CN104794927B - Bus arrival time forecasting method - Google Patents
Bus arrival time forecasting method Download PDFInfo
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- CN104794927B CN104794927B CN201510211699.0A CN201510211699A CN104794927B CN 104794927 B CN104794927 B CN 104794927B CN 201510211699 A CN201510211699 A CN 201510211699A CN 104794927 B CN104794927 B CN 104794927B
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- bus
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
Abstract
The invention provides a bus arrival time forecasting method. The bus arrival time forecasting method comprises the following steps of (1) acquiring data of a current position of a bus and extracting data of all bus stations behind the current position from a bus route database; (2) acquiring a gather of bus stations which are distant from each station within a distance (d) from the bus route database; (3) screening a secondary station gather of which the direction is the same with that of a current route from the gather of the bus stations in the step (2); (4) extracting arrival time of the bus on various routes in the secondary station gather from a bus running record; and (5) performing exponential average operation on arrival time of the secondary station gather and using an operation time as a forecasted arrival time of the bus at this time. By the bus arrival time forecasting method, a sample of the same route is added, and a calculation basis is added; and moreover, by an exponential average method, influences of historical data on a current result are considered, possible road crowding change of current time is also considered, a final calculation result is accurate and reliable, and a calculation process is efficient.
Description
Technical field
The present invention relates to a kind of bus arrival time Forecasting Methodology.
Background technology
At present for the prediction of bus arrival time, the method for generally using is to read many cars on public bus network
After GPS location data, take train arrival time on site location and become as road conditions in this arrive at a station predicted time, but actual life
Change frequency very high, especially peak period morning and evening, because the two neighboring order of classes or grades at school on same route is often differed 3-10 minutes
More than, due to road condition change acutely, arrival time can be caused to change very greatly, therefore this method is inaccurate.
The content of the invention
In order to solve the above technical problems, the invention provides a kind of bus arrival time Forecasting Methodology, the bus is arrived
Time forecasting methods of standing increase basis, and both took into account using exponetial smoothing method by increasing with the sample of section route
Influence of the historical data to current results, has taken into account current time possible road conditions congestion change again, therefore, final calculation result
Accurately, it is reliable, and calculating process is efficient.
The present invention is achieved by the following technical programs.
A kind of bus arrival time Forecasting Methodology that the present invention is provided, comprises the following steps：
1. it is all of after extraction current location from public bus network database after getting current bus location data
Bus station data；
2. the bus station set within each website distance d is obtained from bus routes database；
3. from step 2. in bus station set in, filter out the website subset with current route equidirectional；
4. extraction station idea concentrates the arrival time that each route passes through from bus running record；
5. exponential average computing is done to website subset arrival time, and arrival time is predicted using operation result as this.
5. middle index average calculating operation is specially the step：A (n)=C*R+A (n-1) * (1-R).
The bus station data include the latitude and longitude coordinates and numbering of each website.
The beneficial effects of the present invention are：The sample of same section route is increased, basis increases, and is put down using index
Equal method had both taken into account influence of the historical data to current results, and current time possible road conditions congestion change has been taken into account again, therefore,
Final calculation result is accurate, reliable, and calculating process is efficient.
Brief description of the drawings
Fig. 1 is principle schematic of the invention；
Fig. 2 is schematic flow sheet of the invention.
Specific embodiment
Be described further below technical scheme, but claimed scope be not limited to it is described.
One adjacent bus sample of public bus network very little, but a plurality of bus be possible to by it is same or this apart
Two close websites, therefore two station time predictions are expanded to the route scope of same site, can so increase sample
Quantity, the speed to getting does exponential average, then can be very good to obtain predicted time.
A kind of bus arrival time Forecasting Methodology as shown in Figure 1 and Figure 2, comprises the following steps：
1. it is all of after extraction current location from public bus network database after getting current bus location data
Bus station data；
2. the bus station set within each website distance d is obtained from bus routes database；
3. from step 2. in bus station set in, filter out the website subset with current route equidirectional；
4. extraction station idea concentrates the arrival time that each route passes through from bus running record；
5. exponential average computing is done to website subset arrival time, and arrival time is predicted using operation result as this.
5. middle index average calculating operation is specially the step：A (n)=C*R+A (n-1) * (1-R), wherein, A (n) represents n
The predicted time at moment, C represents the actual time at n-1 moment, and R represents 0~1 random number, and generally R takes 0.5.
The bus station data include the latitude and longitude coordinates and numbering of each website.
In Fig. 1, each module major function is：
Public bus network database：The all of public bus network in the city, including each website latitude and longitude coordinates are stored, is numbered
Deng；
Bus running is recorded：The affiliated circuit of each bus is have recorded, the time at each station is reached, and it is current newest
Prediction arrival time A (n-1)；
Exponential average calculator：Do arrival time A (n) prediction.
Claims (3)
1. a kind of bus arrival time Forecasting Methodology, it is characterised in that：Comprise the following steps：
1. after getting current bus location data, all of public transport after current location is extracted from public bus network database
Station data；
2. the bus station set within each website distance d is obtained from bus routes database；
3. from step 2. in bus station set in, filter out the website subset with current route equidirectional；
4. extraction station idea concentrates the arrival time that each route passes through from bus running record；
5. exponential average computing is done to website subset arrival time, and arrival time is predicted using operation result as this.
2. bus arrival time Forecasting Methodology as claimed in claim 1, it is characterised in that：The step 5. middle exponential average
Computing is specially：A (n)=C*R+A (n-1) * (1-R), wherein, A (n) represents the predicted time at n moment, and C represents the n-1 moment
Actual time, R represents 0~1 random number.
3. bus arrival time Forecasting Methodology as claimed in claim 1, it is characterised in that：The bus station data include
The latitude and longitude coordinates and numbering of each website.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510211699.0A CN104794927B (en) | 2015-04-29 | 2015-04-29 | Bus arrival time forecasting method |
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| CN201510211699.0A CN104794927B (en) | 2015-04-29 | 2015-04-29 | Bus arrival time forecasting method |
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| CN104794927A CN104794927A (en) | 2015-07-22 |
| CN104794927B true CN104794927B (en) | 2017-05-17 |
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Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105303246A (en) * | 2015-09-07 | 2016-02-03 | 天津市市政工程设计研究院 | Multiline arrival time prediction for public transportation |
| CN114973677A (en) * | 2016-04-18 | 2022-08-30 | 北京嘀嘀无限科技发展有限公司 | Method and apparatus for determining estimated time of arrival |
| CN106228830A (en) * | 2016-07-27 | 2016-12-14 | 安徽聚润互联信息技术有限公司 | A kind of bus arrival time real-time estimate system and method |
| CN106327867B (en) * | 2016-08-30 | 2020-02-11 | 北京航空航天大学 | Bus punctuation prediction method based on GPS data |
| CN109166337B (en) * | 2018-09-04 | 2020-10-16 | 深圳市东部公共交通有限公司 | Bus arrival time generation method and device and bus passenger travel OD acquisition method |
| CN112509358A (en) * | 2020-11-19 | 2021-03-16 | 湖南湘江智能科技创新中心有限公司 | Blind person riding method based on man-station cloud cooperation |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19633525A1 (en) * | 1996-08-09 | 1998-02-12 | Siemens Ag | Information system for users of public vehicles |
| AU6404799A (en) * | 1998-09-30 | 2000-04-17 | Global Research Systems, Inc. | Activation system for an advance notification system for monitoring the status of vehicle travel |
| CN1963847B (en) * | 2005-11-07 | 2011-03-09 | 同济大学 | Method for forecasting reaching station of bus |
| CN101388143B (en) * | 2007-09-14 | 2011-04-13 | 同济大学 | Bus arriving time prediction method based on floating data of the bus |
| CN102610088B (en) * | 2012-03-08 | 2014-01-29 | 东南大学 | Method for forecasting travel time between bus stops |
| CN103778800A (en) * | 2014-02-19 | 2014-05-07 | 东南大学 | Method for setting system for notifying arrival time of small-station-space bus in advance |
| CN104240529B (en) * | 2014-09-11 | 2017-02-01 | 江苏云控软件技术有限公司 | Method and system for predicting arrival time of buses |
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Address after: 550081 Guizhou Province, Guiyang city national high tech Zone No. 28 China an even highway western high-tech industrial R & D and production base of 4 building 15 layer Patentee after: Guizhou Zhitong World Information Technology Co. Ltd. Address before: 550081 Guizhou Province, Guiyang city national high tech Zone No. 28 China an even highway western high-tech industrial R & D and production base of 4 building 15 layer Patentee before: GUIZHOU HUNTERSUN INFORMATION TECHNOLOGY CO., LTD. |
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