CN109978267A - City microcirculation public bus network planing method based on urban track traffic data - Google Patents

City microcirculation public bus network planing method based on urban track traffic data Download PDF

Info

Publication number
CN109978267A
CN109978267A CN201910247571.8A CN201910247571A CN109978267A CN 109978267 A CN109978267 A CN 109978267A CN 201910247571 A CN201910247571 A CN 201910247571A CN 109978267 A CN109978267 A CN 109978267A
Authority
CN
China
Prior art keywords
cell
passenger
website
bus
expense
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201910247571.8A
Other languages
Chinese (zh)
Other versions
CN109978267B (en
Inventor
任刚
周哲祎
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southeast University
CETC Big Data Research Institute Co Ltd
Original Assignee
Southeast University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Southeast University filed Critical Southeast University
Priority to CN201910247571.8A priority Critical patent/CN109978267B/en
Publication of CN109978267A publication Critical patent/CN109978267A/en
Application granted granted Critical
Publication of CN109978267B publication Critical patent/CN109978267B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047Optimisation of routes or paths, e.g. travelling salesman problem
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0631Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315Needs-based resource requirements planning or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40Business processes related to the transportation industry

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Tourism & Hospitality (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Traffic Control Systems (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Navigation (AREA)

Abstract

The city microcirculation public bus network planing method based on urban track traffic data that the invention discloses a kind of.The method of the present invention includes the following steps: S1. obtains urban track traffic AFC brushing card data, to multiplying in data away from for 4 stations and trip below expansion space-time analysis, determines that each rail traffic is respectively gone on a journey section spatial and temporal distributions;S2. the densely covered rail traffic trip section of certain short distance trip is chosen, each station and its road and land used in attractived region in the section are investigated;S3. half realization is carried out to the road network in examination range;S4. to the land divide cell in half Actual Road Networks, the land used attribute of each cell is investigated;S5. public bus network terminus is chosen in upstream and downstream rail traffic website attractived region, generates candidate line set;S6. it generates candidate line and corresponds to Website Hosting;S7. passenger flow is distributed to each cell, each bus station;S8. each cell passenger flow is distributed to each bus station;S9. railroad embankment scheme is generated, and chooses optimal case, step terminates.

Description

City microcirculation public bus network planing method based on urban track traffic data
Technical field:
The city microcirculation public bus network planing method based on urban track traffic data that the present invention relates to a kind of, belongs to city City's traffic planning and management technical field.
Background technique:
As the fast development of Urbanization in China, completed region of the city area constantly expand, various regions start to pay attention to city The complete construction of public transit systems.And urban track traffic carries more and more travel amounts as city bus trunk, So that partial section compartment is overstaffed.The a part of microcirculation public transport as city bus system, mentions for city dweller It is serviced for short-range quick trip, it to a certain extent being capable of alternate track friendship for the short distance trip aspect of urban inner Pass-out row.Therefore, scientific and reasonable planning is carried out to microcirculation public bus network it is of great significance to.
At this stage, the city for opening operation microcirculation public bus network is few, and the city of urban rail transit construction has been unfolded to city Short distance trip lacks concern inside city, therefore, if planning is laid with reasonable microcirculation public bus network matching track traffic lines Road transport row can provide multimode choice for traveling, the good service level for improving urban public tranlport system for traveler.
Microcirculation public bus network planing method used at present is mostly based on empirical method or resident's OD trip data And the data analysis of existing routine bus system gauze, lack the considerations of developing to urban mass-transit system, it can not be by Metro Network In short distance travelling traffic take into account.Therefore, it in order to attract the short distance travelling traffic in Metro Network, needs to seek Look for a kind of microcirculation public bus network planing method based on rail traffic data, meeting its trip characteristics.
Summary of the invention
It is micro- the purpose of the present invention is in view of the above problems, providing a kind of city based on urban track traffic data Public bus network planing method is recycled, this method passes through the analysis of rail traffic brushing card data, and analysis is extracted short distance in gauze and separated out The corresponding rail traffic website attractived region in section is chosen in the densely covered section of row, using heuritic approach, and uses actual rail Road traffic data proposes microcirculation public transport distribution method, to start the microcirculation public transport line for being more in line with practical trip characteristics Road.
Above-mentioned purpose is achieved through the following technical solutions:
A kind of city microcirculation public bus network planing method based on urban track traffic data, this method includes following step It is rapid:
S1. obtain urban track traffic AFC brushing card data, to multiply in data away from for 4 stations and trip below expansion space-time Analysis determines that each rail traffic is respectively gone on a journey section spatial and temporal distributions;
S2. the densely covered rail traffic trip section of certain short distance trip is chosen, each station and its suction in the section are investigated Draw the road and land used in range;
S3. half realization is carried out to the road network in examination range;
S4. to the land divide cell in half Actual Road Networks, the land used attribute of each cell is investigated;
S5. public bus network terminus is chosen in upstream and downstream rail traffic website attractived region, generates candidate line set;
S6. it generates candidate line and corresponds to Website Hosting;
S7. passenger flow is distributed to each cell, each bus station;
S8. each cell passenger flow is distributed to each bus station;
S9. railroad embankment scheme is generated, and chooses optimal case, step terminates.
The city microcirculation public bus network planing method based on urban track traffic data, described in step S6 The specific method that generation candidate line corresponds to Website Hosting is: not generating the route of website, setting in load candidate line set Bus station attractived region radius R;Using starting point as the center of circle, R is that radius draws circle, investigates the round friendship with route direction of advance distalmost end Point P1If it is the first bus station;Backward, it is unfolded as follows circulation, using current bus station as the center of circle, R is that radius draws circle, will The round intersection point P with path direction of advance distalmost endn, it is set as bus station, until including route terminal in garden, circulation terminates, raw At candidate line Website Hosting.
The city microcirculation public bus network planing method based on urban track traffic data, described in step S7 The specific method of distribution passenger flow to each cell, each bus station is: according to the land used attribute of each cell, its mining inetesity is investigated, Its passenger flow is marked to occur respectively, attraction coefficient λΟi、λDi;Each cell is investigated to nearest rail traffic website distance li;Define cell Passenger flow contribution rate γ, value are cell generation/attraction coefficient λiThe small nearest rail traffic website distance l of zones valuesiRatio:
Generation/attraction contribution rate: γii/li
For different periods, contribution rate attribute corresponding to each cell is different, and during morning peak, residential land cell is Contribution rate occurs, office cell is to attract contribution rate;During evening peak, residential land cell is to attract contribution rate, cell of handling official business For contribution rate occurs;
The generation passenger flow of each website in research range is distributed to passenger flow to each by accounting of the contribution rate in summation occurs Cell;The passenger flow of each cell is distributed to terminal according to accounting of the attraction contribution rate of each cell in its ending range in summation Each cell;Bus traveler assignment is completed to cell.
The city microcirculation public bus network planing method based on urban track traffic data, described in step S9 Railroad embankment scheme is generated, and the specific method for choosing optimal case is: considering passenger's travel cost and enterprise operation expense two Aspect.Wherein, passenger's travel cost is divided into passenger's walking time expense CA, passenger's riding time expense CB, passenger waiting time Expense CW;Passenger's walking time expense CA, passenger's riding time expense CBIt is laid with line alignment website and determines and determine.Wherein CAFor cell centroid to the walking time of its nearest bus station, by the distance and the point of cell centroid to road network to nearest public affairs The distance of website is handed over to constitute;CBFor the travel time between the nearest bus station of terminus cell;
Passenger waiting time expense is arranged an order according to class and grade variation with operation, in general, passenger waiting time obeys Poisson distribution, if T is The route departure interval, then its passenger waits duration interval section for [0, T], to ensure that its maximum waits duration no more than public transport hair Vehicle interval time, then:
In formula:
T: passenger's arrival time;
λ can be regarded as bus platform and be averaged Waiting time, then can useThen:
According to above-mentioned distribution can passenger's Random Waiting Time;
Operation enterprise running cost CRIt may be expressed as:
CR=(Lm)/(vT)
Wherein, L is line length, and m is vehicle own operations expense, and v is Vehicle Speed, and T is the route departure interval;
The summation of passenger's travel cost and enterprise operation expense is investigated, chooses the smallest scheme of summation as planning route.
The utility model has the advantages that
Compared with prior art, the present invention proposes a kind of city microcirculation public bus network based on urban track traffic data Planing method, the technical effect having are as follows:
1. the present invention has obtained by the analysis to actual track traffic data and has met actual short distance trip characteristics, The urban inner microcirculation layout of roads being unfolded on this basis can more accurately meet the daily short distance of city dweller From trip requirements.
2. the invention proposes a kind of heuritic approaches to have generated line alignment between determining terminus, website is laid and Operation is arranged an order according to class and grade, to improve the coverage area of route and the science of route website selection, plans operation enterprise for public transport Industry has higher application value.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Fig. 2 is the processing that half Actual Road Networks are constructed in the method for the present invention to oblique road.
Fig. 3 is road network in research range in the embodiment of the present invention.
Fig. 4 is the real road network of research range half in the embodiment of the present invention.
Fig. 5 is the half small Division of real road network in the embodiment of the present invention.
Specific embodiment
Further description of the technical solution of the present invention with example with reference to the accompanying drawing.
A kind of city microcirculation public bus network planing method based on urban track traffic data, as shown in Figure 1, including one Lower step:
S1, obtain urban track traffic AFC brushing card data, to multiply in data away from for 4 stations and trip below expansion space-time Analysis determines that each rail traffic is respectively gone on a journey section spatial and temporal distributions;Local rail transportation operation enterprise is gone to, city rail is obtained and hands over Lead to history AFC brushing card data, multiply in garbled data away from 4 stations and trip below, record its terminus and time out of the station, completes The Analysis on Spatial Temporal Distribution of all data determines short distance trip in the distribution density of each section day part.
S2 chooses the densely covered rail traffic trip section of certain short distance trip, investigates each station and its suction in the section Draw the road and land used in range;It chooses S1 step short-distance and medium-distance and goes out the big section of line density and its corresponding period, as Current research object investigates each rail traffic website and attractived region in its section, generally takes 800 meters, determine research range; The road network in range is investigated, determines the road network for public transit vehicle traveling;
S3 carries out half realization to the road network in examination range;It is approximately rectangle side by the road network in research range Half realization road of grid can be as shown in Fig. 2, be changed into the real road of fold-line-shaped half for oblique road;
S4, the land divide cell in double of Actual Road Networks, investigates the land used attribute of each cell;Duty according to different community Can, land used attribute can be divided into inhabitation, business, office, education etc.;
S5 chooses public bus network terminus in upstream and downstream rail traffic website attractived region, generates candidate line set; In research range in the rail traffic attractived region at both ends, suitable public bus network terminus is chosen, deep search is used Method, Load Line length limitation determine candidate line set;
S6 generates candidate line and corresponds to Website Hosting;The route of website is not generated in load candidate line set, setting is public Website attractived region radius R is handed over, is generally set to 300 meters;Using starting point as the center of circle, R is that radius draws circle, investigates circle and route advance side To the intersection point P of distalmost end1If it is the first bus station;Backward, it is unfolded as follows circulation, using current bus station as the center of circle, R It draws and justifies for radius, by the round intersection point P with path direction of advance distalmost endn, it is set as bus station, until whole comprising route in garden Point, circulation terminate, and generate candidate line Website Hosting.
S7, distribution passenger flow to each cell;According to the land used attribute of each cell, its mining inetesity is investigated, marks its visitor respectively Stream generation, attraction coefficient λΟi、λDi;Each cell is investigated to nearest rail traffic website distance li;Define cell passenger flow contribution rate γ, value are cell generation/attraction coefficient λiThe small nearest rail traffic website distance l of zones valuesiRatio:
Generation/attraction contribution rate: γii/li
For different periods, contribution rate attribute corresponding to each cell is different, as during morning peak, residential land cell For contribution rate occurs, office cell is to attract contribution rate.
The generation passenger flow of each website in research range is distributed to passenger flow to each by accounting of the contribution rate in summation occurs Cell;The passenger flow of each cell is distributed to terminal according to accounting of the attraction contribution rate of each cell in its ending range in summation Each cell;Bus traveler assignment is completed to cell.
S8 distributes each cell passenger flow to each bus station;According to nearest distribution principle, by each cell bus traveler assignment to distance Nearest bus station.It is more than the cell of certain value for distance, then is not given up in route attractived region.
S9 generates railroad embankment scheme, and chooses optimal case;Consider passenger's travel cost and two side of enterprise operation expense Face.Wherein, passenger's travel cost is divided into passenger's walking time expense CA, passenger's riding time expense CB, passenger waiting time takes Use CW
Passenger's walking time expense CA, passenger's riding time expense CBIt is laid with line alignment website and determines and determine.Wherein CAFor cell centroid to the walking time of its nearest bus station, by the distance and the point of cell centroid to road network to nearest public affairs The distance of website is handed over to constitute;CBFor the travel time between the nearest bus station of terminus cell;
Passenger waiting time expense is arranged an order according to class and grade variation with operation, in general, passenger waiting time obeys Poisson distribution, if T is The route departure interval, then its passenger waits duration interval section for [0, T], to ensure that its maximum waits duration no more than public transport hair Vehicle interval time, then:
In formula:
T: passenger's arrival time;
λ can be regarded as bus platform and be averaged Waiting time, then can useThen:
According to above-mentioned distribution can passenger's Random Waiting Time.
Operation enterprise running cost CRIt may be expressed as:
CR=(Lm)/(vT)
Wherein, L is line length, and m is vehicle own operations expense, and v is Vehicle Speed, and T is the route departure interval; The summation of passenger's travel cost and enterprise operation expense is investigated, chooses the smallest scheme of summation as planning route.
Below by example, present invention is described:
Embodiment one: by taking certain domestic city's Metro Network and its inner city as an example, to urban inner microcirculation public transport Planning is unfolded in route.
1, locality AFC history brushing card data is obtained, screening wherein multiplies away from the trip for being less than or equal to 4 stations, analyzes its space-time spy Sign, partial results such as the following table 1:
1 morning peak brushing card data example of table
2, it chooses its short-distance and medium-distance and goes on a journey and gather section as research range;Selection 11~website of website, 25 section, which is used as, grinds Study carefully range, section includes 11,10,9,25 4 websites of website.Investigate its website surrounding road and land used;Determine research range It is interior to be total to public transit vehicle walkway road network, as a result as shown in Figure 2:
3, half realization is carried out to the road network (Fig. 3) investigated in range, as a result as shown in Figure 4: wherein number is road Net node serial number.
4, double of realization road network carries out small Division, investigates each cell land used attribute.Cell division result such as Fig. 5 institute Show, number is that respective cell centroid is numbered in figure;
Each cell land used attribute in part is as shown in table 2 below:
2 cell portion land used attribute of table
5, range is investigated, road circuit node 5,59 is chosen and is used as route terminus;In route is arranged in half Actual Road Networks Length limitation is 22, determines all feasible paths between node 5,59 using deep search, forms alternative path set.
6, the path for not generating website in alternative path set, example path trend are loaded are as follows: [59,47,42,63,81, 35,69,72,33,29,73,75,28,10,21,77,20,16,12,8,0,1,2,3,4,80,5].It is the center of circle with starting point 59, 300 meters are radius (radius is 2 in corresponding half Actual Road Networks), draw circle, investigate the intersection point P of itself and path direction of advance distalmost end1, Coordinate is [2,2.73], it is arranged as the first bus station;Backward, using current bus station as the center of circle draw justify, investigate its with before path Into the intersection point of direction distalmost end, it is set as bus station, until circle includes terminal 5.Example path site location such as the following table 3:
3 path candidate website of table lays coordinate example
7, each cell land used attribute, mining inetesity according to listed by table 2 and its at a distance from respective carter traffic website, meter Calculate its passenger flow generation/attraction coefficient λΟi,
The passenger flow genetic coefficient of cell 8 is λO8=1 ÷ 6=0.183;
The attracting passenger flow coefficient of cell 133 is λD133=1 ÷ 3=0.333;
It can then show that attraction coefficient occurs for the passenger flow of all cells.As a result such as the following table 4:
According to generation/attraction coefficient in table 4 by Trip distribution to each cell:
By taking rail traffic website 25 as an example, genetic coefficient summation are as follows:
0.183+0.183+0.2+0.25+0.333=1.149
Section 25-11 is corresponded into the distribution of flow 29 to each cell:
1.149 ≈ 5 of the ÷ of cell 8:29 × 0.183
1.149 ≈ 5 of the ÷ of cell 17:29 × 0.183
1.149 ≈ 5 of the ÷ of cell 18:29 × 0.2
1.149 ≈ 6 of the ÷ of cell 27:29 × 0.25
1.149 ≈ 8 of the ÷ of cell 28:29 × 0.333
Assignment of traffic is completed to cell operation;Then each cell flow is distributed to each terminal cell, by taking cell 28 as an example, Distribute the corresponding flow 8 of cell 28 in the 25-11 of section to each cell to terminal:
Its attraction summation of rail traffic website 11 are as follows:
0.333+0.25+0.5+1=2.083
2.083 ≈ 2 of the ÷ of cell 133:9 × 0.333
2.083 ≈ 1 of the ÷ of cell 134:9 × 0.25
2.083 ≈ 2 of the ÷ of cell 144:9 × 0.5
2.083 ≈ 4 of the ÷ of cell 155:9 × 1
The assignment of traffic work for completing cell 28, can similarly obtain the assignment of traffic of remaining cell.
8, according to nearby principle, each cell is connected to nearest bus station, as a result such as the following table 5:
The nearest bus station of 5 cell of table
9, general expenses is calculated, wherein the cost of general expenses such as the following table 6:
6 general expenses cost of table
By taking 28 passenger flow 28~144 of cell as an example, general expenses are as follows:
Walking time expense:
Bus station 2 (2,2.732) and bus station 12 (10,16.823) are walked to by cell 28 (1.5,3.5) centroid Cell 144 (8.5,14.5) centroid two parts composition is walked to, is respectively 1.268 and 1.177 along path computing distance, and divided by Walking speed 6, multiplied by 15 you can get it walking time C of walking time valueA6 × 15=6.113 of=(1.268+1.177) ÷
Passenger rides expense:
It is 23 along path computing bus station 2 (2,2.732) and bus station 12 (10,16.823) distance, and divided by public affairs The vehicle speed of service 40 is handed over, multiplied by waiting time value 12, you can get it riding time CB=23 40 × 12=6.9 of ÷
Passenger waits expense:
Taking the departure interval is 10, then can calculate its Poisson distributionIt is random to generate in 0~10 section Random number is worth multiplied by waiting time by its matching value Poisson distribution, can obtain CWValue, CW=6 × 12=72;
Enterprise operation expense:
Taking the departure interval is 10, calculates to obtain line length L=36, then can calculate enterprise operation expense is CR=(36 × 300)/(40 × 10/60)=1620.
It successively can be calculated passenger's walking of all passenger flows, ride, expense of waiting, after it is summed it up with enterprise operation expense It can obtain total cost, more all paths, departure interval corresponding total cost take total cost the smallest for optimal path.

Claims (4)

1. a kind of city microcirculation public bus network planing method based on urban track traffic data, which is characterized in that this method The following steps are included:
S1. obtain urban track traffic AFC brushing card data, to multiply in data away from for 4 stations and trip below expansion space-time analysis, Determine that each rail traffic is respectively gone on a journey section spatial and temporal distributions;
S2. the densely covered rail traffic trip section of certain short distance trip is chosen, each station in the section is investigated and its attracts model Enclose interior road and land used;
S3. half realization is carried out to the road network in examination range;
S4. to the land divide cell in half Actual Road Networks, the land used attribute of each cell is investigated;
S5. public bus network terminus is chosen in upstream and downstream rail traffic website attractived region, generates candidate line set;
S6. it generates candidate line and corresponds to Website Hosting;
S7. passenger flow is distributed to each cell, each bus station;
S8. each cell passenger flow is distributed to each bus station;
S9. railroad embankment scheme is generated, and chooses optimal case, step terminates.
2. the city microcirculation public bus network planing method according to claim 1 based on urban track traffic data, It is characterized in that, the specific method that generation candidate line described in step S6 corresponds to Website Hosting is: load candidate line set In do not generate the route of website, set bus station attractived region radius R;Using starting point as the center of circle, R is that radius draws circle, investigates circle With the intersection point P of route direction of advance distalmost end1If it is the first bus station;Backward, it is unfolded as follows circulation, with current public transport Website is the center of circle, and R is that radius draws circle, by the round intersection point P with path direction of advance distalmost endn, it is set as bus station, until in garden Comprising route terminal, circulation terminates, and generates candidate line Website Hosting.
3. the city microcirculation public bus network planing method according to claim 1 based on urban track traffic data, It is characterized in that, the specific method of distribution passenger flow to each cell, each bus station described in step S7 is: the use according to each cell Ground attribute, investigates its mining inetesity, marks its passenger flow to occur respectively, attraction coefficient λΟi、λDi;Each cell is investigated to nearest track Traffic website distance li;Cell passenger flow contribution rate γ is defined, value is cell generation/attraction coefficient λiThe small nearest track of zones values is handed over Logical website distance liRatio:
Generation/attraction contribution rate: γii/li
For different periods, contribution rate attribute corresponding to each cell is different, and during morning peak, residential land cell is to occur Contribution rate, office cell are to attract contribution rate;During evening peak, residential land cell is to attract contribution rate, and office cell is hair Raw contribution rate;
The generation passenger flow of each website in research range is distributed to passenger flow to each cell by accounting of the contribution rate in summation occurs; The passenger flow of each cell is each small to terminal according to accounting distribution of the attraction contribution rate of each cell in its ending range in summation Area;Bus traveler assignment is completed to cell.
4. the city microcirculation public bus network planing method according to claim 1 based on urban track traffic data, It is characterized in that, generation railroad embankment scheme described in step S9, and the specific method for choosing optimal case is: considering that passenger goes out Two aspect of row expense and enterprise operation expense.Wherein, passenger's travel cost is divided into passenger's walking time expense CA, passenger rides Time cost CB, passenger waiting time expense CW
Passenger's walking time expense CA, passenger's riding time expense CBIt is laid with line alignment website and determines and determine.Wherein CAFor Cell centroid to its nearest bus station walking time, by the distance and the point of cell centroid to road network to nearest bus station The distance of point is constituted;CBFor the travel time between the nearest bus station of terminus cell;
Passenger waiting time expense is arranged an order according to class and grade variation with operation, in general, passenger waiting time obeys Poisson distribution, if T is route Departure interval, then its passenger waits duration interval section for [0, T], to ensure that its maximum waits duration no more than between bus departure Every the time, then:
In formula:
T: passenger's arrival time;
λ can be regarded as bus platform and be averaged Waiting time, then can useThen:
According to above-mentioned distribution can passenger's Random Waiting Time;
Operation enterprise running cost CRIt may be expressed as:
CR=(Lm)/(vT)
Wherein, L is line length, and m is vehicle own operations expense, and v is Vehicle Speed, and T is the route departure interval;
The summation of passenger's travel cost and enterprise operation expense is investigated, chooses the smallest scheme of summation as planning route.
CN201910247571.8A 2019-03-28 2019-03-28 Urban microcirculation bus route planning method based on urban rail transit data Active CN109978267B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910247571.8A CN109978267B (en) 2019-03-28 2019-03-28 Urban microcirculation bus route planning method based on urban rail transit data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910247571.8A CN109978267B (en) 2019-03-28 2019-03-28 Urban microcirculation bus route planning method based on urban rail transit data

Publications (2)

Publication Number Publication Date
CN109978267A true CN109978267A (en) 2019-07-05
CN109978267B CN109978267B (en) 2023-01-03

Family

ID=67081486

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910247571.8A Active CN109978267B (en) 2019-03-28 2019-03-28 Urban microcirculation bus route planning method based on urban rail transit data

Country Status (1)

Country Link
CN (1) CN109978267B (en)

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111860972A (en) * 2020-06-29 2020-10-30 交控科技股份有限公司 Rail transit path generation method and device
CN112419704A (en) * 2020-11-06 2021-02-26 杭州图软科技有限公司 Public transport route planning method and system based on big data
CN113160600A (en) * 2020-09-14 2021-07-23 盐城工学院 Vehicle scheduling method for urban microcirculation public transportation system
CN114613123A (en) * 2022-02-17 2022-06-10 华录智达科技股份有限公司 Public transportation intelligent scheduling method based on big data
CN114626682A (en) * 2022-02-17 2022-06-14 华录智达科技股份有限公司 Urban public transport network planning method considering aggregation area
CN114723153A (en) * 2022-04-18 2022-07-08 东南大学 A microcirculation bus route planning method based on functional area classification
CN114781725A (en) * 2022-04-22 2022-07-22 东南大学 Non-motor vehicle passenger flow attraction range judgment method for connection rail traffic
CN117435351A (en) * 2023-12-20 2024-01-23 深圳市城市交通规划设计研究中心股份有限公司 Load balancing method for road simulation distributed computation
CN117540933A (en) * 2024-01-04 2024-02-09 南京城驿城市与交通规划设计有限公司 Rail station influence division method and system considering main travel direction

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101807222A (en) * 2010-02-09 2010-08-18 武汉大学 Station-based urban public traffic network optimized configuration method
CN106097226A (en) * 2016-06-20 2016-11-09 华南理工大学 City Routine Transit Network Design method based on Hierarchical Programming
CN107345816A (en) * 2016-05-06 2017-11-14 高德信息技术有限公司 A kind of bus routes method and device for planning
US20180350237A1 (en) * 2016-10-08 2018-12-06 Dalian University Of Technology Method for estimating distribution of urban road travel time in considering operation state of taxi

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101807222A (en) * 2010-02-09 2010-08-18 武汉大学 Station-based urban public traffic network optimized configuration method
CN107345816A (en) * 2016-05-06 2017-11-14 高德信息技术有限公司 A kind of bus routes method and device for planning
CN106097226A (en) * 2016-06-20 2016-11-09 华南理工大学 City Routine Transit Network Design method based on Hierarchical Programming
US20180350237A1 (en) * 2016-10-08 2018-12-06 Dalian University Of Technology Method for estimating distribution of urban road travel time in considering operation state of taxi

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
周昭明等: "基于常规公交的轨道交通站点吸引范围研究", 《交通科技与经济》 *

Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111860972B (en) * 2020-06-29 2024-03-19 交控科技股份有限公司 Rail transit route generation method and device
CN111860972A (en) * 2020-06-29 2020-10-30 交控科技股份有限公司 Rail transit path generation method and device
CN113160600A (en) * 2020-09-14 2021-07-23 盐城工学院 Vehicle scheduling method for urban microcirculation public transportation system
CN113160600B (en) * 2020-09-14 2022-12-30 盐城工学院 Vehicle scheduling method for urban microcirculation public transportation system
CN112419704A (en) * 2020-11-06 2021-02-26 杭州图软科技有限公司 Public transport route planning method and system based on big data
CN114613123A (en) * 2022-02-17 2022-06-10 华录智达科技股份有限公司 Public transportation intelligent scheduling method based on big data
CN114626682A (en) * 2022-02-17 2022-06-14 华录智达科技股份有限公司 Urban public transport network planning method considering aggregation area
CN114723153A (en) * 2022-04-18 2022-07-08 东南大学 A microcirculation bus route planning method based on functional area classification
CN114781725A (en) * 2022-04-22 2022-07-22 东南大学 Non-motor vehicle passenger flow attraction range judgment method for connection rail traffic
CN114781725B (en) * 2022-04-22 2024-05-03 东南大学 Non-motor vehicle passenger flow attraction range judging method for connecting rail transit
CN117435351A (en) * 2023-12-20 2024-01-23 深圳市城市交通规划设计研究中心股份有限公司 Load balancing method for road simulation distributed computation
CN117435351B (en) * 2023-12-20 2024-04-30 深圳市城市交通规划设计研究中心股份有限公司 Load balancing method for road simulation distributed computation
CN117540933A (en) * 2024-01-04 2024-02-09 南京城驿城市与交通规划设计有限公司 Rail station influence division method and system considering main travel direction
CN117540933B (en) * 2024-01-04 2024-04-05 南京城驿城市与交通规划设计有限公司 Rail station influence division method and system considering main travel direction

Also Published As

Publication number Publication date
CN109978267B (en) 2023-01-03

Similar Documents

Publication Publication Date Title
CN109978267A (en) City microcirculation public bus network planing method based on urban track traffic data
CN103985247B (en) Taxi Transport capacity dispatching system based on city chauffeur demand distribution density
Zhao et al. Land use and travel burden of residents in urban fringe and rural areas: An evaluation of urban-rural integration initiatives in Beijing
CN110458589B (en) Roadside type taxi stop site selection optimization method based on track big data
CN105809962A (en) Traffic trip mode splitting method based on mobile phone data
CN106056242A (en) High-speed train operating scheme evaluation method based on passenger flow dynamic allocation
CN106022514A (en) Public electric bicycle leasing point address-selecting method based on trip chain
CN110414795B (en) Newly-increased high-speed rail junction accessibility influence method based on improved two-step mobile search method
CN110245774A (en) A method of regular service route optimization is carried out according to employee's home address
Liu et al. Understanding the route choice behaviour of metro-bikeshare users
CN106373384B (en) Outlying district regular bus circuit Real-time Generation
Wang et al. A dynamic graph-based many-to-one ride-matching approach for shared autonomous electric vehicles
Cottrell Transforming a bus station into a transit-oriented development: Improving pedestrian, bicycling, and transit connections
Song et al. MaaS for sustainable urban development
Zheng et al. The configuration of transfer facilities in integrated passenger transport hubs
Mai et al. ReStructuring Urban Space of Hanoi City on the Basis of Urban Mass Transit Development
Al-Jameel et al. Assessment of public transportation facilities: Al-Kut city as a case study
Al-Jameel et al. Investigating and Managing the Characteristics of Travel Behavior and Travel Patterns for the University of Kufa and Suggestion a Future Transportation Plan
Cheng et al. Designing Customised Bus Routes for Urban Commuters with the Existence of Multimodal Network–A Bi-Level Programming Approach
Xue et al. Cooperative Optimization of Bus-Subway-Shared Bicycle Based on Uncertainty Theory
Chen et al. The Application of Scenarios and Service Mode of Demand Response Bus
Zhang Urban development along rails in other Asian regions
Song Depot constructions prediction model for expanding One-way Carsharing operations to a new city
Cao Controlling Factors and Strategies of the Shared Bicycles in Jersey City, USA
He et al. Cross-areal Scheduling Strategy of Electric Taxi Clusters

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20191030

Address after: Four pailou Nanjing Xuanwu District of Jiangsu Province, No. 2 210096

Applicant after: SOUTHEAST University

Applicant after: CETC KEDA BIG DATA RESEARCH INSTITUTE Co.,Ltd.

Address before: Four pailou Nanjing Xuanwu District of Jiangsu Province, No. 2 210096

Applicant before: Southeast University

GR01 Patent grant
GR01 Patent grant