CN109520499A - Region isochronal method in real time is realized based on vehicle GPS track data - Google Patents
Region isochronal method in real time is realized based on vehicle GPS track data Download PDFInfo
- Publication number
- CN109520499A CN109520499A CN201811167355.4A CN201811167355A CN109520499A CN 109520499 A CN109520499 A CN 109520499A CN 201811167355 A CN201811167355 A CN 201811167355A CN 109520499 A CN109520499 A CN 109520499A
- Authority
- CN
- China
- Prior art keywords
- grid
- time
- track data
- region
- gps track
- 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
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Automation & Control Theory (AREA)
- Navigation (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention discloses one kind to realize region isochronal method in real time based on vehicle GPS track data, includes the following steps: to acquire the vehicle GPS track data in specified region, is screened, pre-processed to vehicle GPS track data；Distance value M is selected, gridding is carried out to specified region；It is that the grid after each gridding fills corresponding speed according to vehicle GPS track data；Each grid is regarded as a crossing, calculates the running time between any two crossing in specified region；The characteristics of present invention has the driving path that taxi is extracted using the GPS data of taxi, and the journey time between each grid pair is calculated in conjunction with shortest path first, Appreciation gist as accessibility.
Description
Technical field
The present invention relates to traffic zone accessibility technical fields, real based on vehicle GPS track data more particularly, to one kind
Show region isochronal method in real time.
Background technique
City space information is expressed in a manner of digitized, is that intelligent traffic, dynamic navigation and logistics distribution etc. are daily
Demand, which provides optimizing decision, supports it is the correlative study of Contemporary Digital city and the hot issue that Informatization Service is applied, and accessibility is made
It is the deciding factor of spatial behavior and spatial decision for the main space reason in above-mentioned hot issue research.Accessibility is used
In the complexity that description people are arrived at the destination using specific traffic system from a certain place.It is handed over as a kind of reflection
The basic index of logical cost, accessibility are widely used in the research such as Urban Traffic Planning, time suboptimal control, traffic economics
Field.
In city, different goes out line direction, and accessibility is often different.Therefore, it is necessary to up to Journal of Sex Research
In contemplate line direction, its accessibility is at times analyzed in point direction.Space-time accessibility is that one kind goes out from individual angle
Hair comprehensively considers space factor and time factor, the method for studying the reachable space-time unique under specific space-time restriction, the party
The concept of GIS technology and time suboptimal control is combined research transportation network accessibility by method.Isochrone is based on road network
Analysis method of reachability, for indicating from starting point, in the company by all points that can be reached of identical space-time restriction
Line, generation need to analyze road network characteristic and traffic status, and form can reflect accessibility rule.
With the fast development of Urbanization Process In China, a large amount of population pours in city, and the scale in city is caused constantly to expand
Greatly, Urban traffic demand amount surges.Simultaneously as the raising of social and economic level, Chinese vehicle ownership is sharply increased, machine
It is dynamic to dissolve capable ratio and constantly rise, cause urban transport problems to become increasingly conspicuous, especially city traffic congestion is very serious.
Traffic congestion causes vehicle that can not travel by desin speed on road, and practical passage speed, which is often below, to be set
Timing speed.Thus the estimation of accessibility can be made to generate deviation using design speed per hour.
With the continuous development of wireless location and mechanics of communication, the Floating Car based on GPS can be realized round-the-clock, a wide range of
Dynamic traffic information collecting, make it possible the reachable Journal of Sex Research of road actual traffic situation.Floating current vehicle GPS data
In traffic and urban study field extensive application, as traffic accident monitors automatically, the monitoring of road network operational efficiency, the trip of people
Behavioural analysis and the estimation of link traversal time etc..
In traditional traffic accessibility research, due to being limited by technical conditions, theory analysis is laid particular emphasis on mostly, no
Can in a manner of scheming intuitively coming out as the result is shown, therefore, in urban planning using traffic accessibility analyze the result is that than
More difficult.
Summary of the invention
Goal of the invention of the invention is to overcome and carry out estimation meeting band to accessibility using design speed per hour in the prior art
The deficiency for carrying out deviation provides one kind based on vehicle GPS track data and realizes region isochronal method in real time.
To achieve the goals above, the invention adopts the following technical scheme:
One kind realizing region isochronal method in real time based on vehicle GPS track data, includes the following steps:
(1-1) acquires the vehicle GPS track data in specified region, is screened to vehicle GPS track data, is located in advance
Reason；
(1-2) selects distance value M, carries out gridding to specified region；
(1-3) is that the grid after each gridding fills corresponding speed according to vehicle GPS track data；
(1-4) regards each grid as a crossing, calculates the running time between any two crossing in specified region；
(1-5) provides 5 specified time point T1, T2, T3, T4, T5, calculate from each crossing at the specified time point to
The boundary point reached；
(1-6) connects the boundary point in each time point, obtains each crossing and sets out in the isochrone of various time points, clearly
The serious boundary point of indent in isochrone is washed, the isochrone from each crossing on 5 specified time points is finally obtained.
The present invention extracts the driving path of taxi using the GPS data of taxi, calculates in conjunction with shortest path first
Journey time between each grid pair obtains isochrone and its rendering according to journey time as the Appreciation gist of accessibility
Figure, effect meet reality.
Preferably, (1-1) includes the following steps:
The longitude in the specified region is located at [lo1, lo2] section, latitude is located at [la1, la2] section, every vehicle GPS
Track data includes field license plate number car_id, position longitude lo, position latitude la, time time, current vehicle speed speed；
The vehicle GPS track data of each car is sorted to form an independent track route according to time sequencing.
Preferably, (1-2) includes the following steps:
Specified region is divided according to side length M, generates the square of the side lengths M such as multiple, the number of each square is positive
Position where the longitude and latitude in the rectangular lower left corner is denoted as j*len (lo_list)+i, wherein j is the position of latitude, and i is longitude
Position, after len (lo_list) specifies region to be divided according to side length M along longitudinal, obtained number.
Preferably, (1-3) includes the following steps:
Each track of vehicle track data is traversed, for specifying the data in region, finds the starting point longitude and latitude of route
Grid number where the grid number and terminal longitude and latitude at place, is formed by the possessive case in matrix in two diagonal grid
The current vehicle speed speed of tracks data is inserted into son.
Preferably, (1-4) includes the following steps:
Each grid is regarded as a crossing, the longitude and latitude in the grid lower left corner is considered as the longitude and latitude at crossing；Calculate any two
The distance between lower left corner of grid dist and azimuth angle, angle are the line and direct north in the two grid lower left corner
Angle.
The current vehicle speed speed two grid being formed by the matrix where diagonal line in all sub-boxes for including
It is ranked up, obtains current vehicle speed speed sequence, take the current vehicle speed speed for coming middle position in current vehicle speed speed sequence
Numerical value v, the running time between two grid is calculated using formula dist/v.
Preferably, (1-5) includes the following steps:
Select specified time point TiData in range, i=1,2 ..., 5；It will be using the same crossing as the data of starting point
It is divided into one group to discuss, for each group of data, centered on starting point, by data to specify azimuth a1It is divided intoIt is a
Group selects the crossing farthest apart from starting point in each group, and using the crossing farthest apart from starting point as time point TiModel
The feasible boundary point of interior vehicle is enclosed, gives gained boundary point to sequence number in the direction of the clock, if between the point of two neighboring boundary
Orientation difference be greater than a2Degree then adds starting point as boundary point between two neighboring boundary point, and resequences.
Preferably, (1-6) includes the following steps:
It cleans for the first time: deleting 3 lines presentation concave configurations in the same period and angle is less than a3Degree is located at
Between boundary point；
Second of cleaning: each current time T of each starting point is deletediPositioned at small time Ti-1, Ti-2..., T1In range
Boundary point, and deleted simultaneously in bigger time point Ti+1, Ti+2..., T5Upper duplicate boundary point.
Preferably, there are the grid in path to the shortest path in information with all for the grid pair that path is not present
Diameter calculates corresponding velocity amplitude divided by corresponding journey time, and obtained all velocity amplitudes are ranked up, velocity amplitude is obtained
Sequence takes the median w in speed value sequence, the row as the velocity amplitude between missing speed grid, between the grid pair in no path
Sailing the time is shortest path divided by w.
It is calculated at the time of journey time is according to corresponding to two grid of the grid pair on vehicle GPS track data.
Preferably, the shortest path is obtained using Floyd-Warshall algorithm:
If DI1, j1, kFor from grid i1 to grid j1 only with { 1,2 ..., k } set in node be intermediate node most
The length of short path, if shortest path passes through grid k, DI1, j1, k=DI1, k, k-1+DK, j1, k-1,
Otherwise DI1, j1, k=DI1, j1, k-1, therefore DI1, j1, k=min { DI1, j1, k-1, DI1, k, k-1+DK, j1, k-1}。
Therefore, the invention has the following beneficial effects: using taxi GPS data extract taxi driving path,
The journey time between each grid pair is calculated in conjunction with shortest path first, as the Appreciation gist of accessibility, according to stroke
Time obtains isochrone and its rendering figure, effect meet reality, is conducive to analyze traffic accessibility.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the invention；
Fig. 2 is a kind of area results schematic diagram of the invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and detailed description.
As shown in Figure 1, a kind of realize region isochronal method in real time based on vehicle GPS track data, including walk as follows
It is rapid:
Step 100, the vehicle GPS track data in specified region is acquired, vehicle GPS track data is screened, in advance
Processing:
Acquisition longitude is located at [120.5,121.0], and latitude is located at the vehicle GPS track data in [30.5,31.0] range,
The GPS track data of each vehicle form an independent track route according to time-sequencing；
Step 200, distance value M is selected, gridding is carried out to specified region:
Reasonable distance value M=500m is selected, longitude is located at [120.5,121.0], latitude is located at [30.5,31.0]
Regional network is formatted, the corresponding number of each grid；
Step 300, it is that the grid after each gridding fills corresponding speed according to vehicle GPS track data:
According to the vehicle GPS tracks data in step 100, the grid number where the starting point longitude and latitude of route is found
Two diagonal grid are formed by all grid in matrix and are all inserted into the route by the grid number with where terminal longitude and latitude
The current vehicle speed speed of track data；
Step 400, each grid is regarded as a crossing, is calculated between any two crossing in specified region when driving
Between:
For the region after gridding, each grid is regarded as a crossing, the longitude and latitude in the grid lower left corner is considered as crossing
Longitude and latitude.Dist the distance between calculating any two grid, azimuth angle, angle are the company in the two grid lower left corner
The angle of line and direct north, wherein dist distance is calculated using Euclidean distance.
The current vehicle speed speed two grid being formed by the matrix where diagonal line in all sub-boxes for including
It is ranked up, obtains current vehicle speed speed sequence, take the current vehicle speed speed for coming middle position in current vehicle speed speed sequence
Numerical value v, the running time between two grid is calculated using formula dist/v.
Wherein, shortest path is obtained using Floyd-Warshall algorithm:
If DI1, j1, kFor from grid i1 to grid j1 only with { 1,2 ..., k } set in node be intermediate node most
The length of short path, if shortest path passes through grid k, DI1, j1, k=DI1, k, k-1+DK, j1, k-1,
Otherwise DI1, j1, k=DI1, j1, k-1, therefore DI1, j1, k=min { DI1, j1, k-1, DI1, k, k-1+DK, j1, k-1}。
Step 500, specified time point T is providedi, i=1,2 ..., 5；T1=200 seconds, T2=400 seconds, T3=600 seconds, T4
=800 seconds, T5=1000 seconds, each time point is recycled, the data within the scope of specified time will be using the same crossing as starting point
Data be divided into one group and discuss, for each group of data, centered on starting point, data are divided for 1 degree with specified azimuth
At 360 groups, the crossing farthest apart from starting point is selected in each group, and using the crossing farthest apart from starting point as the time
Point TiThe feasible boundary point of vehicle in range；Gained boundary point gives sequence number in the direction of the clock, if two neighboring boundary point
Between orientation difference be greater than 180 degree, then between two neighboring boundary point add starting point arranged as boundary point, and again
Sequence finds out the boundary point of each starting point each period；
Step 600, connect the boundary point in each time point, obtain each crossing set out various time points it is equal whens
Line；Indent in cleaning isochrone is serious and the time does not meet actual boundary point: cleaning, is deleted in the same period for the first time
Concave configuration is presented in 3 lines and angle is located in the middle boundary point less than 90 degree；Second of cleaning, deletes each starting point
Each current time TiPositioned at small time Ti-1, Ti-2..., T1Boundary point in range, and bigger time T is deleted simultaneouslyi+1,
Ti+2..., T5Duplicate boundary point in range.For example, current point in time is T3=600 seconds, then delete be located at 200 seconds time and
Boundary point within the scope of 400 seconds, and delete be the time 800 seconds simultaneously, the boundary point on 1000 seconds.
As shown in Fig. 2, obtaining area results schematic diagram, wherein point in the middle part of Fig. 2 is a crossing, 4 of crossing periphery
Isochrone is using the crossing as the T of starting point1=200 seconds, T2=400 seconds, T3=600 seconds, T4=800 seconds isochrones, the present invention
Intuitively isochrone can be shown by way of figure, be conducive to analyze traffic accessibility.
It should be understood that this embodiment is only used to illustrate the invention but not to limit the scope of the invention.In addition, it should also be understood that,
After having read the content of the invention lectured, those skilled in the art can make various modifications or changes to the present invention, these etc.
Valence form is also fallen within the scope of the appended claims of the present application.
Claims (9)
1. one kind realizes region isochronal method in real time based on vehicle GPS track data, characterized in that include the following steps:
(1-1) acquires the vehicle GPS track data in specified region, is screened, is pre-processed to vehicle GPS track data；
(1-2) selects distance value M, carries out gridding to specified region；
(1-3) is that the grid after each gridding fills corresponding speed according to vehicle GPS track data；
(1-4) regards each grid as a crossing, calculates the running time between any two crossing in specified region；
(1-5) provides 5 specified time point T1, T2, T3, T4, T5, calculate and reach at the specified time point from each crossing
Boundary point；
(1-6) connects the boundary point in each time point, obtains each crossing and sets out in the isochrone of various time points, cleaning etc.
When line in the serious boundary point of indent, finally obtain the isochrone from each crossing on 5 specified time points.
2. according to claim 1 realize region isochronal method in real time, feature based on vehicle GPS track data
It is that (1-1) includes the following steps:
The longitude in the specified region is located at [lo1, lo2] section, latitude is located at [la1, la2] section, every vehicle GPS track number
According to comprising field license plate number car_id, position longitude lo, position latitude la, time time, current vehicle speed speed；According to when
Between sequence the vehicle GPS track data of each car is sorted to form an independent track route.
3. according to claim 1 realize region isochronal method in real time, feature based on vehicle GPS track data
It is that (1-2) includes the following steps:
Specified region is divided according to side length M, generates the square of the side lengths M such as multiple, the number of each square is square
Position where the longitude and latitude in the lower left corner is denoted as j*len (lo_list)+i, wherein j is the position of latitude, and i is the position of longitude
It sets, after len (lo_list) specifies region to be divided according to side length M along longitudinal, obtained number.
4. according to claim 1 realize region isochronal method in real time, feature based on vehicle GPS track data
It is that (1-3) includes the following steps:
Each track of vehicle track data is traversed, for specifying the data in region, finds the starting point longitude and latitude place of route
Grid number and terminal longitude and latitude where grid number, be formed by all grid in matrix in two diagonal grid
It is inserted into the current vehicle speed speed of tracks data.
5. according to claim 1 realize region isochronal method in real time, feature based on vehicle GPS track data
It is that (1-4) includes the following steps:
Each grid is regarded as a crossing, the longitude and latitude in the grid lower left corner is considered as the longitude and latitude at crossing；Calculate any two grid
The distance between lower left corner dist and azimuth angle, angle be the line in two grid lower left corners and the folder of direct north
Angle.
The current vehicle speed speed being formed by the matrix where diagonal line to two grid in all sub-boxes for including is carried out
Sequence, obtains current vehicle speed speed sequence, takes the number of the current vehicle speed speed for coming middle position in current vehicle speed speed sequence
The running time between two grid is calculated using formula dist/v in value v.
6. according to claim 1 realize region isochronal method in real time, feature based on vehicle GPS track data
It is that (1-5) includes the following steps:
Select specified time point TiData in range, i=1,2 ..., 5；One will be divided by the data of starting point of the same crossing
Group is discussed, for each group of data, centered on starting point, by data to specify azimuth a1It is divided intoA group,
The crossing farthest apart from starting point is selected in each group, and using the crossing farthest apart from starting point as time point TiVehicle in range
Feasible boundary point, gives gained boundary point to sequence number, if the orientation between the point of two neighboring boundary in the direction of the clock
Difference is greater than a2Degree then adds starting point as boundary point between two neighboring boundary point, and resequences.
7. according to claim 1 or 2 or 3 or 4 or 5 or 6 realize the real-time isochrone in region based on vehicle GPS track data
Method, characterized in that (1-6) includes the following steps:
It cleans for the first time: deleting 3 lines presentation concave configurations in the same period and angle is less than a3Degree is located in the middle
Boundary point；
Second of cleaning: each current time T of each starting point is deletediPositioned at small time Ti-1, Ti-2..., T1Boundary in range
Point, and deleted simultaneously in bigger time point Ti+1, Ti+2..., T5Upper duplicate boundary point.
8. according to claim 5 realize region isochronal method in real time, feature based on vehicle GPS track data
Be, for be not present path grid pair, with it is all there are the grid in path to the shortest path in information divided by corresponding row
The journey time calculates corresponding velocity amplitude, and obtained all velocity amplitudes are ranked up, speed value sequence is obtained, takes velocity amplitude
Median w in sequence, as the velocity amplitude between missing speed grid, the running time between the grid pair in no path is most short
Path is divided by w.
9. according to claim 8 realize region isochronal method in real time, feature based on vehicle GPS track data
It is that the shortest path is obtained using Floyd-Warshall algorithm:
If DI1, j1, kFor from grid i1 to grid j1 only with { 1,2 ..., k } set in node be intermediate node shortest path
The length of diameter, if shortest path passes through grid k, DI1, j1, k=DI1, k, k-1+DK, j1, k-1,
Otherwise DI1, j1, k=DI1, j1, k-1, therefore DI1, j1, k=min { DI1, j1, k-1, DI1, k, k-1+DK, j1, k-1}。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811167355.4A CN109520499B (en) | 2018-10-08 | 2018-10-08 | Method for realizing regional real-time isochrones based on vehicle GPS track data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811167355.4A CN109520499B (en) | 2018-10-08 | 2018-10-08 | Method for realizing regional real-time isochrones based on vehicle GPS track data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109520499A true CN109520499A (en) | 2019-03-26 |
| CN109520499B CN109520499B (en) | 2020-06-26 |
Family
ID=65772246
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811167355.4A Active CN109520499B (en) | 2018-10-08 | 2018-10-08 | Method for realizing regional real-time isochrones based on vehicle GPS track data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109520499B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110334861A (en) * | 2019-06-27 | 2019-10-15 | 四川大学 | A kind of urban area division methods based on track data |
| CN111210612A (en) * | 2019-10-29 | 2020-05-29 | 浙江浙大中控信息技术有限公司 | Method for extracting bus route track based on bus GPS data and station information |
| CN112017436A (en) * | 2020-09-09 | 2020-12-01 | 中国科学院自动化研究所 | Method and system for predicting urban traffic travel time |
| CN116311914A (en) * | 2023-02-21 | 2023-06-23 | 华南理工大学 | Road line discrete point isochronous characteristic value estimation method for traffic isochronous line |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030074132A1 (en) * | 2001-10-11 | 2003-04-17 | Microsoft Corporation | Polar coordinate-based isochrone generation |
| CN1796942A (en) * | 2004-12-21 | 2006-07-05 | 厦门雅迅网络股份有限公司 | Method for calculating route of navigating cities |
| CN106504523A (en) * | 2015-09-06 | 2017-03-15 | 阿里巴巴集团控股有限公司 | A kind of traffic isochrone information generating method and device |
| CN107291937A (en) * | 2017-07-05 | 2017-10-24 | 武汉大学 | A kind of isochronal method for visualizing of point of interest POI trips |
| CN107609682A (en) * | 2017-08-22 | 2018-01-19 | 上海世脉信息科技有限公司 | Population agglomeration middle or short term method for early warning under a kind of big data environment |
| CN108520354A (en) * | 2018-04-09 | 2018-09-11 | 江苏省城镇化和城乡规划研究中心 | A kind of compound analysis method of reachability of multiple spot traffic |
-
2018
- 2018-10-08 CN CN201811167355.4A patent/CN109520499B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030074132A1 (en) * | 2001-10-11 | 2003-04-17 | Microsoft Corporation | Polar coordinate-based isochrone generation |
| CN1796942A (en) * | 2004-12-21 | 2006-07-05 | 厦门雅迅网络股份有限公司 | Method for calculating route of navigating cities |
| CN106504523A (en) * | 2015-09-06 | 2017-03-15 | 阿里巴巴集团控股有限公司 | A kind of traffic isochrone information generating method and device |
| CN107291937A (en) * | 2017-07-05 | 2017-10-24 | 武汉大学 | A kind of isochronal method for visualizing of point of interest POI trips |
| CN107609682A (en) * | 2017-08-22 | 2018-01-19 | 上海世脉信息科技有限公司 | Population agglomeration middle or short term method for early warning under a kind of big data environment |
| CN108520354A (en) * | 2018-04-09 | 2018-09-11 | 江苏省城镇化和城乡规划研究中心 | A kind of compound analysis method of reachability of multiple spot traffic |
Non-Patent Citations (2)
| Title |
|---|
| 何亚坤 等: "等时线模型支持下的路网可达性分析", 《测绘学报》 * |
| 吴忠才 等: "基于交通等时线的城市商圈识别及交通要素研究", 《商学研究》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110334861A (en) * | 2019-06-27 | 2019-10-15 | 四川大学 | A kind of urban area division methods based on track data |
| CN110334861B (en) * | 2019-06-27 | 2021-08-27 | 四川大学 | Urban area division method based on trajectory data |
| CN111210612A (en) * | 2019-10-29 | 2020-05-29 | 浙江浙大中控信息技术有限公司 | Method for extracting bus route track based on bus GPS data and station information |
| CN111210612B (en) * | 2019-10-29 | 2021-01-19 | 浙江浙大中控信息技术有限公司 | Method for extracting bus route track based on bus GPS data and station information |
| CN112017436A (en) * | 2020-09-09 | 2020-12-01 | 中国科学院自动化研究所 | Method and system for predicting urban traffic travel time |
| CN112017436B (en) * | 2020-09-09 | 2021-09-28 | 中国科学院自动化研究所 | Method and system for predicting urban traffic travel time |
| CN116311914A (en) * | 2023-02-21 | 2023-06-23 | 华南理工大学 | Road line discrete point isochronous characteristic value estimation method for traffic isochronous line |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109520499B (en) | 2020-06-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109520499A (en) | Region isochronal method in real time is realized based on vehicle GPS track data | |
| Wang et al. | Automatic intersection and traffic rule detection by mining motor-vehicle GPS trajectories | |
| Davies et al. | Scalable, distributed, real-time map generation | |
| CN103593430B (en) | Clustering method based on mobile object spatiotemporal information trajectory subsections | |
| CN104050817B (en) | Speed limiting information base generation and speed limiting information detection method and system | |
| CN105674995A (en) | Method for acquiring commuting route based on user's travel locus, and apparatus thereof | |
| Petrovska et al. | Traffic congestion analysis visualisation tool | |
| CN112489426B (en) | Urban traffic flow space-time prediction scheme based on graph convolution neural network | |
| CN108170793A (en) | Dwell point analysis method and its system based on vehicle semanteme track data | |
| CN106710208A (en) | Traffic state acquisition method and device | |
| CN108320501A (en) | Public bus network recognition methods based on user mobile phone signaling | |
| CN105608505A (en) | Cellular signaling data based track traffic travel mode identification method for resident | |
| CN112215427B (en) | Vehicle driving track reconstruction method and system under condition of bayonet data loss | |
| CN110972073B (en) | Living circle defining method based on mobile phone big data and walking accessibility | |
| CN105489004B (en) | The bayonet and floating car data fusion method calculated towards road real-time speed | |
| CN107958302A (en) | Empirical path planing method based on virtual topology transportation network | |
| Leung et al. | Intra-city urban network and traffic flow analysis from GPS mobility trace | |
| CN110414795B (en) | Newly-increased high-speed rail junction accessibility influence method based on improved two-step mobile search method | |
| CN102956105B (en) | Floating car sample point data interpolation method | |
| CN104318794A (en) | Practical routing selection method based on consideration of city intersection time delay | |
| CN109410576A (en) | Road condition analyzing method, apparatus, storage medium and the system of multisource data fusion | |
| Keler et al. | Detecting vehicle traffic patterns in urban environments using taxi trajectory intersection points | |
| CN106547862A (en) | Traffic big data dimension-reduction treatment method based on manifold learning | |
| CN116233757A (en) | Resident travel carbon emission amount calculating method based on mobile phone signaling data | |
| CN107071721A (en) | Stop point extracting method based on mobile phone location data |
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 | ||
| CP01 | Change in the name or title of a patent holder |
Address after: 310053 23-25, 2 building, 352 BINKANG Road, Binjiang District, Hangzhou, Zhejiang. Patentee after: Zhejiang zhongkong Information Industry Co.,Ltd. Address before: 310053 23-25, 2 building, 352 BINKANG Road, Binjiang District, Hangzhou, Zhejiang. Patentee before: ZHEJIANG SUPCON INFORMATION TECHNOLOGY Co.,Ltd. |
|
| CP01 | Change in the name or title of a patent holder |