CN110188938A - A kind of rail traffic networking initial stage routine bus system route screening technique to be adjusted - Google Patents
A kind of rail traffic networking initial stage routine bus system route screening technique to be adjusted Download PDFInfo
- Publication number
- CN110188938A CN110188938A CN201910433889.5A CN201910433889A CN110188938A CN 110188938 A CN110188938 A CN 110188938A CN 201910433889 A CN201910433889 A CN 201910433889A CN 110188938 A CN110188938 A CN 110188938A
- Authority
- CN
- China
- Prior art keywords
- route
- bus system
- analysis
- principal component
- rail
- 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
Links
- 238000000034 method Methods 0.000 title claims abstract description 13
- 230000006855 networking Effects 0.000 title claims abstract description 9
- 238000012216 screening Methods 0.000 title claims abstract description 8
- 238000000513 principal component analysis Methods 0.000 claims abstract description 7
- 230000004069 differentiation Effects 0.000 claims abstract description 3
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000012546 transfer Methods 0.000 claims description 9
- 230000009184 walking Effects 0.000 claims description 7
- 230000000694 effects Effects 0.000 claims description 3
- 238000007417 hierarchical cluster analysis Methods 0.000 claims description 2
- 238000007619 statistical method Methods 0.000 claims description 2
- 230000002860 competitive effect Effects 0.000 claims 1
- 239000000470 constituent Substances 0.000 claims 1
- 230000001105 regulatory effect Effects 0.000 abstract description 4
- 230000010354 integration Effects 0.000 abstract description 3
- 238000004451 qualitative analysis Methods 0.000 abstract description 3
- 238000004445 quantitative analysis Methods 0.000 abstract description 3
- 238000012512 characterization method Methods 0.000 abstract description 2
- 230000002596 correlated effect Effects 0.000 abstract description 2
- 230000002708 enhancing effect Effects 0.000 abstract description 2
- 239000000284 extract Substances 0.000 abstract 1
- 239000011159 matrix material Substances 0.000 description 9
- 230000008569 process Effects 0.000 description 3
- 241000209094 Oryza Species 0.000 description 2
- 235000007164 Oryza sativa Nutrition 0.000 description 2
- 238000000540 analysis of variance Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000009472 formulation Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 235000009566 rice Nutrition 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000004836 empirical method Methods 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000002346 layers by function Substances 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of routine bus system route screening technique to be adjusted of rail traffic networking initial stage, include the following steps: the width for 1) analyzing urban rail corridor band；2) access line characteristic index carries out dimension-reduction treatment using Principal Component Analysis, extracts the principal component of characterization line characteristics；3) routing indicator in rail traffic coverage is clustered with Hierarchical Cluster, the statistical indicator for analyzing the feature of each cluster takes the regulating measures of differentiation.The present invention is on the basis of qualitative analysis, specify that ground is total to the characteristic of division on intersection road using quantitative analysis, the correlated state of routine bus system and rail traffic can be more synthetically analyzed in terms of route geometry, capacity, passenger flow demand, spatial relationship, competing conjunction relationship etc. are several, reference is provided further to formulate detailed line adjustment scheme, be conducive to public transport resources integration and reasonable distribution, alleviate two kinds of public transport modes to vie each other, enhancing linking and cooperation.
Description
Technical field
The invention belongs to public transport line optimisation technique fields, and in particular to a kind of rail traffic networking initial stage is to be adjusted
Routine bus system route screening technique.
Background technique
When routine bus system route to be adjusted on corridor is screened in domestic each city in concrete practice, the differentiation that mainly uses
According to the conllinear website number or distance for being rail line and routine bus system route, index value is obtained by empirical method, and each
There are larger differences in city.It is existing research consider routine bus system route adjustment when, generally only consider routine bus system route with
The spatial relationship of single track route has the applicability in the city at track networking initial stage to be reinforced.Networking initial stage track
Traffic often forms radial pattern network centered on Downtown, and the number of lines is at 2 or more, for serving core space or wearing
The more routine bus system route of core space, it is possible that spatially forming collinear relationship with 1 or more rail line.?
In the formulation process of adjustable strategies, it is generally principle to avoid parallel circuit competition, secondary passenger flow is cancelled or be transferred to route
Corridor fails to fully consider the transfer cooperative relationship between rail traffic and routine bus system.
Summary of the invention
To solve the above problems, the invention discloses a kind of routine bus system route screenings to be adjusted of rail traffic networking initial stage
Method specifies that ground is total to the characteristic of division on intersection road using quantitative analysis on the basis of qualitative analysis, further to formulate
Detailed line adjustment scheme provides reference.Be conducive to public transport resources integration and reasonable distribution.
In order to achieve the above objectives, technical scheme is as follows:
A kind of rail traffic networking initial stage routine bus system route screening technique to be adjusted, comprising the following steps:
1, urban rail corridor width is determined
Urban rail corridor be centered on rail line, two sides certain distance radiation scope be formed by banded regions
Domain, i.e. the routine bus system route of approach urban rail corridor should include road and its two sides parallel track where rail line
The route of road；Routine bus system route where rail line on the road of both sides of the road also will be by rail transportation operation
It influences；Urban rail corridor bandwidth is plugged into according to urban railway station walking apart from progress value.Walking is plugged into apart from by traffic tune
It discovers and seizes, 80 quartile walkings is taken to plug into distance as reference value；
2, the analysis of Influential Factors of line adjustment
The adjustment of routine bus system route needs to consider routine bus system unique characteristics factor and its contacts with rail traffic, line
The influence factor of road adjustment is broadly divided into following a few classes:
(1) route geometrical characteristic factor
Closely related between the geometrical characteristic and line function of routine bus system route, there are the routes of function difference preferably to use difference
The regulating measures of alienation.Correlative factor includes line length (kilometer), average website spacing (rice), website number (a), non-rectilinear
Coefficient etc..
(2) route capacity characteristic factor
Route capacity feature is usually adapted with line function, to influence adjustable strategies formulation.Correlative factor includes height
Peak departure interval (minute), route fitted out vehicles (), shift (secondary) etc. of daily dispatching a car.
(3) route passenger flow characteristic factor
Route passenger flow feature correlative factor can be divided into two classes, and one kind is all fronts passenger flow feature, reflect the passenger flow demand of route
With operation benefits, including the average daily volume of the flow of passengers (people times/day), average daily passenger flow intensity (* kilometers of people times/day) etc.；Second class is transfer
Passenger flow feature, characterization route are strong and weak to the attraction of transfer passenger flow, reflect the cooperation between routine bus system route and urban railway station
Relationship, correlative factor include average daily route transfer amount (people times/day), transfer amount the line is busy road volume of the flow of passengers ratio etc..
(4) route characteristic factor conllinear with urban rail corridor
The conllinear feature of route and urban rail corridor is one of the direct acting factor of line adjustment, conllinear apparent line
Road and track circuit form passenger flow competition, and emphasis is needed to consider regulating measures.Choose collinear lengths (rice), conllinear ground bus station
The description factor as conllinear feature such as number (a), conllinear ratio, wherein conllinear section selection ground public bus network and rail network
The continuous conllinear section of maximum.
3, the principal component analysis of influence factor
There are certain correlativity between the influence factor as described in step 2, using Principal Component Analysis to its into
Row dimension-reduction treatment.Principal Component Analysis is converted to line by the line adjustment influence factor that orthogonal transformation will likely have correlation
The incoherent line characteristics principal component of property.The generalized variable that each principal component factor is made of several influence factors, such as first
Principal component may be expressed as:
PC1=a1X1+a2X2+…+akXk (1)
In formula, XiFor i-th of line adjustment influence factor, aiFor the explanation weight of i-th of influence factor.
First principal component is the weighted array of k influence factor, to the explanatory maximum of the variance of variables set, Second principal component,
It is also the linear combination of initial effects factor, the explanatory of variance ranked second, while non-intersecting with first principal component.Later
Each principal component maximizes the explanation degree to variance.
It is rotated after obtaining principal component load matrix by orthogonal to enhance the interpretation of each principal component, and according to principal component
Score matrix determine the expression formulas of main variables.
4, clustering
Original factor is standardized, and calculates the principal component attribute of each route by principal component expression formula
Value.The input data as clustering is standardized to principal component attribute value again.
During Hierarchical clustering analysis, each routine bus system route belongs to one kind, each step cluster under original state
Two class routes are all polymerized to new one kind by process, and until all classes are polymerized to single class, algorithm is as follows:
Step1: defining each route is one kind；
Step2: the principal component attribute value of the every one kind of calculating and other kinds Euclidean distance；
Step3: two nearest class routes of distance are merged into one kind；
Step4: Step2 and Step3 is repeated, until being incorporated into single class comprising all routes.
Cluster number is needed in combination with line adjustment, is suitably highly being cut, and to obtained classification progress side
Difference analyses (ANOVA), judges whether the difference between a few class routes is generally significant.
And comparison for statistical analysis to the original factor feature of the route in each subset, the sky of summary and induction route subset
Between positional relationship, capacity, length characteristic the characteristics of, in conjunction with the functional hierarchy of each route, selection, which is not adjusted or taken and removes, to stop, prolongs
The measures such as length, truncation, local directed complete set, transport power adjustment and website adjustment.
The beneficial effects of the present invention are:
The present invention specifies that ground is total to the characteristic of division on intersection road, energy on the basis of qualitative analysis, using quantitative analysis
It is enough that routine bus system is more synthetically analyzed in terms of route geometry, capacity, passenger flow demand, spatial relationship, competing conjunction relationship etc. are several
With the correlated state of rail traffic, reference is provided further to formulate detailed line adjustment scheme, is conducive to public transport money
Source integration and reasonable distribution, alleviate two kinds of public transport modes and vie each other, enhancing linking and cooperation.
Detailed description of the invention
Fig. 1 is present invention public bus network screening process figure to be adjusted；
Fig. 2 is line adjustment influence factor principal component quantity judgement figure；
Fig. 3 is route subset hierarchical clustering figure.
Specific embodiment
With reference to the accompanying drawings and detailed description, the present invention is furture elucidated, it should be understood that following specific embodiments are only
For illustrating the present invention rather than limiting the scope of the invention.1, urban rail corridor bandwidth determines
Can be plugged by walking distance and land increment effect of urban rail corridor bandwidth carries out comprehensive descision.According to existing
Investigation, the walking coverage of Beijing urban railway station is about within 900m, when urban railway station 80 quartile walking in Nanjing is plugged into
Between be 12 minutes or so, maximum radius of plugging into is about 680-850m.Futian Area of Shenzhen City, Guangdong Province subway line build up after to suburb website
Residential quarter price has an impact within the scope of 700m, and No. 13 lines of Beijing Rail Transit generate the house within the scope of 1km along the line obvious
Increment effect.Determine that urban rail corridor bandwidth is 800m after comprehensively considering.
2, line adjustment influence factor principal component analysis
By taking in October, the 2016 part operating line of certain city as an example, 180, route are randomly selected.It is examined using Pearson
Analyze the correlation between each factor, between variable there are strong correlation include average daily shift and the average daily volume of the flow of passengers (0.704),
Fitted out vehicles and the average daily volume of the flow of passengers (0.915), related coefficient is greater than 0.9 two-by-two between conllinear ratio, conllinear website number, collinear lengths.
Wherein transfer passenger flow ratio and correlation between other factors are weaker (being lower than 0.27).It is necessary to in addition to transfer passenger flow ratio
11 factors carry out dimension-reduction treatment.
Relevance matrix between 1 line adjustment influence factor of table
The quantity (Fig. 2) for generating principal component is differentiated according to three kinds of Kaiser-Harris criterion, parallel analysis criterion.
Kaiser-Harris criterion suggests the principal component that keeping characteristics value is greater than 1, suggests retaining true number in parallel analysis
According to characteristic value be greater than simulation obtain mean eigenvalue (red dotted line) when principal component.Two kinds of criterion suggest generating 4
Principal component.Obtained initial load matrix is subjected to orthogonal rotation and obtains the rotation load matrix of table 2,4 principal components are explained altogether
The variance of 11 factors 82%.
2 principal component load matrix of table (after rotation)
According to postrotational load matrix, the variance of the whole variables of 1 pair of principal component explains that degree is 28%, mainly by daily objective
Flow, average daily shift, peak departure interval, fitted out vehicles are explained, capacity variable can be named as.Principal component 2 explains whole changes
The variance of amount 26%, is mainly explained by conllinear ratio, collinear lengths, conllinear website number, can be named as collinear relationship variable.
Principal component 3 explains the variance of whole variables 16%, is explained by line length, website number, is named as line length change
Amount.Principal component 4 explains the variance of whole variables 12%, is explained by average website spacing, is named as the change of website spacing
Amount.The expression formula such as table 3 of each principal component is obtained according to the score coefficient matrix of principal component.
3 principal component analysis result of table
3, clustering
Principal component calculated value is standardized, system number Fig. 3 is obtained using hierarchical clustering, distance matrix calculating is adopted
Use Euclidean distance.Combined circuit adjustment needs, and selects the diced system tree graph at height is 19, obtains the line of 5 types
Road.Judge whether this difference of 12 variables between 5 class routes is generally significant respectively using variance analysis (ANOVA).It removes
Outside station spacing factor, there are significant differences between 5 class routes for dependent variable.Each subset statistical nature is shown in Table 4.
Table 4 clusters subset line characteristics statistical form
I class route is based on cross link, and situation conllinear with rail line is least obvious, and line length is longer,
Between 15-35km；For group iii route based on parallel circuit, situation conllinear with rail line is obvious, conveyance equilibrium and
Passenger flow demand is big, and line length is most short, in 15km or less；V class route is equally based on parallel circuit, with rail traffic
The conllinear situation of route is the most obvious, and conveyance equilibrium and passenger flow demand are small.Section II, IV class route are based on route of plugging into, with rail
Road traffic has good cooperative relationship.In conjunction with overall control strategy, route to be adjusted accounts for total line quantitative proportion and preferably controls
5% or so, determine that routine bus system route to be adjusted is chosen from I, III, V class route.In conjunction with the functional layer of each route
It is secondary, it formulates the selectable adjustable strategies of route and is shown in Table 5.
The 5 selectable regulating measures of all types of routes of table
The technical means disclosed in the embodiments of the present invention is not limited only to technological means disclosed in above embodiment, further includes
Technical solution consisting of any combination of the above technical features.
Claims (1)
1. a kind of rail traffic networking initial stage routine bus system route screening technique to be adjusted, which is characterized in that this method includes such as
Lower step:
Step 1: the analysis of urban track traffic width of corridor
According to maximum walking plug into distance and urban railway station periphery land increment effect analysis urban rail corridor band width, with
Competitive space of the urban rail corridor as rail line and routine bus system；
Step 2: routine bus system line characteristics principal component analysis
The influence factor of analyzing influence routine bus system adjustment, including line length, website number, average station spacing, non-linear coefficient,
Collinearly stand number, route and the rail traffic of shift number, peak departure interval, route and rail traffic of dispatching a car of route fitted out vehicles, day is total
Line length, route and rail traffic collinear lengths the line is busy road overall length ratio, the average daily volume of the flow of passengers of route, route and orbit traffic transfer
The volume of the flow of passengers, route are associated with orbital station with orbit traffic transfer relevance intensity, route and count these factors；Each factor is led
Constituent analysis generates the principal component of routine bus system characteristic factor；
Step 3: the analysis of routine bus system route clustering and differentiation adjustment set determine
The standardized value for calculating line adjustment influence factor principal component, it is using Hierarchical clustering analysis that public bus network is special according to route
The different demarcation of sign is several subsets, and for statistical analysis to the characteristic factor of the route in subset, summarizes subset route
Feature；The functional hierarchy of cluster result combined circuit is divided and carries out cross division, selects the corresponding adjustable strategies of all kinds of routes.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910433889.5A CN110188938B (en) | 2019-05-23 | 2019-05-23 | Method for screening ground bus lines to be adjusted in early stage of rail transit networking |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910433889.5A CN110188938B (en) | 2019-05-23 | 2019-05-23 | Method for screening ground bus lines to be adjusted in early stage of rail transit networking |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110188938A true CN110188938A (en) | 2019-08-30 |
| CN110188938B CN110188938B (en) | 2023-08-22 |
Family
ID=67717532
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910433889.5A Active CN110188938B (en) | 2019-05-23 | 2019-05-23 | Method for screening ground bus lines to be adjusted in early stage of rail transit networking |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110188938B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111161560A (en) * | 2019-12-27 | 2020-05-15 | 青岛海信网络科技股份有限公司 | Bus corridor operation order management method and device |
| CN111160722A (en) * | 2019-12-12 | 2020-05-15 | 华侨大学 | Bus route adjusting method based on passenger flow competition relationship |
| CN112200393A (en) * | 2020-12-04 | 2021-01-08 | 深圳市城市交通规划设计研究中心股份有限公司 | Public transport line generation method, device, equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106652434A (en) * | 2016-12-02 | 2017-05-10 | 东南大学 | Bus dispatching method based on rail transit coordination |
| CN107729938A (en) * | 2017-12-11 | 2018-02-23 | 北方工业大学 | Rail station classification method based on bus connection radiation zone characteristics |
| CN109063906A (en) * | 2018-07-23 | 2018-12-21 | 苏州规划设计研究院股份有限公司 | The net of public transport track two merges lower overlapping route recognition methods |
-
2019
- 2019-05-23 CN CN201910433889.5A patent/CN110188938B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106652434A (en) * | 2016-12-02 | 2017-05-10 | 东南大学 | Bus dispatching method based on rail transit coordination |
| CN107729938A (en) * | 2017-12-11 | 2018-02-23 | 北方工业大学 | Rail station classification method based on bus connection radiation zone characteristics |
| CN109063906A (en) * | 2018-07-23 | 2018-12-21 | 苏州规划设计研究院股份有限公司 | The net of public transport track two merges lower overlapping route recognition methods |
Non-Patent Citations (1)
| Title |
|---|
| 李家斌 等: "城市轨道交通运营初期地面公交线网调整策略研究", 《现代城市研究》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111160722A (en) * | 2019-12-12 | 2020-05-15 | 华侨大学 | Bus route adjusting method based on passenger flow competition relationship |
| CN111160722B (en) * | 2019-12-12 | 2022-05-03 | 华侨大学 | Bus route adjusting method based on passenger flow competition relationship |
| CN111161560A (en) * | 2019-12-27 | 2020-05-15 | 青岛海信网络科技股份有限公司 | Bus corridor operation order management method and device |
| CN111161560B (en) * | 2019-12-27 | 2021-05-11 | 青岛海信网络科技股份有限公司 | Bus corridor operation order management method and device |
| CN112200393A (en) * | 2020-12-04 | 2021-01-08 | 深圳市城市交通规划设计研究中心股份有限公司 | Public transport line generation method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110188938B (en) | 2023-08-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108053062B (en) | Customized bus route generation method based on multi-source data | |
| CN110188938A (en) | A kind of rail traffic networking initial stage routine bus system route screening technique to be adjusted | |
| CN104809112B (en) | A kind of city bus development level integrated evaluating method based on multi-source data | |
| CN104778834B (en) | Urban road traffic jam judging method based on vehicle GPS data | |
| CN109636137A (en) | Electric automobile charging station planning and distributing method and system based on step analysis | |
| CN102637357A (en) | Regional traffic state assessment method | |
| CN111861022B (en) | Method for optimizing electric vehicle charging station site selection based on big data analysis | |
| CN106408984A (en) | Urban traffic flow guidance system based on Internet of things | |
| CN114037175B (en) | Large-scale public transportation network hierarchical optimization method based on multi-scale clustering | |
| CN111460598B (en) | Bus trunk line network generation method based on machine learning | |
| CN107085939B (en) | A kind of highway VMS layout optimization method divided based on road network grade | |
| CN109492874A (en) | A kind of decision-making technique of three levels power distribution network investment decision system | |
| Liang et al. | An Overlapping Phase Approach to Optimize Bus Signal Priority Control under Two‐Way Signal Coordination on Urban Arterials | |
| CN106980942A (en) | Calculate method of the bicycle free way to the coverage of public bicycles lease point | |
| CN108416531A (en) | A kind of automatic evaluation method of distribution automation planning design effect | |
| CN104850900A (en) | Public bicycle system branch layout optimization complete set method | |
| CN106845727A (en) | Consider the highway quick charge station heuristic programming algorithm of distribution trend constraint | |
| CN111768628A (en) | Intelligent traffic management method based on traffic flow regulation | |
| CN112116124A (en) | Auditing method of bus network optimization scheme based on traveler visual angle | |
| CN110020799A (en) | A kind of municipal administration's gridding resource configuration based on space-time datum | |
| Sun et al. | An AHP-Fuzzy comprehensive evaluation model for parking lots in urban CBD area | |
| Kłos et al. | Performance evaluation of roundabouts using a microscopic simulation model | |
| CN104881822A (en) | Evaluation method, device and system | |
| Ma et al. | An influence analytical model of dedicated bus lane on network traffic by macroscopic fundamental diagram | |
| Arya et al. | Strategic Placement of Electric Vehicle Charging Stations Using Grading Algorithm |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |