To H 2 Operating time at peak section (peak/flat) where the card swiping time is located;
-average of absolute values of swipe time differences of standard sample fields (6) and (8);
standard sample field (d) and (d)>An average value of absolute values of card swiping time differences;
T actual practice is that of -the card swiping time difference of the departure bus stop and the destination bus stop;
data conversion II: judging whether passengers who are inconvenient to select private car and subway or network taxi and subway travel have transfer conditions or not due to connection;
S 6 performing bus service supply angle index evaluation; the connection bus station, the corresponding subway station, the transit bus line, all transit bus stations of the transit bus line and the longitude and latitude of each station are respectively processed into two tablesTwo correlations; with the association table as an input, a supply angle index value is calculated, the specific index including: the related indexes of the connection sites, namely the number N of the connection sites and the transfer distance L; connection line related index: transfer line number, connection distance D, connection coverage; the relevant index of the opening frequency, namely the opening frequency;
the transfer distance L is calculated only by the average value of the transfer distances between each connection bus station and the subway according to the supply angle, and the specific formula is shown in the formula (2);
wherein: l (L) i The average transfer distance of the bus station connected with each entrance and exit of the subway station i;
N i the total number of bus stops connected with each entrance and exit of the subway station i;
then calculating the number of connection lines, connection distance data, connection coverage, bus line broken line coefficient and running frequency F r Performing evaluation calculation on bus service supply angle indexes;
S 7 the method comprises the following steps of evaluating the angle index of the effect of the bus passenger flow; respectively carrying out association processing on standardized and summarized transfer IC card swiping data, network bus/taxi conversion data, bus trip conversion data and supply data, wherein association fields are key fields of subway stations, bus stations and bus lines;
calculating a passenger flow service effect angle index value by taking the association table as input, wherein the specific index comprises a connection site related index, namely a weighted transfer distance and a transfer time; connection line related index: weighting the connection distance and the connection time; running frequency related index-waiting time; the average number, upper and lower quartiles, 85% fraction and 95% fraction of the index of the overall sample are calculated,
data cleaning is carried out on each index data, abnormal values are eliminated, and three processing stages of key index calculation and service pain point mining are carried out;
S 8 butt joint bus lineOptimizing, optimizing the docking bus route by increasing or extending routes, increasing stations and running frequency and improving the conventional bus traffic environment.
2. The bus connection optimizing device for the subway new line opening stage is characterized by comprising a storage unit, wherein a computer program is stored on the storage unit, and the program is executed by a main controller to realize the method as claimed in claim 1.
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